diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..26d3352 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,3 @@ +# Default ignored files +/shelf/ +/workspace.xml diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..3964d0f --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..7f19ccc --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/radial_distribution.iml b/.idea/radial_distribution.iml new file mode 100644 index 0000000..74d515a --- /dev/null +++ b/.idea/radial_distribution.iml @@ -0,0 +1,10 @@ + + + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000..94a25f7 --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json index 1c1edce..b8f61bb 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -1,4 +1,9 @@ { - "python.pythonPath": "/usr/local/bin/python3.8", - "python.linting.enabled": false + "python.pythonPath": "/usr/bin/python", + "python.linting.enabled": false, + "cSpell.words": [ + "iloc", + "rsif", + "savetxt" + ] } \ No newline at end of file diff --git a/0zd.xyz b/0zd.xyz new file mode 100644 index 0000000..23bd9e3 --- /dev/null +++ b/0zd.xyz @@ -0,0 +1,114 @@ + 112 +Chemical Component 0ZD, taken from http://ligand-expo.rcsb.org/reports/0/0ZD/index.html +O62 -16.202 18.781 -35.336 O 1 O62 +C60 -16.663 19.920 -35.553 C 2 C60 +O61 -16.903 20.277 -36.716 O 3 O61 +C56 -16.953 20.857 -34.410 C 4 C56 +C57 -18.450 20.786 -34.033 C 5 C57 +C59 -18.804 21.710 -32.879 C 6 C59 +C58 -19.029 19.391 -33.818 C 7 C58 +N40 -15.967 20.685 -33.315 N 8 N40 +S41 -14.862 21.721 -33.178 S 9 S41 +O43 -15.375 23.018 -33.550 O 10 O43 +C45 -13.666 21.295 -34.178 C 11 C45 +C5A -13.608 21.787 -35.489 C 12 C5A +C49 -12.580 21.412 -36.358 C 13 C49 +C48 -11.556 20.555 -35.938 C 14 C48 +C50 -10.438 20.173 -36.850 C 15 C50 +C55 -9.924 18.877 -36.889 C 16 C55 +C54 -8.871 18.564 -37.754 C 17 C54 +C53 -8.316 19.542 -38.575 C 18 C53 +C52 -8.806 20.842 -38.528 C 19 C52 +C51 -9.865 21.147 -37.670 C 20 C51 +C47 -11.595 20.071 -34.623 C 21 C47 +C46 -12.639 20.435 -33.755 C 22 C46 +O42 -14.303 21.712 -31.839 O 23 O42 +C39 -15.913 19.409 -32.579 C 24 C39 +C38 -16.273 19.461 -31.104 C 25 C38 +N37 -16.036 18.123 -30.578 N 26 N37 +C35 -16.798 17.063 -30.835 C 27 C35 +O36 -17.843 17.161 -31.482 O 28 O36 +C33 -16.400 15.716 -30.280 C 29 C33 +C32 -17.287 14.645 -30.364 C 30 C32 +C31 -16.928 13.402 -29.843 C 31 C31 +C30 -15.687 13.222 -29.239 C 32 C30 +C34 -15.155 15.529 -29.668 C 33 C34 +C29 -14.789 14.283 -29.148 C 34 C29 +C27 -13.449 14.069 -28.495 C 35 C27 +O28 -13.253 13.028 -27.868 O 36 O28 +N26 -12.488 14.993 -28.605 N 37 N26 +C25 -11.210 14.876 -27.900 C 38 C25 +C24 -11.412 15.375 -26.475 C 39 C24 +N16 -10.222 15.420 -25.603 N 40 N16 +C17 -10.014 14.395 -24.551 C 41 C17 +C21 -11.099 14.469 -23.506 C 42 C21 +O23 -10.828 14.180 -22.324 O 43 O23 +O22 -12.261 14.798 -23.804 O 44 O22 +C18 -9.827 12.933 -24.999 C 45 C18 +C20 -8.739 12.773 -26.054 C 46 C20 +C19 -11.107 12.190 -25.375 C 47 C19 +S13 -9.378 16.690 -25.588 S 48 S13 +O14 -8.025 16.425 -25.183 O 49 O14 +O15 -9.451 17.315 -26.887 O 50 O15 +C10 -10.049 17.691 -24.490 C 51 C10 +C9 -9.657 17.722 -23.139 C 52 C9 +C8 -10.253 18.590 -22.217 C 53 C8 +C11 -11.067 18.572 -24.877 C 54 C11 +C12 -11.666 19.442 -23.963 C 55 C12 +C7 -11.271 19.457 -22.619 C 56 C7 +C1 -11.886 20.424 -21.661 C 57 C1 +C6 -13.250 20.714 -21.686 C 58 C6 +C5 -13.791 21.636 -20.787 C 59 C5 +C4 -12.965 22.295 -19.879 C 60 C4 +C3 -11.601 22.028 -19.863 C 61 C3 +C2 -11.066 21.100 -20.749 C 62 C2 +H1 -16.095 18.320 -36.160 H 63 H1 +H2 -16.797 21.872 -34.805 H 64 H2 +H3 -18.985 21.191 -34.905 H 65 H3 +H4 -19.877 21.620 -32.653 H 66 H4 +H5 -18.217 21.430 -31.992 H 67 H5 +H6 -18.574 22.749 -33.157 H 68 H6 +H7 -20.094 19.472 -33.556 H 69 H7 +H8 -18.922 18.803 -34.742 H 70 H8 +H9 -18.488 18.891 -33.001 H 71 H9 +H10 -14.372 22.468 -35.834 H 72 H10 +H11 -12.575 21.789 -37.370 H 73 H11 +H12 -10.341 18.113 -36.249 H 74 H12 +H13 -8.485 17.556 -37.786 H 75 H13 +H14 -7.508 19.291 -39.246 H 76 H14 +H15 -8.371 21.610 -39.150 H 77 H15 +H16 -10.248 22.156 -37.640 H 78 H16 +H17 -10.815 19.411 -34.273 H 79 H17 +H18 -12.652 20.047 -32.747 H 80 H18 +H19 -16.609 18.711 -33.068 H 81 H19 +H20 -14.887 19.020 -32.659 H 82 H20 +H21 -15.639 20.193 -30.583 H 83 H21 +H22 -17.330 19.737 -30.979 H 84 H22 +H23 -15.244 17.992 -29.981 H 85 H23 +H24 -18.251 14.777 -30.832 H 86 H24 +H25 -17.618 12.573 -29.909 H 87 H25 +H26 -15.419 12.255 -28.839 H 88 H26 +H27 -14.467 16.359 -29.596 H 89 H27 +H28 -12.648 15.790 -29.188 H 90 H28 +H29 -10.887 13.825 -27.885 H 91 H29 +H30 -10.448 15.487 -28.405 H 92 H30 +H31 -11.817 16.396 -26.536 H 93 H31 +H32 -12.150 14.716 -25.995 H 94 H32 +H33 -9.081 14.668 -24.037 H 95 H33 +H34 -11.610 14.261 -21.790 H 96 H34 +H35 -9.444 12.411 -24.110 H 97 H35 +H36 -7.840 13.323 -25.740 H 98 H36 +H37 -8.494 11.707 -26.170 H 99 H37 +H38 -9.098 13.173 -27.014 H 100 H38 +H39 -11.860 12.334 -24.587 H 101 H39 +H40 -11.493 12.583 -26.327 H 102 H40 +H41 -10.890 11.117 -25.483 H 103 H41 +H42 -8.874 17.057 -22.804 H 104 H42 +H43 -9.924 18.589 -21.188 H 105 H43 +H44 -11.396 18.579 -25.906 H 106 H44 +H45 -12.444 20.112 -24.297 H 107 H45 +H46 -13.891 20.223 -22.404 H 108 H46 +H47 -14.852 21.838 -20.796 H 109 H47 +H48 -13.384 23.012 -19.189 H 110 H48 +H49 -10.958 22.541 -19.163 H 111 H49 +H50 -10.005 20.898 -20.734 H 112 H50 diff --git a/2020-10-14-Note-11-34.pdf b/2020-10-14-Note-11-34.pdf deleted file mode 100644 index f1a9646..0000000 Binary files a/2020-10-14-Note-11-34.pdf and /dev/null differ diff --git a/ada_C-C-C.dat b/ada_C-C-C.dat new file mode 100644 index 0000000..9b9ddf4 --- /dev/null +++ b/ada_C-C-C.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=50) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 4 +118.108108 5 +123.243243 41 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_C1-C2-C3.dat b/ada_C1-C2-C3.dat new file mode 100644 index 0000000..32a6d13 --- /dev/null +++ b/ada_C1-C2-C3.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 0 +118.108108 0 +123.243243 1 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_C5-C4-C3.dat b/ada_C5-C4-C3.dat new file mode 100644 index 0000000..32a6d13 --- /dev/null +++ b/ada_C5-C4-C3.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 0 +118.108108 0 +123.243243 1 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_H-O-H.dat b/ada_H-O-H.dat new file mode 100644 index 0000000..6c669f3 --- /dev/null +++ b/ada_H-O-H.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=27) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 6 +20.540541 0 +25.675676 0 +30.810811 2 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 8 +118.108108 2 +123.243243 8 +128.378378 0 +133.513514 1 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_Hg-O-H.dat b/ada_Hg-O-H.dat new file mode 100644 index 0000000..b138baf --- /dev/null +++ b/ada_Hg-O-H.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=6) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 1 +118.108108 2 +123.243243 1 +128.378378 2 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_O-H-O.dat b/ada_O-H-O.dat new file mode 100644 index 0000000..85e2a5c --- /dev/null +++ b/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=7) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 2 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 0 +118.108108 1 +123.243243 0 +128.378378 0 +133.513514 0 +138.648649 2 +143.783784 1 +148.918919 1 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 0 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/ada_O-Hg-O.dat b/ada_O-Hg-O.dat new file mode 100644 index 0000000..f8f9e70 --- /dev/null +++ b/ada_O-Hg-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=6) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 1 +92.432432 0 +97.567568 3 +102.702703 0 +107.837838 0 +112.972973 1 +118.108108 0 +123.243243 0 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 0 +154.054054 0 +159.189189 0 +164.324324 0 +169.459459 1 +174.594595 0 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/analysis_H-transfer.ipynb b/analysis_H-transfer.ipynb new file mode 100644 index 0000000..c09107a --- /dev/null +++ b/analysis_H-transfer.ipynb @@ -0,0 +1,556 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram\n", + "from atoms_transfer import stern_limbach" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_water: Path = Path(\n", + " \"/home/edison/repositories/radial_distribution/files_xyz/others/water\"\n", + ")\n", + "\n", + "files_ice: list = glob(str(dir_water / \"ice_ih\" / \"w_iceih.xyz\"))\n", + "files_water4: list = glob(str(dir_water / \"w4\" / \"w*.xyz\"))\n", + "files_water5: list = glob(str(dir_water / \"w5\" / \"w*.xyz\"))\n", + "files_water6: list = glob(str(dir_water / \"w6\" / \"w*.xyz\"))\n", + "# files_water7: list = glob(str(dir_water / \"w7\" / \"w*.xyz\"))\n", + "files_water7: list = glob(str(dir_water / \"w*\" / \"w*.xyz\"))\n", + "\n", + "coordinates_ice: list = functions.dict_coordinates_xyz(files_ice)\n", + "coordinates_water4: list = functions.dict_coordinates_xyz(files_water4)\n", + "coordinates_water5: list = functions.dict_coordinates_xyz(files_water5)\n", + "coordinates_water6: list = functions.dict_coordinates_xyz(files_water6)\n", + "coordinates_water7: list = functions.dict_coordinates_xyz(files_water7)\n", + "\n", + "\n", + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_ice: dict = distance_matrix.distance_matrix(coordinates_ice, (0, 0, 0))\n", + "distances_dict_water4: dict = distance_matrix.distance_matrix(\n", + " coordinates_water4, (0, 0, 0)\n", + ")\n", + "distances_dict_water5: dict = distance_matrix.distance_matrix(\n", + " coordinates_water5, (0, 0, 0)\n", + ")\n", + "distances_dict_water6: dict = distance_matrix.distance_matrix(\n", + " coordinates_water6, (0, 0, 0)\n", + ")\n", + "distances_dict_water7: dict = distance_matrix.distance_matrix(\n", + " coordinates_water7, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 2, 0.01)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w3s2.xyz': [],\n", + " '/home/edison/repositories/radial_distribution/zora_so/w3s3.xyz': [(1, 6, 4),\n", + " (4, 5, 7)],\n", + " '/home/edison/repositories/radial_distribution/zora_so/w3s1.xyz': [(4, 5, 7)]}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"O\", \"H\", \"O\"] # proton transfer\n", + "\n", + "atoms_index_dict_ice: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_ice, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water6, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water7: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water7, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w3\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "transfer_w1: list = stern_limbach(atoms_index_dict_w1, atoms_list, distances_dict_w1)\n", + "transfer_w2: list = stern_limbach(atoms_index_dict_w2, atoms_list, distances_dict_w2)\n", + "transfer_w3: list = stern_limbach(atoms_index_dict_w3, atoms_list, distances_dict_w3)\n", + "transfer_w4: list = stern_limbach(atoms_index_dict_w4, atoms_list, distances_dict_w4)\n", + "transfer_w5: list = stern_limbach(atoms_index_dict_w5, atoms_list, distances_dict_w5)\n", + "transfer_w6: list = stern_limbach(atoms_index_dict_w6, atoms_list, distances_dict_w6)\n", + "\n", + "transfer_ice: list = stern_limbach(atoms_index_dict_ice, atoms_list, distances_dict_ice)\n", + "transfer_water4: list = stern_limbach(\n", + " atoms_index_dict_water4, atoms_list, distances_dict_water4\n", + ")\n", + "transfer_water5: list = stern_limbach(\n", + " atoms_index_dict_water5, atoms_list, distances_dict_water5\n", + ")\n", + "transfer_water6: list = stern_limbach(\n", + " atoms_index_dict_water6, atoms_list, distances_dict_water6\n", + ")\n", + "transfer_water7: list = stern_limbach(\n", + " atoms_index_dict_water7, atoms_list, distances_dict_water7\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'q1': [0.09286046862432795, 0.14059418946778834, 0.18643117296449774],\n", + " 'q2': [2.4449218384896234, 2.4776340961751355, 2.5115242251394525]}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transfer_w3\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins, endpoint=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ace63a7fba99423aab6c703b3571f19a", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", + "text/html": [ + "\n", + "
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\"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "ax.axvline(x=0.0, color='black', linestyle='-', linewidth=1)\n", + "\n", + "ax.plot(\n", + " # -np.abs(transfer_ice[\"q1\"]),\n", + " transfer_ice[\"q1\"],\n", + " transfer_ice[\"q2\"],\n", + " \"*\",\n", + " # next(linecycler),\n", + " color=\"gray\",\n", + " label=r\"ice $I_h$\",\n", + " markersize=7,\n", + " # alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "# ax.plot(\n", + "# transfer_water4[\"q1\"],\n", + "# transfer_water4[\"q2\"],\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water tetramer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# transfer_water5[\"q1\"],\n", + "# transfer_water5[\"q2\"],\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water pentamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# transfer_water6[\"q1\"],\n", + "# transfer_water6[\"q2\"],\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water hexamer\",\n", + "# markersize=7,\n", + "# alpha=0.3,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " # -np.abs(transfer_water7[\"q1\"]),\n", + " transfer_water7[\"q1\"],\n", + " transfer_water7[\"q2\"],\n", + " \"+\",\n", + " # next(linecycler),\n", + " color=\"gray\",\n", + " label=\"water cluster\",\n", + " markersize=7,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "# ax.plot(\n", + "# transfer_w1[\"q1\"],\n", + "# transfer_w1[\"q2\"],\n", + "# # \"-\",\n", + "next(linecycler),\n", + "# color=next(cm),\n", + "next(cm)\n", + "# label=\"w1\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# transfer_w2[\"q1\"],\n", + "# transfer_w2[\"q2\"],\n", + "# # \"-\",\n", + "next(linecycler),\n", + "# color=next(cm),\n", + "next(cm)\n", + "# label=\"w2\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " transfer_w3[\"q1\"],\n", + " transfer_w3[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.6,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_w4[\"q1\"],\n", + " transfer_w4[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.6,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_w5[\"q1\"],\n", + " transfer_w5[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.6,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_w6[\"q1\"],\n", + " transfer_w6[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.6,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "# plt.xlim(-0.6, 0.4)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "# - legends for the main plot\n", + "ax.set_xlabel(r\"$q_1=\\frac{1}{2}(r_1-r_2) ~[\\AA]$\", fontsize=20)\n", + "ax.set_ylabel(r\"$q_2=r_1+r_2 ~[\\AA]$\", fontsize=20)\n", + "\n", + "plt.legend(loc=\"upper center\", fontsize=12, ncol=2)\n", + "\n", + "ax.annotate(\n", + " f\"Proton Transfer\",\n", + " xy=(-0.1, 2.7),\n", + " xycoords=\"data\",\n", + " fontsize=14,\n", + ")\n", + "\n", + "ax.axvspan(-0.2, 0.2, alpha=0.3, color=\"gray\")\n", + "\n", + "ax.annotate(\n", + " # f'{atoms_list[0]}'r'$-$'f'{atoms_list[1]}'r'$\\cdots\\to$'f'{atoms_list[0]}',\n", + " r\"HO$-$H$\\cdots\\to$OH$_2$\",\n", + " xy=(-0.58, 2.45),\n", + " xycoords=\"data\",\n", + " fontsize=20,\n", + " weight=\"bold\",\n", + ")\n", + "\n", + "ax.annotate(\n", + " # f'{atoms_list[0]}'r'$-$'f'{atoms_list[1]}'r'$\\cdots\\to$'f'{atoms_list[0]}',\n", + " r\"$~~~r_1 \\quad\\quad~~r_2$\",\n", + " xy=(-0.53, 2.48),\n", + " xycoords=\"data\",\n", + " fontsize=13,\n", + " weight=\"bold\",\n", + ")\n", + "\n", + "fig.savefig(\n", + " working_dir / \"stern_limbach.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_H-transfer_gaussian.ipynb b/analysis_H-transfer_gaussian.ipynb new file mode 100644 index 0000000..073faef --- /dev/null +++ b/analysis_H-transfer_gaussian.ipynb @@ -0,0 +1,3241 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "from matplotlib.colors import to_hex,to_rgb,to_rgba\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram\n", + "from atoms_transfer import stern_limbach" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution\")\n", + "\n", + "if not working_dir.exists():\n", + " raise FileNotFoundError(f\"{working_dir} does not exist\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_water: Path = working_dir / \"files_xyz\" / \"others\" / \"water\"\n", + "\n", + "files_ice: list = glob(str(dir_water / \"ice_ih\" / \"w_iceih.xyz\"))\n", + "files_water4: list = glob(str(dir_water / \"w4\" / \"w*.xyz\"))\n", + "files_water5: list = glob(str(dir_water / \"w5\" / \"w*.xyz\"))\n", + "files_water6: list = glob(str(dir_water / \"w6\" / \"w*.xyz\"))\n", + "# files_water7: list = glob(str(dir_water / \"w7\" / \"w*.xyz\"))\n", + "files_water7: list = glob(str(dir_water / \"w*\" / \"w*.xyz\"))\n", + "\n", + "coordinates_ice: list = functions.dict_coordinates_xyz(files_ice)\n", + "coordinates_water4: list = functions.dict_coordinates_xyz(files_water4)\n", + "coordinates_water5: list = functions.dict_coordinates_xyz(files_water5)\n", + "coordinates_water6: list = functions.dict_coordinates_xyz(files_water6)\n", + "coordinates_water7: list = functions.dict_coordinates_xyz(files_water7)\n", + "\n", + "dir_zora: Path = working_dir / \"zora_so\"\n", + "files_w1: list = glob(str(dir_zora / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(dir_zora / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(dir_zora / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(dir_zora / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(dir_zora / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(dir_zora / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "dir_other: Path = working_dir / \"files_xyz\"\n", + "\n", + "files_hf: list = glob(str(dir_other / \"hf\" / \"*.xyz\"))\n", + "files_pbe0: list = glob(str(dir_other / \"pbe0\" / \"*.xyz\"))\n", + "files_camb3lyp: list = glob(str(dir_other / \"camb3lyp\" / \"*.xyz\"))\n", + "files_wb97xd: list = glob(str(dir_other / \"wb97xd_grimmeD2\" / \"*.xyz\"))\n", + "files_b2plypd3: list = glob(str(dir_other / \"b2plypd3\" / \"*.xyz\"))\n", + "files_pbeqidh: list = glob(str(dir_other / \"pbeqidh\" / \"*.xyz\"))\n", + "files_mp2: list = glob(str(dir_other / \"mp2\" / \"*.xyz\"))\n", + "files_zora_nr: list = glob(str(dir_other / \"zora\" / \"c\" / \"*.xyz\"))\n", + "files_zora_sr: list = glob(str(dir_other / \"zora\" / \"sr\" / \"*.xyz\"))\n", + "files_zora_so: list = glob(str(dir_other / \"zora\" / \"so\" / \"*.xyz\"))\n", + "\n", + "\n", + "coordinates_hf: dict = functions.dict_coordinates_xyz(files_hf)\n", + "coordinates_pbe0: dict = functions.dict_coordinates_xyz(files_pbe0)\n", + "coordinates_camb3lyp: dict = functions.dict_coordinates_xyz(files_camb3lyp)\n", + "coordinates_wb97xd: dict = functions.dict_coordinates_xyz(files_wb97xd)\n", + "coordinates_b2plypd3: dict = functions.dict_coordinates_xyz(files_b2plypd3)\n", + "coordinates_pbeqidh: dict = functions.dict_coordinates_xyz(files_pbeqidh)\n", + "coordinates_mp2: dict = functions.dict_coordinates_xyz(files_mp2)\n", + "coordinates_zora_nr: dict = functions.dict_coordinates_xyz(files_zora_nr)\n", + "coordinates_zora_sr: dict = functions.dict_coordinates_xyz(files_zora_sr)\n", + "coordinates_zora_so: dict = functions.dict_coordinates_xyz(files_zora_so)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s7.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.383257 2.989609 3.058074 2.151334 2.816800 \n", + " 1 O 2.383257 0.000000 0.966285 0.966598 2.860677 3.770227 \n", + " 2 H 2.989609 0.966285 0.000000 1.536827 3.399089 4.352765 \n", + " 3 H 3.058074 0.966598 1.536827 0.000000 3.579619 4.410336 \n", + " 4 O 2.151334 2.860677 3.399089 3.579619 0.000000 0.968779 \n", + " 5 H 2.816800 3.770227 4.352765 4.410336 0.968779 0.000000 \n", + " 6 H 2.708972 2.555218 3.071155 3.155471 0.969210 1.563908 \n", + " 7 O 3.913819 5.703443 6.481171 5.849703 5.387064 5.461692 \n", + " 8 H 4.532217 6.506715 7.254153 6.725388 5.928466 5.910116 \n", + " 9 H 4.578106 6.092433 6.892944 6.091536 6.059518 6.158283 \n", + " 10 O 2.041075 3.767066 4.361907 4.095809 4.090583 4.559660 \n", + " 11 H 2.776995 4.589384 5.283538 4.828828 4.573702 4.854593 \n", + " 12 H 2.640925 4.245228 4.673092 4.609865 4.760222 5.282619 \n", + " 13 O 2.349788 3.125244 2.995284 4.059408 2.981526 3.738967 \n", + " 14 H 3.044594 3.774738 3.505716 4.652210 3.940898 4.676256 \n", + " 15 H 2.970362 3.671284 3.503371 4.635967 2.941765 3.578101 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.708972 3.913819 4.532217 4.578106 2.041075 2.776995 2.640925 \n", + " 1 2.555218 5.703443 6.506715 6.092433 3.767066 4.589384 4.245228 \n", + " 2 3.071155 6.481171 7.254153 6.892944 4.361907 5.283538 4.673092 \n", + " 3 3.155471 5.849703 6.725388 6.091536 4.095809 4.828828 4.609865 \n", + " 4 0.969210 5.387064 5.928466 6.059518 4.090583 4.573702 4.760222 \n", + " 5 1.563908 5.461692 5.910116 6.158283 4.559660 4.854593 5.282619 \n", + " 6 0.000000 5.979114 6.608833 6.553004 4.644968 5.165287 5.337954 \n", + " 7 5.979114 0.000000 0.965037 0.965404 2.438552 1.370124 2.956219 \n", + " 8 6.608833 0.965037 0.000000 1.547520 3.079610 2.048548 3.428040 \n", + " 9 6.553004 0.965404 1.547520 0.000000 3.019886 2.024652 3.499314 \n", + " 10 4.644968 2.438552 3.079610 3.019886 0.000000 1.070760 0.966427 \n", + " 11 5.165287 1.370124 2.048548 2.024652 1.070760 0.000000 1.675725 \n", + " 12 5.337954 2.956219 3.428040 3.499314 0.966427 1.675725 0.000000 \n", + " 13 3.460215 5.927073 6.370416 6.668781 3.769601 4.684399 3.811368 \n", + " 14 4.416051 6.292008 6.680190 7.026403 4.051002 5.005046 3.855981 \n", + " 15 3.420364 6.564936 6.952491 7.353184 4.566930 5.402219 4.666671 \n", + " \n", + " 13 14 15 \n", + " 0 2.349788 3.044594 2.970362 \n", + " 1 3.125244 3.774738 3.671284 \n", + " 2 2.995284 3.505716 3.503371 \n", + " 3 4.059408 4.652210 4.635967 \n", + " 4 2.981526 3.940898 2.941765 \n", + " 5 3.738967 4.676256 3.578101 \n", + " 6 3.460215 4.416051 3.420364 \n", + " 7 5.927073 6.292008 6.564936 \n", + " 8 6.370416 6.680190 6.952491 \n", + " 9 6.668781 7.026403 7.353184 \n", + " 10 3.769601 4.051002 4.566930 \n", + " 11 4.684399 5.005046 5.402219 \n", + " 12 3.811368 3.855981 4.666671 \n", + " 13 0.000000 0.966093 0.966075 \n", + " 14 0.966093 0.000000 1.536722 \n", + " 15 0.966075 1.536722 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w2s1.xyz': atoms 0 1 2 3 4 5 6\n", + " 0 Hg 0.000000 2.002985 2.655729 2.654230 2.002865 2.656279 2.654369\n", + " 1 O 2.002985 0.000000 0.976266 0.976423 4.004762 4.615825 4.590586\n", + " 2 H 2.655729 0.976266 0.000000 1.593604 4.615022 5.145897 5.186565\n", + " 3 H 2.654230 0.976423 1.593604 0.000000 4.590420 5.186685 5.224375\n", + " 4 O 2.002865 4.004762 4.615022 4.590420 0.000000 0.976235 0.976387\n", + " 5 H 2.656279 4.615825 5.145897 5.186685 0.976235 0.000000 1.593656\n", + " 6 H 2.654369 4.590586 5.186565 5.224375 0.976387 1.593656 0.000000,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.476439 3.157390 3.157492 1.992162 2.761174 \n", + " 1 O 2.476439 0.000000 0.964459 0.964459 3.236363 3.433535 \n", + " 2 H 3.157390 0.964459 0.000000 1.530762 3.948956 3.955251 \n", + " 3 H 3.157492 0.964459 1.530762 0.000000 3.632443 3.829023 \n", + " 4 O 1.992162 3.236363 3.948956 3.632443 0.000000 1.103796 \n", + " 5 H 2.761174 3.433535 3.955251 3.829023 1.103796 0.000000 \n", + " 6 H 2.573374 4.147842 4.896483 4.495055 0.968105 1.708196 \n", + " 7 O 3.873678 4.002712 4.277960 4.355688 2.415245 1.312660 \n", + " 8 H 4.461573 4.824708 5.026312 5.256855 3.036721 1.982674 \n", + " 9 H 4.554601 4.335068 4.606895 4.492507 2.985620 1.962392 \n", + " 10 O 1.992301 3.230963 3.627591 3.944756 3.981886 4.699314 \n", + " 11 H 2.573725 4.143252 4.490835 4.892755 4.471212 5.198004 \n", + " 12 H 2.760154 3.425543 3.822187 3.948520 4.698159 5.462404 \n", + " 13 O 3.873179 3.993639 4.348054 4.269387 5.692394 6.469403 \n", + " 14 H 4.553997 4.324596 4.483174 4.596566 6.400692 7.087488 \n", + " 15 H 4.461469 4.816373 5.249788 5.018397 6.219620 7.086176 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.573374 3.873678 4.461573 4.554601 1.992301 2.573725 2.760154 \n", + " 1 4.147842 4.002712 4.824708 4.335068 3.230963 4.143252 3.425543 \n", + " 2 4.896483 4.277960 5.026312 4.606895 3.627591 4.490835 3.822187 \n", + " 3 4.495055 4.355688 5.256855 4.492507 3.944756 4.892755 3.948520 \n", + " 4 0.968105 2.415245 3.036721 2.985620 3.981886 4.471212 4.698159 \n", + " 5 1.708196 1.312660 1.982674 1.962392 4.699314 5.198004 5.462404 \n", + " 6 0.000000 2.927477 3.371214 3.447841 4.470990 4.826291 5.196431 \n", + " 7 2.927477 0.000000 0.965974 0.966087 5.693303 6.197755 6.469177 \n", + " 8 3.371214 0.965974 0.000000 1.552835 6.220109 6.612201 7.085603 \n", + " 9 3.447841 0.966087 1.552835 0.000000 6.401839 6.979995 7.087525 \n", + " 10 4.470990 5.693303 6.220109 6.401839 0.000000 0.968110 1.103148 \n", + " 11 4.826291 6.197755 6.612201 6.979995 0.968110 0.000000 1.707520 \n", + " 12 5.196431 6.469177 7.085603 7.087525 1.103148 1.707520 0.000000 \n", + " 13 6.196249 7.462422 8.156641 7.983255 2.415646 2.927703 1.313706 \n", + " 14 6.978406 7.983110 8.670056 8.496880 2.986077 3.448658 1.963403 \n", + " 15 6.611043 8.156816 8.851102 8.670260 3.037362 3.371411 1.983854 \n", + " \n", + " 13 14 15 \n", + " 0 3.873179 4.553997 4.461469 \n", + " 1 3.993639 4.324596 4.816373 \n", + " 2 4.348054 4.483174 5.249788 \n", + " 3 4.269387 4.596566 5.018397 \n", + " 4 5.692394 6.400692 6.219620 \n", + " 5 6.469403 7.087488 7.086176 \n", + " 6 6.196249 6.978406 6.611043 \n", + " 7 7.462422 7.983110 8.156816 \n", + " 8 8.156641 8.670056 8.851102 \n", + " 9 7.983255 8.496880 8.670260 \n", + " 10 2.415646 2.986077 3.037362 \n", + " 11 2.927703 3.448658 3.371411 \n", + " 12 1.313706 1.963403 1.983854 \n", + " 13 0.000000 0.966070 0.965961 \n", + " 14 0.966070 0.000000 1.552708 \n", + " 15 0.965961 1.552708 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.967518 1.570026 5.626979 5.271497 3.631580 \n", + " 1 O 0.967518 0.000000 0.967076 4.844350 4.597359 2.997423 \n", + " 2 H 1.570026 0.967076 0.000000 5.264049 5.160687 3.599504 \n", + " 3 H 5.626979 4.844350 5.264049 0.000000 0.970921 2.396637 \n", + " 4 O 5.271497 4.597359 5.160687 0.970921 0.000000 1.857291 \n", + " 5 H 3.631580 2.997423 3.599504 2.396637 1.857291 0.000000 \n", + " 6 H 9.036223 8.616070 9.363294 4.914353 4.551167 6.099929 \n", + " 7 O 8.613145 8.167674 8.897803 4.386678 3.961166 5.486389 \n", + " 8 H 9.362009 8.890608 9.590449 4.915397 4.549797 6.088293 \n", + " 9 H 1.834267 1.187358 1.849860 3.993771 3.643974 1.897453 \n", + " 10 O 2.932432 2.389904 2.997262 3.339636 2.832994 0.978641 \n", + " 11 H 3.493668 2.974759 3.387515 3.708932 3.253988 1.587261 \n", + " 12 Hg 6.846235 6.299839 6.965272 2.405993 1.926930 3.560040 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 9.036223 8.613145 9.362009 1.834267 2.932432 3.493668 6.846235 \n", + " 1 8.616070 8.167674 8.890608 1.187358 2.389904 2.974759 6.299839 \n", + " 2 9.363294 8.897803 9.590449 1.849860 2.997262 3.387515 6.965272 \n", + " 3 4.914353 4.386678 4.915397 3.993771 3.339636 3.708932 2.405993 \n", + " 4 4.551167 3.961166 4.549797 3.643974 2.832994 3.253988 1.926930 \n", + " 5 6.099929 5.486389 6.088293 1.897453 0.978641 1.587261 3.560040 \n", + " 6 0.000000 0.970779 1.574252 7.769910 6.952114 7.388146 2.674095 \n", + " 7 0.970779 0.000000 0.970811 7.238451 6.328766 6.674224 2.037011 \n", + " 8 1.574252 0.970811 0.000000 7.904850 6.922646 7.159053 2.673601 \n", + " 9 7.769910 7.238451 7.904850 0.000000 1.204656 1.849549 5.355025 \n", + " 10 6.952114 6.328766 6.922646 1.204656 0.000000 0.965236 4.468517 \n", + " 11 7.388146 6.674224 7.159053 1.849549 0.965236 0.000000 4.846180 \n", + " 12 2.674095 2.037011 2.673601 5.355025 4.468517 4.846180 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.971951 1.581726 5.144530 4.546299 5.191550 \n", + " 1 O 0.971951 0.000000 0.971950 4.604974 3.949708 4.574816 \n", + " 2 H 1.581726 0.971950 0.000000 5.143372 4.546369 5.192394 \n", + " 3 H 5.144530 4.604974 5.143372 0.000000 1.083439 1.876062 \n", + " 4 O 4.546299 3.949708 4.546369 1.083439 0.000000 1.084716 \n", + " 5 H 5.191550 4.574816 5.192394 1.876062 1.084716 0.000000 \n", + " 6 H 6.708952 6.165029 6.521080 2.017279 3.043405 3.646023 \n", + " 7 O 6.015604 5.548956 6.013357 1.343857 2.425937 3.138140 \n", + " 8 H 6.523273 6.165039 6.706483 2.017140 3.043115 3.646198 \n", + " 9 H 6.795971 6.098519 6.614612 3.648108 3.043536 2.015955 \n", + " 10 O 6.101246 5.485669 6.102928 3.137601 2.424736 1.341548 \n", + " 11 H 6.613117 6.098931 6.797948 3.648127 3.043275 2.015859 \n", + " 12 Hg 2.668920 2.020387 2.668926 2.647138 1.929777 2.643099 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 6.708952 6.015604 6.523273 6.795971 6.101246 6.613117 2.668920 \n", + " 1 6.165029 5.548956 6.165039 6.098519 5.485669 6.098931 2.020387 \n", + " 2 6.521080 6.013357 6.706483 6.614612 6.102928 6.797948 2.668926 \n", + " 3 2.017279 1.343857 2.017140 3.648108 3.137601 3.648127 2.647138 \n", + " 4 3.043405 2.425937 3.043115 3.043536 2.424736 3.043275 1.929777 \n", + " 5 3.646023 3.138140 3.646198 2.015955 1.341548 2.015859 2.643099 \n", + " 6 0.000000 0.965511 1.551911 4.922204 4.692754 5.161258 4.388920 \n", + " 7 0.965511 0.000000 0.965512 4.695658 4.287380 4.695818 3.745407 \n", + " 8 1.551911 0.965512 0.000000 5.161606 4.693171 4.922835 4.388816 \n", + " 9 4.922204 4.695658 5.161606 0.000000 0.965515 1.552400 4.377169 \n", + " 10 4.692754 4.287380 4.693171 0.965515 0.000000 0.965516 3.733757 \n", + " 11 5.161258 4.695818 4.922835 1.552400 0.965516 0.000000 4.377354 \n", + " 12 4.388920 3.745407 4.388816 4.377169 3.733757 4.377354 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s8.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.966354 1.553414 4.691569 4.089809 4.498128 \n", + " 1 O 0.966354 0.000000 0.966354 3.739647 3.186098 3.673118 \n", + " 2 H 1.553414 0.966354 0.000000 3.560039 3.119994 3.476561 \n", + " 3 H 4.691569 3.739647 3.560039 0.000000 0.965852 1.542595 \n", + " 4 O 4.089809 3.186098 3.119994 0.965852 0.000000 0.965882 \n", + " 5 H 4.498128 3.673118 3.476561 1.542595 0.965882 0.000000 \n", + " 6 H 3.924219 3.395091 3.923856 4.234964 4.219888 5.160126 \n", + " 7 O 3.944664 3.337591 3.944343 3.786622 3.676210 4.615585 \n", + " 8 H 4.887537 4.287849 4.887175 4.234913 4.220035 5.160352 \n", + " 9 H 3.559612 3.739258 4.691274 6.010682 5.290667 5.823144 \n", + " 10 O 3.119579 3.185808 4.089694 5.290667 4.501701 4.954481 \n", + " 11 H 3.476439 3.673161 4.498444 5.823144 4.954481 5.245562 \n", + " 12 H 5.487969 5.027077 5.703701 4.691795 4.090222 4.498574 \n", + " 13 O 5.026885 4.434556 5.026958 3.739726 3.186230 3.673105 \n", + " 14 H 5.703486 5.027011 5.487976 3.560277 3.120252 3.476586 \n", + " 15 Hg 2.884713 2.226698 2.884733 3.005365 2.333386 3.024661 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.924219 3.944664 4.887537 3.559612 3.119579 3.476439 5.487969 \n", + " 1 3.395091 3.337591 4.287849 3.739258 3.185808 3.673161 5.027077 \n", + " 2 3.923856 3.944343 4.887175 4.691274 4.089694 4.498444 5.703701 \n", + " 3 4.234964 3.786622 4.234913 6.010682 5.290667 5.823144 4.691795 \n", + " 4 4.219888 3.676210 4.220035 5.290667 4.501701 4.954481 4.090222 \n", + " 5 5.160126 4.615585 5.160352 5.823144 4.954481 5.245562 4.498574 \n", + " 6 0.000000 0.965489 1.546366 4.234642 4.219660 5.159992 4.888326 \n", + " 7 0.965489 0.000000 0.965489 3.786637 3.676222 4.615597 3.945567 \n", + " 8 1.546366 0.965489 0.000000 4.235261 4.220283 5.160505 3.925741 \n", + " 9 4.234642 3.786637 4.235261 0.000000 0.965852 1.542595 3.560685 \n", + " 10 4.219660 3.676222 4.220283 0.965852 0.000000 0.965882 3.120651 \n", + " 11 5.159992 4.615597 5.160505 1.542595 0.965882 0.000000 3.476693 \n", + " 12 4.888326 3.945567 3.925741 3.560685 3.120651 3.476693 0.000000 \n", + " 13 4.289053 3.338912 3.397071 3.740104 3.186510 3.673052 0.966352 \n", + " 14 4.888685 3.945883 3.926098 4.692079 4.090327 4.498247 1.553442 \n", + " 15 2.971953 2.291468 2.972125 3.005366 2.333388 3.024662 2.884716 \n", + " \n", + " 13 14 15 \n", + " 0 5.026885 5.703486 2.884713 \n", + " 1 4.434556 5.027011 2.226698 \n", + " 2 5.026958 5.487976 2.884733 \n", + " 3 3.739726 3.560277 3.005365 \n", + " 4 3.186230 3.120252 2.333386 \n", + " 5 3.673105 3.476586 3.024661 \n", + " 6 4.289053 4.888685 2.971953 \n", + " 7 3.338912 3.945883 2.291468 \n", + " 8 3.397071 3.926098 2.972125 \n", + " 9 3.740104 4.692079 3.005366 \n", + " 10 3.186510 4.090327 2.333388 \n", + " 11 3.673052 4.498247 3.024662 \n", + " 12 0.966352 1.553442 2.884716 \n", + " 13 0.000000 0.966352 2.226597 \n", + " 14 0.966352 0.000000 2.884697 \n", + " 15 2.226597 2.884697 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s12.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.963638 1.543320 6.188884 6.048607 7.021467 \n", + " 1 O 0.963638 0.000000 0.964115 5.626298 5.487599 6.442942 \n", + " 2 H 1.543320 0.964115 0.000000 6.202684 6.130698 7.076992 \n", + " 3 H 6.188884 5.626298 6.202684 0.000000 0.966846 1.682573 \n", + " 4 O 6.048607 5.487599 6.130698 0.966846 0.000000 1.067806 \n", + " 5 H 7.021467 6.442942 7.076992 1.682573 1.067806 0.000000 \n", + " 6 H 3.603836 3.080963 3.656909 5.193642 4.567202 5.147962 \n", + " 7 O 3.145894 2.474659 3.073339 4.472006 3.977216 4.696748 \n", + " 8 H 2.137026 1.438623 2.103514 4.884744 4.547527 5.395376 \n", + " 9 H 5.953922 5.466224 6.098409 5.171658 4.266587 4.319169 \n", + " 10 O 6.041820 5.508608 6.169335 4.302883 3.375229 3.358352 \n", + " 11 H 6.984971 6.460825 7.123661 4.605500 3.653685 3.349637 \n", + " 12 H 8.908579 8.257574 8.814255 3.433574 3.066536 2.040201 \n", + " 13 O 8.277832 7.693141 8.324079 2.969742 2.442130 1.376620 \n", + " 14 H 8.838974 8.325990 9.011570 3.466549 3.008136 2.017026 \n", + " 15 H 5.349881 4.916610 5.278409 7.018544 6.270529 6.585199 \n", + " 16 O 4.861782 4.485659 5.003999 6.366545 5.598664 5.956471 \n", + " 17 H 4.992486 4.796726 5.367368 6.976211 6.195764 6.566060 \n", + " 18 Hg 4.450971 3.826376 4.488905 2.601584 1.999907 2.740541 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.603836 3.145894 2.137026 5.953922 6.041820 6.984971 8.908579 \n", + " 1 3.080963 2.474659 1.438623 5.466224 5.508608 6.460825 8.257574 \n", + " 2 3.656909 3.073339 2.103514 6.098409 6.169335 7.123661 8.814255 \n", + " 3 5.193642 4.472006 4.884744 5.171658 4.302883 4.605500 3.433574 \n", + " 4 4.567202 3.977216 4.547527 4.266587 3.375229 3.653685 3.066536 \n", + " 5 5.147962 4.696748 5.395376 4.319169 3.358352 3.349637 2.040201 \n", + " 6 0.000000 1.004690 1.721587 2.512373 2.845224 3.789632 6.610686 \n", + " 7 1.004690 0.000000 1.039857 3.068845 3.100639 4.058996 6.297028 \n", + " 8 1.721587 1.039857 0.000000 4.048128 4.099774 5.057999 7.115354 \n", + " 9 2.512373 3.068845 4.048128 0.000000 0.967643 1.547194 5.233754 \n", + " 10 2.845224 3.100639 4.099774 0.967643 0.000000 0.963504 4.317923 \n", + " 11 3.789632 4.058996 5.057999 1.547194 0.963504 0.000000 3.900067 \n", + " 12 6.610686 6.297028 7.115354 5.233754 4.317923 3.900067 0.000000 \n", + " 13 6.040222 5.745984 6.549931 4.672639 3.727622 3.349516 0.965615 \n", + " 14 6.705101 6.440826 7.215452 5.239760 4.318761 3.853837 1.545748 \n", + " 15 2.203917 3.141280 3.752596 2.658245 3.497844 4.161056 7.610318 \n", + " 16 1.597615 2.592482 3.251853 2.098114 2.900855 3.643049 7.135571 \n", + " 17 2.243450 3.224629 3.714907 2.660739 3.494304 4.160678 7.798981 \n", + " 18 2.598768 1.984391 2.666017 3.025812 2.440057 3.193441 4.491858 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 8.277832 8.838974 5.349881 4.861782 4.992486 4.450971 \n", + " 1 7.693141 8.325990 4.916610 4.485659 4.796726 3.826376 \n", + " 2 8.324079 9.011570 5.278409 5.003999 5.367368 4.488905 \n", + " 3 2.969742 3.466549 7.018544 6.366545 6.976211 2.601584 \n", + " 4 2.442130 3.008136 6.270529 5.598664 6.195764 1.999907 \n", + " 5 1.376620 2.017026 6.585199 5.956471 6.566060 2.740541 \n", + " 6 6.040222 6.705101 2.203917 1.597615 2.243450 2.598768 \n", + " 7 5.745984 6.440826 3.141280 2.592482 3.224629 1.984391 \n", + " 8 6.549931 7.215452 3.752596 3.251853 3.714907 2.666017 \n", + " 9 4.672639 5.239760 2.658245 2.098114 2.660739 3.025812 \n", + " 10 3.727622 4.318761 3.497844 2.900855 3.494304 2.440057 \n", + " 11 3.349516 3.853837 4.161056 3.643049 4.160678 3.193441 \n", + " 12 0.965615 1.545748 7.610318 7.135571 7.798981 4.491858 \n", + " 13 0.000000 0.965987 7.141895 6.574826 7.169682 3.892561 \n", + " 14 0.965987 0.000000 7.803721 7.180589 7.688652 4.568983 \n", + " 15 7.141895 7.803721 0.000000 0.966204 1.530824 4.469600 \n", + " 16 6.574826 7.180589 0.966204 0.000000 0.965836 3.806928 \n", + " 17 7.169682 7.688652 1.530824 0.965836 0.000000 4.447433 \n", + " 18 3.892561 4.568983 4.469600 3.806928 4.447433 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s24.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.973694 1.579777 3.680347 3.078824 2.097459 \n", + " 1 O 0.973694 0.000000 0.963465 3.012556 2.430426 1.371666 \n", + " 2 H 1.579777 0.963465 0.000000 3.542903 3.093258 2.054036 \n", + " 3 H 3.680347 3.012556 3.542903 0.000000 0.969188 1.693339 \n", + " 4 O 3.078824 2.430426 3.093258 0.969188 0.000000 1.069910 \n", + " 5 H 2.097459 1.371666 2.054036 1.693339 1.069910 0.000000 \n", + " 6 H 4.859925 5.559267 6.406397 6.465385 5.868423 5.685015 \n", + " 7 O 4.049118 4.679992 5.559298 5.535269 4.913236 4.739309 \n", + " 8 H 3.305100 4.049101 4.859950 5.399955 4.740120 4.360696 \n", + " 9 H 5.400085 5.535315 6.465464 5.186219 4.550697 4.955103 \n", + " 10 O 4.740199 4.913269 5.868471 4.550687 3.970112 4.328231 \n", + " 11 H 4.360841 4.739389 5.685124 4.955059 4.328201 4.437886 \n", + " 12 H 2.393718 3.298430 3.705873 5.840023 5.126896 4.311497 \n", + " 13 O 1.922071 2.871108 3.434185 5.133946 4.493947 3.727341 \n", + " 14 H 2.423152 3.383437 3.831388 5.572620 5.059504 4.267909 \n", + " 15 H 6.438127 5.928718 6.622267 3.752594 3.654136 4.671206 \n", + " 16 O 5.969356 5.569567 6.347116 3.458391 3.340433 4.334290 \n", + " 17 H 6.717075 6.371388 7.170626 4.130377 4.137679 5.131988 \n", + " 18 Hg 3.708544 3.526230 4.432137 2.596317 2.003302 2.575113 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.859925 4.049118 3.305100 5.400085 4.740199 4.360841 2.393718 \n", + " 1 5.559267 4.679992 4.049101 5.535315 4.913269 4.739389 3.298430 \n", + " 2 6.406397 5.559298 4.859950 6.465464 5.868471 5.685124 3.705873 \n", + " 3 6.465385 5.535269 5.399955 5.186219 4.550687 4.955059 5.840023 \n", + " 4 5.868423 4.913236 4.740120 4.550697 3.970112 4.328201 5.126896 \n", + " 5 5.685015 4.739309 4.360696 4.955103 4.328231 4.437886 4.311497 \n", + " 6 0.000000 0.963466 1.579739 3.543105 3.093398 2.054254 3.831574 \n", + " 7 0.963466 0.000000 0.973688 3.012662 2.430514 1.371862 3.383624 \n", + " 8 1.579739 0.973688 0.000000 3.680544 3.078947 2.097697 2.423350 \n", + " 9 3.543105 3.012662 3.680544 0.000000 0.969185 1.693248 5.573087 \n", + " 10 3.093398 2.430514 3.078947 0.969185 0.000000 1.069810 5.059822 \n", + " 11 2.054254 1.371862 2.097697 1.693248 1.069810 0.000000 4.268331 \n", + " 12 3.831574 3.383624 2.423350 5.573087 5.059822 4.268331 0.000000 \n", + " 13 3.434457 2.871399 1.922375 5.134343 4.494228 3.727776 0.966775 \n", + " 14 3.706119 3.298708 2.393976 5.840340 5.127097 4.311878 1.521335 \n", + " 15 7.169777 6.370630 6.716514 4.128274 4.136402 5.130793 7.921272 \n", + " 16 6.346211 5.568766 5.968786 3.455942 3.338885 4.332951 7.353641 \n", + " 17 6.621459 5.928024 6.437649 3.750231 3.652679 4.669955 8.025338 \n", + " 18 4.432211 3.526286 3.708577 2.596345 2.003349 2.575100 4.957291 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.922071 2.423152 6.438127 5.969356 6.717075 3.708544 \n", + " 1 2.871108 3.383437 5.928718 5.569567 6.371388 3.526230 \n", + " 2 3.434185 3.831388 6.622267 6.347116 7.170626 4.432137 \n", + " 3 5.133946 5.572620 3.752594 3.458391 4.130377 2.596317 \n", + " 4 4.493947 5.059504 3.654136 3.340433 4.137679 2.003302 \n", + " 5 3.727341 4.267909 4.671206 4.334290 5.131988 2.575113 \n", + " 6 3.434457 3.706119 7.169777 6.346211 6.621459 4.432211 \n", + " 7 2.871399 3.298708 6.370630 5.568766 5.928024 3.526286 \n", + " 8 1.922375 2.393976 6.716514 5.968786 6.437649 3.708577 \n", + " 9 5.134343 5.840340 4.128274 3.455942 3.750231 2.596345 \n", + " 10 4.494228 5.127097 4.136402 3.338885 3.652679 2.003349 \n", + " 11 3.727776 4.311878 5.130793 4.332951 4.669955 2.575100 \n", + " 12 0.966775 1.521335 7.921272 7.353641 8.025338 4.957291 \n", + " 13 0.000000 0.966781 7.343494 6.717600 7.343566 4.301860 \n", + " 14 0.966781 0.000000 8.025461 7.353844 7.921532 4.957235 \n", + " 15 7.343494 8.025461 0.000000 0.965231 1.534377 3.097979 \n", + " 16 6.717600 7.353844 0.965231 0.000000 0.965236 2.415740 \n", + " 17 7.343566 7.921532 1.534377 0.965236 0.000000 3.097984 \n", + " 18 4.301860 4.957235 3.097979 2.415740 3.097984 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 6.594516 7.105905 7.281634 4.580752 4.859491 \n", + " 1 O 6.594516 0.000000 0.965101 1.045660 2.495867 3.125206 \n", + " 2 H 7.105905 0.965101 0.000000 1.664409 3.009866 3.515057 \n", + " 3 H 7.281634 1.045660 1.664409 0.000000 3.097601 3.609078 \n", + " 4 O 4.580752 2.495867 3.009866 3.097601 0.000000 0.961358 \n", + " 5 H 4.859491 3.125206 3.515057 3.609078 0.961358 0.000000 \n", + " 6 H 5.731063 1.032669 1.654678 1.761169 1.464072 2.133692 \n", + " 7 O 8.294716 2.469423 2.991032 1.425443 4.198369 4.588114 \n", + " 8 H 9.008516 3.134848 3.483897 2.122893 4.742564 4.968911 \n", + " 9 H 8.739799 3.061901 3.588117 2.090211 4.912027 5.398087 \n", + " 10 O 1.999857 8.435920 9.016337 9.039635 6.429605 6.658710 \n", + " 11 H 2.714162 9.252756 9.794628 9.874378 7.124528 7.245179 \n", + " 12 H 2.599148 8.797922 9.399997 9.390851 6.969409 7.299700 \n", + " 13 O 3.861897 10.333175 10.830052 10.966778 8.084783 8.077436 \n", + " 14 H 4.473483 10.994364 11.445147 11.677211 8.784342 8.792971 \n", + " 15 H 4.533614 10.866794 11.403702 11.439263 8.568016 8.503867 \n", + " 16 O 1.924646 4.882917 5.291431 5.667909 2.897773 3.252283 \n", + " 17 H 3.645895 3.171563 3.660434 3.874588 0.971077 1.553748 \n", + " 18 H 2.407452 5.103652 5.352590 5.995263 3.344216 3.688276 \n", + " \n", + " 6 7 8 9 10 11 \\\n", + " 0 5.731063 8.294716 9.008516 8.739799 1.999857 2.714162 \n", + " 1 1.032669 2.469423 3.134848 3.061901 8.435920 9.252756 \n", + " 2 1.654678 2.991032 3.483897 3.588117 9.016337 9.794628 \n", + " 3 1.761169 1.425443 2.122893 2.090211 9.039635 9.874378 \n", + " 4 1.464072 4.198369 4.742564 4.912027 6.429605 7.124528 \n", + " 5 2.133692 4.588114 4.968911 5.398087 6.658710 7.245179 \n", + " 6 0.000000 3.060684 3.676863 3.744829 7.588341 8.362768 \n", + " 7 3.060684 0.000000 0.962813 0.963180 9.927373 10.779100 \n", + " 8 3.676863 0.962813 0.000000 1.545977 10.649519 11.463161 \n", + " 9 3.744829 0.963180 1.545977 0.000000 10.300741 11.200466 \n", + " 10 7.588341 9.927373 10.649519 10.300741 0.000000 1.058537 \n", + " 11 8.362768 10.779100 11.463161 11.200466 1.058537 0.000000 \n", + " 12 8.018230 10.254673 11.025257 10.548359 0.966488 1.669751 \n", + " 13 9.399913 11.882562 12.515262 12.361324 2.449395 1.393450 \n", + " 14 10.075561 12.646992 13.295020 13.124031 3.098079 2.076809 \n", + " 15 9.916075 12.278003 12.878211 12.759531 3.036576 2.050587 \n", + " 16 4.004299 6.820104 7.501851 7.353651 3.921725 4.579987 \n", + " 17 2.193866 5.008074 5.625664 5.638851 5.539799 6.240446 \n", + " 18 4.296261 7.252791 7.929421 7.795674 4.351814 4.921225 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 2.599148 3.861897 4.473483 4.533614 1.924646 3.645895 2.407452 \n", + " 1 8.797922 10.333175 10.994364 10.866794 4.882917 3.171563 5.103652 \n", + " 2 9.399997 10.830052 11.445147 11.403702 5.291431 3.660434 5.352590 \n", + " 3 9.390851 10.966778 11.677211 11.439263 5.667909 3.874588 5.995263 \n", + " 4 6.969409 8.084783 8.784342 8.568016 2.897773 0.971077 3.344216 \n", + " 5 7.299700 8.077436 8.792971 8.503867 3.252283 1.553748 3.688276 \n", + " 6 8.018230 9.399913 10.075561 9.916075 4.004299 2.193866 4.296261 \n", + " 7 10.254673 11.882562 12.646992 12.278003 6.820104 5.008074 7.252791 \n", + " 8 11.025257 12.515262 13.295020 12.878211 7.501851 5.625664 7.929421 \n", + " 9 10.548359 12.361324 13.124031 12.759531 7.353651 5.638851 7.795674 \n", + " 10 0.966488 2.449395 3.098079 3.036576 3.921725 5.539799 4.351814 \n", + " 11 1.669751 1.393450 2.076809 2.050587 4.579987 6.240446 4.921225 \n", + " 12 0.000000 2.975006 3.460135 3.530520 4.468298 6.075504 4.861013 \n", + " 13 2.975006 0.000000 0.964125 0.964467 5.581764 7.226834 5.835959 \n", + " 14 3.460135 0.964125 0.000000 1.547169 6.159715 7.898451 6.287180 \n", + " 15 3.530520 0.964467 1.547169 0.000000 6.238950 7.759184 6.581830 \n", + " 16 4.468298 5.581764 6.159715 6.238950 0.000000 1.930979 0.969116 \n", + " 17 6.075504 7.226834 7.898451 7.759184 1.930979 0.000000 2.438442 \n", + " 18 4.861013 5.835959 6.287180 6.581830 0.969116 2.438442 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964803 1.552046 5.170235 4.959749 3.664601 \n", + " 1 O 0.964803 0.000000 0.964040 4.720864 4.354849 3.032188 \n", + " 2 H 1.552046 0.964040 0.000000 5.495863 5.015609 3.683594 \n", + " 3 H 5.170235 4.720864 5.495863 0.000000 0.968367 2.092948 \n", + " 4 O 4.959749 4.354849 5.015609 0.968367 0.000000 1.589607 \n", + " 5 H 3.664601 3.032188 3.683594 2.092948 1.589607 0.000000 \n", + " 6 H 9.766148 9.055848 9.345472 6.517823 6.145569 7.396118 \n", + " 7 O 9.387604 8.707559 9.084050 5.773753 5.491403 6.846833 \n", + " 8 H 10.011755 9.384283 9.815236 6.208999 6.058397 7.486214 \n", + " 9 H 9.175050 8.409703 8.810398 4.861409 4.488123 5.830449 \n", + " 10 O 8.411375 7.649229 8.042294 4.342220 3.906484 5.250955 \n", + " 11 H 8.791854 8.060175 8.451920 4.852883 4.490873 5.870072 \n", + " 12 H 3.559384 2.985617 3.445250 3.527414 3.102517 1.634716 \n", + " 13 O 2.990887 2.425133 3.075685 2.948851 2.581344 1.005584 \n", + " 14 H 1.998581 1.345706 2.030760 3.670935 3.282049 1.795929 \n", + " 15 H 10.938709 10.212651 10.667328 6.225372 6.050180 7.395063 \n", + " 16 O 10.271827 9.505426 9.906635 5.790453 5.484177 6.758775 \n", + " 17 H 10.785262 9.975821 10.303412 6.535530 6.137717 7.297735 \n", + " 18 Hg 6.629230 5.922118 6.431229 2.432348 1.940110 3.355635 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 9.766148 9.387604 10.011755 9.175050 8.411375 8.791854 3.559384 \n", + " 1 9.055848 8.707559 9.384283 8.409703 7.649229 8.060175 2.985617 \n", + " 2 9.345472 9.084050 9.815236 8.810398 8.042294 8.451920 3.445250 \n", + " 3 6.517823 5.773753 6.208999 4.861409 4.342220 4.852883 3.527414 \n", + " 4 6.145569 5.491403 6.058397 4.488123 3.906484 4.490873 3.102517 \n", + " 5 7.396118 6.846833 7.486214 5.830449 5.250955 5.870072 1.634716 \n", + " 6 0.000000 0.963606 1.539119 3.685202 3.097119 2.137466 8.817086 \n", + " 7 0.963606 0.000000 0.963247 3.109193 2.502581 1.479060 8.313570 \n", + " 8 1.539119 0.963247 0.000000 3.617804 3.171099 2.173976 8.998378 \n", + " 9 3.685202 3.109193 3.617804 0.000000 1.026877 1.719518 6.976225 \n", + " 10 3.097119 2.502581 3.171099 1.026877 0.000000 1.026978 6.515337 \n", + " 11 2.137466 1.479060 2.173976 1.719518 1.026978 0.000000 7.241504 \n", + " 12 8.817086 8.313570 8.998378 6.976225 6.515337 7.241504 0.000000 \n", + " 13 8.326795 7.810142 8.461478 6.790441 6.225055 6.851414 0.965096 \n", + " 14 8.575704 8.137789 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2.175059 1.479534 2.138387 2.612825 \n", + " 10 6.225055 6.787194 3.172326 2.502815 3.097882 1.968065 \n", + " 11 6.851414 7.316412 3.620950 3.110449 3.687189 2.614257 \n", + " 12 0.965096 1.721691 8.380737 7.716155 8.136214 4.724754 \n", + " 13 0.000000 1.081825 8.317934 7.672241 8.170676 4.352331 \n", + " 14 1.081825 0.000000 9.128700 8.446031 8.927488 4.970321 \n", + " 15 8.317934 9.128700 0.000000 0.963230 1.539050 4.411469 \n", + " 16 7.672241 8.446031 0.963230 0.000000 0.963623 3.792781 \n", + " 17 8.170676 8.927488 1.539050 0.963623 0.000000 4.465558 \n", + " 18 4.352331 4.970321 4.411469 3.792781 4.465558 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.803769 4.471357 4.442770 2.385987 3.043698 \n", + " 1 O 3.803769 0.000000 0.967310 0.967047 5.283259 5.835344 \n", + " 2 H 4.471357 0.967310 0.000000 1.532376 5.618413 6.090331 \n", + " 3 H 4.442770 0.967047 1.532376 0.000000 6.138300 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2.162401 \n", + " 2 5.639079 3.096193 2.145226 3.639867 3.557666 4.276200 2.733684 \n", + " 3 6.294680 3.166853 2.174718 3.544754 3.550674 4.180670 2.720917 \n", + " 4 0.966415 3.704134 4.319183 4.370360 3.500114 3.986949 4.205683 \n", + " 5 1.534092 4.056004 4.764772 4.591809 4.379625 4.924186 5.010358 \n", + " 6 0.000000 4.234442 4.677557 5.005847 3.479922 3.839026 4.154814 \n", + " 7 4.234442 0.000000 1.019182 0.967736 3.106313 4.051502 3.069447 \n", + " 8 4.677557 1.019182 0.000000 1.631752 2.893627 3.820988 2.547015 \n", + " 9 5.005847 0.967736 1.631752 0.000000 4.001442 4.923532 3.943223 \n", + " 10 3.479922 3.106313 2.893627 4.001442 0.000000 0.965361 0.968388 \n", + " 11 3.839026 4.051502 3.820988 4.923532 0.965361 0.000000 1.552740 \n", + " 12 4.154814 3.069447 2.547015 3.943223 0.968388 1.552740 0.000000 \n", + " 13 3.475714 4.135807 4.742646 4.599118 3.474690 3.661894 4.356717 \n", + " 14 4.434062 4.652264 5.268055 4.973701 4.157260 4.288355 4.991167 \n", + " 15 3.162982 4.703568 5.373107 5.178656 4.056238 4.208934 4.975186 \n", + " \n", + " 13 14 15 \n", + " 0 2.112507 2.780133 2.689423 \n", + " 1 5.714697 6.259166 6.378973 \n", + " 2 6.437230 7.052373 7.022064 \n", + " 3 6.253501 6.690463 6.999046 \n", + " 4 2.877042 3.797859 2.591399 \n", + " 5 3.550195 4.392349 3.143988 \n", + " 6 3.475714 4.434062 3.162982 \n", + " 7 4.135807 4.652264 4.703568 \n", + " 8 4.742646 5.268055 5.373107 \n", + " 9 4.599118 4.973701 5.178656 \n", + " 10 3.474690 4.157260 4.056238 \n", + " 11 3.661894 4.288355 4.208934 \n", + " 12 4.356717 4.991167 4.975186 \n", + " 13 0.000000 0.969258 0.969467 \n", + " 14 0.969258 0.000000 1.571047 \n", + " 15 0.969467 1.571047 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s18.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.963552 1.540555 2.158860 3.165146 3.588934 \n", + " 1 O 0.963552 0.000000 0.964073 1.458452 2.488654 3.075311 \n", + " 2 H 1.540555 0.964073 0.000000 2.117594 3.079550 3.661813 \n", + " 3 H 2.158860 1.458452 2.117594 0.000000 1.034259 1.699166 \n", + " 4 O 3.165146 2.488654 3.079550 1.034259 0.000000 0.999681 \n", + " 5 H 3.588934 3.075311 3.661813 1.699166 0.999681 0.000000 \n", + " 6 H 6.138314 5.723187 6.429894 5.000786 4.636974 5.235001 \n", + " 7 O 6.047655 5.530485 6.210762 4.610346 4.082613 4.631225 \n", + " 8 H 6.694477 6.085559 6.667976 5.154581 4.580568 5.165233 \n", + " 9 H 4.978694 4.809410 5.407076 3.723587 3.251974 2.272820 \n", + " 10 O 4.885510 4.534192 5.086320 3.279098 2.620059 1.636247 \n", + " 11 H 5.431704 5.020469 5.427023 3.809208 3.164798 2.234534 \n", + " 12 H 5.930101 5.488011 6.166687 4.073520 3.136163 2.589660 \n", + " 13 O 6.038902 5.547253 6.248978 4.146023 3.193536 2.938506 \n", + " 14 H 6.839545 6.404190 7.145389 5.037730 4.119600 3.845320 \n", + " 15 H 7.171647 6.364721 6.743833 5.118014 4.239510 4.548622 \n", + " 16 O 6.496906 5.683690 6.060576 4.542534 3.773371 4.272746 \n", + " 17 H 6.718616 5.843321 6.078316 4.836233 4.179335 4.769152 \n", + " 18 Hg 4.473181 3.857836 4.531492 2.683074 2.013757 2.588275 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.138314 6.047655 6.694477 4.978694 4.885510 5.431704 5.930101 \n", + " 1 5.723187 5.530485 6.085559 4.809410 4.534192 5.020469 5.488011 \n", + " 2 6.429894 6.210762 6.667976 5.407076 5.086320 5.427023 6.166687 \n", + " 3 5.000786 4.610346 5.154581 3.723587 3.279098 3.809208 4.073520 \n", + " 4 4.636974 4.082613 4.580568 3.251974 2.620059 3.164798 3.136163 \n", + " 5 5.235001 4.631225 5.165233 2.272820 1.636247 2.234534 2.589660 \n", + " 6 0.000000 0.968971 1.579334 6.752810 6.260137 7.013011 4.985818 \n", + " 7 0.968971 0.000000 0.970904 6.166813 5.589727 6.280247 4.226458 \n", + " 8 1.579334 0.970904 0.000000 6.786225 6.118620 6.710624 4.689987 \n", + " 9 6.752810 6.166813 6.786225 0.000000 0.965989 1.527517 2.643289 \n", + " 10 6.260137 5.589727 6.118620 0.965989 0.000000 0.966297 2.093206 \n", + " 11 7.013011 6.280247 6.710624 1.527517 0.966297 0.000000 2.656933 \n", + " 12 4.985818 4.226458 4.689987 2.643289 2.093206 2.656933 0.000000 \n", + " 13 4.134042 3.340574 3.770361 3.496177 2.906850 3.497895 0.968827 \n", + " 14 4.269990 3.539320 3.949511 4.071911 3.622472 4.200478 1.550477 \n", + " 15 4.281107 3.347737 2.897792 6.016159 5.127599 5.325019 3.842732 \n", + " 16 3.634845 2.752897 2.313586 6.010447 5.139941 5.439452 4.014957 \n", + " 17 4.228207 3.447607 2.895425 6.643978 5.739814 5.947745 4.839666 \n", + " 18 2.752267 2.085646 2.616749 4.401355 3.749755 4.410066 2.962402 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 6.038902 6.839545 7.171647 6.496906 6.718616 4.473181 \n", + " 1 5.547253 6.404190 6.364721 5.683690 5.843321 3.857836 \n", + " 2 6.248978 7.145389 6.743833 6.060576 6.078316 4.531492 \n", + " 3 4.146023 5.037730 5.118014 4.542534 4.836233 2.683074 \n", + " 4 3.193536 4.119600 4.239510 3.773371 4.179335 2.013757 \n", + " 5 2.938506 3.845320 4.548622 4.272746 4.769152 2.588275 \n", + " 6 4.134042 4.269990 4.281107 3.634845 4.228207 2.752267 \n", + " 7 3.340574 3.539320 3.347737 2.752897 3.447607 2.085646 \n", + " 8 3.770361 3.949511 2.897792 2.313586 2.895425 2.616749 \n", + " 9 3.496177 4.071911 6.016159 6.010447 6.643978 4.401355 \n", + " 10 2.906850 3.622472 5.127599 5.139941 5.739814 3.749755 \n", + " 11 3.497895 4.200478 5.325019 5.439452 5.947745 4.410066 \n", + " 12 0.968827 1.550477 3.842732 4.014957 4.839666 2.962402 \n", + " 13 0.000000 0.964597 3.200066 3.324682 4.224193 2.398772 \n", + " 14 0.964597 0.000000 3.605787 3.841635 4.785922 3.119128 \n", + " 15 3.200066 3.605787 0.000000 0.965777 1.529735 3.085947 \n", + " 16 3.324682 3.841635 0.965777 0.000000 0.966031 2.488528 \n", + " 17 4.224193 4.785922 1.529735 0.966031 0.000000 3.159417 \n", + " 18 2.398772 3.119128 3.085947 2.488528 3.159417 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s9.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.919806 4.589428 4.535429 5.939474 6.492304 \n", + " 1 O 3.919806 0.000000 0.966152 0.965773 9.658094 10.161402 \n", + " 2 H 4.589428 0.966152 0.000000 1.536095 10.153174 10.597745 \n", + " 3 H 4.535429 0.965773 1.536095 0.000000 10.377299 10.918940 \n", + " 4 O 5.939474 9.658094 10.153174 10.377299 0.000000 0.964292 \n", + " 5 H 6.492304 10.161402 10.597745 10.918940 0.964292 0.000000 \n", + " 6 H 6.616074 10.317385 10.840780 11.010525 0.963858 1.549816 \n", + " 7 O 4.138715 8.050901 8.662406 8.664945 2.439783 3.020760 \n", + " 8 H 4.619589 8.527725 9.200480 9.065385 2.973155 3.554819 \n", + " 9 H 4.876809 8.727376 9.289354 9.392492 1.371430 2.031026 \n", + " 10 O 2.521511 2.981886 3.537914 3.633034 7.258923 7.873443 \n", + " 11 H 3.218496 3.754723 4.193389 4.392399 7.150433 7.780817 \n", + " 12 H 3.177369 2.273963 2.801864 2.862438 8.216157 8.816966 \n", + " 13 O 2.022468 2.523823 3.075764 3.146305 7.740868 8.173032 \n", + " 14 H 2.696303 1.500080 2.117675 2.155477 8.514720 8.981339 \n", + " 15 H 2.633870 3.036898 3.545304 3.477748 8.159687 8.551548 \n", + " 16 O 1.955179 5.731305 6.409540 6.314689 4.265290 4.967829 \n", + " 17 H 2.450398 5.850785 6.575820 6.367212 4.571426 5.378287 \n", + " 18 H 3.224033 7.125408 7.762220 7.729415 3.030538 3.704084 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.616074 4.138715 4.619589 4.876809 2.521511 3.218496 3.177369 \n", + " 1 10.317385 8.050901 8.527725 8.727376 2.981886 3.754723 2.273963 \n", + " 2 10.840780 8.662406 9.200480 9.289354 3.537914 4.193389 2.801864 \n", + " 3 11.010525 8.664945 9.065385 9.392492 3.633034 4.392399 2.862438 \n", + " 4 0.963858 2.439783 2.973155 1.371430 7.258923 7.150433 8.216157 \n", + " 5 1.549816 3.020760 3.554819 2.031026 7.873443 7.780817 8.816966 \n", + " 6 0.000000 3.092270 3.441594 2.059661 7.786183 7.602648 8.750583 \n", + " 7 3.092270 0.000000 0.965990 1.070182 6.030131 6.218626 6.932522 \n", + " 8 3.441594 0.965990 0.000000 1.692893 6.606227 6.843244 7.481113 \n", + " 9 2.059661 1.070182 1.692893 0.000000 6.499476 6.545130 7.439093 \n", + " 10 7.786183 6.030131 6.606227 6.499476 0.000000 0.963561 0.964664 \n", + " 11 7.602648 6.218626 6.843244 6.545130 0.963561 0.000000 1.534053 \n", + " 12 8.750583 6.932522 7.481113 7.439093 0.964664 1.534053 0.000000 \n", + " 13 8.492142 5.921198 6.373196 6.692649 3.010750 3.924715 3.093672 \n", + " 14 9.227860 6.776282 7.236687 7.511338 2.778108 3.701130 2.541758 \n", + " 15 8.939819 6.188844 6.548763 7.038789 3.947350 4.874031 3.987096 \n", + " 16 4.825702 2.551019 3.048004 3.194663 3.561851 3.835700 4.448575 \n", + " 17 4.967886 3.112707 3.497158 3.621535 3.422739 3.554894 4.309416 \n", + " 18 3.648012 1.016215 1.636945 1.776110 5.042531 5.250503 5.943329 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.022468 2.696303 2.633870 1.955179 2.450398 3.224033 \n", + " 1 2.523823 1.500080 3.036898 5.731305 5.850785 7.125408 \n", + " 2 3.075764 2.117675 3.545304 6.409540 6.575820 7.762220 \n", + " 3 3.146305 2.155477 3.477748 6.314689 6.367212 7.729415 \n", + " 4 7.740868 8.514720 8.159687 4.265290 4.571426 3.030538 \n", + " 5 8.173032 8.981339 8.551548 4.967829 5.378287 3.704084 \n", + " 6 8.492142 9.227860 8.939819 4.825702 4.967886 3.648012 \n", + " 7 5.921198 6.776282 6.188844 2.551019 3.112707 1.016215 \n", + " 8 6.373196 7.236687 6.548763 3.048004 3.497158 1.636945 \n", + " 9 6.692649 7.511338 7.038789 3.194663 3.621535 1.776110 \n", + " 10 3.010750 2.778108 3.947350 3.561851 3.422739 5.042531 \n", + " 11 3.924715 3.701130 4.874031 3.835700 3.554894 5.250503 \n", + " 12 3.093672 2.541758 3.987096 4.448575 4.309416 5.943329 \n", + " 13 0.000000 1.026294 0.966509 3.969271 4.435853 5.106355 \n", + " 14 1.026294 0.000000 1.634194 4.628071 4.933884 5.904200 \n", + " 15 0.966509 1.634194 0.000000 4.484091 5.025770 5.460106 \n", + " 16 3.969271 4.628071 4.484091 0.000000 0.967107 1.536239 \n", + " 17 4.435853 4.933884 5.025770 0.967107 0.000000 2.139009 \n", + " 18 5.106355 5.904200 5.460106 1.536239 2.139009 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s2.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.060409 2.731948 2.682512 2.050888 2.700025 2.697173 \n", + " 1 O 2.060409 0.000000 0.972336 0.971710 4.075495 4.569883 4.744070 \n", + " 2 H 2.731948 0.972336 0.000000 1.583410 4.600189 4.928434 5.364906 \n", + " 3 H 2.682512 0.971710 1.583410 0.000000 4.723822 5.322516 5.319386 \n", + " 4 O 2.050888 4.075495 4.600189 4.723822 0.000000 0.972870 0.972329 \n", + " 5 H 2.700025 4.569883 4.928434 5.322516 0.972870 0.000000 1.578807 \n", + " 6 H 2.697173 4.744070 5.364906 5.319386 0.972329 1.578807 0.000000 \n", + " 7 O 2.329501 2.994335 3.958028 2.848908 3.577354 4.505183 3.685861 \n", + " 8 H 3.002340 3.686242 4.615772 3.407772 3.999482 4.945588 4.052235 \n", + " 9 H 3.003505 3.504270 4.472701 3.310765 4.158722 5.086300 4.110546 \n", + " \n", + " 7 8 9 \n", + " 0 2.329501 3.002340 3.003505 \n", + " 1 2.994335 3.686242 3.504270 \n", + " 2 3.958028 4.615772 4.472701 \n", + " 3 2.848908 3.407772 3.310765 \n", + " 4 3.577354 3.999482 4.158722 \n", + " 5 4.505183 4.945588 5.086300 \n", + " 6 3.685861 4.052235 4.110546 \n", + " 7 0.000000 0.968360 0.968391 \n", + " 8 0.968360 0.000000 1.542437 \n", + " 9 0.968391 1.542437 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.969573 1.578602 7.244772 6.394650 6.879331 \n", + " 1 O 0.969573 0.000000 0.969556 6.736873 5.778322 6.167413 \n", + " 2 H 1.578602 0.969556 0.000000 7.419354 6.372044 6.650838 \n", + " 3 H 7.244772 6.736873 7.419354 0.000000 1.283170 1.896155 \n", + " 4 O 6.394650 5.778322 6.372044 1.283170 0.000000 0.967742 \n", + " 5 H 6.879331 6.167413 6.650838 1.896155 0.967742 0.000000 \n", + " 6 H 8.798691 8.361471 9.073848 1.773849 2.970337 3.379612 \n", + " 7 O 8.044201 7.620920 8.360692 1.124368 2.406612 2.955599 \n", + " 8 H 8.455013 8.042937 8.796570 1.772117 2.960585 3.390317 \n", + " 9 H 3.390747 2.955635 3.379759 5.298001 4.396416 4.872983 \n", + " 10 O 2.961094 2.406734 2.970421 4.869610 3.916629 4.396258 \n", + " 11 H 1.772415 1.124483 1.774019 5.836252 4.869476 5.297467 \n", + " 12 Hg 4.592894 3.977307 4.572725 2.979537 1.958516 2.502811 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 8.798691 8.044201 8.455013 3.390747 2.961094 1.772415 4.592894 \n", + " 1 8.361471 7.620920 8.042937 2.955635 2.406734 1.124483 3.977307 \n", + " 2 9.073848 8.360692 8.796570 3.379759 2.970421 1.774019 4.572725 \n", + " 3 1.773849 1.124368 1.772117 5.298001 4.869610 5.836252 2.979537 \n", + " 4 2.970337 2.406612 2.960585 4.396416 3.916629 4.869476 1.958516 \n", + " 5 3.379612 2.955599 3.390317 4.872983 4.396258 5.297467 2.502811 \n", + " 6 0.000000 0.969573 1.578598 6.652690 6.373124 7.420187 4.573391 \n", + " 7 0.969573 0.000000 0.969582 6.168170 5.778470 6.736855 3.977330 \n", + " 8 1.578598 0.969582 0.000000 6.879193 6.393812 7.243605 4.592124 \n", + " 9 6.652690 6.168170 6.879193 0.000000 0.967742 1.896082 2.502902 \n", + " 10 6.373124 5.778470 6.393812 0.967742 0.000000 1.283176 1.958514 \n", + " 11 7.420187 6.736855 7.243605 1.896082 1.283176 0.000000 2.979463 \n", + " 12 4.573391 3.977330 4.592124 2.502902 1.958514 2.979463 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s14.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.888228 4.586643 4.489314 2.055280 2.745823 \n", + " 1 O 3.888228 0.000000 0.966573 0.966249 5.762830 6.075192 \n", + " 2 H 4.586643 0.966573 0.000000 1.530871 6.516714 6.852910 \n", + " 3 H 4.489314 0.966249 1.530871 0.000000 6.259410 6.510775 \n", + " 4 O 2.055280 5.762830 6.516714 6.259410 0.000000 1.045132 \n", + " 5 H 2.745823 6.075192 6.852910 6.510775 1.045132 0.000000 \n", + " 6 H 2.645985 6.375420 7.161029 6.811186 0.966940 1.641311 \n", + " 7 O 2.087125 2.578184 3.132045 3.208751 4.102460 4.790241 \n", + " 8 H 2.709099 1.580178 2.187120 2.226174 4.717886 5.252353 \n", + " 9 H 2.708962 3.126116 3.637457 3.586482 4.564503 5.337490 \n", + " 10 O 2.388515 5.120523 5.453003 5.972650 3.235052 3.955017 \n", + " 11 H 3.067741 5.093365 5.259601 6.003471 4.178568 4.887715 \n", + " 12 H 3.063381 6.071808 6.408937 6.914930 3.342033 4.034123 \n", + " 13 O 2.367137 2.897718 3.494187 3.515517 3.610004 3.653560 \n", + " 14 H 2.996451 2.089928 2.655084 2.679306 4.466251 4.537857 \n", + " 15 H 3.082799 3.632941 4.116941 4.218031 3.920826 3.754944 \n", + " 16 O 3.925254 6.708904 7.479643 7.069685 2.475365 1.432814 \n", + " 17 H 4.509814 7.027934 7.849512 7.267224 3.119095 2.108508 \n", + " 18 H 4.624342 7.490189 8.211717 7.902488 3.049611 2.078466 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.645985 2.087125 2.709099 2.708962 2.388515 3.067741 3.063381 \n", + " 1 6.375420 2.578184 1.580178 3.126116 5.120523 5.093365 6.071808 \n", + " 2 7.161029 3.132045 2.187120 3.637457 5.453003 5.259601 6.408937 \n", + " 3 6.811186 3.208751 2.226174 3.586482 5.972650 6.003471 6.914930 \n", + " 4 0.966940 4.102460 4.717886 4.564503 3.235052 4.178568 3.342033 \n", + " 5 1.641311 4.790241 5.252353 5.337490 3.955017 4.887715 4.034123 \n", + " 6 0.000000 4.521261 5.220796 4.802906 3.819678 4.751889 3.833514 \n", + " 7 4.521261 0.000000 1.009015 0.967004 3.291072 3.408540 4.193538 \n", + " 8 5.220796 1.009015 0.000000 1.613297 3.984763 4.026614 4.928060 \n", + " 9 4.802906 0.967004 1.613297 0.000000 3.878031 3.964897 4.711168 \n", + " 10 3.819678 3.291072 3.984763 3.878031 0.000000 0.964290 0.964418 \n", + " 11 4.751889 3.408540 4.026614 3.964897 0.964290 0.000000 1.534743 \n", + " 12 3.833514 4.193538 4.928060 4.711168 0.964418 1.534743 0.000000 \n", + " 13 4.468963 2.983448 2.777096 3.910822 3.541447 3.914372 4.294631 \n", + " 14 5.269672 2.966291 2.440701 3.859374 4.193924 4.406727 5.028989 \n", + " 15 4.846686 3.914477 3.703445 4.853935 3.902103 4.279764 4.529276 \n", + " 16 2.975904 5.879579 6.169813 6.509521 5.057188 5.945565 5.107383 \n", + " 17 3.451501 6.359231 6.581266 6.938851 5.906038 6.792767 6.006106 \n", + " 18 3.507494 6.630335 6.952041 7.284256 5.381449 6.261044 5.280532 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.367137 2.996451 3.082799 3.925254 4.509814 4.624342 \n", + " 1 2.897718 2.089928 3.632941 6.708904 7.027934 7.490189 \n", + " 2 3.494187 2.655084 4.116941 7.479643 7.849512 8.211717 \n", + " 3 3.515517 2.679306 4.218031 7.069685 7.267224 7.902488 \n", + " 4 3.610004 4.466251 3.920826 2.475365 3.119095 3.049611 \n", + " 5 3.653560 4.537857 3.754944 1.432814 2.108508 2.078466 \n", + " 6 4.468963 5.269672 4.846686 2.975904 3.451501 3.507494 \n", + " 7 2.983448 2.966291 3.914477 5.879579 6.359231 6.630335 \n", + " 8 2.777096 2.440701 3.703445 6.169813 6.581266 6.952041 \n", + " 9 3.910822 3.859374 4.853935 6.509521 6.938851 7.284256 \n", + " 10 3.541447 4.193924 3.902103 5.057188 5.906038 5.381449 \n", + " 11 3.914372 4.406727 4.279764 5.945565 6.792767 6.261044 \n", + " 12 4.294631 5.028989 4.529276 5.107383 6.006106 5.280532 \n", + " 13 0.000000 0.968013 0.963725 4.095306 4.593124 4.751281 \n", + " 14 0.968013 0.000000 1.553396 4.942372 5.342701 5.632801 \n", + " 15 0.963725 1.553396 0.000000 3.899965 4.423755 4.423979 \n", + " 16 4.095306 4.942372 3.899965 0.000000 0.964517 0.964938 \n", + " 17 4.593124 5.342701 4.423755 0.964517 0.000000 1.540484 \n", + " 18 4.751281 5.632801 4.423979 0.964938 1.540484 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s6.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 4.124551 4.614938 4.867411 5.902410 6.593990 \n", + " 1 O 4.124551 0.000000 0.966076 1.084711 2.426264 3.073673 \n", + " 2 H 4.614938 0.966076 0.000000 1.711056 2.967521 3.428117 \n", + " 3 H 4.867411 1.084711 1.711056 0.000000 1.343549 2.028072 \n", + " 4 O 5.902410 2.426264 2.967521 1.343549 0.000000 0.964297 \n", + " 5 H 6.593990 3.073673 3.428117 2.028072 0.964297 0.000000 \n", + " 6 H 6.439051 3.000279 3.538456 2.000914 0.964845 1.552036 \n", + " 7 O 3.504384 4.655977 4.917549 5.063896 5.837665 6.048655 \n", + " 8 H 4.149258 5.155442 5.496461 5.387141 5.965673 6.092572 \n", + " 9 H 4.149349 5.115859 5.208584 5.575178 6.393223 6.523767 \n", + " 10 O 1.918722 2.589074 3.069296 3.263015 4.325095 4.891678 \n", + " 11 H 2.400074 3.234320 3.608057 3.777472 4.723154 5.131223 \n", + " 12 H 3.221079 1.006589 1.626490 1.787392 3.020861 3.639779 \n", + " 13 O 2.041780 5.966461 6.445617 6.719402 7.715039 8.478331 \n", + " 14 H 2.680154 6.558426 6.929550 7.391868 8.462160 9.209945 \n", + " 15 H 2.680515 6.598852 7.162707 7.255574 8.143227 8.907896 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.439051 3.504384 4.149258 4.149349 1.918722 2.400074 3.221079 \n", + " 1 3.000279 4.655977 5.155442 5.115859 2.589074 3.234320 1.006589 \n", + " 2 3.538456 4.917549 5.496461 5.208584 3.069296 3.608057 1.626490 \n", + " 3 2.000914 5.063896 5.387141 5.575178 3.263015 3.777472 1.787392 \n", + " 4 0.964845 5.837665 5.965673 6.393223 4.325095 4.723154 3.020861 \n", + " 5 1.552036 6.048655 6.092572 6.523767 4.891678 5.131223 3.639779 \n", + " 6 0.000000 6.712895 6.844182 7.302575 5.021076 5.522242 3.686716 \n", + " 7 6.712895 0.000000 0.963300 0.963358 2.602467 1.606018 3.757483 \n", + " 8 6.844182 0.963300 0.000000 1.529779 3.249679 2.286414 4.302269 \n", + " 9 7.302575 0.963358 1.529779 0.000000 3.250438 2.287778 4.280010 \n", + " 10 5.021076 2.602467 3.249679 3.250438 0.000000 1.004207 1.584376 \n", + " 11 5.522242 1.606018 2.286414 2.287778 1.004207 0.000000 2.263864 \n", + " 12 3.686716 3.757483 4.302269 4.280010 1.584376 2.263864 0.000000 \n", + " 13 8.128014 5.177412 5.751067 5.751258 3.958907 4.371802 5.152256 \n", + " 14 8.898078 5.588545 6.229655 6.032541 4.548378 4.900078 5.751521 \n", + " 15 8.525890 5.577616 6.021238 6.216980 4.548793 4.895326 5.774781 \n", + " \n", + " 13 14 15 \n", + " 0 2.041780 2.680154 2.680515 \n", + " 1 5.966461 6.558426 6.598852 \n", + " 2 6.445617 6.929550 7.162707 \n", + " 3 6.719402 7.391868 7.255574 \n", + " 4 7.715039 8.462160 8.143227 \n", + " 5 8.478331 9.209945 8.907896 \n", + " 6 8.128014 8.898078 8.525890 \n", + " 7 5.177412 5.588545 5.577616 \n", + " 8 5.751067 6.229655 6.021238 \n", + " 9 5.751258 6.032541 6.216980 \n", + " 10 3.958907 4.548378 4.548793 \n", + " 11 4.371802 4.900078 4.895326 \n", + " 12 5.152256 5.751521 5.774781 \n", + " 13 0.000000 0.970097 0.970066 \n", + " 14 0.970097 0.000000 1.573182 \n", + " 15 0.970066 1.573182 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.678433 2.678433\n", + " 1 O 2.048992 0.000000 0.982041 0.982041\n", + " 2 H 2.678433 0.982041 0.000000 1.597839\n", + " 3 H 2.678433 0.982041 1.597839 0.000000,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s1.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.968188 1.555238 5.180709 4.392876 4.500678 \n", + " 1 O 0.968188 0.000000 0.967994 4.771183 4.038622 4.350430 \n", + " 2 H 1.555238 0.967994 0.000000 5.404259 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4.232172 5.120017 2.797889 \n", + " 4 4.263569 3.882645 4.496600 3.708389 3.543622 4.366032 2.145634 \n", + " 5 5.106808 4.729476 5.385901 4.252928 4.111786 4.835362 2.796739 \n", + " 6 0.000000 0.967677 1.549146 4.889790 4.268992 4.841911 2.932177 \n", + " 7 0.967677 0.000000 0.967712 3.996719 3.332463 3.876987 2.250916 \n", + " 8 1.549146 0.967712 0.000000 3.871826 3.305555 3.788628 2.885640 \n", + " 9 4.889790 3.996719 3.871826 0.000000 0.967121 1.546243 2.948884 \n", + " 10 4.268992 3.332463 3.305555 0.967121 0.000000 0.966969 2.272916 \n", + " 11 4.841911 3.876987 3.788628 1.546243 0.966969 0.000000 2.929518 \n", + " 12 2.932177 2.250916 2.885640 2.948884 2.272916 2.929518 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s3.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.022899 2.666166 2.666073 1.941848 3.174919 2.448658 \n", + " 1 O 2.022899 0.000000 0.972445 0.972443 3.963048 5.106188 4.413712 \n", + " 2 H 2.666166 0.972445 0.000000 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'/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.981026 2.799166 2.504665 1.973584 2.865536 \n", + " 1 O 1.981026 0.000000 1.093852 0.969208 3.951294 4.753305 \n", + " 2 H 2.799166 1.093852 0.000000 1.735655 4.689512 5.334823 \n", + " 3 H 2.504665 0.969208 1.735655 0.000000 4.432846 5.369454 \n", + " 4 O 1.973584 3.951294 4.689512 4.432846 0.000000 1.167798 \n", + " 5 H 2.865536 4.753305 5.334823 5.369454 1.167798 0.000000 \n", + " 6 H 2.548917 4.489738 5.341937 4.801330 0.966436 1.792896 \n", + " 7 O 2.595324 2.828984 3.873071 2.321166 3.748962 4.900609 \n", + " 8 H 3.252223 3.419363 4.473481 2.863696 4.262071 5.390238 \n", + " 9 H 3.264032 3.495856 4.456904 2.897429 4.233898 5.398275 \n", + " 10 O 3.925602 5.686465 6.124115 6.395652 2.388479 1.221852 \n", + " 11 H 4.558043 6.321068 6.711548 7.016971 2.967580 1.876788 \n", + " 12 H 4.541113 6.285117 6.754873 6.988400 2.978188 1.879641 \n", + " 13 O 3.943850 2.415498 1.323568 2.979339 5.698137 6.173392 \n", + " 14 H 4.596388 2.994373 1.979687 3.506881 6.349143 6.781947 \n", + " 15 H 4.560294 3.048819 1.999593 3.453987 6.287199 6.774243 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.548917 2.595324 3.252223 3.264032 3.925602 4.558043 4.541113 \n", + " 1 4.489738 2.828984 3.419363 3.495856 5.686465 6.321068 6.285117 \n", + " 2 5.341937 3.873071 4.473481 4.456904 6.124115 6.711548 6.754873 \n", + " 3 4.801330 2.321166 2.863696 2.897429 6.395652 7.016971 6.988400 \n", + " 4 0.966436 3.748962 4.262071 4.233898 2.388479 2.967580 2.978188 \n", + " 5 1.792896 4.900609 5.390238 5.398275 1.221852 1.876788 1.879641 \n", + " 6 0.000000 3.624739 4.042889 3.987961 2.940545 3.409050 3.399032 \n", + " 7 3.624739 0.000000 0.965799 0.965659 6.103561 6.685812 6.617038 \n", + " 8 4.042889 0.965799 0.000000 1.523962 6.582432 7.229512 6.983428 \n", + " 9 3.987961 0.965659 1.523962 0.000000 6.613124 7.094169 7.181079 \n", + " 10 2.940545 6.103561 6.582432 6.613124 0.000000 0.967236 0.967170 \n", + " 11 3.409050 6.685812 7.229512 7.094169 0.967236 0.000000 1.565340 \n", + " 12 3.399032 6.617038 6.983428 7.181079 0.967170 1.565340 0.000000 \n", + " 13 6.441208 5.180903 5.781396 5.714577 6.789515 7.317673 7.429695 \n", + " 14 7.105176 5.763492 6.251551 6.365189 7.344281 7.931258 7.903527 \n", + " 15 7.005419 5.635709 6.300849 6.037486 7.385557 7.824585 8.091874 \n", + " \n", + " 13 14 15 \n", + " 0 3.943850 4.596388 4.560294 \n", + " 1 2.415498 2.994373 3.048819 \n", + " 2 1.323568 1.979687 1.999593 \n", + " 3 2.979339 3.506881 3.453987 \n", + " 4 5.698137 6.349143 6.287199 \n", + " 5 6.173392 6.781947 6.774243 \n", + " 6 6.441208 7.105176 7.005419 \n", + " 7 5.180903 5.763492 5.635709 \n", + " 8 5.781396 6.251551 6.300849 \n", + " 9 5.714577 6.365189 6.037486 \n", + " 10 6.789515 7.344281 7.385557 \n", + " 11 7.317673 7.931258 7.824585 \n", + " 12 7.429695 7.903527 8.091874 \n", + " 13 0.000000 0.965608 0.965206 \n", + " 14 0.965608 0.000000 1.553479 \n", + " 15 0.965206 1.553479 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s1.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 3.476851 4.120858 4.121103 1.956843 3.136292 2.466239 \n", + " 1 O 3.476851 0.000000 0.965758 0.965758 2.462895 3.616760 1.393554 \n", + " 2 H 4.120858 0.965758 0.000000 1.548816 3.097371 4.129523 2.079326 \n", + " 3 H 4.121103 0.965758 1.548816 0.000000 3.097449 4.129600 2.079327 \n", + " 4 O 1.956843 2.462895 3.097371 3.097449 0.000000 1.523954 1.070687 \n", + " 5 H 3.136292 3.616760 4.129523 4.129600 1.523954 0.000000 2.326227 \n", + " 6 H 2.466239 1.393554 2.079326 2.079327 1.070687 2.326227 0.000000 \n", + " 7 O 4.042256 4.543152 4.997191 4.997338 2.551518 1.028424 3.316894 \n", + " 8 H 4.638325 4.851907 5.368609 5.132803 3.089294 1.679764 3.732646 \n", + " 9 H 4.638018 4.851623 5.132339 5.368467 3.089123 1.679767 3.732445 \n", + " \n", + " 7 8 9 \n", + " 0 4.042256 4.638325 4.638018 \n", + " 1 4.543152 4.851907 4.851623 \n", + " 2 4.997191 5.368609 5.132339 \n", + " 3 4.997338 5.132803 5.368467 \n", + " 4 2.551518 3.089294 3.089123 \n", + " 5 1.028424 1.679764 1.679767 \n", + " 6 3.316894 3.732646 3.732445 \n", + " 7 0.000000 0.974079 0.974081 \n", + " 8 0.974079 0.000000 1.599878 \n", + " 9 0.974081 1.599878 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 1.025838 1.720609 7.087869 6.699397 7.530552 \n", + " 1 O 1.025838 0.000000 1.026225 6.609295 6.110603 6.863198 \n", + " 2 H 1.720609 1.026225 0.000000 7.316214 6.723826 7.373659 \n", + " 3 H 7.087869 6.609295 7.316214 0.000000 0.966812 1.686753 \n", + " 4 O 6.699397 6.110603 6.723826 0.966812 0.000000 1.073698 \n", + " 5 H 7.530552 6.863198 7.373659 1.686753 1.073698 0.000000 \n", + " 6 H 3.682729 3.245966 3.692470 4.868975 4.356985 4.951207 \n", + " 7 O 3.268101 2.707314 3.266307 4.461794 3.919844 4.603371 \n", + " 8 H 1.680254 0.985633 1.680879 5.798811 5.283399 6.021902 \n", + " 9 H 3.694710 3.102793 2.147559 8.861112 8.150782 8.635719 \n", + " 10 O 3.094329 2.504868 1.480418 8.411342 7.718621 8.231227 \n", + " 11 H 3.605867 3.182373 2.185518 9.124123 8.425387 8.910078 \n", + " 12 H 2.187351 3.184135 3.608600 8.609082 8.371842 9.268444 \n", + " 13 O 1.481749 2.505759 3.096121 7.908103 7.665110 8.577955 \n", + " 14 H 2.148893 3.103671 3.697249 8.271996 8.086583 9.037371 \n", + " 15 H 9.119017 8.335226 8.692805 3.504567 3.017363 2.018393 \n", + " 16 O 8.605609 7.860031 8.250392 2.961609 2.433347 1.361915 \n", + " 17 H 9.296493 8.579836 8.972193 3.437722 3.073424 2.040622 \n", + " 18 Hg 4.889072 4.302254 4.910337 2.589031 1.991899 2.732259 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.682729 3.268101 1.680254 3.694710 3.094329 3.605867 2.187351 \n", + " 1 3.245966 2.707314 0.985633 3.102793 2.504868 3.182373 3.184135 \n", + " 2 3.692470 3.266307 1.680879 2.147559 1.480418 2.185518 3.608600 \n", + " 3 4.868975 4.461794 5.798811 8.861112 8.411342 9.124123 8.609082 \n", + " 4 4.356985 3.919844 5.283399 8.150782 7.718621 8.425387 8.371842 \n", + " 5 4.951207 4.603371 6.021902 8.635719 8.231227 8.910078 9.268444 \n", + " 6 0.000000 0.968697 2.295975 5.487870 4.682645 5.058376 5.040482 \n", + " 7 0.968697 0.000000 1.723367 5.079185 4.374248 4.917002 4.921983 \n", + " 8 2.295975 1.723367 0.000000 3.715192 3.031807 3.659971 3.661172 \n", + " 9 5.487870 5.079185 3.715192 0.000000 0.962871 1.540443 5.245727 \n", + " 10 4.682645 4.374248 3.031807 0.962871 0.000000 0.962413 4.633523 \n", + " 11 5.058376 4.917002 3.659971 1.540443 0.962413 0.000000 4.784142 \n", + " 12 5.040482 4.921983 3.661172 5.245727 4.633523 4.784142 0.000000 \n", + " 13 4.663761 4.377861 3.031772 4.846589 4.293137 4.632594 0.962429 \n", + " 14 5.466931 5.081670 3.714512 5.257087 4.848057 5.246807 1.540257 \n", + " 15 6.608368 6.256290 7.558321 9.594515 9.320995 10.000391 11.005787 \n", + " 16 5.862676 5.599462 7.022814 9.300035 8.938112 9.577303 10.410871 \n", + " 17 6.320282 6.181278 7.701676 10.064848 9.655432 10.244512 11.019896 \n", + " 18 2.422052 1.930128 3.400417 6.512969 5.961405 6.607752 6.564870 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.481749 2.148893 9.119017 8.605609 9.296493 4.889072 \n", + " 1 2.505759 3.103671 8.335226 7.860031 8.579836 4.302254 \n", + " 2 3.096121 3.697249 8.692805 8.250392 8.972193 4.910337 \n", + " 3 7.908103 8.271996 3.504567 2.961609 3.437722 2.589031 \n", + " 4 7.665110 8.086583 3.017363 2.433347 3.073424 1.991899 \n", + " 5 8.577955 9.037371 2.018393 1.361915 2.040622 2.732259 \n", + " 6 4.663761 5.466931 6.608368 5.862676 6.320282 2.422052 \n", + " 7 4.377861 5.081670 6.256290 5.599462 6.181278 1.930128 \n", + " 8 3.031772 3.714512 7.558321 7.022814 7.701676 3.400417 \n", + " 9 4.846589 5.257087 9.594515 9.300035 10.064848 6.512969 \n", + " 10 4.293137 4.848057 9.320995 8.938112 9.655432 5.961405 \n", + " 11 4.632594 5.246807 10.000391 9.577303 10.244512 6.607752 \n", + " 12 0.962429 1.540257 11.005787 10.410871 11.019896 6.564870 \n", + " 13 0.000000 0.962900 10.286605 9.737645 10.392354 5.917525 \n", + " 14 0.962900 0.000000 10.732845 10.233874 10.924519 6.461935 \n", + " 15 10.286605 10.732845 0.000000 0.964996 1.549942 4.534228 \n", + " 16 9.737645 10.233874 0.964996 0.000000 0.964673 3.866150 \n", + " 17 10.392354 10.924519 1.549942 0.964673 0.000000 4.478000 \n", + " 18 5.917525 6.461935 4.534228 3.866150 4.478000 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964625 1.554902 9.203025 8.574567 9.154834 \n", + " 1 O 0.964625 0.000000 0.965050 8.491399 7.846837 8.425118 \n", + " 2 H 1.554902 0.965050 0.000000 8.974263 8.310104 8.861084 \n", + " 3 H 9.203025 8.491399 8.974263 0.000000 0.967041 1.705050 \n", + " 4 O 8.574567 7.846837 8.310104 0.967041 0.000000 1.090171 \n", + " 5 H 9.154834 8.425118 8.861084 1.705050 1.090171 0.000000 \n", + " 6 H 2.003958 1.321642 1.978598 7.402632 6.837104 7.521187 \n", + " 7 O 3.059759 2.417056 2.989966 6.524299 6.043821 6.823332 \n", + " 8 H 3.417143 2.963515 3.533219 6.829618 6.468466 7.335541 \n", + " 9 H 10.380896 9.607987 9.920841 3.480740 2.999755 1.986641 \n", + " 10 O 9.907778 9.182377 9.578229 2.950779 2.419351 1.331177 \n", + " 11 H 10.569600 9.889651 10.333445 3.419825 3.051635 2.006165 \n", + " 12 H 3.616196 3.001866 3.668562 5.707073 5.203687 5.966984 \n", + " 13 O 4.889905 4.332767 5.034202 4.456762 3.919696 4.630054 \n", + " 14 H 4.973767 4.576570 5.381612 4.871619 4.357987 4.980097 \n", + " 15 Hg 6.692140 6.027618 6.592504 2.579906 1.985538 2.753441 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.003958 3.059759 3.417143 10.380896 9.907778 10.569600 3.616196 \n", + " 1 1.321642 2.417056 2.963515 9.607987 9.182377 9.889651 3.001866 \n", + " 2 1.978598 2.989966 3.533219 9.920841 9.578229 10.333445 3.668562 \n", + " 3 7.402632 6.524299 6.829618 3.480740 2.950779 3.419825 5.707073 \n", + " 4 6.837104 6.043821 6.468466 2.999755 2.419351 3.051635 5.203687 \n", + " 5 7.521187 6.823332 7.335541 1.986641 1.331177 2.006165 5.966984 \n", + " 6 0.000000 1.097352 1.725098 8.864268 8.405932 9.122418 1.790254 \n", + " 7 1.097352 0.000000 0.966264 8.294256 7.817281 8.538502 0.999698 \n", + " 8 1.725098 0.966264 0.000000 8.920009 8.414477 9.112486 1.618140 \n", + " 9 8.864268 8.294256 8.920009 0.000000 0.965496 1.552945 7.500234 \n", + " 10 8.405932 7.817281 8.414477 0.965496 0.000000 0.965207 6.962664 \n", + " 11 9.122418 8.538502 9.112486 1.552945 0.965207 0.000000 7.642571 \n", + " 12 1.790254 0.999698 1.618140 7.500234 6.962664 7.642571 0.000000 \n", + " 13 3.300780 2.628147 3.104480 6.272671 5.619394 6.206239 1.629712 \n", + " 14 3.677724 3.166060 3.561382 6.632038 5.888842 6.353759 2.208566 \n", + " 15 4.998981 4.231235 4.679289 4.535112 3.872841 4.485897 3.317105 \n", + " \n", + " 13 14 15 \n", + " 0 4.889905 4.973767 6.692140 \n", + " 1 4.332767 4.576570 6.027618 \n", + " 2 5.034202 5.381612 6.592504 \n", + " 3 4.456762 4.871619 2.579906 \n", + " 4 3.919696 4.357987 1.985538 \n", + " 5 4.630054 4.980097 2.753441 \n", + " 6 3.300780 3.677724 4.998981 \n", + " 7 2.628147 3.166060 4.231235 \n", + " 8 3.104480 3.561382 4.679289 \n", + " 9 6.272671 6.632038 4.535112 \n", + " 10 5.619394 5.888842 3.872841 \n", + " 11 6.206239 6.353759 4.485897 \n", + " 12 1.629712 2.208566 3.317105 \n", + " 13 0.000000 0.968665 1.935880 \n", + " 14 0.968665 0.000000 2.431262 \n", + " 15 1.935880 2.431262 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s22.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.034840 2.629027 2.702768 2.419084 3.073104 \n", + " 1 O 2.034840 0.000000 0.967010 1.080170 3.718692 4.050679 \n", + " 2 H 2.629027 0.967010 0.000000 1.693982 4.531494 4.820974 \n", + " 3 H 2.702768 1.080170 1.693982 0.000000 4.131972 4.505996 \n", + " 4 O 2.419084 3.718692 4.531494 4.131972 0.000000 0.966365 \n", + " 5 H 3.073104 4.050679 4.820974 4.505996 0.966365 0.000000 \n", + " 6 H 3.039947 4.258766 5.148067 4.458882 0.965741 1.533093 \n", + " 7 O 3.740704 2.420469 2.972316 1.345775 4.799597 5.194041 \n", + " 8 H 4.014811 3.033940 3.556760 2.021400 5.156315 5.684031 \n", + " 9 H 4.604566 3.049535 3.447214 2.016304 5.556816 5.841940 \n", + " 10 O 2.348691 3.440890 4.131981 3.364786 3.369109 4.280913 \n", + " 11 H 3.024190 3.585007 4.243194 3.225429 4.113492 4.969375 \n", + " 12 H 2.991905 4.329925 4.963233 4.311355 3.819310 4.777392 \n", + " 13 O 4.453986 4.230255 4.766017 3.458631 5.569678 6.307345 \n", + " 14 H 5.144047 4.982181 5.591950 4.155420 5.918200 6.634123 \n", + " 15 H 5.020805 4.747874 5.131450 4.013655 6.376488 7.141605 \n", + " 16 O 2.124083 4.112517 4.530312 4.816426 2.830246 3.524458 \n", + " 17 H 2.672853 4.635874 5.135859 5.332955 2.484401 3.061379 \n", + " 18 H 2.783848 4.622890 4.865940 5.412356 3.731472 4.336915 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.039947 3.740704 4.014811 4.604566 2.348691 3.024190 2.991905 \n", + " 1 4.258766 2.420469 3.033940 3.049535 3.440890 3.585007 4.329925 \n", + " 2 5.148067 2.972316 3.556760 3.447214 4.131981 4.243194 4.963233 \n", + " 3 4.458882 1.345775 2.021400 2.016304 3.364786 3.225429 4.311355 \n", + " 4 0.965741 4.799597 5.156315 5.556816 3.369109 4.113492 3.819310 \n", + " 5 1.533093 5.194041 5.684031 5.841940 4.280913 4.969375 4.777392 \n", + " 6 0.000000 4.874717 5.123506 5.624620 3.311323 3.973563 3.685313 \n", + " 7 4.874717 0.000000 0.975484 0.963882 3.640266 3.177280 4.563652 \n", + " 8 5.123506 0.975484 0.000000 1.581542 3.339635 2.657393 4.173249 \n", + " 9 5.624620 0.963882 1.581542 0.000000 4.596089 4.088832 5.511465 \n", + " 10 3.311323 3.640266 3.339635 4.596089 0.000000 0.980370 0.964297 \n", + " 11 3.973563 3.177280 2.657393 4.088832 0.980370 0.000000 1.557461 \n", + " 12 3.685313 4.563652 4.173249 5.511465 0.964297 1.557461 0.000000 \n", + " 13 5.364136 2.765097 1.843487 3.400331 2.789864 1.817785 3.281260 \n", + " 14 5.562869 3.275519 2.377834 3.788592 3.315817 2.378677 3.701614 \n", + " 15 6.222735 3.381437 2.436201 3.923575 3.370122 2.419996 3.723301 \n", + " 16 3.414202 5.778787 5.905287 6.680605 3.181555 4.125663 3.197150 \n", + " 17 3.050619 6.256625 6.440671 7.135700 3.715005 4.685958 3.709390 \n", + " 18 4.361941 6.455771 6.576140 7.344470 3.910055 4.811610 3.843940 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 4.453986 5.144047 5.020805 2.124083 2.672853 2.783848 \n", + " 1 4.230255 4.982181 4.747874 4.112517 4.635874 4.622890 \n", + " 2 4.766017 5.591950 5.131450 4.530312 5.135859 4.865940 \n", + " 3 3.458631 4.155420 4.013655 4.816426 5.332955 5.412356 \n", + " 4 5.569678 5.918200 6.376488 2.830246 2.484401 3.731472 \n", + " 5 6.307345 6.634123 7.141605 3.524458 3.061379 4.336915 \n", + " 6 5.364136 5.562869 6.222735 3.414202 3.050619 4.361941 \n", + " 7 2.765097 3.275519 3.381437 5.778787 6.256625 6.455771 \n", + " 8 1.843487 2.377834 2.436201 5.905287 6.440671 6.576140 \n", + " 9 3.400331 3.788592 3.923575 6.680605 7.135700 7.344470 \n", + " 10 2.789864 3.315817 3.370122 3.181555 3.715005 3.910055 \n", + " 11 1.817785 2.378677 2.419996 4.125663 4.685958 4.811610 \n", + " 12 3.281260 3.701614 3.723301 3.197150 3.709390 3.843940 \n", + " 13 0.000000 0.966282 0.965978 5.870643 6.451862 6.517769 \n", + " 14 0.966282 0.000000 1.524707 6.479854 6.971625 7.187456 \n", + " 15 0.965978 1.524707 0.000000 6.351757 7.019664 6.897846 \n", + " 16 5.870643 6.479854 6.351757 0.000000 0.969539 0.968903 \n", + " 17 6.451862 6.971625 7.019664 0.969539 0.000000 1.567914 \n", + " 18 6.517769 7.187456 6.897846 0.968903 1.567914 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s23.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.347590 2.990435 3.022754 3.740657 4.014224 \n", + " 1 O 2.347590 0.000000 0.964306 0.980503 3.641899 3.341128 \n", + " 2 H 2.990435 0.964306 0.000000 1.557704 4.565260 4.174748 \n", + " 3 H 3.022754 0.980503 1.557704 0.000000 3.178576 2.658693 \n", + " 4 O 3.740657 3.641899 4.565260 3.178576 0.000000 0.975357 \n", + " 5 H 4.014224 3.341128 4.174748 2.658693 0.975357 0.000000 \n", + " 6 H 4.604999 4.597566 5.512934 4.089924 0.963874 1.581238 \n", + " 7 O 2.418065 3.365573 3.816574 4.110175 4.799482 5.155183 \n", + " 8 H 3.072365 4.277574 4.774737 4.966215 5.193970 5.682942 \n", + " 9 H 3.038577 3.306884 3.682102 3.969310 4.874345 5.121913 \n", + " 10 O 2.035282 3.442370 4.330730 3.586142 2.421200 3.034571 \n", + " 11 H 2.702152 3.366588 4.312688 3.227168 1.347406 2.022904 \n", + " 12 H 2.629733 4.133413 4.963632 4.244265 2.972848 3.557256 \n", + " 13 O 2.124644 3.181264 3.196109 4.125205 5.779832 5.905868 \n", + " 14 H 2.673970 3.714388 3.708054 4.685483 6.258762 6.442099 \n", + " 15 H 2.784487 3.909975 3.842933 4.811148 6.456208 6.576206 \n", + " 16 O 4.451396 2.788296 3.279543 1.816009 2.766650 1.845500 \n", + " 17 H 5.018142 3.368443 3.720820 2.418199 3.382805 2.437841 \n", + " 18 H 5.141523 3.314264 3.700419 2.377116 3.276844 2.379401 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.604999 2.418065 3.072365 3.038577 2.035282 2.702152 2.629733 \n", + " 1 4.597566 3.365573 4.277574 3.306884 3.442370 3.366588 4.133413 \n", + " 2 5.512934 3.816574 4.774737 3.682102 4.330730 4.312688 4.963632 \n", + " 3 4.089924 4.110175 4.966215 3.969310 3.586142 3.227168 4.244265 \n", + " 4 0.963874 4.799482 5.193970 4.874345 2.421200 1.347406 2.972848 \n", + " 5 1.581238 5.155183 5.682942 5.121913 3.034571 2.022904 3.557256 \n", + " 6 0.000000 5.556956 5.842214 5.624344 3.050963 2.018326 3.448792 \n", + " 7 5.556956 0.000000 0.966360 0.965739 3.718893 4.131628 4.531971 \n", + " 8 5.842214 0.966360 0.000000 1.533178 4.050976 4.505669 4.821808 \n", + " 9 5.624344 0.965739 1.533178 0.000000 4.258907 4.458652 5.148355 \n", + " 10 3.050963 3.718893 4.050976 4.258907 0.000000 1.079302 0.967017 \n", + " 11 2.018326 4.131628 4.505669 4.458652 1.079302 0.000000 1.692941 \n", + " 12 3.448792 4.531971 4.821808 5.148355 0.967017 1.692941 0.000000 \n", + " 13 6.681942 2.831406 3.525399 3.415440 4.112867 4.816437 4.530194 \n", + " 14 7.138163 2.487124 3.063744 3.053438 4.637257 5.334071 5.136798 \n", + " 15 7.345257 3.732912 4.338312 4.363402 4.622624 5.411631 4.865097 \n", + " 16 3.402129 5.565602 6.303595 5.359107 4.230908 3.460562 4.766792 \n", + " 17 3.925503 6.372295 7.137863 6.217525 4.748540 4.015466 5.132275 \n", + " 18 3.789912 5.914008 6.630090 5.557662 4.982784 4.157335 5.592659 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.124644 2.673970 2.784487 4.451396 5.018142 5.141523 \n", + " 1 3.181264 3.714388 3.909975 2.788296 3.368443 3.314264 \n", + " 2 3.196109 3.708054 3.842933 3.279543 3.720820 3.700419 \n", + " 3 4.125205 4.685483 4.811148 1.816009 2.418199 2.377116 \n", + " 4 5.779832 6.258762 6.456208 2.766650 3.382805 3.276844 \n", + " 5 5.905868 6.442099 6.576206 1.845500 2.437841 2.379401 \n", + " 6 6.681942 7.138163 7.345257 3.402129 3.925503 3.789912 \n", 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6.549629 6.041353 6.795353 \n", + " 2 H 1.725009 1.096997 0.000000 7.227590 6.817667 7.642436 \n", + " 3 H 7.093984 6.549629 7.227590 0.000000 0.966984 1.706264 \n", + " 4 O 6.486089 6.041353 6.817667 0.966984 0.000000 1.090700 \n", + " 5 H 7.129525 6.795353 7.642436 1.706264 1.090700 0.000000 \n", + " 6 H 3.535707 2.990786 1.979665 8.511988 8.264450 9.192349 \n", + " 7 O 2.964423 2.417270 1.322246 8.112245 7.810267 8.699413 \n", + " 8 H 3.418719 3.060619 2.004924 8.867101 8.543343 9.401187 \n", + " 9 H 3.566784 3.165582 3.671780 4.867056 4.358356 4.985870 \n", + " 10 O 3.098394 2.626334 3.302078 4.458962 3.919363 4.627623 \n", + " 11 H 1.618071 0.999907 1.789987 5.721438 5.201189 5.949086 \n", + " 12 H 8.401932 8.229127 9.179309 3.483035 3.000678 1.986753 \n", + " 13 O 7.974072 7.761005 8.672487 2.951710 2.418773 1.330122 \n", + " 14 H 8.709237 8.486378 9.366121 3.422144 3.051338 2.005350 \n", + " 15 Hg 4.695711 4.229701 4.982328 2.580582 1.985322 2.752820 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.535707 2.964423 3.418719 3.566784 3.098394 1.618071 8.401932 \n", + " 1 2.990786 2.417270 3.060619 3.165582 2.626334 0.999907 8.229127 \n", + " 2 1.979665 1.322246 2.004924 3.671780 3.302078 1.789987 9.179309 \n", + " 3 8.511988 8.112245 8.867101 4.867056 4.458962 5.721438 3.483035 \n", + " 4 8.264450 7.810267 8.543343 4.358356 3.919363 5.201189 3.000678 \n", + " 5 9.192349 8.699413 9.401187 4.985870 4.627623 5.949086 1.986753 \n", + " 6 0.000000 0.965055 1.554860 5.369039 5.037429 3.668231 10.808758 \n", + " 7 0.965055 0.000000 0.964620 4.565873 4.336393 3.001655 10.330270 \n", + " 8 1.554860 0.964620 0.000000 4.965529 4.893963 3.616915 11.032731 \n", + " 9 5.369039 4.565873 4.965529 0.000000 0.968652 2.207627 6.641484 \n", + " 10 5.037429 4.336393 4.893963 0.968652 0.000000 1.627808 6.265861 \n", + " 11 3.668231 3.001655 3.616915 2.207627 1.627808 0.000000 7.460328 \n", + " 12 10.808758 10.330270 11.032731 6.641484 6.265861 7.460328 0.000000 \n", + " 13 10.319754 9.791131 10.457925 5.897325 5.612727 6.927336 0.965498 \n", + " 14 11.018805 10.452805 11.082979 6.360532 6.199056 7.609486 1.553116 \n", + " 15 6.555655 5.997192 6.666747 2.431601 1.935815 3.315248 4.532834 \n", + " \n", + " 13 14 15 \n", + " 0 7.974072 8.709237 4.695711 \n", + " 1 7.761005 8.486378 4.229701 \n", + " 2 8.672487 9.366121 4.982328 \n", + " 3 2.951710 3.422144 2.580582 \n", + " 4 2.418773 3.051338 1.985322 \n", + " 5 1.330122 2.005350 2.752820 \n", + " 6 10.319754 11.018805 6.555655 \n", + " 7 9.791131 10.452805 5.997192 \n", + " 8 10.457925 11.082979 6.666747 \n", + " 9 5.897325 6.360532 2.431601 \n", + " 10 5.612727 6.199056 1.935815 \n", + " 11 6.927336 7.609486 3.315248 \n", + " 12 0.965498 1.553116 4.532834 \n", + " 13 0.000000 0.965198 3.869890 \n", + " 14 0.965198 0.000000 4.482631 \n", + " 15 3.869890 4.482631 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.951579 2.628220 2.621794 3.796268 4.434681 \n", + " 1 O 1.951579 0.000000 1.039243 1.039776 2.477258 3.133890 \n", + " 2 H 2.628220 1.039243 0.000000 1.760942 1.440735 2.129140 \n", + " 3 H 2.621794 1.039776 1.760942 0.000000 3.114266 3.619484 \n", + " 4 O 3.796268 2.477258 1.440735 3.114266 0.000000 0.963792 \n", + " 5 H 4.434681 3.133890 2.129140 3.619484 0.963792 0.000000 \n", + " 6 H 4.449723 3.074239 2.102168 3.670378 0.964191 1.542100 \n", + " 7 O 1.951588 3.902529 4.522886 4.495147 5.527948 6.122915 \n", + " 8 H 2.628164 4.522810 5.045603 5.106727 5.937568 6.409034 \n", + " 9 H 2.621752 4.495102 5.106688 5.127420 6.068256 6.752241 \n", + " 10 O 3.778985 5.464104 6.056973 6.102986 6.959369 7.733409 \n", + " 11 H 4.416505 6.054037 6.529110 6.783363 7.277483 8.050387 \n", + " 12 H 4.432582 6.095043 6.777763 6.625648 7.768064 8.552220 \n", + " 13 O 3.796226 5.527857 5.937552 6.068342 6.683857 6.985825 \n", + " 14 H 4.449632 6.163769 6.651984 6.588542 7.476194 7.751060 \n", + " 15 H 4.434699 6.122886 6.409086 6.752383 6.985908 7.245447 \n", + " 16 O 3.779005 2.475892 3.115418 1.439201 4.332200 4.693787 \n", + " 17 H 4.416572 3.136085 3.627524 2.130264 4.702386 4.880479 \n", + " 18 H 4.432553 3.075702 3.675960 2.102928 4.824070 5.243869 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.449723 1.951588 2.628164 2.621752 3.778985 4.416505 4.432582 \n", + " 1 3.074239 3.902529 4.522810 4.495102 5.464104 6.054037 6.095043 \n", + " 2 2.102168 4.522886 5.045603 5.106688 6.056973 6.529110 6.777763 \n", + " 3 3.670378 4.495147 5.106727 5.127420 6.102986 6.783363 6.625648 \n", + " 4 0.964191 5.527948 5.937568 6.068256 6.959369 7.277483 7.768064 \n", + " 5 1.542100 6.122915 6.409034 6.752241 7.733409 8.050387 8.552220 \n", + " 6 0.000000 6.163925 6.652064 6.588522 7.329053 7.585524 8.137044 \n", + " 7 6.163925 0.000000 1.039230 1.039777 2.475897 3.136119 3.075667 \n", + " 8 6.652064 1.039230 0.000000 1.760916 3.115378 3.627487 3.675910 \n", + " 9 6.588522 1.039777 1.760916 0.000000 1.439204 2.130284 2.102914 \n", + " 10 7.329053 2.475897 3.115378 1.439204 0.000000 0.963759 0.964159 \n", + " 11 7.585524 3.136119 3.627487 2.130284 0.963759 0.000000 1.542615 \n", + " 12 8.137044 3.075667 3.675910 2.102914 0.964159 1.542615 0.000000 \n", + " 13 7.476258 2.477288 1.440777 3.114276 4.332174 4.702333 4.824051 \n", + " 14 8.296258 3.074235 2.102193 3.670464 4.819073 5.248279 5.151648 \n", + " 15 7.751216 3.133968 2.129215 3.619470 4.693676 4.880330 5.243733 \n", + " 16 4.818957 5.464116 6.057046 6.102974 7.049353 7.820703 7.429657 \n", + " 17 5.248163 6.054128 6.529284 6.783429 7.820774 8.601205 8.202293 \n", + " 18 5.151510 6.094969 6.777758 6.625541 7.429556 8.202120 7.750946 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.796226 4.449632 4.434699 3.779005 4.416572 4.432553 \n", + " 1 5.527857 6.163769 6.122886 2.475892 3.136085 3.075702 \n", + " 2 5.937552 6.651984 6.409086 3.115418 3.627524 3.675960 \n", + " 3 6.068342 6.588542 6.752383 1.439201 2.130264 2.102928 \n", + " 4 6.683857 7.476194 6.985908 4.332200 4.702386 4.824070 \n", + " 5 6.985825 7.751060 7.245447 4.693787 4.880479 5.243869 \n", + " 6 7.476258 8.296258 7.751216 4.818957 5.248163 5.151510 \n", + " 7 2.477288 3.074235 3.133968 5.464116 6.054128 6.094969 \n", + " 8 1.440777 2.102193 2.129215 6.057046 6.529284 6.777758 \n", + " 9 3.114276 3.670464 3.619470 6.102974 6.783429 6.625541 \n", + " 10 4.332174 4.819073 4.693676 7.049353 7.820774 7.429556 \n", + " 11 4.702333 5.248279 4.880330 7.820703 8.601205 8.202120 \n", + " 12 4.824051 5.151648 5.243733 7.429657 8.202293 7.750946 \n", + " 13 0.000000 0.964192 0.963792 6.959551 7.277784 7.768182 \n", + " 14 0.964192 0.000000 1.542092 7.329174 7.585752 8.137116 \n", + " 15 0.963792 1.542092 0.000000 7.733643 8.050752 8.552382 \n", + " 16 6.959551 7.329174 7.733643 0.000000 0.963759 0.964159 \n", + " 17 7.277784 7.585752 8.050752 0.963759 0.000000 1.542616 \n", + " 18 7.768182 8.137116 8.552382 0.964159 1.542616 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.774105 4.443394 4.397771 3.795897 4.400360 \n", + " 1 O 3.774105 0.000000 0.964015 0.963564 4.316906 4.631988 \n", + " 2 H 4.443394 0.964015 0.000000 1.539448 4.856034 5.231479 \n", + " 3 H 4.397771 0.963564 1.539448 0.000000 4.647931 4.772106 \n", + " 4 O 3.795897 4.316906 4.856034 4.647931 0.000000 0.963848 \n", + " 5 H 4.400360 4.631988 5.231479 4.772106 0.963848 0.000000 \n", + " 6 H 4.485070 4.821093 5.208339 5.203177 0.964072 1.538362 \n", + " 7 O 1.997797 5.450064 6.116607 5.994027 5.564831 6.090895 \n", + " 8 H 2.726935 6.143948 6.705401 6.774855 6.283990 6.898921 \n", + " 9 H 2.590443 5.617945 6.332595 6.045972 6.118526 6.541670 \n", + " 10 O 2.505315 5.727727 6.202266 6.464256 4.052484 4.851650 \n", + " 11 H 3.179547 6.035342 6.376393 6.846069 4.438395 5.317090 \n", + " 12 H 3.179812 6.454949 6.980500 7.129595 4.179068 4.891671 \n", + " 13 O 3.871811 7.160041 7.606271 7.867972 7.283759 7.978306 \n", + " 14 H 4.539200 8.002390 8.477331 8.697831 7.740870 8.417511 \n", + " 15 H 4.483162 7.457600 7.837616 8.168408 8.029175 8.733623 \n", + " 16 O 1.971389 2.496445 3.087647 3.168548 2.497472 3.154484 \n", + " 17 H 2.609273 1.468774 2.126824 2.165508 3.091391 3.575382 \n", + " 18 H 2.613642 3.103615 3.688203 3.605757 1.467061 2.155652 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.485070 1.997797 2.726935 2.590443 2.505315 3.179547 3.179812 \n", + " 1 4.821093 5.450064 6.143948 5.617945 5.727727 6.035342 6.454949 \n", + " 2 5.208339 6.116607 6.705401 6.332595 6.202266 6.376393 6.980500 \n", + " 3 5.203177 5.994027 6.774855 6.045972 6.464256 6.846069 7.129595 \n", + " 4 0.964072 5.564831 6.283990 6.118526 4.052484 4.438395 4.179068 \n", + " 5 1.538362 6.090895 6.898921 6.541670 4.851650 5.317090 4.891671 \n", + " 6 0.000000 6.270120 6.894776 6.897590 4.355983 4.556723 4.451720 \n", + " 7 6.270120 0.000000 1.075431 0.967416 3.109727 3.834009 3.570691 \n", + " 8 6.894776 1.075431 0.000000 1.680253 3.181543 3.718554 3.663402 \n", + " 9 6.897590 0.967416 1.680253 0.000000 4.051585 4.796058 4.466809 \n", + " 10 4.355983 3.109727 3.181543 4.051585 0.000000 0.964087 0.964100 \n", + " 11 4.556723 3.834009 3.718554 4.796058 0.964087 0.000000 1.529059 \n", + " 12 4.451720 3.570691 3.663402 4.466809 0.964100 1.529059 0.000000 \n", + " 13 7.785306 2.437555 1.362992 2.941815 3.686396 3.944514 4.131723 \n", + " 14 8.220235 3.012431 2.011084 3.488192 3.969945 4.219941 4.211663 \n", + " 15 8.529978 3.064740 2.036659 3.380908 4.526610 4.698970 5.043101 \n", + " 16 3.083628 3.967102 4.643156 4.473062 3.374277 3.764634 4.016241 \n", + " 17 3.654639 4.506332 5.213018 4.856539 4.348402 4.700778 5.028713 \n", + " 18 2.118071 4.552613 5.268381 5.084304 3.505587 3.915436 3.942896 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.871811 4.539200 4.483162 1.971389 2.609273 2.613642 \n", + " 1 7.160041 8.002390 7.457600 2.496445 1.468774 3.103615 \n", + " 2 7.606271 8.477331 7.837616 3.087647 2.126824 3.688203 \n", + " 3 7.867972 8.697831 8.168408 3.168548 2.165508 3.605757 \n", + " 4 7.283759 7.740870 8.029175 2.497472 3.091391 1.467061 \n", + " 5 7.978306 8.417511 8.733623 3.154484 3.575382 2.155652 \n", + " 6 7.785306 8.220235 8.529978 3.083628 3.654639 2.118071 \n", + " 7 2.437555 3.012431 3.064740 3.967102 4.506332 4.552613 \n", + " 8 1.362992 2.011084 2.036659 4.643156 5.213018 5.268381 \n", + " 9 2.941815 3.488192 3.380908 4.473062 4.856539 5.084304 \n", + " 10 3.686396 3.969945 4.526610 3.374277 4.348402 3.505587 \n", + " 11 3.944514 4.219941 4.698970 3.764634 4.700778 3.915436 \n", + " 12 4.131723 4.211663 5.043101 4.016241 5.028713 3.942896 \n", + " 13 0.000000 0.965183 0.965127 5.657948 6.249276 6.294097 \n", + " 14 0.965183 0.000000 1.547455 6.343775 7.012494 6.882105 \n", + " 15 0.965127 1.547455 0.000000 6.215459 6.697181 6.944095 \n", + " 16 5.657948 6.343775 6.215459 0.000000 1.031518 1.032577 \n", + " 17 6.249276 7.012494 6.697181 1.031518 0.000000 1.723464 \n", + " 18 6.294097 6.882105 6.944095 1.032577 1.723464 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s1.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 5.872624 6.538889 6.432602 5.872664 6.538949 \n", + " 1 O 5.872624 0.000000 0.963373 0.963765 11.730934 12.364454 \n", + " 2 H 6.538889 0.963373 0.000000 1.547314 12.364450 13.024791 \n", + " 3 H 6.432602 0.963765 1.547314 0.000000 12.271176 12.861850 \n", + " 4 O 5.872664 11.730934 12.364450 12.271176 0.000000 0.963373 \n", + " 5 H 6.538949 12.364454 13.024791 12.861850 0.963373 0.000000 \n", + " 6 H 6.432624 12.271175 12.861844 12.859524 0.963764 1.547304 \n", + " 7 O 4.100839 9.895548 10.590908 10.392851 2.456329 3.116062 \n", + " 8 H 4.607378 10.234415 10.974870 10.672314 2.982788 3.464196 \n", + " 9 H 4.806169 10.669661 11.340527 11.185277 1.402286 2.095437 \n", + " 10 O 4.100942 2.456281 3.116000 3.044131 9.895693 10.591059 \n", + " 11 H 4.806261 1.402205 2.095339 2.064621 10.669799 11.340671 \n", + " 12 H 4.607503 2.982783 3.464188 3.573659 10.234598 10.975053 \n", + " 13 O 1.951240 4.244246 4.792115 4.957508 7.656746 8.382350 \n", + " 14 H 3.172794 3.048227 3.664053 3.729493 8.978110 9.686172 \n", + " 15 H 2.461357 4.461809 4.844096 5.274145 7.780615 8.535487 \n", + " 16 O 1.951245 7.656675 8.382264 8.113336 4.244262 4.792147 \n", + " 17 H 3.172670 8.977940 9.685990 9.460379 3.048298 3.664142 \n", + " 18 H 2.461376 7.780581 8.535413 8.162758 4.461692 4.844010 \n", + " \n", + " 6 7 8 9 10 11 \\\n", + " 0 6.432624 4.100839 4.607378 4.806169 4.100942 4.806261 \n", + " 1 12.271175 9.895548 10.234415 10.669661 2.456281 1.402205 \n", + " 2 12.861844 10.590908 10.974870 11.340527 3.116000 2.095339 \n", + " 3 12.859524 10.392851 10.672314 11.185277 3.044131 2.064621 \n", + " 4 0.963764 2.456329 2.982788 1.402286 9.895693 10.669799 \n", + " 5 1.547304 3.116062 3.464196 2.095437 10.591059 11.340671 \n", + " 6 0.000000 3.044211 3.573733 2.064719 10.392999 11.185416 \n", + " 7 3.044211 0.000000 0.965826 1.055847 7.867056 8.728434 \n", + " 8 3.573733 0.965826 0.000000 1.675333 8.144444 9.038340 \n", + " 9 2.064719 1.055847 1.675333 0.000000 8.728440 9.550153 \n", + " 10 10.392999 7.867056 8.144444 8.728440 0.000000 1.055881 \n", + " 11 11.185416 8.728434 9.038340 9.550153 1.055881 0.000000 \n", + " 12 10.672509 8.144480 8.392222 9.038381 0.965825 1.675380 \n", + " 13 8.113394 5.894318 6.383052 6.619772 2.512533 3.146666 \n", + " 14 9.460543 7.039828 7.396207 7.855963 1.028434 1.769754 \n", + " 15 8.162749 6.240459 6.836256 6.864086 3.065032 3.524019 \n", + " 16 4.957514 2.512464 3.001734 3.146583 5.894419 6.619853 \n", + " 17 3.729569 1.028464 1.647961 1.769745 7.039821 7.855940 \n", + " 18 5.273999 3.064971 3.476180 3.523879 6.240638 6.864223 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 4.607503 1.951240 3.172794 2.461357 1.951245 3.172670 2.461376 \n", + " 1 2.982783 4.244246 3.048227 4.461809 7.656675 8.977940 7.780581 \n", + " 2 3.464188 4.792115 3.664053 4.844096 8.382264 9.685990 8.535413 \n", + " 3 3.573659 4.957508 3.729493 5.274145 8.113336 9.460379 8.162758 \n", + " 4 10.234598 7.656746 8.978110 7.780615 4.244262 3.048298 4.461692 \n", + " 5 10.975053 8.382350 9.686172 8.535487 4.792147 3.664142 4.844010 \n", + " 6 10.672509 8.113394 9.460543 8.162749 4.957514 3.729569 5.273999 \n", + " 7 8.144480 5.894318 7.039828 6.240459 2.512464 1.028464 3.064971 \n", + " 8 8.392222 6.383052 7.396207 6.836256 3.001734 1.647961 3.476180 \n", + " 9 9.038381 6.619772 7.855963 6.864086 3.146583 1.769745 3.523879 \n", + " 10 0.965825 2.512533 1.028434 3.065032 5.894419 7.039821 6.240638 \n", + " 11 1.675380 3.146666 1.769754 3.524019 6.619853 7.855940 6.864223 \n", + " 12 0.000000 3.001824 1.647932 3.476200 6.383185 7.396238 6.836464 \n", + " 13 3.001824 0.000000 1.485157 0.966457 3.901597 5.042611 4.346288 \n", + " 14 1.647932 1.485157 0.000000 2.085306 5.042731 6.198375 5.423761 \n", + " 15 3.476200 0.966457 2.085306 0.000000 4.346280 5.423583 4.794643 \n", + " 16 6.383185 3.901597 5.042731 4.346280 0.000000 1.485058 0.966457 \n", + " 17 7.396238 5.042611 6.198375 5.423583 1.485058 0.000000 2.085226 \n", + " 18 6.836464 4.346288 5.423761 4.794643 0.966457 2.085226 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s15.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964720 1.543486 3.696967 3.305103 3.696855 \n", + " 1 O 0.964720 0.000000 0.964715 3.810803 3.299616 3.810986 \n", + " 2 H 1.543486 0.964715 0.000000 4.758899 4.256734 4.759541 \n", + " 3 H 3.696967 3.810803 4.758899 0.000000 0.964708 1.543486 \n", + " 4 O 3.305103 3.299616 4.256734 0.964708 0.000000 0.964724 \n", + " 5 H 3.696855 3.810986 4.759541 1.543486 0.964724 0.000000 \n", + " 6 H 3.699229 3.307666 3.698230 3.693847 3.809689 4.758330 \n", + " 7 O 3.812815 3.300975 3.810462 3.304811 3.300225 4.257448 \n", + " 8 H 4.760737 4.257962 4.759146 3.693562 3.808757 4.756845 \n", + " 9 H 4.759481 4.256644 4.758791 4.758807 3.810714 3.696823 \n", + " 10 O 3.810940 3.299531 3.810695 4.256698 3.299583 3.305021 \n", + " 11 H 3.696751 3.304978 3.696838 4.759488 3.810942 3.696749 \n", + " 12 H 5.825866 5.301991 6.024298 3.698359 3.307746 3.699305 \n", + " 13 O 5.301347 4.664889 5.299142 3.810565 3.301008 3.812810 \n", + " 14 H 6.023243 5.298586 5.819493 4.759244 4.257994 4.760744 \n", + " 15 H 4.756753 3.808670 3.693406 5.819626 5.298648 6.023248 \n", + " 16 O 4.257348 3.300121 3.304647 5.299201 4.664893 5.301292 \n", + " 17 H 4.758227 3.809588 3.693692 6.024290 5.301929 5.825729 \n", + " 18 Hg 3.011859 2.332161 3.011329 3.011329 2.332149 3.011831 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.699229 3.812815 4.760737 4.759481 3.810940 3.696751 5.825866 \n", + " 1 3.307666 3.300975 4.257962 4.256644 3.299531 3.304978 5.301991 \n", + " 2 3.698230 3.810462 4.759146 4.758791 3.810695 3.696838 6.024298 \n", + " 3 3.693847 3.304811 3.693562 4.758807 4.256698 4.759488 3.698359 \n", + " 4 3.809689 3.300225 3.808757 3.810714 3.299583 3.810942 3.307746 \n", + " 5 4.758330 4.257448 4.756845 3.696823 3.305021 3.696749 3.699305 \n", + " 6 0.000000 0.964718 1.543405 6.024284 5.301944 5.825766 4.755783 \n", + " 7 0.964718 0.000000 0.964715 5.299182 4.664896 5.301314 3.807759 \n", + " 8 1.543405 0.964715 0.000000 5.819593 5.298640 6.023254 3.689788 \n", + " 9 6.024284 5.299182 5.819593 0.000000 0.964707 1.543476 3.693744 \n", + " 10 5.301944 4.664896 5.298640 0.964707 0.000000 0.964715 3.809644 \n", + " 11 5.825766 5.301314 6.023254 1.543476 0.964715 0.000000 4.758277 \n", + " 12 4.755783 3.807759 3.689788 3.693744 3.809644 4.758277 0.000000 \n", + " 13 4.251241 3.293717 3.295922 3.304621 3.300086 4.257307 0.964719 \n", + " 14 4.753242 3.804506 3.688128 3.693416 3.808635 4.756714 1.543407 \n", + " 15 3.689736 3.295800 3.688071 4.759121 4.257881 4.760658 4.753155 \n", + " 16 3.807706 3.293624 3.804483 3.810427 3.300883 3.812728 4.251093 \n", + " 17 4.755723 4.251145 4.753212 3.698170 3.307551 3.699139 4.755622 \n", + " 18 3.012950 2.332730 3.011402 3.011340 2.332171 3.011858 3.012976 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 5.301347 6.023243 4.756753 4.257348 4.758227 3.011859 \n", + " 1 4.664889 5.298586 3.808670 3.300121 3.809588 2.332161 \n", + " 2 5.299142 5.819493 3.693406 3.304647 3.693692 3.011329 \n", + " 3 3.810565 4.759244 5.819626 5.299201 6.024290 3.011329 \n", + " 4 3.301008 4.257994 5.298648 4.664893 5.301929 2.332149 \n", + " 5 3.812810 4.760744 6.023248 5.301292 5.825729 3.011831 \n", + " 6 4.251241 4.753242 3.689736 3.807706 4.755723 3.012950 \n", + " 7 3.293717 3.804506 3.295800 3.293624 4.251145 2.332730 \n", + " 8 3.295922 3.688128 3.688071 3.804483 4.753212 3.011402 \n", + " 9 3.304621 3.693416 4.759121 3.810427 3.698170 3.011340 \n", + " 10 3.300086 3.808635 4.257881 3.300883 3.307551 2.332171 \n", + " 11 4.257307 4.756714 4.760658 3.812728 3.699139 3.011858 \n", + " 12 0.964719 1.543407 4.753155 4.251093 4.755622 3.012976 \n", + " 13 0.000000 0.964719 3.804429 3.293559 3.807584 2.332733 \n", + " 14 0.964719 0.000000 3.687954 3.295688 3.689566 3.011390 \n", + " 15 3.804429 3.687954 0.000000 0.964724 1.543408 3.011423 \n", + " 16 3.293559 3.295688 0.964724 0.000000 0.964712 2.332748 \n", + " 17 3.807584 3.689566 1.543408 0.964712 0.000000 3.012967 \n", + " 18 2.332733 3.011390 3.011423 2.332748 3.012967 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.960012 2.945878 2.515030 1.951041 2.619018 \n", + " 1 O 1.960012 0.000000 1.253130 0.967264 3.910091 4.511643 \n", + " 2 H 2.945878 1.253130 0.000000 1.871024 4.817825 5.434843 \n", + " 3 H 2.515030 0.967264 1.871024 0.000000 4.411901 4.955299 \n", + " 4 O 1.951041 3.910091 4.817825 4.411901 0.000000 1.043064 \n", + " 5 H 2.619018 4.511643 5.434843 4.955299 1.043064 0.000000 \n", + " 6 H 2.619111 4.511696 5.434854 4.955486 1.043130 1.763741 \n", + " 7 O 3.772415 5.488433 6.381512 5.867760 2.472534 3.109538 \n", + " 8 H 4.401416 6.071189 7.049666 6.325929 3.132518 3.613312 \n", + " 9 H 4.435071 6.131064 6.909856 6.598441 3.068262 3.671156 \n", + " 10 O 3.772494 5.488547 6.381719 5.867571 2.472704 1.432593 \n", + " 11 H 4.435051 6.130945 6.909801 6.597992 3.068613 2.094283 \n", + " 12 H 4.401636 6.071576 7.050155 6.326041 3.132547 2.123383 \n", + " 13 O 3.954783 2.397106 1.144968 2.949615 5.726172 6.342944 \n", + " 14 H 4.565181 2.961724 1.794845 3.386443 6.335191 7.041437 \n", + " 15 H 4.565223 2.961758 1.794831 3.386352 6.335257 6.841346 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.619111 3.772415 4.401416 4.435071 3.772494 4.435051 4.401636 \n", + " 1 4.511696 5.488433 6.071189 6.131064 5.488547 6.130945 6.071576 \n", + " 2 5.434854 6.381512 7.049666 6.909856 6.381719 6.909801 7.050155 \n", + " 3 4.955486 5.867760 6.325929 6.598441 5.867571 6.597992 6.326041 \n", + " 4 1.043130 2.472534 3.132518 3.068262 2.472704 3.068613 3.132547 \n", + " 5 1.763741 3.109538 3.613312 3.671156 1.432593 2.094283 2.123383 \n", + " 6 0.000000 1.432360 2.123281 2.093905 3.109737 3.671717 3.613205 \n", + " 7 1.432360 0.000000 0.963963 0.964346 4.319147 4.816926 4.675256 \n", + " 8 2.123281 0.963963 0.000000 1.542955 4.675646 5.231903 4.846006 \n", + " 9 2.093905 0.964346 1.542955 0.000000 4.816431 5.156210 5.230921 \n", + " 10 3.109737 4.319147 4.675646 4.816431 0.000000 0.964344 0.963963 \n", + " 11 3.671717 4.816926 5.231903 5.156210 0.964344 0.000000 1.542915 \n", + " 12 3.613205 4.675256 4.846006 5.230921 0.963963 1.542915 0.000000 \n", + " 13 6.342902 7.257460 7.982410 7.692552 7.257786 7.692608 7.983021 \n", + " 14 6.841215 7.612436 8.318828 8.014167 8.047341 8.505992 8.766366 \n", + " 15 7.041471 8.047081 8.765878 8.505933 7.612849 8.014213 8.319621 \n", + " \n", + " 13 14 15 \n", + " 0 3.954783 4.565181 4.565223 \n", + " 1 2.397106 2.961724 2.961758 \n", + " 2 1.144968 1.794845 1.794831 \n", + " 3 2.949615 3.386443 3.386352 \n", + " 4 5.726172 6.335191 6.335257 \n", + " 5 6.342944 7.041437 6.841346 \n", + " 6 6.342902 6.841215 7.041471 \n", + " 7 7.257460 7.612436 8.047081 \n", + " 8 7.982410 8.318828 8.765878 \n", + " 9 7.692552 8.014167 8.505933 \n", + " 10 7.257786 8.047341 7.612849 \n", + " 11 7.692608 8.505992 8.014213 \n", + " 12 7.983021 8.766366 8.319621 \n", + " 13 0.000000 0.968946 0.968946 \n", + " 14 0.968946 0.000000 1.575607 \n", + " 15 0.968946 1.575607 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s21.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.342527 3.040562 2.932240 2.341854 3.040160 \n", + " 1 O 2.342527 0.000000 0.965495 0.965586 3.443784 3.716290 \n", + " 2 H 3.040562 0.965495 0.000000 1.540138 3.715694 3.935944 \n", + " 3 H 2.932240 0.965586 1.540138 0.000000 3.911662 3.986970 \n", + " 4 O 2.341854 3.443784 3.715694 3.911662 0.000000 0.965493 \n", + " 5 H 3.040160 3.716290 3.935944 3.986970 0.965493 0.000000 \n", + " 6 H 2.931408 3.911299 3.985980 4.501786 0.965581 1.540260 \n", + " 7 O 2.342092 3.006845 3.947462 2.824828 3.756409 3.954889 \n", + " 8 H 3.040310 3.732284 4.622110 3.427082 3.954653 3.971234 \n", + " 9 H 2.931906 3.481273 4.443312 3.258632 4.649087 4.905854 \n", + " 10 O 2.342619 3.756019 3.953738 4.648814 3.004779 3.945435 \n", + " 11 H 2.932168 4.648653 4.904727 5.509345 3.480159 4.442137 \n", + " 12 H 3.040707 3.953611 3.969352 4.904661 3.729980 4.619754 \n", + " 13 O 2.342569 4.670181 5.340892 5.156102 3.007201 3.732867 \n", + " 14 H 2.932465 5.156570 5.768468 5.598691 2.825608 3.428150 \n", + " 15 H 3.040400 5.340336 6.080906 5.767341 3.947768 4.622661 \n", + " 16 O 2.342335 3.005424 3.730845 3.480420 4.668930 5.340115 \n", + " 17 H 3.040472 3.945970 4.620478 4.442405 5.339556 6.080551 \n", + " 18 H 2.931916 2.822615 3.424925 3.257008 5.154407 5.766734 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.931408 2.342092 3.040310 2.931906 2.342619 2.932168 3.040707 \n", + " 1 3.911299 3.006845 3.732284 3.481273 3.756019 4.648653 3.953611 \n", + " 2 3.985980 3.947462 4.622110 4.443312 3.953738 4.904727 3.969352 \n", + " 3 4.501786 2.824828 3.427082 3.258632 4.648814 5.509345 4.904661 \n", + " 4 0.965581 3.756409 3.954653 4.649087 3.004779 3.480159 3.729980 \n", + " 5 1.540260 3.954889 3.971234 4.905854 3.945435 4.442137 4.619754 \n", + " 6 0.000000 4.649007 4.905582 5.509465 2.821689 3.256616 3.423679 \n", + " 7 4.649007 0.000000 0.965492 0.965581 4.669468 5.154723 5.340303 \n", + " 8 4.905582 0.965492 0.000000 1.540217 5.340355 5.766887 6.080942 \n", + " 9 5.509465 0.965581 1.540217 0.000000 5.155117 5.596382 5.767105 \n", + " 10 2.821689 4.669468 5.340355 5.155117 0.000000 0.965584 0.965493 \n", + " 11 3.256616 5.154723 5.766887 5.596382 0.965584 0.000000 1.540164 \n", + " 12 3.423679 5.340303 6.080942 5.767105 0.965493 1.540164 0.000000 \n", + " 13 3.481440 3.443133 3.715822 3.910496 3.005548 2.822829 3.946120 \n", + " 14 3.259275 3.911174 3.986548 4.501045 3.480235 3.256881 4.442219 \n", + " 15 4.443516 3.714471 3.935057 3.984429 3.731250 3.425497 4.620963 \n", + " 16 5.154072 3.005856 3.946574 2.823509 3.443154 3.910063 3.715383 \n", + " 17 5.765686 3.731321 4.621281 3.425882 3.715006 3.984467 3.935054 \n", + " 18 5.595713 3.480744 4.442761 3.257810 3.910689 4.500215 3.985580 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.342569 2.932465 3.040400 2.342335 3.040472 2.931916 \n", + " 1 4.670181 5.156570 5.340336 3.005424 3.945970 2.822615 \n", + " 2 5.340892 5.768468 6.080906 3.730845 4.620478 3.424925 \n", + " 3 5.156102 5.598691 5.767341 3.480420 4.442405 3.257008 \n", + " 4 3.007201 2.825608 3.947768 4.668930 5.339556 5.154407 \n", + " 5 3.732867 3.428150 4.622661 5.340115 6.080551 5.766734 \n", + " 6 3.481440 3.259275 4.443516 5.154072 5.765686 5.595713 \n", + " 7 3.443133 3.911174 3.714471 3.005856 3.731321 3.480744 \n", + " 8 3.715822 3.986548 3.935057 3.946574 4.621281 4.442761 \n", + " 9 3.910496 4.501045 3.984429 2.823509 3.425882 3.257810 \n", + " 10 3.005548 3.480235 3.731250 3.443154 3.715006 3.910689 \n", + " 11 2.822829 3.256881 3.425497 3.910063 3.984467 4.500215 \n", + " 12 3.946120 4.442219 4.620963 3.715383 3.935054 3.985580 \n", + " 13 0.000000 0.965586 0.965493 3.754835 3.952335 4.647673 \n", + " 14 0.965586 0.000000 1.540125 4.647851 4.903484 5.508618 \n", + " 15 0.965493 1.540125 0.000000 3.952178 3.967825 4.903251 \n", + " 16 3.754835 4.647851 3.952178 0.000000 0.965492 0.965583 \n", + " 17 3.952335 4.903484 3.967825 0.965492 0.000000 1.540191 \n", + " 18 4.647673 5.508618 4.903251 0.965583 1.540191 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s11.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.449746 3.050316 3.186190 3.807004 4.465532 \n", + " 1 O 2.449746 0.000000 0.966711 0.963998 2.921375 3.506973 \n", + " 2 H 3.050316 0.966711 0.000000 1.544837 2.141690 2.688479 \n", + " 3 H 3.186190 0.963998 1.544837 0.000000 3.674707 4.154710 \n", + " 4 O 3.807004 2.921375 2.141690 3.674707 0.000000 0.966093 \n", + " 5 H 4.465532 3.506973 2.688479 4.154710 0.966093 0.000000 \n", + " 6 H 4.451487 3.520437 2.700961 4.229430 0.965705 1.531173 \n", + " 7 O 3.842552 5.525040 5.501805 6.472839 4.457486 4.896618 \n", + " 8 H 4.504818 6.184703 6.133392 7.119684 4.969126 5.250580 \n", + " 9 H 4.469066 6.052236 5.978968 7.008961 4.822022 5.318635 \n", + " 10 O 1.999915 3.343937 4.246336 3.599234 5.589816 6.243057 \n", + " 11 H 2.739023 4.341430 5.233630 4.572238 6.472864 7.075763 \n", + " 12 H 2.586349 3.527578 4.438610 3.672419 5.916225 6.647582 \n", + " 13 O 1.982561 3.112843 3.107350 4.052605 2.584347 3.136091 \n", + " 14 H 2.666611 4.107883 4.079823 5.056200 3.230223 3.738544 \n", + " 15 H 2.597565 2.852689 2.546408 3.789173 1.584917 2.194139 \n", + " 16 O 3.862512 5.598066 6.472212 5.809861 7.604048 8.142540 \n", + " 17 H 4.520925 5.996749 6.889615 6.084499 8.144309 8.619722 \n", + " 18 H 4.485275 6.355845 7.223982 6.601887 8.281052 8.865812 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.451487 3.842552 4.504818 4.469066 1.999915 2.739023 2.586349 \n", + " 1 3.520437 5.525040 6.184703 6.052236 3.343937 4.341430 3.527578 \n", + " 2 2.700961 5.501805 6.133392 5.978968 4.246336 5.233630 4.438610 \n", + " 3 4.229430 6.472839 7.119684 7.008961 3.599234 4.572238 3.672419 \n", + " 4 0.965705 4.457486 4.969126 4.822022 5.589816 6.472864 5.916225 \n", + " 5 1.531173 4.896618 5.250580 5.318635 6.243057 7.075763 6.647582 \n", + " 6 0.000000 4.756616 5.318697 4.937942 6.205362 7.129655 6.423174 \n", + " 7 4.756616 0.000000 0.964074 0.963593 5.539908 5.867539 6.068340 \n", + " 8 5.318697 0.964074 0.000000 1.542270 6.175822 6.406019 6.789358 \n", + " 9 4.937942 0.963593 1.542270 0.000000 6.119217 6.484282 6.537122 \n", + " 10 6.205362 5.539908 6.175822 6.119217 0.000000 1.079217 0.967226 \n", + " 11 7.129655 5.867539 6.406019 6.484282 1.079217 0.000000 1.688155 \n", + " 12 6.423174 6.068340 6.789358 6.537122 0.967226 1.688155 0.000000 \n", + " 13 3.216365 2.479826 3.075109 3.149161 3.976607 4.607635 4.530200 \n", + " 14 3.688620 1.445835 2.107965 2.142643 4.566274 5.069206 5.110092 \n", + " 15 2.235104 3.081220 3.651451 3.599572 4.561964 5.321196 5.017384 \n", + " 16 8.303688 6.479023 6.881418 7.128857 2.429649 1.353015 2.955585 \n", + " 17 8.891381 7.279456 7.632126 7.976976 3.008126 2.008308 3.509152 \n", + " 18 8.929740 6.757264 7.160976 7.328450 3.072938 2.032749 3.421884 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.982561 2.666611 2.597565 3.862512 4.520925 4.485275 \n", + " 1 3.112843 4.107883 2.852689 5.598066 5.996749 6.355845 \n", + " 2 3.107350 4.079823 2.546408 6.472212 6.889615 7.223982 \n", + " 3 4.052605 5.056200 3.789173 5.809861 6.084499 6.601887 \n", + " 4 2.584347 3.230223 1.584917 7.604048 8.144309 8.281052 \n", + " 5 3.136091 3.738544 2.194139 8.142540 8.619722 8.865812 \n", + " 6 3.216365 3.688620 2.235104 8.303688 8.891381 8.929740 \n", + " 7 2.479826 1.445835 3.081220 6.479023 7.279456 6.757264 \n", + " 8 3.075109 2.107965 3.651451 6.881418 7.632126 7.160976 \n", + " 9 3.149161 2.142643 3.599572 7.128857 7.976976 7.328450 \n", + " 10 3.976607 4.566274 4.561964 2.429649 3.008126 3.072938 \n", + " 11 4.607635 5.069206 5.321196 1.353015 2.008308 2.032749 \n", + " 12 4.530200 5.110092 5.017384 2.955585 3.509152 3.421884 \n", + " 13 0.000000 1.037356 1.007137 5.548422 6.212613 6.117910 \n", + " 14 1.037356 0.000000 1.719145 5.880384 6.619279 6.327141 \n", + " 15 1.007137 1.719145 0.000000 6.357128 6.976417 6.971599 \n", + " 16 5.548422 5.880384 6.357128 0.000000 0.965354 0.964911 \n", + " 17 6.212613 6.619279 6.976417 0.965354 0.000000 1.550359 \n", + " 18 6.117910 6.327141 6.971599 0.964911 1.550359 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s13.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.940809 4.616270 4.550340 2.468930 3.118227 \n", + " 1 O 3.940809 0.000000 0.964457 0.964023 5.374120 5.320436 \n", + " 2 H 4.616270 0.964457 0.000000 1.542975 5.714868 5.509650 \n", + " 3 H 4.550340 0.964023 1.542975 0.000000 6.189543 6.186537 \n", + " 4 O 2.468930 5.374120 5.714868 6.189543 0.000000 0.964736 \n", + " 5 H 3.118227 5.320436 5.509650 6.186537 0.964736 0.000000 \n", + " 6 H 3.137846 6.261530 6.587873 7.086705 0.964714 1.528207 \n", + " 7 O 3.878718 6.294064 6.862096 6.793626 5.140770 5.844856 \n", + " 8 H 4.489039 6.600118 7.210202 6.984993 6.003740 6.717763 \n", + " 9 H 4.554135 7.021516 7.513530 7.580231 5.425206 6.095468 \n", + " 10 O 2.492846 5.253469 5.944304 5.673904 3.137927 3.698091 \n", + " 11 H 3.226855 5.751920 6.504196 6.035815 4.084052 4.652988 \n", + " 12 H 3.070375 5.909560 6.509826 6.403850 2.923120 3.415175 \n", + " 13 O 2.028883 2.467359 3.051465 3.124374 3.207250 3.304999 \n", + " 14 H 2.751591 1.420892 2.076837 2.108838 4.112666 4.129819 \n", + " 15 H 2.554187 2.990719 3.570432 3.468075 3.525096 3.603100 \n", + " 16 O 2.025211 5.633658 6.315066 6.181499 3.315700 4.197847 \n", + " 17 H 2.730058 5.824822 6.471607 6.353906 4.057785 4.865068 \n", + " 18 H 2.608552 6.279240 7.026774 6.741981 3.875429 4.811514 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.137846 3.878718 4.489039 4.554135 2.492846 3.226855 3.070375 \n", + " 1 6.261530 6.294064 6.600118 7.021516 5.253469 5.751920 5.909560 \n", + " 2 6.587873 6.862096 7.210202 7.513530 5.944304 6.504196 6.509826 \n", + " 3 7.086705 6.793626 6.984993 7.580231 5.673904 6.035815 6.403850 \n", + " 4 0.964714 5.140770 6.003740 5.425206 3.137927 4.084052 2.923120 \n", + " 5 1.528207 5.844856 6.717763 6.095468 3.698091 4.652988 3.415175 \n", + " 6 0.000000 5.151036 6.060848 5.282491 3.754347 4.644403 3.417262 \n", + " 7 5.151036 0.000000 0.964427 0.964790 6.009773 6.523996 6.499142 \n", + " 8 6.060848 0.964427 0.000000 1.545252 6.555099 6.971298 7.126695 \n", + " 9 5.282491 0.964790 1.545252 0.000000 6.656981 7.218597 7.047093 \n", + " 10 3.754347 6.009773 6.555099 6.656981 0.000000 0.965280 0.965111 \n", + " 11 4.644403 6.523996 6.971298 7.218597 0.965280 0.000000 1.532815 \n", + " 12 3.417262 6.499142 7.126695 7.047093 0.965111 1.532815 0.000000 \n", + " 13 4.146185 5.556377 6.091476 6.245737 2.932217 3.611787 3.486596 \n", + " 14 5.034102 5.786044 6.222396 6.509475 3.881840 4.456750 4.499897 \n", + " 15 4.469820 6.301376 6.816505 7.011493 2.515918 3.073288 3.051305 \n", + " 16 3.433620 2.453702 3.103636 3.038721 3.662578 4.193250 4.093803 \n", + " 17 4.119280 1.397331 2.081208 2.054069 4.664829 5.178991 5.133158 \n", + " 18 3.930706 2.964132 3.435711 3.533615 3.621770 3.961654 4.050813 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.028883 2.751591 2.554187 2.025211 2.730058 2.608552 \n", + " 1 2.467359 1.420892 2.990719 5.633658 5.824822 6.279240 \n", + " 2 3.051465 2.076837 3.570432 6.315066 6.471607 7.026774 \n", + " 3 3.124374 2.108838 3.468075 6.181499 6.353906 6.741981 \n", + " 4 3.207250 4.112666 3.525096 3.315700 4.057785 3.875429 \n", + " 5 3.304999 4.129819 3.603100 4.197847 4.865068 4.811514 \n", + " 6 4.146185 5.034102 4.469820 3.433620 4.119280 3.930706 \n", + " 7 5.556377 5.786044 6.301376 2.453702 1.397331 2.964132 \n", + " 8 6.091476 6.222396 6.816505 3.103636 2.081208 3.435711 \n", + " 9 6.245737 6.509475 7.011493 3.038721 2.054069 3.533615 \n", + " 10 2.932217 3.881840 2.515918 3.662578 4.664829 3.621770 \n", + " 11 3.611787 4.456750 3.073288 4.193250 5.178991 3.961654 \n", + " 12 3.486596 4.499897 3.051305 4.093803 5.133158 4.050813 \n", + " 13 0.000000 1.049014 0.968290 4.042319 4.620704 4.597054 \n", + " 14 1.049014 0.000000 1.661421 4.646737 5.047720 5.249538 \n", + " 15 0.968290 1.661421 0.000000 4.546427 5.253160 4.947984 \n", + " 16 4.042319 4.646737 4.546427 0.000000 1.058828 0.967032 \n", + " 17 4.620704 5.047720 5.253160 1.058828 0.000000 1.659198 \n", + " 18 4.597054 5.249538 4.947984 0.967032 1.659198 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s16.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.487358 3.051705 3.187957 3.812219 4.421421 \n", + " 1 O 2.487358 0.000000 0.965857 0.965882 4.487012 5.154954 \n", + " 2 H 3.051705 0.965857 0.000000 1.533803 5.015649 5.774881 \n", + " 3 H 3.187957 0.965882 1.533803 0.000000 4.394426 4.979616 \n", + " 4 O 3.812219 4.487012 5.015649 4.394426 0.000000 0.963819 \n", + " 5 H 4.421421 5.154954 5.774881 4.979616 0.963819 0.000000 \n", + " 6 H 4.499417 4.941197 5.328707 4.803479 0.964224 1.536040 \n", + " 7 O 2.444496 3.097985 2.881819 4.032221 5.503989 6.324213 \n", + " 8 H 3.094081 3.668394 3.408263 4.626565 6.421625 7.213798 \n", + " 9 H 3.102372 3.721492 3.367434 4.589919 5.624912 6.502604 \n", + " 10 O 2.095271 2.733066 3.278955 3.457066 5.658673 6.149925 \n", + " 11 H 2.755300 3.595080 4.203519 4.213609 6.179542 6.557047 \n", + " 12 H 2.609303 2.267036 2.807769 2.876400 5.835731 6.333664 \n", + " 13 O 1.999554 3.834867 4.280546 4.291370 2.511730 3.175371 \n", + " 14 H 2.627814 3.976426 4.483543 4.206964 1.488601 2.177298 \n", + " 15 H 2.619692 4.762732 5.213117 5.261990 3.097299 3.580570 \n", + " 16 O 3.783628 6.119115 6.556279 6.674035 4.329181 4.632528 \n", + " 17 H 4.396989 6.752812 7.276019 7.247695 4.645789 4.756817 \n", + " 18 H 4.464331 6.729850 7.062728 7.319104 4.881309 5.239933 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.499417 2.444496 3.094081 3.102372 2.095271 2.755300 2.609303 \n", + " 1 4.941197 3.097985 3.668394 3.721492 2.733066 3.595080 2.267036 \n", + " 2 5.328707 2.881819 3.408263 3.367434 3.278955 4.203519 2.807769 \n", + " 3 4.803479 4.032221 4.626565 4.589919 3.457066 4.213609 2.876400 \n", + " 4 0.964224 5.503989 6.421625 5.624912 5.658673 6.179542 5.835731 \n", + " 5 1.536040 6.324213 7.213798 6.502604 6.149925 6.557047 6.333664 \n", + " 6 0.000000 5.880887 6.831887 5.863865 6.393160 6.986626 6.525135 \n", + " 7 5.880887 0.000000 0.965237 0.965160 3.028406 3.867014 3.372959 \n", + " 8 6.831887 0.965237 0.000000 1.529865 3.098043 3.833406 3.458809 \n", + " 9 5.863865 0.965160 1.529865 0.000000 3.978855 4.809513 4.310493 \n", + " 10 6.393160 3.028406 3.098043 3.978855 0.000000 0.969134 0.971385 \n", + " 11 6.986626 3.867014 3.833406 4.809513 0.969134 0.000000 1.577133 \n", + " 12 6.525135 3.372959 3.458809 4.310493 0.971385 1.577133 0.000000 \n", + " 13 3.090523 3.506162 4.342609 3.664512 4.075350 4.616256 4.577060 \n", + " 14 2.134844 4.295383 5.180162 4.437388 4.646834 5.178532 5.009218 \n", + " 15 3.666124 4.014142 4.745970 4.122403 4.549468 4.946434 5.196689 \n", + " 16 4.850168 4.923818 5.490841 4.970582 5.436577 5.657496 6.221680 \n", + " 17 5.220365 5.775557 6.313097 5.888973 5.925711 6.016920 6.724753 \n", + " 18 5.254246 5.208966 5.749716 5.088768 6.140167 6.412213 6.929065 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.999554 2.627814 2.619692 3.783628 4.396989 4.464331 \n", + " 1 3.834867 3.976426 4.762732 6.119115 6.752812 6.729850 \n", + " 2 4.280546 4.483543 5.213117 6.556279 7.276019 7.062728 \n", + " 3 4.291370 4.206964 5.261990 6.674035 7.247695 7.319104 \n", + " 4 2.511730 1.488601 3.097299 4.329181 4.645789 4.881309 \n", + " 5 3.175371 2.177298 3.580570 4.632528 4.756817 5.239933 \n", + " 6 3.090523 2.134844 3.666124 4.850168 5.220365 5.254246 \n", + " 7 3.506162 4.295383 4.014142 4.923818 5.775557 5.208966 \n", + " 8 4.342609 5.180162 4.745970 5.490841 6.313097 5.749716 \n", + " 9 3.664512 4.437388 4.122403 4.970582 5.888973 5.088768 \n", + " 10 4.075350 4.646834 4.549468 5.436577 5.925711 6.140167 \n", + " 11 4.616256 5.178532 4.946434 5.657496 6.016920 6.412213 \n", + " 12 4.577060 5.009218 5.196689 6.221680 6.724753 6.929065 \n", + " 13 0.000000 1.026552 1.028087 2.506791 3.178436 3.098250 \n", + " 14 1.026552 0.000000 1.704186 3.094438 3.588930 3.687817 \n", + " 15 1.028087 1.704186 0.000000 1.482418 2.178883 2.139034 \n", + " 16 2.506791 3.094438 1.482418 0.000000 0.963594 0.963994 \n", + " 17 3.178436 3.588930 2.178883 0.963594 0.000000 1.537311 \n", + " 18 3.098250 3.687817 2.139034 0.963994 1.537311 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s9.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.838411 4.493365 4.469937 1.978158 2.573485 \n", + " 1 O 3.838411 0.000000 0.964876 0.964363 2.446629 3.072802 \n", + " 2 H 4.493365 0.964876 0.000000 1.547485 3.038977 3.633789 \n", + " 3 H 4.469937 0.964363 1.547485 0.000000 3.107213 3.580218 \n", + " 4 O 1.978158 2.446629 3.038977 3.107213 0.000000 1.011256 \n", + " 5 H 2.573485 3.072802 3.633789 3.580218 1.011256 0.000000 \n", + " 6 H 2.696402 1.389622 2.053151 2.081640 1.060166 1.759889 \n", + " 7 O 2.057239 5.576264 6.205452 6.165612 4.027052 4.598592 \n", + " 8 H 2.688142 5.840079 6.378450 6.471717 4.556250 5.247230 \n", + " 9 H 2.682688 6.109442 6.821331 6.587754 4.620276 5.116456 \n", + " 10 O 2.388154 5.572428 6.218976 6.108701 3.188446 2.949570 \n", + " 11 H 2.975200 5.563574 6.183777 6.048350 3.176848 2.640844 \n", + " 12 H 3.131898 6.512009 7.139825 7.064283 4.121727 3.882142 \n", + " 13 O 3.711839 4.477187 4.982947 4.840492 2.569046 1.569960 \n", + " 14 H 4.372065 4.915786 5.263625 5.334779 3.124063 2.177096 \n", + " 15 H 4.362420 4.795774 5.354971 4.977329 3.198434 2.214198 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.696402 2.057239 2.688142 2.682688 2.388154 2.975200 3.131898 \n", + " 1 1.389622 5.576264 5.840079 6.109442 5.572428 5.563574 6.512009 \n", + " 2 2.053151 6.205452 6.378450 6.821331 6.218976 6.183777 7.139825 \n", + " 3 2.081640 6.165612 6.471717 6.587754 6.108701 6.048350 7.064283 \n", + " 4 1.060166 4.027052 4.556250 4.620276 3.188446 3.176848 4.121727 \n", + " 5 1.759889 4.598592 5.247230 5.116456 2.949570 2.640844 3.882142 \n", + " 6 0.000000 4.636700 5.049008 5.203248 4.211133 4.189204 5.152221 \n", + " 7 4.636700 0.000000 0.971180 0.970868 3.250332 4.160592 3.484104 \n", + " 8 5.049008 0.971180 0.000000 1.568513 4.124020 5.025488 4.327318 \n", + " 9 5.203248 0.970868 1.568513 0.000000 3.549056 4.461043 3.691001 \n", + " 10 4.211133 3.250332 4.124020 3.549056 0.000000 0.967473 0.965039 \n", + " 11 4.189204 4.160592 5.025488 4.461043 0.967473 0.000000 1.549421 \n", + " 12 5.152221 3.484104 4.327318 3.691001 0.965039 1.549421 0.000000 \n", + " 13 3.272792 5.541766 6.309103 5.954562 2.959397 2.192253 3.722980 \n", + " 14 3.778475 6.193674 6.910120 6.685645 3.536275 2.725936 4.187792 \n", + " 15 3.733198 6.158614 6.971200 6.460445 3.555406 2.744214 4.283061 \n", + " \n", + " 13 14 15 \n", + " 0 3.711839 4.372065 4.362420 \n", + " 1 4.477187 4.915786 4.795774 \n", + " 2 4.982947 5.263625 5.354971 \n", + " 3 4.840492 5.334779 4.977329 \n", + " 4 2.569046 3.124063 3.198434 \n", + " 5 1.569960 2.177096 2.214198 \n", + " 6 3.272792 3.778475 3.733198 \n", + " 7 5.541766 6.193674 6.158614 \n", + " 8 6.309103 6.910120 6.971200 \n", + " 9 5.954562 6.685645 6.460445 \n", + " 10 2.959397 3.536275 3.555406 \n", + " 11 2.192253 2.725936 2.744214 \n", + " 12 3.722980 4.187792 4.283061 \n", + " 13 0.000000 0.966737 0.966357 \n", + " 14 0.966737 0.000000 1.530861 \n", + " 15 0.966357 1.530861 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s19.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.277053 2.964573 2.901210 2.204012 2.867812 \n", + " 1 O 2.277053 0.000000 0.965875 0.965839 4.173434 4.553600 \n", + " 2 H 2.964573 0.965875 0.000000 1.546638 4.558580 4.814468 \n", + " 3 H 2.901210 0.965839 1.546638 0.000000 4.972979 5.429835 \n", + " 4 O 2.204012 4.173434 4.558580 4.972979 0.000000 0.964854 \n", + " 5 H 2.867812 4.553600 4.814468 5.429835 0.964854 0.000000 \n", + " 6 H 2.805523 4.763938 5.096097 5.530572 0.986049 1.584952 \n", + " 7 O 3.929142 5.749974 6.041796 6.394073 2.693441 3.286981 \n", + " 8 H 4.618719 6.231931 6.390638 6.909051 3.317615 3.733241 \n", + " 9 H 4.549956 6.513678 6.882837 7.112353 3.259492 3.851447 \n", + " 10 O 2.295674 3.195725 4.143799 3.117505 4.136436 4.894533 \n", + " 11 H 2.945799 3.935195 4.846409 3.776546 4.590295 5.437877 \n", + " 12 H 2.929678 3.691345 4.656904 3.555422 4.646614 5.315466 \n", + " 13 O 2.294403 3.642311 4.113236 4.013245 3.037317 3.922648 \n", + " 14 H 2.878824 4.428603 4.810917 4.899837 2.874650 3.728679 \n", + " 15 H 2.984462 3.786676 4.157495 4.006448 3.931791 4.771496 \n", + " 16 O 2.341456 3.130773 3.791106 3.660533 3.277452 3.414961 \n", + " 17 H 2.986728 3.082433 3.615402 3.563055 4.027625 4.039951 \n", + " 18 H 3.031829 4.090163 4.726717 4.618621 3.443125 3.460240 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.805523 3.929142 4.618719 4.549956 2.295674 2.945799 2.929678 \n", + " 1 4.763938 5.749974 6.231931 6.513678 3.195725 3.935195 3.691345 \n", + " 2 5.096097 6.041796 6.390638 6.882837 4.143799 4.846409 4.656904 \n", + " 3 5.530572 6.394073 6.909051 7.112353 3.117505 3.776546 3.555422 \n", + " 4 0.986049 2.693441 3.317615 3.259492 4.136436 4.590295 4.646614 \n", + " 5 1.584952 3.286981 3.733241 3.851447 4.894533 5.437877 5.315466 \n", + " 6 0.000000 1.741538 2.358925 2.340733 4.616115 4.901286 5.229757 \n", + " 7 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3.642311 4.428603 3.786676 3.130773 3.082433 4.090163 \n", + " 2 4.113236 4.810917 4.157495 3.791106 3.615402 4.726717 \n", + " 3 4.013245 4.899837 4.006448 3.660533 3.563055 4.618621 \n", + " 4 3.037317 2.874650 3.931791 3.277452 4.027625 3.443125 \n", + " 5 3.922648 3.728679 4.771496 3.414961 4.039951 3.460240 \n", + " 6 2.841471 2.372124 3.701502 4.223589 4.985430 4.394369 \n", + " 7 2.771687 1.853386 3.390928 5.761488 6.543208 5.995108 \n", + " 8 3.388586 2.454253 3.839268 6.468428 7.188842 6.728297 \n", + " 9 3.354144 2.450648 3.974549 6.261122 7.107060 6.390898 \n", + " 10 3.185888 3.990693 3.604122 3.120095 3.709722 3.690469 \n", + " 11 3.152287 3.919155 3.466861 4.027958 4.663426 4.522102 \n", + " 12 4.114222 4.873097 4.568311 3.008007 3.531748 3.442921 \n", + " 13 0.000000 0.977680 0.964625 4.603994 5.274912 5.190269 \n", + " 14 0.977680 0.000000 1.566837 5.108549 5.833780 5.582468 \n", + " 15 0.964625 1.566837 0.000000 5.302020 5.882542 5.971990 \n", + " 16 4.603994 5.108549 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10.342240 \n", + " 11 H 4.458853 8.360138 9.193294 8.635324 10.303257 10.935411 \n", + " 12 H 4.550061 8.220761 9.092883 8.506008 10.234627 10.960560 \n", + " 13 O 2.555658 4.580869 5.536685 4.798514 6.785282 7.554780 \n", + " 14 H 3.230382 4.825390 5.850394 4.851713 7.168728 7.888012 \n", + " 15 H 3.233576 4.914624 5.826996 5.170751 7.025107 7.858037 \n", + " 16 O 2.010607 6.035595 6.711129 6.569309 7.668341 8.382124 \n", + " 17 H 2.692722 6.696951 7.460178 7.122159 8.501488 9.200559 \n", + " 18 H 2.599733 6.596506 7.165188 7.207002 7.999360 8.691048 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.436660 1.952972 3.224238 2.450227 3.862073 4.458853 4.550061 \n", + " 1 3.028660 2.545543 1.018548 3.071950 7.686174 8.360138 8.220761 \n", + " 2 2.039435 3.187224 1.771904 3.518579 8.535473 9.193294 9.092883 \n", + " 3 3.561214 3.019830 1.636021 3.485886 7.981577 8.635324 8.506008 \n", + " 4 0.964227 4.263404 3.029625 4.423135 9.661706 10.303257 10.234627 \n", + " 5 1.549174 4.805207 3.643988 4.801498 10.342240 10.935411 10.960560 \n", + " 6 0.000000 4.981516 3.708969 5.238502 10.177360 10.867769 10.690905 \n", + " 7 4.981516 0.000000 1.527677 0.967440 5.621934 6.161078 6.323255 \n", + " 8 3.708969 1.527677 0.000000 2.107108 6.836871 7.467694 7.432623 \n", + " 9 5.238502 0.967440 2.107108 0.000000 5.985902 6.399245 6.774048 \n", + " 10 10.177360 5.621934 6.836871 5.985902 0.000000 0.964352 0.964296 \n", + " 11 10.867769 6.161078 7.467694 6.399245 0.964352 0.000000 1.542412 \n", + " 12 10.690905 6.323255 7.432623 6.774048 0.964296 1.542412 0.000000 \n", + " 13 7.188921 3.481034 4.009126 4.307302 3.675349 4.537565 3.920574 \n", + " 14 7.607830 3.881827 4.320499 4.659911 3.921479 4.713854 4.128011 \n", + " 15 7.308319 4.164465 4.482400 5.050669 4.091588 5.020368 4.137242 \n", + " 16 8.129364 3.962259 5.165500 4.369695 2.467709 3.103398 3.049985 \n", + " 17 8.991155 4.594756 5.826234 4.982143 1.417528 2.096045 2.066018 \n", + " 18 8.445702 4.469478 5.710501 4.749122 2.959359 3.406390 3.525142 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.555658 3.230382 3.233576 2.010607 2.692722 2.599733 \n", + " 1 4.580869 4.825390 4.914624 6.035595 6.696951 6.596506 \n", + " 2 5.536685 5.850394 5.826996 6.711129 7.460178 7.165188 \n", + " 3 4.798514 4.851713 5.170751 6.569309 7.122159 7.207002 \n", + " 4 6.785282 7.168728 7.025107 7.668341 8.501488 7.999360 \n", + " 5 7.554780 7.888012 7.858037 8.382124 9.200559 8.691048 \n", + " 6 7.188921 7.607830 7.308319 8.129364 8.991155 8.445702 \n", + " 7 3.481034 3.881827 4.164465 3.962259 4.594756 4.469478 \n", + " 8 4.009126 4.320499 4.482400 5.165500 5.826234 5.710501 \n", + " 9 4.307302 4.659911 5.050669 4.369695 4.982143 4.749122 \n", + " 10 3.675349 3.921479 4.091588 2.467709 1.417528 2.959359 \n", + " 11 4.537565 4.713854 5.020368 3.103398 2.096045 3.406390 \n", + " 12 3.920574 4.128011 4.137242 3.049985 2.066018 3.525142 \n", + " 13 0.000000 0.963369 0.963544 3.031201 3.119513 3.970538 \n", + " 14 0.963369 0.000000 1.526804 3.776207 3.670911 4.739423 \n", + " 15 0.963544 1.526804 0.000000 3.433030 3.553317 4.313696 \n", + " 16 3.031201 3.776207 3.433030 0.000000 1.051039 0.967247 \n", + " 17 3.119513 3.670911 3.553317 1.051039 0.000000 1.649764 \n", + " 18 3.970538 4.739423 4.313696 0.967247 1.649764 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s6.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.570708 4.207876 4.220754 1.993418 2.737297 \n", + " 1 O 3.570708 0.000000 0.962811 0.962847 5.211798 5.704481 \n", + " 2 H 4.207876 0.962811 0.000000 1.528980 5.779858 6.342297 \n", + " 3 H 4.220754 0.962847 1.528980 0.000000 5.797060 6.152775 \n", + " 4 O 1.993418 5.211798 5.779858 5.797060 0.000000 1.069199 \n", + " 5 H 2.737297 5.704481 6.342297 6.152775 1.069199 0.000000 \n", + " 6 H 2.595943 5.604151 6.040661 6.264480 0.966375 1.684318 \n", + " 7 O 1.924699 2.617042 3.268109 3.263486 3.916887 4.601440 \n", + " 8 H 2.424434 1.625061 2.308757 2.305970 4.349642 4.970010 \n", + " 9 H 3.120230 3.676189 4.223945 4.214584 5.012407 5.715888 \n", + " 10 O 3.881861 6.520252 7.222652 6.805514 2.436784 1.369783 \n", + " 11 H 4.502650 6.765146 7.423734 6.985631 3.077576 2.048824 \n", + " 12 H 4.541772 7.378636 8.104054 7.665425 3.021752 2.026489 \n", + " 13 O 4.038000 4.582045 5.077300 5.058606 5.838459 6.537602 \n", + " 14 H 4.743985 4.939005 5.256800 5.467716 6.551839 7.336043 \n", + " 15 H 4.559162 4.852911 5.425543 5.160034 6.352810 6.938865 \n", + " 16 O 5.813584 5.714842 5.820116 6.289237 7.575433 8.441892 \n", + " 17 H 6.502906 5.900717 5.914585 6.396646 8.334135 9.186690 \n", + " 18 H 6.352272 6.595787 6.699560 7.204653 7.990193 8.881701 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.595943 1.924699 2.424434 3.120230 3.881861 4.502650 4.541772 \n", + " 1 5.604151 2.617042 1.625061 3.676189 6.520252 6.765146 7.378636 \n", + " 2 6.040661 3.268109 2.308757 4.223945 7.222652 7.423734 8.104054 \n", + " 3 6.264480 3.263486 2.305970 4.214584 6.805514 6.985631 7.665425 \n", + " 4 0.966375 3.916887 4.349642 5.012407 2.436784 3.077576 3.021752 \n", + " 5 1.684318 4.601440 4.970010 5.715888 1.369783 2.048824 2.026489 \n", + " 6 0.000000 4.465094 4.844096 5.569695 2.966072 3.447040 3.506074 \n", + " 7 4.465094 0.000000 0.998678 1.482167 5.607334 6.198061 6.256422 \n", + " 8 4.844096 0.998678 0.000000 2.161499 5.916042 6.377724 6.661936 \n", + " 9 5.569695 1.482167 2.161499 0.000000 6.696647 7.386743 7.219564 \n", + " 10 2.966072 5.607334 5.916042 6.696647 0.000000 0.964509 0.964884 \n", + " 11 3.447040 6.198061 6.377724 7.386743 0.964509 0.000000 1.548979 \n", + " 12 3.506074 6.256422 6.661936 7.219564 0.964884 1.548979 0.000000 \n", + " 13 6.395196 2.509695 3.148407 1.028978 7.491610 8.231952 7.935505 \n", + " 14 7.003771 3.155105 3.652787 1.776565 8.370375 9.096700 8.836913 \n", + " 15 7.001739 3.001308 3.533545 1.649692 7.761937 8.493868 8.179518 \n", + " 16 7.903153 4.264407 4.629126 3.058891 9.557232 10.268922 10.040056 \n", + " 17 8.664209 4.825894 5.027121 3.679535 10.284486 10.958626 10.808223 \n", + " 18 8.275987 4.968370 5.435038 3.733458 10.019037 10.773787 10.439091 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 4.038000 4.743985 4.559162 5.813584 6.502906 6.352272 \n", + " 1 4.582045 4.939005 4.852911 5.714842 5.900717 6.595787 \n", + " 2 5.077300 5.256800 5.425543 5.820116 5.914585 6.699560 \n", + " 3 5.058606 5.467716 5.160034 6.289237 6.396646 7.204653 \n", + " 4 5.838459 6.551839 6.352810 7.575433 8.334135 7.990193 \n", + " 5 6.537602 7.336043 6.938865 8.441892 9.186690 8.881701 \n", + " 6 6.395196 7.003771 7.001739 7.903153 8.664209 8.275987 \n", + " 7 2.509695 3.155105 3.001308 4.264407 4.825894 4.968370 \n", + " 8 3.148407 3.652787 3.533545 4.629126 5.027121 5.435038 \n", + " 9 1.028978 1.776565 1.649692 3.058891 3.679535 3.733458 \n", + " 10 7.491610 8.370375 7.761937 9.557232 10.284486 10.019037 \n", + " 11 8.231952 9.096700 8.493868 10.268922 10.958626 10.773787 \n", + " 12 7.935505 8.836913 8.179518 10.040056 10.808223 10.439091 \n", + " 13 0.000000 1.056374 0.965688 2.455744 3.114382 3.038514 \n", + " 14 1.056374 0.000000 1.676526 1.401291 2.092700 2.061293 \n", + " 15 0.965688 1.676526 0.000000 2.982157 3.460859 3.565754 \n", + " 16 2.455744 1.401291 2.982157 0.000000 0.963426 0.963956 \n", + " 17 3.114382 2.092700 3.460859 0.963426 0.000000 1.546565 \n", + " 18 3.038514 2.061293 3.565754 0.963956 1.546565 0.000000 }" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_ice: dict = distance_matrix.distance_matrix(coordinates_ice, (0, 0, 0))\n", + "distances_dict_water4: dict = distance_matrix.distance_matrix(\n", + " coordinates_water4, (0, 0, 0)\n", + ")\n", + "distances_dict_water5: dict = distance_matrix.distance_matrix(\n", + " coordinates_water5, (0, 0, 0)\n", + ")\n", + "distances_dict_water6: dict = distance_matrix.distance_matrix(\n", + " coordinates_water6, (0, 0, 0)\n", + ")\n", + "distances_dict_water7: dict = distance_matrix.distance_matrix(\n", + " coordinates_water7, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_hf: dict = distance_matrix.distance_matrix(coordinates_hf, (0, 0, 0))\n", + "distances_dict_pbe0: dict = distance_matrix.distance_matrix(coordinates_pbe0, (0, 0, 0))\n", + "distances_dict_camb3lyp: dict = distance_matrix.distance_matrix(\n", + " coordinates_camb3lyp, (0, 0, 0)\n", + ")\n", + "distances_dict_wb97xd: dict = distance_matrix.distance_matrix(\n", + " coordinates_wb97xd, (0, 0, 0)\n", + ")\n", + "distances_dict_b2plypd3: dict = distance_matrix.distance_matrix(\n", + " coordinates_b2plypd3, (0, 0, 0)\n", + ")\n", + "distances_dict_pbeqidh: dict = distance_matrix.distance_matrix(\n", + " coordinates_pbeqidh, (0, 0, 0)\n", + ")\n", + "distances_dict_mp2: dict = distance_matrix.distance_matrix(coordinates_mp2, (0, 0, 0))\n", + "\n", + "distances_dict_zora_nr: dict = distance_matrix.distance_matrix(\n", + " coordinates_zora_nr, (0, 0, 0)\n", + ")\n", + "distances_dict_zora_sr: dict = distance_matrix.distance_matrix(\n", + " coordinates_zora_sr, (0, 0, 0)\n", + ")\n", + "distances_dict_zora_so: dict = distance_matrix.distance_matrix(\n", + " coordinates_zora_so, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_mp2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 2, 0.01)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/wb97xd_grimmeD2/w6s17.xyz': [(7,\n", + " 17,\n", + " 16),\n", + " (10, 18, 16)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/wb97xd_grimmeD2/w5s7.xyz': [(7,\n", + " 11,\n", + " 10)],\n", + " 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13),\n", + " (13, 14, 16)]}" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"O\", \"H\", \"O\"] # proton transfer\n", + "\n", + "atoms_index_dict_ice: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_ice, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water6, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water7: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water7, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_hf: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_hf, atoms_list, grid\n", + ")\n", + "atoms_index_dict_pbe0: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_pbe0, atoms_list, grid\n", + ")\n", + "atoms_index_dict_camb3lyp: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_camb3lyp, atoms_list, grid\n", + ")\n", + "atoms_index_dict_wb97xd: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_wb97xd, atoms_list, grid\n", + ")\n", + "atoms_index_dict_b2plypd3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_b2plypd3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_pbeqidh: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_pbeqidh, atoms_list, grid\n", + ")\n", + "atoms_index_dict_mp2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_mp2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_zora_nr: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_nr, atoms_list, grid\n", + ")\n", + "atoms_index_dict_zora_sr: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_sr, atoms_list, grid\n", + ")\n", + "atoms_index_dict_zora_so: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_so, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_wb97xd\n" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "transfer_ice: list = stern_limbach(atoms_index_dict_ice, atoms_list, distances_dict_ice)\n", + "transfer_water4: list = stern_limbach(\n", + " atoms_index_dict_water4, atoms_list, distances_dict_water4\n", + ")\n", + "transfer_water5: list = stern_limbach(\n", + " atoms_index_dict_water5, atoms_list, distances_dict_water5\n", + ")\n", + "transfer_water6: list = stern_limbach(\n", + " atoms_index_dict_water6, atoms_list, distances_dict_water6\n", + ")\n", + "transfer_water7: list = stern_limbach(\n", + " atoms_index_dict_water7, atoms_list, distances_dict_water7\n", + ")\n", + "\n", + "transfer_hf: list = stern_limbach(atoms_index_dict_hf, atoms_list, distances_dict_hf)\n", + "transfer_pbe0: list = stern_limbach(\n", + " atoms_index_dict_pbe0, atoms_list, distances_dict_pbe0\n", + ")\n", + "transfer_camb3lyp: list = stern_limbach(\n", + " atoms_index_dict_camb3lyp, atoms_list, distances_dict_camb3lyp\n", + ")\n", + "transfer_wb97xd: list = stern_limbach(\n", + " atoms_index_dict_wb97xd, atoms_list, distances_dict_wb97xd\n", + ")\n", + "transfer_b2plypd3: list = stern_limbach(\n", + " atoms_index_dict_b2plypd3, atoms_list, distances_dict_b2plypd3\n", + ")\n", + "transfer_pbeqidh: list = stern_limbach(\n", + " atoms_index_dict_pbeqidh, atoms_list, distances_dict_pbeqidh\n", + ")\n", + "transfer_mp2: list = stern_limbach(atoms_index_dict_mp2, atoms_list, distances_dict_mp2)\n", + "\n", + "transfer_zora_nr: list = stern_limbach(\n", + " atoms_index_dict_zora_nr, atoms_list, distances_dict_zora_nr\n", + ")\n", + "transfer_zora_sr: list = stern_limbach(\n", + " atoms_index_dict_zora_sr, atoms_list, distances_dict_zora_sr\n", + ")\n", + "transfer_zora_so: list = stern_limbach(\n", + " atoms_index_dict_zora_so, atoms_list, distances_dict_zora_so\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'q1': [0.14968211906910212,\n", + " -0.10443211649886242,\n", + " -0.10527898691107096,\n", + " -0.008649318746002055,\n", + " 0.4393247767417406,\n", + " -0.13020881071855062,\n", + " -0.1284163488593848,\n", + " 0.19938289205413795,\n", + " -0.15440684926957438,\n", + " -0.2964622783912536,\n", + " -0.4741882633892561,\n", + " 0.15087819134720293,\n", + " -0.4743436360908872,\n", + " 0.151025900899162,\n", + " -0.18989146925123068,\n", + " -0.2157016926461055,\n", + " -0.47995108366325756,\n", + " -0.16745634407195675,\n", + " 0.13194063193602823,\n", + " 0.29201189934381633,\n", + " 0.2260410503011856,\n", + " -0.22632858272400136,\n", + " 0.2586270927883145,\n", + " 0.21209623849855985,\n", + " -0.31828278131742493,\n", + " 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2.7089998050364583,\n", + " 2.4356134969221164]}" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transfer_zora_nr" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins, endpoint=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "daa93a274bce4320b45de625fc7bad29", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\"#ff7f0e\",\n", + "# \"#2ca02c\",\n", + "# \"#d62728\",\n", + "# \"#9467bd\",\n", + "# \"#8c564b\",\n", + "# \"#e377c2\",\n", + "# \"#7f7f7f\",\n", + "# \"#bcbd22\",\n", + "# \"#17becf\",\n", + "# ]\n", + "# )\n", + "\n", + "color_palette = [to_hex(i) for i in plt.get_cmap('tab20', 18).colors]\n", + "cm = cycle(color_palette)\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "# ax.axvline(x=0.96, color='black', linestyle='-', linewidth=1)\n", + "\n", + "ax.plot(\n", + " # -np.abs(transfer_ice[\"q1\"]),\n", + " transfer_ice[\"q1\"],\n", + " transfer_ice[\"q2\"],\n", + " \"*\",\n", + " # next(linecycler),\n", + " color=\"gray\",\n", + " label=r\"ice $I_h$\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " # -np.abs(transfer_water7[\"q1\"]),\n", + " transfer_water7[\"q1\"],\n", + " transfer_water7[\"q2\"],\n", + " \"+\",\n", + " # next(linecycler),\n", + " color=\"gray\",\n", + " label=\"water cluster\",\n", + " markersize=7,\n", + " alpha=0.4,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_hf[\"q1\"],\n", + " transfer_hf[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"HF(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_pbe0[\"q1\"],\n", + " transfer_pbe0[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"PBE0(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_camb3lyp[\"q1\"],\n", + " transfer_camb3lyp[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"CAM-B3LYP(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_wb97xd[\"q1\"],\n", + " transfer_wb97xd[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"wB97xD(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_b2plypd3[\"q1\"],\n", + " transfer_b2plypd3[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"B2PLYP(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_pbeqidh[\"q1\"],\n", + " transfer_pbeqidh[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"PBEQIDH(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_mp2[\"q1\"],\n", + " transfer_mp2[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"MP2(PP)\",\n", + " markersize=4,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_zora_nr[\"q1\"],\n", + " transfer_zora_nr[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"ZORA(NR)/PBE\",\n", + " markersize=3,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_zora_sr[\"q1\"],\n", + " transfer_zora_sr[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"ZORA(SR)/PBE\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " transfer_zora_so[\"q1\"],\n", + " transfer_zora_so[\"q2\"],\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"ZORA(SO)/PBE\",\n", + " markersize=5,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "\n", + "\n", + "# plt.xlim(-0.6, 0.4)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "# - legends for the main plot\n", + "ax.set_xlabel(r\"$q_1=\\frac{1}{2}(r_1-r_2) ~[\\AA]$\", fontsize=20)\n", + "ax.set_ylabel(r\"$q_2=r_1+r_2 ~[\\AA]$\", fontsize=20)\n", + "\n", + "plt.legend(loc=\"upper center\", fontsize=12, ncol=2)\n", + "\n", + "ax.annotate(\n", + " f\"Proton Transfer\",\n", + " xy=(-0.1, 2.6),\n", + " xycoords=\"data\",\n", + " fontsize=14,\n", + ")\n", + "\n", + "ax.axvspan(-0.2, 0.2, alpha=0.3, color=\"gray\")\n", + "ax.axvline(x=0.0, color=\"black\", linestyle=\"-\", linewidth=0.7)\n", + "\n", + "ax.annotate(\n", + " # f'{atoms_list[0]}'r'$-$'f'{atoms_list[1]}'r'$\\cdots\\to$'f'{atoms_list[0]}',\n", + " r\"HO$-$H$\\cdots\\cdots$OH$_2$\",\n", + " xy=(-0.6, 2.365),\n", + " xycoords=\"data\",\n", + " fontsize=30,\n", + " # weight=\"bold\",\n", + ")\n", + "\n", + "ax.annotate(\n", + " # f'{atoms_list[0]}'r'$-$'f'{atoms_list[1]}'r'$\\cdots\\to$'f'{atoms_list[0]}',\n", + " r\"$r_1 \\qquad r_2$\",\n", + " xy=(-0.5, 2.41),\n", + " xycoords=\"data\",\n", + " fontsize=26,\n", + " weight=\"bold\",\n", + " color=\"blue\"\n", + ")\n", + "\n", + "fig.savefig(\n", + " working_dir / \"stern_limbach_gaussian.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_HOH_ADA.ipynb b/analysis_HOH_ADA.ipynb new file mode 100644 index 0000000..4732447 --- /dev/null +++ b/analysis_HOH_ADA.ipynb @@ -0,0 +1,705 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_water: Path = Path(\n", + " \"/home/edison/repositories/radial_distribution/files_xyz/others/water\"\n", + ")\n", + "\n", + "files_ice: list = glob(str(dir_water / \"ice_ih\" / \"w_iceih.xyz\"))\n", + "files_water4: list = glob(str(dir_water / \"w4\" / \"w*.xyz\"))\n", + "files_water5: list = glob(str(dir_water / \"w5\" / \"w*.xyz\"))\n", + "files_water6: list = glob(str(dir_water / \"w6\" / \"w*.xyz\"))\n", + "# files_water7: list = glob(str(dir_water / \"w7\" / \"w*.xyz\"))\n", + "files_water7: list = glob(str(dir_water / \"w*\" / \"w*.xyz\"))\n", + "\n", + "coordinates_ice: list = functions.dict_coordinates_xyz(files_ice)\n", + "coordinates_water4: list = functions.dict_coordinates_xyz(files_water4)\n", + "coordinates_water5: list = functions.dict_coordinates_xyz(files_water5)\n", + "coordinates_water6: list = functions.dict_coordinates_xyz(files_water6)\n", + "coordinates_water7: list = functions.dict_coordinates_xyz(files_water7)\n", + "\n", + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_ice: dict = distance_matrix.distance_matrix(coordinates_ice, (0, 0, 0))\n", + "distances_dict_water4: dict = distance_matrix.distance_matrix(\n", + " coordinates_water4, (0, 0, 0)\n", + ")\n", + "distances_dict_water5: dict = distance_matrix.distance_matrix(\n", + " coordinates_water5, (0, 0, 0)\n", + ")\n", + "distances_dict_water6: dict = distance_matrix.distance_matrix(\n", + " coordinates_water6, (0, 0, 0)\n", + ")\n", + "distances_dict_water7: dict = distance_matrix.distance_matrix(\n", + " coordinates_water7, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 2.7, 0.005)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': [(2, 1, 3)]}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"H\", \"O\", \"H\"]\n", + "\n", + "atoms_index_dict_ice: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_ice, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water6, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water7: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water7, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "delta_angle = 1.0\n", + "min_angle = 0\n", + "max_angle = 360\n", + "\n", + "nbins_angle = int((max_angle - min_angle) / delta_angle)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 10, 21, 37, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - angular distribution analysis (ADA); i.e., atoms_list_AB = [A, B, C]\n", + "histogram_ice: np.array = histogram.ada(\n", + " atoms_index_dict_ice, coordinates_ice, delta_angle, nbins_angle\n", + ")\n", + "histogram_water4: np.array = histogram.ada(\n", + " atoms_index_dict_water4, coordinates_water4, delta_angle, nbins_angle\n", + ")\n", + "histogram_water5: np.array = histogram.ada(\n", + " atoms_index_dict_water5, coordinates_water5, delta_angle, nbins_angle\n", + ")\n", + "histogram_water6: np.array = histogram.ada(\n", + " atoms_index_dict_water6, coordinates_water6, delta_angle, nbins_angle\n", + ")\n", + "histogram_water7: np.array = histogram.ada(\n", + " atoms_index_dict_water7, coordinates_water7, delta_angle, nbins_angle\n", + ")\n", + "\n", + "histogram_w1: np.array = histogram.ada(\n", + " atoms_index_dict_w1, coordinates_w1, delta_angle, nbins_angle\n", + ")\n", + "histogram_w2: np.array = histogram.ada(\n", + " atoms_index_dict_w2, coordinates_w2, delta_angle, nbins_angle\n", + ")\n", + "histogram_w3: np.array = histogram.ada(\n", + " atoms_index_dict_w3, coordinates_w3, delta_angle, nbins_angle\n", + ")\n", + "histogram_w4: np.array = histogram.ada(\n", + " atoms_index_dict_w4, coordinates_w4, delta_angle, nbins_angle\n", + ")\n", + "histogram_w5: np.array = histogram.ada(\n", + " atoms_index_dict_w5, coordinates_w5, delta_angle, nbins_angle\n", + ")\n", + "histogram_w6: np.array = histogram.ada(\n", + " atoms_index_dict_w6, coordinates_w6, delta_angle, nbins_angle\n", + ")\n", + "\n", + "histogram_ice\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution_angle = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_ice,\n", + " histogram_water4,\n", + " histogram_water5,\n", + " histogram_water6,\n", + " histogram_water7,\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"ada_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution_angle, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_ice_nan = histogram_ice.astype(\"float\")\n", + "histogram_water4_nan = histogram_water4.astype(\"float\")\n", + "histogram_water5_nan = histogram_water5.astype(\"float\")\n", + "histogram_water6_nan = histogram_water6.astype(\"float\")\n", + "histogram_water7_nan = histogram_water7.astype(\"float\")\n", + "\n", + "\n", + "histogram_ice_nan[histogram_ice_nan == 0] = float(\"nan\")\n", + "histogram_water4_nan[histogram_water4_nan == 0] = float(\"nan\")\n", + "histogram_water5_nan[histogram_water5_nan == 0] = float(\"nan\")\n", + "histogram_water6_nan[histogram_water6_nan == 0] = float(\"nan\")\n", + "histogram_water7_nan[histogram_water7_nan == 0] = float(\"nan\")\n", + "\n", + "histogram_w1_nan = histogram_w1.astype(\"float\")\n", + "histogram_w2_nan = histogram_w2.astype(\"float\")\n", + "histogram_w3_nan = histogram_w3.astype(\"float\")\n", + "histogram_w4_nan = histogram_w4.astype(\"float\")\n", + "histogram_w5_nan = histogram_w5.astype(\"float\")\n", + "histogram_w6_nan = histogram_w6.astype(\"float\")\n", + "\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float(\"nan\")\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float(\"nan\")\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float(\"nan\")\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float(\"nan\")\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float(\"nan\")\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "delta_angle = 3.0\n", + "min_angle = 0\n", + "max_angle = 360\n", + "\n", + "nbins_angle = int((max_angle - min_angle) / delta_angle)\n", + "\n", + "# -------------------------------------------------\n", + "grid_all = (0.8, 2.7, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin_all, rmax_all, dr_all = grid_all\n", + "nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "distribution_angle_angle_all = np.linspace(\n", + " rmin_all, rmax_all, nbins_all, endpoint=False\n", + ")\n", + "\n", + "files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_all, atoms_list, grid_all\n", + ")\n", + "histogram_all: np.array = histogram.ada(\n", + " atoms_index_dict_all, coordinates_all, delta_angle, nbins_angle\n", + ")\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y = histogram_all\n", + "smooth = make_interp_spline(x, y, k=3)\n", + "smooth_y = smooth(smooth_x)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fb7bb028bd034cdd9c580421b8f438da", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "ax.axvline(x=104.5, color=\"black\", linestyle=\"-\", linewidth=0.8)\n", + "\n", + "total_ice = sum(histogram_ice)\n", + "total_water4 = sum(histogram_water4)\n", + "total_water5 = sum(histogram_water5)\n", + "total_water6 = sum(histogram_water6)\n", + "total_water7 = sum(histogram_water7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "total_all = sum(histogram_all)\n", + "\n", + "plt.fill_between(\n", + " smooth_x,\n", + " smooth_y / total_all,\n", + " where=(smooth_y / total_all > 0),\n", + " alpha=0.3,\n", + " color=\"gray\",\n", + " label=\"distribution\",\n", + ")\n", + "# ax.plot(\n", + "# # distribution_angle_all,\n", + "# # histogram_all / total_all,\n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_ice_nan / total_ice,\n", + " \"*\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=r\"ice $I_h$\",\n", + " markersize=6,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "# ax.plot(\n", + "# distribution_angle,\n", + "# histogram_water4_nan / total_water4,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water tetramer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution_angle,\n", + "# histogram_water5_nan / total_water5,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water pentamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution_angle,\n", + "# histogram_water6_nan / total_water6,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water hexamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_water7_nan / total_water7,\n", + " \"+\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=\"water cluster\",\n", + " markersize=5,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w1_nan / total_w1,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w1\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w2\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "plt.xlim(80, 130)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(5))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(r\"Angle H$-$O$-$H [degrees]\", fontsize=16)\n", + "plt.legend(loc=\"upper left\", fontsize=10, ncol=2)\n", + "\n", + "fig.savefig(\n", + " working_dir / \"ada_HOH.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_Hg-OH2_TDA.ipynb b/analysis_Hg-OH2_TDA.ipynb new file mode 100644 index 0000000..9968b2b --- /dev/null +++ b/analysis_Hg-OH2_TDA.ipynb @@ -0,0 +1,559 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "# from brokenaxes import brokenaxes\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 2.7, 0.005)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6)]}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"Hg\", \"O\", \"H\", \"H\"]\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "delta_angle = 1.0\n", + "min_angle = 0\n", + "max_angle = 360\n", + "\n", + "nbins_angle = int((max_angle - min_angle) / delta_angle)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - torsion angle distribution analysis (TDA); i.e., atoms_list_AB = [A, B, C, D]\n", + "histogram_w1: np.array = histogram.tda(\n", + " atoms_index_dict_w1, coordinates_w1, delta_angle, nbins_angle\n", + ")\n", + "histogram_w2: np.array = histogram.tda(\n", + " atoms_index_dict_w2, coordinates_w2, delta_angle, nbins_angle\n", + ")\n", + "histogram_w3: np.array = histogram.tda(\n", + " atoms_index_dict_w3, coordinates_w3, delta_angle, nbins_angle\n", + ")\n", + "histogram_w4: np.array = histogram.tda(\n", + " atoms_index_dict_w4, coordinates_w4, delta_angle, nbins_angle\n", + ")\n", + "histogram_w5: np.array = histogram.tda(\n", + " atoms_index_dict_w5, coordinates_w5, delta_angle, nbins_angle\n", + ")\n", + "histogram_w6: np.array = histogram.tda(\n", + " atoms_index_dict_w6, coordinates_w6, delta_angle, nbins_angle\n", + ")\n", + "\n", + "histogram_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution_angle = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"tda_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution_angle, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_w1_nan = histogram_w1.astype(\"float\")\n", + "histogram_w2_nan = histogram_w2.astype(\"float\")\n", + "histogram_w3_nan = histogram_w3.astype(\"float\")\n", + "histogram_w4_nan = histogram_w4.astype(\"float\")\n", + "histogram_w5_nan = histogram_w5.astype(\"float\")\n", + "histogram_w6_nan = histogram_w6.astype(\"float\")\n", + "\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float(\"nan\")\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float(\"nan\")\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float(\"nan\")\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float(\"nan\")\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float(\"nan\")\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "delta_angle = 10.0\n", + "min_angle = 0\n", + "max_angle = 360\n", + "\n", + "nbins_angle = int((max_angle - min_angle) / delta_angle)\n", + "\n", + "# -------------------------------------------------\n", + "grid_all = (0.8, 2.7, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin_all, rmax_all, dr_all = grid_all\n", + "nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "distribution_angle_angle_all = np.linspace(\n", + " rmin_all, rmax_all, nbins_all, endpoint=False\n", + ")\n", + "\n", + "files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_all, atoms_list, grid_all\n", + ")\n", + "histogram_all: np.array = histogram.tda(\n", + " atoms_index_dict_all, coordinates_all, delta_angle, nbins_angle\n", + ")\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y = histogram_all\n", + "smooth = make_interp_spline(x, y, k=3)\n", + "smooth_y = smooth(smooth_x)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "1ed9e7b3164e441a8293cc957b42bd6e", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " Figure\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "\n", + "# ax = brokenaxes(ylims=((0, 0.25),(0.95, 1.05)), hspace=.2)\n", + "ax = fig.add_subplot(111)\n", + "ax.grid(b=True, which=\"major\")\n", + "\n", + "# - lines style in a for loop\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "lines = [\"s\", \"^\", \"v\", \"<\", \">\", \".\", \"s\", \"d\", \"o\"] # , '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "cm = cycle(\n", + " [\n", + " \"#1f77b4\",\n", + " \"#ff7f0e\",\n", + " \"#2ca02c\",\n", + " \"#d62728\",\n", + " \"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "total_all = sum(histogram_all)\n", + "\n", + "plt.fill_between(\n", + " smooth_x,\n", + " smooth_y / total_all,\n", + " where=(smooth_y / total_all > 0),\n", + " alpha=0.3,\n", + " color=\"gray\",\n", + " label=\"distribution\",\n", + ")\n", + "# ax.plot(\n", + "# # distribution_angle_all,\n", + "# # histogram_all / total_all,\n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w1_nan / total_w1,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w1\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w2\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution_angle,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "plt.xlim(120, 190)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "# ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(r\"Torsion Angle Hg$-$OH$_2$ [degrees]\", fontsize=16)\n", + "plt.legend(loc=\"best\", fontsize=10, ncol=2)\n", + "\n", + "fig.savefig(\n", + " working_dir / \"tda_HgOHH.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_Hg-OH2_TDA_gaussian.ipynb b/analysis_Hg-OH2_TDA_gaussian.ipynb new file mode 100644 index 0000000..7e617ff --- /dev/null +++ b/analysis_Hg-OH2_TDA_gaussian.ipynb @@ -0,0 +1,3637 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "# from brokenaxes import brokenaxes\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s7.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.904213 -0.008751 0.301419\n", + " 1 O -0.580352 1.054766 -1.229892\n", + " 2 H -1.534924 1.027242 -1.082449\n", + " 3 H -0.419177 1.879801 -1.707020\n", + " 4 O 0.762510 -1.470814 -1.270373\n", + " 5 H 1.459095 -2.105019 -1.496393\n", + " 6 H 0.380152 -1.147330 -2.100149\n", + " 7 O 4.332718 1.306042 1.655912\n", + " 8 H 4.871531 0.853040 2.316039\n", + " 9 H 4.762822 2.152960 1.483447\n", + " 10 O 1.896629 1.209512 1.604082\n", + " 11 H 2.964187 1.244220 1.679196\n", + " 12 H 1.489583 1.394240 2.460919\n", + " 13 O -1.075542 -1.038734 1.037088\n", + " 14 H -1.562679 -0.883323 1.856771\n", + " 15 H -1.305387 -1.937993 0.769120,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w2s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.000003 -0.016850 -0.000925\n", + " 1 O 2.001553 -0.066381 0.056437\n", + " 2 H 2.527089 0.619895 0.510238\n", + " 3 H 2.532019 -0.457418 -0.664048\n", + " 4 O -2.001446 -0.060612 -0.062220\n", + " 5 H -2.527767 0.663073 -0.452479\n", + " 6 H -2.532151 -0.517141 0.618416,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s5.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.914558 -2.643973 0.686443\n", + " 1 O 0.712683 -3.699747 2.225981\n", + " 2 H 1.108219 -4.576144 2.150752\n", + " 3 H 1.086433 -3.324779 3.032139\n", + " 4 O -2.354312 -2.679462 2.062871\n", + " 5 H -2.703210 -3.601459 2.559414\n", + " 6 H -3.084981 -2.056738 1.938110\n", + " 7 O -3.041570 -4.706514 3.181864\n", + " 8 H -3.822080 -5.202030 2.901910\n", + " 9 H -3.041314 -4.702931 4.147944\n", + " 10 O 0.431293 -2.547471 -0.779380\n", + " 11 H 0.083506 -2.467004 -1.679273\n", + " 12 H 1.400869 -2.029879 -0.684738\n", + " 13 O 2.575686 -1.467890 -0.512117\n", + " 14 H 3.363229 -1.983676 -0.728986\n", + " 15 H 2.734031 -0.567315 -0.823522,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 4.553248 1.280471 -0.422920\n", + " 1 O 4.119260 0.684815 0.203929\n", + " 2 H 4.801326 0.212251 0.700622\n", + " 3 H -0.296608 -0.830301 1.497087\n", + " 4 O -0.312248 -0.475199 0.593568\n", + " 5 H 1.376793 -0.462772 -0.178777\n", + " 6 H -4.474619 1.254645 -0.035262\n", + " 7 O -4.022756 0.481568 -0.410206\n", + " 8 H -4.690007 -0.193699 -0.613343\n", + " 9 H 3.200697 0.059203 -0.214007\n", + " 10 O 2.226213 -0.487538 -0.664174\n", + " 11 H 2.359365 -1.368638 -1.035140\n", + " 12 Hg -2.139592 -0.031947 0.172381,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.739106 0.086721 -0.794654\n", + " 1 O 3.212167 -0.112329 -0.002567\n", + " 2 H 3.740267 0.093319 0.787058\n", + " 3 H -1.273023 0.931148 0.000137\n", + " 4 O -0.736214 -0.009956 -0.000298\n", + " 5 H -1.286255 -0.944867 0.001437\n", + " 6 H -2.336354 2.459551 0.776491\n", + " 7 O -1.858854 2.140591 0.000302\n", + " 8 H -2.337500 2.458975 -0.775419\n", + " 9 H -2.360582 -2.462592 0.780160\n", + " 10 O -1.882318 -2.146724 0.003172\n", + " 11 H -2.362343 -2.463797 -0.772239\n", + " 12 Hg 1.193459 -0.029999 -0.001439,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s8.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -0.795291 2.739472 -0.484097\n", + " 1 O -0.015075 2.217487 -0.254674\n", + " 2 H 0.758086 2.750108 -0.483535\n", + " 3 H 3.005271 0.020194 -0.069280\n", + " 4 O 2.250782 0.016868 -0.672276\n", + " 5 H 2.622681 0.021911 -1.563677\n", + " 6 H -0.005329 0.765733 2.814359\n", + " 7 O 0.000065 -0.006074 2.234314\n", + " 8 H 0.005484 -0.780590 2.810739\n", + " 9 H -3.005276 -0.020002 -0.069238\n", + " 10 O -2.250818 -0.013312 -0.672245\n", + " 11 H -2.622760 -0.013812 -1.563641\n", + " 12 H -0.758132 -2.748350 -0.499285\n", + " 13 O 0.015058 -2.216947 -0.267715\n", + " 14 H 0.795274 -2.737718 -0.499870\n", + " 15 Hg 0.000002 -0.000381 -0.057147,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s12.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.635268 2.627593 -0.850686\n", + " 1 O -3.136349 2.431938 -0.049814\n", + " 2 H -3.643490 2.799844 0.682969\n", + " 3 H 2.483727 2.167442 -0.045432\n", + " 4 O 2.220496 1.252573 -0.214297\n", + " 5 H 3.033923 0.577469 -0.063366\n", + " 6 H -2.010151 -0.428693 0.152181\n", + " 7 O -1.646084 0.491913 0.323478\n", + " 8 H -2.313792 1.265788 0.132200\n", + " 9 H -0.260035 -2.216236 -0.079773\n", + " 10 O 0.539317 -1.670929 -0.076648\n", + " 11 H 1.284933 -2.278404 -0.134704\n", + " 12 H 4.562921 -0.411995 0.856171\n", + " 13 O 4.028937 -0.366730 0.052913\n", + " 14 H 4.642172 -0.468292 -0.686518\n", + " 15 H -2.780345 -2.407163 0.743545\n", + " 16 O -2.343864 -1.982952 -0.006841\n", + " 17 H -2.824921 -2.298220 -0.782747\n", + " 18 Hg 0.301316 0.754355 0.046769,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s24.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -2.29063 1.64864 0.10932\n", + " 1 O -1.60868 2.32360 0.27501\n", + " 2 H -2.03408 3.17375 0.43168\n", + " 3 H 1.15819 2.42805 -0.91201\n", + " 4 O 0.75926 1.97962 -0.15103\n", + " 5 H -0.27757 2.21866 -0.03900\n", + " 6 H -2.03314 -3.17424 -0.43142\n", + " 7 O -1.60793 -2.32398 -0.27483\n", + " 8 H -2.29006 -1.64924 -0.10902\n", + " 9 H 1.15976 -2.42734 0.91064\n", + " 10 O 0.76020 -1.97907 0.14990\n", + " 11 H -0.27649 -2.21855 0.03847\n", + " 12 H -3.86876 -0.02927 0.76048\n", + " 13 O -3.27219 -0.00030 0.00027\n", + " 14 H -3.86901 0.02843 -0.75976\n", + " 15 H 4.03113 0.51860 0.56521\n", + " 16 O 3.44541 -0.00034 0.00014\n", + " 17 H 4.03118 -0.51908 -0.56507\n", + " 18 Hg 1.02967 0.00036 -0.00060,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.74919 -0.49760 -0.08948\n", + " 1 O 5.49239 1.60097 -0.44491\n", + " 2 H 5.72283 2.43527 -0.01799\n", + " 3 H 6.34294 1.04186 -0.68442\n", + " 4 O 3.67419 0.36227 0.73370\n", + " 5 H 3.76649 0.02341 1.62861\n", + " 6 H 4.75307 1.09752 0.07118\n", + " 7 O 7.45053 0.24510 -1.09710\n", + " 8 H 8.22893 0.07578 -0.55633\n", + " 9 H 7.74369 0.24339 -2.01458\n", + " 10 O -2.27270 -1.69252 -0.58999\n", + " 11 H -3.03499 -1.94900 0.09822\n", + " 12 H -2.62338 -1.63145 -1.48854\n", + " 13 O -3.94453 -2.31995 1.08657\n", + " 14 H -4.80354 -1.89352 1.18555\n", + " 15 H -4.07345 -3.25344 1.29193\n", + " 16 O 0.80163 0.53483 0.39354\n", + " 17 H 2.72284 0.41527 0.54631\n", + " 18 H 0.50587 1.42736 0.62828,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 6.03280 0.64763 -0.04446\n", + " 1 O 5.28995 0.38671 -0.60208\n", + " 2 H 5.65815 -0.03066 -1.38923\n", + " 3 H 1.11117 1.48485 1.30014\n", + " 4 O 1.11250 1.04379 0.43805\n", + " 5 H 2.46461 1.44397 -0.29578\n", + " 6 H -2.60556 -3.84010 0.74082\n", + " 7 O -2.52949 -2.99526 1.19798\n", + " 8 H -3.02164 -3.09259 2.02027\n", + " 9 H -3.08335 -0.34841 -0.33646\n", + " 10 O -2.23690 -0.88783 -0.11961\n", + " 11 H -2.41700 -1.73300 0.43531\n", + " 12 H 3.23820 2.42134 -1.35342\n", + " 13 O 3.34234 1.83172 -0.59651\n", + " 14 H 4.20518 1.18151 -0.65200\n", + " 15 H -4.90373 0.82961 -0.16509\n", + " 16 O -4.21344 0.50956 -0.75575\n", + " 17 H -4.63448 0.38386 -1.61336\n", + " 18 Hg -0.56899 0.10264 0.21254,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s10.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.463224 -0.362657 -0.497770\n", + " 1 O 3.105859 0.950322 -0.417849\n", + " 2 H 3.578339 1.368790 0.315183\n", + " 3 H 3.692767 1.051883 -1.179693\n", + " 4 O -1.454933 -0.748648 1.637752\n", + " 5 H -2.050304 -0.135384 2.089434\n", + " 6 H -0.999537 -1.223334 2.345738\n", + " 7 O 0.607952 1.406691 -0.557613\n", + " 8 H 1.623964 1.327102 -0.568376\n", + " 9 H 0.321703 2.145837 -1.112804\n", + " 10 O 1.523837 -1.514768 -0.032813\n", + " 11 H 1.714418 -2.460344 -0.071362\n", + " 12 H 2.375407 -1.055320 -0.071699\n", + " 13 O -1.798184 -1.932784 -0.961743\n", + " 14 H -2.174954 -2.093905 -1.840119\n", + " 15 H -2.475798 -2.135484 -0.298706,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s18.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.91415 -1.64268 0.75893\n", + " 1 O 3.25114 -1.70278 0.06234\n", + " 2 H 3.68548 -2.13135 -0.68406\n", + " 3 H 2.18503 -0.73243 -0.15882\n", + " 4 O 1.36287 -0.13623 -0.35450\n", + " 5 H 1.57309 0.84109 -0.35047\n", + " 6 H -2.03491 -1.92517 2.24479\n", + " 7 O -2.08303 -1.33702 1.47624\n", + " 8 H -2.77925 -1.65420 0.87847\n", + " 9 H 2.13692 2.97386 0.19643\n", + " 10 O 1.55239 2.47672 -0.39035\n", + " 11 H 1.68258 2.87969 -1.25891\n", + " 12 H -0.43321 2.35974 0.26174\n", + " 13 O -1.10641 1.70276 0.49370\n", + " 14 H -1.76453 2.15969 1.03086\n", + " 15 H -2.69291 -0.13725 -1.58904\n", + " 16 O -2.22382 -0.90545 -1.23897\n", + " 17 H -2.22810 -1.54614 -1.96196\n", + " 18 Hg -0.42412 -0.59655 0.45172,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s9.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.33182 0.07170 -0.26049\n", + " 1 O 4.12098 1.05647 -0.06716\n", + " 2 H 4.59046 1.76062 -0.53322\n", + " 3 H 4.81092 0.49671 0.31148\n", + " 4 O -5.53296 1.00679 -0.34602\n", + " 5 H -5.97990 1.30816 -1.14557\n", + " 6 H -6.18740 1.01257 0.36158\n", + " 7 O -3.73583 -0.62877 -0.56467\n", + " 8 H -3.99663 -1.53854 -0.37118\n", + " 9 H -4.54190 0.06291 -0.43383\n", + " 10 O 1.51771 1.73285 1.22014\n", + " 11 H 1.14778 2.43748 1.76337\n", + " 12 H 2.47479 1.82089 1.30274\n", + " 13 O 2.10217 0.09571 -1.23807\n", + " 14 H 2.95198 0.44156 -0.77819\n", + " 15 H 2.32040 -0.62915 -1.83898\n", + " 16 O -1.47900 -0.03955 0.46840\n", + " 17 H -1.43873 0.02130 1.43275\n", + " 18 H -2.85519 -0.39341 -0.11548,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.090607 -0.159300 0.002895\n", + " 1 O -1.806432 -0.959823 0.078324\n", + " 2 H -2.010761 -1.904880 -0.024412\n", + " 3 H -2.568224 -0.435899 -0.220669\n", + " 4 O 2.121115 0.116531 -0.081348\n", + " 5 H 2.748802 -0.626709 -0.072363\n", + " 6 H 2.554998 0.891862 0.313658\n", + " 7 O -0.971061 1.914138 -0.014111\n", + " 8 H -0.990619 2.537018 -0.755299\n", + " 9 H -1.230948 2.428100 0.764401,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.458684 -2.897251 -0.161180\n", + " 1 O 3.173303 -2.160703 0.401070\n", + " 2 H 3.953371 -1.754954 0.809606\n", + " 3 H -3.247714 -0.161504 0.002070\n", + " 4 O -2.112353 0.171974 0.498330\n", + " 5 H -2.171532 0.802920 1.229718\n", + " 6 H -4.744937 0.201972 -0.876991\n", + " 7 O -4.213042 -0.497148 -0.466639\n", + " 8 H -4.785111 -1.037428 0.099864\n", + " 9 H 1.886096 -0.119936 -1.306017\n", + " 10 O 1.562164 -0.660552 -0.571629\n", + " 11 H 2.444923 -1.446147 -0.071511\n", + " 12 Hg -0.268946 -0.216956 -0.036806,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s14.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.433859 -0.186385 -0.209346\n", + " 1 O -2.910003 -1.104610 1.549563\n", + " 2 H -3.650028 -1.659911 1.269801\n", + " 3 H -3.091479 -0.901530 2.476635\n", + " 4 O 1.842448 1.211620 -0.743795\n", + " 5 H 1.616967 2.232129 -0.748408\n", + " 6 H 2.744465 1.085772 -0.418988\n", + " 7 O -0.574432 -1.777392 0.689620\n", + " 8 H -1.469621 -1.587443 1.114669\n", + " 9 H -0.093612 -2.422219 1.226374\n", + " 10 O 0.345511 -1.127734 -2.402759\n", + " 11 H -0.202976 -1.864035 -2.697512\n", + " 12 H 0.960765 -0.959967 -3.126236\n", + " 13 O -1.713337 0.808290 -0.268561\n", + " 14 H -2.444457 0.488336 0.279291\n", + " 15 H -2.066289 1.506610 -0.831180\n", + " 16 O 1.220810 3.605257 -0.851049\n", + " 17 H 1.348709 4.228884 -0.126465\n", + " 18 H 1.427643 4.091021 -1.658736,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s6.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 1.818124 -1.374399 -0.709468\n", + " 1 O -2.184374 -0.470873 -1.128476\n", + " 2 H -2.575883 -0.740098 -1.969631\n", + " 3 H -2.921189 -0.326435 -0.345636\n", + " 4 O -3.771707 -0.065304 0.661118\n", + " 5 H -4.547713 -0.611736 0.831690\n", + " 6 H -4.022513 0.848702 0.841712\n", + " 7 O 0.120501 -4.362084 -0.022064\n", + " 8 H -0.058347 -4.730559 0.849823\n", + " 9 H -0.033924 -5.086793 -0.637701\n", + " 10 O -0.042367 -1.836380 -0.627975\n", + " 11 H -0.077449 -2.812408 -0.394373\n", + " 12 H -1.378583 -1.032517 -0.908295\n", + " 13 O 3.766436 -0.773938 -0.820795\n", + " 14 H 4.335567 -1.031779 -1.562884\n", + " 15 H 4.318311 -0.689459 -0.027494,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 2.600000e-09 0.010739\n", + " 1 O 1.821376 8.000000e-08 -0.090165\n", + " 2 H 2.325945 -7.989195e-01 0.177310\n", + " 3 H 2.325945 7.989197e-01 0.177310,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 1.465191 -0.168688 -2.470133\n", + " 1 O 1.551722 -0.160537 -1.505854\n", + " 2 H 2.382882 -0.609382 -1.294379\n", + " 3 H -2.699888 -0.951794 0.509565\n", + " 4 O -2.229523 -0.365731 -0.102092\n", + " 5 H -2.755488 -0.317063 -0.914515\n", + " 6 H 1.269790 -1.850941 1.828448\n", + " 7 O 1.251734 -0.933711 1.520616\n", + " 8 H 1.606850 -0.396922 2.243261\n", + " 9 H -0.393270 2.668594 0.981053\n", + " 10 O 0.244152 2.088409 0.542415\n", + " 11 H 0.900006 2.669523 0.133525\n", + " 12 Hg -0.104009 -0.075885 -0.058219,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.382557 -0.044085 -0.000312\n", + " 1 O 2.286461 0.639488 -0.000193\n", + " 2 H 2.850681 0.582739 -0.790182\n", + " 3 H 2.850188 0.583476 0.790200\n", + " 4 O -1.480339 -0.592168 -0.000189\n", + " 5 H -2.789681 0.086364 0.000164\n", + " 6 H -1.539437 -1.561275 -0.000488\n", + " 7 O -3.685766 0.615080 0.000118\n", + " 8 H -4.226512 0.481465 -0.797912\n", + " 9 H -4.226965 0.480951 0.797755,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.213891 0.985545 1.772239\n", + " 1 O 1.652717 0.573054 1.252535\n", + " 2 H 2.239996 0.982438 0.425480\n", + " 3 H 1.906127 -0.323837 1.518491\n", + " 4 O -2.046423 1.548248 2.241517\n", + " 5 H -2.589364 2.564087 2.049059\n", + " 6 H -2.552267 0.929653 2.785081\n", + " 7 O 0.290677 -1.317859 2.856418\n", + " 8 H 0.555839 -1.459083 3.774303\n", + " 9 H -0.056865 -2.174070 2.576034\n", + " 10 O -3.101371 3.644887 1.798776\n", + " 11 H -3.868079 3.651177 1.209145\n", + " 12 H -3.287833 4.238993 2.538836\n", + " 13 O 2.927684 1.574390 -0.538113\n", + " 14 H 3.746119 2.034338 -0.312261\n", + " 15 H 3.072095 1.136757 -1.386197,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.740815 -0.166542 0.000527\n", + " 1 O 1.305983 2.643994 -0.000036\n", + " 2 H 1.567043 3.158573 0.774397\n", + " 3 H 1.566940 3.158697 -0.774419\n", + " 4 O 1.184355 0.184104 -0.000069\n", + " 5 H 2.325330 -0.826148 -0.000177\n", + " 6 H 1.277519 1.250731 -0.000144\n", + " 7 O 3.058172 -1.547673 -0.000015\n", + " 8 H 3.614001 -1.548166 -0.799942\n", + " 9 H 3.613971 -1.547842 0.799936,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.30295 0.54243 0.67902\n", + " 1 O -2.67596 -0.16059 0.27283\n", + " 2 H -3.12195 -0.75994 -0.43074\n", + " 3 H 3.71838 0.86623 1.59224\n", + " 4 O 3.38597 0.25586 0.92017\n", + " 5 H 4.18691 -0.16199 0.33989\n", + " 6 H -0.24813 1.43642 -1.17337\n", + " 7 O -0.24681 0.78986 -0.45203\n", + " 8 H -1.81245 0.21164 -0.02258\n", + " 9 H -3.96272 -2.60309 -1.14342\n", + " 10 O -3.70723 -1.71151 -1.40213\n", + " 11 H -4.26694 -1.47642 -2.14892\n", + " 12 H -4.77017 2.14393 0.93780\n", + " 13 O -4.15792 1.53801 1.36708\n", + " 14 H -4.51181 1.37620 2.24785\n", + " 15 H 5.52425 -1.60273 -0.11804\n", + " 16 O 5.12842 -0.77866 -0.42698\n", + " 17 H 5.82673 -0.28093 -0.86882\n", + " 18 Hg 1.56140 0.57914 0.18935,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -5.524051 -0.895808 0.475382\n", + " 1 O -4.854601 -0.714706 -0.195096\n", + " 2 H -5.274591 -0.820318 -1.057521\n", + " 3 H 3.342234 1.500760 -0.108671\n", + " 4 O 2.864612 0.688621 -0.326560\n", + " 5 H 3.544355 -0.139917 -0.526430\n", + " 6 H -3.951276 0.236575 -0.034455\n", + " 7 O -3.161064 0.995523 0.026738\n", + " 8 H -3.459104 1.826286 0.420021\n", + " 9 H 4.611510 -1.305366 -1.730443\n", + " 10 O 4.293323 -1.199103 -0.825099\n", + " 11 H 5.004923 -1.484824 -0.238914\n", + " 12 H -2.285563 0.712207 0.417413\n", + " 13 O -0.811024 0.305806 0.980027\n", + " 14 H -0.820717 -0.076229 1.870121\n", + " 15 Hg 1.023597 0.484591 0.388560,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s22.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.70393 -0.54642 -0.15373\n", + " 1 O -0.58175 -1.97096 0.52324\n", + " 2 H -0.56651 -2.83520 0.08969\n", + " 3 H -1.59085 -1.65592 0.74513\n", + " 4 O 1.57098 0.85796 1.61486\n", + " 5 H 1.97075 0.52961 2.43109\n", + " 6 H 1.14083 1.68642 1.86241\n", + " 7 O -2.77211 -1.12001 1.10365\n", + " 8 H -3.25992 -0.54595 0.48392\n", + " 9 H -3.40092 -1.62359 1.63287\n", + " 10 O -0.72635 1.19065 -0.82696\n", + " 11 H -1.70503 1.14135 -0.85663\n", + " 12 H -0.46928 1.88324 -1.44672\n", + " 13 O -3.49176 0.84224 -0.70672\n", + " 14 H -3.97888 1.57676 -0.31062\n", + " 15 H -3.97952 0.64376 -1.51654\n", + " 16 O 2.35295 0.42869 -1.07113\n", + " 17 H 2.95489 0.86443 -0.44839\n", + " 18 H 2.88670 0.03864 -1.77947,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s23.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.585401 -0.196527 -0.248645\n", + " 1 O -0.786191 1.681191 0.073988\n", + " 2 H -0.499333 2.586044 -0.095835\n", + " 3 H -1.765082 1.685281 0.017945\n", + " 4 O -2.928431 -1.231729 0.508886\n", + " 5 H -3.388936 -0.403973 0.276341\n", + " 6 H -3.580541 -1.916247 0.696613\n", + " 7 O 1.449195 0.057122 1.995584\n", + " 8 H 1.824131 -0.659435 2.524564\n", + " 9 H 1.033753 0.649657 2.635086\n", + " 10 O -0.747132 -1.725523 -0.418642\n", + " 11 H -1.751982 -1.540640 -0.070807\n", + " 12 H -0.744120 -2.238025 -1.238676\n", + " 13 O 2.276929 1.060256 -0.519459\n", + " 14 H 2.877195 1.091023 0.241260\n", + " 15 H 2.814696 1.078074 -1.325214\n", + " 16 O -3.559698 1.409773 -0.018678\n", + " 17 H -4.034966 1.677561 -0.815872\n", + " 18 H -4.036711 1.846110 0.699498,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.091110 1.774449 -0.551765\n", + " 1 O -2.961238 0.817046 -0.538799\n", + " 2 H -3.877099 0.257944 -0.310746\n", + " 3 H 3.061446 -1.756575 -0.501440\n", + " 4 O 2.854601 -0.814615 -0.430850\n", + " 5 H 3.750843 -0.211529 -0.280308\n", + " 6 H -5.398879 -0.887569 -0.850245\n", + " 7 O -4.941965 -0.495853 -0.095844\n", + " 8 H -5.613294 -0.252069 0.552523\n", + " 9 H -0.804912 0.216858 1.699713\n", + " 10 O -0.744652 0.211224 0.732954\n", + " 11 H -2.139930 0.577896 -0.021040\n", + " 12 H 5.258526 0.913606 -0.919176\n", + " 13 O 4.786418 0.610216 -0.133520\n", + " 14 H 5.446874 0.458652 0.553819\n", + " 15 Hg 1.044511 -0.313990 0.212932,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s5.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.000047 0.109967 0.000775\n", + " 1 O -1.943126 0.145411 0.178212\n", + " 2 H -2.431656 -0.627877 0.671557\n", + " 3 H -2.508504 0.661137 -0.525713\n", + " 4 O -3.009793 -1.693878 1.449449\n", + " 5 H -3.463250 -2.449594 1.059367\n", + " 6 H -3.464368 -1.505383 2.278603\n", + " 7 O 1.943250 0.145113 -0.176494\n", + " 8 H 2.431182 -0.625772 -0.674147\n", + " 9 H 2.508939 0.656217 0.530545\n", + " 10 O 3.189958 1.467263 1.505083\n", + " 11 H 3.657015 1.107269 2.267377\n", + " 12 H 3.675584 2.256307 1.238286\n", + " 13 O 3.008545 -1.687843 -1.458045\n", + " 14 H 3.463147 -1.495017 -2.286188\n", + " 15 H 3.461530 -2.446054 -1.072279\n", + " 16 O -3.188927 1.478433 -1.495429\n", + " 17 H -3.656373 1.123259 -2.259744\n", + " 18 H -3.673847 2.266334 -1.224014,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s10.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.10449 0.27043 -0.12521\n", + " 1 O 2.94298 2.45467 0.30594\n", + " 2 H 3.26698 2.89180 1.10172\n", + " 3 H 3.52729 2.73436 -0.40737\n", + " 4 O 3.02985 -1.85717 0.11576\n", + " 5 H 3.61110 -2.03167 -0.63304\n", + " 6 H 3.42747 -2.30886 0.86896\n", + " 7 O -1.97426 0.39080 -0.81851\n", + " 8 H -2.82806 0.39999 -0.16468\n", + " 9 H -2.12943 0.95629 -1.58795\n", + " 10 O -0.87738 -1.72186 1.18247\n", + " 11 H -0.91863 -1.80465 2.14211\n", + " 12 H -1.01357 -2.61645 0.84983\n", + " 13 O -3.88886 0.34634 0.68947\n", + " 14 H -4.54901 -0.34593 0.56085\n", + " 15 H -4.37169 1.14501 0.93538\n", + " 16 O 1.76527 0.26201 0.49953\n", + " 17 H 2.30312 1.13518 0.38853\n", + " 18 H 2.32458 -0.58669 0.31761,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.000095 -0.106079 0.003892\n", + " 1 O 5.854318 -0.393233 0.365965\n", + " 2 H 6.505820 -0.700211 -0.273878\n", + " 3 H 6.317042 -0.283293 1.204203\n", + " 4 O -5.854733 -0.399350 -0.350200\n", + " 5 H -6.506419 -0.688561 0.297681\n", + " 6 H -6.317396 -0.311826 -1.191107\n", + " 7 O -3.931238 1.056244 0.113445\n", + " 8 H -4.135608 1.807394 0.685133\n", + " 9 H -4.774793 0.440972 -0.043615\n", + " 10 O 3.931835 1.050580 -0.136804\n", + " 11 H 4.775021 0.439202 0.036799\n", + " 12 H 4.136677 1.785974 -0.728458\n", + " 13 O 1.782577 -0.075615 -0.788881\n", + " 14 H 3.070968 0.566532 -0.423654\n", + " 15 H 1.829454 -0.685100 -1.537459\n", + " 16 O -1.782733 -0.053301 0.795583\n", + " 17 H -3.070642 0.579521 0.413192\n", + " 18 H -1.830033 -0.642618 1.560114,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s15.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -1.09653 2.59570 -1.06939\n", + " 1 O -1.08850 1.64706 -1.24461\n", + " 2 H -1.61937 1.51473 -2.03918\n", + " 3 H 1.61965 2.12366 1.39376\n", + " 4 O 0.79189 1.63361 1.46674\n", + " 5 H 0.35885 1.95276 2.26756\n", + " 6 H 2.02180 0.86783 -2.05670\n", + " 7 O 1.90484 0.25751 -1.31879\n", + " 8 H 2.73706 -0.22247 -1.23102\n", + " 9 H -2.01909 -0.87011 2.05946\n", + " 10 O -1.90643 -0.25981 1.32088\n", + " 11 H -2.73949 0.21943 1.23712\n", + " 12 H 1.61727 -1.51829 2.03723\n", + " 13 O 1.08715 -1.64644 1.24147\n", + " 14 H 1.09158 -2.59469 1.06403\n", + " 15 H -0.35378 -1.94761 -2.26662\n", + " 16 O -0.78889 -1.63200 -1.46552\n", + " 17 H -1.61665 -2.12267 -1.39678\n", + " 18 Hg -0.00152 0.00221 0.00115,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.358532 -2.383665 1.248423\n", + " 1 O 1.778630 -3.417608 0.378980\n", + " 2 H 2.043565 -3.617024 -0.829481\n", + " 3 H 2.384508 -3.852214 0.995122\n", + " 4 O -1.085048 -1.333344 2.035483\n", + " 5 H -0.861829 -0.403607 2.452310\n", + " 6 H -1.896449 -1.831986 2.461046\n", + " 7 O -3.011426 -2.599093 2.930117\n", + " 8 H -3.159445 -2.811790 3.858597\n", + " 9 H -3.884269 -2.485728 2.536090\n", + " 10 O -0.477860 0.898853 2.908916\n", + " 11 H -0.859329 1.689866 2.510498\n", + " 12 H -0.317246 1.113146 3.834932\n", + " 13 O 2.233641 -3.761780 -1.949244\n", + " 14 H 2.136654 -4.666379 -2.282636\n", + " 15 H 3.060857 -3.390321 -2.290694,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s21.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.088535 0.075710 0.080844\n", + " 1 O -1.110178 1.812787 -0.935563\n", + " 2 H -1.730419 1.765961 -1.674000\n", + " 3 H -1.404001 2.554941 -0.392210\n", + " 4 O -1.806389 -1.225386 0.528828\n", + " 5 H -2.608305 -0.978974 1.006728\n", + " 6 H -2.079177 -1.887525 -0.118865\n", + " 7 O 0.202651 1.697133 1.767070\n", + " 8 H -0.145778 1.657574 2.666629\n", + " 9 H 0.979803 2.268493 1.810994\n", + " 10 O 0.342289 -1.598189 -1.538271\n", + " 11 H 0.903992 -2.357518 -1.337619\n", + " 12 H 0.352085 -1.510787 -2.499751\n", + " 13 O 1.050224 -1.617834 1.382647\n", + " 14 H 0.470616 -2.203019 1.886600\n", + " 15 H 1.891639 -1.609934 1.856078\n", + " 16 O 1.856972 1.384502 -0.723042\n", + " 17 H 2.775690 1.129400 -0.874881\n", + " 18 H 1.666541 2.077517 -1.367881,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s11.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.283345 -0.018428 -0.950445\n", + " 1 O 1.041965 -0.381550 1.350401\n", + " 2 H 0.502089 -0.901250 1.961120\n", + " 3 H 1.879804 -0.221333 1.799456\n", + " 4 O -1.343173 -1.984925 1.874553\n", + " 5 H -1.260602 -2.928618 2.064187\n", + " 6 H -2.035913 -1.672258 2.470319\n", + " 7 O -3.151897 -1.267175 -2.135751\n", + " 8 H -3.354776 -2.044432 -2.668808\n", + " 9 H -3.990630 -0.818036 -1.983068\n", + " 10 O 1.762787 1.209454 -1.501096\n", + " 11 H 2.125198 1.269714 -2.515856\n", + " 12 H 1.800471 2.072970 -1.066995\n", + " 13 O -1.196141 -1.293839 -0.611334\n", + " 14 H -2.051893 -1.281920 -1.197554\n", + " 15 H -1.350081 -1.567453 0.345621\n", + " 16 O 2.599059 1.221450 -3.782258\n", + " 17 H 3.528109 1.003450 -3.928033\n", + " 18 H 2.361893 1.888893 -4.437486,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s13.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.131450 -0.158248 0.013833\n", + " 1 O 3.056667 -2.012862 -1.374074\n", + " 2 H 3.547938 -2.754564 -1.001640\n", + " 3 H 3.533581 -1.744019 -2.167558\n", + " 4 O -0.370637 -0.440129 2.454929\n", + " 5 H 0.261593 -0.905658 3.015539\n", + " 6 H -1.199024 -0.461167 2.948898\n", + " 7 O -3.232632 -1.866376 -1.570282\n", + " 8 H -3.442354 -1.835729 -2.511132\n", + " 9 H -3.953159 -2.347086 -1.145336\n", + " 10 O 0.610240 2.070571 0.848426\n", + " 11 H 0.719899 2.927853 0.418532\n", + " 12 H 0.490121 2.271781 1.784655\n", + " 13 O 1.865487 -0.487383 0.156240\n", + " 14 H 2.402771 -1.092936 -0.510888\n", + " 15 H 2.353499 0.325523 0.352748\n", + " 16 O -2.124279 -0.060244 -0.333313\n", + " 17 H -2.621379 -0.802313 -0.901945\n", + " 18 H -2.489120 0.811335 -0.539202,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s16.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.264147 -0.117851 -0.197904\n", + " 1 O 1.820169 1.741017 0.359196\n", + " 2 H 2.218609 1.733706 1.239009\n", + " 3 H 1.772656 2.673480 0.111842\n", + " 4 O -2.611030 2.373459 0.046513\n", + " 5 H -3.139015 2.658377 -0.707808\n", + " 6 H -2.977139 2.835840 0.809335\n", + " 7 O 1.395302 -0.971701 1.793827\n", + " 8 H 2.101725 -1.629317 1.780004\n", + " 9 H 0.993301 -1.059012 2.666928\n", + " 10 O 2.097453 -0.540192 -1.120282\n", + " 11 H 2.180183 -0.954124 -1.992656\n", + " 12 H 2.696164 0.223658 -1.079452\n", + " 13 O -1.637659 0.083032 0.386043\n", + " 14 H -2.082281 0.991840 0.212297\n", + " 15 H -2.263650 -0.702011 0.165122\n", + " 16 O -3.054748 -1.930988 -0.082553\n", + " 17 H -3.620484 -2.071881 -0.849760\n", + " 18 H -3.483646 -2.391438 0.647732,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s9.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.454001 -0.230491 0.051961\n", + " 1 O -2.926548 -2.040462 -0.119173\n", + " 2 H -3.440602 -2.399947 0.613975\n", + " 3 H -3.425601 -2.224857 -0.923500\n", + " 4 O -1.508180 -0.082228 0.254383\n", + " 5 H -1.884757 0.842482 0.093946\n", + " 6 H -2.159102 -0.895507 0.057334\n", + " 7 O 2.468409 -0.631088 -0.065997\n", + " 8 H 2.853823 -1.390179 0.401365\n", + " 9 H 2.940776 -0.531484 -0.908335\n", + " 10 O 0.762418 2.135494 -0.049394\n", + " 11 H -0.019876 2.703344 -0.088988\n", + " 12 H 1.515728 2.715230 0.117127\n", + " 13 O -2.187243 2.374918 -0.063904\n", + " 14 H -2.633097 2.800941 0.680607\n", + " 15 H -2.657532 2.692245 -0.846194,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s19.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.219781 0.043323 -0.071931\n", + " 1 O 1.728776 -0.648755 -1.630435\n", + " 2 H 1.671640 -0.544383 -2.588953\n", + " 3 H 2.305430 -1.407361 -1.472859\n", + " 4 O -1.408154 1.523153 0.060729\n", + " 5 H -1.383567 2.407664 -0.323951\n", + " 6 H -2.337020 1.193301 0.034271\n", + " 7 O -3.705516 0.117397 0.085283\n", + " 8 H -4.364440 0.179521 -0.618682\n", + " 9 H -4.224488 0.113434 0.900517\n", + " 10 O 1.284661 -1.282622 1.470151\n", + " 11 H 0.851028 -1.990735 1.963227\n", + " 12 H 1.991005 -0.951244 2.039137\n", + " 13 O -1.469720 -1.508460 -0.114862\n", + " 14 H -2.388404 -1.175197 -0.086347\n", + " 15 H -1.482056 -2.356209 -0.574937\n", + " 16 O 1.836552 1.634101 0.509352\n", + " 17 H 2.605863 1.839398 -0.036318\n", + " 18 H 1.752780 2.362852 1.137071,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s8.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.35341 -0.42231 -0.13125\n", + " 1 O -3.61498 0.55542 0.63264\n", + " 2 H -4.45213 0.15523 0.10478\n", + " 3 H -3.83988 0.79310 1.54165\n", + " 4 O -5.49058 -0.32220 -0.66470\n", + " 5 H -6.15043 -0.94067 -0.33132\n", + " 6 H -5.94202 0.26328 -1.28369\n", + " 7 O -1.43536 -0.75833 0.57691\n", + " 8 H -2.75732 0.00697 0.60004\n", + " 9 H -1.53667 -1.70331 0.75771\n", + " 10 O 4.06883 0.38581 0.54566\n", + " 11 H 4.70085 -0.27662 0.84850\n", + " 12 H 4.57755 1.18868 0.38296\n", + " 13 O 0.74772 1.94827 0.73838\n", + " 14 H 0.79237 2.23108 1.65822\n", + " 15 H 0.75585 2.76588 0.22861\n", + " 16 O 2.17043 -0.13464 -0.94256\n", + " 17 H 2.99527 0.06251 -0.32171\n", + " 18 H 2.43662 -0.73175 -1.65542,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s6.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.550981 -0.106655 -0.161353\n", + " 1 O 1.143555 3.023832 0.118923\n", + " 2 H 1.509272 3.534737 -0.610619\n", + " 3 H 1.113717 3.634246 0.862953\n", + " 4 O -2.378949 -0.741668 -0.639898\n", + " 5 H -3.232588 -0.633361 -0.005267\n", + " 6 H -2.629734 -0.758515 -1.573014\n", + " 7 O 1.234848 0.416894 0.329744\n", + " 8 H 1.288420 1.412403 0.271016\n", + " 9 H 2.430794 -0.366712 0.720247\n", + " 10 O -4.261353 -0.539800 0.894286\n", + " 11 H -4.937535 0.144290 0.823042\n", + " 12 H -4.707025 -1.342754 1.190332\n", + " 13 O 3.217361 -0.963883 1.009201\n", + " 14 H 4.085665 -0.932678 0.408369\n", + " 15 H 3.422672 -0.851453 1.946089\n", + " 16 O 5.190712 -0.970343 -0.452485\n", + " 17 H 5.942882 -0.373060 -0.377103\n", + " 18 H 5.537773 -1.816307 -0.757613}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "files_hf: list = glob(str(working_dir.parent / \"files_xyz\" / \"hf\" / \"w*.xyz\"))\n", + "files_pbe0: list = glob(str(working_dir.parent / \"files_xyz\" / \"pbe0\" / \"w*.xyz\"))\n", + "files_camb3lyp: list = glob(\n", + " str(working_dir.parent / \"files_xyz\" / \"camb3lyp\" / \"w*.xyz\")\n", + ")\n", + "files_wb97xd: list = glob(str(working_dir.parent / \"files_xyz\" / \"wb97xd\" / \"w*.xyz\"))\n", + "files_b2plyp: list = glob(str(working_dir.parent / \"files_xyz\" / \"b2plyp_grimmeD2\" / \"w*.xyz\"))\n", + "files_pbeqidh: list = glob(str(working_dir.parent / \"files_xyz\" / \"pbeqidh\" / \"w*.xyz\"))\n", + "files_mp2: list = glob(str(working_dir.parent / \"files_xyz\" / \"mp2\" / \"w*.xyz\"))\n", + "files_zora_nr: list = glob(str(working_dir.parent / \"files_xyz\" / \"zora\" / \"c\" / \"w*.xyz\"))\n", + "files_zora_sr: list = glob(str(working_dir.parent / \"files_xyz\" / \"zora\" / \"sr\" / \"w*.xyz\"))\n", + "files_zora_so: list = glob(str(working_dir.parent / \"files_xyz\" / \"zora\" / \"so\" / \"w*.xyz\"))\n", + "\n", + "\n", + "coordinates_hf: dict = functions.dict_coordinates_xyz(files_hf)\n", + "coordinates_pbe0: dict = functions.dict_coordinates_xyz(files_pbe0)\n", + "coordinates_camb3lyp: dict = functions.dict_coordinates_xyz(files_camb3lyp)\n", + "coordinates_wb97xd: dict = functions.dict_coordinates_xyz(files_wb97xd)\n", + "coordinates_b2plyp: dict = functions.dict_coordinates_xyz(files_b2plyp)\n", + "coordinates_pbeqidh: dict = functions.dict_coordinates_xyz(files_pbeqidh)\n", + "coordinates_mp2: dict = functions.dict_coordinates_xyz(files_mp2)\n", + "coordinates_zora_nr: dict = functions.dict_coordinates_xyz(files_zora_nr)\n", + "coordinates_zora_sr: dict = functions.dict_coordinates_xyz(files_zora_sr)\n", + "coordinates_zora_so: dict = functions.dict_coordinates_xyz(files_zora_so)\n", + "\n", + "coordinates_mp2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s7.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.343871 2.954979 2.994153 2.283344 2.938378 \n", + " 1 O 2.343871 0.000000 0.964454 0.964586 3.086594 4.005807 \n", + " 2 H 2.954979 0.964454 0.000000 1.547005 3.623975 4.583611 \n", + " 3 H 2.994153 0.964586 1.547005 0.000000 3.789978 4.645613 \n", + " 4 O 2.283344 3.086594 3.623975 3.789978 0.000000 0.965072 \n", + " 5 H 2.938378 4.005807 4.583611 4.645613 0.965072 0.000000 \n", + " 6 H 2.865561 2.909099 3.418545 3.506422 0.965295 1.553259 \n", + " 7 O 4.018811 5.876478 6.702128 6.034403 5.109549 4.995061 \n", + " 8 H 4.638137 6.655987 7.437040 6.880510 5.704090 5.514264 \n", + " 9 H 4.669206 6.281761 7.152995 6.301492 5.706270 5.589144 \n", + " 10 O 2.096023 3.824586 4.526268 4.057993 4.042218 4.396160 \n", + " 11 H 2.838739 4.683509 5.452992 4.882021 4.389223 4.524425 \n", + " 12 H 2.687630 4.237652 4.811526 4.440773 4.828636 5.243465 \n", + " 13 O 2.292650 3.156686 3.064907 4.083840 3.030251 3.739764 \n", + " 14 H 2.952328 3.865083 3.666604 4.741031 3.958621 4.611036 \n", + " 15 H 2.888576 3.679723 3.562250 4.641406 2.885230 3.484871 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.865561 4.018811 4.638137 4.669206 2.096023 2.838739 2.687630 \n", + " 1 2.909099 5.876478 6.655987 6.281761 3.824586 4.683509 4.237652 \n", + " 2 3.418545 6.702128 7.437040 7.152995 4.526268 5.452992 4.811526 \n", + " 3 3.506422 6.034403 6.880510 6.301492 4.057993 4.882021 4.440773 \n", + " 4 0.965295 5.109549 5.704090 5.706270 4.042218 4.389223 4.828636 \n", + " 5 1.553259 4.995061 5.514264 5.589144 4.396160 4.524425 5.243465 \n", + " 6 0.000000 5.753898 6.429219 6.245680 4.638677 5.030117 5.428887 \n", + " 7 5.753898 0.000000 0.963405 0.963743 2.455339 1.396563 2.960461 \n", + " 8 6.429219 0.963405 0.000000 1.549778 3.087096 2.068308 3.423946 \n", + " 9 6.245680 0.963743 1.549778 0.000000 3.030648 2.045077 3.493298 \n", + " 10 4.638677 2.455339 3.087096 3.030648 0.000000 1.060169 0.963351 \n", + " 11 5.030117 1.396563 2.068308 2.045077 1.060169 0.000000 1.664721 \n", + " 12 5.428887 2.960461 3.423946 3.493298 0.963351 1.664721 0.000000 \n", + " 13 3.568713 5.966849 6.372122 6.747987 4.032505 4.809234 4.259367 \n", + " 14 4.531626 6.329629 6.639083 7.146290 4.351344 5.147819 4.380238 \n", + " 15 3.405733 6.447927 6.818112 7.251836 4.741392 5.409412 5.067893 \n", + " \n", + " 13 14 15 \n", + " 0 2.292650 2.952328 2.888576 \n", + " 1 3.156686 3.865083 3.679723 \n", + " 2 3.064907 3.666604 3.562250 \n", + " 3 4.083840 4.741031 4.641406 \n", + " 4 3.030251 3.958621 2.885230 \n", + " 5 3.739764 4.611036 3.484871 \n", + " 6 3.568713 4.531626 3.405733 \n", + " 7 5.966849 6.329629 6.447927 \n", + " 8 6.372122 6.639083 6.818112 \n", + " 9 6.747987 7.146290 7.251836 \n", + " 10 4.032505 4.351344 4.741392 \n", + " 11 4.809234 5.147819 5.409412 \n", + " 12 4.259367 4.380238 5.067893 \n", + " 13 0.000000 0.964899 0.964814 \n", + " 14 0.964899 0.000000 1.552415 \n", + " 15 0.964814 1.552415 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w2s1.xyz': atoms 0 1 2 3 4 5 6\n", + " 0 Hg 0.000000 2.035984 2.682186 2.680787 2.035939 2.682275 2.680875\n", + " 1 O 2.035984 0.000000 0.973897 0.974057 4.070666 4.675873 4.649640\n", + " 2 H 2.682186 0.973897 0.000000 1.595559 4.675731 5.201829 5.241338\n", + " 3 H 2.680787 0.974057 1.595559 0.000000 4.649487 5.241175 5.275612\n", + " 4 O 2.035939 4.070666 4.675731 4.649487 0.000000 0.973888 0.974049\n", + " 5 H 2.682275 4.675873 5.201829 5.241175 0.973888 0.000000 1.595576\n", + " 6 H 2.680875 4.649640 5.241338 5.275612 0.974049 1.595576 0.000000,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.458252 3.132118 3.132143 2.033064 2.802967 \n", + " 1 O 2.458252 0.000000 0.962615 0.962615 3.290192 3.552375 \n", + " 2 H 3.132118 0.962615 0.000000 1.539883 4.049878 4.152629 \n", + " 3 H 3.132143 0.962615 1.539883 0.000000 3.617686 3.863326 \n", + " 4 O 2.033064 3.290192 4.049878 3.617686 0.000000 1.092829 \n", + " 5 H 2.802967 3.552375 4.152629 3.863326 1.092829 0.000000 \n", + " 6 H 2.607736 4.174054 4.973475 4.449263 0.964649 1.695371 \n", + " 7 O 3.947306 4.205288 4.593849 4.466022 2.425854 1.333801 \n", + " 8 H 4.527366 5.022510 5.346571 5.364598 3.048174 2.005124 \n", + " 9 H 4.626077 4.536072 4.923877 4.605507 2.999337 1.985431 \n", + " 10 O 2.033077 3.289634 3.617189 4.049475 4.057610 4.787820 \n", + " 11 H 2.607760 4.173575 4.448804 4.973123 4.521812 5.235621 \n", + " 12 H 2.802921 3.551597 3.862683 4.152028 4.787751 5.581544 \n", + " 13 O 3.947293 4.204405 4.465321 4.593107 5.828056 6.652754 \n", + " 14 H 4.626062 4.535102 4.604697 4.923018 6.542723 7.287880 \n", + " 15 H 4.527364 5.021681 5.363942 5.345883 6.333264 7.239239 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.607736 3.947306 4.527366 4.626077 2.033077 2.607760 2.802921 \n", + " 1 4.174054 4.205288 5.022510 4.536072 3.289634 4.173575 3.551597 \n", + " 2 4.973475 4.593849 5.346571 4.923877 3.617189 4.448804 3.862683 \n", + " 3 4.449263 4.466022 5.364598 4.605507 4.049475 4.973123 4.152028 \n", + " 4 0.964649 2.425854 3.048174 2.999337 4.057610 4.521812 4.787751 \n", + " 5 1.695371 1.333801 2.005124 1.985431 4.787820 5.235621 5.581544 \n", + " 6 0.000000 2.926638 3.380687 3.447221 4.521795 4.871774 5.235523 \n", + " 7 2.926638 0.000000 0.964130 0.964278 5.828114 6.259828 6.652744 \n", + " 8 3.380687 0.964130 0.000000 1.556321 6.333316 6.645686 7.239226 \n", + " 9 3.447221 0.964278 1.556321 0.000000 6.542781 7.051541 7.287867 \n", + " 10 4.521795 5.828114 6.333316 6.542781 0.000000 0.964649 1.092798 \n", + " 11 4.871774 6.259828 6.645686 7.051541 0.964649 0.000000 1.695338 \n", + " 12 5.235523 6.652744 7.239226 7.287867 1.092798 1.695338 0.000000 \n", + " 13 6.259727 7.729900 8.388472 8.279436 2.425881 2.926655 1.333860 \n", + " 14 7.051445 8.279448 8.937210 8.819717 2.999364 3.447259 1.985485 \n", + " 15 6.645587 8.388465 9.038828 8.937186 3.048206 3.380694 2.005183 \n", + " \n", + " 13 14 15 \n", + " 0 3.947293 4.626062 4.527364 \n", + " 1 4.204405 4.535102 5.021681 \n", + " 2 4.465321 4.604697 5.363942 \n", + " 3 4.593107 4.923018 5.345883 \n", + " 4 5.828056 6.542723 6.333264 \n", + " 5 6.652754 7.287880 7.239239 \n", + " 6 6.259727 7.051445 6.645587 \n", + " 7 7.729900 8.279448 8.388465 \n", + " 8 8.388472 8.937210 9.038828 \n", + " 9 8.279436 8.819717 8.937186 \n", + " 10 2.425881 2.999364 3.048206 \n", + " 11 2.926655 3.447259 3.380694 \n", + " 12 1.333860 1.985485 2.005183 \n", + " 13 0.000000 0.964277 0.964130 \n", + " 14 0.964277 0.000000 1.556315 \n", + " 15 0.964130 1.556315 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w4s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.965669 1.572093 5.576015 5.229461 3.646816 \n", + " 1 O 0.965669 0.000000 0.965262 4.791596 4.552741 3.007503 \n", + " 2 H 1.572093 0.965262 0.000000 5.200123 5.110024 3.612692 \n", + " 3 H 5.576015 4.791596 5.200123 0.000000 0.965826 2.338097 \n", + " 4 O 5.229461 4.552741 5.110024 0.965826 0.000000 1.800814 \n", + " 5 H 3.646816 3.007503 3.612692 2.338097 1.800814 0.000000 \n", + " 6 H 9.011932 8.598642 9.340301 4.977612 4.603327 6.089136 \n", + " 7 O 8.600019 8.158936 8.887014 4.448595 4.015271 5.480764 \n", + " 8 H 9.347744 8.880948 9.582467 4.979069 4.601199 6.079267 \n", + " 9 H 1.868876 1.215949 1.885035 3.914871 3.571123 1.879258 \n", + " 10 O 2.948539 2.393515 3.009474 3.278370 2.781162 0.982568 \n", + " 11 H 3.503621 2.970753 3.400955 3.658087 3.215806 1.599321 \n", + " 12 Hg 6.809165 6.264594 6.926917 2.434829 1.949221 3.520775 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 9.011932 8.600019 9.347744 1.868876 2.948539 3.503621 6.809165 \n", + " 1 8.598642 8.158936 8.880948 1.215949 2.393515 2.970753 6.264594 \n", + " 2 9.340301 8.887014 9.582467 1.885035 3.009474 3.400955 6.926917 \n", + " 3 4.977612 4.448595 4.979069 3.914871 3.278370 3.658087 2.434829 \n", + " 4 4.603327 4.015271 4.601199 3.571123 2.781162 3.215806 1.949221 \n", + " 5 6.089136 5.480764 6.079267 1.879258 0.982568 1.599321 3.520775 \n", + " 6 0.000000 0.968547 1.577849 7.734829 6.947156 7.401220 2.703228 \n", + " 7 0.968547 0.000000 0.968588 7.209332 6.329810 6.693961 2.068651 \n", + " 8 1.577849 0.968588 0.000000 7.872517 6.919468 7.175461 2.702631 \n", + " 9 7.734829 7.209332 7.872517 0.000000 1.179240 1.823524 5.295670 \n", + " 10 6.947156 6.329810 6.919468 1.179240 0.000000 0.964000 4.435548 \n", + " 11 7.401220 6.693961 7.175461 1.823524 0.964000 0.000000 4.830720 \n", + " 12 2.703228 2.068651 2.702631 5.295670 4.435548 4.830720 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w4s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.969657 1.584460 5.205089 4.603588 5.251087 \n", + " 1 O 0.969657 0.000000 0.969657 4.666475 4.010672 4.639489 \n", + " 2 H 1.584460 0.969657 0.000000 5.205127 4.603615 5.250986 \n", + " 3 H 5.205089 4.666475 5.205127 0.000000 1.075172 1.850107 \n", + " 4 O 4.603588 4.010672 4.603615 1.075172 0.000000 1.076767 \n", + " 5 H 5.251087 4.639489 5.250986 1.850107 1.076767 0.000000 \n", + " 6 H 6.794898 6.249651 6.611155 2.033798 3.052002 3.628450 \n", + " 7 O 6.107407 5.639083 6.107475 1.362925 2.437226 3.122106 \n", + " 8 H 6.611198 6.249740 6.795070 2.033739 3.051906 3.628423 \n", + " 9 H 6.881245 6.189910 6.699512 3.628866 3.051491 2.031654 \n", + " 10 O 6.192044 5.582008 6.191822 3.120434 2.435617 1.359810 \n", + " 11 H 6.699561 6.189720 6.880858 3.629112 3.051490 2.031662 \n", + " 12 Hg 2.698087 2.053815 2.698101 2.672883 1.957316 2.671276 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 6.794898 6.107407 6.611198 6.881245 6.192044 6.699561 2.698087 \n", + " 1 6.249651 5.639083 6.249740 6.189910 5.582008 6.189720 2.053815 \n", + " 2 6.611155 6.107475 6.795070 6.699512 6.191822 6.880858 2.698101 \n", + " 3 2.033798 1.362925 2.033739 3.628866 3.120434 3.629112 2.672883 \n", + " 4 3.052002 2.437226 3.051906 3.051491 2.435617 3.051490 1.957316 \n", + " 5 3.628450 3.122106 3.628423 2.031654 1.359810 2.031662 2.671276 \n", + " 6 0.000000 0.963868 1.555200 4.883608 4.662911 5.125795 4.434434 \n", + " 7 0.963868 0.000000 0.963869 4.665146 4.264085 4.665555 3.796365 \n", + " 8 1.555200 0.963869 0.000000 5.125362 4.662946 4.884094 4.434469 \n", + " 9 4.883608 4.665146 5.125362 0.000000 0.963874 1.555787 4.426751 \n", + " 10 4.662911 4.264085 4.662946 0.963874 0.000000 0.963874 3.788725 \n", + " 11 5.125795 4.665555 4.884094 1.555787 0.963874 0.000000 4.426632 \n", + " 12 4.434434 3.796365 4.434469 4.426751 3.788725 4.426632 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s8.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964387 1.555530 4.700673 4.109117 4.509620 \n", + " 1 O 0.964387 0.000000 0.964385 3.773904 3.247589 3.744268 \n", + " 2 H 1.555530 0.964385 0.000000 3.567918 3.159647 3.539126 \n", + " 3 H 4.700673 3.773904 3.567918 0.000000 0.963812 1.549954 \n", + " 4 O 4.109117 3.247589 3.159647 0.963812 0.000000 0.963741 \n", + " 5 H 4.509620 3.744268 3.539126 1.549954 0.963741 0.000000 \n", + " 6 H 3.893001 3.340652 3.892367 4.404266 4.357076 5.286493 \n", + " 7 O 3.937128 3.318107 3.936598 3.945442 3.811549 4.737895 \n", + " 8 H 4.878296 4.268565 4.877525 4.403280 4.356143 5.285941 \n", + " 9 H 3.567216 3.773330 4.700429 6.022160 5.259123 5.715165 \n", + " 10 O 3.158244 3.246668 4.108711 5.259122 4.438512 4.819945 \n", + " 11 H 3.539115 3.744663 4.510741 5.715150 4.819931 5.024884 \n", + " 12 H 5.558272 5.116089 5.771965 4.699998 4.108259 4.510499 \n", + " 13 O 5.115836 4.541525 5.115890 3.772861 3.246152 3.744361 \n", + " 14 H 5.771140 5.115519 5.557691 3.566476 3.157376 3.538426 \n", + " 15 Hg 2.908583 2.273199 2.908736 3.020327 2.354077 3.035354 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.893001 3.937128 4.878296 3.567216 3.158244 3.539115 5.558272 \n", + " 1 3.340652 3.318107 4.268565 3.773330 3.246668 3.744663 5.116089 \n", + " 2 3.892367 3.936598 4.877525 4.700429 4.108711 4.510741 5.771965 \n", + " 3 4.404266 3.945442 4.403280 6.022160 5.259122 5.715150 4.699998 \n", + " 4 4.357076 3.811549 4.356143 5.259123 4.438512 4.819931 4.108259 \n", + " 5 5.286493 4.737895 5.285941 5.715165 4.819945 5.024884 4.510499 \n", + " 6 0.000000 0.963282 1.554810 4.403193 4.356166 5.285957 4.877013 \n", + " 7 0.963282 0.000000 0.963281 3.944949 3.811172 4.737546 3.935943 \n", + " 8 1.554810 0.963281 0.000000 4.403994 4.356782 5.286217 3.891459 \n", + " 9 4.403193 3.944949 4.403994 0.000000 0.963812 1.549962 3.568356 \n", + " 10 4.356166 3.811172 4.356782 0.963812 0.000000 0.963740 3.159896 \n", + " 11 5.285957 4.737546 5.286217 1.549962 0.963740 0.000000 3.539645 \n", + " 12 4.877013 3.935943 3.891459 3.568356 3.159896 3.539645 0.000000 \n", + " 13 4.268119 3.317622 3.339928 3.774209 3.247734 3.744598 0.964386 \n", + " 14 4.877953 3.936880 3.892537 4.700868 4.109087 4.509722 1.555525 \n", + " 15 2.985357 2.313509 2.985290 3.020240 2.353993 3.035270 2.908784 \n", + " \n", + " 13 14 15 \n", + " 0 5.115836 5.771140 2.908583 \n", + " 1 4.541525 5.115519 2.273199 \n", + " 2 5.115890 5.557691 2.908736 \n", + " 3 3.772861 3.566476 3.020327 \n", + " 4 3.246152 3.157376 2.354077 \n", + " 5 3.744361 3.538426 3.035354 \n", + " 6 4.268119 4.877953 2.985357 \n", + " 7 3.317622 3.936880 2.313509 \n", + " 8 3.339928 3.892537 2.985290 \n", + " 9 3.774209 4.700868 3.020240 \n", + " 10 3.247734 4.109087 2.353993 \n", + " 11 3.744598 4.509722 3.035270 \n", + " 12 0.964386 1.555525 2.908784 \n", + " 13 0.000000 0.964387 2.273230 \n", + " 14 0.964387 0.000000 2.908500 \n", + " 15 2.273230 2.908500 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s12.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.962099 1.547970 6.194348 6.131740 7.132145 \n", + " 1 O 0.962099 0.000000 0.962519 5.638743 5.563998 6.538281 \n", + " 2 H 1.547970 0.962519 0.000000 6.213907 6.192025 7.144839 \n", + " 3 H 6.194348 5.638743 6.213907 0.000000 0.963598 1.680830 \n", + " 4 O 6.131740 5.563998 6.192025 0.963598 0.000000 1.070263 \n", + " 5 H 7.132145 6.538281 7.144839 1.680830 1.070263 0.000000 \n", + " 6 H 3.590764 3.075621 3.641732 5.237283 4.654260 5.297419 \n", + " 7 O 3.143150 2.482398 3.077487 4.501182 4.046444 4.808480 \n", + " 8 H 2.138203 1.447122 2.108162 4.894013 4.610836 5.490909 \n", + " 9 H 5.880975 5.404390 6.024466 5.270139 4.388633 4.565378 \n", + " 10 O 6.019970 5.496994 6.148104 4.426088 3.510354 3.613185 \n", + " 11 H 6.949592 6.444459 7.104531 4.751681 3.792490 3.634868 \n", + " 12 H 9.006368 8.331832 8.843805 3.430614 3.065869 2.039827 \n", + " 13 O 8.431194 7.821975 8.413368 2.952594 2.442618 1.373620 \n", + " 14 H 9.021100 8.478414 9.123981 3.439947 3.011151 2.018735 \n", + " 15 H 5.369224 4.943347 5.289290 7.098699 6.373025 6.758667 \n", + " 16 O 4.882607 4.515923 5.018886 6.454767 5.722063 6.159822 \n", + " 17 H 5.011309 4.824036 5.379336 7.059557 6.328337 6.789834 \n", + " 18 Hg 4.526628 3.904523 4.557814 2.624003 2.036979 2.801017 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.590764 3.143150 2.138203 5.880975 6.019970 6.949592 9.006368 \n", + " 1 3.075621 2.482398 1.447122 5.404390 5.496994 6.444459 8.331832 \n", + " 2 3.641732 3.077487 2.108162 6.024466 6.148104 7.104531 8.843805 \n", + " 3 5.237283 4.501182 4.894013 5.270139 4.426088 4.751681 3.430614 \n", + " 4 4.654260 4.046444 4.610836 4.388633 3.510354 3.792490 3.065869 \n", + " 5 5.297419 4.808480 5.490909 4.565378 3.613185 3.634868 2.039827 \n", + " 6 0.000000 0.998048 1.714510 2.441119 2.811895 3.751068 6.820937 \n", + " 7 0.998048 0.000000 1.037974 3.002905 3.072380 4.031043 6.437622 \n", + " 8 1.714510 1.037974 0.000000 3.979966 4.073840 5.028568 7.217032 \n", + " 9 2.441119 3.002905 3.979966 0.000000 0.968133 1.560359 5.657394 \n", + " 10 2.811895 3.072380 4.073840 0.968133 0.000000 0.961206 4.730128 \n", + " 11 3.751068 4.031043 5.028568 1.560359 0.961206 0.000000 4.432674 \n", + " 12 6.820937 6.437622 7.217032 5.657394 4.730128 4.432674 0.000000 \n", + " 13 6.273962 5.915340 6.693200 5.079750 4.123148 3.828497 0.963747 \n", + " 14 6.948062 6.617780 7.374885 5.642620 4.692632 4.292257 1.552273 \n", + " 15 2.239115 3.172722 3.785851 2.586979 3.452039 4.101794 7.887026 \n", + " 16 1.637915 2.625193 3.286693 2.017753 2.858862 3.577385 7.444718 \n", + " 17 2.274621 3.249129 3.746389 2.588238 3.451822 4.079475 8.142758 \n", + " 18 2.633655 2.025781 2.719463 3.001216 2.424507 3.169081 4.562484 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 8.431194 9.021100 5.369224 4.882607 5.011309 4.526628 \n", + " 1 7.821975 8.478414 4.943347 4.515923 4.824036 3.904523 \n", + " 2 8.413368 9.123981 5.289290 5.018886 5.379336 4.557814 \n", + " 3 2.952594 3.439947 7.098699 6.454767 7.059557 2.624003 \n", + " 4 2.442618 3.011151 6.373025 5.722063 6.328337 2.036979 \n", + " 5 1.373620 2.018735 6.758667 6.159822 6.789834 2.801017 \n", + " 6 6.273962 6.948062 2.239115 1.637915 2.274621 2.633655 \n", + " 7 5.915340 6.617780 3.172722 2.625193 3.249129 2.025781 \n", + " 8 6.693200 7.374885 3.785851 3.286693 3.746389 2.719463 \n", + " 9 5.079750 5.642620 2.586979 2.017753 2.588238 3.001216 \n", + " 10 4.123148 4.692632 3.452039 2.858862 3.451822 2.424507 \n", + " 11 3.828497 4.292257 4.101794 3.577385 4.079475 3.169081 \n", + " 12 0.963747 1.552273 7.887026 7.444718 8.142758 4.562484 \n", + " 13 0.000000 0.964064 7.425002 6.893130 7.523935 3.981286 \n", + " 14 0.964064 0.000000 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4.343254 \n", + " 9 H 5.546164 5.794144 6.677655 5.250204 4.633404 5.083341 \n", + " 10 O 4.741818 5.000911 5.917072 4.633369 4.012619 4.359837 \n", + " 11 H 4.343670 4.801605 5.700820 5.083120 4.359631 4.450655 \n", + " 12 H 2.402304 3.358526 3.711195 5.870655 5.054354 4.251812 \n", + " 13 O 1.900772 2.863097 3.408181 5.227109 4.463577 3.683055 \n", + " 14 H 2.362379 3.274946 3.754549 5.720268 5.057904 4.224688 \n", + " 15 H 6.558438 6.158825 6.809971 3.776370 3.790411 4.840987 \n", + " 16 O 6.048720 5.714174 6.453791 3.463090 3.437930 4.441928 \n", + " 17 H 6.740760 6.418787 7.190575 4.097461 4.190963 5.171573 \n", + " 18 Hg 3.786991 3.665256 4.522251 2.629342 2.042470 2.648038 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.843600 4.073827 3.283952 5.546164 4.741818 4.343670 2.402304 \n", + " 1 5.590272 4.767550 4.073744 5.794144 5.000911 4.801605 3.358526 \n", + " 2 6.399106 5.590409 4.843655 6.677655 5.917072 5.700820 3.711195 \n", + " 3 6.677327 5.793829 5.545801 5.250204 4.633369 5.083120 5.870655 \n", + " 4 5.916710 5.000565 4.741364 4.633404 4.012619 4.359631 5.054354 \n", + " 5 5.700468 4.801331 4.343254 5.083341 4.359837 4.450655 4.251812 \n", + " 6 0.000000 0.962365 1.580979 3.472567 3.056593 2.020344 3.754727 \n", + " 7 0.962365 0.000000 0.975055 2.965813 2.437502 1.361874 3.275210 \n", + " 8 1.580979 0.975055 0.000000 3.714777 3.052621 2.061711 2.362571 \n", + " 9 3.472567 2.965813 3.714777 0.000000 0.965598 1.694922 5.720457 \n", + " 10 3.056593 2.437502 3.052621 0.965598 0.000000 1.078122 5.058232 \n", + " 11 2.020344 1.361874 2.061711 1.694922 1.078122 0.000000 4.225168 \n", + " 12 3.754727 3.275210 2.362571 5.720457 5.058232 4.225168 0.000000 \n", + " 13 3.408409 2.863435 1.901106 5.227496 4.464071 3.683670 0.965241 \n", + " 14 3.711202 3.358689 2.402535 5.871059 5.054863 4.252374 1.527114 \n", + " 15 7.190836 6.418916 6.740713 4.097841 4.191087 5.171544 7.956599 \n", + " 16 6.454044 5.714304 6.048713 3.463575 3.438118 4.441922 7.409334 \n", 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2.105446 \n", + " 7 O 8.286643 2.465623 2.991135 1.415421 4.215844 4.607673 \n", + " 8 H 9.002602 3.121839 3.479202 2.106743 4.758721 4.988130 \n", + " 9 H 8.722100 3.054536 3.576851 2.076944 4.921584 5.412039 \n", + " 10 O 2.027402 8.437399 9.010922 9.050082 6.435437 6.676006 \n", + " 11 H 2.761696 9.271743 9.809611 9.902678 7.150670 7.284106 \n", + " 12 H 2.622401 8.782473 9.380058 9.376413 6.956463 7.297747 \n", + " 13 O 3.926932 10.381881 10.879223 11.025649 8.146525 8.157133 \n", + " 14 H 4.536217 11.047068 11.499643 11.738409 8.852283 8.881350 \n", + " 15 H 4.587259 10.901669 11.440707 11.484779 8.616766 8.571989 \n", + " 16 O 1.945084 4.841858 5.240850 5.642626 2.869178 3.233962 \n", + " 17 H 3.628824 3.156752 3.643121 3.879554 0.972116 1.561864 \n", + " 18 H 2.433857 5.055167 5.292145 5.961354 3.314452 3.666472 \n", + " \n", + " 6 7 8 9 10 11 \\\n", + " 0 5.693643 8.286643 9.002602 8.722100 2.027402 2.761696 \n", + " 1 1.041540 2.465623 3.121839 3.054536 8.437399 9.271743 \n", 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\n", + " 17 2.170136 5.021838 5.639462 5.643060 5.551382 6.272875 \n", + " 18 4.242257 7.222643 7.899239 7.752394 4.406100 5.002888 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 2.622401 3.926932 4.536217 4.587259 1.945084 3.628824 2.433857 \n", + " 1 8.782473 10.381881 11.047068 10.901669 4.841858 3.156752 5.055167 \n", + " 2 9.380058 10.879223 11.499643 11.440707 5.240850 3.643121 5.292145 \n", + " 3 9.376413 11.025649 11.738409 11.484779 5.642626 3.879554 5.961354 \n", + " 4 6.956463 8.146525 8.852283 8.616766 2.869178 0.972116 3.314452 \n", + " 5 7.297747 8.157133 8.881350 8.571989 3.233962 1.561864 3.666472 \n", + " 6 7.990378 9.439447 10.120248 9.941859 3.954159 2.170136 4.242257 \n", + " 7 10.238763 11.947578 12.711219 12.331680 6.802431 5.021838 7.222643 \n", + " 8 11.011708 12.587931 13.368437 12.940228 7.484598 5.639462 7.899239 \n", + " 9 10.521693 12.412525 13.170735 12.800876 7.325776 5.643060 7.752394 \n", + " 10 0.963385 2.449218 3.087848 3.034218 3.970101 5.551382 4.406100 \n", + " 11 1.675158 1.388626 2.066749 2.044254 4.650876 6.272875 5.002888 \n", + " 12 0.000000 2.969088 3.449446 3.514182 4.510837 6.070966 4.919627 \n", + " 13 2.969088 0.000000 0.962782 0.963077 5.682432 7.293445 5.952206 \n", + " 14 3.449446 0.962782 0.000000 1.553004 6.263268 7.969115 6.411577 \n", + " 15 3.514182 0.963077 1.553004 0.000000 6.327833 7.814313 6.685550 \n", + " 16 4.510837 5.682432 6.263268 6.327833 0.000000 1.901479 0.964074 \n", + " 17 6.070966 7.293445 7.969115 7.814313 1.901479 0.000000 2.406822 \n", + " 18 4.919627 5.952206 6.411577 6.685550 0.964074 2.406822 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.963539 1.558419 5.159593 4.964907 3.680308 \n", + " 1 O 0.963539 0.000000 0.962839 4.722355 4.371211 3.057575 \n", + " 2 H 1.558419 0.962839 0.000000 5.495993 5.030639 3.705590 \n", + " 3 H 5.159593 4.722355 5.495993 0.000000 0.963726 2.071215 \n", + " 4 O 4.964907 4.371211 5.030639 0.963726 0.000000 1.563023 \n", + " 5 H 3.680308 3.057575 3.705590 2.071215 1.563023 0.000000 \n", + " 6 H 9.900872 9.173349 9.448899 6.611772 6.223001 7.432039 \n", + " 7 O 9.524827 8.831001 9.193769 5.879522 5.580287 6.895778 \n", + " 8 H 10.160218 9.516661 9.932536 6.323924 6.151854 7.542660 \n", + " 9 H 9.247365 8.485629 8.881023 4.934652 4.549675 5.850598 \n", + " 10 O 8.488015 7.728751 8.119005 4.394650 3.955604 5.263885 \n", + " 11 H 8.884172 8.148330 8.531992 4.925072 4.552209 5.890737 \n", + " 12 H 3.551385 2.990319 3.450726 3.514001 3.086036 1.647142 \n", + " 13 O 2.988221 2.422123 3.063914 2.942216 2.563232 1.011288 \n", + " 14 H 1.986759 1.334331 2.014800 3.673418 3.289814 1.825524 \n", + " 15 H 11.029895 10.308443 10.754631 6.342412 6.144096 7.451293 \n", + " 16 O 10.357317 9.596118 9.989837 5.899092 5.574217 6.807994 \n", + " 17 H 10.854321 10.050288 10.370213 6.633146 6.217152 7.335484 \n", + " 18 Hg 6.669033 5.967428 6.473029 2.459301 1.963119 3.342057 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 9.900872 9.524827 10.160218 9.247365 8.488015 8.884172 3.551385 \n", + " 1 9.173349 8.831001 9.516661 8.485629 7.728751 8.148330 2.990319 \n", + " 2 9.448899 9.193769 9.932536 8.881023 8.119005 8.531992 3.450726 \n", + " 3 6.611772 5.879522 6.323924 4.934652 4.394650 4.925072 3.514001 \n", + " 4 6.223001 5.580287 6.151854 4.549675 3.955604 4.552209 3.086036 \n", + " 5 7.432039 6.895778 7.542660 5.850598 5.263885 5.890737 1.647142 \n", + " 6 0.000000 0.962045 1.544341 3.673263 3.101057 2.139419 8.843170 \n", + " 7 0.962045 0.000000 0.961724 3.108435 2.507508 1.483149 8.356544 \n", + " 8 1.544341 0.961724 0.000000 3.609968 3.163900 2.170218 9.050112 \n", + " 9 3.673263 3.108435 3.609968 0.000000 1.026586 1.721900 6.986935 \n", + " 10 3.101057 2.507508 3.163900 1.026586 0.000000 1.026669 6.524865 \n", + " 11 2.139419 1.483149 2.170218 1.721900 1.026669 0.000000 7.257527 \n", + " 12 8.843170 8.356544 9.050112 6.986935 6.524865 7.257527 0.000000 \n", + " 13 8.356971 7.857419 8.520877 6.804106 6.233541 6.868415 0.962868 \n", + " 14 8.648058 8.223062 8.906394 7.505227 6.836675 7.371995 1.737829 \n", + " 15 5.240654 4.681630 4.838806 2.171236 3.165182 3.613324 8.427042 \n", + " 16 4.835075 4.335305 4.678412 1.483434 2.507613 3.109317 7.752752 \n", + " 17 5.178770 4.834894 5.236760 2.140046 3.101411 3.674057 8.160656 \n", + " 18 4.515134 3.852785 4.470092 2.649979 1.993823 2.651243 4.712315 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.988221 1.986759 11.029895 10.357317 10.854321 6.669033 \n", + " 1 2.422123 1.334331 10.308443 9.596118 10.050288 5.967428 \n", + " 2 3.063914 2.014800 10.754631 9.989837 10.370213 6.473029 \n", + " 3 2.942216 3.673418 6.342412 5.899092 6.633146 2.459301 \n", + " 4 2.563232 3.289814 6.144096 5.574217 6.217152 1.963119 \n", + " 5 1.011288 1.825524 7.451293 6.807994 7.335484 3.342057 \n", + " 6 8.356971 8.648058 5.240654 4.835075 5.178770 4.515134 \n", + " 7 7.857419 8.223062 4.681630 4.335305 4.834894 3.852785 \n", + " 8 8.520877 8.906394 4.838806 4.678412 5.236760 4.470092 \n", + " 9 6.804106 7.505227 2.171236 1.483434 2.140046 2.649979 \n", + " 10 6.233541 6.836675 3.165182 2.507613 3.101411 1.993823 \n", + " 11 6.868415 7.371995 3.613324 3.109317 3.674057 2.651243 \n", + " 12 0.962868 1.737829 8.427042 7.752752 8.160656 4.712315 \n", + " 13 0.000000 1.089678 8.371302 7.713937 8.196534 4.339196 \n", + " 14 1.089678 0.000000 9.210426 8.519719 8.985351 4.993487 \n", + " 15 8.371302 9.210426 0.000000 0.961719 1.544354 4.466757 \n", + " 16 7.713937 8.519719 0.961719 0.000000 0.962050 3.850053 \n", + " 17 8.196534 8.985351 1.544354 0.962050 0.000000 4.512881 \n", + " 18 4.339196 4.993487 4.466757 3.850053 4.512881 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.848339 4.491865 4.506958 2.332645 2.963747 \n", + " 1 O 3.848339 0.000000 0.965624 0.965286 5.547274 5.975849 \n", + " 2 H 4.491865 0.965624 0.000000 1.534900 5.899415 6.252363 \n", + " 3 H 4.506958 0.965286 1.534900 0.000000 6.385422 6.837052 \n", + " 4 O 2.332645 5.547274 5.899415 6.385422 0.000000 0.965124 \n", + " 5 H 2.963747 5.975849 6.252363 6.837052 0.965124 0.000000 \n", + " 6 H 2.957357 5.815508 6.076932 6.688331 0.965173 1.545176 \n", + " 7 O 2.178219 2.639195 3.190062 3.260654 3.819965 4.034340 \n", + " 8 H 2.756348 1.669350 2.261175 2.290474 4.493472 4.790525 \n", + " 9 H 2.824375 3.234441 3.779209 3.675755 4.413890 4.499011 \n", + " 10 O 2.281019 2.782630 3.350525 3.402982 3.769936 4.541152 \n", + " 11 H 2.963908 3.447264 4.000881 3.919333 4.310004 5.167287 \n", + " 12 H 2.853378 1.881655 2.460548 2.478889 4.478058 5.145582 \n", + " 13 O 2.205998 5.825650 6.567265 6.328036 3.021458 3.700630 \n", + " 14 H 2.867296 6.212643 7.029634 6.593634 3.948017 4.561879 \n", + " 15 H 2.802371 6.587228 7.267279 7.156450 2.835739 3.417317 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.957357 2.178219 2.756348 2.824375 2.281019 2.963908 2.853378 \n", + " 1 5.815508 2.639195 1.669350 3.234441 2.782630 3.447264 1.881655 \n", + " 2 6.076932 3.190062 2.261175 3.779209 3.350525 4.000881 2.460548 \n", + " 3 6.688331 3.260654 2.290474 3.675755 3.402982 3.919333 2.478889 \n", + " 4 0.965173 3.819965 4.493472 4.413890 3.769936 4.310004 4.478058 \n", + " 5 1.545176 4.034340 4.790525 4.499011 4.541152 5.167287 5.145582 \n", + " 6 0.000000 4.450882 4.987790 5.148642 3.851950 4.269541 4.599105 \n", + " 7 4.450882 0.000000 0.995977 0.964278 3.062718 3.983670 2.908334 \n", + " 8 4.987790 0.995977 0.000000 1.607661 2.842865 3.734445 2.382745 \n", + " 9 5.148642 0.964278 1.607661 0.000000 3.956016 4.843279 3.770340 \n", + " 10 3.851950 3.062718 2.842865 3.956016 0.000000 0.963450 0.976305 \n", + " 11 4.269541 3.983670 3.734445 4.843279 0.963450 0.000000 1.580823 \n", + " 12 4.599105 2.908334 2.382745 3.770340 0.976305 1.580823 0.000000 \n", + " 13 3.609382 4.179764 4.805670 4.545094 3.798089 4.008921 4.577870 \n", + " 14 4.571148 4.590254 5.193539 4.813665 4.370287 4.522305 5.068967 \n", + " 15 3.389684 4.792974 5.500233 5.139150 4.487576 4.695281 5.317541 \n", + " \n", + " 13 14 15 \n", + " 0 2.205998 2.867296 2.802371 \n", + " 1 5.825650 6.212643 6.587228 \n", + " 2 6.567265 7.029634 7.267279 \n", + " 3 6.328036 6.593634 7.156450 \n", + " 4 3.021458 3.948017 2.835739 \n", + " 5 3.700630 4.561879 3.417317 \n", + " 6 3.609382 4.571148 3.389684 \n", + " 7 4.179764 4.590254 4.792974 \n", + " 8 4.805670 5.193539 5.500233 \n", + " 9 4.545094 4.813665 5.139150 \n", + " 10 3.798089 4.370287 4.487576 \n", + " 11 4.008921 4.522305 4.695281 \n", + " 12 4.577870 5.068967 5.317541 \n", + " 13 0.000000 0.965697 0.965761 \n", + " 14 0.965697 0.000000 1.565200 \n", + " 15 0.965761 1.565200 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s18.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.961914 1.544187 2.170218 3.171155 3.576954 \n", + " 1 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\n", + " 16 O 6.461790 5.651620 6.016511 4.546199 3.842752 4.411391 \n", + " 17 H 6.556516 5.687020 5.909705 4.736253 4.162714 4.827322 \n", + " 18 Hg 4.581371 3.969963 4.635837 2.758392 2.076345 2.634586 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.109151 6.081243 6.709204 5.033769 4.942446 5.497867 5.843555 \n", + " 1 5.739668 5.594031 6.137689 4.875474 4.604491 5.097782 5.412664 \n", + " 2 6.477042 6.289432 6.737954 5.462479 5.147132 5.497306 6.078752 \n", + " 3 5.010414 4.675995 5.239762 3.783683 3.342287 3.875805 3.981969 \n", + " 4 4.677173 4.183839 4.728357 3.302423 2.677518 3.218800 3.051753 \n", + " 5 5.256420 4.737609 5.339913 2.333385 1.708296 2.295718 2.502440 \n", + " 6 0.000000 0.965875 1.572654 6.735569 6.279213 7.047417 5.028598 \n", + " 7 0.965875 0.000000 0.966799 6.267866 5.712565 6.409378 4.370082 \n", + " 8 1.572654 0.966799 0.000000 6.980358 6.342475 6.953675 4.956539 \n", + " 9 6.735569 6.267866 6.980358 0.000000 0.964177 1.531955 2.533364 \n", + " 10 6.279213 5.712565 6.342475 0.964177 0.000000 0.964538 1.957622 \n", + " 11 7.047417 6.409378 6.953675 1.531955 0.964538 0.000000 2.522241 \n", + " 12 5.028598 4.370082 4.956539 2.533364 1.957622 2.522241 0.000000 \n", + " 13 4.235684 3.522107 4.062016 3.434604 2.827733 3.394810 0.971452 \n", + " 14 4.356599 3.703506 4.234812 3.969759 3.510769 4.066630 1.567987 \n", + " 15 4.380087 3.438372 3.059058 6.347090 5.458293 5.661991 4.233098 \n", + " 16 3.734173 2.842435 2.484654 6.242407 5.383290 5.693386 4.287899 \n", + " 17 4.328465 3.529208 3.070971 6.816776 5.931840 6.166816 5.060667 \n", + " 18 2.818124 2.162303 2.707765 4.453620 3.794565 4.437437 2.912656 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 6.035721 6.824076 7.191083 6.461790 6.556516 4.581371 \n", + " 1 5.550462 6.398183 6.376293 5.651620 5.687020 3.969963 \n", + " 2 6.238919 7.128711 6.730202 6.016511 5.909705 4.635837 \n", + " 3 4.122063 5.004008 5.167687 4.546199 4.736253 2.758392 \n", + " 4 3.168508 4.086101 4.351918 3.842752 4.162714 2.076345 \n", + " 5 2.909640 3.805247 4.754451 4.411391 4.827322 2.634586 \n", + " 6 4.235684 4.356599 4.380087 3.734173 4.328465 2.818124 \n", + " 7 3.522107 3.703506 3.438372 2.842435 3.529208 2.162303 \n", + " 8 4.062016 4.234812 3.059058 2.484654 3.070971 2.707765 \n", + " 9 3.434604 3.969759 6.347090 6.242407 6.816776 4.453620 \n", + " 10 2.827733 3.510769 5.458293 5.383290 5.931840 3.794565 \n", + " 11 3.394810 4.066630 5.661991 5.693386 6.166816 4.437437 \n", + " 12 0.971452 1.567987 4.233098 4.287899 5.060667 2.912656 \n", + " 13 0.000000 0.962329 3.535267 3.581244 4.437166 2.368549 \n", + " 14 0.962329 0.000000 3.960190 4.108373 5.028927 3.073271 \n", + " 15 3.535267 3.960190 0.000000 0.964252 1.537619 3.046008 \n", + " 16 3.581244 4.108373 0.964252 0.000000 0.964157 2.441051 \n", + " 17 4.437166 5.028927 1.537619 0.964157 0.000000 3.076002 \n", + " 18 2.368549 3.073271 3.046008 2.441051 3.076002 0.000000 ,\n", + " 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2.064252 2.537633 3.087386 3.153881 7.788977 8.203696 \n", + " 14 H 2.733366 1.519147 2.132587 2.165903 8.575475 9.022334 \n", + " 15 H 2.673824 3.063763 3.570561 3.503051 8.178941 8.550601 \n", + " 16 O 1.984452 5.822770 6.486959 6.409073 4.279710 4.975758 \n", + " 17 H 2.484750 5.981134 6.690447 6.504460 4.570458 5.372358 \n", + " 18 H 3.227822 7.172145 7.792151 7.781534 3.053522 3.719982 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.649968 4.154714 4.631199 4.905086 2.503358 3.201664 3.138199 \n", + " 1 10.408919 8.101708 8.576135 8.794120 2.983649 3.745549 2.221078 \n", + " 2 10.911991 8.695859 9.231244 9.336219 3.573318 4.232091 2.778107 \n", + " 3 11.108817 8.720862 9.120503 9.465155 3.592601 4.326188 2.790092 \n", + " 4 0.962587 2.439004 2.974045 1.364782 7.411762 7.359962 8.338570 \n", + " 5 1.555747 3.018156 3.547864 2.022688 8.029158 8.007298 8.928551 \n", + " 6 0.000000 3.083943 3.439740 2.048591 7.937414 7.804008 8.885037 \n", + " 7 3.083943 0.000000 0.964046 1.075676 6.093921 6.308161 6.974520 \n", + " 8 3.439740 0.964046 0.000000 1.701918 6.648282 6.901140 7.512860 \n", + " 9 2.048591 1.075676 1.701918 0.000000 6.606651 6.691035 7.520352 \n", + " 10 7.937414 6.093921 6.648282 6.606651 0.000000 0.961471 0.963879 \n", + " 11 7.804008 6.308161 6.901140 6.691035 0.961471 0.000000 1.544767 \n", + " 12 8.885037 6.974520 7.512860 7.520352 0.963879 1.544767 0.000000 \n", + " 13 8.543885 5.946978 6.387283 6.731158 3.031078 3.961057 3.041983 \n", + " 14 9.295793 6.809442 7.261740 7.559540 2.797260 3.726582 2.492221 \n", + " 15 8.962531 6.195381 6.542012 7.053791 3.953601 4.894738 3.930392 \n", + " 16 4.835719 2.531289 3.028627 3.196027 3.625578 3.894959 4.512693 \n", + " 17 4.963080 3.076509 3.469337 3.605341 3.491723 3.590625 4.413809 \n", + " 18 3.665985 1.024250 1.648743 1.799720 5.090341 5.316054 5.976072 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.064252 2.733366 2.673824 1.984452 2.484750 3.227822 \n", + " 1 2.537633 1.519147 3.063763 5.822770 5.981134 7.172145 \n", + " 2 3.087386 2.132587 3.570561 6.486959 6.690447 7.792151 \n", + " 3 3.153881 2.165903 3.503051 6.409073 6.504460 7.781534 \n", + " 4 7.788977 8.575475 8.178941 4.279710 4.570458 3.053522 \n", + " 5 8.203696 9.022334 8.550601 4.975758 5.372358 3.719982 \n", + " 6 8.543885 9.295793 8.962531 4.835719 4.963080 3.665985 \n", + " 7 5.946978 6.809442 6.195381 2.531289 3.076509 1.024250 \n", + " 8 6.387283 7.261740 6.542012 3.028627 3.469337 1.648743 \n", + " 9 6.731158 7.559540 7.053791 3.196027 3.605341 1.799720 \n", + " 10 3.031078 2.797260 3.953601 3.625578 3.491723 5.090341 \n", + " 11 3.961057 3.726582 4.894738 3.894959 3.590625 5.316054 \n", + " 12 3.041983 2.492221 3.930392 4.512693 4.413809 5.976072 \n", + " 13 0.000000 1.021866 0.963466 4.033147 4.523763 5.127698 \n", + " 14 1.021866 0.000000 1.635000 4.704687 5.044220 5.934258 \n", + " 15 0.963466 1.635000 0.000000 4.531731 5.099092 5.464894 \n", + " 16 4.033147 4.704687 4.531731 0.000000 0.962494 1.507823 \n", + " 17 4.523763 5.044220 5.099092 0.962494 0.000000 2.101828 \n", + " 18 5.127698 5.934258 5.464894 1.507823 2.101828 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w3s2.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.127299 2.786839 2.746416 2.102209 2.742471 2.745855 \n", + " 1 O 2.127299 0.000000 0.969245 0.968829 4.126517 4.540251 4.844874 \n", + " 2 H 2.786839 0.969245 0.000000 1.579505 4.570769 4.804869 5.381785 \n", + " 3 H 2.746416 0.968829 1.579505 0.000000 4.825100 5.338460 5.483278 \n", + " 4 O 2.102209 4.126517 4.570769 4.825100 0.000000 0.970029 0.969676 \n", + " 5 H 2.742471 4.540251 4.804869 5.338460 0.970029 0.000000 1.578860 \n", + " 6 H 2.745855 4.844874 5.381785 5.483278 0.969676 1.578860 0.000000 \n", + " 7 O 2.297636 3.036276 3.993560 2.923240 3.787743 4.679115 3.964661 \n", + " 8 H 2.947723 3.756418 4.681471 3.530440 4.172197 5.100761 4.277373 \n", + " 9 H 2.946744 3.544756 4.510876 3.398572 4.336885 5.226864 4.373300 \n", + " \n", + " 7 8 9 \n", + " 0 2.297636 2.947723 2.946744 \n", + " 1 3.036276 3.756418 3.544756 \n", + " 2 3.993560 4.681471 4.510876 \n", + " 3 2.923240 3.530440 3.398572 \n", + " 4 3.787743 4.172197 4.336885 \n", + " 5 4.679115 5.100761 5.226864 \n", + " 6 3.964661 4.277373 4.373300 \n", + " 7 0.000000 0.967102 0.967153 \n", + " 8 0.967102 0.000000 1.553967 \n", + " 9 0.967153 1.553967 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w4s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.967124 1.577299 7.218797 6.421075 6.917812 \n", + " 1 O 0.967124 0.000000 0.967079 6.705939 5.803545 6.208087 \n", + " 2 H 1.577299 0.967079 0.000000 7.386560 6.398907 6.694051 \n", + " 3 H 7.218797 6.705939 7.386560 0.000000 1.219911 1.834165 \n", + " 4 O 6.421075 5.803545 6.398907 1.219911 0.000000 0.964351 \n", + " 5 H 6.917812 6.208087 6.694051 1.834165 0.964351 0.000000 \n", + " 6 H 8.808934 8.370442 9.087750 1.832394 2.974999 3.378532 \n", + " 7 O 8.054405 7.630222 8.370563 1.174736 2.394095 2.933298 \n", + " 8 H 8.457070 8.054618 8.809280 1.829743 2.963053 3.394330 \n", + " 9 H 3.394180 2.933258 3.378486 5.305736 4.469059 4.958895 \n", + " 10 O 2.962952 2.394096 2.975020 4.859962 3.973627 4.469031 \n", + " 11 H 1.829734 1.174748 1.832383 5.766083 4.859941 5.305701 \n", + " 12 Hg 4.599728 3.977575 4.580685 2.938915 1.987009 2.543865 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 8.808934 8.054405 8.457070 3.394180 2.962952 1.829734 4.599728 \n", + " 1 8.370442 7.630222 8.054618 2.933258 2.394096 1.174748 3.977575 \n", + " 2 9.087750 8.370563 8.809280 3.378486 2.975020 1.832383 4.580685 \n", + " 3 1.832394 1.174736 1.829743 5.305736 4.859962 5.766083 2.938915 \n", + " 4 2.974999 2.394095 2.963053 4.469059 3.973627 4.859941 1.987009 \n", + " 5 3.378532 2.933298 3.394330 4.958895 4.469031 5.305701 2.543865 \n", + " 6 0.000000 0.967079 1.577287 6.693803 6.398709 7.386382 4.580490 \n", + " 7 0.967079 0.000000 0.967124 6.208004 5.803492 6.705893 3.977494 \n", + " 8 1.577287 0.967124 0.000000 6.917879 6.421192 7.218944 4.599815 \n", + " 9 6.693803 6.208004 6.917879 0.000000 0.964351 1.834148 2.543864 \n", + " 10 6.398709 5.803492 6.421192 0.964351 0.000000 1.219899 1.987009 \n", + " 11 7.386382 6.705893 7.218944 1.834148 1.219899 0.000000 2.938923 \n", + " 12 4.580490 3.977494 4.599815 2.543864 1.987009 2.938923 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s14.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.911607 4.567958 4.544596 2.081576 2.809599 \n", + " 1 O 3.911607 0.000000 0.964913 0.964599 5.823739 6.451324 \n", + " 2 H 4.567958 0.964913 0.000000 1.537068 6.523194 7.223649 \n", + " 3 H 4.544596 0.964599 1.537068 0.000000 6.375339 6.895762 \n", + " 4 O 2.081576 5.823739 6.523194 6.375339 0.000000 1.047824 \n", + " 5 H 2.809599 6.451324 7.223649 6.895762 1.047824 0.000000 \n", + " 6 H 2.612351 6.409536 7.021367 7.047675 0.964574 1.659514 \n", + " 7 O 2.110904 2.572244 3.120265 3.190163 4.156326 4.730004 \n", + " 8 H 2.734898 1.569845 2.175077 2.205743 4.777682 5.373520 \n", + " 9 H 2.728782 3.122510 3.649680 3.554848 4.619915 5.038344 \n", + " 10 O 2.470439 5.339532 5.633629 6.203146 2.997075 3.963017 \n", + " 11 H 3.120364 5.860243 6.076987 6.739540 3.663104 4.531017 \n", + " 12 H 3.097572 5.450285 5.638308 6.352812 3.599304 4.618915 \n", + " 13 O 2.398329 2.921096 3.511232 3.529239 3.600411 4.376829 \n", + " 14 H 3.005987 2.099938 2.672115 2.674046 4.468712 5.194833 \n", + " 15 H 3.085552 3.649103 4.213507 4.140996 3.799193 4.526293 \n", + " 16 O 4.014090 7.405870 8.247843 7.715008 2.472706 1.426699 \n", + " 17 H 4.617279 8.098887 8.925886 8.415504 3.119904 2.107980 \n", + " 18 H 4.682510 7.891367 8.757158 8.147135 3.050794 2.077077 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.612351 2.110904 2.734898 2.728782 2.470439 3.120364 3.097572 \n", + " 1 6.409536 2.572244 1.569845 3.122510 5.339532 5.860243 5.450285 \n", + " 2 7.021367 3.120265 2.175077 3.649680 5.633629 6.076987 5.638308 \n", + " 3 7.047675 3.190163 2.205743 3.554848 6.203146 6.739540 6.352812 \n", + " 4 0.964574 4.156326 4.777682 4.619915 2.997075 3.663104 3.599304 \n", + " 5 1.659514 4.730004 5.373520 5.038344 3.963017 4.531017 4.618915 \n", + " 6 0.000000 4.661996 5.336626 5.147442 2.628535 3.206261 3.196305 \n", + " 7 4.661996 0.000000 1.011449 0.963858 3.676795 4.007772 4.193946 \n", + " 8 5.336626 1.011449 0.000000 1.622459 4.300808 4.720197 4.646314 \n", + " 9 5.147442 0.963858 1.622459 0.000000 4.320258 4.509154 4.942769 \n", + " 10 2.628535 3.676795 4.300808 4.320258 0.000000 0.963449 0.963393 \n", + " 11 3.206261 4.007772 4.720197 4.509154 0.963449 0.000000 1.535765 \n", + " 12 3.196305 4.193946 4.646314 4.942769 0.963393 1.535765 0.000000 \n", + " 13 4.112314 3.052493 2.821507 3.950835 3.652482 4.511193 3.644877 \n", + " 14 5.016595 2.994046 2.452040 3.861925 4.324839 5.102720 4.292109 \n", + " 15 4.290666 3.993275 3.743630 4.869060 4.172201 5.093836 4.050460 \n", + " 16 2.988391 5.706214 6.336748 5.846829 5.348347 5.843061 6.036336 \n", + " 17 3.460327 6.208950 6.924513 6.239178 5.775628 6.138595 6.529206 \n", + " 18 3.552119 6.414564 6.955445 6.606932 6.022625 6.589862 6.623924 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.398329 3.005987 3.085552 4.014090 4.617279 4.682510 \n", + " 1 2.921096 2.099938 3.649103 7.405870 8.098887 7.891367 \n", + " 2 3.511232 2.672115 4.213507 8.247843 8.925886 8.757158 \n", + " 3 3.529239 2.674046 4.140996 7.715008 8.415504 8.147135 \n", + " 4 3.600411 4.468712 3.799193 2.472706 3.119904 3.050794 \n", + " 5 4.376829 5.194833 4.526293 1.426699 2.107980 2.077077 \n", + " 6 4.112314 5.016595 4.290666 2.988391 3.460327 3.552119 \n", + " 7 3.052493 2.994046 3.993275 5.706214 6.208950 6.414564 \n", + " 8 2.821507 2.452040 3.743630 6.336748 6.924513 6.955445 \n", + " 9 3.950835 3.861925 4.869060 5.846829 6.239178 6.606932 \n", + " 10 3.652482 4.324839 4.172201 5.348347 5.775628 6.022625 \n", 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3.427822 2.016948 0.963045 0.000000 \n", + " 6 H 6.463068 2.998330 3.531571 1.992393 0.963553 1.558039 \n", + " 7 O 3.569892 4.603894 4.872640 5.026189 5.813476 6.012743 \n", + " 8 H 4.209488 5.090425 5.442075 5.333190 5.926558 6.041440 \n", + " 9 H 4.209742 5.051045 5.149275 5.524496 6.353665 6.471443 \n", + " 10 O 1.940019 2.570724 3.052062 3.266911 4.341371 4.904211 \n", + " 11 H 2.433693 3.194342 3.575407 3.759799 4.721721 5.125643 \n", + " 12 H 3.219056 1.012534 1.636129 1.810745 3.043396 3.657787 \n", + " 13 O 2.074755 6.010427 6.477640 6.775251 7.779505 8.541427 \n", + " 14 H 2.709491 6.597995 6.957204 7.442995 8.520025 9.266793 \n", + " 15 H 2.710010 6.635698 7.188780 7.304896 8.204425 8.968912 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.463068 3.569892 4.209488 4.209742 1.940019 2.433693 3.219056 \n", + " 1 2.998330 4.603894 5.090425 5.051045 2.570724 3.194342 1.012534 \n", + " 2 3.531571 4.872640 5.442075 5.149275 3.052062 3.575407 1.636129 \n", + " 3 1.992393 5.026189 5.333190 5.524496 3.266911 3.759799 1.810745 \n", + " 4 0.963553 5.813476 5.926558 6.353665 4.341371 4.721721 3.043396 \n", + " 5 1.558039 6.012743 6.041440 6.471443 4.904211 5.125643 3.657787 \n", + " 6 0.000000 6.688865 6.806986 7.262399 5.029723 5.515529 3.702116 \n", + " 7 6.688865 0.000000 0.961540 0.961607 2.611300 1.617491 3.717503 \n", + " 8 6.806986 0.961540 0.000000 1.535213 3.252399 2.292408 4.252757 \n", + " 9 7.262399 0.961607 1.535213 0.000000 3.251476 2.292927 4.232339 \n", + " 10 5.029723 2.611300 3.252399 3.251476 0.000000 1.000115 1.559588 \n", + " 11 5.515529 1.617491 2.292408 2.292927 1.000115 0.000000 2.224443 \n", + " 12 3.702116 3.717503 4.252757 4.232339 1.559588 2.224443 0.000000 \n", + " 13 8.181322 5.291094 5.863985 5.864664 4.013152 4.441532 5.185158 \n", + " 14 8.943446 5.708719 6.350132 6.156515 4.599167 4.970060 5.780984 \n", + " 15 8.576183 5.699872 6.146783 6.340480 4.600577 4.966455 5.801149 \n", + " \n", + " 13 14 15 \n", + " 0 2.074755 2.709491 2.710010 \n", + " 1 6.010427 6.597995 6.635698 \n", + " 2 6.477640 6.957204 7.188780 \n", + " 3 6.775251 7.442995 7.304896 \n", + " 4 7.779505 8.520025 8.204425 \n", + " 5 8.541427 9.266793 8.968912 \n", + " 6 8.181322 8.943446 8.576183 \n", + " 7 5.291094 5.708719 5.699872 \n", + " 8 5.863985 6.350132 6.146783 \n", + " 9 5.864664 6.156515 6.340480 \n", + " 10 4.013152 4.599167 4.600577 \n", + " 11 4.441532 4.970060 4.966455 \n", + " 12 5.185158 5.780984 5.801149 \n", + " 13 0.000000 0.967856 0.967821 \n", + " 14 0.967856 0.000000 1.576555 \n", + " 15 0.967821 1.576555 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.088069 2.695708 2.695708\n", + " 1 O 2.088069 0.000000 0.980959 0.980959\n", + " 2 H 2.695708 0.980959 0.000000 1.597566\n", + " 3 H 2.695708 0.980959 1.597566 0.000000,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w4s1.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.965709 1.559621 5.105659 4.320775 4.369701 \n", + " 1 O 0.965709 0.000000 0.965718 4.766496 4.032454 4.293446 \n", + " 2 H 1.559621 0.965718 0.000000 5.424548 4.783985 5.116293 \n", + " 3 H 5.105659 4.766496 5.424548 0.000000 0.966292 1.559488 \n", + " 4 O 4.320775 4.032454 4.783985 0.966292 0.000000 0.966342 \n", + " 5 H 4.369701 4.293446 5.116293 1.559488 0.966342 0.000000 \n", + " 6 H 4.694832 3.865042 3.718795 4.185887 4.202459 5.016431 \n", + " 7 O 4.215779 3.313975 3.267363 4.046108 3.885050 4.718437 \n", + " 8 H 4.936178 3.991390 3.901786 4.633590 4.506504 5.393598 \n", + " 9 H 4.980036 4.439271 5.121325 4.135669 3.529142 4.051160 \n", + " 10 O 4.172705 3.564147 4.195725 4.142730 3.460508 4.020855 \n", + " 11 H 4.189637 3.639880 4.216075 5.044847 4.299835 4.762901 \n", + " 12 Hg 2.904143 2.238551 2.868114 2.861925 2.218210 2.862126 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 4.694832 4.215779 4.936178 4.980036 4.172705 4.189637 2.904143 \n", + " 1 3.865042 3.313975 3.991390 4.439271 3.564147 3.639880 2.238551 \n", + " 2 3.718795 3.267363 3.901786 5.121325 4.195725 4.216075 2.868114 \n", + " 3 4.185887 4.046108 4.633590 4.135669 4.142730 5.044847 2.861925 \n", + " 4 4.202459 3.885050 4.506504 3.529142 3.460508 4.299835 2.218210 \n", + " 5 5.016431 4.718437 5.393598 4.051160 4.020855 4.762901 2.862126 \n", + " 6 0.000000 0.965491 1.555526 5.127754 4.506629 5.105597 2.930335 \n", + " 7 0.965491 0.000000 0.965806 4.274421 3.603040 4.160216 2.269039 \n", + " 8 1.555526 0.965806 0.000000 4.261417 3.651094 4.150162 2.904464 \n", + " 9 5.127754 4.274421 4.261417 0.000000 0.965116 1.556073 2.927994 \n", + " 10 4.506629 3.603040 3.651094 0.965116 0.000000 0.965178 2.274211 \n", + " 11 5.105597 4.160216 4.150162 1.556073 0.965178 0.000000 2.927581 \n", + " 12 2.930335 2.269039 2.904464 2.927994 2.274211 2.927581 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w3s3.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.054280 2.693950 2.693968 1.968084 3.140470 2.482327 \n", + " 1 O 2.054280 0.000000 0.970198 0.970199 4.020738 5.105593 4.480798 \n", + " 2 H 2.693950 0.970198 0.000000 1.583416 4.610901 5.711600 5.016351 \n", + " 3 H 2.693968 0.970199 1.583416 0.000000 4.610954 5.711631 5.016418 \n", + " 4 O 1.968084 4.020738 4.610901 4.610954 0.000000 1.418617 0.966411 \n", + " 5 H 3.140470 5.105593 5.711600 5.711631 1.418617 0.000000 2.012383 \n", + " 6 H 2.482327 4.480798 5.016351 5.016418 0.966411 2.012383 0.000000 \n", + " 7 O 4.105091 5.987697 6.594065 6.594005 2.478923 1.060771 3.013311 \n", + " 8 H 4.696364 6.580266 7.089470 7.265630 3.030579 1.716981 3.440416 \n", + " 9 H 4.696079 6.580018 7.265446 7.089136 3.030305 1.716943 3.440038 \n", + " \n", + " 7 8 9 \n", + " 0 4.105091 4.696364 4.696079 \n", + " 1 5.987697 6.580266 6.580018 \n", + " 2 6.594065 7.089470 7.265446 \n", + " 3 6.594005 7.265630 7.089136 \n", + " 4 2.478923 3.030579 3.030305 \n", + " 5 1.060771 1.716981 1.716943 \n", + " 6 3.013311 3.440416 3.440038 \n", + " 7 0.000000 0.971202 0.971204 \n", + " 8 0.971202 0.000000 1.597698 \n", + " 9 0.971204 1.597698 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.018423 2.838226 2.555233 2.015239 2.838547 \n", + " 1 O 2.018423 0.000000 1.094545 0.964874 4.026037 4.745003 \n", + " 2 H 2.838226 1.094545 0.000000 1.727070 4.748723 5.307814 \n", + " 3 H 2.555233 0.964874 1.727070 0.000000 4.539970 5.389264 \n", + " 4 O 2.015239 4.026037 4.748723 4.539970 0.000000 1.112704 \n", + " 5 H 2.838547 4.745003 5.307814 5.389264 1.112704 0.000000 \n", + " 6 H 2.597164 4.588640 5.430332 4.950695 0.963486 1.733327 \n", + " 7 O 2.536790 2.966558 4.032935 2.555652 3.664160 4.757762 \n", + " 8 H 3.195726 3.536894 4.610765 3.067382 4.188049 5.257245 \n", + " 9 H 3.198061 3.623027 4.622592 3.120634 4.122435 5.231791 \n", + " 10 O 3.957622 5.711906 6.111410 6.453180 2.408171 1.296399 \n", + " 11 H 4.598550 6.351437 6.706707 7.080224 2.989424 1.953217 \n", + " 12 H 4.572529 6.298611 6.711788 7.044142 3.022299 1.964133 \n", + " 13 O 3.990626 2.418990 1.325680 2.965802 5.753284 6.143805 \n", + " 14 H 4.634273 2.997726 1.980997 3.487973 6.394365 6.743310 \n", + " 15 H 4.604767 3.044518 1.997890 3.436760 6.340064 6.740849 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.597164 2.536790 3.195726 3.198061 3.957622 4.598550 4.572529 \n", + " 1 4.588640 2.966558 3.536894 3.623027 5.711906 6.351437 6.298611 \n", + " 2 5.430332 4.032935 4.610765 4.622592 6.111410 6.706707 6.711788 \n", + " 3 4.950695 2.555652 3.067382 3.120634 6.453180 7.080224 7.044142 \n", + " 4 0.963486 3.664160 4.188049 4.122435 2.408171 2.989424 3.022299 \n", + " 5 1.733327 4.757762 5.257245 5.231791 1.296399 1.953217 1.964133 \n", + " 6 0.000000 3.553133 3.954325 3.915727 2.941889 3.446855 3.410609 \n", + " 7 3.553133 0.000000 0.963799 0.963733 6.036269 6.623522 6.573200 \n", + " 8 3.954325 0.963799 0.000000 1.533718 6.525348 7.177191 6.952794 \n", + " 9 3.915727 0.963733 1.533718 0.000000 6.520196 7.004227 7.118172 \n", + " 10 2.941889 6.036269 6.525348 6.520196 0.000000 0.964718 0.964496 \n", + " 11 3.446855 6.623522 7.177191 7.004227 0.964718 0.000000 1.561874 \n", + " 12 3.410609 6.573200 6.952794 7.118172 0.964496 1.561874 0.000000 \n", + " 13 6.525889 5.349812 5.927382 5.899262 6.754558 7.291734 7.345656 \n", + " 14 7.161409 5.930012 6.396574 6.549582 7.298457 7.893927 7.801002 \n", + " 15 7.109709 5.822745 6.465729 6.248398 7.340778 7.788417 7.999081 \n", + " \n", + " 13 14 15 \n", + " 0 3.990626 4.634273 4.604767 \n", + " 1 2.418990 2.997726 3.044518 \n", + " 2 1.325680 1.980997 1.997890 \n", + " 3 2.965802 3.487973 3.436760 \n", + " 4 5.753284 6.394365 6.340064 \n", + " 5 6.143805 6.743310 6.740849 \n", + " 6 6.525889 7.161409 7.109709 \n", + " 7 5.349812 5.930012 5.822745 \n", + " 8 5.927382 6.396574 6.465729 \n", + " 9 5.899262 6.549582 6.248398 \n", + " 10 6.754558 7.298457 7.340778 \n", + " 11 7.291734 7.893927 7.788417 \n", + " 12 7.345656 7.801002 7.999081 \n", + " 13 0.000000 0.964232 0.963905 \n", + " 14 0.964232 0.000000 1.558547 \n", + " 15 0.963905 1.558547 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w3s1.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 3.597846 4.237478 4.237535 1.978040 3.061007 2.528261 \n", + " 1 O 3.597846 0.000000 0.964088 0.964088 2.469570 3.474942 1.411067 \n", + " 2 H 4.237478 0.964088 0.000000 1.552652 3.097633 3.981363 2.091525 \n", + " 3 H 4.237535 0.964088 1.552652 0.000000 3.097658 3.981478 2.091532 \n", + " 4 O 1.978040 2.469570 3.097633 3.097658 0.000000 1.416906 1.059088 \n", + " 5 H 3.061007 3.474942 3.981363 3.981478 1.416906 0.000000 2.183746 \n", + " 6 H 2.528261 1.411067 2.091525 2.091532 1.059088 2.183746 0.000000 \n", + " 7 O 3.996004 4.396710 4.833084 4.833183 2.477929 1.061399 3.192955 \n", + " 8 H 4.597574 4.707633 5.208097 4.964151 3.030268 1.718726 3.621786 \n", + " 9 H 4.597658 4.707678 4.964090 5.208210 3.030395 1.718732 3.621879 \n", + " \n", + " 7 8 9 \n", + " 0 3.996004 4.597574 4.597658 \n", + " 1 4.396710 4.707633 4.707678 \n", + " 2 4.833084 5.208097 4.964090 \n", + " 3 4.833183 4.964151 5.208210 \n", + " 4 2.477929 3.030268 3.030395 \n", + " 5 1.061399 1.718726 1.718732 \n", + " 6 3.192955 3.621786 3.621879 \n", + " 7 0.000000 0.971401 0.971400 \n", + " 8 0.971401 0.000000 1.598796 \n", + " 9 0.971400 1.598796 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 1.030114 1.736389 7.152502 6.773911 7.611893 \n", + " 1 O 1.030114 0.000000 1.030169 6.670126 6.182342 6.941156 \n", + " 2 H 1.736389 1.030169 0.000000 7.372435 6.790340 7.447022 \n", + " 3 H 7.152502 6.670126 7.372435 0.000000 0.963621 1.688890 \n", + " 4 O 6.773911 6.182342 6.790340 0.963621 0.000000 1.074593 \n", + " 5 H 7.611893 6.941156 7.447022 1.688890 1.074593 0.000000 \n", + " 6 H 3.666295 3.218881 3.679996 4.923980 4.409355 5.030161 \n", + " 7 O 3.273467 2.704242 3.273215 4.507457 3.969961 4.672190 \n", + " 8 H 1.693459 0.986720 1.693779 5.844748 5.338472 6.086864 \n", + " 9 H 3.692464 3.095814 2.136506 8.897505 8.202245 8.694943 \n", + " 10 O 3.103123 2.502006 1.473354 8.457046 7.775144 8.296293 \n", + " 11 H 3.608824 3.170471 2.171834 9.167342 8.476491 8.971588 \n", + " 12 H 2.172101 3.170726 3.608609 8.675965 8.442009 9.346814 \n", + " 13 O 1.473622 2.502204 3.104043 7.974351 7.738001 8.657026 \n", + " 14 H 2.136804 3.096220 3.695413 8.332948 8.155067 9.108550 \n", + " 15 H 9.209754 8.426307 8.782569 3.491766 3.019272 2.018509 \n", + " 16 O 8.709274 7.961523 8.350735 2.957596 2.436020 1.362756 \n", + " 17 H 9.400371 8.680267 9.073547 3.432974 3.068105 2.037856 \n", + " 18 Hg 4.926472 4.334810 4.942384 2.613719 2.020354 2.777119 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.666295 3.273467 1.693459 3.692464 3.103123 3.608824 2.172101 \n", + " 1 3.218881 2.704242 0.986720 3.095814 2.502006 3.170471 3.170726 \n", + " 2 3.679996 3.273215 1.693779 2.136506 1.473354 2.171834 3.608609 \n", + " 3 4.923980 4.507457 5.844748 8.897505 8.457046 9.167342 8.675965 \n", + " 4 4.409355 3.969961 5.338472 8.202245 7.775144 8.476491 8.442009 \n", + " 5 5.030161 4.672190 6.086864 8.694943 8.296293 8.971588 9.346814 \n", + " 6 0.000000 0.963879 2.275165 5.481810 4.679982 5.052748 5.027258 \n", + " 7 0.963879 0.000000 1.718196 5.083394 4.384176 4.923708 4.925922 \n", + " 8 2.275165 1.718196 0.000000 3.716529 3.041757 3.666145 3.666767 \n", + " 9 5.481810 5.083394 3.716529 0.000000 0.961512 1.546627 5.231482 \n", + " 10 4.679982 4.384176 3.041757 0.961512 0.000000 0.961094 4.633168 \n", + " 11 5.052748 4.923708 3.666145 1.546627 0.961094 0.000000 4.783142 \n", + " 12 5.027258 4.925922 3.666767 5.231482 4.633168 4.783142 0.000000 \n", + " 13 4.651712 4.383241 3.040709 4.835056 4.296885 4.635342 0.961113 \n", + " 14 5.450003 5.079756 3.714292 5.229187 4.838356 5.238240 1.546525 \n", + " 15 6.712439 6.343222 7.637173 9.677469 9.408978 10.088281 11.089807 \n", + " 16 5.979335 5.698833 7.113904 9.391774 9.035515 9.673919 10.510613 \n", + " 17 6.443270 6.282622 7.793622 10.160124 9.756317 10.345827 11.122607 \n", + " 18 2.445823 1.951485 3.422060 6.533659 5.987950 6.630248 6.599366 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.473622 2.136804 9.209754 8.709274 9.400371 4.926472 \n", + " 1 2.502204 3.096220 8.426307 7.961523 8.680267 4.334810 \n", + " 2 3.104043 3.695413 8.782569 8.350735 9.073547 4.942384 \n", + " 3 7.974351 8.332948 3.491766 2.957596 3.432974 2.613719 \n", + " 4 7.738001 8.155067 3.019272 2.436020 3.068105 2.020354 \n", + " 5 8.657026 9.108550 2.018509 1.362756 2.037856 2.777119 \n", + " 6 4.651712 5.450003 6.712439 5.979335 6.443270 2.445823 \n", + " 7 4.383241 5.079756 6.343222 5.698833 6.282622 1.951485 \n", + " 8 3.040709 3.714292 7.637173 7.113904 7.793622 3.422060 \n", + " 9 4.835056 5.229187 9.677469 9.391774 10.160124 6.533659 \n", + " 10 4.296885 4.838356 9.408978 9.035515 9.756317 5.987950 \n", + " 11 4.635342 5.238240 10.088281 9.673919 10.345827 6.630248 \n", + " 12 0.961113 1.546525 11.089807 10.510613 11.122607 6.599366 \n", + " 13 0.000000 0.961536 10.369046 9.835882 10.492360 5.953846 \n", + " 14 0.961536 0.000000 10.801327 10.319774 11.012207 6.491879 \n", + " 15 10.369046 10.801327 0.000000 0.963515 1.555216 4.588168 \n", + " 16 9.835882 10.319774 0.963515 0.000000 0.963246 3.931201 \n", + " 17 10.492360 11.012207 1.555216 0.963246 0.000000 4.540883 \n", + " 18 5.953846 6.491879 4.588168 3.931201 4.540883 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.963419 1.561150 9.250889 8.630834 9.222104 \n", + " 1 O 0.963419 0.000000 0.963806 8.540886 7.907355 8.494845 \n", + " 2 H 1.561150 0.963806 0.000000 9.011765 8.362279 8.920985 \n", + " 3 H 9.250889 8.540886 9.011765 0.000000 0.963864 1.705235 \n", + " 4 O 8.630834 7.907355 8.362279 0.963864 0.000000 1.089870 \n", + " 5 H 9.222104 8.494845 8.920985 1.705235 1.089870 0.000000 \n", + " 6 H 1.991570 1.312140 1.969014 7.451065 6.894901 7.584541 \n", + " 7 O 3.052567 2.415983 2.988383 6.562312 6.091649 6.875468 \n", + " 8 H 3.419885 2.965602 3.527912 6.860407 6.508524 7.380158 \n", + " 9 H 10.471910 9.699390 10.002288 3.470628 3.004509 1.990238 \n", + " 10 O 10.009132 9.284249 9.669846 2.947147 2.423048 1.334323 \n", + " 11 H 10.673724 9.993426 10.426987 3.417317 3.048204 2.006468 \n", + " 12 H 3.631649 3.022080 3.682382 5.735372 5.239238 6.009445 \n", + " 13 O 4.900711 4.349639 5.045265 4.502553 3.970613 4.697109 \n", + " 14 H 4.977362 4.586397 5.387271 4.926522 4.411918 5.058251 \n", + " 15 Hg 6.720285 6.060009 6.616900 2.603907 2.013587 2.794911 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 1.991570 3.052567 3.419885 10.471910 10.009132 10.673724 3.631649 \n", + " 1 1.312140 2.415983 2.965602 9.699390 9.284249 9.993426 3.022080 \n", + " 2 1.969014 2.988383 3.527912 10.002288 9.669846 10.426987 3.682382 \n", + " 3 7.451065 6.562312 6.860407 3.470628 2.947147 3.417317 5.735372 \n", + " 4 6.894901 6.091649 6.508524 3.004509 2.423048 3.048204 5.239238 \n", + " 5 7.584541 6.875468 7.380158 1.990238 1.334323 2.006468 6.009445 \n", + " 6 0.000000 1.105404 1.737558 8.943087 8.495401 9.211559 1.813161 \n", + " 7 1.105404 0.000000 0.964377 8.359630 7.892248 8.611155 1.003836 \n", + " 8 1.737558 0.964377 0.000000 8.972901 8.480316 9.178112 1.626296 \n", + " 9 8.943087 8.359630 8.972901 0.000000 0.963999 1.557938 7.556824 \n", + " 10 8.495401 7.892248 8.480316 0.963999 0.000000 0.963756 7.029557 \n", + " 11 9.211559 8.611155 9.178112 1.557938 0.963756 0.000000 7.707979 \n", + " 12 1.813161 1.003836 1.626296 7.556824 7.029557 7.707979 0.000000 \n", + " 13 3.307392 2.611755 3.088057 6.358343 5.715472 6.301271 1.608703 \n", + " 14 3.670921 3.133311 3.533840 6.734953 6.002716 6.470209 2.178256 \n", + " 15 5.025843 4.243617 4.686955 4.587272 3.934041 4.543448 3.320361 \n", + " \n", + " 13 14 15 \n", + " 0 4.900711 4.977362 6.720285 \n", + " 1 4.349639 4.586397 6.060009 \n", + " 2 5.045265 5.387271 6.616900 \n", + " 3 4.502553 4.926522 2.603907 \n", + " 4 3.970613 4.411918 2.013587 \n", + " 5 4.697109 5.058251 2.794911 \n", + " 6 3.307392 3.670921 5.025843 \n", + " 7 2.611755 3.133311 4.243617 \n", + " 8 3.088057 3.533840 4.686955 \n", + " 9 6.358343 6.734953 4.587272 \n", + " 10 5.715472 6.002716 3.934041 \n", + " 11 6.301271 6.470209 4.543448 \n", + " 12 1.608703 2.178256 3.320361 \n", + " 13 0.000000 0.963989 1.958448 \n", + " 14 0.963989 0.000000 2.456952 \n", + " 15 1.958448 2.456952 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s22.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.104208 2.698911 2.734983 2.380148 3.001902 \n", + " 1 O 2.104208 0.000000 0.963723 1.053213 3.776559 3.998576 \n", + " 2 H 2.698911 0.963723 0.000000 1.661431 4.511961 4.677319 \n", + " 3 H 2.734983 1.053213 1.661431 0.000000 4.311608 4.583880 \n", + " 4 O 2.380148 3.776559 4.511961 4.311608 0.000000 0.964516 \n", + " 5 H 3.001902 3.998576 4.677319 4.583880 0.964516 0.000000 \n", + " 6 H 3.002222 4.384086 5.208069 4.739259 0.964222 1.541693 \n", + " 7 O 3.802365 2.454544 2.991706 1.406094 5.152665 5.467808 \n", + " 8 H 4.032518 3.071548 3.604080 2.086338 5.484095 5.935640 \n", + " 9 H 4.682204 3.101586 3.489804 2.087298 5.918892 6.132441 \n", + " 10 O 2.306294 3.536477 4.230046 3.480372 3.590817 4.459457 \n", + " 11 H 2.966885 3.652315 4.324033 3.319210 4.362376 5.166277 \n", + " 12 H 2.938845 4.406982 5.035314 4.410200 4.037644 4.971422 \n", + " 13 O 4.356324 4.267812 4.842055 3.538247 5.791563 6.478800 \n", + " 14 H 5.015188 4.984948 5.635542 4.206455 6.140762 6.816892 \n", + " 15 H 4.945868 4.813987 5.246351 4.105893 6.582807 7.295959 \n", + " 16 O 2.218353 4.181273 4.507782 4.909128 2.961114 3.649054 \n", + " 17 H 2.782155 4.740232 5.118193 5.501187 2.699276 3.288800 \n", + " 18 H 2.868701 4.613722 4.756592 5.394119 3.864852 4.471681 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.002222 3.802365 4.032518 4.682204 2.306294 2.966885 2.938845 \n", + " 1 4.384086 2.454544 3.071548 3.101586 3.536477 3.652315 4.406982 \n", + " 2 5.208069 2.991706 3.604080 3.489804 4.230046 4.324033 5.035314 \n", + " 3 4.739259 1.406094 2.086338 2.087298 3.480372 3.319210 4.410200 \n", + " 4 0.964222 5.152665 5.484095 5.918892 3.590817 4.362376 4.037644 \n", + " 5 1.541693 5.467808 5.935640 6.132441 4.459457 5.166277 4.971422 \n", + " 6 0.000000 5.356761 5.592449 6.115821 3.603674 4.331282 3.975550 \n", + " 7 5.356761 0.000000 0.970730 0.961489 3.773486 3.273731 4.689803 \n", + " 8 5.592449 0.970730 0.000000 1.579008 3.440980 2.736579 4.272458 \n", + " 9 6.115821 0.961489 1.579008 0.000000 4.723219 4.178566 5.632255 \n", + " 10 3.603674 3.773486 3.440980 4.723219 0.000000 0.985937 0.962076 \n", + " 11 4.331282 3.273731 2.736579 4.178566 0.985937 0.000000 1.577843 \n", 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3.254802 4.495646 \n", + " 7 2.827235 3.316469 3.422927 5.963569 6.560488 6.508109 \n", + " 8 1.919952 2.428657 2.485132 6.058654 6.713833 6.592751 \n", + " 9 3.478570 3.845762 3.983097 6.868132 7.445879 7.396838 \n", + " 10 2.728252 3.238218 3.305482 3.334153 3.956600 3.983750 \n", + " 11 1.747430 2.305938 2.348640 4.252389 4.917299 4.836944 \n", + " 12 3.225510 3.650577 3.642418 3.325474 3.929129 3.901824 \n", + " 13 0.000000 0.964683 0.964376 5.913053 6.610218 6.435352 \n", + " 14 0.964683 0.000000 1.530772 6.542335 7.163803 7.135910 \n", + " 15 0.964376 1.530772 0.000000 6.357877 7.128602 6.767374 \n", + " 16 5.913053 6.542335 6.357877 0.000000 0.965809 0.965528 \n", + " 17 6.610218 7.163803 7.128602 0.965809 0.000000 1.561454 \n", + " 18 6.435352 7.135910 6.767374 0.965528 1.561454 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s23.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.306385 2.938482 2.967068 3.802053 4.032820 \n", + " 1 O 2.306385 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O 4.356836 2.728526 3.225676 1.747703 2.826940 1.919870 \n", + " 17 H 4.946420 3.305193 3.641420 2.348460 3.423139 2.485303 \n", + " 18 H 5.015582 3.238841 3.651760 2.306467 3.315994 2.428561 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.681619 2.379711 3.002053 3.001765 2.104192 2.734859 2.699043 \n", + " 1 4.723055 3.588640 4.458114 3.600929 3.536251 3.480123 4.229461 \n", + " 2 5.631899 4.036038 4.970290 3.973886 4.405982 4.409356 5.033529 \n", + " 3 4.178359 4.359921 5.164882 4.327889 3.652081 3.318904 4.323546 \n", + " 4 0.961495 5.151825 5.468833 5.355160 2.454591 1.406196 2.992007 \n", + " 5 1.578995 5.483315 5.936581 5.590792 3.071656 2.086411 3.604069 \n", + " 6 0.000000 5.918370 6.133862 6.114728 3.101014 2.086811 3.489309 \n", + " 7 5.918370 0.000000 0.964520 0.964224 3.778310 4.312277 4.514268 \n", + " 8 6.133862 0.964520 0.000000 1.541662 4.002185 4.586477 4.681709 \n", + " 9 6.114728 0.964224 1.541662 0.000000 4.385443 4.739428 5.209847 \n", + " 10 3.101014 3.778310 4.002185 4.385443 0.000000 1.053188 0.963719 \n", + " 11 2.086811 4.312277 4.586477 4.739428 1.053188 0.000000 1.661481 \n", + " 12 3.489309 4.514268 4.681709 5.209847 0.963719 1.661481 0.000000 \n", + " 13 6.867798 2.960737 3.648043 3.544652 4.181363 4.909161 4.507841 \n", + " 14 7.445688 2.699032 3.287641 3.254666 4.741274 5.501735 5.119594 \n", + " 15 7.396708 3.864325 4.470365 4.495494 4.613448 5.394136 4.756159 \n", + " 16 3.478536 5.789421 6.477982 5.719596 4.267861 3.538178 4.841942 \n", + " 17 3.983501 6.580648 7.295241 6.558686 4.814101 4.105996 5.246302 \n", + " 18 3.845746 6.138174 6.815449 5.923927 4.984999 4.206368 5.635443 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.218668 2.782591 2.869069 4.356836 4.946420 5.015582 \n", + " 1 3.334047 3.955490 3.984507 2.728526 3.305193 3.238841 \n", + " 2 3.324634 3.927414 3.901645 3.225676 3.641420 3.651760 \n", + " 3 4.252559 4.916401 4.838180 1.747703 2.348460 2.306467 \n", + " 4 5.963479 6.560372 6.508412 2.826940 3.423139 3.315994 \n", + " 5 6.059085 6.713985 6.593762 1.919870 2.485303 2.428561 \n", + " 6 6.867798 7.445688 7.396708 3.478536 3.983501 3.845746 \n", + " 7 2.960737 2.699032 3.864325 5.789421 6.580648 6.138174 \n", + " 8 3.648043 3.287641 4.470365 6.477982 7.295241 6.815449 \n", + " 9 3.544652 3.254666 4.495494 5.719596 6.558686 5.923927 \n", + " 10 4.181363 4.741274 4.613448 4.267861 4.814101 4.984999 \n", + " 11 4.909161 5.501735 5.394136 3.538178 4.105996 4.206368 \n", + " 12 4.507841 5.119594 4.756159 4.841942 5.246302 5.635443 \n", + " 13 0.000000 0.965795 0.965522 5.913672 6.358353 6.542937 \n", + " 14 0.965795 0.000000 1.561418 6.609841 7.128090 7.163194 \n", + " 15 0.965522 1.561418 0.000000 6.437130 6.769191 7.137686 \n", + " 16 5.913672 6.609841 6.437130 0.000000 0.964374 0.964679 \n", + " 17 6.358353 7.128090 6.769191 0.964374 0.000000 1.530766 \n", + " 18 6.542937 7.163194 7.137686 0.964679 1.530766 0.000000 ,\n", + " 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8.765481 2.949508 2.423160 1.334301 \n", + " 14 H 8.787121 8.567355 9.460937 3.421403 3.048980 2.006850 \n", + " 15 Hg 4.704267 4.244219 5.011193 2.604835 2.013146 2.794228 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.531045 2.966897 3.423253 3.538524 3.083594 1.626411 8.468866 \n", + " 1 2.990311 2.416781 3.054769 3.131963 2.610179 1.004084 8.300081 \n", + " 2 1.971838 1.314312 1.994741 3.663141 3.307007 1.812241 9.257963 \n", + " 3 8.563775 8.169752 8.919219 4.922633 4.505751 5.748497 3.473756 \n", + " 4 8.325344 7.876477 8.603184 4.411030 3.970463 5.238861 3.005467 \n", + " 5 9.255309 8.772165 9.470936 5.062043 4.694555 5.996266 1.990666 \n", + " 6 0.000000 0.963825 1.560883 5.374798 5.047863 3.683450 10.869315 \n", + " 7 0.963825 0.000000 0.963426 4.574869 4.351920 3.022708 10.407619 \n", + " 8 1.560883 0.963426 0.000000 4.967090 4.902941 3.633337 11.112409 \n", + " 9 5.374798 4.574869 4.967090 0.000000 0.963957 2.176725 6.739359 \n", + " 10 5.047863 4.351920 4.902941 0.963957 0.000000 1.606964 6.348872 \n", + " 11 3.683450 3.022708 3.633337 2.176725 1.606964 0.000000 7.523246 \n", + " 12 10.869315 10.407619 11.112409 6.739359 6.348872 7.523246 0.000000 \n", + " 13 10.400791 9.886817 10.554638 6.008285 5.708417 7.001768 0.964059 \n", + " 14 11.105148 10.553453 11.185023 6.477352 6.296570 7.684130 1.557987 \n", + " 15 6.586526 6.033889 6.697503 2.456889 1.958720 3.319686 4.583337 \n", + " \n", + " 13 14 15 \n", + " 0 8.051481 8.787121 4.704267 \n", + " 1 7.842745 8.567355 4.244219 \n", + " 2 8.765481 9.460937 5.011193 \n", + " 3 2.949508 3.421403 2.604835 \n", + " 4 2.423160 3.048980 2.013146 \n", + " 5 1.334301 2.006850 2.794228 \n", + " 6 10.400791 11.105148 6.586526 \n", + " 7 9.886817 10.553453 6.033889 \n", + " 8 10.554638 11.185023 6.697503 \n", + " 9 6.008285 6.477352 2.456889 \n", + " 10 5.708417 6.296570 1.958720 \n", + " 11 7.001768 7.684130 3.319686 \n", + " 12 0.964059 1.557987 4.583337 \n", + " 13 0.000000 0.963806 3.931410 \n", + " 14 0.963806 0.000000 4.542874 \n", + " 15 3.931410 4.542874 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.977888 2.662241 2.658238 3.848990 4.484538 \n", + " 1 O 1.977888 0.000000 1.037559 1.038075 2.484301 3.128811 \n", + " 2 H 2.662241 1.037559 0.000000 1.758676 1.448487 2.129622 \n", + " 3 H 2.658238 1.038075 1.758676 0.000000 3.112658 3.615375 \n", + " 4 O 3.848990 2.484301 1.448487 3.112658 0.000000 0.962254 \n", + " 5 H 4.484538 3.128811 2.129622 3.615375 0.962254 0.000000 \n", + " 6 H 4.493018 3.082937 2.108854 3.657417 0.962559 1.546973 \n", + " 7 O 1.977890 3.955339 4.583216 4.562066 5.611208 6.208820 \n", + " 8 H 2.662283 4.583241 5.133815 5.177551 6.068181 6.545735 \n", + " 9 H 2.658227 4.562079 5.177545 5.195545 6.162204 6.847252 \n", + " 10 O 3.837427 5.562944 6.152872 6.193484 7.073951 7.846827 \n", + " 11 H 4.472193 6.156902 6.630935 6.876120 7.401325 8.171532 \n", + " 12 H 4.481761 6.182891 6.861457 6.704802 7.869543 8.653105 \n", + " 13 O 3.849065 5.611248 6.068077 6.162342 6.877193 7.193198 \n", + " 14 H 4.493222 6.234804 6.772881 6.671732 7.662547 7.957255 \n", + " 15 H 4.484474 6.208776 6.545553 6.847338 7.193128 7.467393 \n", + " 16 O 3.837682 2.483174 3.113130 1.447045 4.318074 4.679831 \n", + " 17 H 4.472830 3.130379 3.620964 2.130161 4.686141 4.864316 \n", + " 18 H 4.481635 3.083959 3.661389 2.109295 4.785888 5.207346 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.493018 1.977890 2.662283 2.658227 3.837427 4.472193 4.481761 \n", + " 1 3.082937 3.955339 4.583241 4.562079 5.562944 6.156902 6.182891 \n", + " 2 2.108854 4.583216 5.133815 5.177545 6.152872 6.630935 6.861457 \n", + " 3 3.657417 4.562066 5.177551 5.195545 6.193484 6.876120 6.704802 \n", + " 4 0.962559 5.611208 6.068181 6.162204 7.073951 7.401325 7.869543 \n", + " 5 1.546973 6.208820 6.545735 6.847252 7.846827 8.171532 8.653105 \n", + " 6 0.000000 6.234645 6.772896 6.671455 7.435059 7.706435 8.228369 \n", + " 7 6.234645 0.000000 1.037554 1.038086 2.483198 3.130056 3.084259 \n", + " 8 6.772896 1.037554 0.000000 1.758663 3.113120 3.620469 3.661717 \n", + " 9 6.671455 1.038086 1.758663 0.000000 1.447039 2.130087 2.109239 \n", + " 10 7.435059 2.483198 3.113120 1.447039 0.000000 0.962227 0.962534 \n", + " 11 7.706435 3.130056 3.620469 2.130087 0.962227 0.000000 1.547391 \n", + " 12 8.228369 3.084259 3.661717 2.109239 0.962534 1.547391 0.000000 \n", + " 13 7.662471 2.484347 1.448524 3.112635 4.318021 4.685357 4.786356 \n", + " 14 8.471822 3.083088 2.108849 3.657548 4.782073 5.209569 5.086176 \n", + " 15 7.957092 3.128656 2.129604 3.615028 4.679099 4.862731 5.207048 \n", + " 16 4.781634 5.563233 6.153420 6.193549 7.154566 7.925902 7.524614 \n", + " 17 5.209820 6.157563 6.631938 6.876514 7.926196 8.705545 8.297545 \n", + " 18 5.085110 6.182801 6.861667 6.704414 7.524116 8.296779 7.837824 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.849065 4.493222 4.484474 3.837682 4.472830 4.481635 \n", + " 1 5.611248 6.234804 6.208776 2.483174 3.130379 3.083959 \n", + " 2 6.068077 6.772881 6.545553 3.113130 3.620964 3.661389 \n", + " 3 6.162342 6.671732 6.847338 1.447045 2.130161 2.109295 \n", + " 4 6.877193 7.662547 7.193128 4.318074 4.686141 4.785888 \n", + " 5 7.193198 7.957255 7.467393 4.679831 4.864316 5.207346 \n", + " 6 7.662471 8.471822 7.957092 4.781634 5.209820 5.085110 \n", + " 7 2.484347 3.083088 3.128656 5.563233 6.157563 6.182801 \n", + " 8 1.448524 2.108849 2.129604 6.153420 6.631938 6.861667 \n", + " 9 3.112635 3.657548 3.615028 6.193549 6.876514 6.704414 \n", + " 10 4.318021 4.782073 4.679099 7.154566 7.926196 7.524116 \n", + " 11 4.685357 5.209569 4.862731 7.925902 8.705545 8.296779 \n", + " 12 4.786356 5.086176 5.207048 7.524614 8.297545 7.837824 \n", + " 13 0.000000 0.962559 0.962253 7.075033 7.402986 7.870357 \n", + " 14 0.962559 0.000000 1.546980 7.436393 7.708269 8.229549 \n", + " 15 0.962253 1.546980 0.000000 7.847881 8.173306 8.653798 \n", + " 16 7.075033 7.436393 7.847881 0.000000 0.962227 0.962534 \n", + " 17 7.402986 7.708269 8.173306 0.962227 0.000000 1.547384 \n", + " 18 7.870357 8.229549 8.653798 0.962534 1.547384 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.833012 4.492580 4.455221 3.876180 4.469248 \n", + " 1 O 3.833012 0.000000 0.962402 0.961991 4.299656 4.619054 \n", + " 2 H 4.492580 0.962402 0.000000 1.543892 4.818396 5.201953 \n", + " 3 H 4.455221 0.961991 1.543892 0.000000 4.617552 4.745524 \n", + " 4 O 3.876180 4.299656 4.818396 4.617552 0.000000 0.962127 \n", + " 5 H 4.469248 4.619054 5.201953 4.745524 0.962127 0.000000 \n", + " 6 H 4.562502 4.777956 5.139648 5.145337 0.962354 1.543273 \n", + " 7 O 2.036694 5.513150 6.173359 6.053817 5.716528 6.224934 \n", + " 8 H 2.779980 6.208239 6.765259 6.831129 6.472760 7.065328 \n", + " 9 H 2.620855 5.678637 6.394928 6.099736 6.221899 6.623374 \n", + " 10 O 2.494233 5.760957 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1.543273 6.224934 7.065328 6.623374 4.961594 5.325261 5.092996 \n", + " 6 0.000000 6.428181 7.098497 7.007355 4.497076 4.586971 4.699932 \n", + " 7 6.428181 0.000000 1.071272 0.963935 3.179595 3.943490 3.581821 \n", + " 8 7.098497 1.071272 0.000000 1.675426 3.308597 3.916475 3.714163 \n", + " 9 7.007355 0.963935 1.675426 0.000000 4.102801 4.891951 4.454918 \n", + " 10 4.497076 3.179595 3.308597 4.102801 0.000000 0.962202 0.962210 \n", + " 11 4.586971 3.943490 3.916475 4.891951 0.962202 0.000000 1.537005 \n", + " 12 4.699932 3.581821 3.714163 4.454918 0.962210 1.537005 0.000000 \n", + " 13 8.064597 2.444772 1.374030 2.939605 3.886739 4.258035 4.245509 \n", + " 14 8.538437 3.021766 2.024499 3.475966 4.195053 4.567349 4.353941 \n", + " 15 8.773035 3.070288 2.047424 3.391479 4.706311 4.996269 5.144126 \n", + " 16 3.092068 4.036445 4.740779 4.516975 3.412263 3.742840 4.091456 \n", + " 17 3.636734 4.562765 5.284055 4.898274 4.374090 4.666682 5.092954 \n", + " 18 2.128238 4.648480 5.394950 5.143398 3.569078 3.894626 4.066496 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.955311 4.624478 4.551091 2.006405 2.647969 2.661480 \n", + " 1 7.249777 8.100255 7.512234 2.506455 1.480530 3.103006 \n", + " 2 7.693990 8.572029 7.892034 3.094642 2.134493 3.677085 \n", + " 3 7.944534 8.782923 8.207735 3.166899 2.168957 3.595617 \n", + " 4 7.536293 8.025152 8.247352 2.506595 3.086346 1.477829 \n", + " 5 8.204144 8.675351 8.924773 3.155902 3.572245 2.161933 \n", + " 6 8.064597 8.538437 8.773035 3.092068 3.636734 2.128238 \n", + " 7 2.444772 3.021766 3.070288 4.036445 4.562765 4.648480 \n", + " 8 1.374030 2.024499 2.047424 4.740779 5.284055 5.394950 \n", + " 9 2.939605 3.475966 3.391479 4.516975 4.898274 5.143398 \n", + " 10 3.886739 4.195053 4.706311 3.412263 4.374090 3.569078 \n", + " 11 4.258035 4.567349 4.996269 3.742840 4.666682 3.894626 \n", + " 12 4.245509 4.353941 5.144126 4.091456 5.092954 4.066496 \n", + " 13 0.000000 0.963487 0.963357 5.806810 6.359747 6.476151 \n", + " 14 0.963487 0.000000 1.552254 6.503469 7.132765 7.082996 \n", + " 15 0.963357 1.552254 0.000000 6.337071 6.776994 7.095360 \n", + " 16 5.806810 6.503469 6.337071 0.000000 1.028704 1.030002 \n", + " 17 6.359747 7.132765 6.776994 1.028704 0.000000 1.718626 \n", + " 18 6.476151 7.082996 7.095360 1.030002 1.718626 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s1.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 5.912526 6.578592 6.462725 5.912294 6.578218 \n", + " 1 O 5.912526 0.000000 0.962147 0.962505 11.812366 12.447215 \n", + " 2 H 6.578592 0.962147 0.000000 1.553538 12.447226 13.109473 \n", + " 3 H 6.462725 0.962505 1.553538 0.000000 12.343095 12.935443 \n", + " 4 O 5.912294 11.812366 12.447226 12.343095 0.000000 0.962145 \n", + " 5 H 6.578218 12.447215 13.109473 12.935443 0.962145 0.000000 \n", + " 6 H 6.462635 12.343059 12.935408 12.921665 0.962503 1.553529 \n", + " 7 O 4.117036 9.951669 10.647170 10.436210 2.452924 3.103691 \n", + " 8 H 4.617281 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10.436210 10.707676 11.246058 3.037240 2.051404 \n", + " 4 0.962503 2.452924 2.982515 1.391941 9.951670 10.741320 \n", + " 5 1.553529 3.103691 3.459007 2.079359 10.647172 11.412279 \n", + " 6 0.000000 3.037342 3.562958 2.051534 10.436203 11.246066 \n", + " 7 3.037342 0.000000 0.963894 1.062433 7.912736 8.783755 \n", + " 8 3.562958 0.963894 0.000000 1.686126 8.183223 9.086072 \n", + " 9 2.051534 1.062433 1.686126 0.000000 8.783725 9.617333 \n", + " 10 10.436203 7.912736 8.183223 8.783725 0.000000 1.062469 \n", + " 11 11.246066 8.783755 9.086072 9.617333 1.062469 0.000000 \n", + " 12 10.707501 8.183113 8.418708 9.085911 0.963894 1.686182 \n", + " 13 8.166093 5.939297 6.417998 6.676695 2.500244 3.155334 \n", + " 14 9.493657 7.071973 7.420618 7.898063 1.036064 1.794841 \n", + " 15 8.225402 6.289619 6.873416 6.925772 3.038600 3.521809 \n", + " 16 4.966851 2.500131 2.993019 3.155304 5.939701 6.677124 \n", + " 17 3.742914 1.036119 1.659697 1.794857 7.072082 7.898188 \n", + " 18 5.282119 3.038648 3.459335 3.521916 6.290194 6.926381 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 4.617603 1.974766 3.178034 2.486924 1.974782 3.177702 2.486952 \n", + " 1 2.982501 4.261442 3.069603 4.475252 7.719882 9.022542 7.852249 \n", + " 2 3.458857 4.807384 3.680300 4.857159 8.445651 9.730334 8.608140 \n", + " 3 3.562938 4.966562 3.742724 5.281749 8.166365 9.493713 8.225879 \n", + " 4 10.281889 7.719491 9.022461 7.851655 4.261568 3.069682 4.475494 \n", + " 5 11.020859 8.445138 9.730217 8.607410 4.807307 3.680297 4.857166 \n", + " 6 10.707501 8.166093 9.493657 8.225402 4.966851 3.742914 5.282119 \n", + " 7 8.183113 5.939297 7.071973 6.289619 2.500131 1.036119 3.038648 \n", + " 8 8.418708 6.417998 7.420618 6.873416 2.993019 1.659697 3.459335 \n", + " 9 9.085911 6.676695 7.898063 6.925772 3.155304 1.794857 3.521916 \n", + " 10 0.963894 2.500244 1.036064 3.038600 5.939701 7.072082 6.290194 \n", + " 11 1.686182 3.155334 1.794841 3.521809 6.677124 7.898188 6.926381 \n", + " 12 0.000000 2.993263 1.659654 3.459381 6.418340 7.420650 6.873923 \n", + " 13 2.993263 0.000000 1.464870 0.962189 3.948812 5.074347 4.396331 \n", + " 14 1.659654 1.464870 0.000000 2.056941 5.074703 6.216683 5.459234 \n", + " 15 3.459381 0.962189 2.056941 0.000000 4.396335 5.458741 4.849048 \n", + " 16 6.418340 3.948812 5.074703 4.396335 0.000000 1.464706 0.962189 \n", + " 17 7.420650 5.074347 6.216683 5.458741 1.464706 0.000000 2.056928 \n", + " 18 6.873923 4.396331 5.459234 4.849048 0.962189 2.056928 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s15.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.962537 1.549510 3.730408 3.341261 3.729926 \n", + " 1 O 0.962537 0.000000 0.962529 3.851209 3.346219 3.850969 \n", + " 2 H 1.549510 0.962529 0.000000 4.797004 4.300264 4.797250 \n", + " 3 H 3.730408 3.851209 4.797004 0.000000 0.962530 1.549504 \n", + " 4 O 3.341261 3.346219 4.300264 0.962530 0.000000 0.962534 \n", + " 5 H 3.729926 3.850969 4.797250 1.549504 0.962534 0.000000 \n", + " 6 H 3.732406 3.344004 3.731418 3.727862 3.850056 4.796391 \n", + " 7 O 3.852853 3.347697 3.850650 3.341767 3.347159 4.301255 \n", + " 8 H 4.798447 4.301581 4.797061 3.727392 3.849173 4.794978 \n", + " 9 H 4.797060 4.300091 4.796766 4.796563 3.850785 3.729874 \n", + " 10 O 3.850821 3.346040 3.850927 4.300139 3.346089 3.341100 \n", + " 11 H 3.729652 3.341017 3.730091 4.797017 3.850716 3.729597 \n", + " 12 H 5.876232 5.360183 6.075041 3.731402 3.344024 3.732368 \n", + " 13 O 5.359509 4.731176 5.357767 3.850602 3.347679 3.852792 \n", + " 14 H 6.073842 5.357081 5.870747 4.797031 4.301559 4.798365 \n", + " 15 H 4.794770 3.848959 3.727091 5.870861 5.357134 6.073849 \n", + " 16 O 4.301141 3.347033 3.341567 5.357805 4.731168 5.359458 \n", + " 17 H 4.796050 3.849710 3.727356 6.075023 5.360118 5.876109 \n", + " 18 Hg 3.037089 2.365295 3.036795 3.036787 2.365275 3.037061 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.732406 3.852853 4.798447 4.797060 3.850821 3.729652 5.876232 \n", + " 1 3.344004 3.347697 4.301581 4.300091 3.346040 3.341017 5.360183 \n", + " 2 3.731418 3.850650 4.797061 4.796766 3.850927 3.730091 6.075041 \n", + " 3 3.727862 3.341767 3.727392 4.796563 4.300139 4.797017 3.731402 \n", + " 4 3.850056 3.347159 3.849173 3.850785 3.346089 3.850716 3.344024 \n", + " 5 4.796391 4.301255 4.794978 3.729874 3.341100 3.729597 3.732368 \n", + " 6 0.000000 0.962532 1.549509 6.074921 5.360033 5.876036 4.794155 \n", + " 7 0.962532 0.000000 0.962531 5.357692 4.731075 5.359376 3.848418 \n", + " 8 1.549509 0.962531 0.000000 5.870723 5.357025 6.073754 3.723932 \n", + " 9 6.074921 5.357692 5.870723 0.000000 0.962529 1.549517 3.727526 \n", + " 10 5.360033 4.731075 5.357025 0.962529 0.000000 0.962537 3.849901 \n", + " 11 5.876036 5.359376 6.073754 1.549517 0.962537 0.000000 4.796208 \n", + " 12 4.794155 3.848418 3.723932 3.727526 3.849901 4.796208 0.000000 \n", + " 13 4.295280 3.340866 3.332979 3.341581 3.347040 4.301145 0.962532 \n", + " 14 4.791818 3.845343 3.722411 3.727220 3.848990 4.794832 1.549504 \n", + " 15 3.723704 3.332912 3.722337 4.797193 4.301482 4.798410 4.791918 \n", + " 16 3.848228 3.340784 3.845239 3.850753 3.347599 3.852853 4.295263 \n", + " 17 4.793912 4.295198 4.791767 3.731627 3.343902 3.732376 4.794192 \n", + " 18 3.038175 2.365830 3.036722 3.036751 2.365249 3.037036 3.038251 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 5.359509 6.073842 4.794770 4.301141 4.796050 3.037089 \n", + " 1 4.731176 5.357081 3.848959 3.347033 3.849710 2.365295 \n", + " 2 5.357767 5.870747 3.727091 3.341567 3.727356 3.036795 \n", + " 3 3.850602 4.797031 5.870861 5.357805 6.075023 3.036787 \n", + " 4 3.347679 4.301559 5.357134 4.731168 5.360118 2.365275 \n", + " 5 3.852792 4.798365 6.073849 5.359458 5.876109 3.037061 \n", + " 6 4.295280 4.791818 3.723704 3.848228 4.793912 3.038175 \n", + " 7 3.340866 3.845343 3.332912 3.340784 4.295198 2.365830 \n", + " 8 3.332979 3.722411 3.722337 3.845239 4.791767 3.036722 \n", + " 9 3.341581 3.727220 4.797193 3.850753 3.731627 3.036751 \n", + " 10 3.347040 3.848990 4.301482 3.347599 3.343902 2.365249 \n", + " 11 4.301145 4.794832 4.798410 3.852853 3.732376 3.037036 \n", + " 12 0.962532 1.549504 4.791918 4.295263 4.794192 3.038251 \n", + " 13 0.000000 0.962530 3.845421 3.340844 3.848472 2.365885 \n", + " 14 0.962530 0.000000 3.722478 3.332919 3.723972 3.036758 \n", + " 15 3.845421 3.722478 0.000000 0.962527 1.549496 3.036792 \n", + " 16 3.340844 3.332919 0.962527 0.000000 0.962533 2.365897 \n", + " 17 3.848472 3.723972 1.549496 0.962533 0.000000 3.038241 \n", + " 18 2.365885 3.036758 3.036792 2.365897 3.038241 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.993468 2.882120 2.569785 1.973216 2.655983 \n", + " 1 O 1.993468 0.000000 1.162898 0.963791 3.966088 4.582892 \n", + " 2 H 2.882120 1.162898 0.000000 1.784111 4.784251 5.408229 \n", + " 3 H 2.569785 0.963791 1.784111 0.000000 4.490057 5.059609 \n", + " 4 O 1.973216 3.966088 4.784251 4.490057 0.000000 1.045751 \n", + " 5 H 2.655983 4.582892 5.408229 5.059609 1.045751 0.000000 \n", + " 6 H 2.655911 4.582835 5.408269 5.059496 1.045695 1.772437 \n", + " 7 O 3.822375 5.580808 6.376076 6.001002 2.472663 3.107772 \n", + " 8 H 4.450690 6.169634 7.048342 6.471664 3.117995 3.605651 \n", + " 9 H 4.473359 6.209356 6.894390 6.715719 3.070355 3.655988 \n", + " 10 O 3.822394 5.580848 6.375938 6.001149 2.472576 1.428635 \n", + " 11 H 4.473441 6.209486 6.894341 6.715959 3.070277 2.090196 \n", + " 12 H 4.450640 6.169607 7.048144 6.471741 3.117857 2.110911 \n", + " 13 O 3.958029 2.392688 1.230357 2.933157 5.750617 6.367598 \n", + " 14 H 4.578743 2.979181 1.889483 3.402107 6.361729 7.068542 \n", + " 15 H 4.578805 2.979237 1.889502 3.402123 6.361788 6.868947 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.655911 3.822375 4.450690 4.473359 3.822394 4.473441 4.450640 \n", + " 1 4.582835 5.580808 6.169634 6.209356 5.580848 6.209486 6.169607 \n", + " 2 5.408269 6.376076 7.048342 6.894390 6.375938 6.894341 7.048144 \n", + " 3 5.059496 6.001002 6.471664 6.715719 6.001149 6.715959 6.471741 \n", + " 4 1.045695 2.472663 3.117995 3.070355 2.472576 3.070277 3.117857 \n", + " 5 1.772437 3.107772 3.605651 3.655988 1.428635 2.090196 2.110911 \n", + " 6 0.000000 1.428783 2.111072 2.090342 3.107605 3.655800 3.605424 \n", + " 7 1.428783 0.000000 0.962610 0.962901 4.297200 4.768449 4.651879 \n", + " 8 2.111072 0.962610 0.000000 1.548751 4.651940 5.183108 4.820265 \n", + " 9 2.090342 0.962901 1.548751 0.000000 4.768516 5.075688 5.183146 \n", + " 10 3.107605 4.297200 4.651940 4.768516 0.000000 0.962903 0.962612 \n", + " 11 3.655800 4.768449 5.183108 5.075688 0.962903 0.000000 1.548762 \n", + " 12 3.605424 4.651879 4.820265 5.183146 0.962612 1.548762 0.000000 \n", + " 13 6.367697 7.296868 8.032180 7.711595 7.296623 7.711431 8.031881 \n", + " 14 6.868997 7.658339 8.381066 8.035707 8.086561 8.516935 8.820681 \n", + " 15 7.068676 8.086839 8.820985 8.517173 7.658157 8.035653 8.380796 \n", + " \n", + " 13 14 15 \n", + " 0 3.958029 4.578743 4.578805 \n", + " 1 2.392688 2.979181 2.979237 \n", + " 2 1.230357 1.889483 1.889502 \n", + " 3 2.933157 3.402107 3.402123 \n", + " 4 5.750617 6.361729 6.361788 \n", + " 5 6.367598 7.068542 6.868947 \n", + " 6 6.367697 6.868997 7.068676 \n", + " 7 7.296868 7.658339 8.086839 \n", + " 8 8.032180 8.381066 8.820985 \n", + " 9 7.711595 8.035707 8.517173 \n", + " 10 7.296623 8.086561 7.658157 \n", + " 11 7.711431 8.516935 8.035653 \n", + " 12 8.031881 8.820681 8.380796 \n", + " 13 0.000000 0.965787 0.965786 \n", + " 14 0.965787 0.000000 1.569848 \n", + " 15 0.965786 1.569848 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s21.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.378023 3.057264 2.951366 2.377866 3.057095 \n", + " 1 O 2.378023 0.000000 0.963375 0.963568 3.537003 3.792889 \n", + " 2 H 3.057264 0.963375 0.000000 1.544708 3.792584 4.004930 \n", + " 3 H 2.951366 0.963568 1.544708 0.000000 3.962144 4.017499 \n", + " 4 O 2.377866 3.537003 3.792584 3.962144 0.000000 0.963373 \n", + " 5 H 3.057095 3.792889 4.004930 4.017499 0.963373 0.000000 \n", + " 6 H 2.951351 3.962016 4.017054 4.510951 0.963563 1.544736 \n", + " 7 O 2.377632 3.069479 3.996783 2.870737 3.735871 3.889981 \n", + " 8 H 3.057230 3.808711 4.681105 3.500747 3.890069 3.865528 \n", + " 9 H 2.950868 3.539735 4.499529 3.310302 4.625721 4.839561 \n", + " 10 O 2.377978 3.735078 3.888996 4.625213 3.069220 3.996540 \n", + " 11 H 2.951315 4.625131 4.838668 5.486524 3.539245 4.499026 \n", + " 12 H 3.057484 3.888942 3.864291 4.838660 3.808608 4.681032 \n", + " 13 O 2.378151 4.750437 5.394763 5.236873 3.068751 3.808617 \n", + " 14 H 2.951297 5.236438 5.824106 5.673638 2.869477 3.500425 \n", + " 15 H 3.057404 5.395070 6.113489 5.824862 3.995934 4.680849 \n", + " 16 O 2.378402 3.068831 3.808642 3.538645 4.750428 5.395019 \n", + " 17 H 3.057775 3.995923 4.680708 4.498336 5.395063 6.113741 \n", + " 18 H 2.951513 2.869353 3.500344 3.308120 5.236284 5.824218 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.951351 2.377632 3.057230 2.950868 2.377978 2.951315 3.057484 \n", + " 1 3.962016 3.069479 3.808711 3.539735 3.735078 4.625131 3.888942 \n", + " 2 4.017054 3.996783 4.681105 4.499529 3.888996 4.838668 3.864291 \n", + " 3 4.510951 2.870737 3.500747 3.310302 4.625213 5.486524 4.838660 \n", + " 4 0.963563 3.735871 3.890069 4.625721 3.069220 3.539245 3.808608 \n", + " 5 1.544736 3.889981 3.865528 4.839561 3.996540 4.499026 4.681032 \n", + " 6 0.000000 4.625916 4.839734 5.486990 2.870401 3.309538 3.500698 \n", + " 7 4.625916 0.000000 0.963372 0.963562 4.749637 5.235438 5.394481 \n", + " 8 4.839734 0.963372 0.000000 1.544759 5.394851 5.824181 6.113607 \n", + " 9 5.486990 0.963562 1.544759 0.000000 5.235092 5.671454 5.823419 \n", + " 10 2.870401 4.749637 5.394851 5.235092 0.000000 0.963552 0.963366 \n", + " 11 3.309538 5.235438 5.824181 5.671454 0.963552 0.000000 1.544749 \n", + " 12 3.500698 5.394481 6.113607 5.823419 0.963366 1.544749 0.000000 \n", + " 13 3.538331 3.537258 3.794135 3.961629 3.067342 2.867874 3.994793 \n", + " 14 3.308079 3.962371 4.018769 4.510610 3.537516 3.307256 4.497283 \n", + " 15 4.498053 3.792728 4.006091 4.016515 3.806977 3.498461 4.679564 \n", + " 16 5.236598 3.067691 3.995262 2.868127 3.536360 3.961170 3.792616 \n", + " 17 5.824506 3.807577 4.680388 3.498923 3.791756 4.016015 4.004369 \n", + " 18 5.673245 3.537538 4.497334 3.307324 3.961426 4.510118 4.017156 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.378151 2.951297 3.057404 2.378402 3.057775 2.951513 \n", + " 1 4.750437 5.236438 5.395070 3.068831 3.995923 2.869353 \n", + " 2 5.394763 5.824106 6.113489 3.808642 4.680708 3.500344 \n", + " 3 5.236873 5.673638 5.824862 3.538645 4.498336 3.308120 \n", + " 4 3.068751 2.869477 3.995934 4.750428 5.395063 5.236284 \n", + " 5 3.808617 3.500425 4.680849 5.395019 6.113741 5.824218 \n", + " 6 3.538331 3.308079 4.498053 5.236598 5.824506 5.673245 \n", + " 7 3.537258 3.962371 3.792728 3.067691 3.807577 3.537538 \n", + " 8 3.794135 4.018769 4.006091 3.995262 4.680388 4.497334 \n", + " 9 3.961629 4.510610 4.016515 2.868127 3.498923 3.307324 \n", + " 10 3.067342 3.537516 3.806977 3.536360 3.791756 3.961426 \n", + " 11 2.867874 3.307256 3.498461 3.961170 4.016015 4.510118 \n", + " 12 3.994793 4.497283 4.679564 3.792616 4.004369 4.017156 \n", + " 13 0.000000 0.963562 0.963367 3.735372 3.889326 4.625332 \n", + " 14 0.963562 0.000000 1.544698 4.625391 4.838986 5.486595 \n", + " 15 0.963367 1.544698 0.000000 3.889173 3.864714 4.838808 \n", + " 16 3.735372 4.625391 3.889173 0.000000 0.963371 0.963561 \n", + " 17 3.889326 4.838986 3.864714 0.963371 0.000000 1.544674 \n", + " 18 4.625332 5.486595 4.838808 0.963561 1.544674 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s11.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.439175 3.015587 3.168374 3.837341 4.487206 \n", + " 1 O 2.439175 0.000000 0.966990 0.961804 2.890435 3.484833 \n", + " 2 H 3.015587 0.966990 0.000000 1.556993 2.067667 2.629270 \n", + " 3 H 3.168374 0.961804 1.556993 0.000000 3.617040 4.095521 \n", + " 4 O 3.837341 2.890435 2.067667 3.617040 0.000000 0.964317 \n", + " 5 H 4.487206 3.484833 2.629270 4.095521 0.964317 0.000000 \n", + " 6 H 4.480655 3.473261 2.626215 4.161934 0.964003 1.535343 \n", + " 7 O 3.913286 5.532076 5.451664 6.477488 4.492031 4.929755 \n", + " 8 H 4.567240 6.191115 6.077555 7.119505 4.995393 5.276236 \n", + " 9 H 4.535730 6.040360 5.913659 6.998218 4.844939 5.341217 \n", + " 10 O 2.036328 3.437845 4.325453 3.697701 5.677945 6.317710 \n", + " 11 H 2.787844 4.451950 5.320852 4.695486 6.564883 7.159684 \n", + " 12 H 2.620179 3.562391 4.483462 3.701358 5.990947 6.702138 \n", + " 13 O 2.021724 3.117581 3.059038 4.048253 2.615695 3.165112 \n", + " 14 H 2.717181 4.109370 4.028510 5.051990 3.268634 3.775616 \n", + " 15 H 2.624588 2.851134 2.495678 3.774779 1.624474 2.226339 \n", + " 16 O 3.937029 5.742521 6.588563 5.971499 7.723790 8.261417 \n", + " 17 H 4.583580 6.164336 7.027908 6.276428 8.263480 8.735695 \n", + " 18 H 4.558677 6.469224 7.312869 6.731584 8.389811 8.977443 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.480655 3.913286 4.567240 4.535730 2.036328 2.787844 2.620179 \n", + " 1 3.473261 5.532076 6.191115 6.040360 3.437845 4.451950 3.562391 \n", + " 2 2.626215 5.451664 6.077555 5.913659 4.325453 5.320852 4.483462 \n", + " 3 4.161934 6.477488 7.119505 6.998218 3.697701 4.695486 3.701358 \n", + " 4 0.964003 4.492031 4.995393 4.844939 5.677945 6.564883 5.990947 \n", + " 5 1.535343 4.929755 5.276236 5.341217 6.317710 7.159684 6.702138 \n", + " 6 0.000000 4.786190 5.341087 4.956668 6.295232 7.217911 6.508103 \n", + " 7 4.786190 0.000000 0.962522 0.962081 5.622090 5.941916 6.197668 \n", + " 8 5.341087 0.962522 0.000000 1.547357 6.246137 6.473644 6.903834 \n", + " 9 4.956668 0.962081 1.547357 0.000000 6.204274 6.557486 6.678315 \n", + " 10 6.295232 5.622090 6.246137 6.204274 0.000000 1.075970 0.963778 \n", + " 11 7.217911 5.941916 6.473644 6.557486 1.075970 0.000000 1.686799 \n", + " 12 6.508103 6.197668 6.903834 6.678315 0.963778 1.686799 0.000000 \n", + " 13 3.238763 2.485131 3.075832 3.145129 4.046633 4.678555 4.610538 \n", + " 14 3.721382 1.450617 2.108770 2.140773 4.634657 5.132822 5.207699 \n", + " 15 2.264220 3.074980 3.637733 3.584733 4.637447 5.394918 5.096907 \n", + " 16 8.413355 6.561402 6.963895 7.203807 2.436057 1.361704 2.955351 \n", + " 17 9.003003 7.339293 7.686350 8.032297 3.013504 2.015376 3.500926 \n", + " 18 9.025289 6.857453 7.270190 7.418628 3.071462 2.037456 3.419730 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.021724 2.717181 2.624588 3.937029 4.583580 4.558677 \n", + " 1 3.117581 4.109370 2.851134 5.742521 6.164336 6.469224 \n", + " 2 3.059038 4.028510 2.495678 6.588563 7.027908 7.312869 \n", + " 3 4.048253 5.051990 3.774779 5.971499 6.276428 6.731584 \n", + " 4 2.615695 3.268634 1.624474 7.723790 8.263480 8.389811 \n", + " 5 3.165112 3.775616 2.226339 8.261417 8.735695 8.977443 \n", + " 6 3.238763 3.721382 2.264220 8.413355 9.003003 9.025289 \n", + " 7 2.485131 1.450617 3.074980 6.561402 7.339293 6.857453 \n", + " 8 3.075832 2.108770 3.637733 6.963895 7.686350 7.270190 \n", + " 9 3.145129 2.140773 3.584733 7.203807 8.032297 7.418628 \n", + " 10 4.046633 4.634657 4.637447 2.436057 3.013504 3.071462 \n", + " 11 4.678555 5.132822 5.394918 1.361704 2.015376 2.037456 \n", + " 12 4.610538 5.207699 5.096907 2.955351 3.500926 3.419730 \n", + " 13 0.000000 1.036977 1.000536 5.641752 6.295044 6.211410 \n", + " 14 1.036977 0.000000 1.713844 5.959150 6.681726 6.413571 \n", + " 15 1.000536 1.713844 0.000000 6.452277 7.065977 7.060924 \n", + " 16 5.641752 5.959150 6.452277 0.000000 0.963779 0.963371 \n", + " 17 6.295044 6.681726 7.065977 0.963779 0.000000 1.554750 \n", + " 18 6.211410 6.413571 7.060924 0.963371 1.554750 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s13.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 4.010359 4.673157 4.620651 2.444020 3.094051 \n", + " 1 O 4.010359 0.000000 0.962900 0.962489 5.361826 5.296392 \n", + " 2 H 4.673157 0.962900 0.000000 1.547072 5.671302 5.455388 \n", + " 3 H 4.620651 0.962489 1.547072 0.000000 6.194163 6.176933 \n", + " 4 O 2.444020 5.361826 5.671302 6.194163 0.000000 0.962553 \n", + " 5 H 3.094051 5.296392 5.455388 6.176933 0.962553 0.000000 \n", + " 6 H 3.105279 6.211523 6.502291 7.054602 0.962517 1.538778 \n", + " 7 O 3.968529 6.274707 6.875606 6.717743 5.241333 5.991118 \n", + " 8 H 4.580662 6.629483 7.282754 6.951597 6.094336 6.856327 \n", + " 9 H 4.630085 6.945224 7.463646 7.447836 5.525466 6.245335 \n", + " 10 O 2.482506 5.384589 6.075448 5.800448 3.409939 3.942464 \n", + " 11 H 3.177984 5.840149 6.599359 6.119511 4.354452 4.905462 \n", + " 12 H 3.096294 6.066536 6.672713 6.547287 3.314126 3.777088 \n", + " 13 O 2.081264 2.477056 3.055613 3.124273 3.297513 3.375455 \n", + " 14 H 2.802932 1.433229 2.083859 2.114274 4.138716 4.142390 \n", + " 15 H 2.615289 2.988246 3.559896 3.455090 3.711286 3.757446 \n", + " 16 O 2.076684 5.678913 6.354023 6.220680 3.340547 4.237334 \n", + " 17 H 2.787588 5.829672 6.487958 6.331470 4.105222 4.941055 \n", + " 18 H 2.656257 6.391255 7.120221 6.866726 3.856877 4.799765 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.105279 3.968529 4.580662 4.630085 2.482506 3.177984 3.096294 \n", + " 1 6.211523 6.274707 6.629483 6.945224 5.384589 5.840149 6.066536 \n", + " 2 6.502291 6.875606 7.282754 7.463646 6.075448 6.599359 6.672713 \n", + " 3 7.054602 6.717743 6.951597 7.447836 5.800448 6.119511 6.547287 \n", + " 4 0.962517 5.241333 6.094336 5.525466 3.409939 4.354452 3.314126 \n", + " 5 1.538778 5.991118 6.856327 6.245335 3.942464 4.905462 3.777088 \n", + " 6 0.000000 5.225574 6.123115 5.361183 4.047613 4.950335 3.853024 \n", + " 7 5.225574 0.000000 0.962756 0.963119 6.004453 6.394542 6.589438 \n", + " 8 6.123115 0.962756 0.000000 1.548707 6.483767 6.755602 7.137819 \n", + " 9 5.361183 0.963119 1.548707 0.000000 6.694021 7.142649 7.194641 \n", + " 10 4.047613 6.004453 6.483767 6.694021 0.000000 0.963107 0.963209 \n", + " 11 4.950335 6.394542 6.755602 7.142649 0.963107 0.000000 1.538283 \n", + " 12 3.853024 6.589438 7.137819 7.194641 0.963209 1.538283 0.000000 \n", + " 13 4.226188 5.631580 6.167081 6.309506 3.050415 3.687728 3.634575 \n", + " 14 5.037979 5.803446 6.262818 6.494957 4.002009 4.535944 4.646367 \n", + " 15 4.658039 6.369835 6.864296 7.084860 2.693031 3.220253 3.239425 \n", + " 16 3.434188 2.466862 3.109141 3.047624 3.686800 4.156461 4.171547 \n", + " 17 4.142581 1.416235 2.095016 2.068655 4.653404 5.074430 5.197017 \n", + " 18 3.884347 2.968876 3.434319 3.532078 3.607461 3.910899 4.044197 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.081264 2.802932 2.615289 2.076684 2.787588 2.656257 \n", + " 1 2.477056 1.433229 2.988246 5.678913 5.829672 6.391255 \n", + " 2 3.055613 2.083859 3.559896 6.354023 6.487958 7.120221 \n", + " 3 3.124273 2.114274 3.455090 6.220680 6.331470 6.866726 \n", + " 4 3.297513 4.138716 3.711286 3.340547 4.105222 3.856877 \n", + " 5 3.375455 4.142390 3.757446 4.237334 4.941055 4.799765 \n", + " 6 4.226188 5.037979 4.658039 3.434188 4.142581 3.884347 \n", + " 7 5.631580 5.803446 6.369835 2.466862 1.416235 2.968876 \n", + " 8 6.167081 6.262818 6.864296 3.109141 2.095016 3.434319 \n", + " 9 6.309506 6.494957 7.084860 3.047624 2.068655 3.532078 \n", + " 10 3.050415 4.002009 2.693031 3.686800 4.653404 3.607461 \n", + " 11 3.687728 4.535944 3.220253 4.156461 5.074430 3.910899 \n", + " 12 3.634575 4.646367 3.239425 4.171547 5.197017 4.044197 \n", + " 13 0.000000 1.045603 0.964335 4.129394 4.685656 4.703211 \n", + " 14 1.045603 0.000000 1.654376 4.700997 5.070057 5.348931 \n", + " 15 0.964335 1.654376 0.000000 4.662271 5.328057 5.086613 \n", + " 16 4.129394 4.700997 4.662271 0.000000 1.052211 0.963496 \n", + " 17 4.685656 5.070057 5.328057 1.052211 0.000000 1.653573 \n", + " 18 4.703211 5.348931 5.086613 0.963496 1.653573 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s16.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.373811 2.944415 3.030975 3.913222 4.543263 \n", + " 1 O 2.373811 0.000000 0.964388 0.964134 4.680596 5.254180 \n", + " 2 H 2.944415 0.964388 0.000000 1.545490 5.183702 5.846076 \n", + " 3 H 3.030975 0.964134 1.545490 0.000000 4.532363 4.990885 \n", + " 4 O 3.913222 4.680596 5.183702 4.532363 0.000000 0.962063 \n", + " 5 H 4.543263 5.254180 5.846076 4.990885 0.962063 0.000000 \n", + " 6 H 4.568576 5.246693 5.613583 5.105135 0.962494 1.539473 \n", + " 7 O 2.396725 3.128892 2.937920 4.047443 5.562731 6.392545 \n", + " 8 H 3.017883 3.659872 3.438382 4.617686 6.465735 7.267798 \n", + " 9 H 3.041823 3.824638 3.522981 4.679364 5.655626 6.548584 \n", + " 10 O 2.225913 2.881653 3.417034 3.606520 5.966390 6.452118 \n", + " 11 H 2.875827 3.786606 4.370375 4.434810 6.482417 6.887029 \n", + " 12 H 2.781529 2.598254 3.124393 3.211602 6.286654 6.733728 \n", + " 13 O 2.057025 3.973036 4.498136 4.336721 2.530528 3.181173 \n", + " 14 H 2.696338 4.124063 4.665491 4.272597 1.513338 2.191470 \n", + " 15 H 2.687602 4.830459 5.399238 5.218405 3.109480 3.578405 \n", + " 16 O 3.885819 6.163358 6.756533 6.589883 4.351484 4.634422 \n", + " 17 H 4.518965 6.715795 7.389691 7.058034 4.648367 4.737971 \n", + " 18 H 4.537574 6.842397 7.351351 7.317985 4.879151 5.216432 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.568576 2.396725 3.017883 3.041823 2.225913 2.875827 2.781529 \n", + " 1 5.246693 3.128892 3.659872 3.824638 2.881653 3.786606 2.598254 \n", + " 2 5.613583 2.937920 3.438382 3.522981 3.417034 4.370375 3.124393 \n", + " 3 5.105135 4.047443 4.617686 4.679364 3.606520 4.434810 3.211602 \n", + " 4 0.962494 5.562731 6.465735 5.655626 5.966390 6.482417 6.286654 \n", + " 5 1.539473 6.392545 7.267798 6.548584 6.452118 6.887029 6.733728 \n", + 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\n", + " 0 2.057025 2.696338 2.687602 3.885819 4.518965 4.537574 \n", + " 1 3.973036 4.124063 4.830459 6.163358 6.715795 6.842397 \n", + " 2 4.498136 4.665491 5.399238 6.756533 7.389691 7.351351 \n", + " 3 4.336721 4.272597 5.218405 6.589883 7.058034 7.317985 \n", + " 4 2.530528 1.513338 3.109480 4.351484 4.648367 4.879151 \n", + " 5 3.181173 2.191470 3.578405 4.634422 4.737971 5.216432 \n", + " 6 3.103965 2.153287 3.672434 4.863125 5.214007 5.240026 \n", + " 7 3.718940 4.417137 4.314453 5.339419 6.181562 5.650923 \n", + " 8 4.491024 5.262340 4.970347 5.829586 6.655124 6.115239 \n", + " 9 3.902498 4.561290 4.484895 5.485530 6.389616 5.652708 \n", + " 10 4.140492 4.812349 4.479622 5.245664 5.728160 5.928130 \n", + " 11 4.554037 5.273482 4.696127 5.206726 5.583399 5.900543 \n", + " 12 4.761509 5.299993 5.208699 6.073573 6.514961 6.796913 \n", + " 13 0.000000 1.019745 1.020703 2.526502 3.184986 3.106593 \n", + " 14 1.019745 0.000000 1.697002 3.109122 3.590033 3.684569 \n", + " 15 1.020703 1.697002 0.000000 1.508798 2.193248 2.154514 \n", + " 16 2.526502 3.109122 1.508798 0.000000 0.961914 0.962366 \n", + " 17 3.184986 3.590033 2.193248 0.961914 0.000000 1.540427 \n", + " 18 3.106593 3.684569 2.154514 0.962366 1.540427 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w5s9.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.918273 4.565132 4.545046 2.020802 2.600486 \n", + " 1 O 3.918273 0.000000 0.963321 0.962862 2.452822 3.061359 \n", + " 2 H 4.565132 0.963321 0.000000 1.552132 3.041492 3.615897 \n", + " 3 H 4.545046 0.962862 1.552132 0.000000 3.105266 3.562380 \n", + " 4 O 2.020802 2.452822 3.041492 3.105266 0.000000 1.001707 \n", + " 5 H 2.600486 3.061359 3.615897 3.562380 1.001707 0.000000 \n", + " 6 H 2.753042 1.396664 2.056808 2.083162 1.058471 1.747549 \n", + " 7 O 2.103045 5.664100 6.279981 6.256190 4.105753 4.686346 \n", + " 8 H 2.729237 5.900818 6.425993 6.535848 4.611194 5.308768 \n", + " 9 H 2.726624 6.216994 6.914181 6.702594 4.707651 5.216341 \n", + " 10 O 2.372690 5.568545 6.215955 6.084285 3.178534 2.928187 \n", + " 11 H 2.931439 5.487876 6.101315 5.958108 3.102730 2.559580 \n", + " 12 H 3.103983 6.505084 7.129665 7.040094 4.101258 3.846279 \n", + " 13 O 3.742978 4.525033 5.022995 4.879615 2.612498 1.626396 \n", + " 14 H 4.396367 4.958424 5.299471 5.369289 3.164090 2.223731 \n", + " 15 H 4.390923 4.841965 5.394808 5.016522 3.233093 2.258427 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.753042 2.103045 2.729237 2.726624 2.372690 2.931439 3.103983 \n", + " 1 1.396664 5.664100 5.900818 6.216994 5.568545 5.487876 6.505084 \n", + " 2 2.056808 6.279981 6.425993 6.914181 6.215955 6.101315 7.129665 \n", + " 3 2.083162 6.256190 6.535848 6.702594 6.084285 5.958108 7.040094 \n", + " 4 1.058471 4.105753 4.611194 4.707651 3.178534 3.102730 4.101258 \n", + " 5 1.747549 4.686346 5.308768 5.216341 2.928187 2.559580 3.846279 \n", + " 6 0.000000 4.711615 5.097212 5.293090 4.197498 4.109520 5.131848 \n", + " 7 4.711615 0.000000 0.968349 0.968165 3.387103 4.279192 3.623942 \n", + " 8 5.097212 0.968349 0.000000 1.571098 4.263221 5.132866 4.482370 \n", + " 9 5.293090 0.968165 1.571098 0.000000 3.669109 4.588223 3.818220 \n", + " 10 4.197498 3.387103 4.263221 3.669109 0.000000 0.968632 0.962906 \n", + " 11 4.109520 4.279192 5.132866 4.588223 0.968632 0.000000 1.564695 \n", + " 12 5.131848 3.623942 4.482370 3.818220 0.962906 1.564695 0.000000 \n", + " 13 3.322047 5.647480 6.396648 6.069212 2.892713 2.067893 3.622989 \n", + " 14 3.823814 6.287875 6.986539 6.786575 3.487018 2.624659 4.093788 \n", + " 15 3.779109 6.264769 7.058604 6.580110 3.466737 2.620024 4.166044 \n", + " \n", + " 13 14 15 \n", + " 0 3.742978 4.396367 4.390923 \n", + " 1 4.525033 4.958424 4.841965 \n", + " 2 5.022995 5.299471 5.394808 \n", + " 3 4.879615 5.369289 5.016522 \n", + " 4 2.612498 3.164090 3.233093 \n", + " 5 1.626396 2.223731 2.258427 \n", + " 6 3.322047 3.823814 3.779109 \n", + " 7 5.647480 6.287875 6.264769 \n", + " 8 6.396648 6.986539 7.058604 \n", + " 9 6.069212 6.786575 6.580110 \n", + " 10 2.892713 3.487018 3.466737 \n", + " 11 2.067893 2.624659 2.620024 \n", + " 12 3.622989 4.093788 4.166044 \n", + " 13 0.000000 0.964961 0.964675 \n", + " 14 0.964961 0.000000 1.534481 \n", + " 15 0.964675 1.534481 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s19.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.328047 2.997351 2.943132 2.260798 2.911556 \n", + " 1 O 2.328047 0.000000 0.963679 0.963807 4.183643 4.498827 \n", + " 2 H 2.997351 0.963679 0.000000 1.549034 4.508295 4.687351 \n", + " 3 H 2.943132 0.963807 1.549034 0.000000 5.000151 5.392916 \n", + " 4 O 2.260798 4.183643 4.508295 5.000151 0.000000 0.962544 \n", + " 5 H 2.911556 4.498827 4.687351 5.392916 0.962544 0.000000 \n", + " 6 H 2.841552 4.765501 5.033521 5.545552 0.983787 1.584390 \n", + " 7 O 3.955886 5.769676 5.998908 6.420632 2.712834 3.303505 \n", + " 8 H 4.640925 6.222272 6.315333 6.897978 3.331847 3.739869 \n", + " 9 H 4.568393 6.543714 6.849151 7.157354 3.272071 3.874271 \n", + " 10 O 2.325274 3.320839 4.257921 3.256750 4.267133 5.021166 \n", + " 11 H 2.956066 4.079501 4.978124 3.951633 4.695103 5.539935 \n", + " 12 H 2.940748 3.798976 4.761342 3.689128 4.762556 5.437450 \n", + " 13 O 2.309642 3.759296 4.205959 4.127690 3.064947 3.932731 \n", + " 14 H 2.876369 4.493114 4.836460 4.971764 2.859442 3.695979 \n", + " 15 H 2.967442 3.869776 4.220978 4.089998 3.926552 4.735996 \n", + " 16 O 2.354343 3.182199 3.848740 3.721251 3.314929 3.476941 \n", + " 17 H 2.985985 3.106061 3.658714 3.602335 4.021442 4.038529 \n", + " 18 H 3.020196 4.126820 4.754384 4.683869 3.426865 3.484742 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.841552 3.955886 4.640925 4.568393 2.325274 2.956066 2.940748 \n", + " 1 4.765501 5.769676 6.222272 6.543714 3.320839 4.079501 3.798976 \n", + " 2 5.033521 5.998908 6.315333 6.849151 4.257921 4.978124 4.761342 \n", + " 3 5.545552 6.420632 6.897978 7.157354 3.256750 3.951633 3.689128 \n", + " 4 0.983787 2.712834 3.331847 3.272071 4.267133 4.695103 4.762556 \n", + " 5 1.584390 3.303505 3.739869 3.874271 5.021166 5.539935 5.437450 \n", + " 6 0.000000 1.762227 2.375471 2.354720 4.727493 4.990664 5.328870 \n", + " 7 1.762227 0.000000 0.964439 0.964732 5.454123 5.430848 6.199167 \n", + " 8 2.375471 0.964439 0.000000 1.533079 6.271101 6.266066 7.049554 \n", + " 9 2.354720 0.964732 1.533079 0.000000 5.805054 5.670754 6.497158 \n", + " 10 4.727493 5.454123 6.271101 5.805054 0.000000 0.963674 0.963649 \n", + " 11 4.990664 5.430848 6.266066 5.670754 0.963674 0.000000 1.549650 \n", + " 12 5.328870 6.199167 7.049554 6.497158 0.963649 1.549650 0.000000 \n", + " 13 2.848728 2.750101 3.366416 3.317130 3.217573 3.166294 4.133978 \n", + " 14 2.343242 1.812539 2.419621 2.404830 4.043402 3.964304 4.911150 \n", + " 15 3.677633 3.345678 3.779762 3.931261 3.620309 3.487887 4.580076 \n", + " 16 4.249418 5.789352 6.500061 6.275840 3.152998 4.036402 3.019910 \n", 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4.580076 3.019910 3.555506 3.501483 \n", + " 13 0.000000 0.979838 0.962639 4.620748 5.293150 5.166246 \n", + " 14 0.979838 0.000000 1.574874 5.099081 5.815684 5.525482 \n", + " 15 0.962639 1.574874 0.000000 5.301851 5.882956 5.938275 \n", + " 16 4.620748 5.099081 5.301851 0.000000 0.963368 0.963471 \n", + " 17 5.293150 5.815684 5.882956 0.963368 0.000000 1.549994 \n", + " 18 5.166246 5.525482 5.938275 0.963471 1.549994 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s8.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 4.167864 4.872777 4.680699 5.911330 6.571325 \n", + " 1 O 4.167864 0.000000 1.071958 0.964109 2.443490 3.089733 \n", + " 2 H 4.872777 1.071958 0.000000 1.695034 1.372909 2.057915 \n", + " 3 H 4.680699 0.964109 1.695034 0.000000 2.973857 3.440461 \n", + " 4 O 5.911330 2.443490 1.372909 2.973857 0.000000 0.962571 \n", + " 5 H 6.571325 3.089733 2.057915 3.440461 0.962571 0.000000 \n", + " 6 H 6.467398 3.025861 2.032033 3.553457 0.962904 1.554837 \n", + " 7 O 1.983340 2.524123 3.187733 3.001921 4.279575 4.820171 \n", + " 8 H 3.223517 1.027773 1.796933 1.649062 3.056135 3.665878 \n", + " 9 H 2.481383 3.037427 3.505807 3.465131 4.429851 4.809825 \n", + " 10 O 3.944751 7.900603 8.731610 8.216830 9.836770 10.502531 \n", + " 11 H 4.524245 8.538509 9.345008 8.846721 10.424738 11.040916 \n", + " 12 H 4.634414 8.469171 9.325938 8.769750 10.449828 11.158811 \n", + " 13 O 2.539951 4.636029 5.606772 4.817435 6.866400 7.620826 \n", + " 14 H 3.211226 4.822697 5.859174 4.812144 7.184135 7.884147 \n", + " 15 H 3.211463 5.077385 6.008658 5.290732 7.221765 8.038265 \n", + " 16 O 2.048923 6.098003 6.777623 6.630564 7.739902 8.452815 \n", + " 17 H 2.750594 6.823578 7.579916 7.256103 8.613639 9.304404 \n", + " 18 H 2.629157 6.589188 7.156080 7.210096 7.991105 8.692612 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.467398 1.983340 3.223517 2.481383 3.944751 4.524245 4.634414 \n", + " 1 3.025861 2.524123 1.027773 3.037427 7.900603 8.538509 8.469171 \n", + " 2 2.032033 3.187733 1.796933 3.505807 8.731610 9.345008 9.325938 \n", + " 3 3.553457 3.001921 1.649062 3.465131 8.216830 8.846721 8.769750 \n", + " 4 0.962904 4.279575 3.056135 4.429851 9.836770 10.424738 10.449828 \n", + " 5 1.554837 4.820171 3.665878 4.809825 10.502531 11.040916 11.158811 \n", + " 6 0.000000 4.989065 3.727580 5.238120 10.354190 10.989806 10.912854 \n", + " 7 4.989065 0.000000 1.496978 0.962770 5.760612 6.270033 6.474291 \n", + " 8 3.727580 1.496978 0.000000 2.069101 7.009124 7.604849 7.631251 \n", + " 9 5.238120 0.962770 2.069101 0.000000 6.070792 6.451284 6.869126 \n", + " 10 10.354190 5.760612 7.009124 6.070792 0.000000 0.962674 0.962747 \n", + " 11 10.989806 6.270033 7.604849 6.451284 0.962674 0.000000 1.548322 \n", + " 12 10.912854 6.474291 7.631251 6.869126 0.962747 1.548322 0.000000 \n", + " 13 7.273453 3.484456 4.037771 4.293588 3.962923 4.810849 4.230163 \n", + " 14 7.628749 3.838539 4.295062 4.599364 4.317295 5.106611 4.553978 \n", 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3.962923 4.317295 4.264211 2.470208 1.419342 2.955818 \n", + " 11 4.810849 5.106611 5.184950 3.103552 2.096687 3.414640 \n", + " 12 4.230163 4.553978 4.339000 3.053147 2.070317 3.509560 \n", + " 13 0.000000 0.961508 0.961636 3.119874 3.305216 4.027217 \n", + " 14 0.961508 0.000000 1.534922 3.898352 3.916032 4.840474 \n", + " 15 0.961636 1.534922 0.000000 3.440125 3.635609 4.280508 \n", + " 16 3.119874 3.898352 3.440125 0.000000 1.051413 0.963847 \n", + " 17 3.305216 3.916032 3.635609 1.051413 0.000000 1.650419 \n", + " 18 4.027217 4.840474 4.280508 0.963847 1.650419 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/pbe0/w6s6.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.645078 4.276906 4.289757 2.020834 2.781323 \n", + " 1 O 3.645078 0.000000 0.961095 0.961144 5.331194 5.848109 \n", + " 2 H 4.276906 0.961095 0.000000 1.534811 5.898570 6.483615 \n", + " 3 H 4.289757 0.961144 1.534811 0.000000 5.916550 6.302370 \n", + " 4 O 2.020834 5.331194 5.898570 5.916550 0.000000 1.072196 \n", + " 5 H 2.781323 5.848109 6.483615 6.302370 1.072196 0.000000 \n", + " 6 H 2.617943 5.751131 6.192220 6.415333 0.963321 1.688136 \n", + " 7 O 1.947039 2.622565 3.267566 3.261616 3.966768 4.670753 \n", + " 8 H 2.461514 1.631489 2.310412 2.307174 4.416311 5.057556 \n", + " 9 H 3.108850 3.625222 4.167005 4.154327 5.031736 5.754808 \n", + " 10 O 3.941811 6.690025 7.386559 6.990496 2.437904 1.366987 \n", + " 11 H 4.558946 6.949763 7.601890 7.195559 3.069089 2.041371 \n", + " 12 H 4.591661 7.533963 8.254715 7.833821 3.021984 2.022814 \n", + " 13 O 4.038459 4.522878 5.008752 4.984186 5.869673 6.587827 \n", + " 14 H 4.757807 4.896827 5.202547 5.410835 6.591774 7.393263 \n", + " 15 H 4.556272 4.799866 5.365786 5.089162 6.375950 6.982893 \n", + " 16 O 5.840857 5.693474 5.787967 6.251770 7.626135 8.506447 \n", + " 17 H 6.531896 5.871440 5.874549 6.350484 8.387568 9.254743 \n", + " 18 H 6.367382 6.575315 6.671288 7.166663 8.026765 8.929268 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.617943 1.947039 2.461514 3.108850 3.941811 4.558946 4.591661 \n", + " 1 5.751131 2.622565 1.631489 3.625222 6.690025 6.949763 7.533963 \n", + " 2 6.192220 3.267566 2.310412 4.167005 7.386559 7.601890 8.254715 \n", + " 3 6.415333 3.261616 2.307174 4.154327 6.990496 7.195559 7.833821 \n", + " 4 0.963321 3.966768 4.416311 5.031736 2.437904 3.069089 3.021984 \n", + " 5 1.688136 4.670753 5.057556 5.754808 1.366987 2.041371 2.022814 \n", + " 6 0.000000 4.508609 4.917723 5.570816 2.960650 3.437945 3.492161 \n", + " 7 4.508609 0.000000 0.995755 1.449548 5.703236 6.294984 6.340820 \n", + " 8 4.917723 0.995755 0.000000 2.117702 6.030003 6.497496 6.762679 \n", + " 9 5.570816 1.449548 2.117702 0.000000 6.767778 7.457479 7.282044 \n", + " 10 2.960650 5.703236 6.030003 6.767778 0.000000 0.963166 0.963482 \n", + " 11 3.437945 6.294984 6.497496 7.457479 0.963166 0.000000 1.554636 \n", + " 12 3.492161 6.340820 6.762679 7.282044 0.963482 1.554636 0.000000 \n", + " 13 6.402798 2.489147 3.109809 1.040665 7.575471 8.316023 8.010721 \n", + " 14 7.019703 3.154162 3.636800 1.802811 8.457661 9.184233 8.912923 \n", + " 15 7.003632 2.986076 3.504166 1.665366 7.845137 8.583374 8.251202 \n", + " 16 7.931647 4.278723 4.634320 3.087290 9.646236 10.358053 10.115019 \n", + " 17 8.700185 4.838668 5.031120 3.702659 10.378139 11.054607 10.886907 \n", + " 18 8.286480 4.974236 5.434557 3.754308 10.087911 10.841609 10.493179 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 4.038459 4.757807 4.556272 5.840857 6.531896 6.367382 \n", + " 1 4.522878 4.896827 4.799866 5.693474 5.871440 6.575315 \n", + " 2 5.008752 5.202547 5.365786 5.787967 5.874549 6.671288 \n", + " 3 4.984186 5.410835 5.089162 6.251770 6.350484 7.166663 \n", + " 4 5.869673 6.591774 6.375950 7.626135 8.387568 8.026765 \n", + " 5 6.587827 7.393263 6.982893 8.506447 9.254743 8.929268 \n", + " 6 6.402798 7.019703 7.003632 7.931647 8.700185 8.286480 \n", + " 7 2.489147 3.154162 2.986076 4.278723 4.838668 4.974236 \n", + " 8 3.109809 3.636800 3.504166 4.634320 5.031120 5.434557 \n", + " 9 1.040665 1.802811 1.665366 3.087290 3.702659 3.754308 \n", + " 10 7.575471 8.457661 7.845137 9.646236 10.378139 10.087911 \n", + " 11 8.316023 9.184233 8.583374 10.358053 11.054607 10.841609 \n", + " 12 8.010721 8.912923 8.251202 10.115019 10.886907 10.493179 \n", + " 13 0.000000 1.060125 0.963666 2.456019 3.106177 3.036018 \n", + " 14 1.060125 0.000000 1.683337 1.397440 2.083370 2.054748 \n", + " 15 0.963666 1.683337 0.000000 2.982792 3.457441 3.556576 \n", + " 16 2.456019 1.397440 2.982792 0.000000 0.962131 0.962607 \n", + " 17 3.106177 2.083370 3.457441 0.962131 0.000000 1.552142 \n", + " 18 3.036018 2.054748 3.556576 0.962607 1.552142 0.000000 }" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_hf: dict = distance_matrix.distance_matrix(coordinates_hf, (0, 0, 0))\n", + "distances_dict_pbe0: dict = distance_matrix.distance_matrix(coordinates_pbe0, (0, 0, 0))\n", + "distances_dict_camb3lyp: dict = distance_matrix.distance_matrix(\n", + " coordinates_camb3lyp, (0, 0, 0)\n", + ")\n", + "distances_dict_wb97xd: dict = distance_matrix.distance_matrix(coordinates_wb97xd, (0, 0, 0))\n", + "distances_dict_b2plyp: dict = distance_matrix.distance_matrix(\n", + " coordinates_b2plyp, (0, 0, 0)\n", + ")\n", + "distances_dict_pbeqidh: dict = distance_matrix.distance_matrix(\n", + " coordinates_pbeqidh, (0, 0, 0)\n", + ")\n", + "distances_dict_mp2: dict = distance_matrix.distance_matrix(coordinates_mp2, (0, 0, 0))\n", + "distances_dict_zora_nr: dict = distance_matrix.distance_matrix(coordinates_zora_nr, (0, 0, 0))\n", + "distances_dict_zora_sr: dict = distance_matrix.distance_matrix(coordinates_zora_sr, (0, 0, 0))\n", + "distances_dict_zora_so: dict = distance_matrix.distance_matrix(coordinates_zora_so, (0, 0, 0))\n", + "\n", + "distances_dict_pbe0\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 2.7, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/hf/w5s7.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w2s1.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s5.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 10, 11, 12)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w4s3.xyz': [(12,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (12, 7, 6, 8)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w4s2.xyz': [(12,\n", + " 1,\n", + " 0,\n", + " 2),\n", + " (12, 4, 3, 5)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s8.xyz': [(15,\n", + " 1,\n", + " 0,\n", + " 2),\n", + " (15, 4, 3, 5),\n", + " (15, 7, 6, 8),\n", + " (15, 10, 9, 11),\n", + " (15, 13, 12, 14)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s12.xyz': [(18,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (18, 7, 6, 8),\n", + " (18, 10, 9, 11)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s24.xyz': [(18,\n", + " 1,\n", + " 0,\n", + " 2),\n", + " (18, 4, 3, 5),\n", + " (18, 7, 6, 8),\n", + " (18, 10, 9, 11),\n", + " (18, 16, 15, 17)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s2.xyz': [(18,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (18, 10, 9, 11)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s10.xyz': [(0,\n", + " 4,\n", + " 5,\n", + " 6),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s18.xyz': [(18,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (18, 7, 6, 8),\n", + " (18, 13, 12, 14),\n", + " (18, 16, 15, 17)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s9.xyz': [(0,\n", + " 10,\n", + " 11,\n", + " 12),\n", + " (0, 13, 14, 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w3s2.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 7, 8, 9)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w4s4.xyz': [(12,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (12, 10, 9, 11)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s14.xyz': [(0,\n", + " 4,\n", + " 5,\n", + " 6),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s6.xyz': [(0,\n", + " 7,\n", + " 8,\n", + " 9),\n", + " (0, 7, 8, 15),\n", + " (0, 7, 9, 15),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w1s1.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w4s1.xyz': [(12,\n", + " 1,\n", + " 0,\n", + " 2),\n", + " (12, 4, 3, 5),\n", + " (12, 7, 6, 8),\n", + " (12, 10, 9, 11)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w3s3.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s4.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 7, 8, 9)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w3s1.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s4.xyz': [(18,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (18, 7, 6, 8)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s2.xyz': [(15,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (15, 13, 12, 14)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s22.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 10, 11, 12),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s23.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s1.xyz': [(15,\n", + " 4,\n", + " 3,\n", + " 5),\n", + " (15, 10, 9, 11)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s5.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 7, 8, 9)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s10.xyz': [(0,\n", + " 7,\n", + " 8,\n", + " 9),\n", + " (0, 10, 11, 12),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s1.xyz': [(0,\n", + " 13,\n", + " 14,\n", + " 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s15.xyz': [(18,\n", + " 1,\n", + " 0,\n", + " 2),\n", + " (18, 4, 3, 5),\n", + " (18, 7, 6, 8),\n", + " (18, 10, 9, 11),\n", + " (18, 13, 12, 14),\n", + " (18, 16, 15, 17)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s3.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s21.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s11.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s13.xyz': [(0,\n", + " 4,\n", + " 5,\n", + " 6),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s16.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w5s9.xyz': [(0,\n", + " 4,\n", + " 5,\n", + " 6),\n", + " (0, 7, 8, 9),\n", + " (0, 10, 11, 12)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s19.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 4, 5, 6),\n", + " (0, 10, 11, 12),\n", + " (0, 13, 14, 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s8.xyz': [(0,\n", + " 7,\n", + " 8,\n", + " 9),\n", + " (0, 13, 14, 15),\n", + " (0, 16, 17, 18)],\n", + " '/home/edison/repositories/radial_distribution/files_xyz/hf/w6s6.xyz': [(0,\n", + " 1,\n", + " 2,\n", + " 3),\n", + " (0, 1, 2, 6),\n", + " (0, 1, 3, 6),\n", + " (0, 4, 5, 6),\n", + " (0, 7, 8, 9)]}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"Hg\", \"O\", \"H\", \"H\"]\n", + "\n", + "atoms_index_dict_hf: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_hf, atoms_list, grid\n", + ")\n", + "atoms_index_dict_pbe0: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_pbe0, atoms_list, grid\n", + ")\n", + "atoms_index_dict_camb3lyp: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_camb3lyp, atoms_list, grid\n", + ")\n", + "atoms_index_dict_wb97xd: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_wb97xd, atoms_list, grid\n", + ")\n", + "atoms_index_dict_b2plyp: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_b2plyp, atoms_list, grid\n", + ")\n", + "atoms_index_dict_pbeqidh: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_pbeqidh, atoms_list, grid\n", + ")\n", + "atoms_index_dict_mp2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_mp2, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_zora_nr: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_nr, atoms_list, grid\n", + ")\n", + "atoms_index_dict_zora_sr: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_sr, atoms_list, grid\n", + ")\n", + "atoms_index_dict_zora_so: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_zora_so, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_hf\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "delta_angle = 5.0\n", + "min_angle = 0\n", + "max_angle = 360\n", + "\n", + "nbins_angle = int((max_angle - min_angle) / delta_angle)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,\n", + " 1, 0, 0, 0, 0, 1, 1, 4, 0, 0, 2, 2, 11, 26, 18, 23, 11,\n", + " 4, 11, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - torsion angle distribution analysis (TDA); i.e., atoms_list_AB = [A, B, C, D]\n", + "histogram_hf: np.array = histogram.tda(\n", + " atoms_index_dict_hf, coordinates_hf, delta_angle, nbins_angle\n", + ")\n", + "histogram_pbe0: np.array = histogram.tda(\n", + " atoms_index_dict_pbe0, coordinates_pbe0, delta_angle, nbins_angle\n", + ")\n", + "histogram_camb3lyp: np.array = histogram.tda(\n", + " atoms_index_dict_camb3lyp, coordinates_camb3lyp, delta_angle, nbins_angle\n", + ")\n", + "histogram_wb97xd: np.array = histogram.tda(\n", + " atoms_index_dict_wb97xd, coordinates_wb97xd, delta_angle, nbins_angle\n", + ")\n", + "histogram_b2plyp: np.array = histogram.tda(\n", + " atoms_index_dict_b2plyp, coordinates_b2plyp, delta_angle, nbins_angle\n", + ")\n", + "histogram_pbeqidh: np.array = histogram.tda(\n", + " atoms_index_dict_pbeqidh, coordinates_pbeqidh, delta_angle, nbins_angle\n", + ")\n", + "histogram_mp2: np.array = histogram.tda(\n", + " atoms_index_dict_mp2, coordinates_mp2, delta_angle, nbins_angle\n", + ")\n", + "histogram_zora_nr: np.array = histogram.tda(\n", + " atoms_index_dict_zora_nr, coordinates_zora_nr, delta_angle, nbins_angle\n", + ")\n", + "histogram_zora_sr: np.array = histogram.tda(\n", + " atoms_index_dict_zora_sr, coordinates_zora_sr, delta_angle, nbins_angle\n", + ")\n", + "histogram_zora_so: np.array = histogram.tda(\n", + " atoms_index_dict_zora_so, coordinates_zora_so, delta_angle, nbins_angle\n", + ")\n", + "\n", + "\n", + "\n", + "histogram_pbeqidh\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution_angle = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_hf,\n", + " histogram_pbe0,\n", + " histogram_camb3lyp,\n", + " histogram_wb97xd,\n", + " histogram_b2plyp,\n", + " histogram_pbeqidh,\n", + " histogram_mp2,\n", + " histogram_zora_nr,\n", + " histogram_zora_sr,\n", + " histogram_zora_so,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"tda_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution_angle, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_hf_nan = histogram_hf.astype(\"float\")\n", + "histogram_pbe0_nan = histogram_pbe0.astype(\"float\")\n", + "histogram_camb3lyp_nan = histogram_camb3lyp.astype(\"float\")\n", + "histogram_wb97xd_nan = histogram_wb97xd.astype(\"float\")\n", + "histogram_b2plyp_nan = histogram_b2plyp.astype(\"float\")\n", + "histogram_pbeqidh_nan = histogram_pbeqidh.astype(\"float\")\n", + "histogram_mp2_nan = histogram_mp2.astype(\"float\")\n", + "histogram_zora_nr_nan = histogram_zora_nr.astype(\"float\")\n", + "histogram_zora_sr_nan = histogram_zora_sr.astype(\"float\")\n", + "histogram_zora_so_nan = histogram_zora_so.astype(\"float\")\n", + "\n", + "\n", + "histogram_hf_nan[histogram_hf_nan == 0] = float(\"nan\")\n", + "histogram_pbe0_nan[histogram_pbe0_nan == 0] = float(\"nan\")\n", + "histogram_wb97xd_nan[histogram_wb97xd_nan == 0] = float(\"nan\")\n", + "histogram_camb3lyp_nan[histogram_camb3lyp_nan == 0] = float(\"nan\")\n", + "histogram_b2plyp_nan[histogram_b2plyp_nan == 0] = float(\"nan\")\n", + "histogram_pbeqidh_nan[histogram_pbeqidh_nan == 0] = float(\"nan\")\n", + "histogram_mp2_nan[histogram_mp2_nan == 0] = float(\"nan\")\n", + "histogram_zora_nr_nan[histogram_zora_nr_nan == 0] = float(\"nan\")\n", + "histogram_zora_sr_nan[histogram_zora_sr_nan == 0] = float(\"nan\")\n", + "histogram_zora_so_nan[histogram_zora_so_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# - dihedral analysis; i.e., input_list = [A, B, C, D]\n", + "\n", + "# # grid = 0.1 --> 3600 = (3600 - 0)/0.1\n", + "# delta_angle = 10.0\n", + "# min_angle = 0\n", + "# max_angle = 360\n", + "\n", + "# nbins_angle = int((max_angle - min_angle) / delta_angle)\n", + "\n", + "# # -------------------------------------------------\n", + "# grid_all = (0.8, 2.7, 0.1)\n", + "\n", + "# # - number of bins for the accurences\n", + "# rmin_all, rmax_all, dr_all = grid_all\n", + "# nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "# distribution_angle_angle_all = np.linspace(\n", + "# rmin_all, rmax_all, nbins_all, endpoint=False\n", + "# )\n", + "\n", + "# files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "# coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "# distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "# atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + "# distances_dict_all, atoms_list, grid_all\n", + "# )\n", + "# histogram_all: np.array = histogram.tda(\n", + "# atoms_index_dict_all, coordinates_all, delta_angle, nbins_angle\n", + "# )\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(min_angle, max_angle, nbins_angle, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y_hf = histogram_hf\n", + "smooth = make_interp_spline(x, y_hf, k=3)\n", + "smooth_y_hf = smooth(smooth_x)\n", + "\n", + "y_pbe0 = histogram_pbe0\n", + "smooth = make_interp_spline(x, y_pbe0, k=3)\n", + "smooth_y_pbe0 = smooth(smooth_x)\n", + "\n", + "y_wb97xd = histogram_wb97xd\n", + "smooth = make_interp_spline(x, y_wb97xd, k=3)\n", + "smooth_y_wb97xd = smooth(smooth_x)\n", + "\n", + "y_camb3lyp = histogram_camb3lyp\n", + "smooth = make_interp_spline(x, y_camb3lyp, k=3)\n", + "smooth_y_camb3lyp = smooth(smooth_x)\n", + "\n", + "y_b2plyp = histogram_b2plyp\n", + "smooth = make_interp_spline(x, y_b2plyp, k=3)\n", + "smooth_y_b2plyp = smooth(smooth_x)\n", + "\n", + "y_pbeqidh = histogram_pbeqidh\n", + "smooth = make_interp_spline(x, y_pbeqidh, k=3)\n", + "smooth_y_pbeqidh = smooth(smooth_x)\n", + "\n", + "y_mp2 = histogram_mp2\n", + "smooth = make_interp_spline(x, y_mp2, k=3)\n", + "smooth_y_mp2 = smooth(smooth_x)\n", + "\n", + "y_zora_nr = histogram_zora_nr\n", + "smooth = make_interp_spline(x, y_zora_nr, k=3)\n", + "smooth_y_zora_nr = smooth(smooth_x)\n", + "\n", + "y_zora_sr = histogram_zora_sr\n", + "smooth = make_interp_spline(x, y_zora_sr, k=3)\n", + "smooth_y_zora_sr = smooth(smooth_x)\n", + "\n", + "y_zora_so = histogram_zora_so\n", + "smooth = make_interp_spline(x, y_zora_so, k=3)\n", + "smooth_y_zora_so = smooth(smooth_x)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_628388/1416589247.py:76: RuntimeWarning: invalid value encountered in true_divide\n", + " smooth_y_wb97xd / total_wb97xd,\n", + "/tmp/ipykernel_628388/1416589247.py:84: RuntimeWarning: invalid value encountered in true_divide\n", + " smooth_y_b2plyp / total_b2plyp,\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2a8b103416134a90bf2b94774dbaeca1", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "\n", + "# ax = brokenaxes(ylims=((0, 0.25),(0.95, 1.05)), hspace=.2)\n", + "ax = fig.add_subplot(111)\n", + "ax.grid(b=True, which=\"major\")\n", + "\n", + "# - lines style in a for loop\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "lines = [\"s\", \"^\", \"v\", \"<\", \">\", \".\", \"s\", \"d\", \"o\"] # , '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "cm = cycle(\n", + " [\n", + " \"#1f77b4\",\n", + " \"#ff7f0e\",\n", + " \"#2ca02c\",\n", + " \"#d62728\",\n", + " \"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " \"#7f7f7f\",\n", + " \"#e377c2\",\n", + " ]\n", + ")\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "total_hf = sum(histogram_hf)\n", + "total_pbe0 = sum(histogram_pbe0)\n", + "total_camb3lyp = sum(histogram_camb3lyp)\n", + "total_wb97xd = sum(histogram_wb97xd)\n", + "total_b2plyp = sum(histogram_b2plyp)\n", + "total_pbeqidh = sum(histogram_pbeqidh)\n", + "total_mp2 = sum(histogram_mp2)\n", + "total_zora_nr = sum(histogram_zora_nr)\n", + "total_zora_sr = sum(histogram_zora_sr)\n", + "total_zora_so = sum(histogram_zora_so)\n", + "\n", + "# plt.plot(\n", + "# smooth_x,\n", + "# smooth_y_hf / total_hf,\n", + "# where=(smooth_y_hf / total_hf>0),\n", + "# alpha=0.3,\n", + "# color=next(cm),\n", + "# label=\"HF\",\n", + "# )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_hf / total_hf,\n", + " # where=(smooth_y_hf / total_hf>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"HF(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_pbe0 / total_pbe0,\n", + " # where=(smooth_y_pbe0 / total_pbe0>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"PBE0(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_camb3lyp / total_camb3lyp,\n", + " # where=(smooth_y_camb3lyp / total_camb3lyp>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"CAM-B3LYP(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_wb97xd / total_wb97xd,\n", + " # where=(smooth_y_wb97xd / total_wb97xd>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"WB97XD(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_b2plyp / total_b2plyp,\n", + " # where=(smooth_y_b2plyp / total_b2plyp>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"B2PLYP(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_pbeqidh / total_pbeqidh,\n", + " # where=(smooth_y_pbeqidh / total_pbeqidh>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"PBEQIDH(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_mp2 / total_mp2,\n", + " # where=(smooth_y_mp2 / total_mp2>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"MP2(PP)\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_zora_nr / total_zora_nr,\n", + " # where=(smooth_y_mp2 / total_mp2>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"ZORA(NR)/PBE\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_zora_sr / total_zora_sr,\n", + " # where=(smooth_y_mp2 / total_mp2>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"ZORA(SR)/PBE\",\n", + " )\n", + "plt.plot(\n", + " smooth_x,\n", + " smooth_y_zora_so / total_zora_so,\n", + " # where=(smooth_y_mp2 / total_mp2>0),\n", + " # alpha=0.3,\n", + " color=next(cm),\n", + " label=\"ZORA(SO)/PBE\",\n", + " )\n", + "plt.xlim(100, 190)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "# ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(r\"Torsion Angle Hg$-$OH$_2$ [degrees]\", fontsize=16)\n", + "plt.legend(loc=\"upper left\", fontsize=10, ncol=2)\n", + "\n", + "fig.savefig(\n", + " working_dir / \"tda_all_HgOHH.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_Hg-O_RDA.ipynb b/analysis_Hg-O_RDA.ipynb new file mode 100644 index 0000000..89e64ed --- /dev/null +++ b/analysis_Hg-O_RDA.ipynb @@ -0,0 +1,518 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# from brokenaxes import brokenaxes\n", + "\n", + "# # interactive plots\n", + "# %matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "# working_dir: Path = Path(\n", + "# \"/home/edison/repositories/radial_distribution/mp2_xyz\"\n", + "# )\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir(parents=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.000082 -0.029616 -0.001848\n", + " 1 O 2.054672 -0.115947 0.106434\n", + " 2 H 2.536426 0.652793 0.494815\n", + " 3 H 2.550725 -0.434644 -0.684894\n", + " 4 O -2.054798 -0.106318 -0.117075\n", + " 5 H -2.536990 0.694278 -0.433967\n", + " 6 H -2.550654 -0.495978 0.641955}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (1.5, 3, 0.005)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': [(0, 1),\n", + " (0, 4)]}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"Hg\", \"O\"]\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - radial (bond) distribution analysis (RDA); i.e., atoms_list_AB = [A, B]\n", + "histogram_w1: np.array = histogram.rda(\n", + " atoms_index_dict_w1, distances_dict_w1, grid, nbins\n", + ")\n", + "histogram_w2: np.array = histogram.rda(\n", + " atoms_index_dict_w2, distances_dict_w2, grid, nbins\n", + ")\n", + "histogram_w3: np.array = histogram.rda(\n", + " atoms_index_dict_w3, distances_dict_w3, grid, nbins\n", + ")\n", + "histogram_w4: np.array = histogram.rda(\n", + " atoms_index_dict_w4, distances_dict_w4, grid, nbins\n", + ")\n", + "histogram_w5: np.array = histogram.rda(\n", + " atoms_index_dict_w5, distances_dict_w5, grid, nbins\n", + ")\n", + "histogram_w6: np.array = histogram.rda(\n", + " atoms_index_dict_w6, distances_dict_w6, grid, nbins\n", + ")\n", + "\n", + "histogram_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"rda_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_w1_nan = histogram_w1.astype(\"float\")\n", + "histogram_w2_nan = histogram_w2.astype(\"float\")\n", + "histogram_w3_nan = histogram_w3.astype(\"float\")\n", + "histogram_w4_nan = histogram_w4.astype(\"float\")\n", + "histogram_w5_nan = histogram_w5.astype(\"float\")\n", + "histogram_w6_nan = histogram_w6.astype(\"float\")\n", + "\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float(\"nan\")\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float(\"nan\")\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float(\"nan\")\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float(\"nan\")\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float(\"nan\")\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "grid_all = (1.5, 3, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin_all, rmax_all, dr_all = grid_all\n", + "nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "distribution_all = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "\n", + "files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_all, atoms_list, grid_all\n", + ")\n", + "histogram_all: np.array = histogram.rda(\n", + " atoms_index_dict_all, distances_dict_all, grid_all, nbins_all\n", + ")\n", + "\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y = histogram_all\n", + "smooth = make_interp_spline(x, y, k=3)\n", + "smooth_y = smooth(smooth_x)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "\n", + "# ax = brokenaxes(ylims=((0, 0.25),(0.95, 1.05)), hspace=.2)\n", + "ax = fig.add_subplot(111)\n", + "ax.grid(b=True, which=\"major\")\n", + "\n", + "# - lines style in a for loop\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "lines = [\"s\", \"^\", \"v\", \"<\", \">\", \".\", \"s\", \"d\", \"o\"] # , '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "cm = cycle(\n", + " [\n", + " \"#1f77b4\",\n", + " \"#ff7f0e\",\n", + " \"#2ca02c\",\n", + " \"#d62728\",\n", + " \"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "total_all = sum(histogram_all)\n", + "\n", + "plt.fill_between(\n", + " smooth_x,\n", + " smooth_y / total_all,\n", + " where=(smooth_y / total_all > 0),\n", + " alpha=0.3,\n", + " color=\"gray\",\n", + " label=\"distribution\",\n", + ")\n", + "# ax.plot(\n", + "# # distribution_all,\n", + "# # histogram_all / total_all,\n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w1_nan / total_w1,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w1\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w2\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "plt.xlim(1.9, 2.7)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list)}' r\" [$\\AA$]\", fontsize=16)\n", + "plt.legend(loc=\"best\", fontsize=10, ncol=2)\n", + "\n", + "fig.savefig(\n", + " working_dir / \"rda_HgO.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_Hg-O_RDA_gaussian.ipynb b/analysis_Hg-O_RDA_gaussian.ipynb new file mode 100644 index 0000000..9c7aaef --- /dev/null +++ b/analysis_Hg-O_RDA_gaussian.ipynb @@ -0,0 +1,3290 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution\")\n", + "\n", + "if not working_dir.exists():\n", + " raise FileNotFoundError(f\"{working_dir} does not exist\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s7.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.904213 -0.008751 0.301419\n", + " 1 O -0.580352 1.054766 -1.229892\n", + " 2 H -1.534924 1.027242 -1.082449\n", + " 3 H -0.419177 1.879801 -1.707020\n", + " 4 O 0.762510 -1.470814 -1.270373\n", + " 5 H 1.459095 -2.105019 -1.496393\n", + " 6 H 0.380152 -1.147330 -2.100149\n", + " 7 O 4.332718 1.306042 1.655912\n", + " 8 H 4.871531 0.853040 2.316039\n", + " 9 H 4.762822 2.152960 1.483447\n", + " 10 O 1.896629 1.209512 1.604082\n", + " 11 H 2.964187 1.244220 1.679196\n", + " 12 H 1.489583 1.394240 2.460919\n", + " 13 O -1.075542 -1.038734 1.037088\n", + " 14 H -1.562679 -0.883323 1.856771\n", + " 15 H -1.305387 -1.937993 0.769120,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w2s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.000003 -0.016850 -0.000925\n", + " 1 O 2.001553 -0.066381 0.056437\n", + " 2 H 2.527089 0.619895 0.510238\n", + " 3 H 2.532019 -0.457418 -0.664048\n", + " 4 O -2.001446 -0.060612 -0.062220\n", + " 5 H -2.527767 0.663073 -0.452479\n", + " 6 H -2.532151 -0.517141 0.618416,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s5.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.914558 -2.643973 0.686443\n", + " 1 O 0.712683 -3.699747 2.225981\n", + " 2 H 1.108219 -4.576144 2.150752\n", + " 3 H 1.086433 -3.324779 3.032139\n", + " 4 O -2.354312 -2.679462 2.062871\n", + " 5 H -2.703210 -3.601459 2.559414\n", + " 6 H -3.084981 -2.056738 1.938110\n", + " 7 O -3.041570 -4.706514 3.181864\n", + " 8 H -3.822080 -5.202030 2.901910\n", + " 9 H -3.041314 -4.702931 4.147944\n", + " 10 O 0.431293 -2.547471 -0.779380\n", + " 11 H 0.083506 -2.467004 -1.679273\n", + " 12 H 1.400869 -2.029879 -0.684738\n", + " 13 O 2.575686 -1.467890 -0.512117\n", + " 14 H 3.363229 -1.983676 -0.728986\n", + " 15 H 2.734031 -0.567315 -0.823522,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 4.553248 1.280471 -0.422920\n", + " 1 O 4.119260 0.684815 0.203929\n", + " 2 H 4.801326 0.212251 0.700622\n", + " 3 H -0.296608 -0.830301 1.497087\n", + " 4 O -0.312248 -0.475199 0.593568\n", + " 5 H 1.376793 -0.462772 -0.178777\n", + " 6 H -4.474619 1.254645 -0.035262\n", + " 7 O -4.022756 0.481568 -0.410206\n", + " 8 H -4.690007 -0.193699 -0.613343\n", + " 9 H 3.200697 0.059203 -0.214007\n", + " 10 O 2.226213 -0.487538 -0.664174\n", + " 11 H 2.359365 -1.368638 -1.035140\n", + " 12 Hg -2.139592 -0.031947 0.172381,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.739106 0.086721 -0.794654\n", + " 1 O 3.212167 -0.112329 -0.002567\n", + " 2 H 3.740267 0.093319 0.787058\n", + " 3 H -1.273023 0.931148 0.000137\n", + " 4 O -0.736214 -0.009956 -0.000298\n", + " 5 H -1.286255 -0.944867 0.001437\n", + " 6 H -2.336354 2.459551 0.776491\n", + " 7 O -1.858854 2.140591 0.000302\n", + " 8 H -2.337500 2.458975 -0.775419\n", + " 9 H -2.360582 -2.462592 0.780160\n", + " 10 O -1.882318 -2.146724 0.003172\n", + " 11 H -2.362343 -2.463797 -0.772239\n", + " 12 Hg 1.193459 -0.029999 -0.001439,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s8.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -0.795291 2.739472 -0.484097\n", + " 1 O -0.015075 2.217487 -0.254674\n", + " 2 H 0.758086 2.750108 -0.483535\n", + " 3 H 3.005271 0.020194 -0.069280\n", + " 4 O 2.250782 0.016868 -0.672276\n", + " 5 H 2.622681 0.021911 -1.563677\n", + " 6 H -0.005329 0.765733 2.814359\n", + " 7 O 0.000065 -0.006074 2.234314\n", + " 8 H 0.005484 -0.780590 2.810739\n", + " 9 H -3.005276 -0.020002 -0.069238\n", + " 10 O -2.250818 -0.013312 -0.672245\n", + " 11 H -2.622760 -0.013812 -1.563641\n", + " 12 H -0.758132 -2.748350 -0.499285\n", + " 13 O 0.015058 -2.216947 -0.267715\n", + " 14 H 0.795274 -2.737718 -0.499870\n", + " 15 Hg 0.000002 -0.000381 -0.057147,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s12.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.635268 2.627593 -0.850686\n", + " 1 O -3.136349 2.431938 -0.049814\n", + " 2 H -3.643490 2.799844 0.682969\n", + " 3 H 2.483727 2.167442 -0.045432\n", + " 4 O 2.220496 1.252573 -0.214297\n", + " 5 H 3.033923 0.577469 -0.063366\n", + " 6 H -2.010151 -0.428693 0.152181\n", + " 7 O -1.646084 0.491913 0.323478\n", + " 8 H -2.313792 1.265788 0.132200\n", + " 9 H -0.260035 -2.216236 -0.079773\n", + " 10 O 0.539317 -1.670929 -0.076648\n", + " 11 H 1.284933 -2.278404 -0.134704\n", + " 12 H 4.562921 -0.411995 0.856171\n", + " 13 O 4.028937 -0.366730 0.052913\n", + " 14 H 4.642172 -0.468292 -0.686518\n", + " 15 H -2.780345 -2.407163 0.743545\n", + " 16 O -2.343864 -1.982952 -0.006841\n", + " 17 H -2.824921 -2.298220 -0.782747\n", + " 18 Hg 0.301316 0.754355 0.046769,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s24.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -2.29063 1.64864 0.10932\n", + " 1 O -1.60868 2.32360 0.27501\n", + " 2 H -2.03408 3.17375 0.43168\n", + " 3 H 1.15819 2.42805 -0.91201\n", + " 4 O 0.75926 1.97962 -0.15103\n", + " 5 H -0.27757 2.21866 -0.03900\n", + " 6 H -2.03314 -3.17424 -0.43142\n", + " 7 O -1.60793 -2.32398 -0.27483\n", + " 8 H -2.29006 -1.64924 -0.10902\n", + " 9 H 1.15976 -2.42734 0.91064\n", + " 10 O 0.76020 -1.97907 0.14990\n", + " 11 H -0.27649 -2.21855 0.03847\n", + " 12 H -3.86876 -0.02927 0.76048\n", + " 13 O -3.27219 -0.00030 0.00027\n", + " 14 H -3.86901 0.02843 -0.75976\n", + " 15 H 4.03113 0.51860 0.56521\n", + " 16 O 3.44541 -0.00034 0.00014\n", + " 17 H 4.03118 -0.51908 -0.56507\n", + " 18 Hg 1.02967 0.00036 -0.00060,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.74919 -0.49760 -0.08948\n", + " 1 O 5.49239 1.60097 -0.44491\n", + " 2 H 5.72283 2.43527 -0.01799\n", + " 3 H 6.34294 1.04186 -0.68442\n", + " 4 O 3.67419 0.36227 0.73370\n", + " 5 H 3.76649 0.02341 1.62861\n", + " 6 H 4.75307 1.09752 0.07118\n", + " 7 O 7.45053 0.24510 -1.09710\n", + " 8 H 8.22893 0.07578 -0.55633\n", + " 9 H 7.74369 0.24339 -2.01458\n", + " 10 O -2.27270 -1.69252 -0.58999\n", + " 11 H -3.03499 -1.94900 0.09822\n", + " 12 H -2.62338 -1.63145 -1.48854\n", + " 13 O -3.94453 -2.31995 1.08657\n", + " 14 H -4.80354 -1.89352 1.18555\n", + " 15 H -4.07345 -3.25344 1.29193\n", + " 16 O 0.80163 0.53483 0.39354\n", + " 17 H 2.72284 0.41527 0.54631\n", + " 18 H 0.50587 1.42736 0.62828,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 6.03280 0.64763 -0.04446\n", + " 1 O 5.28995 0.38671 -0.60208\n", + " 2 H 5.65815 -0.03066 -1.38923\n", + " 3 H 1.11117 1.48485 1.30014\n", + " 4 O 1.11250 1.04379 0.43805\n", + " 5 H 2.46461 1.44397 -0.29578\n", + " 6 H -2.60556 -3.84010 0.74082\n", + " 7 O -2.52949 -2.99526 1.19798\n", + " 8 H -3.02164 -3.09259 2.02027\n", + " 9 H -3.08335 -0.34841 -0.33646\n", + " 10 O -2.23690 -0.88783 -0.11961\n", + " 11 H -2.41700 -1.73300 0.43531\n", + " 12 H 3.23820 2.42134 -1.35342\n", + " 13 O 3.34234 1.83172 -0.59651\n", + " 14 H 4.20518 1.18151 -0.65200\n", + " 15 H -4.90373 0.82961 -0.16509\n", + " 16 O -4.21344 0.50956 -0.75575\n", + " 17 H -4.63448 0.38386 -1.61336\n", + " 18 Hg -0.56899 0.10264 0.21254,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s10.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.463224 -0.362657 -0.497770\n", + " 1 O 3.105859 0.950322 -0.417849\n", + " 2 H 3.578339 1.368790 0.315183\n", + " 3 H 3.692767 1.051883 -1.179693\n", + " 4 O -1.454933 -0.748648 1.637752\n", + " 5 H -2.050304 -0.135384 2.089434\n", + " 6 H -0.999537 -1.223334 2.345738\n", + " 7 O 0.607952 1.406691 -0.557613\n", + " 8 H 1.623964 1.327102 -0.568376\n", + " 9 H 0.321703 2.145837 -1.112804\n", + " 10 O 1.523837 -1.514768 -0.032813\n", + " 11 H 1.714418 -2.460344 -0.071362\n", + " 12 H 2.375407 -1.055320 -0.071699\n", + " 13 O -1.798184 -1.932784 -0.961743\n", + " 14 H -2.174954 -2.093905 -1.840119\n", + " 15 H -2.475798 -2.135484 -0.298706,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s18.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.91415 -1.64268 0.75893\n", + " 1 O 3.25114 -1.70278 0.06234\n", + " 2 H 3.68548 -2.13135 -0.68406\n", + " 3 H 2.18503 -0.73243 -0.15882\n", + " 4 O 1.36287 -0.13623 -0.35450\n", + " 5 H 1.57309 0.84109 -0.35047\n", + " 6 H -2.03491 -1.92517 2.24479\n", + " 7 O -2.08303 -1.33702 1.47624\n", + " 8 H -2.77925 -1.65420 0.87847\n", + " 9 H 2.13692 2.97386 0.19643\n", + " 10 O 1.55239 2.47672 -0.39035\n", + " 11 H 1.68258 2.87969 -1.25891\n", + " 12 H -0.43321 2.35974 0.26174\n", + " 13 O -1.10641 1.70276 0.49370\n", + " 14 H -1.76453 2.15969 1.03086\n", + " 15 H -2.69291 -0.13725 -1.58904\n", + " 16 O -2.22382 -0.90545 -1.23897\n", + " 17 H -2.22810 -1.54614 -1.96196\n", + " 18 Hg -0.42412 -0.59655 0.45172,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s9.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.33182 0.07170 -0.26049\n", + " 1 O 4.12098 1.05647 -0.06716\n", + " 2 H 4.59046 1.76062 -0.53322\n", + " 3 H 4.81092 0.49671 0.31148\n", + " 4 O -5.53296 1.00679 -0.34602\n", + " 5 H -5.97990 1.30816 -1.14557\n", + " 6 H -6.18740 1.01257 0.36158\n", + " 7 O -3.73583 -0.62877 -0.56467\n", + " 8 H -3.99663 -1.53854 -0.37118\n", + " 9 H -4.54190 0.06291 -0.43383\n", + " 10 O 1.51771 1.73285 1.22014\n", + " 11 H 1.14778 2.43748 1.76337\n", + " 12 H 2.47479 1.82089 1.30274\n", + " 13 O 2.10217 0.09571 -1.23807\n", + " 14 H 2.95198 0.44156 -0.77819\n", + " 15 H 2.32040 -0.62915 -1.83898\n", + " 16 O -1.47900 -0.03955 0.46840\n", + " 17 H -1.43873 0.02130 1.43275\n", + " 18 H -2.85519 -0.39341 -0.11548,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.090607 -0.159300 0.002895\n", + " 1 O -1.806432 -0.959823 0.078324\n", + " 2 H -2.010761 -1.904880 -0.024412\n", + " 3 H -2.568224 -0.435899 -0.220669\n", + " 4 O 2.121115 0.116531 -0.081348\n", + " 5 H 2.748802 -0.626709 -0.072363\n", + " 6 H 2.554998 0.891862 0.313658\n", + " 7 O -0.971061 1.914138 -0.014111\n", + " 8 H -0.990619 2.537018 -0.755299\n", + " 9 H -1.230948 2.428100 0.764401,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 3.458684 -2.897251 -0.161180\n", + " 1 O 3.173303 -2.160703 0.401070\n", + " 2 H 3.953371 -1.754954 0.809606\n", + " 3 H -3.247714 -0.161504 0.002070\n", + " 4 O -2.112353 0.171974 0.498330\n", + " 5 H -2.171532 0.802920 1.229718\n", + " 6 H -4.744937 0.201972 -0.876991\n", + " 7 O -4.213042 -0.497148 -0.466639\n", + " 8 H -4.785111 -1.037428 0.099864\n", + " 9 H 1.886096 -0.119936 -1.306017\n", + " 10 O 1.562164 -0.660552 -0.571629\n", + " 11 H 2.444923 -1.446147 -0.071511\n", + " 12 Hg -0.268946 -0.216956 -0.036806,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s14.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.433859 -0.186385 -0.209346\n", + " 1 O -2.910003 -1.104610 1.549563\n", + " 2 H -3.650028 -1.659911 1.269801\n", + " 3 H -3.091479 -0.901530 2.476635\n", + " 4 O 1.842448 1.211620 -0.743795\n", + " 5 H 1.616967 2.232129 -0.748408\n", + " 6 H 2.744465 1.085772 -0.418988\n", + " 7 O -0.574432 -1.777392 0.689620\n", + " 8 H -1.469621 -1.587443 1.114669\n", + " 9 H -0.093612 -2.422219 1.226374\n", + " 10 O 0.345511 -1.127734 -2.402759\n", + " 11 H -0.202976 -1.864035 -2.697512\n", + " 12 H 0.960765 -0.959967 -3.126236\n", + " 13 O -1.713337 0.808290 -0.268561\n", + " 14 H -2.444457 0.488336 0.279291\n", + " 15 H -2.066289 1.506610 -0.831180\n", + " 16 O 1.220810 3.605257 -0.851049\n", + " 17 H 1.348709 4.228884 -0.126465\n", + " 18 H 1.427643 4.091021 -1.658736,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s6.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 1.818124 -1.374399 -0.709468\n", + " 1 O -2.184374 -0.470873 -1.128476\n", + " 2 H -2.575883 -0.740098 -1.969631\n", + " 3 H -2.921189 -0.326435 -0.345636\n", + " 4 O -3.771707 -0.065304 0.661118\n", + " 5 H -4.547713 -0.611736 0.831690\n", + " 6 H -4.022513 0.848702 0.841712\n", + " 7 O 0.120501 -4.362084 -0.022064\n", + " 8 H -0.058347 -4.730559 0.849823\n", + " 9 H -0.033924 -5.086793 -0.637701\n", + " 10 O -0.042367 -1.836380 -0.627975\n", + " 11 H -0.077449 -2.812408 -0.394373\n", + " 12 H -1.378583 -1.032517 -0.908295\n", + " 13 O 3.766436 -0.773938 -0.820795\n", + " 14 H 4.335567 -1.031779 -1.562884\n", + " 15 H 4.318311 -0.689459 -0.027494,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 2.600000e-09 0.010739\n", + " 1 O 1.821376 8.000000e-08 -0.090165\n", + " 2 H 2.325945 -7.989195e-01 0.177310\n", + " 3 H 2.325945 7.989197e-01 0.177310,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H 1.465191 -0.168688 -2.470133\n", + " 1 O 1.551722 -0.160537 -1.505854\n", + " 2 H 2.382882 -0.609382 -1.294379\n", + " 3 H -2.699888 -0.951794 0.509565\n", + " 4 O -2.229523 -0.365731 -0.102092\n", + " 5 H -2.755488 -0.317063 -0.914515\n", + " 6 H 1.269790 -1.850941 1.828448\n", + " 7 O 1.251734 -0.933711 1.520616\n", + " 8 H 1.606850 -0.396922 2.243261\n", + " 9 H -0.393270 2.668594 0.981053\n", + " 10 O 0.244152 2.088409 0.542415\n", + " 11 H 0.900006 2.669523 0.133525\n", + " 12 Hg -0.104009 -0.075885 -0.058219,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.382557 -0.044085 -0.000312\n", + " 1 O 2.286461 0.639488 -0.000193\n", + " 2 H 2.850681 0.582739 -0.790182\n", + " 3 H 2.850188 0.583476 0.790200\n", + " 4 O -1.480339 -0.592168 -0.000189\n", + " 5 H -2.789681 0.086364 0.000164\n", + " 6 H -1.539437 -1.561275 -0.000488\n", + " 7 O -3.685766 0.615080 0.000118\n", + " 8 H -4.226512 0.481465 -0.797912\n", + " 9 H -4.226965 0.480951 0.797755,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.213891 0.985545 1.772239\n", + " 1 O 1.652717 0.573054 1.252535\n", + " 2 H 2.239996 0.982438 0.425480\n", + " 3 H 1.906127 -0.323837 1.518491\n", + " 4 O -2.046423 1.548248 2.241517\n", + " 5 H -2.589364 2.564087 2.049059\n", + " 6 H -2.552267 0.929653 2.785081\n", + " 7 O 0.290677 -1.317859 2.856418\n", + " 8 H 0.555839 -1.459083 3.774303\n", + " 9 H -0.056865 -2.174070 2.576034\n", + " 10 O -3.101371 3.644887 1.798776\n", + " 11 H -3.868079 3.651177 1.209145\n", + " 12 H -3.287833 4.238993 2.538836\n", + " 13 O 2.927684 1.574390 -0.538113\n", + " 14 H 3.746119 2.034338 -0.312261\n", + " 15 H 3.072095 1.136757 -1.386197,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.740815 -0.166542 0.000527\n", + " 1 O 1.305983 2.643994 -0.000036\n", + " 2 H 1.567043 3.158573 0.774397\n", + " 3 H 1.566940 3.158697 -0.774419\n", + " 4 O 1.184355 0.184104 -0.000069\n", + " 5 H 2.325330 -0.826148 -0.000177\n", + " 6 H 1.277519 1.250731 -0.000144\n", + " 7 O 3.058172 -1.547673 -0.000015\n", + " 8 H 3.614001 -1.548166 -0.799942\n", + " 9 H 3.613971 -1.547842 0.799936,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s4.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.30295 0.54243 0.67902\n", + " 1 O -2.67596 -0.16059 0.27283\n", + " 2 H -3.12195 -0.75994 -0.43074\n", + " 3 H 3.71838 0.86623 1.59224\n", + " 4 O 3.38597 0.25586 0.92017\n", + " 5 H 4.18691 -0.16199 0.33989\n", + " 6 H -0.24813 1.43642 -1.17337\n", + " 7 O -0.24681 0.78986 -0.45203\n", + " 8 H -1.81245 0.21164 -0.02258\n", + " 9 H -3.96272 -2.60309 -1.14342\n", + " 10 O -3.70723 -1.71151 -1.40213\n", + " 11 H -4.26694 -1.47642 -2.14892\n", + " 12 H -4.77017 2.14393 0.93780\n", + " 13 O -4.15792 1.53801 1.36708\n", + " 14 H -4.51181 1.37620 2.24785\n", + " 15 H 5.52425 -1.60273 -0.11804\n", + " 16 O 5.12842 -0.77866 -0.42698\n", + " 17 H 5.82673 -0.28093 -0.86882\n", + " 18 Hg 1.56140 0.57914 0.18935,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s2.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -5.524051 -0.895808 0.475382\n", + " 1 O -4.854601 -0.714706 -0.195096\n", + " 2 H -5.274591 -0.820318 -1.057521\n", + " 3 H 3.342234 1.500760 -0.108671\n", + " 4 O 2.864612 0.688621 -0.326560\n", + " 5 H 3.544355 -0.139917 -0.526430\n", + " 6 H -3.951276 0.236575 -0.034455\n", + " 7 O -3.161064 0.995523 0.026738\n", + " 8 H -3.459104 1.826286 0.420021\n", + " 9 H 4.611510 -1.305366 -1.730443\n", + " 10 O 4.293323 -1.199103 -0.825099\n", + " 11 H 5.004923 -1.484824 -0.238914\n", + " 12 H -2.285563 0.712207 0.417413\n", + " 13 O -0.811024 0.305806 0.980027\n", + " 14 H -0.820717 -0.076229 1.870121\n", + " 15 Hg 1.023597 0.484591 0.388560,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s22.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.70393 -0.54642 -0.15373\n", + " 1 O -0.58175 -1.97096 0.52324\n", + " 2 H -0.56651 -2.83520 0.08969\n", + " 3 H -1.59085 -1.65592 0.74513\n", + " 4 O 1.57098 0.85796 1.61486\n", + " 5 H 1.97075 0.52961 2.43109\n", + " 6 H 1.14083 1.68642 1.86241\n", + " 7 O -2.77211 -1.12001 1.10365\n", + " 8 H -3.25992 -0.54595 0.48392\n", + " 9 H -3.40092 -1.62359 1.63287\n", + " 10 O -0.72635 1.19065 -0.82696\n", + " 11 H -1.70503 1.14135 -0.85663\n", + " 12 H -0.46928 1.88324 -1.44672\n", + " 13 O -3.49176 0.84224 -0.70672\n", + " 14 H -3.97888 1.57676 -0.31062\n", + " 15 H -3.97952 0.64376 -1.51654\n", + " 16 O 2.35295 0.42869 -1.07113\n", + " 17 H 2.95489 0.86443 -0.44839\n", + " 18 H 2.88670 0.03864 -1.77947,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s23.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.585401 -0.196527 -0.248645\n", + " 1 O -0.786191 1.681191 0.073988\n", + " 2 H -0.499333 2.586044 -0.095835\n", + " 3 H -1.765082 1.685281 0.017945\n", + " 4 O -2.928431 -1.231729 0.508886\n", + " 5 H -3.388936 -0.403973 0.276341\n", + " 6 H -3.580541 -1.916247 0.696613\n", + " 7 O 1.449195 0.057122 1.995584\n", + " 8 H 1.824131 -0.659435 2.524564\n", + " 9 H 1.033753 0.649657 2.635086\n", + " 10 O -0.747132 -1.725523 -0.418642\n", + " 11 H -1.751982 -1.540640 -0.070807\n", + " 12 H -0.744120 -2.238025 -1.238676\n", + " 13 O 2.276929 1.060256 -0.519459\n", + " 14 H 2.877195 1.091023 0.241260\n", + " 15 H 2.814696 1.078074 -1.325214\n", + " 16 O -3.559698 1.409773 -0.018678\n", + " 17 H -4.034966 1.677561 -0.815872\n", + " 18 H -4.036711 1.846110 0.699498,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -3.091110 1.774449 -0.551765\n", + " 1 O -2.961238 0.817046 -0.538799\n", + " 2 H -3.877099 0.257944 -0.310746\n", + " 3 H 3.061446 -1.756575 -0.501440\n", + " 4 O 2.854601 -0.814615 -0.430850\n", + " 5 H 3.750843 -0.211529 -0.280308\n", + " 6 H -5.398879 -0.887569 -0.850245\n", + " 7 O -4.941965 -0.495853 -0.095844\n", + " 8 H -5.613294 -0.252069 0.552523\n", + " 9 H -0.804912 0.216858 1.699713\n", + " 10 O -0.744652 0.211224 0.732954\n", + " 11 H -2.139930 0.577896 -0.021040\n", + " 12 H 5.258526 0.913606 -0.919176\n", + " 13 O 4.786418 0.610216 -0.133520\n", + " 14 H 5.446874 0.458652 0.553819\n", + " 15 Hg 1.044511 -0.313990 0.212932,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s5.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.000047 0.109967 0.000775\n", + " 1 O -1.943126 0.145411 0.178212\n", + " 2 H -2.431656 -0.627877 0.671557\n", + " 3 H -2.508504 0.661137 -0.525713\n", + " 4 O -3.009793 -1.693878 1.449449\n", + " 5 H -3.463250 -2.449594 1.059367\n", + " 6 H -3.464368 -1.505383 2.278603\n", + " 7 O 1.943250 0.145113 -0.176494\n", + " 8 H 2.431182 -0.625772 -0.674147\n", + " 9 H 2.508939 0.656217 0.530545\n", + " 10 O 3.189958 1.467263 1.505083\n", + " 11 H 3.657015 1.107269 2.267377\n", + " 12 H 3.675584 2.256307 1.238286\n", + " 13 O 3.008545 -1.687843 -1.458045\n", + " 14 H 3.463147 -1.495017 -2.286188\n", + " 15 H 3.461530 -2.446054 -1.072279\n", + " 16 O -3.188927 1.478433 -1.495429\n", + " 17 H -3.656373 1.123259 -2.259744\n", + " 18 H -3.673847 2.266334 -1.224014,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s10.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.10449 0.27043 -0.12521\n", + " 1 O 2.94298 2.45467 0.30594\n", + " 2 H 3.26698 2.89180 1.10172\n", + " 3 H 3.52729 2.73436 -0.40737\n", + " 4 O 3.02985 -1.85717 0.11576\n", + " 5 H 3.61110 -2.03167 -0.63304\n", + " 6 H 3.42747 -2.30886 0.86896\n", + " 7 O -1.97426 0.39080 -0.81851\n", + " 8 H -2.82806 0.39999 -0.16468\n", + " 9 H -2.12943 0.95629 -1.58795\n", + " 10 O -0.87738 -1.72186 1.18247\n", + " 11 H -0.91863 -1.80465 2.14211\n", + " 12 H -1.01357 -2.61645 0.84983\n", + " 13 O -3.88886 0.34634 0.68947\n", + " 14 H -4.54901 -0.34593 0.56085\n", + " 15 H -4.37169 1.14501 0.93538\n", + " 16 O 1.76527 0.26201 0.49953\n", + " 17 H 2.30312 1.13518 0.38853\n", + " 18 H 2.32458 -0.58669 0.31761,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.000095 -0.106079 0.003892\n", + " 1 O 5.854318 -0.393233 0.365965\n", + " 2 H 6.505820 -0.700211 -0.273878\n", + " 3 H 6.317042 -0.283293 1.204203\n", + " 4 O -5.854733 -0.399350 -0.350200\n", + " 5 H -6.506419 -0.688561 0.297681\n", + " 6 H -6.317396 -0.311826 -1.191107\n", + " 7 O -3.931238 1.056244 0.113445\n", + " 8 H -4.135608 1.807394 0.685133\n", + " 9 H -4.774793 0.440972 -0.043615\n", + " 10 O 3.931835 1.050580 -0.136804\n", + " 11 H 4.775021 0.439202 0.036799\n", + " 12 H 4.136677 1.785974 -0.728458\n", + " 13 O 1.782577 -0.075615 -0.788881\n", + " 14 H 3.070968 0.566532 -0.423654\n", + " 15 H 1.829454 -0.685100 -1.537459\n", + " 16 O -1.782733 -0.053301 0.795583\n", + " 17 H -3.070642 0.579521 0.413192\n", + " 18 H -1.830033 -0.642618 1.560114,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s15.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 H -1.09653 2.59570 -1.06939\n", + " 1 O -1.08850 1.64706 -1.24461\n", + " 2 H -1.61937 1.51473 -2.03918\n", + " 3 H 1.61965 2.12366 1.39376\n", + " 4 O 0.79189 1.63361 1.46674\n", + " 5 H 0.35885 1.95276 2.26756\n", + " 6 H 2.02180 0.86783 -2.05670\n", + " 7 O 1.90484 0.25751 -1.31879\n", + " 8 H 2.73706 -0.22247 -1.23102\n", + " 9 H -2.01909 -0.87011 2.05946\n", + " 10 O -1.90643 -0.25981 1.32088\n", + " 11 H -2.73949 0.21943 1.23712\n", + " 12 H 1.61727 -1.51829 2.03723\n", + " 13 O 1.08715 -1.64644 1.24147\n", + " 14 H 1.09158 -2.59469 1.06403\n", + " 15 H -0.35378 -1.94761 -2.26662\n", + " 16 O -0.78889 -1.63200 -1.46552\n", + " 17 H -1.61665 -2.12267 -1.39678\n", + " 18 Hg -0.00152 0.00221 0.00115,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s3.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.358532 -2.383665 1.248423\n", + " 1 O 1.778630 -3.417608 0.378980\n", + " 2 H 2.043565 -3.617024 -0.829481\n", + " 3 H 2.384508 -3.852214 0.995122\n", + " 4 O -1.085048 -1.333344 2.035483\n", + " 5 H -0.861829 -0.403607 2.452310\n", + " 6 H -1.896449 -1.831986 2.461046\n", + " 7 O -3.011426 -2.599093 2.930117\n", + " 8 H -3.159445 -2.811790 3.858597\n", + " 9 H -3.884269 -2.485728 2.536090\n", + " 10 O -0.477860 0.898853 2.908916\n", + " 11 H -0.859329 1.689866 2.510498\n", + " 12 H -0.317246 1.113146 3.834932\n", + " 13 O 2.233641 -3.761780 -1.949244\n", + " 14 H 2.136654 -4.666379 -2.282636\n", + " 15 H 3.060857 -3.390321 -2.290694,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s21.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.088535 0.075710 0.080844\n", + " 1 O -1.110178 1.812787 -0.935563\n", + " 2 H -1.730419 1.765961 -1.674000\n", + " 3 H -1.404001 2.554941 -0.392210\n", + " 4 O -1.806389 -1.225386 0.528828\n", + " 5 H -2.608305 -0.978974 1.006728\n", + " 6 H -2.079177 -1.887525 -0.118865\n", + " 7 O 0.202651 1.697133 1.767070\n", + " 8 H -0.145778 1.657574 2.666629\n", + " 9 H 0.979803 2.268493 1.810994\n", + " 10 O 0.342289 -1.598189 -1.538271\n", + " 11 H 0.903992 -2.357518 -1.337619\n", + " 12 H 0.352085 -1.510787 -2.499751\n", + " 13 O 1.050224 -1.617834 1.382647\n", + " 14 H 0.470616 -2.203019 1.886600\n", + " 15 H 1.891639 -1.609934 1.856078\n", + " 16 O 1.856972 1.384502 -0.723042\n", + " 17 H 2.775690 1.129400 -0.874881\n", + " 18 H 1.666541 2.077517 -1.367881,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s11.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.283345 -0.018428 -0.950445\n", + " 1 O 1.041965 -0.381550 1.350401\n", + " 2 H 0.502089 -0.901250 1.961120\n", + " 3 H 1.879804 -0.221333 1.799456\n", + " 4 O -1.343173 -1.984925 1.874553\n", + " 5 H -1.260602 -2.928618 2.064187\n", + " 6 H -2.035913 -1.672258 2.470319\n", + " 7 O -3.151897 -1.267175 -2.135751\n", + " 8 H -3.354776 -2.044432 -2.668808\n", + " 9 H -3.990630 -0.818036 -1.983068\n", + " 10 O 1.762787 1.209454 -1.501096\n", + " 11 H 2.125198 1.269714 -2.515856\n", + " 12 H 1.800471 2.072970 -1.066995\n", + " 13 O -1.196141 -1.293839 -0.611334\n", + " 14 H -2.051893 -1.281920 -1.197554\n", + " 15 H -1.350081 -1.567453 0.345621\n", + " 16 O 2.599059 1.221450 -3.782258\n", + " 17 H 3.528109 1.003450 -3.928033\n", + " 18 H 2.361893 1.888893 -4.437486,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s13.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.131450 -0.158248 0.013833\n", + " 1 O 3.056667 -2.012862 -1.374074\n", + " 2 H 3.547938 -2.754564 -1.001640\n", + " 3 H 3.533581 -1.744019 -2.167558\n", + " 4 O -0.370637 -0.440129 2.454929\n", + " 5 H 0.261593 -0.905658 3.015539\n", + " 6 H -1.199024 -0.461167 2.948898\n", + " 7 O -3.232632 -1.866376 -1.570282\n", + " 8 H -3.442354 -1.835729 -2.511132\n", + " 9 H -3.953159 -2.347086 -1.145336\n", + " 10 O 0.610240 2.070571 0.848426\n", + " 11 H 0.719899 2.927853 0.418532\n", + " 12 H 0.490121 2.271781 1.784655\n", + " 13 O 1.865487 -0.487383 0.156240\n", + " 14 H 2.402771 -1.092936 -0.510888\n", + " 15 H 2.353499 0.325523 0.352748\n", + " 16 O -2.124279 -0.060244 -0.333313\n", + " 17 H -2.621379 -0.802313 -0.901945\n", + " 18 H -2.489120 0.811335 -0.539202,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s16.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.264147 -0.117851 -0.197904\n", + " 1 O 1.820169 1.741017 0.359196\n", + " 2 H 2.218609 1.733706 1.239009\n", + " 3 H 1.772656 2.673480 0.111842\n", + " 4 O -2.611030 2.373459 0.046513\n", + " 5 H -3.139015 2.658377 -0.707808\n", + " 6 H -2.977139 2.835840 0.809335\n", + " 7 O 1.395302 -0.971701 1.793827\n", + " 8 H 2.101725 -1.629317 1.780004\n", + " 9 H 0.993301 -1.059012 2.666928\n", + " 10 O 2.097453 -0.540192 -1.120282\n", + " 11 H 2.180183 -0.954124 -1.992656\n", + " 12 H 2.696164 0.223658 -1.079452\n", + " 13 O -1.637659 0.083032 0.386043\n", + " 14 H -2.082281 0.991840 0.212297\n", + " 15 H -2.263650 -0.702011 0.165122\n", + " 16 O -3.054748 -1.930988 -0.082553\n", + " 17 H -3.620484 -2.071881 -0.849760\n", + " 18 H -3.483646 -2.391438 0.647732,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s9.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.454001 -0.230491 0.051961\n", + " 1 O -2.926548 -2.040462 -0.119173\n", + " 2 H -3.440602 -2.399947 0.613975\n", + " 3 H -3.425601 -2.224857 -0.923500\n", + " 4 O -1.508180 -0.082228 0.254383\n", + " 5 H -1.884757 0.842482 0.093946\n", + " 6 H -2.159102 -0.895507 0.057334\n", + " 7 O 2.468409 -0.631088 -0.065997\n", + " 8 H 2.853823 -1.390179 0.401365\n", + " 9 H 2.940776 -0.531484 -0.908335\n", + " 10 O 0.762418 2.135494 -0.049394\n", + " 11 H -0.019876 2.703344 -0.088988\n", + " 12 H 1.515728 2.715230 0.117127\n", + " 13 O -2.187243 2.374918 -0.063904\n", + " 14 H -2.633097 2.800941 0.680607\n", + " 15 H -2.657532 2.692245 -0.846194,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s19.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.219781 0.043323 -0.071931\n", + " 1 O 1.728776 -0.648755 -1.630435\n", + " 2 H 1.671640 -0.544383 -2.588953\n", + " 3 H 2.305430 -1.407361 -1.472859\n", + " 4 O -1.408154 1.523153 0.060729\n", + " 5 H -1.383567 2.407664 -0.323951\n", + " 6 H -2.337020 1.193301 0.034271\n", + " 7 O -3.705516 0.117397 0.085283\n", + " 8 H -4.364440 0.179521 -0.618682\n", + " 9 H -4.224488 0.113434 0.900517\n", + " 10 O 1.284661 -1.282622 1.470151\n", + " 11 H 0.851028 -1.990735 1.963227\n", + " 12 H 1.991005 -0.951244 2.039137\n", + " 13 O -1.469720 -1.508460 -0.114862\n", + " 14 H -2.388404 -1.175197 -0.086347\n", + " 15 H -1.482056 -2.356209 -0.574937\n", + " 16 O 1.836552 1.634101 0.509352\n", + " 17 H 2.605863 1.839398 -0.036318\n", + " 18 H 1.752780 2.362852 1.137071,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s8.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg 0.35341 -0.42231 -0.13125\n", + " 1 O -3.61498 0.55542 0.63264\n", + " 2 H -4.45213 0.15523 0.10478\n", + " 3 H -3.83988 0.79310 1.54165\n", + " 4 O -5.49058 -0.32220 -0.66470\n", + " 5 H -6.15043 -0.94067 -0.33132\n", + " 6 H -5.94202 0.26328 -1.28369\n", + " 7 O -1.43536 -0.75833 0.57691\n", + " 8 H -2.75732 0.00697 0.60004\n", + " 9 H -1.53667 -1.70331 0.75771\n", + " 10 O 4.06883 0.38581 0.54566\n", + " 11 H 4.70085 -0.27662 0.84850\n", + " 12 H 4.57755 1.18868 0.38296\n", + " 13 O 0.74772 1.94827 0.73838\n", + " 14 H 0.79237 2.23108 1.65822\n", + " 15 H 0.75585 2.76588 0.22861\n", + " 16 O 2.17043 -0.13464 -0.94256\n", + " 17 H 2.99527 0.06251 -0.32171\n", + " 18 H 2.43662 -0.73175 -1.65542,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s6.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.550981 -0.106655 -0.161353\n", + " 1 O 1.143555 3.023832 0.118923\n", + " 2 H 1.509272 3.534737 -0.610619\n", + " 3 H 1.113717 3.634246 0.862953\n", + " 4 O -2.378949 -0.741668 -0.639898\n", + " 5 H -3.232588 -0.633361 -0.005267\n", + " 6 H -2.629734 -0.758515 -1.573014\n", + " 7 O 1.234848 0.416894 0.329744\n", + " 8 H 1.288420 1.412403 0.271016\n", + " 9 H 2.430794 -0.366712 0.720247\n", + " 10 O -4.261353 -0.539800 0.894286\n", + " 11 H -4.937535 0.144290 0.823042\n", + " 12 H -4.707025 -1.342754 1.190332\n", + " 13 O 3.217361 -0.963883 1.009201\n", + " 14 H 4.085665 -0.932678 0.408369\n", + " 15 H 3.422672 -0.851453 1.946089\n", + " 16 O 5.190712 -0.970343 -0.452485\n", + " 17 H 5.942882 -0.373060 -0.377103\n", + " 18 H 5.537773 -1.816307 -0.757613}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_other: Path = working_dir / \"files_xyz\"\n", + "\n", + "files_hf: list = glob(str(dir_other / \"hf\" / \"*.xyz\"))\n", + "files_pbe0: list = glob(str(dir_other / \"pbe0\" / \"*.xyz\"))\n", + "files_camb3lyp: list = glob(str(dir_other / \"camb3lyp\" / \"*.xyz\"))\n", + "files_wb97xd: list = glob(str(dir_other / \"wb97xd_grimmeD2\" / \"*.xyz\"))\n", + "files_b2plypd3: list = glob(str(dir_other / \"b2plypd3\" / \"*.xyz\"))\n", + "files_pbeqidh: list = glob(str(dir_other / \"pbeqidh\" / \"*.xyz\"))\n", + "files_mp2: list = glob(str(dir_other / \"mp2\" / \"*.xyz\"))\n", + "files_zora_sr: list = glob(str(dir_other / \"zora\" / \"sr\" / \"*.xyz\"))\n", + "files_zora_so: list = glob(str(dir_other / \"zora\" / \"so\" / \"*.xyz\"))\n", + "\n", + "\n", + "coordinates_hf: dict = functions.dict_coordinates_xyz(files_hf)\n", + "coordinates_pbe0: dict = functions.dict_coordinates_xyz(files_pbe0)\n", + "coordinates_camb3lyp: dict = functions.dict_coordinates_xyz(files_camb3lyp)\n", + "coordinates_wb97xd: dict = functions.dict_coordinates_xyz(files_wb97xd)\n", + "coordinates_b2plypd3: dict = functions.dict_coordinates_xyz(files_b2plypd3)\n", + "coordinates_pbeqidh: dict = functions.dict_coordinates_xyz(files_pbeqidh)\n", + "coordinates_mp2: dict = functions.dict_coordinates_xyz(files_mp2)\n", + "coordinates_zora_sr: dict = functions.dict_coordinates_xyz(files_zora_sr)\n", + "coordinates_zora_so: dict = functions.dict_coordinates_xyz(files_zora_so)\n", + "\n", + "coordinates_mp2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s7.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.383257 2.989609 3.058074 2.151334 2.816800 \n", + " 1 O 2.383257 0.000000 0.966285 0.966598 2.860677 3.770227 \n", + " 2 H 2.989609 0.966285 0.000000 1.536827 3.399089 4.352765 \n", + " 3 H 3.058074 0.966598 1.536827 0.000000 3.579619 4.410336 \n", + " 4 O 2.151334 2.860677 3.399089 3.579619 0.000000 0.968779 \n", + " 5 H 2.816800 3.770227 4.352765 4.410336 0.968779 0.000000 \n", + " 6 H 2.708972 2.555218 3.071155 3.155471 0.969210 1.563908 \n", + " 7 O 3.913819 5.703443 6.481171 5.849703 5.387064 5.461692 \n", + " 8 H 4.532217 6.506715 7.254153 6.725388 5.928466 5.910116 \n", + " 9 H 4.578106 6.092433 6.892944 6.091536 6.059518 6.158283 \n", + " 10 O 2.041075 3.767066 4.361907 4.095809 4.090583 4.559660 \n", + " 11 H 2.776995 4.589384 5.283538 4.828828 4.573702 4.854593 \n", + " 12 H 2.640925 4.245228 4.673092 4.609865 4.760222 5.282619 \n", + " 13 O 2.349788 3.125244 2.995284 4.059408 2.981526 3.738967 \n", + " 14 H 3.044594 3.774738 3.505716 4.652210 3.940898 4.676256 \n", + " 15 H 2.970362 3.671284 3.503371 4.635967 2.941765 3.578101 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.708972 3.913819 4.532217 4.578106 2.041075 2.776995 2.640925 \n", + " 1 2.555218 5.703443 6.506715 6.092433 3.767066 4.589384 4.245228 \n", + " 2 3.071155 6.481171 7.254153 6.892944 4.361907 5.283538 4.673092 \n", + " 3 3.155471 5.849703 6.725388 6.091536 4.095809 4.828828 4.609865 \n", + " 4 0.969210 5.387064 5.928466 6.059518 4.090583 4.573702 4.760222 \n", + " 5 1.563908 5.461692 5.910116 6.158283 4.559660 4.854593 5.282619 \n", + " 6 0.000000 5.979114 6.608833 6.553004 4.644968 5.165287 5.337954 \n", + " 7 5.979114 0.000000 0.965037 0.965404 2.438552 1.370124 2.956219 \n", + " 8 6.608833 0.965037 0.000000 1.547520 3.079610 2.048548 3.428040 \n", + " 9 6.553004 0.965404 1.547520 0.000000 3.019886 2.024652 3.499314 \n", + " 10 4.644968 2.438552 3.079610 3.019886 0.000000 1.070760 0.966427 \n", + " 11 5.165287 1.370124 2.048548 2.024652 1.070760 0.000000 1.675725 \n", + " 12 5.337954 2.956219 3.428040 3.499314 0.966427 1.675725 0.000000 \n", + " 13 3.460215 5.927073 6.370416 6.668781 3.769601 4.684399 3.811368 \n", + " 14 4.416051 6.292008 6.680190 7.026403 4.051002 5.005046 3.855981 \n", + " 15 3.420364 6.564936 6.952491 7.353184 4.566930 5.402219 4.666671 \n", + " \n", + " 13 14 15 \n", + " 0 2.349788 3.044594 2.970362 \n", + " 1 3.125244 3.774738 3.671284 \n", + " 2 2.995284 3.505716 3.503371 \n", + " 3 4.059408 4.652210 4.635967 \n", + " 4 2.981526 3.940898 2.941765 \n", + " 5 3.738967 4.676256 3.578101 \n", + " 6 3.460215 4.416051 3.420364 \n", + " 7 5.927073 6.292008 6.564936 \n", + " 8 6.370416 6.680190 6.952491 \n", + " 9 6.668781 7.026403 7.353184 \n", + " 10 3.769601 4.051002 4.566930 \n", + " 11 4.684399 5.005046 5.402219 \n", + " 12 3.811368 3.855981 4.666671 \n", + " 13 0.000000 0.966093 0.966075 \n", + " 14 0.966093 0.000000 1.536722 \n", + " 15 0.966075 1.536722 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w2s1.xyz': atoms 0 1 2 3 4 5 6\n", + " 0 Hg 0.000000 2.002985 2.655729 2.654230 2.002865 2.656279 2.654369\n", + " 1 O 2.002985 0.000000 0.976266 0.976423 4.004762 4.615825 4.590586\n", + " 2 H 2.655729 0.976266 0.000000 1.593604 4.615022 5.145897 5.186565\n", + " 3 H 2.654230 0.976423 1.593604 0.000000 4.590420 5.186685 5.224375\n", + " 4 O 2.002865 4.004762 4.615022 4.590420 0.000000 0.976235 0.976387\n", + " 5 H 2.656279 4.615825 5.145897 5.186685 0.976235 0.000000 1.593656\n", + " 6 H 2.654369 4.590586 5.186565 5.224375 0.976387 1.593656 0.000000,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.476439 3.157390 3.157492 1.992162 2.761174 \n", + " 1 O 2.476439 0.000000 0.964459 0.964459 3.236363 3.433535 \n", + " 2 H 3.157390 0.964459 0.000000 1.530762 3.948956 3.955251 \n", + " 3 H 3.157492 0.964459 1.530762 0.000000 3.632443 3.829023 \n", + " 4 O 1.992162 3.236363 3.948956 3.632443 0.000000 1.103796 \n", + " 5 H 2.761174 3.433535 3.955251 3.829023 1.103796 0.000000 \n", + " 6 H 2.573374 4.147842 4.896483 4.495055 0.968105 1.708196 \n", + " 7 O 3.873678 4.002712 4.277960 4.355688 2.415245 1.312660 \n", + " 8 H 4.461573 4.824708 5.026312 5.256855 3.036721 1.982674 \n", + " 9 H 4.554601 4.335068 4.606895 4.492507 2.985620 1.962392 \n", + " 10 O 1.992301 3.230963 3.627591 3.944756 3.981886 4.699314 \n", + " 11 H 2.573725 4.143252 4.490835 4.892755 4.471212 5.198004 \n", + " 12 H 2.760154 3.425543 3.822187 3.948520 4.698159 5.462404 \n", + " 13 O 3.873179 3.993639 4.348054 4.269387 5.692394 6.469403 \n", + " 14 H 4.553997 4.324596 4.483174 4.596566 6.400692 7.087488 \n", + " 15 H 4.461469 4.816373 5.249788 5.018397 6.219620 7.086176 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.573374 3.873678 4.461573 4.554601 1.992301 2.573725 2.760154 \n", + " 1 4.147842 4.002712 4.824708 4.335068 3.230963 4.143252 3.425543 \n", + " 2 4.896483 4.277960 5.026312 4.606895 3.627591 4.490835 3.822187 \n", + " 3 4.495055 4.355688 5.256855 4.492507 3.944756 4.892755 3.948520 \n", + " 4 0.968105 2.415245 3.036721 2.985620 3.981886 4.471212 4.698159 \n", + " 5 1.708196 1.312660 1.982674 1.962392 4.699314 5.198004 5.462404 \n", + " 6 0.000000 2.927477 3.371214 3.447841 4.470990 4.826291 5.196431 \n", + " 7 2.927477 0.000000 0.965974 0.966087 5.693303 6.197755 6.469177 \n", + " 8 3.371214 0.965974 0.000000 1.552835 6.220109 6.612201 7.085603 \n", + " 9 3.447841 0.966087 1.552835 0.000000 6.401839 6.979995 7.087525 \n", + " 10 4.470990 5.693303 6.220109 6.401839 0.000000 0.968110 1.103148 \n", + " 11 4.826291 6.197755 6.612201 6.979995 0.968110 0.000000 1.707520 \n", + " 12 5.196431 6.469177 7.085603 7.087525 1.103148 1.707520 0.000000 \n", + " 13 6.196249 7.462422 8.156641 7.983255 2.415646 2.927703 1.313706 \n", + " 14 6.978406 7.983110 8.670056 8.496880 2.986077 3.448658 1.963403 \n", + " 15 6.611043 8.156816 8.851102 8.670260 3.037362 3.371411 1.983854 \n", + " \n", + " 13 14 15 \n", + " 0 3.873179 4.553997 4.461469 \n", + " 1 3.993639 4.324596 4.816373 \n", + " 2 4.348054 4.483174 5.249788 \n", + " 3 4.269387 4.596566 5.018397 \n", + " 4 5.692394 6.400692 6.219620 \n", + " 5 6.469403 7.087488 7.086176 \n", + " 6 6.196249 6.978406 6.611043 \n", + " 7 7.462422 7.983110 8.156816 \n", + " 8 8.156641 8.670056 8.851102 \n", + " 9 7.983255 8.496880 8.670260 \n", + " 10 2.415646 2.986077 3.037362 \n", + " 11 2.927703 3.448658 3.371411 \n", + " 12 1.313706 1.963403 1.983854 \n", + " 13 0.000000 0.966070 0.965961 \n", + " 14 0.966070 0.000000 1.552708 \n", + " 15 0.965961 1.552708 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.967518 1.570026 5.626979 5.271497 3.631580 \n", + " 1 O 0.967518 0.000000 0.967076 4.844350 4.597359 2.997423 \n", + " 2 H 1.570026 0.967076 0.000000 5.264049 5.160687 3.599504 \n", + " 3 H 5.626979 4.844350 5.264049 0.000000 0.970921 2.396637 \n", + " 4 O 5.271497 4.597359 5.160687 0.970921 0.000000 1.857291 \n", + " 5 H 3.631580 2.997423 3.599504 2.396637 1.857291 0.000000 \n", + " 6 H 9.036223 8.616070 9.363294 4.914353 4.551167 6.099929 \n", + " 7 O 8.613145 8.167674 8.897803 4.386678 3.961166 5.486389 \n", + " 8 H 9.362009 8.890608 9.590449 4.915397 4.549797 6.088293 \n", + " 9 H 1.834267 1.187358 1.849860 3.993771 3.643974 1.897453 \n", + " 10 O 2.932432 2.389904 2.997262 3.339636 2.832994 0.978641 \n", + " 11 H 3.493668 2.974759 3.387515 3.708932 3.253988 1.587261 \n", + " 12 Hg 6.846235 6.299839 6.965272 2.405993 1.926930 3.560040 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 9.036223 8.613145 9.362009 1.834267 2.932432 3.493668 6.846235 \n", + " 1 8.616070 8.167674 8.890608 1.187358 2.389904 2.974759 6.299839 \n", + " 2 9.363294 8.897803 9.590449 1.849860 2.997262 3.387515 6.965272 \n", + " 3 4.914353 4.386678 4.915397 3.993771 3.339636 3.708932 2.405993 \n", + " 4 4.551167 3.961166 4.549797 3.643974 2.832994 3.253988 1.926930 \n", + " 5 6.099929 5.486389 6.088293 1.897453 0.978641 1.587261 3.560040 \n", + " 6 0.000000 0.970779 1.574252 7.769910 6.952114 7.388146 2.674095 \n", + " 7 0.970779 0.000000 0.970811 7.238451 6.328766 6.674224 2.037011 \n", + " 8 1.574252 0.970811 0.000000 7.904850 6.922646 7.159053 2.673601 \n", + " 9 7.769910 7.238451 7.904850 0.000000 1.204656 1.849549 5.355025 \n", + " 10 6.952114 6.328766 6.922646 1.204656 0.000000 0.965236 4.468517 \n", + " 11 7.388146 6.674224 7.159053 1.849549 0.965236 0.000000 4.846180 \n", + " 12 2.674095 2.037011 2.673601 5.355025 4.468517 4.846180 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.971951 1.581726 5.144530 4.546299 5.191550 \n", + " 1 O 0.971951 0.000000 0.971950 4.604974 3.949708 4.574816 \n", + " 2 H 1.581726 0.971950 0.000000 5.143372 4.546369 5.192394 \n", + " 3 H 5.144530 4.604974 5.143372 0.000000 1.083439 1.876062 \n", + " 4 O 4.546299 3.949708 4.546369 1.083439 0.000000 1.084716 \n", + " 5 H 5.191550 4.574816 5.192394 1.876062 1.084716 0.000000 \n", + " 6 H 6.708952 6.165029 6.521080 2.017279 3.043405 3.646023 \n", + " 7 O 6.015604 5.548956 6.013357 1.343857 2.425937 3.138140 \n", + " 8 H 6.523273 6.165039 6.706483 2.017140 3.043115 3.646198 \n", + " 9 H 6.795971 6.098519 6.614612 3.648108 3.043536 2.015955 \n", + " 10 O 6.101246 5.485669 6.102928 3.137601 2.424736 1.341548 \n", + " 11 H 6.613117 6.098931 6.797948 3.648127 3.043275 2.015859 \n", + " 12 Hg 2.668920 2.020387 2.668926 2.647138 1.929777 2.643099 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 6.708952 6.015604 6.523273 6.795971 6.101246 6.613117 2.668920 \n", + " 1 6.165029 5.548956 6.165039 6.098519 5.485669 6.098931 2.020387 \n", + " 2 6.521080 6.013357 6.706483 6.614612 6.102928 6.797948 2.668926 \n", + " 3 2.017279 1.343857 2.017140 3.648108 3.137601 3.648127 2.647138 \n", + " 4 3.043405 2.425937 3.043115 3.043536 2.424736 3.043275 1.929777 \n", + " 5 3.646023 3.138140 3.646198 2.015955 1.341548 2.015859 2.643099 \n", + " 6 0.000000 0.965511 1.551911 4.922204 4.692754 5.161258 4.388920 \n", + " 7 0.965511 0.000000 0.965512 4.695658 4.287380 4.695818 3.745407 \n", + " 8 1.551911 0.965512 0.000000 5.161606 4.693171 4.922835 4.388816 \n", + " 9 4.922204 4.695658 5.161606 0.000000 0.965515 1.552400 4.377169 \n", + " 10 4.692754 4.287380 4.693171 0.965515 0.000000 0.965516 3.733757 \n", + " 11 5.161258 4.695818 4.922835 1.552400 0.965516 0.000000 4.377354 \n", + " 12 4.388920 3.745407 4.388816 4.377169 3.733757 4.377354 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s8.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.966354 1.553414 4.691569 4.089809 4.498128 \n", + " 1 O 0.966354 0.000000 0.966354 3.739647 3.186098 3.673118 \n", + " 2 H 1.553414 0.966354 0.000000 3.560039 3.119994 3.476561 \n", + " 3 H 4.691569 3.739647 3.560039 0.000000 0.965852 1.542595 \n", + " 4 O 4.089809 3.186098 3.119994 0.965852 0.000000 0.965882 \n", + " 5 H 4.498128 3.673118 3.476561 1.542595 0.965882 0.000000 \n", + " 6 H 3.924219 3.395091 3.923856 4.234964 4.219888 5.160126 \n", + " 7 O 3.944664 3.337591 3.944343 3.786622 3.676210 4.615585 \n", + " 8 H 4.887537 4.287849 4.887175 4.234913 4.220035 5.160352 \n", + " 9 H 3.559612 3.739258 4.691274 6.010682 5.290667 5.823144 \n", + " 10 O 3.119579 3.185808 4.089694 5.290667 4.501701 4.954481 \n", + " 11 H 3.476439 3.673161 4.498444 5.823144 4.954481 5.245562 \n", + " 12 H 5.487969 5.027077 5.703701 4.691795 4.090222 4.498574 \n", + " 13 O 5.026885 4.434556 5.026958 3.739726 3.186230 3.673105 \n", + " 14 H 5.703486 5.027011 5.487976 3.560277 3.120252 3.476586 \n", + " 15 Hg 2.884713 2.226698 2.884733 3.005365 2.333386 3.024661 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.924219 3.944664 4.887537 3.559612 3.119579 3.476439 5.487969 \n", + " 1 3.395091 3.337591 4.287849 3.739258 3.185808 3.673161 5.027077 \n", + " 2 3.923856 3.944343 4.887175 4.691274 4.089694 4.498444 5.703701 \n", + " 3 4.234964 3.786622 4.234913 6.010682 5.290667 5.823144 4.691795 \n", + " 4 4.219888 3.676210 4.220035 5.290667 4.501701 4.954481 4.090222 \n", + " 5 5.160126 4.615585 5.160352 5.823144 4.954481 5.245562 4.498574 \n", + " 6 0.000000 0.965489 1.546366 4.234642 4.219660 5.159992 4.888326 \n", + " 7 0.965489 0.000000 0.965489 3.786637 3.676222 4.615597 3.945567 \n", + " 8 1.546366 0.965489 0.000000 4.235261 4.220283 5.160505 3.925741 \n", + " 9 4.234642 3.786637 4.235261 0.000000 0.965852 1.542595 3.560685 \n", + " 10 4.219660 3.676222 4.220283 0.965852 0.000000 0.965882 3.120651 \n", + " 11 5.159992 4.615597 5.160505 1.542595 0.965882 0.000000 3.476693 \n", + " 12 4.888326 3.945567 3.925741 3.560685 3.120651 3.476693 0.000000 \n", + " 13 4.289053 3.338912 3.397071 3.740104 3.186510 3.673052 0.966352 \n", + " 14 4.888685 3.945883 3.926098 4.692079 4.090327 4.498247 1.553442 \n", + " 15 2.971953 2.291468 2.972125 3.005366 2.333388 3.024662 2.884716 \n", + " \n", + " 13 14 15 \n", + " 0 5.026885 5.703486 2.884713 \n", + " 1 4.434556 5.027011 2.226698 \n", + " 2 5.026958 5.487976 2.884733 \n", + " 3 3.739726 3.560277 3.005365 \n", + " 4 3.186230 3.120252 2.333386 \n", + " 5 3.673105 3.476586 3.024661 \n", + " 6 4.289053 4.888685 2.971953 \n", + " 7 3.338912 3.945883 2.291468 \n", + " 8 3.397071 3.926098 2.972125 \n", + " 9 3.740104 4.692079 3.005366 \n", + " 10 3.186510 4.090327 2.333388 \n", + " 11 3.673052 4.498247 3.024662 \n", + " 12 0.966352 1.553442 2.884716 \n", + " 13 0.000000 0.966352 2.226597 \n", + " 14 0.966352 0.000000 2.884697 \n", + " 15 2.226597 2.884697 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s12.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.963638 1.543320 6.188884 6.048607 7.021467 \n", + " 1 O 0.963638 0.000000 0.964115 5.626298 5.487599 6.442942 \n", + " 2 H 1.543320 0.964115 0.000000 6.202684 6.130698 7.076992 \n", + " 3 H 6.188884 5.626298 6.202684 0.000000 0.966846 1.682573 \n", + " 4 O 6.048607 5.487599 6.130698 0.966846 0.000000 1.067806 \n", + " 5 H 7.021467 6.442942 7.076992 1.682573 1.067806 0.000000 \n", + " 6 H 3.603836 3.080963 3.656909 5.193642 4.567202 5.147962 \n", + " 7 O 3.145894 2.474659 3.073339 4.472006 3.977216 4.696748 \n", + " 8 H 2.137026 1.438623 2.103514 4.884744 4.547527 5.395376 \n", + " 9 H 5.953922 5.466224 6.098409 5.171658 4.266587 4.319169 \n", + " 10 O 6.041820 5.508608 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5.147962 4.696748 5.395376 4.319169 3.358352 3.349637 2.040201 \n", + " 6 0.000000 1.004690 1.721587 2.512373 2.845224 3.789632 6.610686 \n", + " 7 1.004690 0.000000 1.039857 3.068845 3.100639 4.058996 6.297028 \n", + " 8 1.721587 1.039857 0.000000 4.048128 4.099774 5.057999 7.115354 \n", + " 9 2.512373 3.068845 4.048128 0.000000 0.967643 1.547194 5.233754 \n", + " 10 2.845224 3.100639 4.099774 0.967643 0.000000 0.963504 4.317923 \n", + " 11 3.789632 4.058996 5.057999 1.547194 0.963504 0.000000 3.900067 \n", + " 12 6.610686 6.297028 7.115354 5.233754 4.317923 3.900067 0.000000 \n", + " 13 6.040222 5.745984 6.549931 4.672639 3.727622 3.349516 0.965615 \n", + " 14 6.705101 6.440826 7.215452 5.239760 4.318761 3.853837 1.545748 \n", + " 15 2.203917 3.141280 3.752596 2.658245 3.497844 4.161056 7.610318 \n", + " 16 1.597615 2.592482 3.251853 2.098114 2.900855 3.643049 7.135571 \n", + " 17 2.243450 3.224629 3.714907 2.660739 3.494304 4.160678 7.798981 \n", + " 18 2.598768 1.984391 2.666017 3.025812 2.440057 3.193441 4.491858 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 8.277832 8.838974 5.349881 4.861782 4.992486 4.450971 \n", + " 1 7.693141 8.325990 4.916610 4.485659 4.796726 3.826376 \n", + " 2 8.324079 9.011570 5.278409 5.003999 5.367368 4.488905 \n", + " 3 2.969742 3.466549 7.018544 6.366545 6.976211 2.601584 \n", + " 4 2.442130 3.008136 6.270529 5.598664 6.195764 1.999907 \n", + " 5 1.376620 2.017026 6.585199 5.956471 6.566060 2.740541 \n", + " 6 6.040222 6.705101 2.203917 1.597615 2.243450 2.598768 \n", + " 7 5.745984 6.440826 3.141280 2.592482 3.224629 1.984391 \n", + " 8 6.549931 7.215452 3.752596 3.251853 3.714907 2.666017 \n", + " 9 4.672639 5.239760 2.658245 2.098114 2.660739 3.025812 \n", + " 10 3.727622 4.318761 3.497844 2.900855 3.494304 2.440057 \n", + " 11 3.349516 3.853837 4.161056 3.643049 4.160678 3.193441 \n", + " 12 0.965615 1.545748 7.610318 7.135571 7.798981 4.491858 \n", + " 13 0.000000 0.965987 7.141895 6.574826 7.169682 3.892561 \n", + " 14 0.965987 0.000000 7.803721 7.180589 7.688652 4.568983 \n", + " 15 7.141895 7.803721 0.000000 0.966204 1.530824 4.469600 \n", + " 16 6.574826 7.180589 0.966204 0.000000 0.965836 3.806928 \n", + " 17 7.169682 7.688652 1.530824 0.965836 0.000000 4.447433 \n", + " 18 3.892561 4.568983 4.469600 3.806928 4.447433 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s24.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.973694 1.579777 3.680347 3.078824 2.097459 \n", + " 1 O 0.973694 0.000000 0.963465 3.012556 2.430426 1.371666 \n", + " 2 H 1.579777 0.963465 0.000000 3.542903 3.093258 2.054036 \n", + " 3 H 3.680347 3.012556 3.542903 0.000000 0.969188 1.693339 \n", + " 4 O 3.078824 2.430426 3.093258 0.969188 0.000000 1.069910 \n", + " 5 H 2.097459 1.371666 2.054036 1.693339 1.069910 0.000000 \n", + " 6 H 4.859925 5.559267 6.406397 6.465385 5.868423 5.685015 \n", + " 7 O 4.049118 4.679992 5.559298 5.535269 4.913236 4.739309 \n", + " 8 H 3.305100 4.049101 4.859950 5.399955 4.740120 4.360696 \n", + " 9 H 5.400085 5.535315 6.465464 5.186219 4.550697 4.955103 \n", + " 10 O 4.740199 4.913269 5.868471 4.550687 3.970112 4.328231 \n", + " 11 H 4.360841 4.739389 5.685124 4.955059 4.328201 4.437886 \n", + " 12 H 2.393718 3.298430 3.705873 5.840023 5.126896 4.311497 \n", + " 13 O 1.922071 2.871108 3.434185 5.133946 4.493947 3.727341 \n", + " 14 H 2.423152 3.383437 3.831388 5.572620 5.059504 4.267909 \n", + " 15 H 6.438127 5.928718 6.622267 3.752594 3.654136 4.671206 \n", + " 16 O 5.969356 5.569567 6.347116 3.458391 3.340433 4.334290 \n", + " 17 H 6.717075 6.371388 7.170626 4.130377 4.137679 5.131988 \n", + " 18 Hg 3.708544 3.526230 4.432137 2.596317 2.003302 2.575113 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.859925 4.049118 3.305100 5.400085 4.740199 4.360841 2.393718 \n", + " 1 5.559267 4.679992 4.049101 5.535315 4.913269 4.739389 3.298430 \n", + " 2 6.406397 5.559298 4.859950 6.465464 5.868471 5.685124 3.705873 \n", + " 3 6.465385 5.535269 5.399955 5.186219 4.550687 4.955059 5.840023 \n", + " 4 5.868423 4.913236 4.740120 4.550697 3.970112 4.328201 5.126896 \n", + " 5 5.685015 4.739309 4.360696 4.955103 4.328231 4.437886 4.311497 \n", + " 6 0.000000 0.963466 1.579739 3.543105 3.093398 2.054254 3.831574 \n", + " 7 0.963466 0.000000 0.973688 3.012662 2.430514 1.371862 3.383624 \n", + " 8 1.579739 0.973688 0.000000 3.680544 3.078947 2.097697 2.423350 \n", + " 9 3.543105 3.012662 3.680544 0.000000 0.969185 1.693248 5.573087 \n", + " 10 3.093398 2.430514 3.078947 0.969185 0.000000 1.069810 5.059822 \n", + " 11 2.054254 1.371862 2.097697 1.693248 1.069810 0.000000 4.268331 \n", + " 12 3.831574 3.383624 2.423350 5.573087 5.059822 4.268331 0.000000 \n", + " 13 3.434457 2.871399 1.922375 5.134343 4.494228 3.727776 0.966775 \n", + " 14 3.706119 3.298708 2.393976 5.840340 5.127097 4.311878 1.521335 \n", + " 15 7.169777 6.370630 6.716514 4.128274 4.136402 5.130793 7.921272 \n", + " 16 6.346211 5.568766 5.968786 3.455942 3.338885 4.332951 7.353641 \n", + " 17 6.621459 5.928024 6.437649 3.750231 3.652679 4.669955 8.025338 \n", + " 18 4.432211 3.526286 3.708577 2.596345 2.003349 2.575100 4.957291 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.922071 2.423152 6.438127 5.969356 6.717075 3.708544 \n", + " 1 2.871108 3.383437 5.928718 5.569567 6.371388 3.526230 \n", + " 2 3.434185 3.831388 6.622267 6.347116 7.170626 4.432137 \n", + " 3 5.133946 5.572620 3.752594 3.458391 4.130377 2.596317 \n", + " 4 4.493947 5.059504 3.654136 3.340433 4.137679 2.003302 \n", + " 5 3.727341 4.267909 4.671206 4.334290 5.131988 2.575113 \n", + " 6 3.434457 3.706119 7.169777 6.346211 6.621459 4.432211 \n", + " 7 2.871399 3.298708 6.370630 5.568766 5.928024 3.526286 \n", + " 8 1.922375 2.393976 6.716514 5.968786 6.437649 3.708577 \n", + " 9 5.134343 5.840340 4.128274 3.455942 3.750231 2.596345 \n", + " 10 4.494228 5.127097 4.136402 3.338885 3.652679 2.003349 \n", + " 11 3.727776 4.311878 5.130793 4.332951 4.669955 2.575100 \n", + " 12 0.966775 1.521335 7.921272 7.353641 8.025338 4.957291 \n", + " 13 0.000000 0.966781 7.343494 6.717600 7.343566 4.301860 \n", + " 14 0.966781 0.000000 8.025461 7.353844 7.921532 4.957235 \n", + " 15 7.343494 8.025461 0.000000 0.965231 1.534377 3.097979 \n", + " 16 6.717600 7.353844 0.965231 0.000000 0.965236 2.415740 \n", + " 17 7.343566 7.921532 1.534377 0.965236 0.000000 3.097984 \n", + " 18 4.301860 4.957235 3.097979 2.415740 3.097984 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 6.594516 7.105905 7.281634 4.580752 4.859491 \n", + " 1 O 6.594516 0.000000 0.965101 1.045660 2.495867 3.125206 \n", + " 2 H 7.105905 0.965101 0.000000 1.664409 3.009866 3.515057 \n", + " 3 H 7.281634 1.045660 1.664409 0.000000 3.097601 3.609078 \n", + " 4 O 4.580752 2.495867 3.009866 3.097601 0.000000 0.961358 \n", + " 5 H 4.859491 3.125206 3.515057 3.609078 0.961358 0.000000 \n", + " 6 H 5.731063 1.032669 1.654678 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8.435920 9.252756 \n", + " 2 1.654678 2.991032 3.483897 3.588117 9.016337 9.794628 \n", + " 3 1.761169 1.425443 2.122893 2.090211 9.039635 9.874378 \n", + " 4 1.464072 4.198369 4.742564 4.912027 6.429605 7.124528 \n", + " 5 2.133692 4.588114 4.968911 5.398087 6.658710 7.245179 \n", + " 6 0.000000 3.060684 3.676863 3.744829 7.588341 8.362768 \n", + " 7 3.060684 0.000000 0.962813 0.963180 9.927373 10.779100 \n", + " 8 3.676863 0.962813 0.000000 1.545977 10.649519 11.463161 \n", + " 9 3.744829 0.963180 1.545977 0.000000 10.300741 11.200466 \n", + " 10 7.588341 9.927373 10.649519 10.300741 0.000000 1.058537 \n", + " 11 8.362768 10.779100 11.463161 11.200466 1.058537 0.000000 \n", + " 12 8.018230 10.254673 11.025257 10.548359 0.966488 1.669751 \n", + " 13 9.399913 11.882562 12.515262 12.361324 2.449395 1.393450 \n", + " 14 10.075561 12.646992 13.295020 13.124031 3.098079 2.076809 \n", + " 15 9.916075 12.278003 12.878211 12.759531 3.036576 2.050587 \n", + " 16 4.004299 6.820104 7.501851 7.353651 3.921725 4.579987 \n", + " 17 2.193866 5.008074 5.625664 5.638851 5.539799 6.240446 \n", + " 18 4.296261 7.252791 7.929421 7.795674 4.351814 4.921225 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 2.599148 3.861897 4.473483 4.533614 1.924646 3.645895 2.407452 \n", + " 1 8.797922 10.333175 10.994364 10.866794 4.882917 3.171563 5.103652 \n", + " 2 9.399997 10.830052 11.445147 11.403702 5.291431 3.660434 5.352590 \n", + " 3 9.390851 10.966778 11.677211 11.439263 5.667909 3.874588 5.995263 \n", + " 4 6.969409 8.084783 8.784342 8.568016 2.897773 0.971077 3.344216 \n", + " 5 7.299700 8.077436 8.792971 8.503867 3.252283 1.553748 3.688276 \n", + " 6 8.018230 9.399913 10.075561 9.916075 4.004299 2.193866 4.296261 \n", + " 7 10.254673 11.882562 12.646992 12.278003 6.820104 5.008074 7.252791 \n", + " 8 11.025257 12.515262 13.295020 12.878211 7.501851 5.625664 7.929421 \n", + " 9 10.548359 12.361324 13.124031 12.759531 7.353651 5.638851 7.795674 \n", + " 10 0.966488 2.449395 3.098079 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6.431229 2.432348 1.940110 3.355635 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 9.766148 9.387604 10.011755 9.175050 8.411375 8.791854 3.559384 \n", + " 1 9.055848 8.707559 9.384283 8.409703 7.649229 8.060175 2.985617 \n", + " 2 9.345472 9.084050 9.815236 8.810398 8.042294 8.451920 3.445250 \n", + " 3 6.517823 5.773753 6.208999 4.861409 4.342220 4.852883 3.527414 \n", + " 4 6.145569 5.491403 6.058397 4.488123 3.906484 4.490873 3.102517 \n", + " 5 7.396118 6.846833 7.486214 5.830449 5.250955 5.870072 1.634716 \n", + " 6 0.000000 0.963606 1.539119 3.685202 3.097119 2.137466 8.817086 \n", + " 7 0.963606 0.000000 0.963247 3.109193 2.502581 1.479060 8.313570 \n", + " 8 1.539119 0.963247 0.000000 3.617804 3.171099 2.173976 8.998378 \n", + " 9 3.685202 3.109193 3.617804 0.000000 1.026877 1.719518 6.976225 \n", + " 10 3.097119 2.502581 3.171099 1.026877 0.000000 1.026978 6.515337 \n", + " 11 2.137466 1.479060 2.173976 1.719518 1.026978 0.000000 7.241504 \n", + " 12 8.817086 8.313570 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7 7.810142 8.137789 4.703680 4.351610 4.873712 3.796266 \n", + " 8 8.461478 8.811123 4.868441 4.701293 5.281120 4.415074 \n", + " 9 6.790441 7.454052 2.175059 1.479534 2.138387 2.612825 \n", + " 10 6.225055 6.787194 3.172326 2.502815 3.097882 1.968065 \n", + " 11 6.851414 7.316412 3.620950 3.110449 3.687189 2.614257 \n", + " 12 0.965096 1.721691 8.380737 7.716155 8.136214 4.724754 \n", + " 13 0.000000 1.081825 8.317934 7.672241 8.170676 4.352331 \n", + " 14 1.081825 0.000000 9.128700 8.446031 8.927488 4.970321 \n", + " 15 8.317934 9.128700 0.000000 0.963230 1.539050 4.411469 \n", + " 16 7.672241 8.446031 0.963230 0.000000 0.963623 3.792781 \n", + " 17 8.170676 8.927488 1.539050 0.963623 0.000000 4.465558 \n", + " 18 4.352331 4.970321 4.411469 3.792781 4.465558 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.803769 4.471357 4.442770 2.385987 3.043698 \n", + " 1 O 3.803769 0.000000 0.967310 0.967047 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\\\n", + " 0 3.018930 2.069200 2.686377 2.699429 2.343493 3.053562 2.952820 \n", + " 1 5.405227 2.543099 1.536436 3.108657 2.954271 3.699839 2.162401 \n", + " 2 5.639079 3.096193 2.145226 3.639867 3.557666 4.276200 2.733684 \n", + " 3 6.294680 3.166853 2.174718 3.544754 3.550674 4.180670 2.720917 \n", + " 4 0.966415 3.704134 4.319183 4.370360 3.500114 3.986949 4.205683 \n", + " 5 1.534092 4.056004 4.764772 4.591809 4.379625 4.924186 5.010358 \n", + " 6 0.000000 4.234442 4.677557 5.005847 3.479922 3.839026 4.154814 \n", + " 7 4.234442 0.000000 1.019182 0.967736 3.106313 4.051502 3.069447 \n", + " 8 4.677557 1.019182 0.000000 1.631752 2.893627 3.820988 2.547015 \n", + " 9 5.005847 0.967736 1.631752 0.000000 4.001442 4.923532 3.943223 \n", + " 10 3.479922 3.106313 2.893627 4.001442 0.000000 0.965361 0.968388 \n", + " 11 3.839026 4.051502 3.820988 4.923532 0.965361 0.000000 1.552740 \n", + " 12 4.154814 3.069447 2.547015 3.943223 0.968388 1.552740 0.000000 \n", + " 13 3.475714 4.135807 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2.643289 \n", + " 10 6.260137 5.589727 6.118620 0.965989 0.000000 0.966297 2.093206 \n", + " 11 7.013011 6.280247 6.710624 1.527517 0.966297 0.000000 2.656933 \n", + " 12 4.985818 4.226458 4.689987 2.643289 2.093206 2.656933 0.000000 \n", + " 13 4.134042 3.340574 3.770361 3.496177 2.906850 3.497895 0.968827 \n", + " 14 4.269990 3.539320 3.949511 4.071911 3.622472 4.200478 1.550477 \n", + " 15 4.281107 3.347737 2.897792 6.016159 5.127599 5.325019 3.842732 \n", + " 16 3.634845 2.752897 2.313586 6.010447 5.139941 5.439452 4.014957 \n", + " 17 4.228207 3.447607 2.895425 6.643978 5.739814 5.947745 4.839666 \n", + " 18 2.752267 2.085646 2.616749 4.401355 3.749755 4.410066 2.962402 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 6.038902 6.839545 7.171647 6.496906 6.718616 4.473181 \n", + " 1 5.547253 6.404190 6.364721 5.683690 5.843321 3.857836 \n", + " 2 6.248978 7.145389 6.743833 6.060576 6.078316 4.531492 \n", + " 3 4.146023 5.037730 5.118014 4.542534 4.836233 2.683074 \n", + " 4 3.193536 4.119600 4.239510 3.773371 4.179335 2.013757 \n", + " 5 2.938506 3.845320 4.548622 4.272746 4.769152 2.588275 \n", + " 6 4.134042 4.269990 4.281107 3.634845 4.228207 2.752267 \n", + " 7 3.340574 3.539320 3.347737 2.752897 3.447607 2.085646 \n", + " 8 3.770361 3.949511 2.897792 2.313586 2.895425 2.616749 \n", + " 9 3.496177 4.071911 6.016159 6.010447 6.643978 4.401355 \n", + " 10 2.906850 3.622472 5.127599 5.139941 5.739814 3.749755 \n", + " 11 3.497895 4.200478 5.325019 5.439452 5.947745 4.410066 \n", + " 12 0.968827 1.550477 3.842732 4.014957 4.839666 2.962402 \n", + " 13 0.000000 0.964597 3.200066 3.324682 4.224193 2.398772 \n", + " 14 0.964597 0.000000 3.605787 3.841635 4.785922 3.119128 \n", + " 15 3.200066 3.605787 0.000000 0.965777 1.529735 3.085947 \n", + " 16 3.324682 3.841635 0.965777 0.000000 0.966031 2.488528 \n", + " 17 4.224193 4.785922 1.529735 0.966031 0.000000 3.159417 \n", + " 18 2.398772 3.119128 3.085947 2.488528 3.159417 0.000000 ,\n", + " 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2.022468 2.523823 3.075764 3.146305 7.740868 8.173032 \n", + " 14 H 2.696303 1.500080 2.117675 2.155477 8.514720 8.981339 \n", + " 15 H 2.633870 3.036898 3.545304 3.477748 8.159687 8.551548 \n", + " 16 O 1.955179 5.731305 6.409540 6.314689 4.265290 4.967829 \n", + " 17 H 2.450398 5.850785 6.575820 6.367212 4.571426 5.378287 \n", + " 18 H 3.224033 7.125408 7.762220 7.729415 3.030538 3.704084 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.616074 4.138715 4.619589 4.876809 2.521511 3.218496 3.177369 \n", + " 1 10.317385 8.050901 8.527725 8.727376 2.981886 3.754723 2.273963 \n", + " 2 10.840780 8.662406 9.200480 9.289354 3.537914 4.193389 2.801864 \n", + " 3 11.010525 8.664945 9.065385 9.392492 3.633034 4.392399 2.862438 \n", + " 4 0.963858 2.439783 2.973155 1.371430 7.258923 7.150433 8.216157 \n", + " 5 1.549816 3.020760 3.554819 2.031026 7.873443 7.780817 8.816966 \n", + " 6 0.000000 3.092270 3.441594 2.059661 7.786183 7.602648 8.750583 \n", + " 7 3.092270 0.000000 0.965990 1.070182 6.030131 6.218626 6.932522 \n", + " 8 3.441594 0.965990 0.000000 1.692893 6.606227 6.843244 7.481113 \n", + " 9 2.059661 1.070182 1.692893 0.000000 6.499476 6.545130 7.439093 \n", + " 10 7.786183 6.030131 6.606227 6.499476 0.000000 0.963561 0.964664 \n", + " 11 7.602648 6.218626 6.843244 6.545130 0.963561 0.000000 1.534053 \n", + " 12 8.750583 6.932522 7.481113 7.439093 0.964664 1.534053 0.000000 \n", + " 13 8.492142 5.921198 6.373196 6.692649 3.010750 3.924715 3.093672 \n", + " 14 9.227860 6.776282 7.236687 7.511338 2.778108 3.701130 2.541758 \n", + " 15 8.939819 6.188844 6.548763 7.038789 3.947350 4.874031 3.987096 \n", + " 16 4.825702 2.551019 3.048004 3.194663 3.561851 3.835700 4.448575 \n", + " 17 4.967886 3.112707 3.497158 3.621535 3.422739 3.554894 4.309416 \n", + " 18 3.648012 1.016215 1.636945 1.776110 5.042531 5.250503 5.943329 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.022468 2.696303 2.633870 1.955179 2.450398 3.224033 \n", + " 1 2.523823 1.500080 3.036898 5.731305 5.850785 7.125408 \n", + " 2 3.075764 2.117675 3.545304 6.409540 6.575820 7.762220 \n", + " 3 3.146305 2.155477 3.477748 6.314689 6.367212 7.729415 \n", + " 4 7.740868 8.514720 8.159687 4.265290 4.571426 3.030538 \n", + " 5 8.173032 8.981339 8.551548 4.967829 5.378287 3.704084 \n", + " 6 8.492142 9.227860 8.939819 4.825702 4.967886 3.648012 \n", + " 7 5.921198 6.776282 6.188844 2.551019 3.112707 1.016215 \n", + " 8 6.373196 7.236687 6.548763 3.048004 3.497158 1.636945 \n", + " 9 6.692649 7.511338 7.038789 3.194663 3.621535 1.776110 \n", + " 10 3.010750 2.778108 3.947350 3.561851 3.422739 5.042531 \n", + " 11 3.924715 3.701130 4.874031 3.835700 3.554894 5.250503 \n", + " 12 3.093672 2.541758 3.987096 4.448575 4.309416 5.943329 \n", + " 13 0.000000 1.026294 0.966509 3.969271 4.435853 5.106355 \n", + " 14 1.026294 0.000000 1.634194 4.628071 4.933884 5.904200 \n", + " 15 0.966509 1.634194 0.000000 4.484091 5.025770 5.460106 \n", + " 16 3.969271 4.628071 4.484091 0.000000 0.967107 1.536239 \n", + " 17 4.435853 4.933884 5.025770 0.967107 0.000000 2.139009 \n", + " 18 5.106355 5.904200 5.460106 1.536239 2.139009 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s2.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.060409 2.731948 2.682512 2.050888 2.700025 2.697173 \n", + " 1 O 2.060409 0.000000 0.972336 0.971710 4.075495 4.569883 4.744070 \n", + " 2 H 2.731948 0.972336 0.000000 1.583410 4.600189 4.928434 5.364906 \n", + " 3 H 2.682512 0.971710 1.583410 0.000000 4.723822 5.322516 5.319386 \n", + " 4 O 2.050888 4.075495 4.600189 4.723822 0.000000 0.972870 0.972329 \n", + " 5 H 2.700025 4.569883 4.928434 5.322516 0.972870 0.000000 1.578807 \n", + " 6 H 2.697173 4.744070 5.364906 5.319386 0.972329 1.578807 0.000000 \n", + " 7 O 2.329501 2.994335 3.958028 2.848908 3.577354 4.505183 3.685861 \n", + " 8 H 3.002340 3.686242 4.615772 3.407772 3.999482 4.945588 4.052235 \n", + " 9 H 3.003505 3.504270 4.472701 3.310765 4.158722 5.086300 4.110546 \n", + " \n", + " 7 8 9 \n", + " 0 2.329501 3.002340 3.003505 \n", + " 1 2.994335 3.686242 3.504270 \n", + " 2 3.958028 4.615772 4.472701 \n", + " 3 2.848908 3.407772 3.310765 \n", + " 4 3.577354 3.999482 4.158722 \n", + " 5 4.505183 4.945588 5.086300 \n", + " 6 3.685861 4.052235 4.110546 \n", + " 7 0.000000 0.968360 0.968391 \n", + " 8 0.968360 0.000000 1.542437 \n", + " 9 0.968391 1.542437 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w4s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.969573 1.578602 7.244772 6.394650 6.879331 \n", + " 1 O 0.969573 0.000000 0.969556 6.736873 5.778322 6.167413 \n", + " 2 H 1.578602 0.969556 0.000000 7.419354 6.372044 6.650838 \n", + " 3 H 7.244772 6.736873 7.419354 0.000000 1.283170 1.896155 \n", + " 4 O 6.394650 5.778322 6.372044 1.283170 0.000000 0.967742 \n", + " 5 H 6.879331 6.167413 6.650838 1.896155 0.967742 0.000000 \n", + " 6 H 8.798691 8.361471 9.073848 1.773849 2.970337 3.379612 \n", + " 7 O 8.044201 7.620920 8.360692 1.124368 2.406612 2.955599 \n", + " 8 H 8.455013 8.042937 8.796570 1.772117 2.960585 3.390317 \n", + " 9 H 3.390747 2.955635 3.379759 5.298001 4.396416 4.872983 \n", + " 10 O 2.961094 2.406734 2.970421 4.869610 3.916629 4.396258 \n", + " 11 H 1.772415 1.124483 1.774019 5.836252 4.869476 5.297467 \n", + " 12 Hg 4.592894 3.977307 4.572725 2.979537 1.958516 2.502811 \n", + " \n", + " 6 7 8 9 10 11 12 \n", + " 0 8.798691 8.044201 8.455013 3.390747 2.961094 1.772415 4.592894 \n", + " 1 8.361471 7.620920 8.042937 2.955635 2.406734 1.124483 3.977307 \n", + " 2 9.073848 8.360692 8.796570 3.379759 2.970421 1.774019 4.572725 \n", + " 3 1.773849 1.124368 1.772117 5.298001 4.869610 5.836252 2.979537 \n", + " 4 2.970337 2.406612 2.960585 4.396416 3.916629 4.869476 1.958516 \n", + " 5 3.379612 2.955599 3.390317 4.872983 4.396258 5.297467 2.502811 \n", + " 6 0.000000 0.969573 1.578598 6.652690 6.373124 7.420187 4.573391 \n", + " 7 0.969573 0.000000 0.969582 6.168170 5.778470 6.736855 3.977330 \n", + " 8 1.578598 0.969582 0.000000 6.879193 6.393812 7.243605 4.592124 \n", + " 9 6.652690 6.168170 6.879193 0.000000 0.967742 1.896082 2.502902 \n", + " 10 6.373124 5.778470 6.393812 0.967742 0.000000 1.283176 1.958514 \n", + " 11 7.420187 6.736855 7.243605 1.896082 1.283176 0.000000 2.979463 \n", + " 12 4.573391 3.977330 4.592124 2.502902 1.958514 2.979463 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s14.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.888228 4.586643 4.489314 2.055280 2.745823 \n", + " 1 O 3.888228 0.000000 0.966573 0.966249 5.762830 6.075192 \n", + " 2 H 4.586643 0.966573 0.000000 1.530871 6.516714 6.852910 \n", + " 3 H 4.489314 0.966249 1.530871 0.000000 6.259410 6.510775 \n", + " 4 O 2.055280 5.762830 6.516714 6.259410 0.000000 1.045132 \n", + " 5 H 2.745823 6.075192 6.852910 6.510775 1.045132 0.000000 \n", + " 6 H 2.645985 6.375420 7.161029 6.811186 0.966940 1.641311 \n", + " 7 O 2.087125 2.578184 3.132045 3.208751 4.102460 4.790241 \n", + " 8 H 2.709099 1.580178 2.187120 2.226174 4.717886 5.252353 \n", + " 9 H 2.708962 3.126116 3.637457 3.586482 4.564503 5.337490 \n", + " 10 O 2.388515 5.120523 5.453003 5.972650 3.235052 3.955017 \n", + " 11 H 3.067741 5.093365 5.259601 6.003471 4.178568 4.887715 \n", + " 12 H 3.063381 6.071808 6.408937 6.914930 3.342033 4.034123 \n", + " 13 O 2.367137 2.897718 3.494187 3.515517 3.610004 3.653560 \n", + " 14 H 2.996451 2.089928 2.655084 2.679306 4.466251 4.537857 \n", + " 15 H 3.082799 3.632941 4.116941 4.218031 3.920826 3.754944 \n", + " 16 O 3.925254 6.708904 7.479643 7.069685 2.475365 1.432814 \n", + " 17 H 4.509814 7.027934 7.849512 7.267224 3.119095 2.108508 \n", + " 18 H 4.624342 7.490189 8.211717 7.902488 3.049611 2.078466 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.645985 2.087125 2.709099 2.708962 2.388515 3.067741 3.063381 \n", + " 1 6.375420 2.578184 1.580178 3.126116 5.120523 5.093365 6.071808 \n", + " 2 7.161029 3.132045 2.187120 3.637457 5.453003 5.259601 6.408937 \n", + " 3 6.811186 3.208751 2.226174 3.586482 5.972650 6.003471 6.914930 \n", + " 4 0.966940 4.102460 4.717886 4.564503 3.235052 4.178568 3.342033 \n", + " 5 1.641311 4.790241 5.252353 5.337490 3.955017 4.887715 4.034123 \n", + " 6 0.000000 4.521261 5.220796 4.802906 3.819678 4.751889 3.833514 \n", + " 7 4.521261 0.000000 1.009015 0.967004 3.291072 3.408540 4.193538 \n", + " 8 5.220796 1.009015 0.000000 1.613297 3.984763 4.026614 4.928060 \n", + " 9 4.802906 0.967004 1.613297 0.000000 3.878031 3.964897 4.711168 \n", + " 10 3.819678 3.291072 3.984763 3.878031 0.000000 0.964290 0.964418 \n", + " 11 4.751889 3.408540 4.026614 3.964897 0.964290 0.000000 1.534743 \n", + " 12 3.833514 4.193538 4.928060 4.711168 0.964418 1.534743 0.000000 \n", + " 13 4.468963 2.983448 2.777096 3.910822 3.541447 3.914372 4.294631 \n", + " 14 5.269672 2.966291 2.440701 3.859374 4.193924 4.406727 5.028989 \n", + " 15 4.846686 3.914477 3.703445 4.853935 3.902103 4.279764 4.529276 \n", + " 16 2.975904 5.879579 6.169813 6.509521 5.057188 5.945565 5.107383 \n", + " 17 3.451501 6.359231 6.581266 6.938851 5.906038 6.792767 6.006106 \n", + " 18 3.507494 6.630335 6.952041 7.284256 5.381449 6.261044 5.280532 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.367137 2.996451 3.082799 3.925254 4.509814 4.624342 \n", + " 1 2.897718 2.089928 3.632941 6.708904 7.027934 7.490189 \n", + " 2 3.494187 2.655084 4.116941 7.479643 7.849512 8.211717 \n", + " 3 3.515517 2.679306 4.218031 7.069685 7.267224 7.902488 \n", + " 4 3.610004 4.466251 3.920826 2.475365 3.119095 3.049611 \n", + " 5 3.653560 4.537857 3.754944 1.432814 2.108508 2.078466 \n", + " 6 4.468963 5.269672 4.846686 2.975904 3.451501 3.507494 \n", + " 7 2.983448 2.966291 3.914477 5.879579 6.359231 6.630335 \n", + " 8 2.777096 2.440701 3.703445 6.169813 6.581266 6.952041 \n", + " 9 3.910822 3.859374 4.853935 6.509521 6.938851 7.284256 \n", + " 10 3.541447 4.193924 3.902103 5.057188 5.906038 5.381449 \n", 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2.028072 0.964297 0.000000 \n", + " 6 H 6.439051 3.000279 3.538456 2.000914 0.964845 1.552036 \n", + " 7 O 3.504384 4.655977 4.917549 5.063896 5.837665 6.048655 \n", + " 8 H 4.149258 5.155442 5.496461 5.387141 5.965673 6.092572 \n", + " 9 H 4.149349 5.115859 5.208584 5.575178 6.393223 6.523767 \n", + " 10 O 1.918722 2.589074 3.069296 3.263015 4.325095 4.891678 \n", + " 11 H 2.400074 3.234320 3.608057 3.777472 4.723154 5.131223 \n", + " 12 H 3.221079 1.006589 1.626490 1.787392 3.020861 3.639779 \n", + " 13 O 2.041780 5.966461 6.445617 6.719402 7.715039 8.478331 \n", + " 14 H 2.680154 6.558426 6.929550 7.391868 8.462160 9.209945 \n", + " 15 H 2.680515 6.598852 7.162707 7.255574 8.143227 8.907896 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.439051 3.504384 4.149258 4.149349 1.918722 2.400074 3.221079 \n", + " 1 3.000279 4.655977 5.155442 5.115859 2.589074 3.234320 1.006589 \n", + " 2 3.538456 4.917549 5.496461 5.208584 3.069296 3.608057 1.626490 \n", + " 3 2.000914 5.063896 5.387141 5.575178 3.263015 3.777472 1.787392 \n", + " 4 0.964845 5.837665 5.965673 6.393223 4.325095 4.723154 3.020861 \n", + " 5 1.552036 6.048655 6.092572 6.523767 4.891678 5.131223 3.639779 \n", + " 6 0.000000 6.712895 6.844182 7.302575 5.021076 5.522242 3.686716 \n", + " 7 6.712895 0.000000 0.963300 0.963358 2.602467 1.606018 3.757483 \n", + " 8 6.844182 0.963300 0.000000 1.529779 3.249679 2.286414 4.302269 \n", + " 9 7.302575 0.963358 1.529779 0.000000 3.250438 2.287778 4.280010 \n", + " 10 5.021076 2.602467 3.249679 3.250438 0.000000 1.004207 1.584376 \n", + " 11 5.522242 1.606018 2.286414 2.287778 1.004207 0.000000 2.263864 \n", + " 12 3.686716 3.757483 4.302269 4.280010 1.584376 2.263864 0.000000 \n", + " 13 8.128014 5.177412 5.751067 5.751258 3.958907 4.371802 5.152256 \n", + " 14 8.898078 5.588545 6.229655 6.032541 4.548378 4.900078 5.751521 \n", + " 15 8.525890 5.577616 6.021238 6.216980 4.548793 4.895326 5.774781 \n", + " \n", + " 13 14 15 \n", + " 0 2.041780 2.680154 2.680515 \n", 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3.334897 2.200968 \n", + " 2 3.540126 3.051047 3.627984 4.861042 3.902058 3.871569 2.827957 \n", + " 3 4.278582 4.078954 4.675637 4.318564 4.232172 5.120017 2.797889 \n", + " 4 4.263569 3.882645 4.496600 3.708389 3.543622 4.366032 2.145634 \n", + " 5 5.106808 4.729476 5.385901 4.252928 4.111786 4.835362 2.796739 \n", + " 6 0.000000 0.967677 1.549146 4.889790 4.268992 4.841911 2.932177 \n", + " 7 0.967677 0.000000 0.967712 3.996719 3.332463 3.876987 2.250916 \n", + " 8 1.549146 0.967712 0.000000 3.871826 3.305555 3.788628 2.885640 \n", + " 9 4.889790 3.996719 3.871826 0.000000 0.967121 1.546243 2.948884 \n", + " 10 4.268992 3.332463 3.305555 0.967121 0.000000 0.966969 2.272916 \n", + " 11 4.841911 3.876987 3.788628 1.546243 0.966969 0.000000 2.929518 \n", + " 12 2.932177 2.250916 2.885640 2.948884 2.272916 2.929518 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s3.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 2.022899 2.666166 2.666073 1.941848 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7 0.000000 0.973197 0.973196 \n", + " 8 0.973197 0.000000 1.595667 \n", + " 9 0.973196 1.595667 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s4.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.981026 2.799166 2.504665 1.973584 2.865536 \n", + " 1 O 1.981026 0.000000 1.093852 0.969208 3.951294 4.753305 \n", + " 2 H 2.799166 1.093852 0.000000 1.735655 4.689512 5.334823 \n", + " 3 H 2.504665 0.969208 1.735655 0.000000 4.432846 5.369454 \n", + " 4 O 1.973584 3.951294 4.689512 4.432846 0.000000 1.167798 \n", + " 5 H 2.865536 4.753305 5.334823 5.369454 1.167798 0.000000 \n", + " 6 H 2.548917 4.489738 5.341937 4.801330 0.966436 1.792896 \n", + " 7 O 2.595324 2.828984 3.873071 2.321166 3.748962 4.900609 \n", + " 8 H 3.252223 3.419363 4.473481 2.863696 4.262071 5.390238 \n", + " 9 H 3.264032 3.495856 4.456904 2.897429 4.233898 5.398275 \n", + " 10 O 3.925602 5.686465 6.124115 6.395652 2.388479 1.221852 \n", + " 11 H 4.558043 6.321068 6.711548 7.016971 2.967580 1.876788 \n", + " 12 H 4.541113 6.285117 6.754873 6.988400 2.978188 1.879641 \n", + " 13 O 3.943850 2.415498 1.323568 2.979339 5.698137 6.173392 \n", + " 14 H 4.596388 2.994373 1.979687 3.506881 6.349143 6.781947 \n", + " 15 H 4.560294 3.048819 1.999593 3.453987 6.287199 6.774243 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.548917 2.595324 3.252223 3.264032 3.925602 4.558043 4.541113 \n", + " 1 4.489738 2.828984 3.419363 3.495856 5.686465 6.321068 6.285117 \n", + " 2 5.341937 3.873071 4.473481 4.456904 6.124115 6.711548 6.754873 \n", + " 3 4.801330 2.321166 2.863696 2.897429 6.395652 7.016971 6.988400 \n", + " 4 0.966436 3.748962 4.262071 4.233898 2.388479 2.967580 2.978188 \n", + " 5 1.792896 4.900609 5.390238 5.398275 1.221852 1.876788 1.879641 \n", + " 6 0.000000 3.624739 4.042889 3.987961 2.940545 3.409050 3.399032 \n", + " 7 3.624739 0.000000 0.965799 0.965659 6.103561 6.685812 6.617038 \n", + " 8 4.042889 0.965799 0.000000 1.523962 6.582432 7.229512 6.983428 \n", + 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7.824585 \n", + " 12 7.429695 7.903527 8.091874 \n", + " 13 0.000000 0.965608 0.965206 \n", + " 14 0.965608 0.000000 1.553479 \n", + " 15 0.965206 1.553479 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w3s1.xyz': atoms 0 1 2 3 4 5 6 \\\n", + " 0 Hg 0.000000 3.476851 4.120858 4.121103 1.956843 3.136292 2.466239 \n", + " 1 O 3.476851 0.000000 0.965758 0.965758 2.462895 3.616760 1.393554 \n", + " 2 H 4.120858 0.965758 0.000000 1.548816 3.097371 4.129523 2.079326 \n", + " 3 H 4.121103 0.965758 1.548816 0.000000 3.097449 4.129600 2.079327 \n", + " 4 O 1.956843 2.462895 3.097371 3.097449 0.000000 1.523954 1.070687 \n", + " 5 H 3.136292 3.616760 4.129523 4.129600 1.523954 0.000000 2.326227 \n", + " 6 H 2.466239 1.393554 2.079326 2.079327 1.070687 2.326227 0.000000 \n", + " 7 O 4.042256 4.543152 4.997191 4.997338 2.551518 1.028424 3.316894 \n", + " 8 H 4.638325 4.851907 5.368609 5.132803 3.089294 1.679764 3.732646 \n", + " 9 H 4.638018 4.851623 5.132339 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4.356985 4.951207 \n", + " 7 O 3.268101 2.707314 3.266307 4.461794 3.919844 4.603371 \n", + " 8 H 1.680254 0.985633 1.680879 5.798811 5.283399 6.021902 \n", + " 9 H 3.694710 3.102793 2.147559 8.861112 8.150782 8.635719 \n", + " 10 O 3.094329 2.504868 1.480418 8.411342 7.718621 8.231227 \n", + " 11 H 3.605867 3.182373 2.185518 9.124123 8.425387 8.910078 \n", + " 12 H 2.187351 3.184135 3.608600 8.609082 8.371842 9.268444 \n", + " 13 O 1.481749 2.505759 3.096121 7.908103 7.665110 8.577955 \n", + " 14 H 2.148893 3.103671 3.697249 8.271996 8.086583 9.037371 \n", + " 15 H 9.119017 8.335226 8.692805 3.504567 3.017363 2.018393 \n", + " 16 O 8.605609 7.860031 8.250392 2.961609 2.433347 1.361915 \n", + " 17 H 9.296493 8.579836 8.972193 3.437722 3.073424 2.040622 \n", + " 18 Hg 4.889072 4.302254 4.910337 2.589031 1.991899 2.732259 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.682729 3.268101 1.680254 3.694710 3.094329 3.605867 2.187351 \n", + " 1 3.245966 2.707314 0.985633 3.102793 2.504868 3.182373 3.184135 \n", + " 2 3.692470 3.266307 1.680879 2.147559 1.480418 2.185518 3.608600 \n", + " 3 4.868975 4.461794 5.798811 8.861112 8.411342 9.124123 8.609082 \n", + " 4 4.356985 3.919844 5.283399 8.150782 7.718621 8.425387 8.371842 \n", + " 5 4.951207 4.603371 6.021902 8.635719 8.231227 8.910078 9.268444 \n", + " 6 0.000000 0.968697 2.295975 5.487870 4.682645 5.058376 5.040482 \n", + " 7 0.968697 0.000000 1.723367 5.079185 4.374248 4.917002 4.921983 \n", + " 8 2.295975 1.723367 0.000000 3.715192 3.031807 3.659971 3.661172 \n", + " 9 5.487870 5.079185 3.715192 0.000000 0.962871 1.540443 5.245727 \n", + " 10 4.682645 4.374248 3.031807 0.962871 0.000000 0.962413 4.633523 \n", + " 11 5.058376 4.917002 3.659971 1.540443 0.962413 0.000000 4.784142 \n", + " 12 5.040482 4.921983 3.661172 5.245727 4.633523 4.784142 0.000000 \n", + " 13 4.663761 4.377861 3.031772 4.846589 4.293137 4.632594 0.962429 \n", + " 14 5.466931 5.081670 3.714512 5.257087 4.848057 5.246807 1.540257 \n", + " 15 6.608368 6.256290 7.558321 9.594515 9.320995 10.000391 11.005787 \n", + " 16 5.862676 5.599462 7.022814 9.300035 8.938112 9.577303 10.410871 \n", + " 17 6.320282 6.181278 7.701676 10.064848 9.655432 10.244512 11.019896 \n", + " 18 2.422052 1.930128 3.400417 6.512969 5.961405 6.607752 6.564870 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.481749 2.148893 9.119017 8.605609 9.296493 4.889072 \n", + " 1 2.505759 3.103671 8.335226 7.860031 8.579836 4.302254 \n", + " 2 3.096121 3.697249 8.692805 8.250392 8.972193 4.910337 \n", + " 3 7.908103 8.271996 3.504567 2.961609 3.437722 2.589031 \n", + " 4 7.665110 8.086583 3.017363 2.433347 3.073424 1.991899 \n", + " 5 8.577955 9.037371 2.018393 1.361915 2.040622 2.732259 \n", + " 6 4.663761 5.466931 6.608368 5.862676 6.320282 2.422052 \n", + " 7 4.377861 5.081670 6.256290 5.599462 6.181278 1.930128 \n", + " 8 3.031772 3.714512 7.558321 7.022814 7.701676 3.400417 \n", + " 9 4.846589 5.257087 9.594515 9.300035 10.064848 6.512969 \n", + " 10 4.293137 4.848057 9.320995 8.938112 9.655432 5.961405 \n", + " 11 4.632594 5.246807 10.000391 9.577303 10.244512 6.607752 \n", + " 12 0.962429 1.540257 11.005787 10.410871 11.019896 6.564870 \n", + " 13 0.000000 0.962900 10.286605 9.737645 10.392354 5.917525 \n", + " 14 0.962900 0.000000 10.732845 10.233874 10.924519 6.461935 \n", + " 15 10.286605 10.732845 0.000000 0.964996 1.549942 4.534228 \n", + " 16 9.737645 10.233874 0.964996 0.000000 0.964673 3.866150 \n", + " 17 10.392354 10.924519 1.549942 0.964673 0.000000 4.478000 \n", + " 18 5.917525 6.461935 4.534228 3.866150 4.478000 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s2.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964625 1.554902 9.203025 8.574567 9.154834 \n", + " 1 O 0.964625 0.000000 0.965050 8.491399 7.846837 8.425118 \n", + " 2 H 1.554902 0.965050 0.000000 8.974263 8.310104 8.861084 \n", + " 3 H 9.203025 8.491399 8.974263 0.000000 0.967041 1.705050 \n", + " 4 O 8.574567 7.846837 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3.533219 9.920841 9.578229 10.333445 3.668562 \n", + " 3 7.402632 6.524299 6.829618 3.480740 2.950779 3.419825 5.707073 \n", + " 4 6.837104 6.043821 6.468466 2.999755 2.419351 3.051635 5.203687 \n", + " 5 7.521187 6.823332 7.335541 1.986641 1.331177 2.006165 5.966984 \n", + " 6 0.000000 1.097352 1.725098 8.864268 8.405932 9.122418 1.790254 \n", + " 7 1.097352 0.000000 0.966264 8.294256 7.817281 8.538502 0.999698 \n", + " 8 1.725098 0.966264 0.000000 8.920009 8.414477 9.112486 1.618140 \n", + " 9 8.864268 8.294256 8.920009 0.000000 0.965496 1.552945 7.500234 \n", + " 10 8.405932 7.817281 8.414477 0.965496 0.000000 0.965207 6.962664 \n", + " 11 9.122418 8.538502 9.112486 1.552945 0.965207 0.000000 7.642571 \n", + " 12 1.790254 0.999698 1.618140 7.500234 6.962664 7.642571 0.000000 \n", + " 13 3.300780 2.628147 3.104480 6.272671 5.619394 6.206239 1.629712 \n", + " 14 3.677724 3.166060 3.561382 6.632038 5.888842 6.353759 2.208566 \n", + " 15 4.998981 4.231235 4.679289 4.535112 3.872841 4.485897 3.317105 \n", + " \n", + " 13 14 15 \n", + " 0 4.889905 4.973767 6.692140 \n", + " 1 4.332767 4.576570 6.027618 \n", + " 2 5.034202 5.381612 6.592504 \n", + " 3 4.456762 4.871619 2.579906 \n", + " 4 3.919696 4.357987 1.985538 \n", + " 5 4.630054 4.980097 2.753441 \n", + " 6 3.300780 3.677724 4.998981 \n", + " 7 2.628147 3.166060 4.231235 \n", + " 8 3.104480 3.561382 4.679289 \n", + " 9 6.272671 6.632038 4.535112 \n", + " 10 5.619394 5.888842 3.872841 \n", + " 11 6.206239 6.353759 4.485897 \n", + " 12 1.629712 2.208566 3.317105 \n", + " 13 0.000000 0.968665 1.935880 \n", + " 14 0.968665 0.000000 2.431262 \n", + " 15 1.935880 2.431262 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s22.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.034840 2.629027 2.702768 2.419084 3.073104 \n", + " 1 O 2.034840 0.000000 0.967010 1.080170 3.718692 4.050679 \n", + " 2 H 2.629027 0.967010 0.000000 1.693982 4.531494 4.820974 \n", + " 3 H 2.702768 1.080170 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2.783848 4.622890 4.865940 5.412356 3.731472 4.336915 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.039947 3.740704 4.014811 4.604566 2.348691 3.024190 2.991905 \n", + " 1 4.258766 2.420469 3.033940 3.049535 3.440890 3.585007 4.329925 \n", + " 2 5.148067 2.972316 3.556760 3.447214 4.131981 4.243194 4.963233 \n", + " 3 4.458882 1.345775 2.021400 2.016304 3.364786 3.225429 4.311355 \n", + " 4 0.965741 4.799597 5.156315 5.556816 3.369109 4.113492 3.819310 \n", + " 5 1.533093 5.194041 5.684031 5.841940 4.280913 4.969375 4.777392 \n", + " 6 0.000000 4.874717 5.123506 5.624620 3.311323 3.973563 3.685313 \n", + " 7 4.874717 0.000000 0.975484 0.963882 3.640266 3.177280 4.563652 \n", + " 8 5.123506 0.975484 0.000000 1.581542 3.339635 2.657393 4.173249 \n", + " 9 5.624620 0.963882 1.581542 0.000000 4.596089 4.088832 5.511465 \n", + " 10 3.311323 3.640266 3.339635 4.596089 0.000000 0.980370 0.964297 \n", + " 11 3.973563 3.177280 2.657393 4.088832 0.980370 0.000000 1.557461 \n", + " 12 3.685313 4.563652 4.173249 5.511465 0.964297 1.557461 0.000000 \n", + " 13 5.364136 2.765097 1.843487 3.400331 2.789864 1.817785 3.281260 \n", + " 14 5.562869 3.275519 2.377834 3.788592 3.315817 2.378677 3.701614 \n", + " 15 6.222735 3.381437 2.436201 3.923575 3.370122 2.419996 3.723301 \n", + " 16 3.414202 5.778787 5.905287 6.680605 3.181555 4.125663 3.197150 \n", + " 17 3.050619 6.256625 6.440671 7.135700 3.715005 4.685958 3.709390 \n", + " 18 4.361941 6.455771 6.576140 7.344470 3.910055 4.811610 3.843940 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 4.453986 5.144047 5.020805 2.124083 2.672853 2.783848 \n", + " 1 4.230255 4.982181 4.747874 4.112517 4.635874 4.622890 \n", + " 2 4.766017 5.591950 5.131450 4.530312 5.135859 4.865940 \n", + " 3 3.458631 4.155420 4.013655 4.816426 5.332955 5.412356 \n", + " 4 5.569678 5.918200 6.376488 2.830246 2.484401 3.731472 \n", + " 5 6.307345 6.634123 7.141605 3.524458 3.061379 4.336915 \n", + " 6 5.364136 5.562869 6.222735 3.414202 3.050619 4.361941 \n", + " 7 2.765097 3.275519 3.381437 5.778787 6.256625 6.455771 \n", + " 8 1.843487 2.377834 2.436201 5.905287 6.440671 6.576140 \n", + " 9 3.400331 3.788592 3.923575 6.680605 7.135700 7.344470 \n", + " 10 2.789864 3.315817 3.370122 3.181555 3.715005 3.910055 \n", + " 11 1.817785 2.378677 2.419996 4.125663 4.685958 4.811610 \n", + " 12 3.281260 3.701614 3.723301 3.197150 3.709390 3.843940 \n", + " 13 0.000000 0.966282 0.965978 5.870643 6.451862 6.517769 \n", + " 14 0.966282 0.000000 1.524707 6.479854 6.971625 7.187456 \n", + " 15 0.965978 1.524707 0.000000 6.351757 7.019664 6.897846 \n", + " 16 5.870643 6.479854 6.351757 0.000000 0.969539 0.968903 \n", + " 17 6.451862 6.971625 7.019664 0.969539 0.000000 1.567914 \n", + " 18 6.517769 7.187456 6.897846 0.968903 1.567914 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s23.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.347590 2.990435 3.022754 3.740657 4.014224 \n", + " 1 O 2.347590 0.000000 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4.451396 2.788296 3.279543 1.816009 2.766650 1.845500 \n", + " 17 H 5.018142 3.368443 3.720820 2.418199 3.382805 2.437841 \n", + " 18 H 5.141523 3.314264 3.700419 2.377116 3.276844 2.379401 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.604999 2.418065 3.072365 3.038577 2.035282 2.702152 2.629733 \n", + " 1 4.597566 3.365573 4.277574 3.306884 3.442370 3.366588 4.133413 \n", + " 2 5.512934 3.816574 4.774737 3.682102 4.330730 4.312688 4.963632 \n", + " 3 4.089924 4.110175 4.966215 3.969310 3.586142 3.227168 4.244265 \n", + " 4 0.963874 4.799482 5.193970 4.874345 2.421200 1.347406 2.972848 \n", + " 5 1.581238 5.155183 5.682942 5.121913 3.034571 2.022904 3.557256 \n", + " 6 0.000000 5.556956 5.842214 5.624344 3.050963 2.018326 3.448792 \n", + " 7 5.556956 0.000000 0.966360 0.965739 3.718893 4.131628 4.531971 \n", + " 8 5.842214 0.966360 0.000000 1.533178 4.050976 4.505669 4.821808 \n", + " 9 5.624344 0.965739 1.533178 0.000000 4.258907 4.458652 5.148355 \n", + " 10 3.050963 3.718893 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3.276844 \n", + " 5 5.905868 6.442099 6.576206 1.845500 2.437841 2.379401 \n", + " 6 6.681942 7.138163 7.345257 3.402129 3.925503 3.789912 \n", + " 7 2.831406 2.487124 3.732912 5.565602 6.372295 5.914008 \n", + " 8 3.525399 3.063744 4.338312 6.303595 7.137863 6.630090 \n", + " 9 3.415440 3.053438 4.363402 5.359107 6.217525 5.557662 \n", + " 10 4.112867 4.637257 4.622624 4.230908 4.748540 4.982784 \n", + " 11 4.816437 5.334071 5.411631 3.460562 4.015466 4.157335 \n", + " 12 4.530194 5.136798 4.865097 4.766792 5.132275 5.592659 \n", + " 13 0.000000 0.969516 0.968893 5.868488 6.348933 6.478076 \n", + " 14 0.969516 0.000000 1.567774 6.450020 7.017089 6.970096 \n", + " 15 0.968893 1.567774 0.000000 6.515363 6.894686 7.185480 \n", + " 16 5.868488 6.450020 6.515363 0.000000 0.965976 0.966286 \n", + " 17 6.348933 7.017089 6.894686 0.965976 0.000000 1.524716 \n", + " 18 6.478076 6.970096 7.185480 0.966286 1.524716 0.000000 ,\n", + " 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8.672487 2.951710 2.418773 1.330122 \n", + " 14 H 8.709237 8.486378 9.366121 3.422144 3.051338 2.005350 \n", + " 15 Hg 4.695711 4.229701 4.982328 2.580582 1.985322 2.752820 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.535707 2.964423 3.418719 3.566784 3.098394 1.618071 8.401932 \n", + " 1 2.990786 2.417270 3.060619 3.165582 2.626334 0.999907 8.229127 \n", + " 2 1.979665 1.322246 2.004924 3.671780 3.302078 1.789987 9.179309 \n", + " 3 8.511988 8.112245 8.867101 4.867056 4.458962 5.721438 3.483035 \n", + " 4 8.264450 7.810267 8.543343 4.358356 3.919363 5.201189 3.000678 \n", + " 5 9.192349 8.699413 9.401187 4.985870 4.627623 5.949086 1.986753 \n", + " 6 0.000000 0.965055 1.554860 5.369039 5.037429 3.668231 10.808758 \n", + " 7 0.965055 0.000000 0.964620 4.565873 4.336393 3.001655 10.330270 \n", + " 8 1.554860 0.964620 0.000000 4.965529 4.893963 3.616915 11.032731 \n", + " 9 5.369039 4.565873 4.965529 0.000000 0.968652 2.207627 6.641484 \n", + " 10 5.037429 4.336393 4.893963 0.968652 0.000000 1.627808 6.265861 \n", + " 11 3.668231 3.001655 3.616915 2.207627 1.627808 0.000000 7.460328 \n", + " 12 10.808758 10.330270 11.032731 6.641484 6.265861 7.460328 0.000000 \n", + " 13 10.319754 9.791131 10.457925 5.897325 5.612727 6.927336 0.965498 \n", + " 14 11.018805 10.452805 11.082979 6.360532 6.199056 7.609486 1.553116 \n", + " 15 6.555655 5.997192 6.666747 2.431601 1.935815 3.315248 4.532834 \n", + " \n", + " 13 14 15 \n", + " 0 7.974072 8.709237 4.695711 \n", + " 1 7.761005 8.486378 4.229701 \n", + " 2 8.672487 9.366121 4.982328 \n", + " 3 2.951710 3.422144 2.580582 \n", + " 4 2.418773 3.051338 1.985322 \n", + " 5 1.330122 2.005350 2.752820 \n", + " 6 10.319754 11.018805 6.555655 \n", + " 7 9.791131 10.452805 5.997192 \n", + " 8 10.457925 11.082979 6.666747 \n", + " 9 5.897325 6.360532 2.431601 \n", + " 10 5.612727 6.199056 1.935815 \n", + " 11 6.927336 7.609486 3.315248 \n", + " 12 0.965498 1.553116 4.532834 \n", + " 13 0.000000 0.965198 3.869890 \n", + " 14 0.965198 0.000000 4.482631 \n", + " 15 3.869890 4.482631 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s5.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.951579 2.628220 2.621794 3.796268 4.434681 \n", + " 1 O 1.951579 0.000000 1.039243 1.039776 2.477258 3.133890 \n", + " 2 H 2.628220 1.039243 0.000000 1.760942 1.440735 2.129140 \n", + " 3 H 2.621794 1.039776 1.760942 0.000000 3.114266 3.619484 \n", + " 4 O 3.796268 2.477258 1.440735 3.114266 0.000000 0.963792 \n", + " 5 H 4.434681 3.133890 2.129140 3.619484 0.963792 0.000000 \n", + " 6 H 4.449723 3.074239 2.102168 3.670378 0.964191 1.542100 \n", + " 7 O 1.951588 3.902529 4.522886 4.495147 5.527948 6.122915 \n", + " 8 H 2.628164 4.522810 5.045603 5.106727 5.937568 6.409034 \n", + " 9 H 2.621752 4.495102 5.106688 5.127420 6.068256 6.752241 \n", + " 10 O 3.778985 5.464104 6.056973 6.102986 6.959369 7.733409 \n", + " 11 H 4.416505 6.054037 6.529110 6.783363 7.277483 8.050387 \n", + " 12 H 4.432582 6.095043 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\n", + " 7 6.163925 0.000000 1.039230 1.039777 2.475897 3.136119 3.075667 \n", + " 8 6.652064 1.039230 0.000000 1.760916 3.115378 3.627487 3.675910 \n", + " 9 6.588522 1.039777 1.760916 0.000000 1.439204 2.130284 2.102914 \n", + " 10 7.329053 2.475897 3.115378 1.439204 0.000000 0.963759 0.964159 \n", + " 11 7.585524 3.136119 3.627487 2.130284 0.963759 0.000000 1.542615 \n", + " 12 8.137044 3.075667 3.675910 2.102914 0.964159 1.542615 0.000000 \n", + " 13 7.476258 2.477288 1.440777 3.114276 4.332174 4.702333 4.824051 \n", + " 14 8.296258 3.074235 2.102193 3.670464 4.819073 5.248279 5.151648 \n", + " 15 7.751216 3.133968 2.129215 3.619470 4.693676 4.880330 5.243733 \n", + " 16 4.818957 5.464116 6.057046 6.102974 7.049353 7.820703 7.429657 \n", + " 17 5.248163 6.054128 6.529284 6.783429 7.820774 8.601205 8.202293 \n", + " 18 5.151510 6.094969 6.777758 6.625541 7.429556 8.202120 7.750946 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.796226 4.449632 4.434699 3.779005 4.416572 4.432553 \n", + " 1 5.527857 6.163769 6.122886 2.475892 3.136085 3.075702 \n", + " 2 5.937552 6.651984 6.409086 3.115418 3.627524 3.675960 \n", + " 3 6.068342 6.588542 6.752383 1.439201 2.130264 2.102928 \n", + " 4 6.683857 7.476194 6.985908 4.332200 4.702386 4.824070 \n", + " 5 6.985825 7.751060 7.245447 4.693787 4.880479 5.243869 \n", + " 6 7.476258 8.296258 7.751216 4.818957 5.248163 5.151510 \n", + " 7 2.477288 3.074235 3.133968 5.464116 6.054128 6.094969 \n", + " 8 1.440777 2.102193 2.129215 6.057046 6.529284 6.777758 \n", + " 9 3.114276 3.670464 3.619470 6.102974 6.783429 6.625541 \n", + " 10 4.332174 4.819073 4.693676 7.049353 7.820774 7.429556 \n", + " 11 4.702333 5.248279 4.880330 7.820703 8.601205 8.202120 \n", + " 12 4.824051 5.151648 5.243733 7.429657 8.202293 7.750946 \n", + " 13 0.000000 0.964192 0.963792 6.959551 7.277784 7.768182 \n", + " 14 0.964192 0.000000 1.542092 7.329174 7.585752 8.137116 \n", + " 15 0.963792 1.542092 0.000000 7.733643 8.050752 8.552382 \n", + " 16 6.959551 7.329174 7.733643 0.000000 0.963759 0.964159 \n", + " 17 7.277784 7.585752 8.050752 0.963759 0.000000 1.542616 \n", + " 18 7.768182 8.137116 8.552382 0.964159 1.542616 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s10.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.774105 4.443394 4.397771 3.795897 4.400360 \n", + " 1 O 3.774105 0.000000 0.964015 0.963564 4.316906 4.631988 \n", + " 2 H 4.443394 0.964015 0.000000 1.539448 4.856034 5.231479 \n", + " 3 H 4.397771 0.963564 1.539448 0.000000 4.647931 4.772106 \n", + " 4 O 3.795897 4.316906 4.856034 4.647931 0.000000 0.963848 \n", + " 5 H 4.400360 4.631988 5.231479 4.772106 0.963848 0.000000 \n", + " 6 H 4.485070 4.821093 5.208339 5.203177 0.964072 1.538362 \n", + " 7 O 1.997797 5.450064 6.116607 5.994027 5.564831 6.090895 \n", + " 8 H 2.726935 6.143948 6.705401 6.774855 6.283990 6.898921 \n", + " 9 H 2.590443 5.617945 6.332595 6.045972 6.118526 6.541670 \n", + " 10 O 2.505315 5.727727 6.202266 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6.090895 6.898921 6.541670 4.851650 5.317090 4.891671 \n", + " 6 0.000000 6.270120 6.894776 6.897590 4.355983 4.556723 4.451720 \n", + " 7 6.270120 0.000000 1.075431 0.967416 3.109727 3.834009 3.570691 \n", + " 8 6.894776 1.075431 0.000000 1.680253 3.181543 3.718554 3.663402 \n", + " 9 6.897590 0.967416 1.680253 0.000000 4.051585 4.796058 4.466809 \n", + " 10 4.355983 3.109727 3.181543 4.051585 0.000000 0.964087 0.964100 \n", + " 11 4.556723 3.834009 3.718554 4.796058 0.964087 0.000000 1.529059 \n", + " 12 4.451720 3.570691 3.663402 4.466809 0.964100 1.529059 0.000000 \n", + " 13 7.785306 2.437555 1.362992 2.941815 3.686396 3.944514 4.131723 \n", + " 14 8.220235 3.012431 2.011084 3.488192 3.969945 4.219941 4.211663 \n", + " 15 8.529978 3.064740 2.036659 3.380908 4.526610 4.698970 5.043101 \n", + " 16 3.083628 3.967102 4.643156 4.473062 3.374277 3.764634 4.016241 \n", + " 17 3.654639 4.506332 5.213018 4.856539 4.348402 4.700778 5.028713 \n", + " 18 2.118071 4.552613 5.268381 5.084304 3.505587 3.915436 3.942896 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 3.871811 4.539200 4.483162 1.971389 2.609273 2.613642 \n", + " 1 7.160041 8.002390 7.457600 2.496445 1.468774 3.103615 \n", + " 2 7.606271 8.477331 7.837616 3.087647 2.126824 3.688203 \n", + " 3 7.867972 8.697831 8.168408 3.168548 2.165508 3.605757 \n", + " 4 7.283759 7.740870 8.029175 2.497472 3.091391 1.467061 \n", + " 5 7.978306 8.417511 8.733623 3.154484 3.575382 2.155652 \n", + " 6 7.785306 8.220235 8.529978 3.083628 3.654639 2.118071 \n", + " 7 2.437555 3.012431 3.064740 3.967102 4.506332 4.552613 \n", + " 8 1.362992 2.011084 2.036659 4.643156 5.213018 5.268381 \n", + " 9 2.941815 3.488192 3.380908 4.473062 4.856539 5.084304 \n", + " 10 3.686396 3.969945 4.526610 3.374277 4.348402 3.505587 \n", + " 11 3.944514 4.219941 4.698970 3.764634 4.700778 3.915436 \n", + " 12 4.131723 4.211663 5.043101 4.016241 5.028713 3.942896 \n", + " 13 0.000000 0.965183 0.965127 5.657948 6.249276 6.294097 \n", + " 14 0.965183 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10.974870 10.672314 2.982788 3.464196 \n", + " 9 H 4.806169 10.669661 11.340527 11.185277 1.402286 2.095437 \n", + " 10 O 4.100942 2.456281 3.116000 3.044131 9.895693 10.591059 \n", + " 11 H 4.806261 1.402205 2.095339 2.064621 10.669799 11.340671 \n", + " 12 H 4.607503 2.982783 3.464188 3.573659 10.234598 10.975053 \n", + " 13 O 1.951240 4.244246 4.792115 4.957508 7.656746 8.382350 \n", + " 14 H 3.172794 3.048227 3.664053 3.729493 8.978110 9.686172 \n", + " 15 H 2.461357 4.461809 4.844096 5.274145 7.780615 8.535487 \n", + " 16 O 1.951245 7.656675 8.382264 8.113336 4.244262 4.792147 \n", + " 17 H 3.172670 8.977940 9.685990 9.460379 3.048298 3.664142 \n", + " 18 H 2.461376 7.780581 8.535413 8.162758 4.461692 4.844010 \n", + " \n", + " 6 7 8 9 10 11 \\\n", + " 0 6.432624 4.100839 4.607378 4.806169 4.100942 4.806261 \n", + " 1 12.271175 9.895548 10.234415 10.669661 2.456281 1.402205 \n", + " 2 12.861844 10.590908 10.974870 11.340527 3.116000 2.095339 \n", + " 3 12.859524 10.392851 10.672314 11.185277 3.044131 2.064621 \n", + " 4 0.963764 2.456329 2.982788 1.402286 9.895693 10.669799 \n", + " 5 1.547304 3.116062 3.464196 2.095437 10.591059 11.340671 \n", + " 6 0.000000 3.044211 3.573733 2.064719 10.392999 11.185416 \n", + " 7 3.044211 0.000000 0.965826 1.055847 7.867056 8.728434 \n", + " 8 3.573733 0.965826 0.000000 1.675333 8.144444 9.038340 \n", + " 9 2.064719 1.055847 1.675333 0.000000 8.728440 9.550153 \n", + " 10 10.392999 7.867056 8.144444 8.728440 0.000000 1.055881 \n", + " 11 11.185416 8.728434 9.038340 9.550153 1.055881 0.000000 \n", + " 12 10.672509 8.144480 8.392222 9.038381 0.965825 1.675380 \n", + " 13 8.113394 5.894318 6.383052 6.619772 2.512533 3.146666 \n", + " 14 9.460543 7.039828 7.396207 7.855963 1.028434 1.769754 \n", + " 15 8.162749 6.240459 6.836256 6.864086 3.065032 3.524019 \n", + " 16 4.957514 2.512464 3.001734 3.146583 5.894419 6.619853 \n", + " 17 3.729569 1.028464 1.647961 1.769745 7.039821 7.855940 \n", + " 18 5.273999 3.064971 3.476180 3.523879 6.240638 6.864223 \n", + " \n", + " 12 13 14 15 16 17 18 \n", + " 0 4.607503 1.951240 3.172794 2.461357 1.951245 3.172670 2.461376 \n", + " 1 2.982783 4.244246 3.048227 4.461809 7.656675 8.977940 7.780581 \n", + " 2 3.464188 4.792115 3.664053 4.844096 8.382264 9.685990 8.535413 \n", + " 3 3.573659 4.957508 3.729493 5.274145 8.113336 9.460379 8.162758 \n", + " 4 10.234598 7.656746 8.978110 7.780615 4.244262 3.048298 4.461692 \n", + " 5 10.975053 8.382350 9.686172 8.535487 4.792147 3.664142 4.844010 \n", + " 6 10.672509 8.113394 9.460543 8.162749 4.957514 3.729569 5.273999 \n", + " 7 8.144480 5.894318 7.039828 6.240459 2.512464 1.028464 3.064971 \n", + " 8 8.392222 6.383052 7.396207 6.836256 3.001734 1.647961 3.476180 \n", + " 9 9.038381 6.619772 7.855963 6.864086 3.146583 1.769745 3.523879 \n", + " 10 0.965825 2.512533 1.028434 3.065032 5.894419 7.039821 6.240638 \n", + " 11 1.675380 3.146666 1.769754 3.524019 6.619853 7.855940 6.864223 \n", + " 12 0.000000 3.001824 1.647932 3.476200 6.383185 7.396238 6.836464 \n", + " 13 3.001824 0.000000 1.485157 0.966457 3.901597 5.042611 4.346288 \n", + " 14 1.647932 1.485157 0.000000 2.085306 5.042731 6.198375 5.423761 \n", + " 15 3.476200 0.966457 2.085306 0.000000 4.346280 5.423583 4.794643 \n", + " 16 6.383185 3.901597 5.042731 4.346280 0.000000 1.485058 0.966457 \n", + " 17 7.396238 5.042611 6.198375 5.423583 1.485058 0.000000 2.085226 \n", + " 18 6.836464 4.346288 5.423761 4.794643 0.966457 2.085226 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s15.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 H 0.000000 0.964720 1.543486 3.696967 3.305103 3.696855 \n", + " 1 O 0.964720 0.000000 0.964715 3.810803 3.299616 3.810986 \n", + " 2 H 1.543486 0.964715 0.000000 4.758899 4.256734 4.759541 \n", + " 3 H 3.696967 3.810803 4.758899 0.000000 0.964708 1.543486 \n", + " 4 O 3.305103 3.299616 4.256734 0.964708 0.000000 0.964724 \n", + " 5 H 3.696855 3.810986 4.759541 1.543486 0.964724 0.000000 \n", + " 6 H 3.699229 3.307666 3.698230 3.693847 3.809689 4.758330 \n", + " 7 O 3.812815 3.300975 3.810462 3.304811 3.300225 4.257448 \n", + " 8 H 4.760737 4.257962 4.759146 3.693562 3.808757 4.756845 \n", + " 9 H 4.759481 4.256644 4.758791 4.758807 3.810714 3.696823 \n", + " 10 O 3.810940 3.299531 3.810695 4.256698 3.299583 3.305021 \n", + " 11 H 3.696751 3.304978 3.696838 4.759488 3.810942 3.696749 \n", + " 12 H 5.825866 5.301991 6.024298 3.698359 3.307746 3.699305 \n", + " 13 O 5.301347 4.664889 5.299142 3.810565 3.301008 3.812810 \n", + " 14 H 6.023243 5.298586 5.819493 4.759244 4.257994 4.760744 \n", + " 15 H 4.756753 3.808670 3.693406 5.819626 5.298648 6.023248 \n", + " 16 O 4.257348 3.300121 3.304647 5.299201 4.664893 5.301292 \n", + " 17 H 4.758227 3.809588 3.693692 6.024290 5.301929 5.825729 \n", + " 18 Hg 3.011859 2.332161 3.011329 3.011329 2.332149 3.011831 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.699229 3.812815 4.760737 4.759481 3.810940 3.696751 5.825866 \n", + " 1 3.307666 3.300975 4.257962 4.256644 3.299531 3.304978 5.301991 \n", + " 2 3.698230 3.810462 4.759146 4.758791 3.810695 3.696838 6.024298 \n", + " 3 3.693847 3.304811 3.693562 4.758807 4.256698 4.759488 3.698359 \n", + " 4 3.809689 3.300225 3.808757 3.810714 3.299583 3.810942 3.307746 \n", + " 5 4.758330 4.257448 4.756845 3.696823 3.305021 3.696749 3.699305 \n", + " 6 0.000000 0.964718 1.543405 6.024284 5.301944 5.825766 4.755783 \n", + " 7 0.964718 0.000000 0.964715 5.299182 4.664896 5.301314 3.807759 \n", + " 8 1.543405 0.964715 0.000000 5.819593 5.298640 6.023254 3.689788 \n", + " 9 6.024284 5.299182 5.819593 0.000000 0.964707 1.543476 3.693744 \n", + " 10 5.301944 4.664896 5.298640 0.964707 0.000000 0.964715 3.809644 \n", + " 11 5.825766 5.301314 6.023254 1.543476 0.964715 0.000000 4.758277 \n", + " 12 4.755783 3.807759 3.689788 3.693744 3.809644 4.758277 0.000000 \n", + " 13 4.251241 3.293717 3.295922 3.304621 3.300086 4.257307 0.964719 \n", + " 14 4.753242 3.804506 3.688128 3.693416 3.808635 4.756714 1.543407 \n", + " 15 3.689736 3.295800 3.688071 4.759121 4.257881 4.760658 4.753155 \n", + " 16 3.807706 3.293624 3.804483 3.810427 3.300883 3.812728 4.251093 \n", + " 17 4.755723 4.251145 4.753212 3.698170 3.307551 3.699139 4.755622 \n", + " 18 3.012950 2.332730 3.011402 3.011340 2.332171 3.011858 3.012976 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 5.301347 6.023243 4.756753 4.257348 4.758227 3.011859 \n", + " 1 4.664889 5.298586 3.808670 3.300121 3.809588 2.332161 \n", + " 2 5.299142 5.819493 3.693406 3.304647 3.693692 3.011329 \n", + " 3 3.810565 4.759244 5.819626 5.299201 6.024290 3.011329 \n", + " 4 3.301008 4.257994 5.298648 4.664893 5.301929 2.332149 \n", + " 5 3.812810 4.760744 6.023248 5.301292 5.825729 3.011831 \n", + " 6 4.251241 4.753242 3.689736 3.807706 4.755723 3.012950 \n", + " 7 3.293717 3.804506 3.295800 3.293624 4.251145 2.332730 \n", + " 8 3.295922 3.688128 3.688071 3.804483 4.753212 3.011402 \n", + " 9 3.304621 3.693416 4.759121 3.810427 3.698170 3.011340 \n", + " 10 3.300086 3.808635 4.257881 3.300883 3.307551 2.332171 \n", + " 11 4.257307 4.756714 4.760658 3.812728 3.699139 3.011858 \n", + " 12 0.964719 1.543407 4.753155 4.251093 4.755622 3.012976 \n", + " 13 0.000000 0.964719 3.804429 3.293559 3.807584 2.332733 \n", + " 14 0.964719 0.000000 3.687954 3.295688 3.689566 3.011390 \n", + " 15 3.804429 3.687954 0.000000 0.964724 1.543408 3.011423 \n", + " 16 3.293559 3.295688 0.964724 0.000000 0.964712 2.332748 \n", + " 17 3.807584 3.689566 1.543408 0.964712 0.000000 3.012967 \n", + " 18 2.332733 3.011390 3.011423 2.332748 3.012967 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s3.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 1.960012 2.945878 2.515030 1.951041 2.619018 \n", + " 1 O 1.960012 0.000000 1.253130 0.967264 3.910091 4.511643 \n", + " 2 H 2.945878 1.253130 0.000000 1.871024 4.817825 5.434843 \n", + " 3 H 2.515030 0.967264 1.871024 0.000000 4.411901 4.955299 \n", + " 4 O 1.951041 3.910091 4.817825 4.411901 0.000000 1.043064 \n", + " 5 H 2.619018 4.511643 5.434843 4.955299 1.043064 0.000000 \n", + " 6 H 2.619111 4.511696 5.434854 4.955486 1.043130 1.763741 \n", + " 7 O 3.772415 5.488433 6.381512 5.867760 2.472534 3.109538 \n", + " 8 H 4.401416 6.071189 7.049666 6.325929 3.132518 3.613312 \n", + " 9 H 4.435071 6.131064 6.909856 6.598441 3.068262 3.671156 \n", + " 10 O 3.772494 5.488547 6.381719 5.867571 2.472704 1.432593 \n", + " 11 H 4.435051 6.130945 6.909801 6.597992 3.068613 2.094283 \n", + " 12 H 4.401636 6.071576 7.050155 6.326041 3.132547 2.123383 \n", + " 13 O 3.954783 2.397106 1.144968 2.949615 5.726172 6.342944 \n", + " 14 H 4.565181 2.961724 1.794845 3.386443 6.335191 7.041437 \n", + " 15 H 4.565223 2.961758 1.794831 3.386352 6.335257 6.841346 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.619111 3.772415 4.401416 4.435071 3.772494 4.435051 4.401636 \n", + " 1 4.511696 5.488433 6.071189 6.131064 5.488547 6.130945 6.071576 \n", + " 2 5.434854 6.381512 7.049666 6.909856 6.381719 6.909801 7.050155 \n", + " 3 4.955486 5.867760 6.325929 6.598441 5.867571 6.597992 6.326041 \n", + " 4 1.043130 2.472534 3.132518 3.068262 2.472704 3.068613 3.132547 \n", + " 5 1.763741 3.109538 3.613312 3.671156 1.432593 2.094283 2.123383 \n", + " 6 0.000000 1.432360 2.123281 2.093905 3.109737 3.671717 3.613205 \n", + " 7 1.432360 0.000000 0.963963 0.964346 4.319147 4.816926 4.675256 \n", + " 8 2.123281 0.963963 0.000000 1.542955 4.675646 5.231903 4.846006 \n", + " 9 2.093905 0.964346 1.542955 0.000000 4.816431 5.156210 5.230921 \n", + " 10 3.109737 4.319147 4.675646 4.816431 0.000000 0.964344 0.963963 \n", + " 11 3.671717 4.816926 5.231903 5.156210 0.964344 0.000000 1.542915 \n", + " 12 3.613205 4.675256 4.846006 5.230921 0.963963 1.542915 0.000000 \n", + " 13 6.342902 7.257460 7.982410 7.692552 7.257786 7.692608 7.983021 \n", + " 14 6.841215 7.612436 8.318828 8.014167 8.047341 8.505992 8.766366 \n", + " 15 7.041471 8.047081 8.765878 8.505933 7.612849 8.014213 8.319621 \n", + " \n", + " 13 14 15 \n", + " 0 3.954783 4.565181 4.565223 \n", + " 1 2.397106 2.961724 2.961758 \n", + " 2 1.144968 1.794845 1.794831 \n", + " 3 2.949615 3.386443 3.386352 \n", + " 4 5.726172 6.335191 6.335257 \n", + " 5 6.342944 7.041437 6.841346 \n", + " 6 6.342902 6.841215 7.041471 \n", + " 7 7.257460 7.612436 8.047081 \n", + " 8 7.982410 8.318828 8.765878 \n", + " 9 7.692552 8.014167 8.505933 \n", + " 10 7.257786 8.047341 7.612849 \n", + " 11 7.692608 8.505992 8.014213 \n", + " 12 7.983021 8.766366 8.319621 \n", + " 13 0.000000 0.968946 0.968946 \n", + " 14 0.968946 0.000000 1.575607 \n", + " 15 0.968946 1.575607 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s21.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.342527 3.040562 2.932240 2.341854 3.040160 \n", + " 1 O 2.342527 0.000000 0.965495 0.965586 3.443784 3.716290 \n", + " 2 H 3.040562 0.965495 0.000000 1.540138 3.715694 3.935944 \n", + " 3 H 2.932240 0.965586 1.540138 0.000000 3.911662 3.986970 \n", + " 4 O 2.341854 3.443784 3.715694 3.911662 0.000000 0.965493 \n", + " 5 H 3.040160 3.716290 3.935944 3.986970 0.965493 0.000000 \n", + " 6 H 2.931408 3.911299 3.985980 4.501786 0.965581 1.540260 \n", + " 7 O 2.342092 3.006845 3.947462 2.824828 3.756409 3.954889 \n", + " 8 H 3.040310 3.732284 4.622110 3.427082 3.954653 3.971234 \n", + " 9 H 2.931906 3.481273 4.443312 3.258632 4.649087 4.905854 \n", + " 10 O 2.342619 3.756019 3.953738 4.648814 3.004779 3.945435 \n", + " 11 H 2.932168 4.648653 4.904727 5.509345 3.480159 4.442137 \n", + " 12 H 3.040707 3.953611 3.969352 4.904661 3.729980 4.619754 \n", + " 13 O 2.342569 4.670181 5.340892 5.156102 3.007201 3.732867 \n", + " 14 H 2.932465 5.156570 5.768468 5.598691 2.825608 3.428150 \n", + " 15 H 3.040400 5.340336 6.080906 5.767341 3.947768 4.622661 \n", + " 16 O 2.342335 3.005424 3.730845 3.480420 4.668930 5.340115 \n", + " 17 H 3.040472 3.945970 4.620478 4.442405 5.339556 6.080551 \n", + " 18 H 2.931916 2.822615 3.424925 3.257008 5.154407 5.766734 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.931408 2.342092 3.040310 2.931906 2.342619 2.932168 3.040707 \n", + " 1 3.911299 3.006845 3.732284 3.481273 3.756019 4.648653 3.953611 \n", + " 2 3.985980 3.947462 4.622110 4.443312 3.953738 4.904727 3.969352 \n", + " 3 4.501786 2.824828 3.427082 3.258632 4.648814 5.509345 4.904661 \n", + " 4 0.965581 3.756409 3.954653 4.649087 3.004779 3.480159 3.729980 \n", + " 5 1.540260 3.954889 3.971234 4.905854 3.945435 4.442137 4.619754 \n", + " 6 0.000000 4.649007 4.905582 5.509465 2.821689 3.256616 3.423679 \n", + " 7 4.649007 0.000000 0.965492 0.965581 4.669468 5.154723 5.340303 \n", + " 8 4.905582 0.965492 0.000000 1.540217 5.340355 5.766887 6.080942 \n", + " 9 5.509465 0.965581 1.540217 0.000000 5.155117 5.596382 5.767105 \n", + " 10 2.821689 4.669468 5.340355 5.155117 0.000000 0.965584 0.965493 \n", + " 11 3.256616 5.154723 5.766887 5.596382 0.965584 0.000000 1.540164 \n", 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5.765686 5.595713 \n", + " 7 3.443133 3.911174 3.714471 3.005856 3.731321 3.480744 \n", + " 8 3.715822 3.986548 3.935057 3.946574 4.621281 4.442761 \n", + " 9 3.910496 4.501045 3.984429 2.823509 3.425882 3.257810 \n", + " 10 3.005548 3.480235 3.731250 3.443154 3.715006 3.910689 \n", + " 11 2.822829 3.256881 3.425497 3.910063 3.984467 4.500215 \n", + " 12 3.946120 4.442219 4.620963 3.715383 3.935054 3.985580 \n", + " 13 0.000000 0.965586 0.965493 3.754835 3.952335 4.647673 \n", + " 14 0.965586 0.000000 1.540125 4.647851 4.903484 5.508618 \n", + " 15 0.965493 1.540125 0.000000 3.952178 3.967825 4.903251 \n", + " 16 3.754835 4.647851 3.952178 0.000000 0.965492 0.965583 \n", + " 17 3.952335 4.903484 3.967825 0.965492 0.000000 1.540191 \n", + " 18 4.647673 5.508618 4.903251 0.965583 1.540191 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s11.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.449746 3.050316 3.186190 3.807004 4.465532 \n", + " 1 O 2.449746 0.000000 0.966711 0.963998 2.921375 3.506973 \n", + " 2 H 3.050316 0.966711 0.000000 1.544837 2.141690 2.688479 \n", + " 3 H 3.186190 0.963998 1.544837 0.000000 3.674707 4.154710 \n", + " 4 O 3.807004 2.921375 2.141690 3.674707 0.000000 0.966093 \n", + " 5 H 4.465532 3.506973 2.688479 4.154710 0.966093 0.000000 \n", + " 6 H 4.451487 3.520437 2.700961 4.229430 0.965705 1.531173 \n", + " 7 O 3.842552 5.525040 5.501805 6.472839 4.457486 4.896618 \n", + " 8 H 4.504818 6.184703 6.133392 7.119684 4.969126 5.250580 \n", + " 9 H 4.469066 6.052236 5.978968 7.008961 4.822022 5.318635 \n", + " 10 O 1.999915 3.343937 4.246336 3.599234 5.589816 6.243057 \n", + " 11 H 2.739023 4.341430 5.233630 4.572238 6.472864 7.075763 \n", + " 12 H 2.586349 3.527578 4.438610 3.672419 5.916225 6.647582 \n", + " 13 O 1.982561 3.112843 3.107350 4.052605 2.584347 3.136091 \n", + " 14 H 2.666611 4.107883 4.079823 5.056200 3.230223 3.738544 \n", + " 15 H 2.597565 2.852689 2.546408 3.789173 1.584917 2.194139 \n", + " 16 O 3.862512 5.598066 6.472212 5.809861 7.604048 8.142540 \n", + " 17 H 4.520925 5.996749 6.889615 6.084499 8.144309 8.619722 \n", + " 18 H 4.485275 6.355845 7.223982 6.601887 8.281052 8.865812 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.451487 3.842552 4.504818 4.469066 1.999915 2.739023 2.586349 \n", + " 1 3.520437 5.525040 6.184703 6.052236 3.343937 4.341430 3.527578 \n", + " 2 2.700961 5.501805 6.133392 5.978968 4.246336 5.233630 4.438610 \n", + " 3 4.229430 6.472839 7.119684 7.008961 3.599234 4.572238 3.672419 \n", + " 4 0.965705 4.457486 4.969126 4.822022 5.589816 6.472864 5.916225 \n", + " 5 1.531173 4.896618 5.250580 5.318635 6.243057 7.075763 6.647582 \n", + " 6 0.000000 4.756616 5.318697 4.937942 6.205362 7.129655 6.423174 \n", + " 7 4.756616 0.000000 0.964074 0.963593 5.539908 5.867539 6.068340 \n", + " 8 5.318697 0.964074 0.000000 1.542270 6.175822 6.406019 6.789358 \n", + " 9 4.937942 0.963593 1.542270 0.000000 6.119217 6.484282 6.537122 \n", + " 10 6.205362 5.539908 6.175822 6.119217 0.000000 1.079217 0.967226 \n", + " 11 7.129655 5.867539 6.406019 6.484282 1.079217 0.000000 1.688155 \n", + " 12 6.423174 6.068340 6.789358 6.537122 0.967226 1.688155 0.000000 \n", + " 13 3.216365 2.479826 3.075109 3.149161 3.976607 4.607635 4.530200 \n", + " 14 3.688620 1.445835 2.107965 2.142643 4.566274 5.069206 5.110092 \n", + " 15 2.235104 3.081220 3.651451 3.599572 4.561964 5.321196 5.017384 \n", + " 16 8.303688 6.479023 6.881418 7.128857 2.429649 1.353015 2.955585 \n", + " 17 8.891381 7.279456 7.632126 7.976976 3.008126 2.008308 3.509152 \n", + " 18 8.929740 6.757264 7.160976 7.328450 3.072938 2.032749 3.421884 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.982561 2.666611 2.597565 3.862512 4.520925 4.485275 \n", + " 1 3.112843 4.107883 2.852689 5.598066 5.996749 6.355845 \n", + " 2 3.107350 4.079823 2.546408 6.472212 6.889615 7.223982 \n", + " 3 4.052605 5.056200 3.789173 5.809861 6.084499 6.601887 \n", + " 4 2.584347 3.230223 1.584917 7.604048 8.144309 8.281052 \n", + " 5 3.136091 3.738544 2.194139 8.142540 8.619722 8.865812 \n", + " 6 3.216365 3.688620 2.235104 8.303688 8.891381 8.929740 \n", + " 7 2.479826 1.445835 3.081220 6.479023 7.279456 6.757264 \n", + " 8 3.075109 2.107965 3.651451 6.881418 7.632126 7.160976 \n", + " 9 3.149161 2.142643 3.599572 7.128857 7.976976 7.328450 \n", + " 10 3.976607 4.566274 4.561964 2.429649 3.008126 3.072938 \n", + " 11 4.607635 5.069206 5.321196 1.353015 2.008308 2.032749 \n", + " 12 4.530200 5.110092 5.017384 2.955585 3.509152 3.421884 \n", + " 13 0.000000 1.037356 1.007137 5.548422 6.212613 6.117910 \n", + " 14 1.037356 0.000000 1.719145 5.880384 6.619279 6.327141 \n", + " 15 1.007137 1.719145 0.000000 6.357128 6.976417 6.971599 \n", + " 16 5.548422 5.880384 6.357128 0.000000 0.965354 0.964911 \n", + " 17 6.212613 6.619279 6.976417 0.965354 0.000000 1.550359 \n", + " 18 6.117910 6.327141 6.971599 0.964911 1.550359 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s13.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.940809 4.616270 4.550340 2.468930 3.118227 \n", + " 1 O 3.940809 0.000000 0.964457 0.964023 5.374120 5.320436 \n", + " 2 H 4.616270 0.964457 0.000000 1.542975 5.714868 5.509650 \n", + " 3 H 4.550340 0.964023 1.542975 0.000000 6.189543 6.186537 \n", + " 4 O 2.468930 5.374120 5.714868 6.189543 0.000000 0.964736 \n", + " 5 H 3.118227 5.320436 5.509650 6.186537 0.964736 0.000000 \n", + " 6 H 3.137846 6.261530 6.587873 7.086705 0.964714 1.528207 \n", + " 7 O 3.878718 6.294064 6.862096 6.793626 5.140770 5.844856 \n", + " 8 H 4.489039 6.600118 7.210202 6.984993 6.003740 6.717763 \n", + " 9 H 4.554135 7.021516 7.513530 7.580231 5.425206 6.095468 \n", + " 10 O 2.492846 5.253469 5.944304 5.673904 3.137927 3.698091 \n", + " 11 H 3.226855 5.751920 6.504196 6.035815 4.084052 4.652988 \n", + " 12 H 3.070375 5.909560 6.509826 6.403850 2.923120 3.415175 \n", + " 13 O 2.028883 2.467359 3.051465 3.124374 3.207250 3.304999 \n", + " 14 H 2.751591 1.420892 2.076837 2.108838 4.112666 4.129819 \n", + " 15 H 2.554187 2.990719 3.570432 3.468075 3.525096 3.603100 \n", + " 16 O 2.025211 5.633658 6.315066 6.181499 3.315700 4.197847 \n", + " 17 H 2.730058 5.824822 6.471607 6.353906 4.057785 4.865068 \n", + " 18 H 2.608552 6.279240 7.026774 6.741981 3.875429 4.811514 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 3.137846 3.878718 4.489039 4.554135 2.492846 3.226855 3.070375 \n", + " 1 6.261530 6.294064 6.600118 7.021516 5.253469 5.751920 5.909560 \n", + " 2 6.587873 6.862096 7.210202 7.513530 5.944304 6.504196 6.509826 \n", + " 3 7.086705 6.793626 6.984993 7.580231 5.673904 6.035815 6.403850 \n", + " 4 0.964714 5.140770 6.003740 5.425206 3.137927 4.084052 2.923120 \n", + " 5 1.528207 5.844856 6.717763 6.095468 3.698091 4.652988 3.415175 \n", + " 6 0.000000 5.151036 6.060848 5.282491 3.754347 4.644403 3.417262 \n", + " 7 5.151036 0.000000 0.964427 0.964790 6.009773 6.523996 6.499142 \n", + " 8 6.060848 0.964427 0.000000 1.545252 6.555099 6.971298 7.126695 \n", + " 9 5.282491 0.964790 1.545252 0.000000 6.656981 7.218597 7.047093 \n", + " 10 3.754347 6.009773 6.555099 6.656981 0.000000 0.965280 0.965111 \n", + " 11 4.644403 6.523996 6.971298 7.218597 0.965280 0.000000 1.532815 \n", + " 12 3.417262 6.499142 7.126695 7.047093 0.965111 1.532815 0.000000 \n", + " 13 4.146185 5.556377 6.091476 6.245737 2.932217 3.611787 3.486596 \n", + " 14 5.034102 5.786044 6.222396 6.509475 3.881840 4.456750 4.499897 \n", + " 15 4.469820 6.301376 6.816505 7.011493 2.515918 3.073288 3.051305 \n", + " 16 3.433620 2.453702 3.103636 3.038721 3.662578 4.193250 4.093803 \n", + " 17 4.119280 1.397331 2.081208 2.054069 4.664829 5.178991 5.133158 \n", + " 18 3.930706 2.964132 3.435711 3.533615 3.621770 3.961654 4.050813 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.028883 2.751591 2.554187 2.025211 2.730058 2.608552 \n", + " 1 2.467359 1.420892 2.990719 5.633658 5.824822 6.279240 \n", + " 2 3.051465 2.076837 3.570432 6.315066 6.471607 7.026774 \n", + " 3 3.124374 2.108838 3.468075 6.181499 6.353906 6.741981 \n", + " 4 3.207250 4.112666 3.525096 3.315700 4.057785 3.875429 \n", + " 5 3.304999 4.129819 3.603100 4.197847 4.865068 4.811514 \n", + " 6 4.146185 5.034102 4.469820 3.433620 4.119280 3.930706 \n", + " 7 5.556377 5.786044 6.301376 2.453702 1.397331 2.964132 \n", + " 8 6.091476 6.222396 6.816505 3.103636 2.081208 3.435711 \n", + " 9 6.245737 6.509475 7.011493 3.038721 2.054069 3.533615 \n", + " 10 2.932217 3.881840 2.515918 3.662578 4.664829 3.621770 \n", + " 11 3.611787 4.456750 3.073288 4.193250 5.178991 3.961654 \n", + " 12 3.486596 4.499897 3.051305 4.093803 5.133158 4.050813 \n", + " 13 0.000000 1.049014 0.968290 4.042319 4.620704 4.597054 \n", + " 14 1.049014 0.000000 1.661421 4.646737 5.047720 5.249538 \n", + " 15 0.968290 1.661421 0.000000 4.546427 5.253160 4.947984 \n", + " 16 4.042319 4.646737 4.546427 0.000000 1.058828 0.967032 \n", + " 17 4.620704 5.047720 5.253160 1.058828 0.000000 1.659198 \n", + " 18 4.597054 5.249538 4.947984 0.967032 1.659198 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s16.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.487358 3.051705 3.187957 3.812219 4.421421 \n", + " 1 O 2.487358 0.000000 0.965857 0.965882 4.487012 5.154954 \n", + " 2 H 3.051705 0.965857 0.000000 1.533803 5.015649 5.774881 \n", + " 3 H 3.187957 0.965882 1.533803 0.000000 4.394426 4.979616 \n", + " 4 O 3.812219 4.487012 5.015649 4.394426 0.000000 0.963819 \n", + " 5 H 4.421421 5.154954 5.774881 4.979616 0.963819 0.000000 \n", + " 6 H 4.499417 4.941197 5.328707 4.803479 0.964224 1.536040 \n", + " 7 O 2.444496 3.097985 2.881819 4.032221 5.503989 6.324213 \n", + " 8 H 3.094081 3.668394 3.408263 4.626565 6.421625 7.213798 \n", + " 9 H 3.102372 3.721492 3.367434 4.589919 5.624912 6.502604 \n", + " 10 O 2.095271 2.733066 3.278955 3.457066 5.658673 6.149925 \n", + " 11 H 2.755300 3.595080 4.203519 4.213609 6.179542 6.557047 \n", + " 12 H 2.609303 2.267036 2.807769 2.876400 5.835731 6.333664 \n", + " 13 O 1.999554 3.834867 4.280546 4.291370 2.511730 3.175371 \n", + " 14 H 2.627814 3.976426 4.483543 4.206964 1.488601 2.177298 \n", + " 15 H 2.619692 4.762732 5.213117 5.261990 3.097299 3.580570 \n", + " 16 O 3.783628 6.119115 6.556279 6.674035 4.329181 4.632528 \n", + " 17 H 4.396989 6.752812 7.276019 7.247695 4.645789 4.756817 \n", + " 18 H 4.464331 6.729850 7.062728 7.319104 4.881309 5.239933 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 4.499417 2.444496 3.094081 3.102372 2.095271 2.755300 2.609303 \n", + " 1 4.941197 3.097985 3.668394 3.721492 2.733066 3.595080 2.267036 \n", + " 2 5.328707 2.881819 3.408263 3.367434 3.278955 4.203519 2.807769 \n", + " 3 4.803479 4.032221 4.626565 4.589919 3.457066 4.213609 2.876400 \n", + " 4 0.964224 5.503989 6.421625 5.624912 5.658673 6.179542 5.835731 \n", + " 5 1.536040 6.324213 7.213798 6.502604 6.149925 6.557047 6.333664 \n", + " 6 0.000000 5.880887 6.831887 5.863865 6.393160 6.986626 6.525135 \n", + " 7 5.880887 0.000000 0.965237 0.965160 3.028406 3.867014 3.372959 \n", + " 8 6.831887 0.965237 0.000000 1.529865 3.098043 3.833406 3.458809 \n", + " 9 5.863865 0.965160 1.529865 0.000000 3.978855 4.809513 4.310493 \n", + " 10 6.393160 3.028406 3.098043 3.978855 0.000000 0.969134 0.971385 \n", + " 11 6.986626 3.867014 3.833406 4.809513 0.969134 0.000000 1.577133 \n", + " 12 6.525135 3.372959 3.458809 4.310493 0.971385 1.577133 0.000000 \n", + " 13 3.090523 3.506162 4.342609 3.664512 4.075350 4.616256 4.577060 \n", + " 14 2.134844 4.295383 5.180162 4.437388 4.646834 5.178532 5.009218 \n", + " 15 3.666124 4.014142 4.745970 4.122403 4.549468 4.946434 5.196689 \n", + " 16 4.850168 4.923818 5.490841 4.970582 5.436577 5.657496 6.221680 \n", + " 17 5.220365 5.775557 6.313097 5.888973 5.925711 6.016920 6.724753 \n", + " 18 5.254246 5.208966 5.749716 5.088768 6.140167 6.412213 6.929065 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 1.999554 2.627814 2.619692 3.783628 4.396989 4.464331 \n", + " 1 3.834867 3.976426 4.762732 6.119115 6.752812 6.729850 \n", + " 2 4.280546 4.483543 5.213117 6.556279 7.276019 7.062728 \n", + " 3 4.291370 4.206964 5.261990 6.674035 7.247695 7.319104 \n", + " 4 2.511730 1.488601 3.097299 4.329181 4.645789 4.881309 \n", + " 5 3.175371 2.177298 3.580570 4.632528 4.756817 5.239933 \n", + " 6 3.090523 2.134844 3.666124 4.850168 5.220365 5.254246 \n", + " 7 3.506162 4.295383 4.014142 4.923818 5.775557 5.208966 \n", + " 8 4.342609 5.180162 4.745970 5.490841 6.313097 5.749716 \n", + " 9 3.664512 4.437388 4.122403 4.970582 5.888973 5.088768 \n", + " 10 4.075350 4.646834 4.549468 5.436577 5.925711 6.140167 \n", + " 11 4.616256 5.178532 4.946434 5.657496 6.016920 6.412213 \n", + " 12 4.577060 5.009218 5.196689 6.221680 6.724753 6.929065 \n", + " 13 0.000000 1.026552 1.028087 2.506791 3.178436 3.098250 \n", + " 14 1.026552 0.000000 1.704186 3.094438 3.588930 3.687817 \n", + " 15 1.028087 1.704186 0.000000 1.482418 2.178883 2.139034 \n", + " 16 2.506791 3.094438 1.482418 0.000000 0.963594 0.963994 \n", + " 17 3.178436 3.588930 2.178883 0.963594 0.000000 1.537311 \n", + " 18 3.098250 3.687817 2.139034 0.963994 1.537311 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w5s9.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.838411 4.493365 4.469937 1.978158 2.573485 \n", + " 1 O 3.838411 0.000000 0.964876 0.964363 2.446629 3.072802 \n", + " 2 H 4.493365 0.964876 0.000000 1.547485 3.038977 3.633789 \n", + " 3 H 4.469937 0.964363 1.547485 0.000000 3.107213 3.580218 \n", + " 4 O 1.978158 2.446629 3.038977 3.107213 0.000000 1.011256 \n", + " 5 H 2.573485 3.072802 3.633789 3.580218 1.011256 0.000000 \n", + " 6 H 2.696402 1.389622 2.053151 2.081640 1.060166 1.759889 \n", + " 7 O 2.057239 5.576264 6.205452 6.165612 4.027052 4.598592 \n", + " 8 H 2.688142 5.840079 6.378450 6.471717 4.556250 5.247230 \n", + " 9 H 2.682688 6.109442 6.821331 6.587754 4.620276 5.116456 \n", + " 10 O 2.388154 5.572428 6.218976 6.108701 3.188446 2.949570 \n", + " 11 H 2.975200 5.563574 6.183777 6.048350 3.176848 2.640844 \n", + " 12 H 3.131898 6.512009 7.139825 7.064283 4.121727 3.882142 \n", + " 13 O 3.711839 4.477187 4.982947 4.840492 2.569046 1.569960 \n", + " 14 H 4.372065 4.915786 5.263625 5.334779 3.124063 2.177096 \n", + " 15 H 4.362420 4.795774 5.354971 4.977329 3.198434 2.214198 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.696402 2.057239 2.688142 2.682688 2.388154 2.975200 3.131898 \n", + " 1 1.389622 5.576264 5.840079 6.109442 5.572428 5.563574 6.512009 \n", + " 2 2.053151 6.205452 6.378450 6.821331 6.218976 6.183777 7.139825 \n", + " 3 2.081640 6.165612 6.471717 6.587754 6.108701 6.048350 7.064283 \n", + " 4 1.060166 4.027052 4.556250 4.620276 3.188446 3.176848 4.121727 \n", + " 5 1.759889 4.598592 5.247230 5.116456 2.949570 2.640844 3.882142 \n", + " 6 0.000000 4.636700 5.049008 5.203248 4.211133 4.189204 5.152221 \n", + " 7 4.636700 0.000000 0.971180 0.970868 3.250332 4.160592 3.484104 \n", + " 8 5.049008 0.971180 0.000000 1.568513 4.124020 5.025488 4.327318 \n", + " 9 5.203248 0.970868 1.568513 0.000000 3.549056 4.461043 3.691001 \n", + " 10 4.211133 3.250332 4.124020 3.549056 0.000000 0.967473 0.965039 \n", + " 11 4.189204 4.160592 5.025488 4.461043 0.967473 0.000000 1.549421 \n", + " 12 5.152221 3.484104 4.327318 3.691001 0.965039 1.549421 0.000000 \n", + " 13 3.272792 5.541766 6.309103 5.954562 2.959397 2.192253 3.722980 \n", + " 14 3.778475 6.193674 6.910120 6.685645 3.536275 2.725936 4.187792 \n", + " 15 3.733198 6.158614 6.971200 6.460445 3.555406 2.744214 4.283061 \n", + " \n", + " 13 14 15 \n", + " 0 3.711839 4.372065 4.362420 \n", + " 1 4.477187 4.915786 4.795774 \n", + " 2 4.982947 5.263625 5.354971 \n", + " 3 4.840492 5.334779 4.977329 \n", + " 4 2.569046 3.124063 3.198434 \n", + " 5 1.569960 2.177096 2.214198 \n", + " 6 3.272792 3.778475 3.733198 \n", + " 7 5.541766 6.193674 6.158614 \n", + " 8 6.309103 6.910120 6.971200 \n", + " 9 5.954562 6.685645 6.460445 \n", + " 10 2.959397 3.536275 3.555406 \n", + " 11 2.192253 2.725936 2.744214 \n", + " 12 3.722980 4.187792 4.283061 \n", + " 13 0.000000 0.966737 0.966357 \n", + " 14 0.966737 0.000000 1.530861 \n", + " 15 0.966357 1.530861 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s19.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 2.277053 2.964573 2.901210 2.204012 2.867812 \n", + " 1 O 2.277053 0.000000 0.965875 0.965839 4.173434 4.553600 \n", + " 2 H 2.964573 0.965875 0.000000 1.546638 4.558580 4.814468 \n", + " 3 H 2.901210 0.965839 1.546638 0.000000 4.972979 5.429835 \n", + " 4 O 2.204012 4.173434 4.558580 4.972979 0.000000 0.964854 \n", + " 5 H 2.867812 4.553600 4.814468 5.429835 0.964854 0.000000 \n", + " 6 H 2.805523 4.763938 5.096097 5.530572 0.986049 1.584952 \n", + " 7 O 3.929142 5.749974 6.041796 6.394073 2.693441 3.286981 \n", + " 8 H 4.618719 6.231931 6.390638 6.909051 3.317615 3.733241 \n", + " 9 H 4.549956 6.513678 6.882837 7.112353 3.259492 3.851447 \n", + " 10 O 2.295674 3.195725 4.143799 3.117505 4.136436 4.894533 \n", + " 11 H 2.945799 3.935195 4.846409 3.776546 4.590295 5.437877 \n", + " 12 H 2.929678 3.691345 4.656904 3.555422 4.646614 5.315466 \n", + " 13 O 2.294403 3.642311 4.113236 4.013245 3.037317 3.922648 \n", + " 14 H 2.878824 4.428603 4.810917 4.899837 2.874650 3.728679 \n", + " 15 H 2.984462 3.786676 4.157495 4.006448 3.931791 4.771496 \n", + " 16 O 2.341456 3.130773 3.791106 3.660533 3.277452 3.414961 \n", + " 17 H 2.986728 3.082433 3.615402 3.563055 4.027625 4.039951 \n", + " 18 H 3.031829 4.090163 4.726717 4.618621 3.443125 3.460240 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.805523 3.929142 4.618719 4.549956 2.295674 2.945799 2.929678 \n", + " 1 4.763938 5.749974 6.231931 6.513678 3.195725 3.935195 3.691345 \n", + " 2 5.096097 6.041796 6.390638 6.882837 4.143799 4.846409 4.656904 \n", + " 3 5.530572 6.394073 6.909051 7.112353 3.117505 3.776546 3.555422 \n", + " 4 0.986049 2.693441 3.317615 3.259492 4.136436 4.590295 4.646614 \n", + " 5 1.584952 3.286981 3.733241 3.851447 4.894533 5.437877 5.315466 \n", + " 6 0.000000 1.741538 2.358925 2.340733 4.616115 4.901286 5.229757 \n", + " 7 1.741538 0.000000 0.966233 0.966413 5.364679 5.360315 6.116363 \n", + " 8 2.358925 0.966233 0.000000 1.527062 6.197856 6.211068 6.980997 \n", + " 9 2.340733 0.966413 1.527062 0.000000 5.711758 5.596226 6.407992 \n", + " 10 4.616115 5.364679 6.197856 5.711758 0.000000 0.965704 0.965650 \n", + " 11 4.901286 5.360315 6.211068 5.596226 0.965704 0.000000 1.544621 \n", + " 12 5.229757 6.116363 6.980997 6.407992 0.965650 1.544621 0.000000 \n", + " 13 2.841471 2.771687 3.388586 3.354144 3.185888 3.152287 4.114222 \n", + " 14 2.372124 1.853386 2.454253 2.450648 3.990693 3.919155 4.873097 \n", + " 15 3.701502 3.390928 3.839268 3.974549 3.604122 3.466861 4.568311 \n", + " 16 4.223589 5.761488 6.468428 6.261122 3.120095 4.027958 3.008007 \n", + " 17 4.985430 6.543208 7.188842 7.107060 3.709722 4.663426 3.531748 \n", + " 18 4.394369 5.995108 6.728297 6.390898 3.690469 4.522102 3.442921 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.294403 2.878824 2.984462 2.341456 2.986728 3.031829 \n", + " 1 3.642311 4.428603 3.786676 3.130773 3.082433 4.090163 \n", + " 2 4.113236 4.810917 4.157495 3.791106 3.615402 4.726717 \n", + " 3 4.013245 4.899837 4.006448 3.660533 3.563055 4.618621 \n", + " 4 3.037317 2.874650 3.931791 3.277452 4.027625 3.443125 \n", + " 5 3.922648 3.728679 4.771496 3.414961 4.039951 3.460240 \n", + " 6 2.841471 2.372124 3.701502 4.223589 4.985430 4.394369 \n", + " 7 2.771687 1.853386 3.390928 5.761488 6.543208 5.995108 \n", + " 8 3.388586 2.454253 3.839268 6.468428 7.188842 6.728297 \n", + " 9 3.354144 2.450648 3.974549 6.261122 7.107060 6.390898 \n", + " 10 3.185888 3.990693 3.604122 3.120095 3.709722 3.690469 \n", + " 11 3.152287 3.919155 3.466861 4.027958 4.663426 4.522102 \n", + " 12 4.114222 4.873097 4.568311 3.008007 3.531748 3.442921 \n", + " 13 0.000000 0.977680 0.964625 4.603994 5.274912 5.190269 \n", + " 14 0.977680 0.000000 1.566837 5.108549 5.833780 5.582468 \n", + " 15 0.964625 1.566837 0.000000 5.302020 5.882542 5.971990 \n", + " 16 4.603994 5.108549 5.302020 0.000000 0.965268 0.965466 \n", + " 17 5.274912 5.833780 5.882542 0.965268 0.000000 1.542269 \n", + " 18 5.190269 5.582468 5.971990 0.965466 1.542269 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s8.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 4.157836 4.845872 4.675414 5.869140 6.527531 \n", + " 1 O 4.157836 0.000000 1.067524 0.966111 2.443600 3.097743 \n", + " 2 H 4.845872 1.067524 0.000000 1.687105 1.377831 2.067705 \n", + " 3 H 4.675414 0.966111 1.687105 0.000000 2.972656 3.442763 \n", + " 4 O 5.869140 2.443600 1.377831 2.972656 0.000000 0.963872 \n", + " 5 H 6.527531 3.097743 2.067705 3.442763 0.963872 0.000000 \n", + " 6 H 6.436660 3.028660 2.039435 3.561214 0.964227 1.549174 \n", + " 7 O 1.952972 2.545543 3.187224 3.019830 4.263404 4.805207 \n", + " 8 H 3.224238 1.018548 1.771904 1.636021 3.029625 3.643988 \n", + " 9 H 2.450227 3.071950 3.518579 3.485886 4.423135 4.801498 \n", + " 10 O 3.862073 7.686174 8.535473 7.981577 9.661706 10.342240 \n", + " 11 H 4.458853 8.360138 9.193294 8.635324 10.303257 10.935411 \n", + " 12 H 4.550061 8.220761 9.092883 8.506008 10.234627 10.960560 \n", + " 13 O 2.555658 4.580869 5.536685 4.798514 6.785282 7.554780 \n", + " 14 H 3.230382 4.825390 5.850394 4.851713 7.168728 7.888012 \n", + " 15 H 3.233576 4.914624 5.826996 5.170751 7.025107 7.858037 \n", + " 16 O 2.010607 6.035595 6.711129 6.569309 7.668341 8.382124 \n", + " 17 H 2.692722 6.696951 7.460178 7.122159 8.501488 9.200559 \n", + " 18 H 2.599733 6.596506 7.165188 7.207002 7.999360 8.691048 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 6.436660 1.952972 3.224238 2.450227 3.862073 4.458853 4.550061 \n", + " 1 3.028660 2.545543 1.018548 3.071950 7.686174 8.360138 8.220761 \n", + " 2 2.039435 3.187224 1.771904 3.518579 8.535473 9.193294 9.092883 \n", + " 3 3.561214 3.019830 1.636021 3.485886 7.981577 8.635324 8.506008 \n", + " 4 0.964227 4.263404 3.029625 4.423135 9.661706 10.303257 10.234627 \n", + " 5 1.549174 4.805207 3.643988 4.801498 10.342240 10.935411 10.960560 \n", + " 6 0.000000 4.981516 3.708969 5.238502 10.177360 10.867769 10.690905 \n", + " 7 4.981516 0.000000 1.527677 0.967440 5.621934 6.161078 6.323255 \n", + " 8 3.708969 1.527677 0.000000 2.107108 6.836871 7.467694 7.432623 \n", + " 9 5.238502 0.967440 2.107108 0.000000 5.985902 6.399245 6.774048 \n", + " 10 10.177360 5.621934 6.836871 5.985902 0.000000 0.964352 0.964296 \n", + " 11 10.867769 6.161078 7.467694 6.399245 0.964352 0.000000 1.542412 \n", + " 12 10.690905 6.323255 7.432623 6.774048 0.964296 1.542412 0.000000 \n", + " 13 7.188921 3.481034 4.009126 4.307302 3.675349 4.537565 3.920574 \n", + " 14 7.607830 3.881827 4.320499 4.659911 3.921479 4.713854 4.128011 \n", + " 15 7.308319 4.164465 4.482400 5.050669 4.091588 5.020368 4.137242 \n", + " 16 8.129364 3.962259 5.165500 4.369695 2.467709 3.103398 3.049985 \n", + " 17 8.991155 4.594756 5.826234 4.982143 1.417528 2.096045 2.066018 \n", + " 18 8.445702 4.469478 5.710501 4.749122 2.959359 3.406390 3.525142 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 2.555658 3.230382 3.233576 2.010607 2.692722 2.599733 \n", + " 1 4.580869 4.825390 4.914624 6.035595 6.696951 6.596506 \n", + " 2 5.536685 5.850394 5.826996 6.711129 7.460178 7.165188 \n", + " 3 4.798514 4.851713 5.170751 6.569309 7.122159 7.207002 \n", + " 4 6.785282 7.168728 7.025107 7.668341 8.501488 7.999360 \n", + " 5 7.554780 7.888012 7.858037 8.382124 9.200559 8.691048 \n", + " 6 7.188921 7.607830 7.308319 8.129364 8.991155 8.445702 \n", + " 7 3.481034 3.881827 4.164465 3.962259 4.594756 4.469478 \n", + " 8 4.009126 4.320499 4.482400 5.165500 5.826234 5.710501 \n", + " 9 4.307302 4.659911 5.050669 4.369695 4.982143 4.749122 \n", + " 10 3.675349 3.921479 4.091588 2.467709 1.417528 2.959359 \n", + " 11 4.537565 4.713854 5.020368 3.103398 2.096045 3.406390 \n", + " 12 3.920574 4.128011 4.137242 3.049985 2.066018 3.525142 \n", + " 13 0.000000 0.963369 0.963544 3.031201 3.119513 3.970538 \n", + " 14 0.963369 0.000000 1.526804 3.776207 3.670911 4.739423 \n", + " 15 0.963544 1.526804 0.000000 3.433030 3.553317 4.313696 \n", + " 16 3.031201 3.776207 3.433030 0.000000 1.051039 0.967247 \n", + " 17 3.119513 3.670911 3.553317 1.051039 0.000000 1.649764 \n", + " 18 3.970538 4.739423 4.313696 0.967247 1.649764 0.000000 ,\n", + " '/home/edison/repositories/radial_distribution/files_xyz/mp2/w6s6.xyz': atoms 0 1 2 3 4 5 \\\n", + " 0 Hg 0.000000 3.570708 4.207876 4.220754 1.993418 2.737297 \n", + " 1 O 3.570708 0.000000 0.962811 0.962847 5.211798 5.704481 \n", + " 2 H 4.207876 0.962811 0.000000 1.528980 5.779858 6.342297 \n", + " 3 H 4.220754 0.962847 1.528980 0.000000 5.797060 6.152775 \n", + " 4 O 1.993418 5.211798 5.779858 5.797060 0.000000 1.069199 \n", + " 5 H 2.737297 5.704481 6.342297 6.152775 1.069199 0.000000 \n", + " 6 H 2.595943 5.604151 6.040661 6.264480 0.966375 1.684318 \n", + " 7 O 1.924699 2.617042 3.268109 3.263486 3.916887 4.601440 \n", + " 8 H 2.424434 1.625061 2.308757 2.305970 4.349642 4.970010 \n", + " 9 H 3.120230 3.676189 4.223945 4.214584 5.012407 5.715888 \n", + " 10 O 3.881861 6.520252 7.222652 6.805514 2.436784 1.369783 \n", + " 11 H 4.502650 6.765146 7.423734 6.985631 3.077576 2.048824 \n", + " 12 H 4.541772 7.378636 8.104054 7.665425 3.021752 2.026489 \n", + " 13 O 4.038000 4.582045 5.077300 5.058606 5.838459 6.537602 \n", + " 14 H 4.743985 4.939005 5.256800 5.467716 6.551839 7.336043 \n", + " 15 H 4.559162 4.852911 5.425543 5.160034 6.352810 6.938865 \n", + " 16 O 5.813584 5.714842 5.820116 6.289237 7.575433 8.441892 \n", + " 17 H 6.502906 5.900717 5.914585 6.396646 8.334135 9.186690 \n", + " 18 H 6.352272 6.595787 6.699560 7.204653 7.990193 8.881701 \n", + " \n", + " 6 7 8 9 10 11 12 \\\n", + " 0 2.595943 1.924699 2.424434 3.120230 3.881861 4.502650 4.541772 \n", + " 1 5.604151 2.617042 1.625061 3.676189 6.520252 6.765146 7.378636 \n", + " 2 6.040661 3.268109 2.308757 4.223945 7.222652 7.423734 8.104054 \n", + " 3 6.264480 3.263486 2.305970 4.214584 6.805514 6.985631 7.665425 \n", + " 4 0.966375 3.916887 4.349642 5.012407 2.436784 3.077576 3.021752 \n", + " 5 1.684318 4.601440 4.970010 5.715888 1.369783 2.048824 2.026489 \n", + " 6 0.000000 4.465094 4.844096 5.569695 2.966072 3.447040 3.506074 \n", + " 7 4.465094 0.000000 0.998678 1.482167 5.607334 6.198061 6.256422 \n", + " 8 4.844096 0.998678 0.000000 2.161499 5.916042 6.377724 6.661936 \n", + " 9 5.569695 1.482167 2.161499 0.000000 6.696647 7.386743 7.219564 \n", + " 10 2.966072 5.607334 5.916042 6.696647 0.000000 0.964509 0.964884 \n", + " 11 3.447040 6.198061 6.377724 7.386743 0.964509 0.000000 1.548979 \n", + " 12 3.506074 6.256422 6.661936 7.219564 0.964884 1.548979 0.000000 \n", + " 13 6.395196 2.509695 3.148407 1.028978 7.491610 8.231952 7.935505 \n", + " 14 7.003771 3.155105 3.652787 1.776565 8.370375 9.096700 8.836913 \n", + " 15 7.001739 3.001308 3.533545 1.649692 7.761937 8.493868 8.179518 \n", + " 16 7.903153 4.264407 4.629126 3.058891 9.557232 10.268922 10.040056 \n", + " 17 8.664209 4.825894 5.027121 3.679535 10.284486 10.958626 10.808223 \n", + " 18 8.275987 4.968370 5.435038 3.733458 10.019037 10.773787 10.439091 \n", + " \n", + " 13 14 15 16 17 18 \n", + " 0 4.038000 4.743985 4.559162 5.813584 6.502906 6.352272 \n", + " 1 4.582045 4.939005 4.852911 5.714842 5.900717 6.595787 \n", + " 2 5.077300 5.256800 5.425543 5.820116 5.914585 6.699560 \n", + " 3 5.058606 5.467716 5.160034 6.289237 6.396646 7.204653 \n", + " 4 5.838459 6.551839 6.352810 7.575433 8.334135 7.990193 \n", + " 5 6.537602 7.336043 6.938865 8.441892 9.186690 8.881701 \n", + " 6 6.395196 7.003771 7.001739 7.903153 8.664209 8.275987 \n", + " 7 2.509695 3.155105 3.001308 4.264407 4.825894 4.968370 \n", + " 8 3.148407 3.652787 3.533545 4.629126 5.027121 5.435038 \n", + " 9 1.028978 1.776565 1.649692 3.058891 3.679535 3.733458 \n", + " 10 7.491610 8.370375 7.761937 9.557232 10.284486 10.019037 \n", + " 11 8.231952 9.096700 8.493868 10.268922 10.958626 10.773787 \n", + " 12 7.935505 8.836913 8.179518 10.040056 10.808223 10.439091 \n", + " 13 0.000000 1.056374 0.965688 2.455744 3.114382 3.038514 \n", + " 14 1.056374 0.000000 1.676526 1.401291 2.092700 2.061293 \n", + " 15 0.965688 1.676526 0.000000 2.982157 3.460859 3.565754 \n", + " 16 2.455744 1.401291 2.982157 0.000000 0.963426 0.963956 \n", + " 17 3.114382 2.092700 3.460859 0.963426 0.000000 1.546565 \n", + " 18 3.038514 2.061293 3.565754 0.963956 1.546565 0.000000 }" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_hf: dict = distance_matrix.distance_matrix(coordinates_hf, (0, 0, 0))\n", + "distances_dict_pbe0: dict = distance_matrix.distance_matrix(coordinates_pbe0, (0, 0, 0))\n", + "distances_dict_camb3lyp: dict = distance_matrix.distance_matrix(coordinates_camb3lyp, (0, 0, 0))\n", + "distances_dict_wb97xd: dict = distance_matrix.distance_matrix(coordinates_wb97xd, (0, 0, 0))\n", + "distances_dict_b2plypd3: dict = distance_matrix.distance_matrix(coordinates_b2plypd3, (0, 0, 0))\n", + "distances_dict_pbeqidh: dict = distance_matrix.distance_matrix(coordinates_pbeqidh, (0, 0, 0))\n", + "distances_dict_mp2: dict = distance_matrix.distance_matrix(coordinates_mp2, (0, 0, 0))\n", + "distances_dict_zora_sr: dict = distance_matrix.distance_matrix(coordinates_zora_sr, (0, 0, 0))\n", + "distances_dict_zora_so: dict = distance_matrix.distance_matrix(coordinates_zora_so, (0, 0, 0))\n", + "\n", + "distances_dict_mp2" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (1.5, 3, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "atoms_list: list = ['Hg', 'O']\n", + "\n", + "atoms_index_dict_hf: dict = atoms_index_list.atoms_index_dict(distances_dict_hf, atoms_list, grid)\n", + "atoms_index_dict_pbe0: dict = atoms_index_list.atoms_index_dict(distances_dict_pbe0, atoms_list, grid)\n", + "atoms_index_dict_camb3lyp: dict = atoms_index_list.atoms_index_dict(distances_dict_camb3lyp, atoms_list, grid)\n", + "atoms_index_dict_wb97xd: dict = atoms_index_list.atoms_index_dict(distances_dict_wb97xd, atoms_list, grid)\n", + "atoms_index_dict_b2plypd3: dict = atoms_index_list.atoms_index_dict(distances_dict_b2plypd3, atoms_list, grid)\n", + "atoms_index_dict_pbeqidh: dict = atoms_index_list.atoms_index_dict(distances_dict_pbeqidh, atoms_list, grid)\n", + "atoms_index_dict_mp2: dict = atoms_index_list.atoms_index_dict(distances_dict_mp2, atoms_list, grid)\n", + "atoms_index_dict_zora_sr: dict = atoms_index_list.atoms_index_dict(distances_dict_zora_sr, atoms_list, grid)\n", + "atoms_index_dict_zora_so: dict = atoms_index_list.atoms_index_dict(distances_dict_zora_so, atoms_list, grid)\n", + "\n", + "# atoms_index_dict_wb97xd" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# - radial (bond) distribution analysis (RDA); i.e., atoms_list_AB = [A, B]\n", + "histogram_hf: np.array = histogram.rda(atoms_index_dict_hf, distances_dict_hf, grid, nbins)\n", + "histogram_pbe0: np.array = histogram.rda(atoms_index_dict_pbe0, distances_dict_pbe0, grid, nbins)\n", + "histogram_camb3lyp: np.array = histogram.rda(atoms_index_dict_camb3lyp, distances_dict_camb3lyp, grid, nbins)\n", + "histogram_wb97xd: np.array = histogram.rda(atoms_index_dict_wb97xd, distances_dict_wb97xd, grid, nbins)\n", + "histogram_b2plypd3: np.array = histogram.rda(atoms_index_dict_b2plypd3, distances_dict_b2plypd3, grid, nbins)\n", + "histogram_pbeqidh: np.array = histogram.rda(atoms_index_dict_pbeqidh, distances_dict_pbeqidh, grid, nbins)\n", + "histogram_mp2: np.array = histogram.rda(atoms_index_dict_mp2, distances_dict_mp2, grid, nbins)\n", + "histogram_zora_sr: np.array = histogram.rda(atoms_index_dict_zora_sr, distances_dict_zora_sr, grid, nbins)\n", + "histogram_zora_so: np.array = histogram.rda(atoms_index_dict_zora_so, distances_dict_zora_so, grid, nbins)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_hf_nan = histogram_hf.astype('float')\n", + "histogram_pbe0_nan = histogram_pbe0.astype('float')\n", + "histogram_camb3lyp_nan = histogram_camb3lyp.astype('float')\n", + "histogram_wb97xd_nan = histogram_wb97xd.astype('float')\n", + "histogram_b2plypd3_nan = histogram_b2plypd3.astype('float')\n", + "histogram_pbeqidh_nan = histogram_pbeqidh.astype('float')\n", + "histogram_mp2_nan = histogram_mp2.astype('float')\n", + "histogram_zora_sr_nan = histogram_zora_sr.astype('float')\n", + "histogram_zora_so_nan = histogram_zora_so.astype('float')\n", + "\n", + "\n", + "histogram_hf_nan[histogram_hf_nan == 0] = float('nan')\n", + "histogram_pbe0_nan[histogram_pbe0_nan == 0] = float('nan')\n", + "histogram_camb3lyp_nan[histogram_camb3lyp_nan == 0] = float('nan')\n", + "histogram_wb97xd_nan[histogram_wb97xd_nan == 0] = float('nan')\n", + "histogram_b2plypd3_nan[histogram_b2plypd3_nan == 0] = float('nan')\n", + "histogram_pbeqidh_nan[histogram_pbeqidh_nan == 0] = float('nan')\n", + "histogram_mp2_nan[histogram_mp2_nan == 0] = float('nan')\n", + "histogram_zora_sr_nan[histogram_zora_sr_nan == 0] = float('nan')\n", + "histogram_zora_so_nan[histogram_zora_so_nan == 0] = float('nan')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "distribution = np.linspace(rmin, rmax, nbins, endpoint = False)\n", + "distribution_smooth = np.linspace(rmin, rmax, len(distribution) * 100, endpoint = False)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "612be6240d6a47efb98c46640d64cb17", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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+ "text/html": [ + "\n", + "
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'#17becf'])\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "total_hf = sum(histogram_hf)\n", + "total_pbe0 = sum(histogram_pbe0)\n", + "total_camb3lyp = sum(histogram_camb3lyp)\n", + "total_wb97xd = sum(histogram_wb97xd)\n", + "total_b2plypd3 = sum(histogram_b2plypd3)\n", + "total_pbeqidh = sum(histogram_pbeqidh)\n", + "total_mp2 = sum(histogram_mp2)\n", + "total_zora_sr = sum(histogram_zora_sr)\n", + "total_zora_so = sum(histogram_zora_so)\n", + "\n", + "# plt.fill_between(\n", + "# smooth_x, \n", + "# smooth_y / total_all, \n", + "# where=(smooth_y / total_all>0),\n", + "# alpha=0.3,\n", + "# color=\"gray\",\n", + "# label=\"distribution\",\n", + " # )\n", + "# ax.plot(\n", + "# # distribution_all, \n", + "# # histogram_all / total_all, \n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "\n", + "\n", + "smooth = make_interp_spline(distribution, histogram_hf / total_hf, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"HF\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "smooth = make_interp_spline(distribution, histogram_pbe0 / total_pbe0, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"PBE0\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "smooth = make_interp_spline(distribution, histogram_camb3lyp / total_camb3lyp, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"CAM-B3LYP\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "\n", + "smooth = make_interp_spline(distribution, histogram_wb97xd / total_wb97xd, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"wB97XD\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "smooth = make_interp_spline(distribution, histogram_b2plypd3 / total_b2plypd3, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"B2PLYP-D3\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "smooth = make_interp_spline(distribution, histogram_pbeqidh / total_pbeqidh, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"PBEQIDH\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " ) \n", + "smooth = make_interp_spline(distribution, histogram_mp2 / total_mp2, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"MP2\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " ) \n", + "smooth = make_interp_spline(distribution, histogram_zora_sr / total_zora_so, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"ZORA+SR\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " ) \n", + "smooth = make_interp_spline(distribution, histogram_zora_so / total_zora_so, k=3)\n", + "ax.plot(\n", + " distribution_smooth, \n", + " smooth(distribution_smooth), \n", + " # \"-\",\n", + " # next(linecycler),\n", + " color=next(cm),\n", + " label=\"ZORA+SO\",\n", + " # markersize=7,\n", + " # alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " ) \n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_hf / total_hf, \n", + "# # \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"HF\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_pbe0 / total_pbe0, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"PBE0\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_camb3lyp / total_camb3lyp, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"CAM-B3LYP\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_wb97xd / total_wb97xd, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"wB97xD\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_b2plypd3 / total_b2plypd3, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"B2PLYP-D3\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_pbeqidh / total_pbeqidh,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"PBEQIDH\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_mp2 / total_mp2, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"MP2\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_zora_sr / total_zora_sr, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=next(cm),\n", + "# label=\"ZORA+SR\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# ) \n", + "# ax.plot(\n", + "# distribution, \n", + "# histogram_zora_so / total_zora_so, \n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# # color=next(cm),\n", + "# color=\"black\",\n", + "# label=\"ZORA+SO\",\n", + "# # markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# ) \n", + "\n", + "\n", + "\n", + "plt.xlim(1.8, 2.7)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "ax.set_ylabel('Relative Number of Occurrences', fontsize=12)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list)}'r\" [$\\AA$]\", fontsize=12)\n", + "plt.legend(loc=\"best\", fontsize=10, ncol=1)\n", + "\n", + "fig.savefig(\n", + " working_dir / 'rda_HgO_gaussian.png',\n", + " dpi=500,\n", + " bbox_inches='tight',\n", + " ) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_O-H_RDA.ipynb b/analysis_O-H_RDA.ipynb new file mode 100644 index 0000000..b600e50 --- /dev/null +++ b/analysis_O-H_RDA.ipynb @@ -0,0 +1,667 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_water: Path = Path(\n", + " \"/home/edison/repositories/radial_distribution/files_xyz/others/water\"\n", + ")\n", + "\n", + "files_ice: list = glob(str(dir_water / \"ice_ih\" / \"w_iceih.xyz\"))\n", + "files_water4: list = glob(str(dir_water / \"w4\" / \"w*.xyz\"))\n", + "files_water5: list = glob(str(dir_water / \"w5\" / \"w*.xyz\"))\n", + "files_water6: list = glob(str(dir_water / \"w6\" / \"w*.xyz\"))\n", + "# files_water7: list = glob(str(dir_water / \"w7\" / \"w*.xyz\"))\n", + "files_water7: list = glob(str(dir_water / \"w*\" / \"w*.xyz\"))\n", + "\n", + "coordinates_ice: list = functions.dict_coordinates_xyz(files_ice)\n", + "coordinates_water4: list = functions.dict_coordinates_xyz(files_water4)\n", + "coordinates_water5: list = functions.dict_coordinates_xyz(files_water5)\n", + "coordinates_water6: list = functions.dict_coordinates_xyz(files_water6)\n", + "coordinates_water7: list = functions.dict_coordinates_xyz(files_water7)\n", + "\n", + "\n", + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_ice: dict = distance_matrix.distance_matrix(coordinates_ice, (0, 0, 0))\n", + "distances_dict_water4: dict = distance_matrix.distance_matrix(\n", + " coordinates_water4, (0, 0, 0)\n", + ")\n", + "distances_dict_water5: dict = distance_matrix.distance_matrix(\n", + " coordinates_water5, (0, 0, 0)\n", + ")\n", + "distances_dict_water6: dict = distance_matrix.distance_matrix(\n", + " coordinates_water6, (0, 0, 0)\n", + ")\n", + "distances_dict_water7: dict = distance_matrix.distance_matrix(\n", + " coordinates_water7, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (0.8, 3.5, 0.05)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': [(1, 2),\n", + " (1, 3),\n", + " (4, 5),\n", + " (4, 6)]}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"O\", \"H\"]\n", + "\n", + "atoms_index_dict_ice: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_ice, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water6, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water7: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water7, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 0, 0, 578, 426, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 1, 12, 55, 114, 74, 65, 92, 78, 42, 29,\n", + " 22, 8, 9, 3, 4, 0, 1, 1, 1, 2, 2, 5, 6,\n", + " 23, 76, 59, 57, 31, 56, 115, 146, 164, 172, 161, 165, 212,\n", + " 189, 166])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - radial (bond) distribution analysis (RDA); i.e., atoms_list_AB = [A, B]\n", + "histogram_ice: np.array = histogram.rda(\n", + " atoms_index_dict_ice, distances_dict_ice, grid, nbins\n", + ")\n", + "histogram_water4: np.array = histogram.rda(\n", + " atoms_index_dict_water4, distances_dict_water4, grid, nbins\n", + ")\n", + "histogram_water5: np.array = histogram.rda(\n", + " atoms_index_dict_water5, distances_dict_water5, grid, nbins\n", + ")\n", + "histogram_water6: np.array = histogram.rda(\n", + " atoms_index_dict_water6, distances_dict_water6, grid, nbins\n", + ")\n", + "histogram_water7: np.array = histogram.rda(\n", + " atoms_index_dict_water7, distances_dict_water7, grid, nbins\n", + ")\n", + "\n", + "histogram_w1: np.array = histogram.rda(\n", + " atoms_index_dict_w1, distances_dict_w1, grid, nbins\n", + ")\n", + "histogram_w2: np.array = histogram.rda(\n", + " atoms_index_dict_w2, distances_dict_w2, grid, nbins\n", + ")\n", + "histogram_w3: np.array = histogram.rda(\n", + " atoms_index_dict_w3, distances_dict_w3, grid, nbins\n", + ")\n", + "histogram_w4: np.array = histogram.rda(\n", + " atoms_index_dict_w4, distances_dict_w4, grid, nbins\n", + ")\n", + "histogram_w5: np.array = histogram.rda(\n", + " atoms_index_dict_w5, distances_dict_w5, grid, nbins\n", + ")\n", + "histogram_w6: np.array = histogram.rda(\n", + " atoms_index_dict_w6, distances_dict_w6, grid, nbins\n", + ")\n", + "\n", + "histogram_water7\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_ice,\n", + " histogram_water4,\n", + " histogram_water5,\n", + " histogram_water6,\n", + " histogram_water7,\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"rda_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_ice_nan = histogram_ice.astype(\"float\")\n", + "histogram_water4_nan = histogram_water4.astype(\"float\")\n", + "histogram_water5_nan = histogram_water5.astype(\"float\")\n", + "histogram_water6_nan = histogram_water6.astype(\"float\")\n", + "histogram_water7_nan = histogram_water7.astype(\"float\")\n", + "\n", + "histogram_w1_nan = histogram_w1.astype(\"float\")\n", + "histogram_w2_nan = histogram_w2.astype(\"float\")\n", + "histogram_w3_nan = histogram_w3.astype(\"float\")\n", + "histogram_w4_nan = histogram_w4.astype(\"float\")\n", + "histogram_w5_nan = histogram_w5.astype(\"float\")\n", + "histogram_w6_nan = histogram_w6.astype(\"float\")\n", + "\n", + "histogram_ice_nan[histogram_ice_nan == 0] = float(\"nan\")\n", + "histogram_water4_nan[histogram_water4_nan == 0] = float(\"nan\")\n", + "histogram_water5_nan[histogram_water5_nan == 0] = float(\"nan\")\n", + "histogram_water6_nan[histogram_water6_nan == 0] = float(\"nan\")\n", + "histogram_water7_nan[histogram_water7_nan == 0] = float(\"nan\")\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float(\"nan\")\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float(\"nan\")\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float(\"nan\")\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float(\"nan\")\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float(\"nan\")\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "grid_all = (0.9, 2.5, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin_all, rmax_all, dr_all = grid_all\n", + "nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "distribution_all = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "\n", + "files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_all, atoms_list, grid_all\n", + ")\n", + "histogram_all: np.array = histogram.rda(\n", + " atoms_index_dict_all, distances_dict_all, grid_all, nbins_all\n", + ")\n", + "\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y = histogram_all\n", + "smooth = make_interp_spline(x, y, k=3)\n", + "smooth_y = smooth(smooth_x)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b5bf0940662842c88d35e5e77fbe1d32", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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YmFjtOceOHUNJSQn69u3reey3335DSkoKfvnlF0yaNKlKrzz5RtTfxiB0yA2AUgnHqVMQDQbPnFBfSE9Px9atW7Fv3z4oFAqkpqYiLS0NmZmZyMjI8Mwp2rRpE+bPnw+VSgWVSoWJEyeitLQUKpWKyzqT18luCNatt96KxYsX46WXXsKePXug1Wrx1FNP4dFHH6103AcffAAADd4HJD09/ZK/MD788MMqj6WlpWHPnj0Nul5zo1cDLRXFMAo6BIl/rXahgQil+NeKIEZBh5aKYug5io2ILlNOTg5CQkJgMpl8utBHUFAQnn32WTzzzDPQaDQYMGAALly4gIMHD2LixIkIDQ3FU089hSeffBJmsxk33HADjEYjtm/fDr1ej/vvv7/Kc+7evRuCIHjeZDObzXC5XJgwYQKA8nmQ4eHhPmsj/SWoSxfEPf98pTkgYlFR+VAsvd7rvSGDBg2CwWDAwoULkZaWBkEQkJaWhnnz5qG4uBiPP/44gPLtA0RR9Jz3zTff4LXXXsP27dvRqlUrr9ZIJLsAApT3gkydOhUFBQVo0aJFtROVHn/8cUydOhUdOnTwQ4VUm+hwPYQHlsFi/GvXeofTiT3/+x+u7N8fatVfP5od9JGICtf7o0wiagJCQkKQlJSE/v3744orrsDOnTuRn5+PkJAQn9Xw4osvQqVS4R//+AfOnTuH+Ph4TJkyxfP1l19+GS1atMBbb72Fxx9/HBEREejTpw+ef/75ap9vz5496NChA0JDQwEABw4cQL9+/TxfP3DgAB566CHvNopqJAgCgrt2RVBqarVBRKhm6d3G4p4H8sknn2DRokUAykPJ3XffDYfDgfT0dADlGyZXtGvXLigUCnTr1s1rtRG5yTKAAIBSqayy70ZFF//DosATFZsAxCZ4Pnc4HNBmn0CrpFRO3CeiRhMWFoYXXngBSqUSgiCgb9++EEURKpV3/wvMyMjw/F2hUOCFF17ACy+8UO2xgiDg0Ucfxf3334+wsLBaVwCaN28e5s2b5/n8t99+Q/fu3T2f79+/nzeSAaCmIOIyGqHQe++NtcGDB2PPnj2esBEZGYnU1FScO3eO90cUEGQbQADg9OnT2Lp1K86ePQuLxeKZnwH8tXuuRqPxY4VERBQIKoYNQRC8Hj58bf/+/Z5VttwrfnlzeWGqn+qCiPN8PhR/9mA1tvnz52P+/PmVHnMvqlOT8ePHY/z48V6ph+hisvwNXFBQgIcffhirV6+uNE+jYgB54IEHsHLlSuzYsaPSJD0iIqKmxj3UBigPW3/88Ycfq6GaVAwicDohsLefminZrYJlMBiQlpaGL774Aq1atcL48eOrnSz14IMPQpIkz8Y6RERERIFAEASGD2rWZBdAXn/9dWRnZ+POO+/E77//juXLl6Nt27ZVjhs0aBCCg4M9mxQSEREREZH/yS6ArFq1ClqtFh988MElN3dSKBRISUmptFcHERERERH5l+wCyIkTJ9CxY8c6rW+u0+lQUFDgg6qIiIiIiKguZBdAgoKCYDAYaj8Q5buVcyMmIiIiIqLAIbsA0rVrV5w+fRonT5685HFZWVk4deoUV8AiIiIiIgogsgsg9913H0RRxEMPPQSz2VztMcXFxZg4cSIEQcC4ceN8XCEREREREdVEdvuATJo0CStXrsTGjRvRvXt33H333Th//jwAYMWKFThw4AA++eQTFBQUYOjQobjnnnv8XDEREREREbnJrgdEqVRi7dq1GD16NI4fP4433ngDR44cgSRJmDRpEhYuXIiCggKMGjUKq1ev9ne5RERE1IyIoqvSJsmB6sSJE+X7kVz08cMPP/i7NGoGZNcDAgChoaFYuXIlnn/+eXz11VfYv38/SktLodfrkZqaittvv51zP4iIiBqJIAj46quvcNttt/m7lIBmMdqR8elh6CO06Hx1PGIS9RAEwd9lXdKPP/6Irl27ej6PioryYzXUXMgygLh1794d3bt393cZREQkAwaDAbt370bfvn0RGhrq73LqJT09Hb169cLChQv9Xcply8jIwODBg1FcXIyIiAh/l9Oo7BYnygosKDhtwLkjJUhIifBpEFmzZg3Gjh2LoqIiKBQKZGVloXfv3njqqafwxhtvAAAmT56MsrIyzJs3DwAQHR2Nli1ber02oopkNwSLiIioIYxGIzIyMmA0Gv1dit/Y7XZ/l9BoJEmC0+n0dxnVCo0KglqrxKlDhdj072xs++8fuHDK4PWhWYMGDYLBYMDevXsBAJmZmYiJiUFmZqbnmIyMDKSlpXk+HzFiBGJjYzFgwACsWrXKq/URuckugGRlZWHChAlYuXLlJY/77LPPMGHCBOzfv99HlREREZW/Cx0REQGXywWg/P8tQRDw9NNPe46ZPHky7r33XgBAYWEh7r33XrRp0wYJCQno2bNnpf/jxo8fj8zMTCxatMgzTv/EiRMAgEOHDuGmm26CXq9HXFwcxo4dW2kD3vT0dDzyyCOYMWMGYmJiMGTIkBrrXrFiBbp27QqtVov4+Hg88sgj1R6XkZEBQRBQUlLieczdRnddJ0+exK233orIyEiEhISga9euWLduHU6cOIHBgwcDACIjIyEIAsaPHw+gPFC88cYb6NWrF0JCQtCzZ89KN8Tu665fvx79+vWDVqvF1q1ba/lu+I82WIXwFsE+DSLh4eHo1asXMjIyAJS/ZtOnT8e+fftgMBiQl5eHnJwcpKenQ6/X480338SqVauwbt06XH/99Rg9ejQ++eQTr9RGVJHsAsjSpUvx0UcfoU2bNpc8rm3btvjwww/x/vvv+6gyIiKi+r8LbbVa0bdvX3z77bfYvn07Jk2ahLFjx+J///sfAGDRokW4+uqrMWnSJOTm5iI3NxeJiYnIzc1FWloaevXqhV27duGHH37A+fPnMWrUqEr1fPTRR1CpVPj555+xdOnSamt+77338PDDD+Ohhx7C/v378e233yIlJaXBr8HDDz8Mm82GLVu2YP/+/Xjttdeg1+uRmJjoWSDm8OHDyM3NxaJFiwAAf//73/Hhhx9iwYIF2L9/P6ZPn4777ruv0usGAM888wzmzZuH7Oxs9OjRo8E1+oIgCDUHkdN121S5vtLT05GRkQFJkrB161aMHDkS3bp1w7Zt27B582bExcWhc+fOiImJwfTp03HllVeiX79+mDNnDqZNm4bXX3/dK3URVSS7OSCZmZkICwvDgAEDLnncgAEDEB4ejs2bN/uoMiIiCiQGg6HScKvc3NxKf7rp9fpGnRNS8V3ovn37et6Fnj17NgwGA0wmk+ddaABo1aoVnnrqKbhcLpSVlaFHjx5Yv349vvjiC/Tv3x/h4eHQaDTQ6XSVxuq/99576NOnD1599VXPYytWrEBiYiJycnLQsWNHAEBKSkqtN5Vz587Fk08+iccff9zz2BVXXNHg1+DUqVO48847PfM0k5OTPV9zT3KOjY31zAExmUx48803PROiw8LCkJKSgm3btmHp0qWVhgzNmTPnkj05gcgdRDRBShiLbTiWdQEOu4jrxnZp9Gulp6dj+fLl2LdvHxQKBVJTU5GWlobMzEwUFxdXei0vdtVVV+GDDz5o9JqILia7AHL69GnPL9XaJCUl4dixY16uiIiIAtHu3bs9Q1Eq+vbbbyt9np6e7gkDjcX9LvSMGTOwdetWzJ07F6tXr8a2bdtQUlLieRcaAERRxP/93//h888/x5kzZ2C322Gz2RASEnLJa+zevRubN2+GXq+v8rWjR496/q/s16/fJZ8nPz8f586dw/XXX9/A1lb12GOPYerUqdiwYQNuuOEG3HnnnZfsrTh06BCsViuGDRtW6XG73Y7evXtXeqy29gQiSZJgt4qwGOxQaZRI7tUCna+J98q13D1wCxcuRFpaGgRBQFpaGubNm4fi4uJKIfNie/fuRXy8d+oiqkh2AUShUNR5Ep3D4YAoil6uiIiIAlHfvn3RqVMnz+e5ubn49ttvMWLEiEo3WdXdwF+u+rwLvWDBArz11lt48803kZSUhLi4OMyYMaPW/+tcLhduvfVWvPbaa1W+VrF9tQWZ4ODgerVNoSgfvV1xHoPD4ah0zIMPPohhw4bhu+++w4YNGzBv3jwsWLAAjz76aLXP6Z4vs2bNGoSHh0Ov13uuo9VqKx1bW3sCycXBo01qtNdXxXL3wH3yySee4W2DBg3C3XffDYfD4QnbH330EdRqNXr37g2FQoE1a9Zg8eLF1f48ETU22QWQ9u3bY//+/cjNzb1kSj937hyys7ORmprqw+qIiChQhIaGVju0Kj4+3uvv8tbnXWj3OP377rsPZWVl0Ov1+OOPP9Cly1/DczQaTZU31Pr06YPVq1ejXbt2UKka/t95aGgo2rVrh59++skzQfxSWrRoAaA80EVGRgIon4R+scTEREyZMgVTpkzBzJkzsWzZMjz66KPQaDQAUKk9qamp0Gq1OHXqFEaOHImwsDBPAJErm8Xp0+BR0eDBg7Fnzx5P2IiMjERqairOnTtX6edq7ty5OHnyJJRKJTp27IgVK1bgvvvu83p9RLL7133rrbdCFEVMmjSpyjsubk6nE5MnT4YkSRgxYoSPKyQiouau4rvQ7pvAQYMGYc+ePZXmfwDlczQ2btyI7du34/Dhw5gyZQry8vIqPV+7du3wv//9DydOnEBBQQFcLhcefvhhFBUV4d5778WOHTtw7NgxbNiwARMmTKh37/+sWbOwYMECLF68GH/88Qf27NmDt99+u9pjU1JSkJiYiFmzZiEnJwffffcdFixYUOmYJ554AuvXr8fx48exZ88ebNq0yXPj27ZtWwiCgLVr1+LChQswGo0IDQ3FU089hSeffBIrV67E0aNHsXfvXrz77rv46KOP6tWWQGAossJhE9EmNRrXje2Ca0d1QIs2oT7blHD+/PmQJKnSBoNZWVnIz8/31HD//ffj0KFDMJlMKCsrw65duxg+yGdkF0CeeOIJxMfH4/vvv0efPn3wwQcfYP/+/Th9+jT279+PZcuWoU+fPvjuu+/QsmVLPPnkk/4umYiImqHBgwdDFMUq70K3aNGi0rvQL774Ivr06YPhw4fj1ltvRcuWLavsOP7UU09BqVR6zj916hQSEhLw888/QxRFDBs2DN26dcPjjz+O8PDwevce3H///Vi4cCGWLFmCrl274pZbbsEff/xR7bFqtRorV67E77//jp49e+K1117D3LlzKx0jiiIefvhhdOnSBTfeeCM6deqEJUuWACifdD979mw899xziIuL8yz3+/LLL+PFF1/EW2+9ha5du2LYsGFYs2YNkpKS6tUWf9IEqxAWE4x23WP8EjyI5EKQvL0rjhfs27cPI0aMwOnTp6v9Ry1JEtq2bYtvvvkm4Jfoq6isrAzh4eEoKChAdHS0v8u5LO62lJaWIiwsrE7nOBwOrFu3DjfddBPUarWXKww8zb39AF8Dtr9q+61WK44fP46kpCQEBQVd1vMH+k7o7lWwmsLwo4ZqCq+BKLqgUAgNCh1Nof2XI5Daf6nfPQ25x6HKZDcHBAB69uyJAwcO4J///Ce+/fZbZGdno6ysDKGhoejatStuu+02PPTQQ16ZWEhERPIUGhra6KtdEV1MqWx+wYGovmQZQIDy/0iefvrpSjvLEhERERFRYGNMJyIiIiIin2EAISIiIiIin5HlECyHw4F//etf+P7773Hs2DEYjUbUNJdeEAQcPXrUxxUSEREREVF1ZBdACgoKcN111+HgwYM1ho6KuPQdEREREVHgkF0Aee6553DgwAG0bt0azzzzDK644grExsb6fbk2IiIiIiKqnewCyNq1a6FWq7Fp0yakpKT4uxwiIiIiIqoH2XUblJaWolOnTgwfRERERJdBkiTMnz8fHTt2hFarRWJiIl599VV/l0XNgOx6QFJSUmC32/1dBhERBbhCow1Gm7PW4/RaFaL1Wh9URBRYHn/8cWzYsAHz589H9+7dUVpaioKCAn+XRc2A7ALIgw8+iBkzZmD37t3o27evv8shIqIAVGi04fH/7EWx2VHrsZE6NRbd09tvIcRqtWLKlCnYvXs3srOzcfPNN+Obb77xSy0kb2vWrMHYsWNRVFQEhUKBrKws9O7dG0899RTeeOMNAMDkyZNRVlaGf/zjH3jvvfdw4MABdOrUyc+VU3MjuyFYjz32GO69917cdttt/AVNRETVMtqcKDY7oFUqEBakqvFDq1Sg2OyoU0+Jt4iiiODgYDzyyCNIT0/3Wx3U+Jx2O3J+3Ya969ci59dtcHp5BMegQYNgMBiwd+9eAEBmZiZiYmKQmZnpOSYjIwNpaWlYs2YNkpOTsXbtWiQlJaFdu3Z48MEHUVRU5NUaiQAZ9oBcf/31AID8/HzccccdiIyMRPv27RESElLt8YIg4KeffvJliUREFCC0agV0mkv9V+eETXQ1+nXr8070ypUr8d5778HlciEzMxMmk6nR6yHfc9rt2PzR+ziTfRCABEDAyf1ZGHz/Q1BpNF65Znh4OHr16oWMjAz07dsXGRkZmD59OmbPng2DwQCTyYScnBykp6dj4cKFOHnyJL744gt8/PHHEEUR06dPx1133YVNmzZ5pT4iN9kFkIyMjEqfFxUVXTKtcx8QIiLytYrvRPft27fGd6KnT5/uxyrJm47t2YEz2QcREhEJtVYLh82GM9kHcWzPDnS86lqvXTc9PR0ZGRmYMWMGtm7dirlz52L16tXYtm0bSkpKEBcXh86dO8PlcsFms+Hjjz9Gx44dAQDLly9H3759cfjwYQ7LIq+SXQDZvHmzv0sgIiK6pPq8E01Nk6m0BIAEtbZ8bpFaqwUk6c/HvSc9PR3Lly/Hvn37oFAokJqairS0NGRmZqK4uBhpaWkAgPj4eKhUKk/4AIAuXboAAE6dOsUAQl4luwDi/odDREQUyOr6TjQ1TSHhEQAEOGw2Tw8IBOHPx73H3fu2cOFCpKWlQRAEpKWlYd68eSguLsbjjz8OABgwYACcTieOHj2K9u3bAwBycnIAAG3btvVqjUSym4ROREQkB+np6di6dWu170S7JwJT05Xc50q07tIVppJilOTlwlRSjNZduiK5z5Veva679+2TTz7x9LANGjQIe/bsqdTrdsMNN6BPnz6YMGEC9u7di927d2Py5MkYMmRIpV4RIm+QXQ9IRT///DMyMzNx9uxZWK1WLF++3PO1EydOwG638x8RERH5RV3fiaamSaXRYPD9D+HYnh0wlZYgJDwCyX2u9NoE9IoGDx6MPXv2eMJGZGQkUlNTce7cOc8wK4VCgTVr1uDRRx/FoEGDEBISguHDh2PBggVer49IlgHkyJEj+Nvf/oZdu3YBKN/JUxCESgHk9ddfx9KlS5GRkYGBAwf6q1QiImqmKr4TvWjRIgDloeTuu++Gw+GoNP/j0KFDsFqtKC4uhtVqRVZWFgCgV69evi+cGo1Ko/HqhPOazJ8/H/Pnz6/0mPtnqqKEhASsXr3aR1UR/UV2AeT8+fNIS0tDbm4urrjiCtxyyy3497//jaNHj1Y6bvz48fjnP/+J1atXM4AQETVTNocLQM17fJR/3Xvq8k40ANx00004efKk5/PevXsDKH+DjYioqZHdHJBXX30Vubm5ePjhh/Hrr7/ixRdfRFxcXJXjrrzySoSGhmL79u1+qJKIiPxJr1UhUqeGTXShzOqs8cMmuhCpU0Ov9c77cfPnz4ckSejatavnsaysLOTn51daJv7EiRMQRRHFxcUQRRGSJDF8EFGTJbsekLVr1yIkJATz58+vdY+P5ORknD592keVERFRoIjWa7Hont512uFcr1UhWq/1QVVERATIMICcPXsWqamp0Gpr/89Cq9WiuLjYB1UREVGgidZrGSyIiAKQ7IZg6fV6XLhwoU7Hnjp1CtHR0V6uiIiIiIiI6kp2AaR37944d+4c9u/ff8njMjMzkZeXh6uuuspHlRERERERUW1kF0AmTpwISZIwYcIE5ObmVnvM0aNHMWHCBAiCgEmTJvm4QiIiIiIiqons5oDcc889+PLLL7Fq1SqkpqZi2LBhOHXqFADgH//4Bw4cOIB169bBbrdj7NixuPHGG/1cMRERERERuckugADAZ599hvbt22PhwoX473//63n8lVdegSRJ0Gg0eOaZZ/DKK6/4sUoiIiIiIrqYLAOISqXCvHnz8OSTT2LdunXYv38/SktLodfrkZqaiptvvhnx8fH+LpOIiIjI79LT09GrVy8sXLgQ7dq1wxNPPIEnnniiUa8xfvx4lJSU4Ouvv65yzcZ28bVIfmQXQObMmQNBEPDss88iJiYG48aN83dJRERE1Aw4HA6Ioui153e5XLDZbLBarVAoFFAqlVCr1Y16jZ07dyIkJKROx9YnrCxatKjRN888ceIEkpKSsHfvXvTq1cur1yLfkl0Aefnll9GxY0e8+OKL/i6FiIiImgmHw4HDhw/DYrF47RqSJMFqtSIoKAiCICA4OBidOnVq1BDSokWLRnsuABBFEYIgIDw8vFGf91J8eS3yDtmtghUXFwedTufvMoiISG5yfwO+ebT8zwCSkZGBkSNHolWrVmjVqhX69OmDTz/91N9l0UVEUYTFYoFKpUJQUJDXPrRaLYKCgqBSqWCxWOrd42IymTBu3Djo9XrEx8djwYIFlb7erl27SsOiZs2ahTZt2kCr1SIhIQGPPfYYgPIhVCdPnsT06dMhCAIEQQAAfPjhh4iIiMDatWs9G0OfPHkS48ePx2233VbpWk6nE4888ggiIiIQHR2Nv//975V6LgRBqDKMqm3btvjwww8BAElJSQDKt2AQBAHp6ekAUOVaNpsNjz32GGJjYxEUFIRrr70WO3fu9Hw9IyMDgiDgp59+Qr9+/aDT6XDNNdfg8OHD9XptqfHILoDccMMNOHjwIEpLS/1dChERyYUkAVmfAEd/Kv8zgIZvbN++HT169MAXX3yBbdu24YEHHsC4ceOwZs0af5dG1VCpVNBoNF77UKvV0Gg0UKkaNkjl6aefxubNm/HVV19hw4YNyMjIwO7du6s9dtWqVXjrrbewdOlS/PHHH/j666/RvXt3AMCXX36J1q1bY86cOcjNza209YHZbMa8efPwwQcf4ODBg4iNja32+T/66COoVCr873//w+LFi/HWW2/hgw8+qHNbduzYAQD48ccfkZubiy+//LLa45555hmsXr0aH330Efbs2YOUlBQMGzYMRUVFlY574YUXsGDBAuzatQsqlQoTJkyocy3UuGQ3BGvWrFn49ttv8cADD+DTTz9FcHCwv0siIqJAl7sPOPkLEBxR/mfuPiChl9cut2bNGowdOxZFRUVQKBTIyspC79698dRTT+GNN94AAEyePBllZWVYuXIlgPLx/2VlZejZsyc2bNiAr776CrfeeqvXaqSmx2g0Yvny5fj4448xZMgQAOUhoHXr1tUef+rUKbRs2RI33HAD1Go12rRpgyuvvBIAEBUVBaVSidDQULRs2bLSeQ6HA0uWLEHPnj0vWU9iYiLeeustCIKATp06Yf/+/XjrrbfqvEebe7hYdHR0lRrcTCYT3nvvPXz44YcYPnw4AGDZsmXYuHEjli9fjqefftpz7CuvvIK0tDQAwHPPPYebb77ZM+SNfEt2PSBbtmzBlClTsGbNGqSkpOCxxx7De++9h48//rjGj4ZasmQJkpKSEBQUhL59+2Lr1q2XPP7TTz9Fz549odPpEB8fjwceeACFhYUNvj4RETUCSQL2fQY4LEBY6/I/933m1V6QQYMGwWAwYO/evQCAzMxMxMTEIDMz03NMRkaG52boYqWlpYiKivJafdQ0HT16FHa7HVdffbXnsaioKHTq1Kna4++++25YLBYkJydj0qRJ+Oqrr+B0Omu9jkajQY8ePWo97qqrrvIM3QKAq6++Gn/88UejTuQ/evQoHA4HBgwY4HlMrVbjyiuvRHZ2dqVjK9bsXi01Pz+/0WqhupNdD8j48eMhCAIkSUJubi7efffdWs9pyEpZn3/+OZ544gksWbIEAwYMwNKlSzF8+HAcOnQIbdq0qXL8tm3bMG7cOLz11lu49dZbcfbsWUyZMgUPPvggvvrqq3pfn4iIGom79yMkBhCE8j+93AsSHh6OXr16ISMjA3379kVGRgamT5+O2bNnw2AwwGQyIScnxzOmvaJVq1Zh586dWLp0qVdqo6arvitDJSYm4vDhw9i4cSN+/PFHTJs2DW+88QYyMzMvOfE9ODi4UrBoKPf9XEV1CUAVuc+/uB5Jkqo8VrFN7q+5XK56XY8ah+wCyLhx4xrlh742b775JiZOnIgHH3wQALBw4UKsX78e7733HubNm1fl+F9//RXt2rXzTN5KSkrC5MmT8frrr3u9ViIiqkHF3o/QP/eH0oYBpoLyx+N7locSL0hPT0dGRgZmzJiBrVu3Yu7cuVi9ejW2bduGkpISxMXFoXPnzpXO2bZtGyZMmIBly5aha9euXqmLmq6UlBSo1Wr8+uuvnjdLi4uLkZOTU2NvW3BwMEaMGIERI0bg4YcfRufOnbF//3706dMHGo3msnorfv311yqfd+jQAUqlEkD5EKuKc0v++OMPmM1mz+cajQYALllDSkoKNBoNtm3bhjFjxgAoHyK2a9euRt/rhBqP7AKIe2UEb7Lb7di9ezeee+65So8PHToU27dvr/aca665Bi+88ALWrVuH4cOHIz8/H6tWrcLNN9/s9XqJiKgGF/d+AD7rBUlPT8fy5cuxb98+KBQKpKamIi0tDZmZmSguLq5yQ5iZmYl7770X8+fP5x5X1CB6vR4TJ07E008/jejoaMTFxeGFF16AQlH9iPsPP/wQoiiif//+0Ol0+Pe//43g4GC0bdsWQPmKWVu2bME999wDrVaLmJiYetVz+vRpzJgxA5MnT8aePXvw9ttvV1qV67rrrsM777yDq666Ci6XC88++2ylXorY2FgEBwfjhx9+QOvWrREUFFRlCd6QkBBMnToVTz/9NKKiotCmTRu8/vrrMJvNmDhxYr3qJd+RXQCZMGECVCoV3nnnHU8ybmwFBQUQRRFxcXGVHo+Li0NeXl6151xzzTX49NNPMXr0aFitVjidTowYMQJvv/12jdex2Wyw2Wyez8vKygCUJ3eHw9EILfEfd/31aUvFc5qj5t5+gK8B21+1/Q6HA5IkweVy1X+ohCRByPoMcJgBfcvKcz40oYDpApD1GaS47l7pBbn22mthMBjw1ltvYdCgQZAkCQMHDsRrr72G4uJiPPbYY542ZWRkYMSIEXjppZcwadKkZjssxD2cxv09DyQulwuSJHl+Jr3B/fw2mw2iKDboZ/+1116DwWDAiBEjEBoaihkzZqC0tLTSa+r+e1hYGF5//XXMmDEDoiiie/fu+OabbxAZGQmXy4VZs2Zh6tSpaN++vacm93NcXJMkSVW+b2PHjoXZbMaVV14JpVKJRx55BA8++KDnmDfeeAMTJkzAoEGDkJCQgDfffBO7du3yPL9CocDChQsxd+5c/OMf/8DAgQOxadOmKtd69dVXIYoixo4dC4PBgH79+uH7779HeHh4pdfv4r9f/FhFFb/f7h4bt+b6O7oxCZLMtpLUaDTo2rWrZ2KfN5w7dw6tWrXC9u3bK03keuWVV/Dvf/8bv//+e5VzDh06hBtuuAHTp0/HsGHDkJubi6effhpXXHEFli9fXu11Zs2ahdmzZ1d5/LPPPpP9XidmsxljxoxpEm0hIv9RqVRo2bIlEhMT6/2mkzJ/P4I3PgtJrSsfdnUxWxkEhxmWIa9BjO3eSBVXlp6ejgMHDmDevHmYNGkSSkpK0LFjRzgcDvzyyy/o3Lkztm3bhtGjR2Py5MmYPHmy51yNRoPIyEiv1EX153Q6cfTo0UpvHHqbVqtF+/btG7wkLzWc3W7H6dOnkZeXV2Veivsep7S0FGFh1fxuoVrJLoAkJSUhIiLCqwHEbrdDp9Phiy++wO233+55/PHHH0dWVlalVUzcxo4dC6vVii+++MLz2LZt2zBw4ECcO3fOs9pCRdX1gCQmJiI3NxfR0dGN3CrfKisrQ0xMDAoKCur8j9PhcGDjxo0YMmRIo+76KhfNvf0AXwO2v2r7rVYrTp8+jXbt2tVvqUxJgrB+JvDH+vKVr1BdD4cElJ0BOgyDNGyeV3pBnn76abz55pv47bffPHM6+vTpg3PnziE3NxeCIOCBBx6odsXGtLQ0bNq0qdFrCmSSJMFgMCA0NNQn8z3ry+FwNOoKTheTJAlGoxF6vR6CIECpVDar3wWB9P23Wq04ceIEEhMTq/zucd/jMIA0nOwi9c0334z3338fubm51d7UNwaNRoO+ffti48aNlQLIxo0bMXLkyGrPMZvNVd6hcHfZ1ZTxtFottFptlcfVarXsf+G4629IW5pC+y9Hc28/wNeA7f+r/aIoQhAEKBSKGsexV0t0AIbc8p4PW1nNx2nDAEMuBLgAReO/5gsWLKiyE3VWVlalzz/66CN89NFHnn1AwsLC6tfWJsQ9FMb9PQ801f2f3ZhcLhccDgeCg4MDsv3eFkjff4VCAUEQqv193Jx/PzcW2QWQWbNmYe3atRg1ahRWrVpVZZ5GY5kxYwbGjh2Lfv364eqrr8b777+PU6dOYcqUKQCAmTNn4uzZs553rW699VZMmjQJ7733nmcI1hNPPIErr7wSCQkJXqmRiIhqoFQDtywEbKW1H6sNLz+eiIh8QnYBZMmSJbjllluwdOlSJCUl4YYbbkCXLl0QEhJS7fGCIODFF1+s93VGjx6NwsJCzJkzB7m5uejWrRvWrVvnWRkiNzcXp06d8hw/fvx4GAwGvPPOO3jyyScRERGB6667Dq+99lrDGkpERJcnJLr8g4iIAorsAsisWbM8G9eIooi1a9di7dq1VY5zH9PQAAIA06ZNw7Rp06r9WnXLAT/66KN49NFHG3QtIiIiIqLmQHYB5KWXXvJ3CURERERE1EAMIERERERE5DPNb4kFIiIiIiLyGwYQIiIiIiLyGdkNwZozZ069jr+cSehERERERNS4ZBdAKq6CdbGLd8283FWwiIiIiIiocckugFxqErrJZMKRI0ewfv16iKKIadOmITw83IfVERFRoCi2FsNoN9Z6nF6jR2RQpA8qIiIioIkFELczZ87gb3/7G9avX49ffvnFB1UREVEgcbgcmPPLHJwxnqn12Nb61ng97XWoFf7ZDf3w4cOYMmUKDh06hNLSUiQkJGDMmDF46aWXoFZzh3YianpkF0DqonXr1vjPf/6Dtm3b4sUXX8SiRYv8XRIREfmQSlAhVheL34t+R4I+ocbjzhnPIVYXC5Xgv/8O1Wo1xo0bh169ekGpVOLYsWOYPHkyXC4XXn31Vb/VRUTkLU12Faz4+Hh069YNX331lb9LISIiHxMEASNTRkKv0cPpciJYFVzlw+lyQq/RY2TKyCpzCC/XmjVrEBERAZfLBQDIysqCIAh4+umnPcdMnjwZ9957L5KTk/HAAw+gZ8+eaNOmDUaMGIG//e1v2Lp1a6PWREQUKJpsAAGA0tJSXLhwwd9lEBGRH3SJ6oI+sX1QZC2qsnCJJEkoshahT2wfdInq0ujXHjRoEAwGA/bu3QsAyMzMRExMDDIzMz3HZGRkIC0trcq5R44cwQ8//FDt14iImoImG0C+//57HD9+HImJif4uhYiI/MDdCxKkCoLRUXkyutFhRJAqyCu9HwAQHh6OXr16ISMjA0B52Jg+fTr27dsHg8GAvLw85OTkID093XPOtddei5YtW6JTp04YOHBgvZedJyKSC9nNAfn4449r/JokSbhw4QJ27tyJr7/+GoIg4P777/dhdUREFEjcvSDbz22HXq33LONeZC3CNQnXeKX3wy09PR0ZGRmYMWMGtm7dirlz52L16tXYtm0bSkpKEBcXh86dO3uOX7lyJXJzc3H06FE8++yzmD9/Pp555hmv1UdE5C+yCyDjx4+v9d0qd1f7xIkTMXPmTF+URUREAcjdC7Infw+MDiNCNaFe7/1wS09Px/Lly7Fv3z4oFAqkpqYiLS0NmZmZKC4urjLEKjExEeHh4bjyyishSRIeeughPPnkk1AqlV6rkYjIH2QXQMaNG1fjfxiCICAkJATJyckYPnx4pXeWiIioebq4F8QXvR/AX/NAFi5ciLS0NAiCgLS0NMybNw/FxcV4/PHHazxXkiQ4HI5qN90lIpI72QWQDz/80N8lEBGRjFTsBckz5/mk9wP4ax7IJ5984lkOftCgQbj77rvhcDg88z8+/fRTqNVqdO3aFQ6HA4cPH8bMmTMxevRoqFSy+2+aiKhW/M1GRERNnrsXZNOpTbiuzXVe7/1wGzx4MPbs2eMJG5GRkUhNTcW5c+fQpUt5DSqVCq+99hpycnIgSRLatm2Lhx9+GNOnT/dJjUREvia7AOJwOJCbm4uQkBBER0fXeFxhYSFMJhMSEhL4DhIRUTMnCAJu73A7rE4rbu9wu9d7P9zmz5+P+fPnV3osKyur0uejR4/G6NGj4XK5UFZWhrCwMCgUTXaRSiIi+S3Du2zZMiQlJeHf//73JY/797//jaSkJKxYscJHlRERUSDrHNUZswfMRucozg8kIvIn2QWQVatWQaFQYPz48Zc8bvz48VAoFPjiiy98UxjViSRJEEXR32UQERERkZ/IbmzS4cOHkZiYiIiIiEseFxERgcTERBw+fNg3hVGtSktLcfbsWdhsNkRERKBVq1bQaDT+LouIiIiIfEh2PSCFhYVo0aJFnY5t0aIFLly44OWKqC7Kyspw5MgRlJWVAQDOnTuH48ePw+l0+rkyIiIiIvIl2fWAREdH4/jx43U69vjx4wgPD/dyRVQbp9OJ06dPw+FwIDIyEgCg1WpRUFCAkJAQtG7d2s8VElGg434YRORL/J3jXbLrAenfvz8KCwuxcuXKSx73n//8BwUFBejfv7+PKqOaFBUVobS0FGFhYZ7HlEolQkJCkJeXB5PJ5MfqiCiQqdVqAIDZbPZzJUTUnLh/57h/B1Hjkl0PyNSpU/H111/joYcegiRJGDNmTJVjVq5ciYceegiCIGDq1Kl+qJLcRFFEfn4+1Go1lEplpa8FBwejsLAQ+fn5SEpK8lOFRBTIlEolIiIikJ+fDwDQ6XQ+W0LX11wuF+x2O6xWa7Ndhre5vwZsv//bL0kSzGYz8vPzERERUeXehRqH7ALIkCFDMG3aNCxZsgRjx47Fs88+iyuvvBIREREoKSnBzp07cfbsWUiShGnTpuHGG2/0d8nNmsFggMFgqHEoXEhICIqKitCyZUvu10JE1WrZsiUAeEJIUyVJEiwWC4KDg5tsyKpNc38N2P7AaX9ERITndw81Plne8b3zzjvo0KED5s6di7Nnz+Krr76q9PWYmBi8+OKLePTRR/1UIbmVlJQAQI3vIGi1WhiNRhQXF9d5cQEial4EQUB8fDxiY2PhcDj8XY7XOBwObNmyBYMGDWq2wz6a+2vA9gdG+6sbtUGNS5YBBAAef/xxTJ48GT///DOys7NRVlaG0NBQdO3aFQMGDIBWq/V3iYTypXf1en2NXxcEwTMhPSoqyoeVEZHcKJXKJn1ToFQq4XQ6ERQU1CxvPgG+Bmx/825/cyLbAAIAQUFBuP7663H99df7uxSqgdVqRUxMzCWP0el0KCsr42R0IiIiomag+c1wIp+rbSKZUqmEy+WCwWDwUUVERERE5C+yCyDffvstkpOTsWDBgkset2DBAiQnJ2PdunU+qowqcq+fXdedzrVaLYqLi71ZEhEREREFANkFkI8//hgnT57E7bfffsnjRo4ciRMnTuDjjz/2UWVUkcViAYA6z8UJCgrynENERERETZfsAsjevXsRGxuL5OTkSx6XkpKCuLg47Nq1y0eVUUXuMFHXSWQqlQqiKHqzJCIiIiIKALILIOfOnUObNm3qdGxiYiJyc3O9XBFVpyETyt3DtdzDt4iIiIio6ZFdAAkJCcGFCxfqdGxBQQGX4/UDSZIaNKHc/b2y2+2NXRIRERERBQjZBZDu3bvj5MmTtQ6t2rVrF06cOIFu3br5qDJys9lssNls9T7PPVyLy/ESERERNV2yCyBjxoyBJEn429/+hmPHjlV7zPHjx/G3v/0NgiBgzJgxPq6QrFYrnE5nvc8TBAEAYDabG7skIiIiIgoQstuIcMKECfjoo4+wfft2dOvWDXfccQf69++PiIgIlJSU4Ndff8XXX38Ni8WCa665BpMmTfJ3yc2O1Wq9rHkcpaWlkCTJE0iIiIiIqOmQXQBRKpVYu3YtHnjgAXzzzTf47LPPsHLlSs/X3Te+t99+O5YvXw6lUumvUpstk8lU6+aDl2Kz2WC1WhEcHNyIVRERERFRIJBdAAGAiIgIfPXVV9i1axe++eYbZGdno6ysDKGhoejatStuu+029OnTx99lNkuSJMFoNNZ5+d3qOBwOmM1mBhAiIiKiJkiWAcStX79+6Nevn7/LoApsNhscDsdlBRCgfB5IdHR0I1VFRERERIFCdpPQKbDZbDbY7XaoVA3PthqNBmVlZdwPhIiIiKgJkl0PiMFgwLp16/DLL7/gzJkzMBgMCA0NRatWrXD11VfjpptuQlhYmL/LbLbcy+9ezhwQjUYDq9UKu93OfVyIiIiImhjZBBCn04lZs2bh7bffhtFoBFB5x2xBEPDOO+9Ar9fjkUcewaxZsy57GBDVn9VqveznUKlUsFgssFqtDCBERERETYwsAkhZWRmGDh2KnTt3QpIkqFQqdOnSBe3bt0dISAhMJhOOHj2K7OxsGAwG/N///R82btyIH3/8kb0hPmYymS47+CkUCkiSBIvFgvDw8EaqjIiIiIgCgSwCyN13340dO3ZAr9fj+eefx6RJk6qdoFxYWIhly5bh1Vdfxe7du3H33Xdj/fr1fqi4eRJFEVarFWq1GqIoXtZzKZVKT08XERERETUdAT8J/dtvv8XGjRsRFxeHX3/9Fc8991yNqyNFR0fjueeewy+//IIWLVrgxx9/xLfffuvjipsvu90Op9N5WRPQ3dRqNYxGI1wuVyNURkRERESBIuADyCeffAJBEPD2228jNTW1Tud07doVb7/9NiRJwieffOLlCsmtMQOIRqOBw+FolDklRERERBQ4Aj6A/Prrr4iMjMQdd9xRr/PuuOMOREZG4tdff/VSZXQxm80GSZIgCMJlP5dKpWIAISIiImqCAj6AXLhwAcnJyfVe1lWpVCI5ORkXLlzwUmV0MZvN1ijhA4DneSwWS6M8HxEREREFhoAPIDqdDmazuUHnWiwW6HS6Rq6IamKxWKBUKhvt+ZRKJUwmU6M9HxERERH5X8AHkOTkZOTk5KCwsLBe5xUUFODw4cNISkryUmVUkXvZ3MaY/+Gm0WhgMpkue0UtIiIiIgocAR9Ahg8fDqfTiTlz5tTrvNmzZ8PlcuGmm27yUmVUkcPhaLQJ6G5qtRpOp9OzuzoRERERyV/AB5BHH30UoaGheOeddzyh4lJcLhdmzZqFd999F3q9Ho8++qiPKm3e3AGkMYdguSeiM4AQERERNR0BH0BatGiBZcuWQRAEzJkzBz169MDixYuxb98+GI1GSJIEo9GIffv2YfHixejZsydefvllCIKA999/Hy1atPB3E5oFu90OURQbNYC4J6JzJSwiIiKipkMWO6GPGjUKCoUCDz30EA4dOoTp06fXeKwkSQgPD8f777+Pu+++24dVNm8OhwMAGm0VLDdORCciIiJqWgK+B8TtrrvuQnZ2Np5//nmkpKRAkqQqHykpKXj++eeRnZ3N8OFjjbkEb0UqlQomkwmSJDX6cxMRERGR78miB8QtLi4Oc+fOxdy5c1FYWIizZ8/CYDAgNDQUrVq1QnR0tL9LbLasVmu992qpC7VaDbvdDrvdDq1W2+jPT0RERES+JasAUlF0dDQDR4DwxhK8bmq1GiaTCVarlQGEiIiIqAmQzRAsf1iyZAmSkpIQFBSEvn37YuvWrZc83maz4YUXXkDbtm2h1WrRvn17rFixwkfV+o8oio2+ApabQqGAJEmw2+2N/txERERE5Huy7QHxts8//xxPPPEElixZggEDBmDp0qUYPnw4Dh06hDZt2lR7zqhRo3D+/HksX74cKSkpyM/Ph9Pp9HHlvudwOCCKIjQajVeeXxAEWCwWrzw3EREREfkWA0gN3nzzTUycOBEPPvggAGDhwoVYv3493nvvPcybN6/K8T/88AMyMzNx7NgxREVFAQDatWvny5L9xht7gFTknohORERERPLHAFINu92O3bt347nnnqv0+NChQ7F9+/Zqz/n222/Rr18/vP766/j3v/+NkJAQjBgxAi+//DKCg4OrPcdms1XaZK+srAxA+Q29e1lbObBYLBBFEZIkQRRFAKj0p/vvtbn4XDelUgmz2Qyr1eq1kBMI3N9zOX3vG1tzfw3Yfra/4p/NUXN/Ddh+ebQ/0OuTAwaQahQUFEAURcTFxVV6PC4uDnl5edWec+zYMWzbtg1BQUH46quvUFBQgGnTpqGoqKjGeSDz5s3D7Nmzqzy+efNm6HS6y2+IjxUWFnr+bjabAQBHjx6td1uOHTtW7eNnzpxpeHEysnHjRn+X4HfN/TVg+9n+5q65vwZsf2C3332PQw3HAHIJF+9rIUlSjXtduFwuCIKATz/9FOHh4QDKh3HdddddePfdd6vtBZk5cyZmzJjh+bysrAyJiYkYPHiwrFb4Onv2LM6cOeMZegYARqMRANC+fXvo9fo6PY8oijh27BiSk5Mr9XRIkoTi4mJ06tQJERERjVp7IHE4HNi4cSOGDBkCtVrt73L8orm/Bmw/29+c2w/wNWD75dF+94gVariADiDXXXcdevTogYULF3oe27JlC8LDw9GzZ0+vXTcmJgZKpbJKb0d+fn6VXhG3+Ph4tGrVyhM+AKBLly6QJAlnzpxBhw4dqpyj1WqrXVpWrVYH9D+8izkcDmg0mkqhwf13pVJZ72FT1Z2jUCggiqKsXpeGktv33xua+2vA9rP9zbn9AF8Dtj+w2x/ItclFQC/Dm5GRgT179lR6LD09HY899phXr6vRaNC3b98qXYAbN27ENddcU+05AwYMwLlz5zzv/ANATk4OFAoFWrdu7dV6/c1ms3l9boYgCLBarV69BhERERF5X0AHELVaXe04O0mSvH7tGTNm4IMPPsCKFSuQnZ2N6dOn49SpU5gyZQqA8uFT48aN8xw/ZswYREdH44EHHsChQ4ewZcsWPP3005gwYUKNk9CbAlEU4XA4vB5A3BsSEhEREZG8BfQQrKSkJBw8eBB79+5F7969fXrt0aNHo7CwEHPmzEFubi66deuGdevWoW3btgCA3NxcnDp1ynO8Xq/Hxo0b8eijj6Jfv36Ijo7GqFGjMHfuXJ/W7WvuPUC8vUu5SqWCzWaD0+n0yo7rREREROQbAX0nN27cOPz973/HFVdcgRYtWnh6Enbt2oXk5OQ6PYcgCDh69GiDrj9t2jRMmzat2q99+OGHVR7r3LlzwK/c0NicTiecTqfXV+1y94DYbDYGECIiIiIZC+g7ueeeew4mkwlLly7F+fPnPY9brVacOHGiTs9R06pV1DgcDgdcLhcUCu+O5lMqlXA6nbDb7QgJCfHqtYiIiIjIewI6gCgUCrzyyit45ZVXcOHCBZjNZiQlJeGKK67Af//7X3+XRyjvAQG8H/Tcz19x40YiIiIikp+ADiAVtWjRwvN3rVbrmYtB/uUOIL7AlbCIiIiI5E82AcTN5XL5uwSqwG63+2yYG1fCIiIiIpI/2QWQi1ksFhw9ehQGgwGhoaFo3759k172NtD4Yg8QN5VKBbvdzpWwiIiIiGQsoPcBuZT169cjPT3dsyv6tddei549eyI8PBzXXXcdNmzY4O8SmwWr1erTAOKeiE5ERERE8iTLADJr1izcdNNN2LJlC5xOJ9RqNRISEqBWq+F0OpGRkYHhw4dj1qxZ/i61SRNFEaIo+jSAOBwOBhAiIiIiGZNdAPnhhx8wZ84cKBQKTJs2DYcPH4bVasXp06dhtVpx+PBhTJs2DUqlEi+//DLWr1/v75KbLKfT6dMA4p5rwgBCREREJF+yCyCLFy+GIAhYsWIF3nnnHXTo0KHS1zt06IB33nkHK1asgCRJWLRokZ8qbfrcAcTbe4BcjCthEREREcmX7ALIzp070bp1a4wdO/aSx913331ITEzEjh07fFRZ8+PrHhCgfCUsi8Xis+sRERERUeOSXQAxGAyIi4ur07FxcXFcttWLfLUJYUUqlQoWi4XLMRMRERHJlOwCSEJCAn7//fdag4XJZEJ2djbi4+N9VFnz48tNCN24EhYRERGRvMkugAwbNgxGoxGTJk2q8SbUbrfjwQcfhNlsxo033ujjCpsPh8Ph82sygBARERHJm+x2c3v++efx+eef4/PPP0dGRgYmTZqE1NRUxMbGIj8/H4cOHcKyZctw/vx5hIeHY+bMmf4uucmy2+0+n4CuUCjgcrkYQIiIiIhkSnYBJDExEd9//z1GjRqF06dPY+7cuVWOkSQJbdq0wX//+18kJib6ocrmwW63+3QCekX+6H0hIiIiossnuwACAP3798fvv/+Ozz77DBs2bEBOTg6MRiP0ej06duyIYcOG4d5770VwcLC/S22yJEnySw8IUN4LwpWwiIiIiORJlgEEAIKDgzFx4kRMnDjR36U0Sy6Xy+dL8LqpVCqYzWafX5eIiIiILp/sJqFTYPDXJoRA+V4gdrvdL6twEREREdHlYQChBnE6nXC5XH7rAeFKWERERETyxABCDSKKot96QJRKJQMIERERkUwxgFCDOJ1OSJLklwDi3nmdAYSIiIhIfhhAqEGcTqcnCPiDIAiw2Wx+uz4RERERNQwDCDWIKIqQJMlv11cqlVyKl4iIiEiGZLsML/mXw+G47B6QMkcZzOJfy+mKoohCsRCh1tBKk9t1Sh3C1GGVzlWpVLBYLJAkya89MURERERUP7ILIBMmTIBSqcS7774LjUbj73KarcvdhNDpcuL94+/jvPW85zEJEmxWG7RHtRDwV6iIC4rDEylPQKX468dVpVLB4XDA4XDw54CIiIhIRmQ3BOuTTz7Brl27eNPpZ3a7/bKW4FUKSkSpo2AWzdApdQhRhiBEEYIgIQghihCEKEOgU+pgFs2IUkdBKVS+FpfiJSIiIpIn2QWQVq1a+buEZk+SJDgcjsvqAREEAemx6dApdXBJLmiVWmiVWmgEjefvLskFnVKH9Nj0KsOsFAoFRFGEw+G43OYQERERkQ/JLoDcfPPNOHjwIHJzc/1dSrMliiJcLtdlL8GbpEtCl9AuKHWWVpnQLkkSSp2l6BLaBUm6pCrncileIiIiInmSXQCZNWsWEhISMGrUKJw/f772E6jRuTchvNxd0N29IFqFFhax8opWFtECrUJbbe9HxfO5FC8RERGRvMhuEvqSJUtwyy23YOnSpUhKSsINN9yALl26ICQkpNrjBUHAiy++6OMqmzan09koPSDAX70gWaVZCFIEAfir96NXeK9qez/cuBQvERERkfzILoDMmjULgiBAkiSIooi1a9di7dq1VY5zH8MA0vjcPSCNEUDcvSDZhmxYXOVhwuKqvfcD+Gsp3sYKQ0RERETkfbILIC+99JK/S2j23JsQNtZNv7sXZG/pXoRKoShzlqF3eO9L9n4AlZfi1Wq1jVILEREREXkXAwjVmyiKjbr5n7sX5JDhEEqlUgQrgmvt/QDKA4jZbGYAISIiIpIRjluhenM6nY3+nEm6JHTWd4ZFsqCzvnOtvR9A+RwQl8vFlbCIiIiIZER2PSAV2Ww27N69G2fPnoXFYsG4ceP8XVKz4I0AIggCBrcYjAslFzC4xeB69bAwgBARERHJhyx7QGw2G5599lnExsZi4MCBuOeee/DAAw9UOmbixIlISEjA4cOH/VRl0+VwOBp1CJZbO1073K67He107ep8DpfiJSIiIpIX2QUQu92OoUOHYv78+ZAkCenp6YiJialy3B133IG8vDysWrXKD1U2bZe7C3pjUqlUsFqt/i6DiIiIiOooMO4i62Hx4sXYunUrrr32WuTk5OCnn35Cx44dqxw3ZMgQaDQabNiwwQ9VNm12uz1gAoh7LxCXy+XvUoiIiIioDgLjLrIePv30U6jVaqxcuRItW7as8TiNRoOUlBScPHnSh9U1fZIkwel0BkwAUalUEEURDofD36UQERERUR0Exl1kPeTk5KBDhw5ISEio9djQ0FCcP3/eB1U1H6IowuVyQalU+rsUAJX3AiEiIiKiwCe7AOK+4ayLwsJChISEeLmi5sUdQAKlB4RL8RIRERHJS2DcRdZDx44dceLECVy4cOGSxx09ehRHjhxB9+7dfVRZ8xBoAcSNPSBERERE8hBYd5F1cNddd8HhcGD69Ok1Tjy22+2YOnUqBEHAPffc4+MKmzan0xlwAYRL8RIRERHJh+w2Inzsscfw8ccfY+XKlTh69Cjuv/9+lJaWAgA2b96M/fv3Y+nSpcjOzkafPn0wYcIEP1fctARiD4h7JSwiIiIiCnyyCyDBwcHYuHEj7r77bvzyyy/YsWOH52s33HADgPKVmq666ip8+eWXUKvV/iq1SRJF0SubEF4O914gkiQFXG1EREREVJnsAggAJCQkYNu2bfjuu+/w5ZdfYv/+/SgtLYVer0dqairuuOMO3H777bwZ9QJRFP1dQhUVV8LSaDT+LoeIiIiILkGWAQQoH/d/yy234JZbbvF3Kc2KKIqQJMnfZVTiHoLFAEJEREQU+AJnID/JgtPpDLieJaVSCVEUuRQvERERkQzItgcEAE6cOIENGzYgJycHBoMBoaGh6NixI4YMGYKkpCR/l9ck2e32gJqADsATiLgULxEREVHgk2UAKSgowMMPP4zVq1d7hgNVnIAsCALuvPNOvP3224iNjfVnqU2Ow+EIuAACcCleIiIiIrmQXQApLi7GgAEDcOTIEUiShGuvvRZdunRBXFwc8vPzkZ2dja1bt2LVqlXYu3cvfv31V0RFRfm77CYjUAMIl+IlIiIikgfZBZAXX3wRf/zxB3r27ImPP/642p3ODxw4gHHjxmHfvn146aWX8Pbbb/uh0qbH5XJBFMWADSBcipeIiIgo8AXenWQtvv76a6jVaqxZs6ba8AEA3bp1w7fffgulUomvvvrKxxU2Xe4VsAIxgLiX4nU6nf4uhYiIiIguIfDuJGtRWFiIbt26oXXr1pc8rnXr1ujevTuKiop8VFnT549d0CVJglSHUKFSqSCKIieiExEREQU42Q3BatOmDUwmU52ONZlMSExM9HJFzYcvA4gkScCxY5A2bQIKi4BpUyGEhdV4fMWleHU6ndfrIyIiIqKGkV0PyJgxY/DHH39gy5Ytlzxuy5YtyMnJwX333eejypo+l8vl/QAiScDRY5A++ADSO+8AO3cB5/OAWkKnIAiQJIk9IEREREQBTnYB5IUXXsBNN92EkSNHYvHixVV6Q8xmM95++23cdtttuOWWW/D888/7qdKmx5s9INKfwaPFmjXAkiXA3iwgKAiIbVGv5+FSvERERESBLaCHYF133XXVPi5JEkwmE6ZPn45nn30WrVu3RmxsLC5cuIDTp0/DbrdDpVLBYDBg6NCh+Omnn3xcedMkimKjP2eloVYHD0FnMAAtWgDRUYAgAFZrnZ/LvRIWEREREQWugA4gGRkZtR5js9lw9OhRHD16tNLjDocDmZmZXJK1ETV2AJGOHYP000/AoUOAzQ6EhcGh1UAToisPH/XEAEJEREQU+AI6gGzevNmv11+yZAneeOMN5ObmomvXrli4cCEGDhxY63k///wz0tLS0K1bN2RlZXm/UB9p9ACybl35UCt9CBDfsvzBOi4wUJ2KS/GqVAH9o01ERETUbAX0XVpaWprfrv3555/jiSeewJIlSzBgwAAsXboUw4cPx6FDh9CmTZsazystLcW4ceNw/fXX4/z58z6s2PsaO4AIN90ESast7wHJzQPCwsonoTeQSqWCxWKBw+FgACEiIiIKULKbhO4rb775JiZOnIgHH3wQXbp0wcKFC5GYmIj33nvvkudNnjwZY8aMwdVXX+2jSn3H4XA06gR0ITkZwoMPQnjkEaB3L8BqhbqgEDCZGxRElEolnE4nV8IiIiIiCmAMINWw2+3YvXs3hg4dWunxoUOHYvv27TWe969//QtHjx7FSy+95O0S/cLpdDb6CliCIEBo3x7Cgw8C06bB3Klj+cTz3NqX3r2YQqGAJEmw2+2NWiMRERERNR5ZjlOx2+3417/+hR9++AHHjh2D0WgsX02pGoIgVJmgXpuCggKIooi4uLhKj8fFxSEvL6/ac/744w8899xz2Lp1a52H/9hstkrLxpaVlQEo72kIxHfx3RO86zIUy32MKIp1HroltmuLC7feilBBgHLLFuBQNmA2AzodJJcLqMPzuFwuWK3WgHz9auOuWY61N5bm/hqw/Wx/xT+bo+b+GrD98mh/oNcnB7ILILm5ubj++utx+PDhGkNHRZezCtbF50qSVO3ziaKIMWPGYPbs2ejYsWOdn3/evHmYPXt2lcc3b94s+928zWYzAODo0aP1a4sg4BgADBwIbfv2CNu9G6rSMpzPy4PLYKjTUxQWFta/4ACyceNGf5fgd839NWD72f7mrrm/Bmx/YLfffY9DDSdIdbmLDyBjxozBf/7zHyQnJ+OZZ55B79690aJFi0sGjbZt29brGna7HTqdDl988QVuv/12z+OPP/44srKykJmZWen4kpISREZGQqlUeh5zuVyQJAlKpRIbNmyodk+T6npAEhMTkZubi+jo6HrV7G2iKOLgwYMQBAFBQUG1Hm80GtG/f3/873//g16vr/M1jh07huTk5L9eS0kq7/moY6+SwWCATqdD586d63R8IHE4HNi4cSOGDBkCtVrt73L8orm/Bmw/29+c2w/wNWD75dH+srIyxMTEoLS0FGFhYf4uR5Zk1wPyww8/ICgoCJmZmWjVqpVXrqHRaNC3b19s3LixUgDZuHEjRo4cWeX4sLAw7N+/v9JjS5YswaZNm7Bq1SokJSVVex2tVgutVlvlcbVaHbD/8JRKZaWgdanj6nP8Ja9RjxWtNBoNnE4nlEqlV3Zs94VA/v77SnN/Ddh+tr85tx/ga8D2B3b7A7k2uZBdABFFEZ07d/Za+HCbMWMGxo4di379+uHqq6/G+++/j1OnTmHKlCkAgJkzZ+Ls2bP4+OOPoVAo0K1bt0rnx8bGIigoqMrjciWKIlwuV8Df1KtUKthsNjgcjmrDHRERERH5l+wCSI8ePXDq1CmvX2f06NEoLCzEnDlzkJubi27dumHdunWe4Vy5ubk+qSNQiKIISZICPoC4l+K12+0MIEREREQBKLDvJqvx9NNP4/Tp0/j888+9fq1p06bhxIkTsNls2L17NwYNGuT52ocffoiMjIwaz501a1aT2gXd5XLJogdEqVTC5XJxhQoiIiKiABXYd5PVGDFiBBYsWIAHH3wQTz75JA4ePOhZHpa8xz0E63JWFfMlBhAiIiKiwCS7AAKUr4SVnp6OhQsXokePHggJCfFMXL74o657ctCliaJYvmmgDAKIIAiVVhcjIiIiosAhu7vzI0eOID09Hbm5uXXaB0RmqwwHLPeywnKgVCphsVj8XQYRERERVUN2PSDPPPMMzp07h/79+2P9+vU4f/68Z35CTR90+dw9IHKgUqlgtVplE5iIiIiImhPZ9YBkZmZCr9fjhx9+4OYvPiSnHhCVSgWHwwGHwwGNRuPvcoiIiIioAtn1gLhcLnTq1Inhw8ecTqdsekDcS/FyIjoRERFR4JFdAOnbty/OnDnj7zKaHbvdHvBL8LoplUqIogi73e7vUoiIiIjoIvK4o6zgxRdfREFBARYtWuTvUpoVURRlE0DcPTXsASEiIiIKPLKbA5KUlIQ33ngDzz77LLZs2YIJEyagffv20Ol0NZ7Tpk0bH1bYNDkcDtkMwXJjDwgRERFR4JFdAGnXrh0EQYAkSfj666/x9ddfX/J4QRDgdDp9U1wTJUmSrHpAAC7FS0RERBSoZBdA2rRpI7t34uXOvZyxnAKISqWCxWKBJEn8eSEiIiIKILILICdOnPB3Cc2OKIpwuVxQq9X+LqXOVCoVnE4nRFGESiW7H3MiIiKiJks+b2mT37h7QOTUk8CVsIiIiIgCEwMI1UoURUiSJLshWO7NCImIiIgocMhubMqpU6fqfQ5Xwbo8cpwDwqV4iYiIiAKT7AKIexWsuuIqWJdPjkOw3DgEi4iIiCiwyC6AXGoVLJPJhIKCAgCAWq1GQkKCL0trskRRBADZBRCFQgGr1ervMoiIiIioAtkFkNpWwSorK8OyZcvw8ssvY8yYMXjllVd8U1gTJtfeD/dSvEREREQUOGQXQGoTFhaGJ598El27dsXNN9+Mzp07Y+zYsf4uS9bck9DlRqVSwW63QxRFKJVKf5dDRERERGjCq2DdeOONaNu2LRYtWuTvUmTP5XL5u4QGce8FwnkgRERERIGjyQYQAIiIiMDvv//u7zJkT66T+N17gXAlLCIiIqLA0WQDSH5+PrKzsxEUFOTvUmRPFEVZLcHrplAo4HK5GECIiIiIAoj87iprUVBQgO+//x7Dhw+H3W7HDTfc4O+SZM/hcMgygLhxCBYRERFR4JDdJPS6TiaWJAktW7bE//3f/3m5oqbP6XTKchUsgEvxEhEREQUa2QWQ2lZjCgkJQXJyMoYPH46nnnoKMTExPqqs6ZLrECygPLAygBAREREFDtkFELmuyCRXkiTJugdEpVLBarXC5XLJNkQRERERNSW8I6NLcrlckCRJtjfvKpUKoihyHggRERFRgJDnXSX5jCiKsu49cO8FwpWwiIiIiAKDPO8qyWdcLhdcLpdsh2C5l+JlDwgRERFRYAj4OSB1XfWqJoIgyHYjvUDgzSFYLlGCoIDXw40gCOwBISIiIgoQAR9Aalv1irzLPQSrsUOC3SIi+8cSBOmViE/VITRW3ajPfzGbzebV5yciIiKiugn4AHL69Ol6HV9UVIT58+fjs88+gyiKXqqq+XAPwWrsHhCnTYK1VITxggMlZ+2IaKVBXOcgeCNvqlQqmM3mxn9iIiIiIqq3gA8grVq1qtNxZWVlWLBgARYtWgSDwQBJknDLLbdg9uzZXq6waXMve1xbD4jocOB8ziHYjQZo9KEIadWmTs8fFKqE5AIKT9pQfNYGSaeFIcKB8JaKRut1UalUsNlssp5MT0RERNRUBHwAqY3BYMDChQvx1ltvobS0FJIkYfjw4Zg9ezb69evn7/JkTxTFOoWPg99/jaKTxwAJgACEJiRCVcebfZVWAaVGgNPmgqlAid9/KkVkK61naNblBhF3AHE4HNBqtZf1XERERER0eWQbQEwmExYtWoQ333wTxcXFkCQJQ4YMwZw5c9C/f39/l9dkuCehX8r5nEMoOnkMWn0YlGoNRIcdpWdOITUhts7XEQShPIgES1CqBBSetHmGZiV01SE0VtPgNiiVSjidTtjtdgYQIiIiIj+TXQAxm814++23MX/+fBQVFUGSJFx33XWYM2cOrrnmGn+X1+TUZed5u9EASIBSXR4SlGoNJEmCPqj+N/uCUN4jotICNqOI/CMWiE4JqUMuL4C4XC6uhEVEREQUAGQTQKxWK9599128/vrrKCgogCRJSEtLw+zZszFo0CB/l9dk1SWAaPShgACIDrunB0QQBBit9V95SpIAp80Fh7W8JyQ2JRgJXXUNKb0SQRC4FwgRERFRAAj4AGKz2fDee+/htddeQ35+PiRJwrXXXovZs2dj8ODB/i4voJw7dw7ff/89hg8fjoSEhEZ5TqfTWescjLiOqSg4mlNpDkh46zY4dC6/zteRJAlOmwuiRYAoSIhu23hzQNy4FC8RERGR/wV8AElOTkZeXh4kScI111yD2bNn4/rrr/d3WQFp3759+OGHH5CQkODTAKJUq9F1+G1VVsFyvjCnbtewuWC3uKBQAdoYEZ2vDkd4S22j7j3CpXiJiIiIAkPAB5Dc3NzyCcoqFfLz8zF16tR6nS8IAg4fPuyl6vyvpKQEZrMZgiBgx44dKCgowI4dO9CrVy9IkgSdToeIiIgGP7/T6azT0rVKtRoJXXt6PjcajXV6fqtBhEqjQHRbLeI6ByG3pLhRez3cuBQvERERUWAI+AAC/Dk8x+nEkSNH6n1uY9/IBpr58+cjLy8PTqcTRqMRKSkp2L9/P2bOnAmVSoWWLVti7ty5DX7+ugaQ+lJpBQSFKxGk13iGWrlcLuSVNvqlyq/HpXiJiIiIAkLAB5DNmzf7u4SANmrUKKxatQqHDh1Cq1atEBkZCZ1Oh7NnzyI1NRV33XXXZT1/XYZgNYQmWInuN0VBUPgmJHIpXiIiIqLAEPABJC0tzd8lBLQePXqgRYsWnh4Pm80GlUoFvV6PqVOnIj4+vsHPLUkSXC6X1wKCQum73in3UrxcCYuIiIjIvwI+gFDd5eTkICQkBCaTCdHR0Zf9fO5NCJvSnAnuBUJERETkXwwgTUBISAiSkpLQv39/XHHFFdi5cyfy8/MREhJyWc8riiJcLhfUanUjVepfCoUCFovF32UQERERNWsMIE1AWFgYXnjhBSiVSgiCgL59+0IURahUl/ftdblcXh2C5WtKpZIBhIiIiMjPms7YmmZOpVJ5goJ72eLL1dSGYLnnyIii6O9SiIiIiJqtpnFnSV7R1HpAVCoVnE4n54EQERER+REDCNWoKfaAuJfiJSIiIiL/aBp3luQV7gDSVHpAFAoFJEliACEiIiLyIwYQqpEoik0mfFTEAEJERETkP7JeBctms2H37t04e/YsLBYLxo0b5++SmhR3D0hTwpWwiIiIiPxLlj0gNpsNzz77LGJjYzFw4EDcc889eOCBByodM3HiRCQkJODw4cN+qlL+XC6Xv0todCqVChaLpckFKyIiIiK5kF0AsdvtGDp0KObPnw9JkpCeno6YmJgqx91xxx3Iy8vDqlWr/FBl09BUA4jdbofT6fR3KURERETNkuwCyOLFi7F161Zce+21yMnJwU8//YSOHTtWOW7IkCHQaDTYsGGDH6psGprifhlcCYuIiIjIv2QXQD799FOo1WqsXLkSLVu2rPE4jUaDlJQUnDx50ofVNS1Op7PJTUJXKpXcC4SIiIjIj2QXQHJyctChQwckJCTUemxoaCjOnz/vg6qaJqfT2WT2AHFzByr2gBARERH5h+zuLlUqVZ3fvS4sLERISIiXK2q6muoyvABgtVr9XQIRERFRsyS7ANKxY0ecOHECFy5cuORxR48exZEjR9C9e3cfVdb0iKLY5HpAgL9WwiIiIiIi35Pd3eVdd90Fh8OB6dOn17hKk91ux9SpUyEIAu65554GX2vJkiVISkpCUFAQ+vbti61bt9Z47JdffokhQ4agRYsWCAsLw9VXX43169c3+NqBoCnOAQH+CiBNcZUvIiIiokAnuwDy2GOPoUuXLli5ciUGDBiAf/7znygtLQUAbN68GYsXL0bv3r3x448/onfv3pgwYUKDrvP555/jiSeewAsvvIC9e/di4MCBGD58OE6dOlXt8Vu2bMGQIUOwbt067N69G4MHD8att96KvXv3Nrit/iRJElwuV5PsAVGr1VwJi4iIiMhPZLcTenBwMDZu3Ii7774bv/zyC3bs2OH52g033ACg/Ob5qquuwpdffgm1Wt2g67z55puYOHEiHnzwQQDAwoULsX79erz33nuYN29eleMXLlxY6fNXX30V33zzDdasWYPevXs3qAZ/cu+C3lR7QEwmE+x2O4KCgvxdDhEREVGzIrsAAgAJCQnYtm0bvvvuO3z55ZfYv38/SktLodfrkZqaijvuuAO33357g2+e7XY7du/ejeeee67S40OHDsX27dvr9BwulwsGgwFRUVENqsHfXC4XXC5XgwNcIFMoFBBFkT0gRERERH4gywAClC+nesstt+CWW25p9OcuKCiAKIqIi4ur9HhcXBzy8vLq9BwLFiyAyWTCqFGjajzGZrPBZrN5Pi8rKwMAOBwOv+9TYbfbIYoiVCpVgzYkdJ8jimKdz694jrdJkgSz2ez317kidy2BVJOvNffXgO1n+yv+2Rw199eA7ZdH+wO9PjmQXQApLi5GZGSkT651cQ9KXYckrVy5ErNmzcI333yD2NjYGo+bN28eZs+eXeXxzZs3Q6fT1b/gAGI2mwGUr0ZW37YcO3bMGyVVUVhYGJBzdDZu3OjvEvyuub8GbD/b39w199eA7Q/s9rvvcajhZBdAWrZsiWHDhmHMmDEYMWKEV27UY2JioFQqq/R25OfnV+kVudjnn3+OiRMn4osvvvDMSanJzJkzMWPGDM/nZWVlSExMxODBgxEdHd3wBjQCk8mE7Oxs6PV6KJXKep9vNBoBAO3bt4der6/TOaIo4tixY0hOTm7QNevDZDJBrVYjNTU1YOa5OBwObNy4EUOGDGmSQ9/qorm/Bmw/29+c2w/wNWD75dF+94gVajjZBRBJkrB27Vp899130Ol0GDFiBO655x4MHz4cKlXjNEej0aBv377YuHEjbr/9ds/jGzduxMiRI2s8b+XKlZgwYQJWrlyJm2++udbraLVaaLXaKo+r1Wq//8NTKBQQBAEqlapBK2G5A4RSqax3mGjIOfWl1Wo9Xaj+fq0vFgjff39r7q8B28/2N+f2A3wN2P7Abn8g1yYXsltj9fz58/jnP/+JQYMGwWKxYOXKlbjtttsQFxeHyZMnIyMjo1GuM2PGDHzwwQdYsWIFsrOzMX36dJw6dQpTpkwBUN57MW7cOM/xK1euxLhx47BgwQJcddVVyMvLQ15enmeJYLlxT0JvisvwAuUrYTkcDk5EJyIiIvIx2d1dRkZG4qGHHsLmzZtx+vRpLFiwAH379kVxcTGWLVuG66+/Hq1bt8ZTTz2FXbt2Nfg6o0ePxsKFCzFnzhz06tULW7Zswbp169C2bVsAQG5ubqU9QZYuXQqn04mHH34Y8fHxno/HH3/8stvsD019kz6lUgmXy1VpEQAiIiIi8j7ZDcGqKD4+HtOnT8f06dNx7NgxfPbZZ1i5ciWys7Px1ltv4a233kJKSgoOHz7coOefNm0apk2bVu3XPvzww0qfN1bPS6BoSAAxGo04ePAgunbt6oWKvIM9IERERES+JbsekJokJyfj73//Ow4ePIisrCwMGzYMkiThyJEj/i5NllwuV70nZ5vNZuzYsUM2q0MoFArZ1EpERETUVMi6B+Rix44dw8qVKz29INRw7p3QmzK1Wg2TydRkd3wnIiIiCkSyDyB5eXn4/PPPsXLlSuzcuRNA+UpZ8fHxGD16NMaMGePnCuWpqc8BAf6aiO5wOKDRaPxdDhEREVGzIMsAUlJSglWrVmHlypXYsmWL5936iIgI3HHHHRgzZgwGDx7Md7UvQ112IzcajZWGMF24cMHzZ0hICIDyXeUB1HkvEF9Sq9WwWCyw2+0MIEREREQ+IrsAMmLECGzYsAEOhwOSJCE4OBi33HILxowZg+HDh/NGspGIoljrErwHDx7Ejh07qjy+adMmz+Tu1atX49prr0X//v29UuflqLgSViAGJCIiIqKmSHYBZO3atVCpVBg6dCjGjBmD22+/nTePXuB0OmvtQeratSuSkpI8n1+4cAGbNm3Cddddh5CQECxbtgx33nknYmJivF3uZbFarf4ugYiIiKjZkF0AefvttzF69OiAv6mVu7r0gOj1+mrDX4sWLaDT6QAAMTExAR0QlUolLBaLv8sgIiIiajZkF0Aefvhhf5fQLIii2Czm0HAlLCIiIiLfajL7gFDjqssQrKbAvRIWNyQkIiIi8o2A7gGZMGECgPIdz1955ZVKj9WVIAhYvnx5o9fWlEmS1KCNCHU6Ha688krP8Cs5cPeA2Gw2aLVaf5dDRERE1OQFdAD58MMPAQCdO3f2BBD3Y3XFAFJ/7mWNa5sDcjG9Xu9Z7cpoNHqjtEanUCggSRJsNpu/SyEiIiJqFgI6gPzrX/8CAISHh1d5jLzH5XLB5XJBpbr0j4dLlCAoIPuhWoIgcCI6ERERkY8EdAC5//776/QYNa669IDYLSKyfyxBkF6J+FQdQmPVsg0iKpUKJpPJ32UQERERNQsBHUDIP9wB5FKBwmmTYC0VYbzgQMlZOyJaaWQbRNRqNaxWK5xOZ629PkRERER0eWS3CpZSqURaWlqdjh08eDBvKBvAPQSrLkEiKFQJpVpA4UkbsjeWICejFGXn7ZAkyQeVNg61Wg2Hw8F5IEREREQ+ILu7c0mS6nVzK6cb4UBR30noKq0CSo0A0S6h8KQNJWft0MUKaB3ToV6vv8lkwv79+5GQkICwsLCGll9vKpUKTqcTVqsVISEhPrsuERERUXMkux6Q+jCZTFCr1f4uQ3bqMgTrYoIgQKVVIDi8vEek9IwTfxv0JE78YoUhv257bJjNZhw4cABms7mhpV8Wq9Xql+sSERERNSdNNoAcPnwYBw4cQKtWrfxdiuw0JIC4uYOINkyAoFCg+IQDp/cF/gRvTkQnIiIi8o2AH4K1aNEiLFq0qNJju3btQnJyco3nWCwW5OfnAwBGjhzp1fqaooZsQugmSRJEuwSbSYLkciGynRqJPQN/WJN7Q0JRFKFUKv1dDhEREVGTFfABpKSkBCdOnPB8LggCrFZrpceqExoairvvvhtz5871boFNUEPmzbiDh93iglIlILy1Cp+uWIC7Zn6G0FBNtecYjcZKw60uXLjg+bPi/BOdTge9Xl/vmupDrVbDYrHAZrPJaid3IiIiIrkJ+ADyxBNPYPz48QDKb3KTk5NxxRVX4L///W+1xwuCgODgYLRo0cKHVTYtLperXsc7bS5P8Ihuq0V8qg6CzoYzBX9csifl4MGD2LFjh+dzd/DZvHlzpfOuvPJKzw7r3qJSqeBwOGC1WhlAiIiIiLwo4ANIeHh4pZ3Q77//fnTq1Alt27b1Y1VNm3sOSF1YDSJUGoUneLj3ATEaa5943rVrVyQlJXk+P3/+PFatWoXBgwcjLi7O87gvAoE78HBHdCIiIiLvCvgAcrF//etf/i6hyatLD4hKKyAoXIkgfcM3INTr9ZWGVrmv26JFC8TGxtav6EbAiehERERE3ie7AELeJ4pirWFCE6xE95uiICggu53Pa8KJ6ERERETeJ9sAcvz4cXz++efYt28fioqK4HA4qj1OEAT89NNPPq5O3uoSQABAoWwawcNNo9HAaDTCYrF4fdI7ERERUXMlywDyxhtv4IUXXoDT6fTcKFecs1Dxsaby7rwvVXxdfUmn06Fbt25+mwSuUqkgiiKsVisDCBEREZGXyG4jwnXr1uHZZ59FixYt8MEHH6Br164AgI0bN2LFihV4/PHHERISgqCgICxatAibNm3yc8XyU9cekEa9psOBspNHkahVoOzkUYg19Gh5myAIftuJnYj869y5c1i+fDnOnTvn71KIiJo02fWAvP322xAEAf/9738xYMAAz6T066+/3nPM3//+d9x555148cUXsXPnTn+VKluiKFbah8Pr13M4cPD7r1F44hjsdjssJ46g6PgRdB1+G5Rqtc/qAMrngZSVlbH3jKgZ2rdvH3744QckJCQgISHB3+UQETVZsusB2b17N+Lj4zFgwIAaj4mOjsbKlSthNpsxe/ZsH1bXNPi6B+R8ziEUnTwGbWgo1PowaENDUXTyGM7nHPJZDW4ajQZWqxV2e+3LCBOR/JWUlODcuXPIzc3Fjh07UFBQgB07diA3Nxfnzp1DSUmJv0skImpyZNcDUlZWhp49e3o+DwoK8jweFhbmeTw+Ph7dunXD5s2bfV6jnEmSBJfL5dMAYjcaAAlQqjWAzVH+p/Tn4z6mVqs9O7RrtVqfX5+IfGv+/PnIy8uD0+mE0WhESkoK9u/fj5kzZ0KlUqFly5aYO3dunZ7r3Llz+P777zF8+HD2oBARXYLsekBiY2NRVlZW6XMAOHz4cJVjjUYjCgsLfVZbU+AOIL4cgqXRhwICIDrKex1Ehx0Q/nzcx9zt5jwQouZh1KhRSEhIgNFoRKtWrTwfRqMRCQkJGDVqVJ2fyz2Ea9++fV6smIhI/mQXQNq3b19pgmD//v0hSRLee++9Ssf99NNPOHLkCFq1auXrEmXNvQu6L3tA4jqmIqptMmwGAxzGMtgMBkS1TUZcx1Sf1VCRSqWCweD73hci8r0ePXpg6tSp0Ov1UKlUsNlsUKlU0Ov1mDp1Knr06HHJ8zmEi4io/mQ3BOvGG2/Eli1bsHPnTlxxxRUYM2YMXnrpJXz00UfIycnB1VdfjfPnz+O///0vBEHA2LFj/V2yrPgjgCjVanQdfhtyfz+AM8ePoXVSMuI7d/P5BHQ3rVYLk8kEu90OjUbjlxqIyPdycnIQEhICk8mE6OjoOp3TmEO4iIiaC9kFkFGjRuHIkSMoKioCAMTExODzzz/HPffcg+3bt2P79u2eY++66y78/e9/91epsuRyuXw+BwQoDyHxqT1gVAcjvkMHv+5ErtFoYDabYTabGUCImoGQkBAkJSWhf//+uOKKK7Bz507k5+cjJCSk1nNHjRqFVatW4dChQ2jVqhUiIyOh0+lw9uxZpKam4q677vJBC4iI5EV2ASQpKQnLli2r9NjQoUNx/PhxfP/99zhx4gSCg4MxcOBA9OnTx09Vype7B8SXc0ACjUKhgCRJMJlMiIiI8Hc5RORlYWFheOGFF6BUKiEIAvr27QtRFKFS1f5fZI8ePdCiRQtPj8fFQ7ji4+N90AIiInmRXQCpSXh4OO655x5/lyF7/uoBCTRqtRqlpaVISEho9q8FUXNQMWwIglCn8HGxhgzhIiJqjppMAKHGIUkSADT7m26tVguz2QybzeZZ6pmIqDqXM4SLiKg5YgChStgDUk6j0cBoNMJkMjGAENElXc4QLiKi5iigfzs2xkRkQRDgdDoboZrmweVyAWAPiCAIEAQBRqORQymIqFaNMYSLiKi5COiZxpIkXfaH+4aa6qbRXy9JgiTTAKjValFSUgJRFP1dChEREVGTEdBv0TA8+F6jveaShC5aLdQf/xuSwQBMmwohLKxxnttHgoKCUFZWBpPJhDCZ1U5EREQUqAI6gJDvXe4mhJIkAceOQf3DerzcMh7KrCxAHwKYTIDMbuKVSiVEUYTBYGAAISIiImokDCBUiXsfkPpyBw9p0ybg0CEoLVaYXC5IMTGA1eKFSn1Do9GguLiYy/ESERERNRLZBhC73Y4vvvgCmZmZOHv2LKxWK3766SfP13/55RcYDAZcf/31ft1VW27qOwTr4uABmx0ID4MUFg7jH394qUrfCQ4Ohtlshslkgl6v93c5RERERLInywDy66+/YvTo0Thz5kyN+1Z88803eOONN7Bu3ToMGzbMH2XKkiiKdX6nXzp2DNJPP1UKHoiKAgQBcDaNidtqtRoOhwNlZWUMIIBnYYeKCz24H3f/3AiCAIVC4fmTiIiIqCLZBZBjx47hxhtvRFlZGe68806MGDECr7/+Og4dOlTpuPvuuw+vv/46Vq9ezQBSD/UKIOvWAXuzyud4xLcsDx5+IjocOJ9zCHajARp9KOI6pkKpVl/280qSBI1CgaKiIrRs2bLeN9SSJAFOJ4QG1nK559f2HKLogkIhwOVyweFwwOFwwOl0ej4cDgfsdjscDgdEUYTT6awSPqrjfp2USiVUSiWUggCtTgeNRgOVSgWVSgW1Wu35YC8lERFR8yG7ADJ37lyUlZXhlVdewcyZMwEA77//fpXjunXrhqioKOzcudPXJcpafQKIcNNNkLTa8h6Q3LzyHhCdzmdBpMxRBrNohsvpxKkNm2A8fQaABEDAqcP70GbodVCoVNApdQhTV51E7j6/WpIE1fHTCMr8BZqiMpjG3g9jmzaVJqMXW4thtBtrOF2C6/AROL7bCGVhCdq8/CpUkZF1bpskSbAeOoTSr7+G83w+Ws6eVa/za3oORXg4rFYrbDYbyopM+OXrE3Bp7AhJdkAVIUIUnZBcFYKFUB4mQlQhCNeEe3o13D0cNV1XkiRILhecOTnAlq1wFhWh5P5xECvsDK1QKGCWzLALdmi1Wuh0OiiVShSKhThaeBQ6nQ4Cyq+h1+gRGVS1/Zf6HlRU0/lERETke7ILIBs3bkR4eDiee+65Wo9t164dTp486YOqmo56BZDkZCApqfIckNKy8iCi0Xq1TqfLifePv4/z1vOIOSOh3VEJ9iDApQIUTkBztBCZW35DQWsBcUFxeCLlCagUqmrPr0SSkJBrQ9+9ZUg6aYFkdcEZrIXaWIaSkhJPAHG4HJjz88s4YzoNCJXPjz9rRa/dxWh7zIwgqwgxJAgtS4vrFiD+DA2mtWth3rUbLqMRCr0eLoMBqGMAqRg8TDt3QTQYAF0wju3fD3NYmKenw1zmxKm884BDCedJG4ojzuJcfDYMoRcqtwmo9jW81PUr/UyYzECIDhq1GkKFTR3tTjuWHVmG89bzkPBnj4oEOJ1OrM5YDUEhQKlQQqFUoLW+NV5Pex3BmmDP+Q6XA3N+mYMzxjO11uQ+X624/F4xqpnBYMDu3bvRt29fhIaG+rscIiIKULILIBcuXEC3bt3qdJOsVCphNNb+7ij9pT4BBPhz7k379kBycqWbTqG4BHovjv9XCkpEqaNw3HQcensYFHBAUCugBAA1oLC6oLercUosQ5Q6CkpBWeP5MZoYKJwS2h20oM1RM1oUWBBjtMKsV8OodSDGoUSwNhiFhYWIj48vnxdicqHtjquhcMXDlnIelrAixJ41oeuOfLQ+aoDKIcKsV6NQK6GFS1Xl+hdzh4YWa9Ygv7AIsNmgjIqCMjS0PEDUgSRJsBw8iIIvVsG6ZzdEswWiXg9XaCgEsxmWklKo9HoEBwcjNDQUQQon1IoilAQVQQMtYouSEVPaBqURechvlQNTaCEkQUKBvaDa17C661e3IAFC/lyG+SJqpRox2hictJxEjCYGAgRIkgSzaEaQOujPXhQJhbZCtFG0QfaBbOj1eoSGhkKn0yEoKAixulj8XvQ7EvQJNdZ1zngOsbpYqATZ/bqTHaPRiIyMDHTq1IkBhIiIaiS7/5EjIiJw9uzZOh179OhRxMXFebmipqW+AcTt4iAi/rAeIcePQygoKJ8j0sgEQUBaTDqyy7Jh1wKCoIDSKUBSCRCcEgRBAbsW0Cl1SI9Nr9ImQRCQHpuO7LJDiDtlRMeddsAqQJRUyNWHoTgkGFFOA1R2JfTqUGiDglFssaCkpAQtWrSAwyoi0h4HZ4kKioI2CLecQOvT26E3lsKi18IcEQRREqG0qRCujrjkcKWKvRW6ggIo2iRCGRcHQRDgstS+hLHT6UTx7t0o+epr2LOyIFmtcIXqIcTEQKFUQm23AyolwsJCIVQYAiUIAvQqPQyuEohKG+wqJ5RONaKKEhFRGg9DZD7OtjwIXYi52tewYhuqDR7uBQms1hq/h+mx6cg2ZMMluaBT6SBJEpyCE8HKYAiCALPTjFAhFEMShkChUKCkpAQXLlyAQqGARqNBT1VP/E/4H6x2KyJUYQg5Y4XSIkIMVsLSJhhlLhP0Gj1GpozkMspUK/bgEBH5huwCyJVXXonvvvsOW7duxcCBA2s87uuvv0ZRURGGDx/uw+rkTxTFy1q5yB1EHOPG4sX3l+I/I0ZAYTCUvwveiOwWEcaMcFztuh1Z4ZsQ1cKMkAtOlM8BAUwtVDgZa0SP0F5I0iVV+xzt8oD7N4pwnSpEfkgElHABCgEuQYJFUMMgKNFapYHWqYGgEKBSqXDhwgVE/zmMSOMEIixlEMx2SMo2OB2XAG30Keht+6ARz8Eu2tFCE4YgBFV7fWt2Nkq+/BLmXbshWa1QREbAERMNRWhorTfLkiTBbDajcNculH39NXDwEGC3AeERUERFQams8D28xFNpFBqEIAQlUjEUCiVEtQOiygGlU43wCwkIKoxEh1gbYlq2Bqr5FlZcCU202ZEfoYctPARahQKxAGqbWp6kS0KX0C7IKs1CsDK40tckSUKpsxS9wnshJTQFgiAgOLj8GJfLBbvdjmhrNNoq2iK75CASD1kQWuAsnzciCNCeNuNUDxOuShyALlFdaqmEiD04RES+IrsA8vDDD2Pt2rWYMGECVq9ejR49elQ5ZsuWLXjooYcgCAIefvhhP1QpT+7lVRvlnWJBQLbNBse4sdAEB0NQNe6PmtMmwVoqIsqaiF75N6Ms/CxKUn6HKJTBGazA+Tgn1IL2ku/c4/t16HioGAfDVBCVApR/3qkrADgBuBRqRCrCAbF8SeGQkBCUlZWhrKwMAjQQi4oRbHTACSscSjsgBMOsSYFV0xYa+wkEW3YhWq0GLNUvSVzwyUqYf94KVVgY1G3aQIIE1NLjIYoiSktLUVBQgNLSUqg++QSag4cghIZCaN263gsACBAQoYlAmaMULkksH2YlAKLaAbvSCrUtBJHn2+DMbyakDtFUOd+9EpqoD8GhFmEokpyAywa4gAKFA6lK3SVDiOQC0lqU94JYREulEGIRLdAqqv8eKhQKBAUFISgoCDeqb4Qh8yhCLjhgD1LApRKgcErQnDMhKgK4otMVuHDhgud4tVrN3pBGYjAYKg1zzc3NrfSnm3voXF2eb//+/Rg4cCCioqIapcbGWEmurtiDQkRUN7ILIMOGDcNjjz2GxYsXo1+/fujTpw+OHz8OABg3bhwOHDiAffv2QZIkzJw5E1dddZWfK5YP9+pFjXpzJgiNHj4qCg0PgtGsQnhRGyhUbWCIykdB2BGUuA6hV0TNvR8AIN14E5RqLYKz/wel6AIglfeAAJAECXqFGsEIAlA+f0H1ZzvOnz+PuMhEqKIiIShFuEryoLE54VJbIChskBRaWNQpcGqScUIqRivHvirXthjt2Bc5DMp+nRB3cgtCT52CMjICqGFpW6fTiZL8fJw/fx4Gg6F8ZaqQEKjvuANSePhlrUQWrAxGqEuPUmcZFIISggQonGoobTpoNWrEJ4WgVdfqe7DcK6Hl5xxCkcOKIIUCSqUKogQUuZzIVzgQX8N17RYR2T+WQKuPRI+IK7FT3IogRXlvUcXej0t9D4HyXpQ2aAkXcgG1CgoAUAtwWRxo7WoJnUGHI4YjUCgUUKvVnhW3goODodFoPEsDu5cDru/Pv/vfjcvlqvJRccniiksXC4IAQRAguSQoVUqoVCoolcpLLm0ciHbv3o2MjIwqj3/77beVPk9PT0d6enqtz2c0GnHgwAEYjcYGBZCKAUCv11/2SnL1xR4UIqK6kV0AAYCFCxeiS5cumDVrFnbs2OF5/JNPPgEAxMTEYM6cOZgyZYq/SpQl902TyouBwRui9OE4IZyERgxCeEECQopiEBreGldf2bXGc+wWEdnZ4dB2vAuK1FSImz6FZFNBcAEuBRDksqOtOhK4qPNCr9ejuLgYOlUEhKAgaCLbQTKHovjUH9CZXdA4RYhKM6AwQ6mJQx4S4Qx2IbXK9Z0w2tSwByWhuFMiIq2nEXsiE6qC03DpdBBCw8rngEjl+3P88ccfMOr10Gg0iIiI+GvfjEutRFaPIBKtjYbBaYTgUELrCIFTYUdR9Clcc2VXdGpT8xwW90po9nXfALv/B6XVBjhtUKpUgEKATXLVeE13L5bxggNtVVfBHhyMC62OAGozLK6aez+q1CAI6BLXE4cP5kFyOCGoVeV/Cgp0S+jtGTIniiIcDgdsNhuMRiNcrvLaFAoFlEollEolFAqFJwyoVKoqmym6Q4XL5YIoipX+rBhEagoeldpvlXD6VwfUIQrEdtRA30LlaeuJEyeg1+uh1WoRFBQErVbrk71S6vsOft++fdGpUyfP57m5ufj2228xYsQIxMf/FT19tYmn0WhExubNaC8IMG3bVutKco3dg0NERHUjrzvNCiZPnowJEybgl19+wf79+1FaWgq9Xo/U1FQMHDgQWq13l4Ftitw3TnLbvVqn1CFUpUcpyiCpRIgOIKGkA0q36pDTqhQJXXUIja08fKjiza9SkwJT93tQXLIe7c+VIiq/DK0sIkKjI6v8C1H/OYzjwoULAMqnV+gjY5GHMpSUFiCqDFBZFBCEUCglCS1cp9DKsh/AyGprD40KgsslodCQjKLOraGMPIgOxVkIPXUSCA2F3SnCZbdDFEVERUVV+72paSUyTxCpw42rxhmESFssTDCiNPosDsfuQFKreHRuc/MlA4BLlCAoAG27JAjHDkNUqqEsKYFoNAIuCVqnAqhl6dugUCUklwIJJR0QXhIPQ+h5HG21B11aJdfa++HWrXs6cn7fAeW5IqisLjjhgpAQhW7d0z3HuENGlTb8GSLcH1ar9ZLBwd17cfGHu/ek4k7wFT8uZip2wGkpgrVEgvmCHeHxLkSnqCBJ5T9f7p8xd+9MxRXAdDodVCqVZyPJxuq1rO87+KGhodUeFx8fXymA+IIkSXDm5KD3nr0w794DlSjWupJcY/fgXC5vDEEjIgpEsg0gQPnN4KBBgzBo0KBqv26327FixQr2hNRRo84B8Smh/B180QiHZAfUAsLCggELkH/EAtEpVTt/AXDf/AJRJUmAeBeOdDoNR9ffMPpcMHDkDFBUvodFRaGhocg/UwynUwEtVBAAxOnicNRkQak+CMpgB1IEE9qc2QF9yXEoa3n3VxusgiZICZtFjQJzBxyK6YxQw3G0OJGJsLITUIXoodbpINQSDGsMIqaqbajIahCh0igQ3TYIO3XfoFR/HgqFAulx917yZ8E9hCpIr0RcxxREtUlG0aljkPQhELQaRDldiM0rBkwll7w+AKi0SoRFBsNgKEFESWv0NrREoiUahhAHQmNrn7Oh0mjQ55ZRWP3z+1BbRTiCFLhzwCioNNV/3ytyb6yo9sEcgYoEQYAAAcFhCkguoOSME2V5Tkg6LeIjQhDesvxNFPeO9EVFRcjPz4dSqYRWq8X/t3fn4VEV6eLHv6e3dHd2EkgChLAY9kUhskVFRGBwrjq4MYsbLjOIzqCMznXUO+gsj/PMwqBXcR/UO4A7XL0/FHABZHGEEAUMgQRICJCFrJ1Od9Jb/f4I3ZKNdLYOCe/nefJATtfpU1V9unLeU3WqTDoLOVvtRPWxMOaygfRLiepx393GPRBFRUWBf8/+PM7VA3H2THKOXV+RWFyMNngwxj59Wp1JrqM9OJ3dg9LRIWhCCNFT9OgApCUOh4MXXniB5cuXU1RUJAFIkLrkGZAQseqtROojqHBV0keLB7sJzaDR7yIL/ce0dvGrI9pkxm4z0KcsBbMplZJRieinVhCR8RlaeXmDWbzq70ibcLudeH0mfE6Fr1pPlBZNXmwWCZeY+Y8fPIAre2pg/LmulYsPTdMwmDT0VoVHp3HaOpTK0YOIcRwnyZFFVBtmEWs2ECkrbzITmSFMwxytxxxhImm0lYi+8RzIj+dkxRGmRE9ptffh7F6kypMuohJnkjxxKDq9k7DISPqljkJfUNDi8Ruz6kyY6wpx1JURbuiH60Q/DpZUEjPA1GwvVmPDolLpO2o0/674N1NipzAsKjW4CusAfw9QR78zhjAdepOGp85HTame7M+qiB0QRtJoK5H9jBiNRqzW+vPY6/XicrkoLS6nvLCO0oJqjmeX0m9IJCOnJpI8vG/Ig6n2atwD4T0z4cNHH33UoLeqpR6Isj0ZVH7wPp59+6GuDrfVSnVEBOEGA5qrDgDlqkPna34iiI724HS0B6Wze7Cg7cPoGudBHqQXodQV34GedPwLWY8JQKqqqti0aRN5eXlYrVYuvvhi0tPTG6Sx2+0sX76cZ599loqKCpRS9O/f8gJloqGe9gDs2ZSCWC0evctChDmc+EHmwMVbMA2LpunoExFDiaGEKF0fyo+7qDJEEJ16E/1Hmut7VM5itVrxeWuoOl1DeJSFQaPjSB0dTlnVHq4ffT16vR7LmDGYR49udQYepRR1Lhe1zlo0DUwWA2arjjq7ntO+YfiGjyb6zArsbdEgEPF6m0wGYLLoGXdNnwYX0DP7zaTOV8fMfjODbpD9vUgVJ7zoDcnEDDARN8SK3mhEO8fxG9SBz0Plic0Yqo9j9bnR64pweSrRx1xFSa73nL1YZ5e3Pflvr7N7gNpyrrVE07T6QMSi0Bs0yvLrqDzpahKA6fV6LBYLKtqIwVCOzgpej49Thyo5lVOB2/gVE64czPAJg4iMjDzncNTOvoMfERHBlVdeGfQzH417IAoKCli+fDnXXnstycnJDd63OXkvrETtzcRlMuGwWqG6GjSNouLiQBq9x0NcFw3J7UgPitPuYsvqQ0TEhDFyWhLxyZ3znExbhtE1lwd5kF6ESld9BzpyfAlEQqdHBCCrV6/m/vvvp7rRON7LLruMDz/8kOjoaNasWcOSJUsoLy9HKcWoUaN4+OGHufXWW7sp1yJUPHU+XE4fRkMYw1Ij230xaNVbGRw+GABlVtTZvZzOrcXngdFJDQMQo1lHeB8TGD2Mnh7LmLRh6HQ6JtNwWmhN0+AcwYfX66Guxo3L7UanaSgFPhfU1XrRB9mD0xpN06CFi3+dvmEdDQkfwn3D7mvzMfx38L0u1eDCOfBZtDKxgbMqhzp7AQZjJDqloSkftbYCDKYjJIwcH3QdtDf/7dG4B6hBedvxR0z5PNSUZ2OrLEaLScAaOwKXo/VhhDpNw2g1EmYx4LTXUVWi48DGMgr2V5M0ykK/lChiY2MJDw/HarU2eI6os5+BiIyMbNOzEo17INxuNwCJiYlB9UAMvm9xoAck7kwPSJHNRmJiImHm+qBD1daicziCzlNbdKQHxeX0UFFcQ3FeJfkHTxM/yEpYYv2inW0ZgtYRLqcHW6mT0oJqTuVW0v+iGOJSDf7llNqloz0oHX0OpjOO3509QD29/G3Zv7nzL2m0lf37QlP+5o6fPD6KY0UHSUtLkwC8i533AciePXu488478Xq9hIeHM3z4cBwOB0eOHGH79u0sXryYtLQ0Hn74YZRSTJ06lUcffZTrrruuw8deuXIlf/3rXyksLGTMmDGsWLHinIsfbt26laVLl/Ldd9/Rv39/fvOb38jwry72/fMLYZ1yF1ophdelcDl95wwATBY9438YR52rFruzlMJCK/379w/62C6XC5fLRZ3Hg6YHg96A16XwOjW8muq08oRS/R18rdlApLUhVD5PzZkZiA0orw9Nb0RvhH6piuFXRp/XdeDvASo9VkNx9j7CIuqIH9qHlEvHBfUMCvh7gDZRazuOx+3G5szBUZFPVMLV9LvIGlwAprx4anPw1p1CuZKwF6ZytNRJcXYtMUNPE51QP6NWbGwsERERWK3WTp3FyuNycXTv19RUVRIeHcPQiZODLn97xaVNos+kiYFnQKp2fUWk3Y7J4yHMdGYmOZ/CW1sXVP5Lsr9jdHw0Jdnf0Tcursvz73Q4qHJUoNk1yk6bUHgZap7Gxx98gQpzBhYR7eqH4P2TYeQfKObQvw8TbveS9cVO4m/8D4xt7D3qaA9KR5+D6Yzjd2cPUE8vf3v2959/x7PKyMsqwZEfyYncUmIvjW1z29/R4+cfPE1hVQEJ0SmMukR6RLrSeR+APPPMM3i9Xm6++WZeffXVwAmVk5PD/Pnzeeedd1i3bh1xcXG88sorXH9987MNtdXbb7/Ngw8+yMqVK0lPT+ell15i3rx5ZGVlMWjQoCbpjx07xjXXXMO9997Lv/71L3bs2MHixYvp27cvN954Y6fkSXyv8fMLnR14BBMA6PTfr8ydn5+Py+ViwIABmM5x0eJyuSgrKyMv9xRulxujRY/Op6O2xofOAGHxXkZOiyY6MazHNnxnByJ1dm+rd/ABUFaUD3xeNzqTDkukwufSE5XU8hTAnc3rdlN8OAuXvRpTRCQJw0ejD/JZCr3RR13159RVF2AvVZTna5zcn834a39EdH9rq2VwVuVQV12Apg9H5wNND8p7kr7DChk6fWKr+wcCmOrj6NxunOXHCIs4gSXmKqoKdBj0ZpKGWKmtraWgoACAsLAwwsPDiYqKCqyL4h+G2dZZrDwuF1+88TInDn5H/e1zjfz93zDzjp8HfRHvcbk4sW8v/VT9v/0TE4PaV9O0wHBH15atHFz+d6IdDupsNnR9+oBOh/J6sdls6M70kDeeLtnrdrPn/bWUHM0BFF8fziLv271MuuHHGEymBjOZNZ7hzP+7TqfD4XDgdrupra3F5XI1Oyva2SxWKxExVgwmHT6vm4pTB4i1VxPl6EvysJkMnhRPTKK52Qspfxn8i6P6fy8sLMTlcpGbmxvYrpTCYrEQERHRYIa36rI66urqcHlr0em92Eo/pa66AJ3Xx74N+Rz5dyajr7mWqCQLkZGRREVFNSnz2T96vT4wvXV7tPcc6C0u5PL7J2OprnQQa0zm2/9XQtUxQjY0yn98u82JydWHvR8WUpbjkaFZXei8D0B27NiBxWLh5ZdfbtAIp6amsmLFCubMmYPP5+Ozzz5j2rRpnXbc5cuXc/fdd3PPPfcA9WuPbNy4kRdeeIGnn366SfoXX3yRQYMGsWLFCgBGjRrFnj17+Nvf/iYBSBdo7vmF9vIP4Qo28GjMYrGg1+s5deoUNpuNvn37EhUVhenMhYvH46G2thabzUZZWRlOpxN8RvQGPe4ahcFU3+ORMNJMYWVFj+r1aE6wvUh+tdVeDOZhRPQ9jttZgMfjxltnIm7wUBKGN15BpWt43W6++3g95flH/dfPlB45zJh5PwoqCHFW5eCqKUBvikCnM+LzuLCfzmffhxmBIWTn6gFyO+34fAqd3ojbZyOyTxTKVYfe4DznueD1efG5fbgrc6itPg46C0pvRqFRW3Uc9IeJHTqCuOH1s3z5h/X4fD5cLhc2m43y8nI0TcNkMmGz2aisrOT06dOBhRqNRmNgTZSWHN37NScOfkd4TCzGsDDcdXWcOPgdR/d+zfCpl7Vaf/4AJv/APpJNOrI2/T9sJ/JJ/8mdaHp9YIrkxlMmu91uPB5P4KfI7eLjpCSiJk8mbt9+9IcOgcOBslgozc3FZ7MBTduM0sNZnDz0HUZrBHqjEa/bzclD36H7YjNxqaOa7NP4eTl/cOFwOEhOTiY/P5/y8nKAwJC3sy/YNU2j1ubD43aDTkPho7KgvgdMud04yo0c+fdxTuddTWyylcTRFiLiDfXfLa+3QRCxe/du9uzZ0yBfSineeOONBvm85JJLmDhxYoN811XXBzB2RyW489DXHkVpZtCF1Qc3JXnseutL7AYrfYcbmXTZ2CaLaTYuV2lpKcXFxRw+fBibzRY4f/zr6/gDlcb/+jwevlz9T/IP7KMfbg5s/D9qCk+0KYjtyfzfgWP7vrkgyw/155TRrMPpq8JgTOR4VllgaNTI6Un0Te7aHqn64+vx6p0YTHEhP/6F5rwPQAoLCxk+fDjR0dFNXpsyZQoAQ4cO7dTgw+VykZGRwaOPPtpg+5w5c9i5c2ez++zatYs5c+Y02DZ37lxee+013G53j5mVBurHYXfkLhbU16H/X///W+M/ptvtDsyG06ogkzXmdnvxKR9Om0Jv0ohJNpEwMoyIeAOa9v1Y9LaIjIykpqaGnJwczGZzYEFHn69+MUG3243FYiEqKgq304c50oUpQh84rlIKraqN5e9G/jr0KR2a8gUCD7dToTPQpE4bnwdK8xEWqREZUZ/OEnM9pw9nU1iQT1JyCv1GjMKrFN4gz5+OKDq4n7K8I5giItEbTXjdLsryjnAyax+Jo8a1Wn6v245SoOkMKBSawYjmBY/bTnGuE3edl+FXRTbZ3+P1UFuh8PrC0PSghTlwOCqIcOnRPB7sLjcnT57EarUS3mgWMbfbi9PpxOaoRKs9hc7tBr0FHXq8PvD5XJRV72XfoW+5NPpSYpMubbC/TqcL9OAppXC73djtdqqqqsjNzcVutze4cPQvzui/oDz7zndhwXE8Hg8+TaPO5YIzgXdRQQFRg4ua9Dr4Fz31er14PB5O7s/kyDcZmMIjiYjvBwY9x/Zl4ouIoc9FI5rsd3YZzr74NRqNTJw0CcPw4XgvuQSOH0e/dRu6igrC+/aFFoZklPu8aJoO05n60BsMeJwOdD5vUMM4/OUzm81MmTKlQYDg8XiarCujlKLWVl92pQNX5eH6AFJvQXlNaAY93roCHLbD1B1OpcZey+D0+ovQxuvLjBgxgkGDBgUCpPLycrZu3crMmTPp27dvII/NnUMGnxer1U14pIU6WzG1HiMYwnG7XRhNFvC4MZp1RJlHEq3TNxmK5/P5sNvtgYkMlFKUlJTgdrs5duwYlZWVgc/ObDYTHh7epOfE6XRSW1tLdf5RSjJ3owxG6tBR51Mc3vM1dr2JuItGEhkZSXR0dIPeF03TqKmpwel0BuqjpKSEmpoasrKyKCsrC2z39/b569DPbrejlAq01ydPnqSuro7Dhw9TVVUVKFd4eDiRkZFNPseWfm9pYVL/Oew///31V3HkMKf2fB0ovy7MTN7+b8n4bBODLp7U4nNAHZ1Iorv393p91LlceKkP1Gvr6odLejU35igzTpubnIwiHDW1zL1rfJP9O/v4dbW1oIEPN2FRYa0eX7TfeR+A1NXVNRt8AIGTKTExsVOPWVpaitfrJSEhocH2hISEwDz1jRUVFTWb3uPxUFpa2uxwhrq6+u5vP9uZu3P+i9VQ8/l8mEymBnlqL+eZufedTmfQCxv6LywcDkeXL4bo9ipM4WDsqyPuIgPWOA1Nc+N0dqzedTodZrMZqF+/wc9/AaeUwnHmgdhBl9dfmPuPG8ryd4Zap69+fL3Xi9fDmcBDIzIp+Do9uw5cbohMGYrTEkFkv37UudzgCs33wF5Rjs+nQFd/tx1d/VASe0V54PNqLFB+nxd09ReuPq8bTWfA53GjvApNbyUmWUefVJq8j9urcHqqKKk+RYX3CFFeJ5bKKsLwYSsrxWkw8e2u3aiv9jBx4kQmTZrU5PgmUxjxlnjc1Qk4y46BBi5fHZZw0GEk+eKxRKUMw2KxtFiOs4WHh3PppZcSExMTOF8bt0eNh+BomkadV+HxenBUVwcCOI/XQ53PR3FxcYMLtMarxgPYysvO1H/9ea87c+y6murAIo/B8M+QCOD2eHD37w8/XgBeb/1EDC3VgcGIUgpXbW2gB0QpBQZjUPUWLP+Fb33dAZoHdKC89cfQdEbAi6YZ8fmcKJ+D2BQD8amGJm3C2UGPv80BAr1BERERTQKOxmWpdfoADZ1Bw2CKAE1DU57657F8HpQP9MZw+gyuz0NzdfHtt9+yd+/eJtu3b9/e4PfmzmGAgwcPsnfvXmJdNcS6HLh09Z91WUUFJp+XvC1fULHzayZOnEhaWlqTACwjI4OMjIwG9Qvw3nvvNaj3Sy+9lMmTJzc5/u7du/nmm28C1xMOh4Pa2lrefvvtBun8+7e0QGnjIMT/f/853jgw8cvIyGhQfre+/rLsdFk5ek8dmzb8H66d/2bGjBnMmDGjyXH//e9/s3Xr1ibb161b1+D383F/j9uDw1GD7XQFSjtzY+FM3ZQUlqJTJsCHy1RJv6gBzV4XdfrxARQUnTp9zuN3xzVab3PeByDB6KrhKo3ft7U1MppL39x2v6effpqnnnqqyfYvvvgiMOd/T+X/Q1VcXNzmspSUlHRFlpqwjgQ0qPZAdXGryUMmVOXvKE+NhsdjweXU0BkVplgv4QPcGKN8Ha7TUNeBw1U/lMdpr0FnMODzePB6vDhc7hZvOvjL70WhmQaiD0vC4zx55u+nhik6iT6X9MMYW4HNDbZm3qbPxbVYai0M1saivKOoOJZLfu5hUoYNJ2nIRQw7c+FtsVia5MNTo+HzWfDVaejChmCKzsftKMDjqsbnicCaNABz4gA8Hg/V1dVNZhFsyYABA9qUHsBnMmOIicNe8n0eLf0SsRvNOPLyWt0/UP81DnQGA84aR6v135l84VEY+8TjbJR/V3hUlx3/7PPHq0won0J53Bj1Yfg8btArwgfpMKa0fP40p7y8HLvdTklJSYObIK3lwX8Oux0n0fl8+Dw6TNH9Wz+H+/RpMCV+RUUFX3/9NZMnTyY2Njawvblz+Oz9XUUncORkEabTU1ldTaTVis7nJS51NKbEgVgsliZ3taH+RqR/NERrx8/NzW2yv9lsZsKECe3ev6NaKr9Jr0OnmYjuPwBT4kBKS0vZsGFDk/2dTidDhw5tNf/n4/71518YZrMFTa9QCjx1Xiw6I0a9CVOMB0PfGjSrD7sndMevq/Fitp77+J15Y+JC1SMCkJKSEt588812v3777be36Xjx8fHo9fomjWVJSUmTXg6/xMTEZtMbDAbi4uKa3ee3v/0tS5cuDfxus9lITk5m5syZLe7TU/h7c+bMmRPo9m6N2+1m8+bNzJ49u0cNWessPa38tXY3X9pysEaHMWJKAnEDwzt8M6C76sDjcrHtX69xMjsLlBcMOgakTeaKW+9ucfy17bSTzUcPYrIYUD5FmPZDPHW5hMf4SBk7kHGz0ts8g9Dx48d5/PHHWXLXvc1OdnG2xvUf3e9yvtnyKZ9t/IQpc3/AJTNnh3TsuGfuDzj2zR4cVZVYo2MYcnFamx5A3/av1zh58DvsdhsR4eGt1n9n60j+2+Ps88cbHclpRxHu2gKUVoM1ysKgsWnMuO2eNuehsLCQo0ePMmvWrFYnEmjuHK6tOURlTT7jrhhP+o/mtfkcLiwspKKigptuuqnNExls+9dr5O3/Fmd1FRHmMAaPm9Dmc6C9x++s/durt5S/Lfs3Pv+c1W58YR6yK/dy04LZjE27qM1/Uzp6fGX2UqgdYcZPpjHy4sEtHt9/jSPar0cEIDk5OSxcuLDZ1zRNa/X1tgYgJpOJSZMmsXnzZubPnx/Yvnnz5hZn2Zo2bRofffRRg22bNm0iLS2txQupsLCwZhcJO/th0Z7Kn//2lKU3lL8jekr5jbFG5t47rktWkQ11HRiNRmYtXNSmaWQNRnf9GPSKOkwWA4PHJTBy2sUdmjGlLd+b5up/yKQpePd8w5BJU7C0svJ8ZzMajYxObzpEI9h9Zy1cxOHdu9i9cweXTk9n+KXTQhpAdST/7dH4/Blz5Y8xh58g+1AGl6a3v/yxsbHMmjWL2NjYVs+h5s7h5PGpgXUQrEEuKHk2o9GIXq9v83fYfw58vWkDb/3Pm1z1g2uZPOeaNtdBe4/fWfu3V28pf1v2b3z+pYyJI3oIbFi+i/iB8885o2RXHT8u1cA7//spfZPnnPP4PeFv9PnuvA9Azn64LpSWLl3KbbfdRlpaGtOmTePll1/m+PHjgXU9fvvb33Ly5MlAz8uiRYt47rnnWLp0Kffeey+7du3itddeY+3atSHPuxChotef/8+qBMtgMgU1Y5OfyWIgKt7SravoNq7/tq5Efj4xmEykTp5OTmklqZOnY+jlf+CbO388nuEUUduh8rdlMciWzuHBozr3ucpgGUwmBo6fSIn2FgPHT7xgZn/yu9DK39z5558mvLuOX1RUFFh/R3St8z4AyQti/HBXWLBgAWVlZfz+97+nsLCQsWPHsmHDBlJSUoD6br7jx48H0g8ZMoQNGzbw0EMP8fzzz9O/f3+effZZmYJXiF7KEmFizj1jOrUHKCIigrFjx7Y7gGjrSuSi+3TF+XM+5KGjQXBHvwOdcfzuDOJ7evnbsn9z518oy9/S8XvqTZye5rwPQLrT4sWLWbx4cbOvvf766022zZgxo9nZQIQQvVNn9wBFRkYybty4blmBWYTe+dCD2BXncEeC4I5+Bzrj+N0ZxPf08rd1/8bnX6jL39zx5SZOaHR/6yeEEEIIIYS4YEgAIoQQQgghhAgZCUCEEEIIIYQQISMBiBBCCCGEECJkJAARQgghhBBChIwEIEIIIYQQQoiQkQBECCGEEEIIETISgAghhBBCCCFCRgIQIYQQQgghRMhIACKEEEIIIYQIGUN3Z0B8TykFQHV1NUajsZtz0zE2m63Bv8Fwu904HA5sNluPL397XOjlB6kDKb+U/0IuP0gdSPl7Rvn91zb+6zbRdhKAnEfKysoAGDJkSDfnpPMkJyd3dxaEEEIIITpddXU10dHR3Z2NHkkCkPNInz59ADh+/PgFeULbbDaSk5MpKCggKiqqu7MTchd6+UHqQMov5b+Qyw9SB1L+nlF+pRTV1dX079+/u7PSY0kAch7R6eofyYmOjj6vv3hdLSoqSsp/AZcfpA6k/FL+C7n8IHUg5T//y38h3ijuTPIQuhBCCCGEECJkJAARQgghhBBChIwEIOeRsLAwli1bRlhYWHdnpVtI+S/s8oPUgZRfyn8hlx+kDqT8F3b5LySakjnEhBBCCCGEECEiPSBCCCGEEEKIkJEARAghhBBCCBEyEoAIIYQQQgghQkYCECGEEEIIIUTISAASYitXrmTIkCGYzWYmTZrEl19+ec70q1evZsKECVitVpKSkli4cCFlZWUhym3n2rZtG9deey39+/dH0zTWr1/f6j5bt25l0qRJmM1mhg4dyosvvtj1Ge0ibS3/Bx98wOzZs+nbty9RUVFMmzaNjRs3hiazXaA9n7/fjh07MBgMXHzxxV2Wv67WnvLX1dXx+OOPk5KSQlhYGMOGDeOf//xn12e2i7SnDnpLG/j0009z6aWXEhkZSb9+/fjRj37EoUOHWt2vN7WB7amD3tQOtvcc8Ovp7WB7y9/b2kFRTwKQEHr77bd58MEHefzxx8nMzOTyyy9n3rx5HD9+vNn027dv5/bbb+fuu+/mu+++491332X37t3cc889Ic5556ipqWHChAk899xzQaU/duwY11xzDZdffjmZmZk89thj/OpXv+L999/v4px2jbaWf9u2bcyePZsNGzaQkZHBzJkzufbaa8nMzOzinHaNtpbfr6qqittvv51Zs2Z1Uc5Coz3lv+WWW/jss8947bXXOHToEGvXrmXkyJFdmMuu1dY66E1t4NatW7n//vv56quv2Lx5Mx6Phzlz5lBTU9PiPr2tDWxPHfSmdrA95ffrDe1ge8vf29pBcYYSITN58mS1aNGiBttGjhypHn300WbT//Wvf1VDhw5tsO3ZZ59VAwcO7LI8hgqg1q1bd840v/nNb9TIkSMbbPvFL36hpk6d2oU5C41gyt+c0aNHq6eeeqrzMxRibSn/ggUL1BNPPKGWLVumJkyY0KX5CpVgyv/xxx+r6OhoVVZWFppMhVgwddCb28CSkhIFqK1bt7aYpje3gUoFVwfN6S3tYFvK3xvbwWDK39vbwQuZ9ICEiMvlIiMjgzlz5jTYPmfOHHbu3NnsPtOnT+fEiRNs2LABpRTFxcW89957/PCHPwxFlrvdrl27mtTX3Llz2bNnD263u5ty1X18Ph/V1dX06dOnu7MSMqtWreLIkSMsW7asu7MSch9++CFpaWn85S9/YcCAAQwfPpyHH34Yp9PZ3VkLmd7cBlZVVQGc8/vc29vAYOqgsd7UDgZb/t7aDgZTfmkHey9Dd2fgQlFaWorX6yUhIaHB9oSEBIqKiprdZ/r06axevZoFCxZQW1uLx+Phuuuu47//+79DkeVuV1RU1Gx9eTweSktLSUpK6qacdY+///3v1NTUcMstt3R3VkIiJyeHRx99lC+//BKD4cJrqo4ePcr27dsxm82sW7eO0tJSFi9eTHl5+QUz/rm3toFKKZYuXcpll13G2LFjW0zXm9vAYOugsd7SDgZb/t7aDgZbfmkHey/pAQkxTdMa/K6UarLNLysri1/96lf87ne/IyMjg08++YRjx46xaNGiUGT1vNBcfTW3vbdbu3YtTz75JG+//Tb9+vXr7ux0Oa/Xy09/+lOeeuophg8f3t3Z6RY+nw9N01i9ejWTJ0/mmmuuYfny5bz++usXzN2/3toGPvDAA+zbt4+1a9e2mra3toFtqQO/3tQOBlP+3twOBvv5SzvYe/WecPo8Fx8fj16vb9LbUVJS0uQOl9/TTz9Neno6jzzyCADjx48nPDycyy+/nD/+8Y89+u5XMBITE5utL4PBQFxcXDflKvTefvtt7r77bt59912uvvrq7s5OSFRXV7Nnzx4yMzN54IEHgPo/REopDAYDmzZt4qqrrurmXHatpKQkBgwYQHR0dGDbqFGjUEpx4sQJUlNTuzF3odEb28Bf/vKXfPjhh2zbto2BAweeM21vbQPbUgd+vakdDLb8vbUdbMvnL+1g7yU9ICFiMpmYNGkSmzdvbrB98+bNTJ8+vdl9HA4HOl3Dj0iv1wPf3wXrzaZNm9akvjZt2kRaWhpGo7GbchVaa9eu5c4772TNmjW9Ytx7sKKioti/fz/ffPNN4GfRokWMGDGCb775hilTpnR3Frtceno6p06dwm63B7YdPnwYnU4X9EVbT9eb2kClFA888AAffPABn3/+OUOGDGl1n97WBranDqD3tINtLX9vawfb8/lLO9iLhfih9wvaW2+9pYxGo3rttddUVlaWevDBB1V4eLjKy8tTSin16KOPqttuuy2QftWqVcpgMKiVK1eqI0eOqO3bt6u0tDQ1efLk7ipCh1RXV6vMzEyVmZmpALV8+XKVmZmp8vPzlVJNy3/06FFltVrVQw89pLKystRrr72mjEajeu+997qrCB3S1vKvWbNGGQwG9fzzz6vCwsLAT2VlZXcVoUPaWv7GevrsL20tf3V1tRo4cKC66aab1Hfffae2bt2qUlNT1T333NNdReiwttZBb2oD77vvPhUdHa22bNnS4PvscDgCaXp7G9ieOuhN7WB7yt9YT24H21P+3tgOinoSgITY888/r1JSUpTJZFITJ05sMP3cHXfcoWbMmNEg/bPPPqtGjx6tLBaLSkpKUj/72c/UiRMnQpzrzvHFF18ooMnPHXfcoZRqvvxbtmxRl1xyiTKZTGrw4MHqhRdeCH3GO0lbyz9jxoxzpu9p2vP5n60n/+FVqn3lP3jwoLr66quVxWJRAwcOVEuXLm3wx7qnaU8d9JY2sLlyA2rVqlWBNL29DWxPHfSmdrC958DZenI72N7y97Z2UNTTlOph/dhCCCGEEEKIHkueARFCCCGEEEKEjAQgQgghhBBCiJCRAEQIIYQQQggRMhKACCGEEEIIIUJGAhAhhBBCCCFEyEgAIoQQQgghhAgZCUCEEEIIIYQQISMBiBBCCCGEECJkJAARQgghhBBChIwEIEIIIcR5prS0lIceeohrrrmGp556itra2u7OkhBCdBpNKaW6OxNCCCGEqOd0Ohk/fjy5ubmBbVdddRWffvopmqZ1Y86EEKJzSA+IEEIIcR5Zu3YteXl5fPDBB9jtdv7617/y+eef8+WXX3Z31oQQolNIACKEEEKcR44ePcqIESOYP38+4eHhLF26FIPBQF5eXndnTQghOoUEIEII0QGDBw9G0zS5OBRN5OXloWlag58nn3yy1f3GjBnDoUOHWLduHTU1NSxfvhyPx8PEiRObpL344osbvP+VV17Z+QURQohOJgGIEOKC5Q8e/D86nY6oqCiSk5OZPXs2TzzxBFlZWV2ejxUrVvDkk09SWVnZ5cfqqT766CMWLFjAoEGDMJvN9OnTh0mTJvFf//VfFBcXt/t9/efA66+/fs50V155ZdABRGNhYWGkp6eTnp7OoEGDWk1/yy23MHPmTG644QYiIiJ45JFH+N3vfsfYsWObpL3kkktIT09v9jUhhDhfGbo7A0II0d1SU1Pp168fALW1tZSWlvLpp5/y6aef8qc//Ykbb7yRl156ibi4uCb7Dhs2DLPZjNFobPfxV6xYQX5+PnfeeScxMTHtfp/eqKqqigULFrBx40YA+vbty7hx47DZbGRmZrJ3716eeeYZXn31VW655ZZuzm3zEhMT2b59e9Dp9Xo9ERERgd+jo6N56qmnmk27atUqALZs2cLMmTM7llEhhAgR6QERQlzwHnvsMbZv38727dvZs2cPeXl5nD59mhUrVhAfH8/777/PZZddRlVVVZN9P/vsM7KzsxkwYEA35Lx3c7lczJ49m40bNzJ48GA2bNhAcXExu3fv5tChQ+Tn5/PjH/+Y6upqfvKTn/D+++93d5Y7xc6dO1m3bh3R0dFomkZVVRUFBQXdnS0hhOg0EoAIIUQz4uPjWbJkCXv27CEpKYns7GwefPDB7s7WBWXZsmXs3r2bpKQkvvzyS+bNm9dgGtrk5GTWrl3LwoUL8fl83HPPPR0ajnW+ePjhhwF49NFHSU5OBmD//v3dmSUhhOhUEoAIIcQ5pKSksHLlSgD+9a9/NbkT3dJD6Pn5+fziF79g6NChhIWFERkZydChQ5k/fz5vvfUWAK+//jqappGfnw/AkCFDGjyTsmXLlsD7HThwgGXLljFt2jSSkpIwmUwkJSVxww03sHPnzhbz738vgI8//pgrrriCyMhIoqOjmTdvHpmZmS3u6/F4eOWVV5g5cyZxcXGYzWaGDh3KjTfeyP/+7/82m/7FF1/ksssuIyYmBrPZzMiRI3niiSew2WwtV3IzKisree655wD429/+xsCBA1tM+8wzzxAfH99gn57q/fffZ9euXQwYMIAlS5YwZswYQAIQIUTvIgGIEEK04rrrrqN///54PB42bdrUavq8vDzS0tJ4+eWXKS4uZsSIEVx00UVUVVWxfv16/vznPwOQkJBAeno6YWFhAKSlpQUeVk5PTyc6Ojrwng8++CC///3vyc7OJjY2lnHjxuHxeFi3bh1XXHEFa9asOWeeXnzxRX74wx+Sm5vL8OHD8Xq9fPLJJ1xxxRVkZ2c3SV9RUcGVV17Jz3/+c7Zs2UJkZCTjxo2jpqaGDz74gCVLljRIb7PZmDVrFvfddx+7du0iJiaG1NRUjh07xp/+9CemTp1KSUlJq3Xnt2HDBux2O/Hx8dx8883nTBsZGcnPfvYzAN55552gj3G+cbvd/Pa3vwXgySefxGKxBAKQffv2dWfWhBCiU0kAIoQQrdDpdEybNg2A3bt3t5r+73//O6Wlpdxxxx0UFxezb98+MjMzKSsr4+DBgyxevBiAefPmsX37dhITEwF49913A8+ibN++nUsuuSTwnosWLWLfvn1UVFSQlZVFRkYGJSUlrF+/HovFwn333Ud1dXWLefr1r3/NP//5T06dOkVGRgaFhYXMmjULu93e7MxOd911Fzt27GDYsGF89dVX5OXlsXv3boqLi8nJyeH+++9vkP4Xv/gF27ZtY9asWeTk5JCXl8f+/fspKirihhtu4ODBg032ORd/r8706dODesD/iiuuAODw4cOUlZUFfZzzyYsvvkhOTg6jRo1i4cKFANIDIoTolSQAEUKIIPjH4gdzFz8nJweApUuXNpjNCGDkyJH8/Oc/b/Pxb7rpJsaNG9dgm6ZpXH/99Tz44IPYbDY++uijFve/++67ufPOOwO/R0ZG8o9//AOATz75pEHa3bt3s379esLCwvj444+ZMmVKg9cvuugiHnnkkcDv+/bt46233iIlJYV169YxdOjQwGuxsbH8z//8D8nJybz//vuB4WatOXnyJFA/y1gwzk7n37ctFi5c2GTNjrN/tm7d2ub3bAubzcYf/vAHAJ5++mn0ej0Ao0ePBiA7Oxu3292leRBCiFCRaXiFECII4eHhAOfsZfDzByvvvfce48aNa/DgdEccP36cNWvWsHfvXkpLS3G5XMD3QdG3337LT3/602b3veeee5psGzduHGazmaqqKsrKygLTDPuf75g/fz6pqamt5mvdunVA/foVkZGRTV63Wq1cffXVrFq1ii+//JKUlJRW39Nfz/56b83Z6YL5jBo7eyrm5uzfv7/Nz7G0xZ///GdOnz7N9OnTuf766wPbR48ejaZpuN1uDh06JOt9CCF6BQlAhBAiCHa7HYCoqKhW095///288cYb/OEPf+DNN9/kBz/4AZdffjkzZ86kf//+7Tr+G2+8waJFi6itrW0xTXl5eYuvtdST0LdvXwoKCrDb7YEA5ODBgwBMnTo1qLz5hwetW7euxQfi/T0fwfZO+AOZmpqaoNKfna65IKg1jz32WIMeosauvPLKLusFOXnyJCtWrADgL3/5S4PXIiIiGDRoEPn5+ezfv18CECFEryABiBBCBOH48eMA57xL7nfxxRezbds2li1bxueff85LL73ESy+9hKZpzJ49mxUrVjBq1Kigj33kyBHuvfde3G43v/71r7n11lsZNmwYERERaJrGq6++Gni9JS31JOh09SNxlVKBbf47/cEuiuhfHyU3N5fc3NxzpnU6nUG9p39dlSNHjgSV/ux0/n1vvvlmCgsLm6Rty6KAofDEE0/gdDq57rrrSE9Pb/L6mDFjAgHIT37yk27IoRBCdC4JQIQQohU+n49du3YBMHny5KD2mTp1Khs3bsRut7Njxw6++OIL1qxZw6ZNm5g9ezYHDhwI+gL/nXfewe128+Mf/5i//e1vTV7v7EXq/D0IlZWVQaX3P+fyyiuvNDvUqz2mT5/O888/z86dO/F4PBgM5/5ztW3bNqB+KJW/J2f37t1BP3PSXfbv38+bb74JwIcffnjO4XryILoQoreQh9CFEKIV69evp6ioCKPRyJw5c9q0b0REBHPnzuXPf/4z2dnZDBs2jJMnT/Lxxx8H0rT2jIh/jZHp06c3+/q3337bpjy1xj/z0ldffRVUev+D0gcOHOi0PFxzzTWEh4dTWlrKu+++e8601dXVrF69GoAFCxYEtufl5aGUavJzPnnkkUfw+XxERUWRkJDQ7E9sbCwgAYgQoveQAEQIIc4hPz+fBx54AIDbb789MLynPaxWa2Amq1OnTgW2WywWoOXhSf7Xm1vlOzs7+5yzX7XHj370I6A+8ApmCNT8+fOB+oUaO2sK3JiYmMC0vb/+9a85ceJEi2mXLFlCaWkp0dHRbZrqt7t9+umnbNy4EbPZzL59+ygqKmr259NPPwXqz8WufBBeCCFCRQIQIYRoRmlpKc8++yxpaWkUFhYyevRoli9fHtS+9913H2+//TYOh6PB9m3btvHZZ58BMHHixMB2/7S1LT3kfNlllwGwcuVKvvnmm8D2w4cPc/PNN2MymYIuVzAmTZrE/Pnzqa2tZd68eU3WPsnNzW0wFCwtLY1bbrmFsrIyZs+e3WR1da/Xy5YtW/jZz35GXV1d0Pn4/e9/z8SJEyksLOSKK67gk08+adCDceLECX7605+yatUqNE3j5ZdfDqypcr5TSvGb3/wGgIceeuicM4ONGjUq8KxOZ/YyCSFEt1FCCHGBSklJUYBKTU1V6enpKj09XaWlpanBgwcrIPBz8803q7KysnO+x7FjxwLbJkyYoABlMBjUqFGj1OTJkwPpAHXrrbc2eI8333wz8NrYsWPVjBkz1IwZM1RmZqZSSim3262mTp2qAKXX69WoUaPU2LFjlaZpKikpSf3xj39UgLrjjjua5M//vq3Vwdn5V0qp8vJyNW3atMD+gwcPVmlpaSohIUEBKiUlpUH66upqNXv27ED6QYMGqSlTpqhx48Ypi8US2O50OlvMS3MqKirU1VdfHdi/b9++Ki0tTY0YMUJpmqYAFRERodasWdOm921c/lWrVp0z3YwZMxSgli1bFvR7Hzt2rNm6Uur7z7xfv37KZrO1+l7Dhg1TgHrxxRebff2LL75QgJoxY0bQ+RNCiO4iPSBCiAteTk4OO3bsYMeOHWRnZ+PxeLj66qt5/PHHycrK4p133qFPnz5Bv98//vEPlixZwvjx4yktLQ30WsydO5cPP/ww8NCx32233cYzzzzD+PHjOXLkCFu3bmXr1q2Bh8ANBgMbN27kl7/8JQkJCeTm5lJZWcndd99NRkZGh4aFtSQ2NpatW7fy/PPPk56eTkVFBQcOHMBqtXLTTTfx3HPPNUgfERHBJ598wurVq5k7dy4OhyOwXsn48eP5z//8T77++mvMZnOb8hETE8PmzZtZv349N910E2FhYYHhShMmTOCxxx4jJyenR80OVVtbyxNPPAHU9/IEM22w/7mcffv2dWnehBAiFDSlzrMn8oQQQoheIC8vjyFDhpCSkhKYSKCrbNmyhZkzZzJjxgy2bNnSpccSQoiOkml4hRBCiC5UVFQUeI7nrrvu4q677uq09164cCE5OTmBtViEEKIn+P/S2P4SbSXqoAAAAABJRU5ErkJggg==", + "text/html": [ + "\n", + "
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\"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "ax.axvline(x=0.96, color=\"black\", linestyle=\"-\", linewidth=0.8)\n", + "\n", + "total_ice = sum(histogram_ice)\n", + "total_water4 = sum(histogram_water4)\n", + "total_water5 = sum(histogram_water5)\n", + "total_water6 = sum(histogram_water6)\n", + "total_water7 = sum(histogram_water7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "total_all = sum(histogram_all)\n", + "\n", + "plt.fill_between(\n", + " smooth_x,\n", + " smooth_y / total_all,\n", + " where=(smooth_y / total_all > 0),\n", + " alpha=0.3,\n", + " color=\"gray\",\n", + " label=\"distribution\",\n", + ")\n", + "# ax.plot(\n", + "# # distribution_all,\n", + "# # histogram_all / total_all,\n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_ice_nan / total_ice,\n", + " \"*\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=r\"ice $I_h$\",\n", + " markersize=6,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water4_nan / total_water4,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water tetramer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water5_nan / total_water5,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water pentamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water6_nan / total_water6,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water hexamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_water7_nan / total_water7,\n", + " \"+\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=\"water cluster\",\n", + " markersize=7,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w1_nan / total_w1,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w1\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w2\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "plt.xlim(0.8, 2.73)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.2))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list)}' r\" [$\\AA$]\", fontsize=16)\n", + "plt.legend(loc=\"best\", fontsize=10, ncol=2)\n", + "\n", + "\n", + "fig.savefig(\n", + " working_dir / \"rda_OH.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_O-O_RDA.ipynb b/analysis_O-O_RDA.ipynb new file mode 100644 index 0000000..5618c72 --- /dev/null +++ b/analysis_O-O_RDA.ipynb @@ -0,0 +1,664 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir_water: Path = Path(\n", + " \"/home/edison/repositories/radial_distribution/files_xyz/others/water\"\n", + ")\n", + "\n", + "files_ice: list = glob(str(dir_water / \"ice_ih\" / \"w_iceih.xyz\"))\n", + "files_water4: list = glob(str(dir_water / \"w4\" / \"w*.xyz\"))\n", + "files_water5: list = glob(str(dir_water / \"w5\" / \"w*.xyz\"))\n", + "files_water6: list = glob(str(dir_water / \"w6\" / \"w*.xyz\"))\n", + "# files_water7: list = glob(str(dir_water / \"w7\" / \"w*.xyz\"))\n", + "files_water7: list = glob(str(dir_water / \"w*\" / \"w*.xyz\"))\n", + "\n", + "coordinates_ice: list = functions.dict_coordinates_xyz(files_ice)\n", + "coordinates_water4: list = functions.dict_coordinates_xyz(files_water4)\n", + "coordinates_water5: list = functions.dict_coordinates_xyz(files_water5)\n", + "coordinates_water6: list = functions.dict_coordinates_xyz(files_water6)\n", + "coordinates_water7: list = functions.dict_coordinates_xyz(files_water7)\n", + "\n", + "\n", + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_ice: dict = distance_matrix.distance_matrix(coordinates_ice, (0, 0, 0))\n", + "distances_dict_water4: dict = distance_matrix.distance_matrix(\n", + " coordinates_water4, (0, 0, 0)\n", + ")\n", + "distances_dict_water5: dict = distance_matrix.distance_matrix(\n", + " coordinates_water5, (0, 0, 0)\n", + ")\n", + "distances_dict_water6: dict = distance_matrix.distance_matrix(\n", + " coordinates_water6, (0, 0, 0)\n", + ")\n", + "distances_dict_water7: dict = distance_matrix.distance_matrix(\n", + " coordinates_water7, (0, 0, 0)\n", + ")\n", + "\n", + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (1.5, 7.0, 0.1)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': [(1, 4)]}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list: list = [\"O\", \"O\"]\n", + "\n", + "atoms_index_dict_ice: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_ice, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water6, atoms_list, grid\n", + ")\n", + "atoms_index_dict_water7: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_water7, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w1: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w1, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w2: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w2, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w3: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w3, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w4: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w4, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w5: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w5, atoms_list, grid\n", + ")\n", + "atoms_index_dict_w6: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_w6, atoms_list, grid\n", + ")\n", + "\n", + "atoms_index_dict_w2\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 205,\n", + " 233, 141, 21, 2, 1, 0, 3, 14, 4, 11, 21, 74, 28,\n", + " 26, 23, 29, 61, 39, 43, 37, 39, 31, 22, 24, 18, 16,\n", + " 23, 15, 10, 8, 5, 6, 7, 6, 9, 7, 2, 9, 3,\n", + " 4, 9, 9])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - radial (bond) distribution analysis (RDA); i.e., atoms_list_AB = [A, B]\n", + "histogram_ice: np.array = histogram.rda(\n", + " atoms_index_dict_ice, distances_dict_ice, grid, nbins\n", + ")\n", + "histogram_water4: np.array = histogram.rda(\n", + " atoms_index_dict_water4, distances_dict_water4, grid, nbins\n", + ")\n", + "histogram_water5: np.array = histogram.rda(\n", + " atoms_index_dict_water5, distances_dict_water5, grid, nbins\n", + ")\n", + "histogram_water6: np.array = histogram.rda(\n", + " atoms_index_dict_water6, distances_dict_water6, grid, nbins\n", + ")\n", + "histogram_water7: np.array = histogram.rda(\n", + " atoms_index_dict_water7, distances_dict_water7, grid, nbins\n", + ")\n", + "\n", + "histogram_w1: np.array = histogram.rda(\n", + " atoms_index_dict_w1, distances_dict_w1, grid, nbins\n", + ")\n", + "histogram_w2: np.array = histogram.rda(\n", + " atoms_index_dict_w2, distances_dict_w2, grid, nbins\n", + ")\n", + "histogram_w3: np.array = histogram.rda(\n", + " atoms_index_dict_w3, distances_dict_w3, grid, nbins\n", + ")\n", + "histogram_w4: np.array = histogram.rda(\n", + " atoms_index_dict_w4, distances_dict_w4, grid, nbins\n", + ")\n", + "histogram_w5: np.array = histogram.rda(\n", + " atoms_index_dict_w5, distances_dict_w5, grid, nbins\n", + ")\n", + "histogram_w6: np.array = histogram.rda(\n", + " atoms_index_dict_w6, distances_dict_w6, grid, nbins\n", + ")\n", + "\n", + "histogram_water7\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins, endpoint=False)\n", + "\n", + "histograms: list = [\n", + " histogram_ice,\n", + " histogram_water4,\n", + " histogram_water5,\n", + " histogram_water6,\n", + " histogram_water7,\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (\n", + " f\"rda_w{count + 1}_\" + \"-\".join(atoms_list) + \".dat\"\n", + " )\n", + " np.savetxt(\n", + " histogram_name,\n", + " np.transpose([distribution, hist]),\n", + " delimiter=\" \",\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt=\"%.6f %28i\",\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_ice_nan = histogram_ice.astype(\"float\")\n", + "histogram_water4_nan = histogram_water4.astype(\"float\")\n", + "histogram_water5_nan = histogram_water5.astype(\"float\")\n", + "histogram_water6_nan = histogram_water6.astype(\"float\")\n", + "histogram_water7_nan = histogram_water7.astype(\"float\")\n", + "\n", + "histogram_w1_nan = histogram_w1.astype(\"float\")\n", + "histogram_w2_nan = histogram_w2.astype(\"float\")\n", + "histogram_w3_nan = histogram_w3.astype(\"float\")\n", + "histogram_w4_nan = histogram_w4.astype(\"float\")\n", + "histogram_w5_nan = histogram_w5.astype(\"float\")\n", + "histogram_w6_nan = histogram_w6.astype(\"float\")\n", + "\n", + "histogram_ice_nan[histogram_ice_nan == 0] = float(\"nan\")\n", + "histogram_water4_nan[histogram_water4_nan == 0] = float(\"nan\")\n", + "histogram_water5_nan[histogram_water5_nan == 0] = float(\"nan\")\n", + "histogram_water6_nan[histogram_water6_nan == 0] = float(\"nan\")\n", + "histogram_water7_nan[histogram_water7_nan == 0] = float(\"nan\")\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float(\"nan\")\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float(\"nan\")\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float(\"nan\")\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float(\"nan\")\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float(\"nan\")\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float(\"nan\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "grid_all = (1.5, 7.0, 0.5)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin_all, rmax_all, dr_all = grid_all\n", + "nbins_all = int((rmax_all - rmin_all) / dr_all)\n", + "\n", + "distribution_all = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "\n", + "files_all: list = glob(str(working_dir / \"w*.xyz\"))\n", + "coordinates_all: dict = functions.dict_coordinates_xyz(files_all)\n", + "distances_dict_all: dict = distance_matrix.distance_matrix(coordinates_all, (0, 0, 0))\n", + "\n", + "atoms_index_dict_all: dict = atoms_index_list.atoms_index_dict(\n", + " distances_dict_all, atoms_list, grid_all\n", + ")\n", + "histogram_all: np.array = histogram.rda(\n", + " atoms_index_dict_all, distances_dict_all, grid_all, nbins_all\n", + ")\n", + "\n", + "\n", + "# -----------------------------------------------------------------------------------------------------------------------\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "\n", + "x = np.linspace(rmin_all, rmax_all, nbins_all, endpoint=False)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100, endpoint=False)\n", + "\n", + "y = histogram_all\n", + "smooth = make_interp_spline(x, y, k=3)\n", + "smooth_y = smooth(smooth_x)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e10f9765fe0a4cea810e096efc7f9ade", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " Figure\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "\n", + "# ax = brokenaxes(ylims=((0, 0.25),(0.95, 1.05)), hspace=.2)\n", + "ax = fig.add_subplot(111)\n", + "ax.grid(b=True, which=\"major\")\n", + "\n", + "# - lines style in a for loop\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "lines = [\"s\", \"^\", \"v\", \"<\", \">\", \".\", \"s\", \"d\", \"o\"] # , '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "cm = cycle(\n", + " [\n", + " \"#1f77b4\",\n", + " \"#ff7f0e\",\n", + " \"#2ca02c\",\n", + " \"#d62728\",\n", + " \"#9467bd\",\n", + " \"#8c564b\",\n", + " \"#e377c2\",\n", + " \"#7f7f7f\",\n", + " \"#bcbd22\",\n", + " \"#17becf\",\n", + " ]\n", + ")\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "# ax.axvline(x=0.96, color='black', linestyle='-', linewidth=1)\n", + "\n", + "total_ice = sum(histogram_ice)\n", + "total_water4 = sum(histogram_water4)\n", + "total_water5 = sum(histogram_water5)\n", + "total_water6 = sum(histogram_water6)\n", + "total_water7 = sum(histogram_water7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "total_all = sum(histogram_all)\n", + "\n", + "plt.fill_between(\n", + " smooth_x,\n", + " smooth_y / total_all,\n", + " where=(smooth_y / total_all > 0),\n", + " alpha=0.3,\n", + " color=\"gray\",\n", + " label=\"distribution\",\n", + ")\n", + "# ax.plot(\n", + "# # distribution_all,\n", + "# # histogram_all / total_all,\n", + "# smooth_x,\n", + "# smooth_y / total_all,\n", + "# \"-\",\n", + "# # next(linecycler),\n", + "# color=\"black\",\n", + "# label=\"distribution\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_ice_nan / total_ice,\n", + " \"*\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=r\"ice $I_h$\",\n", + " markersize=6,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water4_nan / total_water4,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water tetramer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water5_nan / total_water5,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water pentamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_water6_nan / total_water6,\n", + "# # \"o\",\n", + "# next(linecycler),\n", + "# color=\"b\",\n", + "# label=\"water hexamer\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_water7_nan / total_water7,\n", + " \"+\",\n", + " # next(linecycler),\n", + " color=\"black\",\n", + " label=\"water cluster\",\n", + " markersize=7,\n", + " alpha=0.5,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "# ax.plot(\n", + "# distribution,\n", + "# histogram_w1_nan / total_w1,\n", + "# # \"-\",\n", + "next(linecycler),\n", + "# color=next(cm),\n", + "color = (next(cm),)\n", + "# label=\"w1\",\n", + "# markersize=7,\n", + "# alpha=0.7,\n", + "# # color=\"black\",\n", + "# # markerfacecolor=\"none\",\n", + "# )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w2\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w3\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w4\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w5\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " color=next(cm),\n", + " label=\"w6\",\n", + " markersize=7,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "\n", + "plt.xlim(2.0, 6.6)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.5))\n", + "\n", + "ax.set_ylabel(\"Relative Number of Occurrences\", fontsize=16)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list)}' r\" [$\\AA$]\", fontsize=16)\n", + "plt.legend(loc=\"upper right\", fontsize=10, ncol=2)\n", + "\n", + "\n", + "fig.savefig(\n", + " working_dir / \"rda_OO.pdf\",\n", + " dpi=500,\n", + " bbox_inches=\"tight\",\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.7 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "8bfa2ac5c09c63b51e43800e6e6b1b66ecca8dd5e88c320e0c3745a9652f5f00" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/analysis_RDA.ipynb b/analysis_RDA.ipynb new file mode 100644 index 0000000..e16a7a3 --- /dev/null +++ b/analysis_RDA.ipynb @@ -0,0 +1,991 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from glob import glob\n", + "from itertools import cycle\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "from matplotlib.ticker import MultipleLocator\n", + "from scipy.interpolate import make_interp_spline, BSpline\n", + "from brokenaxes import brokenaxes\n", + "\n", + "# interactive plots\n", + "%matplotlib widget\n", + "\n", + "import matrix_r # module to calculate of matriz distance\n", + "import functions # module with all the individuals function to do analysis\n", + "import distance_matrix\n", + "import atoms_index_list\n", + "import histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "working_dir: Path = Path(\"/home/edison/repositories/radial_distribution/zora_so\")\n", + "\n", + "if not working_dir.exists():\n", + " working_dir.mkdir()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': element x-coordinate y-coordinate z-coordinate\n", + " 0 Hg -0.225130 0.010739 0.00000\n", + " 1 O 1.821376 -0.090165 0.00000\n", + " 2 H 2.325945 0.187310 0.79892\n", + " 3 H 2.325945 0.177310 -0.79892}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "files_w1: list = glob(str(working_dir / \"w1s*.xyz\"))\n", + "files_w2: list = glob(str(working_dir / \"w2s*.xyz\"))\n", + "files_w3: list = glob(str(working_dir / \"w3s*.xyz\"))\n", + "files_w4: list = glob(str(working_dir / \"w4s*.xyz\"))\n", + "files_w5: list = glob(str(working_dir / \"w5s*.xyz\"))\n", + "files_w6: list = glob(str(working_dir / \"w6s*.xyz\"))\n", + "\n", + "coordinates_w1: dict = functions.dict_coordinates_xyz(files_w1)\n", + "coordinates_w2: dict = functions.dict_coordinates_xyz(files_w2)\n", + "coordinates_w3: dict = functions.dict_coordinates_xyz(files_w3)\n", + "coordinates_w4: dict = functions.dict_coordinates_xyz(files_w4)\n", + "coordinates_w5: dict = functions.dict_coordinates_xyz(files_w5)\n", + "coordinates_w6: dict = functions.dict_coordinates_xyz(files_w6)\n", + "\n", + "coordinates_w1" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w1s1.xyz': atoms 0 1 2 3\n", + " 0 Hg 0.000000 2.048992 2.679073 2.678433\n", + " 1 O 2.048992 0.000000 0.984812 0.982042\n", + " 2 H 2.679073 0.984812 0.000000 1.597871\n", + " 3 H 2.678433 0.982042 1.597871 0.000000}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "distances_dict_w1: dict = distance_matrix.distance_matrix(coordinates_w1, (0, 0, 0))\n", + "distances_dict_w2: dict = distance_matrix.distance_matrix(coordinates_w2, (0, 0, 0))\n", + "distances_dict_w3: dict = distance_matrix.distance_matrix(coordinates_w3, (0, 0, 0))\n", + "distances_dict_w4: dict = distance_matrix.distance_matrix(coordinates_w4, (0, 0, 0))\n", + "distances_dict_w5: dict = distance_matrix.distance_matrix(coordinates_w5, (0, 0, 0))\n", + "distances_dict_w6: dict = distance_matrix.distance_matrix(coordinates_w6, (0, 0, 0))\n", + "\n", + "distances_dict_w1" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [], + "source": [ + "grid = (1.5, 3, 0.005)\n", + "\n", + "# - number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'/home/edison/repositories/radial_distribution/zora_so/w2s1.xyz': [(0, 1),\n", + " (0, 4)]}" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_list_HgO: list = ['Hg', 'O']\n", + "\n", + "atoms_index_dict_w1_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w1, atoms_list_HgO, grid)\n", + "atoms_index_dict_w2_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w2, atoms_list_HgO, grid)\n", + "atoms_index_dict_w3_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w3, atoms_list_HgO, grid)\n", + "atoms_index_dict_w4_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w4, atoms_list_HgO, grid)\n", + "atoms_index_dict_w5_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w5, atoms_list_HgO, grid)\n", + "atoms_index_dict_w6_HgO: dict = atoms_index_list.atoms_index_dict(distances_dict_w6, atoms_list_HgO, grid)\n", + "\n", + "atoms_index_dict_w2_HgO" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# - radial (bond) distribution analysis (RDA); i.e., atoms_list_AB = [A, B]\n", + "histogram_w1: np.array = histogram.rda(atoms_index_dict_w1_HgO, distances_dict_w1, grid, nbins)\n", + "histogram_w2: np.array = histogram.rda(atoms_index_dict_w2_HgO, distances_dict_w2, grid, nbins)\n", + "histogram_w3: np.array = histogram.rda(atoms_index_dict_w3_HgO, distances_dict_w3, grid, nbins)\n", + "histogram_w4: np.array = histogram.rda(atoms_index_dict_w4_HgO, distances_dict_w4, grid, nbins)\n", + "histogram_w5: np.array = histogram.rda(atoms_index_dict_w5_HgO, distances_dict_w5, grid, nbins)\n", + "histogram_w6: np.array = histogram.rda(atoms_index_dict_w6_HgO, distances_dict_w6, grid, nbins)\n", + "\n", + "histogram_w1" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [], + "source": [ + "# - saving histogram\n", + "distribution = np.linspace(rmin, rmax, nbins)\n", + "\n", + "histograms: list =[\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "\n", + "for count, hist in enumerate(histograms):\n", + " histogram_name = working_dir / (f\"rda_w{count + 1}_\" + \"-\".join(atoms_list_HgO) + \".dat\")\n", + " np.savetxt(histogram_name, np.transpose([distribution, hist]),\n", + " delimiter=' ',\n", + " header=f\"distance [Angstrom] occurrence (total={sum(hist)})\",\n", + " fmt='%.6f %28i')" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [], + "source": [ + "histogram_w1_nan = histogram_w1.astype('float')\n", + "histogram_w2_nan = histogram_w2.astype('float')\n", + "histogram_w3_nan = histogram_w3.astype('float')\n", + "histogram_w4_nan = histogram_w4.astype('float')\n", + "histogram_w5_nan = histogram_w5.astype('float')\n", + "histogram_w6_nan = histogram_w6.astype('float')\n", + "\n", + "\n", + "histogram_w1_nan[histogram_w1_nan == 0] = float('nan')\n", + "histogram_w2_nan[histogram_w2_nan == 0] = float('nan')\n", + "histogram_w3_nan[histogram_w3_nan == 0] = float('nan')\n", + "histogram_w4_nan[histogram_w4_nan == 0] = float('nan')\n", + "histogram_w5_nan[histogram_w5_nan == 0] = float('nan')\n", + "histogram_w6_nan[histogram_w6_nan == 0] = float('nan')" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":5: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n", + " ax.grid(b=True, which='major')\n" + ] + }, + { + "ename": "ValueError", + "evalue": "x and y must have same first dimension, but have shapes (170,) and (300,)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/edison/repositories/radial_distribution/analysis_RDA.ipynb Cell 10'\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 20\u001b[0m total_w5 \u001b[39m=\u001b[39m \u001b[39msum\u001b[39m(histogram_w5)\n\u001b[1;32m 21\u001b[0m total_w6 \u001b[39m=\u001b[39m \u001b[39msum\u001b[39m(histogram_w6)\n\u001b[0;32m---> 23\u001b[0m ax\u001b[39m.\u001b[39;49mplot(\n\u001b[1;32m 24\u001b[0m distribution, \n\u001b[1;32m 25\u001b[0m histogram_w1_nan \u001b[39m/\u001b[39;49m total_w1, \n\u001b[1;32m 26\u001b[0m \u001b[39m# \"-\",\u001b[39;49;00m\n\u001b[1;32m 27\u001b[0m \u001b[39mnext\u001b[39;49m(linecycler),\n\u001b[1;32m 28\u001b[0m label\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mw1\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m 29\u001b[0m markersize\u001b[39m=\u001b[39;49m\u001b[39m8\u001b[39;49m,\n\u001b[1;32m 30\u001b[0m alpha\u001b[39m=\u001b[39;49m\u001b[39m0.7\u001b[39;49m,\n\u001b[1;32m 31\u001b[0m \u001b[39m# color=\"black\",\u001b[39;49;00m\n\u001b[1;32m 32\u001b[0m \u001b[39m# markerfacecolor=\"none\",\u001b[39;49;00m\n\u001b[1;32m 33\u001b[0m )\n\u001b[1;32m 34\u001b[0m ax\u001b[39m.\u001b[39mplot(\n\u001b[1;32m 35\u001b[0m distribution,\n\u001b[1;32m 36\u001b[0m histogram_w2_nan \u001b[39m/\u001b[39m total_w2,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[39m# markerfacecolor=\"none\",\u001b[39;00m\n\u001b[1;32m 44\u001b[0m )\n\u001b[1;32m 45\u001b[0m ax\u001b[39m.\u001b[39mplot(\n\u001b[1;32m 46\u001b[0m distribution,\n\u001b[1;32m 47\u001b[0m histogram_w3_nan \u001b[39m/\u001b[39m total_w3,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[39m# markerfacecolor=\"none\",\u001b[39;00m\n\u001b[1;32m 55\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/matplotlib/axes/_axes.py:1632\u001b[0m, in \u001b[0;36mAxes.plot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1390\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 1391\u001b[0m \u001b[39mPlot y versus x as lines and/or markers.\u001b[39;00m\n\u001b[1;32m 1392\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1629\u001b[0m \u001b[39m(``'green'``) or hex strings (``'#008000'``).\u001b[39;00m\n\u001b[1;32m 1630\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 1631\u001b[0m kwargs \u001b[39m=\u001b[39m cbook\u001b[39m.\u001b[39mnormalize_kwargs(kwargs, mlines\u001b[39m.\u001b[39mLine2D)\n\u001b[0;32m-> 1632\u001b[0m lines \u001b[39m=\u001b[39m [\u001b[39m*\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_lines(\u001b[39m*\u001b[39margs, data\u001b[39m=\u001b[39mdata, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)]\n\u001b[1;32m 1633\u001b[0m \u001b[39mfor\u001b[39;00m line \u001b[39min\u001b[39;00m lines:\n\u001b[1;32m 1634\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39madd_line(line)\n", + "File \u001b[0;32m~/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/matplotlib/axes/_base.py:312\u001b[0m, in \u001b[0;36m_process_plot_var_args.__call__\u001b[0;34m(self, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 310\u001b[0m this \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m args[\u001b[39m0\u001b[39m],\n\u001b[1;32m 311\u001b[0m args \u001b[39m=\u001b[39m args[\u001b[39m1\u001b[39m:]\n\u001b[0;32m--> 312\u001b[0m \u001b[39myield from\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_plot_args(this, kwargs)\n", + "File \u001b[0;32m~/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/matplotlib/axes/_base.py:498\u001b[0m, in \u001b[0;36m_process_plot_var_args._plot_args\u001b[0;34m(self, tup, kwargs, return_kwargs)\u001b[0m\n\u001b[1;32m 495\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39maxes\u001b[39m.\u001b[39myaxis\u001b[39m.\u001b[39mupdate_units(y)\n\u001b[1;32m 497\u001b[0m \u001b[39mif\u001b[39;00m x\u001b[39m.\u001b[39mshape[\u001b[39m0\u001b[39m] \u001b[39m!=\u001b[39m y\u001b[39m.\u001b[39mshape[\u001b[39m0\u001b[39m]:\n\u001b[0;32m--> 498\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mx and y must have same first dimension, but \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 499\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhave shapes \u001b[39m\u001b[39m{\u001b[39;00mx\u001b[39m.\u001b[39mshape\u001b[39m}\u001b[39;00m\u001b[39m and \u001b[39m\u001b[39m{\u001b[39;00my\u001b[39m.\u001b[39mshape\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 500\u001b[0m \u001b[39mif\u001b[39;00m x\u001b[39m.\u001b[39mndim \u001b[39m>\u001b[39m \u001b[39m2\u001b[39m \u001b[39mor\u001b[39;00m y\u001b[39m.\u001b[39mndim \u001b[39m>\u001b[39m \u001b[39m2\u001b[39m:\n\u001b[1;32m 501\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mx and y can be no greater than 2D, but have \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 502\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mshapes \u001b[39m\u001b[39m{\u001b[39;00mx\u001b[39m.\u001b[39mshape\u001b[39m}\u001b[39;00m\u001b[39m and \u001b[39m\u001b[39m{\u001b[39;00my\u001b[39m.\u001b[39mshape\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n", + "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (170,) and (300,)" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d14759b010784bb6b4d1cf561c4d5b25", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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AACCNAAEAANIIEAAAII0AAQAA0ggQAAAgjQABAADSCBAAACCNAAEAANIIEAAAII0AAQAA0ggQAAAgjQC5hNbW1li6dGnU1tZGXV1dHDp06LLuO3z4cMyePTu+9KUvjfCEAAAwvgiQQezduzeamppi3bp10d7eHgsXLozVq1fH6dOnL3nfBx98EBs3bozPfe5zSZMCAMD4IUAGsXPnzlixYkWsXLkyZs6cGY2NjTF9+vTYtWvXJe976qmn4t57741bbrklZ1AAABhHBMgAent749ixY7F48eJ+54sWLYojR44Met/u3bvj17/+dXzta18b6REBAGBcmjTaA4xFhUIhisViVFVV9Tuvrq6Orq6uAe/51a9+Fc3NzdHa2hqTJl3Zv9ZisRjFYvGKfg3GvvM7tuvyYN/lxb7Li32XF3u+cgLkEiZMmNDv41KpdNFZxB/+h/jYY4/FI488EjfddNMVP+7x48ev+Ndg/Ojo6BjtEUhk3+XFvsuLfcPlESADmDp1alRUVER3d3e/87Nnz0Z1dfVF1/f09MTRo0fjxIkT8a1vfSsiIs6dOxelUilmz54dP/rRj4b0Q+mzZ8+OysrKK3sSjHnFYjE6OjqitrY2KioqRnscRph9lxf7Li/2XV56e3t9sfgKCZABVFZWxpw5c2L//v1x1113XTg/cOBALFu27KLrP/nJT8bPfvazfmcvvvhi/O///m9873vfi8985jNDevyKigp/gJUR+y4v9l1e7Lu82Hd5sOMrJ0AGsWrVqtiwYUPMnTs35s+fHy+//HJ0dnZGfX19REQ0NzfHb37zm3juuedi4sSJUVNT0+/+qqqquPbaay86BwCAciZABrF8+fIoFAqxffv2OHPmTNTU1ERLS0vMmDEjIiK6urqis7NzlKcEAIDxRYBcQkNDQzQ0NAz4ua1bt17y3kceeSQeeeSRkRgLAADGLf8/IAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBAgAApBEgAABAGgECAACkESAAAEAaAQIAAKQRIAAAQBoBcgmtra2xdOnSqK2tjbq6ujh06NCg1/785z+PVatWxW233RYLFiyIBx98MH7xi18kTgsAAGOfABnE3r17o6mpKdatWxft7e2xcOHCWL16dZw+fXrA6w8ePBi33357tLS0xI9//OO49dZbY926dXH8+PHkyQEAYOwSIIPYuXNnrFixIlauXBkzZ86MxsbGmD59euzatWvA6xsbG2P16tVx8803x4033hj/+I//GH/1V38Vr732WvLkAAAwdk0a7QHGot7e3jh27FisWbOm3/miRYviyJEjl/VrnDt3Lnp6emLKlClDfvxisRjFYnHI9zG+nN+xXZcH+y4v9l1e7Lu82POVEyADKBQKUSwWo6qqqt95dXV1dHV1XdavsWPHjvj9738f99xzz5Af37dtlZeOjo7RHoFE9l1e7Lu82DdcHgFyCRMmTOj3calUuuhsIHv27Invf//7sX379osi5nLMnj07Kisrh3wf40uxWIyOjo6ora2NioqK0R6HEWbf5cW+y4t9l5fe3l5fLL5CAmQAU6dOjYqKiuju7u53fvbs2aiurr7kvXv37o3Gxsb47ne/G7fffvuwHr+iosIfYGXEvsuLfZcX+y4v9l0e7PjK+SH0AVRWVsacOXNi//79/c4PHDgQ8+fPH/S+PXv2xOOPPx7Nzc3x+c9/foSnBACA8cc7IINYtWpVbNiwIebOnRvz58+Pl19+OTo7O6O+vj4iIpqbm+M3v/lNPPfccxHxh/jYuHFj/NM//VPMmzfvws+KXHfddTF58uRRex4AADCWCJBBLF++PAqFQmzfvj3OnDkTNTU10dLSEjNmzIiIiK6urujs7Lxw/csvvxx9fX3xzDPPxDPPPHPh/P7774+tW7emzw8AAGORALmEhoaGaGhoGPBzfxwV//Zv/5YxEgAAjGt+BgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AAAIA0AgQAAEgjQAAAgDQCBAAASCNAAACANAIEAABII0AuobW1NZYuXRq1tbVRV1cXhw4duuT1b775ZtTV1UVtbW0sW7Ysdu3alTQpAACMDwJkEHv37o2mpqZYt25dtLe3x8KFC2P16tVx+vTpAa8/depUrFmzJhYuXBjt7e2xdu3a2Lx5c+zbty95cgAAGLsEyCB27twZK1asiJUrV8bMmTOjsbExpk+fPui7Gi+99FJ8+tOfjsbGxpg5c2asXLky6urqYseOHcmTAwDA2CVABtDb2xvHjh2LxYsX9ztftGhRHDlyZMB73nrrrVi0aFG/szvuuCOOHj0aH3300YjNCgAA48mk0R5gLCoUClEsFqOqqqrfeXV1dXR1dQ14T3d3d1RXV/c7q6qqir6+vigUCjFt2rQ/+bilUiki/hBA/PkrFosR8Yd9V1RUjPI0jDT7Li/2XV7su7ycf512/nUbQydALmHChAn9Pi6VShed/anrBzofzLlz5yIi4u233x7KmIxzx48fH+0RSGTf5cW+y4t9l5fzr9sYOgEygKlTp0ZFRUV0d3f3Oz979uxF73KcN9C7I++//35MmjQppkyZclmPO2nSpKitrY2JEydedrQAAJCnVCrFuXPnYtIkL6OHy7+5AVRWVsacOXNi//79cdddd104P3DgQCxbtmzAe2655Zb4r//6r35nb7zxRsydOzeuueaay3rciRMnRmVl5fAHBwCAMc4PoQ9i1apV0dbWFm1tbXHy5MnYsmVLdHZ2Rn19fURENDc3x4YNGy5cX19fH6dPn46mpqY4efJktLW1xe7du+Phhx8eracAAABjjndABrF8+fIoFAqxffv2OHPmTNTU1ERLS0vMmDEjIiK6urqis7PzwvU33HBDtLS0RFNTU7S2tsa0adOisbEx7r777tF6CgAAMOZMKPkRfgAAIIlvwQIAANIIEAAAII0AAQAA0ggQAAAgjQABAADSCJBkra2tsXTp0qitrY26uro4dOjQJa9/8803o66uLmpra2PZsmWxa9eupEm5Goay75///OexatWquO2222LBggXx4IMPxi9+8YvEablSQ/39fd7hw4dj9uzZ8aUvfWmEJ+RqGuq+e3t74/nnn48777wz5s6dG1/4wheira0taVqu1FD3/dOf/jTuu+++mDdvXixevDieeOKJKBQKSdMyXAcPHoy1a9fG4sWLY9asWfHqq6/+yXu8Vhs6AZJo79690dTUFOvWrYv29vZYuHBhrF69Ok6fPj3g9adOnYo1a9bEwoULo729PdauXRubN2+Offv2JU/OcAx13wcPHozbb789Wlpa4sc//nHceuutsW7dujh+/Hjy5AzHUPd93gcffBAbN26Mz33uc0mTcjUMZ9+PPvpo/M///E9s3rw5/vM//zP++Z//Of76r/86cWqGa6j7PnToUGzcuDEeeOCB2LNnT3znO9+Jjo6O+MY3vpE8OUP1u9/9LmbNmhVPPfXUZV3vtdowlUjzwAMPlJ566ql+Z1/84hdL27ZtG/D65557rvTFL36x39mTTz5Z+vu///sRm5GrZ6j7Hsjy5ctL//Iv/3K1R2MEDHff69evLz3//POl733ve6X77rtvJEfkKhrqvl9//fXSwoULS4VCIWE6rrah7vuFF14oLVu2rN/Zv/7rv5b+7u/+bsRm5OqrqakpvfLKK5e8xmu14fEOSJLe3t44duxYLF68uN/5okWL4siRIwPe89Zbb8WiRYv6nd1xxx1x9OjR+Oijj0ZsVq7ccPb9x86dOxc9PT0xZcqUEZiQq2m4+969e3f8+te/jq997WsjPSJX0XD2/dprr8XcuXPjhRdeiDvuuCPuvvvuePbZZ+PDDz/MGJkrMJx9z58/P9577714/fXXo1QqRXd3d+zbty+WLFmSMTKJvFYbnkmjPUC5KBQKUSwWo6qqqt95dXV1dHV1DXhPd3d3VFdX9zurqqqKvr6+KBQKMW3atBGblysznH3/sR07dsTvf//7uOeee0ZiRK6i4ez7V7/6VTQ3N0dra2tMmuSP4vFkOPs+depUHD58OK699tr4wQ9+EIVCIb75zW/Gb3/722hqasoYm2Eazr4XLFgQ27Zti/Xr10dvb2/09fXF0qVL48knn8wYmUReqw2Pd0CSTZgwod/HpVLporM/df1A54xNQ933eXv27Invf//78fz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\n", + " Figure\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "\n", + "# ax = brokenaxes(ylims=((0, 0.25),(0.95, 1.05)), hspace=.2)\n", + "ax = fig.add_subplot(111)\n", + "ax.grid(b=True, which='major')\n", + "\n", + "# - lines style in a for loop\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "lines = ['o', '^', 'v', '<', '>', 's', 'd'] #, '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "# ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "total_w1 = sum(histogram_w1)\n", + "total_w2 = sum(histogram_w2)\n", + "total_w3 = sum(histogram_w3)\n", + "total_w4 = sum(histogram_w4)\n", + "total_w5 = sum(histogram_w5)\n", + "total_w6 = sum(histogram_w6)\n", + "\n", + "ax.plot(\n", + " distribution, \n", + " histogram_w1_nan / total_w1, \n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w1\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + " )\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w2_nan / total_w2,\n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w2\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w3_nan / total_w3,\n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w3\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\",\n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w4_nan / total_w4,\n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w4\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\", \n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w5_nan / total_w5,\n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w5\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\", \n", + ")\n", + "ax.plot(\n", + " distribution,\n", + " histogram_w6_nan / total_w6,\n", + " # \"-\",\n", + " next(linecycler),\n", + " label=\"w6\",\n", + " markersize=8,\n", + " alpha=0.7,\n", + " # color=\"black\",\n", + " # markerfacecolor=\"none\", \n", + ")\n", + "\n", + "plt.xlim(1.9, 2.7)\n", + "# plt.ylim(0.001, 1.1)\n", + "\n", + "ax.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "ax.set_ylabel('Relative Number of Occurrences', fontsize=12)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=12)\n", + "plt.legend(loc=\"upper right\", fontsize=12, ncol=3)" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f13a2e8335d64a26a4a3afa531824175", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " Figure\n", + "
\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "ax = fig.add_subplot(111)\n", + "ax.grid()\n", + "\n", + "# - lines style in a for loop\n", + "lines = ['-o', '-^', '-v', '-<', '->', '-s', '-d'] #, '-h', '-p', '-D', '-H']\n", + "# lines = ['-o', '-^', '-v', '-<', '->', '-s', '-+', '-x', '-d', '-1', '-2', '-3', '-4', '-h', '-p', '-|', '-_', '-D', '-H']\n", + "# lines = [\"-\",\"--\",\"-.\",\":\"]\n", + "linecycler = cycle(lines)\n", + "\n", + "ax.axhline(y=0, color='black', linestyle='-', linewidth=0.7)\n", + "\n", + "\n", + "x = np.linspace(rmin, rmax, nbins)\n", + "smooth_x = np.linspace(x[0], x[-1], len(x) * 100)\n", + "\n", + "y_w1 = histogram_w1\n", + "y_w2 = histogram_w2\n", + "y_w3 = histogram_w3\n", + "y_w4 = histogram_w4\n", + "y_w5 = histogram_w5\n", + "y_w6 = histogram_w6\n", + "\n", + "total_w1 = sum(y_w1)\n", + "total_w2 = sum(y_w2)\n", + "total_w3 = sum(y_w3)\n", + "total_w4 = sum(y_w4)\n", + "total_w5 = sum(y_w5)\n", + "total_w6 = sum(y_w6)\n", + "\n", + "smooth_w1 = make_interp_spline(x, y_w1, k=2)\n", + "smooth_w2 = make_interp_spline(x, y_w2, k=2)\n", + "smooth_w3 = make_interp_spline(x, y_w3, k=2)\n", + "smooth_w4 = make_interp_spline(x, y_w4, k=2)\n", + "smooth_w5 = make_interp_spline(x, y_w5, k=2)\n", + "smooth_w6 = make_interp_spline(x, y_w6, k=2)\n", + "\n", + "smooth_y_w1 = smooth_w1(smooth_x)\n", + "smooth_y_w2 = smooth_w2(smooth_x)\n", + "smooth_y_w3 = smooth_w3(smooth_x)\n", + "smooth_y_w4 = smooth_w4(smooth_x)\n", + "smooth_y_w5 = smooth_w5(smooth_x)\n", + "smooth_y_w6 = smooth_w6(smooth_x)\n", + "\n", + "# ax.plot(\n", + "# smooth_x, \n", + "# smooth_y_w1 / total_w1, \n", + "# \"-\",\n", + "# label=\"w1\",\n", + "# )\n", + "# ax.plot(\n", + "# smooth_x,\n", + "# smooth_y_w2 / total_w2,\n", + "# \"-\",\n", + "# label=\"w2\",\n", + "# )\n", + "ax.plot(\n", + " smooth_x,\n", + " smooth_y_w3 / total_w3,\n", + " \"-\",\n", + " label=\"w3\",\n", + ")\n", + "ax.plot(\n", + " smooth_x,\n", + " smooth_y_w4 / total_w4,\n", + " \"-\",\n", + " label=\"w4\",\n", + ")\n", + "ax.plot(\n", + " smooth_x,\n", + " smooth_y_w5 / total_w5,\n", + " \"-\",\n", + " label=\"w5\",\n", + ")\n", + "ax.plot(\n", + " smooth_x,\n", + " smooth_y_w6 / total_w6,\n", + " \"-\",\n", + " label=\"w6\",\n", + ")\n", + "\n", + "plt.xlim(1.9, 3)\n", + "ax.set_ylabel('Relative Number of Occurrences', fontsize=12)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=12)\n", + "plt.legend(loc=\"upper right\", fontsize=8)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fa04746f520643728b7c1354e0dfa14b", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", + "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "ax = fig.add_subplot(111)\n", + "ax.grid()\n", + "\n", + "# ax.hist(distribution, bins=nbins, weights=histogram_w1, density=True, label=\"w1\", alpha=0.5)\n", + "# ax.hist(distribution, bins=nbins, weights=histogram_w2, density=True, label=\"w2\", alpha=0.5)\n", + "ax.hist(distribution, bins=nbins, weights=histogram_w3, density=True, label=\"w3\", alpha=0.7, stacked=True)\n", + "ax.hist(distribution, bins=nbins, weights=histogram_w4, density=True, label=\"w4\", alpha=0.7, stacked=True)\n", + "ax.hist(distribution, bins=nbins, weights=histogram_w5, density=True, label=\"w5\", alpha=0.7, stacked=True)\n", + "ax.hist(distribution, bins=nbins, weights=histogram_w6, density=True, label=\"w6\", alpha=0.7, stacked=True)\n", + "\n", + "plt.xlim(1.9, 2.7)\n", + "ax.set_ylabel('Number of Occurrences', fontsize=12)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=12)\n", + "plt.legend(loc=\"upper right\", fontsize=8)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9894a703991144909335e82a2593a7c1", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " Figure\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 5))\n", + "# ax = fig.add_subplot(111)\n", + "# ax.grid()\n", + "\n", + "cm = cycle(['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])\n", + "\n", + "# x y w h\n", + "ax1 = fig.add_axes([0.10, 0.70, 0.4, 0.29])\n", + "ax2 = fig.add_axes([0.53, 0.70, 0.4, 0.29])\n", + "ax3 = fig.add_axes([0.10, 0.40, 0.4, 0.29])\n", + "ax4 = fig.add_axes([0.53, 0.40, 0.4, 0.29])\n", + "ax5 = fig.add_axes([0.10, 0.10, 0.4, 0.29])\n", + "ax6 = fig.add_axes([0.53, 0.10, 0.4, 0.29])\n", + "\n", + "ax1.hist(distribution, bins=nbins, weights=histogram_w1, color=next(cm), density=True, label=\"w1\", alpha=0.7)\n", + "ax2.hist(distribution, bins=nbins, weights=histogram_w2, color=next(cm), density=True, label=\"w2\", alpha=0.7)\n", + "ax3.hist(distribution, bins=nbins, weights=histogram_w3, color=next(cm), density=True, label=\"w3\", alpha=0.7)\n", + "ax4.hist(distribution, bins=nbins, weights=histogram_w4, color=next(cm), density=True, label=\"w4\", alpha=0.7)\n", + "ax5.hist(distribution, bins=nbins, weights=histogram_w5, color=next(cm), density=True, label=\"w5\", alpha=0.7)\n", + "ax6.hist(distribution, bins=nbins, weights=histogram_w6, color=next(cm), density=True, label=\"w6\", alpha=0.7)\n", + "\n", + "ax1.set_xlim(1.9, 2.7)\n", + "ax1.set_ylim(0, 2.5)\n", + "ax1.axes.xaxis.set_ticklabels([])\n", + "ax1.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax1.axes.yaxis.set_ticklabels([])\n", + "ax1.legend(loc=\"upper right\", fontsize=10)\n", + "ax1.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "\n", + "ax2.set_xlim(1.9, 2.7)\n", + "ax2.set_ylim(0, 2.5)\n", + "ax2.axes.xaxis.set_ticklabels([])\n", + "ax2.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax2.axes.yaxis.set_ticklabels([])\n", + "ax2.legend(loc=\"upper right\", fontsize=10)\n", + "ax2.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "\n", + "ax3.set_xlim(1.9, 2.7)\n", + "ax3.set_ylim(0, 2.5)\n", + "ax3.axes.xaxis.set_ticklabels([])\n", + "ax3.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax3.axes.yaxis.set_ticklabels([])\n", + "ax3.legend(loc=\"upper right\", fontsize=10)\n", + "ax3.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "\n", + "ax4.set_xlim(1.9, 2.7)\n", + "ax4.set_ylim(0, 2.5)\n", + "ax4.axes.xaxis.set_ticklabels([])\n", + "ax4.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax4.axes.yaxis.set_ticklabels([])\n", + "ax4.legend(loc=\"upper right\", fontsize=10)\n", + "ax4.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "\n", + "ax5.set_xlim(1.9, 2.7)\n", + "ax5.set_ylim(0, 2.5)\n", + "ax5.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax5.axes.yaxis.set_ticklabels([])\n", + "ax5.legend(loc=\"upper right\", fontsize=10)\n", + "ax5.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=10)\n", + "ax5.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "\n", + "ax6.set_xlim(1.9, 2.7)\n", + "ax6.set_ylim(0, 2.5)\n", + "ax6.xaxis.set_major_locator(ticker.MultipleLocator(0.5))\n", + "ax6.axes.yaxis.set_ticklabels([])\n", + "ax6.legend(loc=\"upper right\", fontsize=10)\n", + "ax6.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=10)\n", + "ax6.xaxis.set_major_locator(MultipleLocator(0.1))\n", + "\n", + "# ax.set_ylabel('Number of Occurrences', fontsize=10)\n", + "# ax.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=10)\n", + "# plt.legend(loc=\"upper right\", fontsize=10)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/edison/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "275262ba8db74574bd2edfca4c261ffc", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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number of bins for the accurences\n", + "rmin, rmax, dr = grid\n", + "nbins = int((rmax - rmin) / dr)\n", + "\n", + "distribution = np.linspace(rmin, rmax, nbins)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 2, 1, 0, 1, 0, 0, 0, 2, 0, 1, 0, 0, 2, 0, 0, 4, 2,\n", + " 0, 3, 2, 1, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1,\n", + " 0, 0, 0, 1, 0, 0, 4, 1, 7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1,\n", + " 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,\n", + " 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "histogram_w6" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "ename": "IndexError", + "evalue": "index 172 is out of bounds for axis 0 with size 170", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/edison/repositories/radial_distribution/analysis_RDA.ipynb Cell 18'\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[39mcontinue\u001b[39;00m\n\u001b[1;32m 19\u001b[0m \u001b[39mfor\u001b[39;00m _ \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39mint\u001b[39m(occurrence)):\n\u001b[0;32m---> 20\u001b[0m new_histogram\u001b[39m.\u001b[39mappend(distribution[count])\n\u001b[1;32m 22\u001b[0m new_histogram_dict[name] \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(new_histogram)\n", + "\u001b[0;31mIndexError\u001b[0m: index 172 is out of bounds for axis 0 with size 170" + ] + } + ], + "source": [ + "new_histogram_dict = {}\n", + "\n", + "histograms: list =[\n", + " histogram_w1,\n", + " histogram_w2,\n", + " histogram_w3,\n", + " histogram_w4,\n", + " histogram_w5,\n", + " histogram_w6,\n", + "]\n", + "for water, hist in enumerate(histograms):\n", + " name = f\"histogram_w{water + 1}\"\n", + "\n", + " new_histogram = []\n", + " for count, occurrence in enumerate(hist):\n", + " if occurrence == 0:\n", + " continue\n", + "\n", + " for _ in range(int(occurrence)):\n", + " new_histogram.append(distribution[count])\n", + " \n", + " new_histogram_dict[name] = np.array(new_histogram)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/edison/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n", + " warnings.warn(msg, FutureWarning)\n", + "/home/edison/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n", + " warnings.warn(msg, FutureWarning)\n", + "/home/edison/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n", + " warnings.warn(msg, FutureWarning)\n", + "/home/edison/anaconda3/envs/openmm_py38/lib/python3.8/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "515a45c00605411b994371381d58ef01", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "\n", + "plt.figure(figsize=(8, 5))\n", + "\n", + "sns.set_style('whitegrid')\n", + "\n", + "# sns.distplot(new_histogram_dict[\"histogram_w1\"], hist=False, label=\"w1\")\n", + "# sns.distplot(new_histogram_dict[\"histogram_w2\"], hist=False, label=\"w2\")\n", + "sns.distplot(new_histogram_dict[\"histogram_w3\"], hist=False, label=\"w3\") #, bins=len(new_histogram_dict[\"histogram_w3\"]))\n", + "sns.distplot(new_histogram_dict[\"histogram_w4\"], hist=False, label=\"w4\") #, bins=len(new_histogram_dict[\"histogram_w4\"]))\n", + "sns.distplot(new_histogram_dict[\"histogram_w5\"], hist=False, label=\"w5\") #, bins=len(new_histogram_dict[\"histogram_w5\"]))\n", + "sns.distplot(new_histogram_dict[\"histogram_w6\"], hist=False, label=\"w6\") #, bins=len(new_histogram_dict[\"histogram_w6\"]))\n", + "\n", + "# plt.xlim(1.9, 4.6)\n", + "ax.set_ylabel('Number of Occurrences', fontsize=12)\n", + "ax.set_xlabel(f'Distance {\"-\".join(atoms_list_HgO)}'r\" [$\\AA$]\", fontsize=12)\n", + "plt.legend(loc=\"upper right\", fontsize=8)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "interpreter": { + "hash": "c1ba9d3c0a03acbe4d4d1326c45506f86eeb7a55b6666e00094e020e60f32bf8" + }, + "kernelspec": { + "display_name": "Python 3.8.12 64-bit ('helico-base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/angle.py b/angle.py new file mode 100644 index 0000000..093d7b5 --- /dev/null +++ b/angle.py @@ -0,0 +1,67 @@ +import pandas as pd +import numpy as np + +dfxyz =\ + pd.DataFrame(np.transpose([['A','B','A','C','C','C'],\ + [0.,2.,3.,0.,1.,2.],[0.,0.,1.,0.,5.,0.],[0.,1.,0.,2.,1.,4.]]),\ + columns=['atom','x','y','z']) + +df =\ + pd.DataFrame(\ + np.transpose([['A','B','A','C','C','C'],\ + [0.0,2.24,3.16,2.00,5.20,4.47],[2.24,0.0,1.73,2.24,5.10,3.00],[3.16,1.73,0.0,3.74,4.58,4.24]]),\ + columns=['atom','A','B','A']) + +ncols = len(df.iloc[0,:]) +nrows = len(df.iloc[:,0]) +for icol in range(ncols): + if df.columns[icol] == 'A': #filtro por label del átomo del vertice + vector_vertice=df.iloc[:, [0,icol]].sort_values(by=['A']) + print('\nDistancias con respecto al vertice seleccionado \n',vector_vertice,'\n') + #Se cuenta desde el segundo átomo, ya se sabe quien es el verice, además el segundo átomo se + #empareja con todos los posibles átomos que están a menos de 3 al verice como el segundo átomo + irow_atom1 = 1 + while irow_atom1 < nrows and float(vector_vertice.iloc[irow_atom1+1,1]) < 3. : + #Número de línea del átomo 1 de interes en el dataframe con las coordenadas + nline_atom1_xyz= vector_vertice.index.values[irow_atom1] + #theta = cos^{-1}(A . B/(|A||B|)) + #Coordenadas del primer átomo a una distancia máxima de 3 al verice + A1 = np.zeros((3),dtype=float) + A1[0]=dfxyz.iloc[nline_atom1_xyz,1] + A1[1]=dfxyz.iloc[nline_atom1_xyz,2] + A1[2]=dfxyz.iloc[nline_atom1_xyz,3] + #contador del 2 atomo al vertice + irow_atom2 = irow_atom1 + 1 + #Filtro por distancia máxima + while irow_atom2 < nrows and float(vector_vertice.iloc[irow_atom2,1]) < 3. : + #Número de línea del átomo 2 de interes en el dataframe con las coordenadas + nline_atom2_xyz= vector_vertice.index.values[irow_atom2] + #Coordenadas del segundo átomo a una distancia máxima de 3 al verice + A2 = np.zeros((3),dtype=float) + A2[0]=dfxyz.iloc[nline_atom2_xyz,1] + A2[1]=dfxyz.iloc[nline_atom2_xyz,2] + A2[2]=dfxyz.iloc[nline_atom2_xyz,3] + A1pA2 = np.dot(A1,A2) + #cos(theta) + costheta =\ + A1pA2/(float(vector_vertice.iloc[irow_atom1,1])\ + *float(vector_vertice.iloc[irow_atom2,1])) + #theta + theta = np.arccos(costheta) + #atomo con indice A1--A0(vertice)--A2 + label_A1 = str(vector_vertice.iloc[irow_atom1,0])\ + + str(vector_vertice.index.values[irow_atom1]) + label_A0 = str(vector_vertice.iloc[0,0])\ + + str(vector_vertice.index.values[0]) + label_A2 = str(vector_vertice.iloc[irow_atom2,0])\ + + str(vector_vertice.index.values[irow_atom2]) + print('Angulo entre (',label_A1,',',label_A0,',',label_A2,') : ',theta) + irow_atom2 += 1 + else: + irow_atom2 = nrows + print('\n No hay un segundo átomo a 3 al vertice ',str(vector_vertice.iloc[0,0])\ + + str(vector_vertice.index.values[0])) + irow_atom1 += 1 + else: + if irow_atom1 == 1: + print('\n No hay 2 átomos que estén a una distancia inferior de 3 al vertice') diff --git a/atoms_index_list.py b/atoms_index_list.py new file mode 100644 index 0000000..acb86a4 --- /dev/null +++ b/atoms_index_list.py @@ -0,0 +1,213 @@ +#!/usr/bin/env python3 +# ------------------------------------------------------------------------------------ +# July 2020 +# +# python3.x script by: +# +# name: Edison Florez (github.com/e-florez/) +# email: edisonffh@gmail.com + +# ------------------------------------------------------------------------------------ +# Main body +# ------------------------------------------------------------------------------------ + +def neighbors_atoms_pair(distance_matrix, input_pair, rmin, rmax): + import pandas as pd + + """ + Finding pair of atoms, neighborhood definded by rmin and rmax + + Args: + distance (dict): dict with a matrix distance for each XYZ file + input_pair (list [str]): pair of atoms to get the bond distance analysis + grid (3D tuple [float]): min and max distance and bind width to do the histogram + + Return: + atoms_pair (list of 2D tuples [int]): list of atoms pair with a distance between rmin and rmax + """ + + # - distances matrix (no atoms or labels) + df_dist = distance_matrix.loc[:, distance_matrix.columns != 'atoms'] + + # - filtering atoms labels (one column) + df_label = distance_matrix.loc[:, distance_matrix.columns == 'atoms'] + + # - filtering for the each atom from the input pair + df_first_atom = df_label[df_label['atoms'] == input_pair[0]] + df_second_atom = df_label[df_label['atoms'] == input_pair[1]] + + # - getting the index (in tuples) + first_atom = tuple(df_first_atom.index) + second_atom = tuple(df_second_atom.index) + + # - checking what pairs are into rmin, rmax + atoms_pair = [] + for atom_a in first_atom: + for atom_b in second_atom: + distance = df_dist.iloc[atom_a, atom_b] + + if (rmin <= distance) and (distance <= rmax): + atoms_pair.append((atom_a, atom_b)) + + return atoms_pair +# --------------------------------------------------------------------------------------- + + +def atoms_index_list(distances, input_list, grid): + """ + For a list of max 4 elements: bond distance [A, B]; bond angle [A, B, C]; and + dihedral angle [A, B, C, D], we split every list in pairs and compute which of them + are into rmin, rmax. + + WARNING: input_list order MATTER! [A, B, C] != [A, C, B] + + For instance, + input: [A, B, C] splits into [A, B] and [B, C] to find neighbors and returns + atoms index for those between rmin, rmax + + Args: + distance (dataframe): distances matrix for each XYZ file + input_list (list [str]): list of atoms to define neighbors + grid (3D tuple [float]): min and max distance and bind width to do the histogram + + + Return: + + """ + rmin, rmax, dr = grid + + # - max number of elements is four; two for bond, three for angle an d three for dihedral + input_list = input_list[:4] + + # - list of indexes + list_atoms_index = [] + + # - splitting list into pair; i.e., for + # bond: [A, B] we get one pair [A, B] + # angle: [A, B, C] we get two pairs [A, B] and [B, C] (B as a pivot) + # dihedral: [A, B, C, D] we get three pairs [A, B], [B, C] and [B, D] (B as a pivot) + + # - max number of pair + max_pair = range(len(input_list) - 1) + + n = 0 + for n in max_pair: + if n < 2: + pair = [input_list[n], input_list[n+1]] + else: + # - only for dihedral [A, B, C, D] + # to get [A, B]; [B, C]; [B, D] (instead of [C, D]) + pair = [input_list[n-1], input_list[n+1]] + + # - computing list of pair into a region + atoms_pair = neighbors_atoms_pair(distances, pair, rmin, rmax) + + # - list of lists (max 3 lists), for each pair we have a list of index + list_atoms_index.append(atoms_pair) + + #-------------------------------- + # - groupping these indexes + + # - list of tuples to compute distances, angle or dihedrals + index_to_return = [] + + # - avoiding equivalent trends; i.e., + # [A, B] is equivalent to [B, A] + # [A, B, C] is equivalent to [C, B, A] + # [A, B, C, D] is equivalent to [A, B, D, C] + duplicates_list = [] + + # - bond distance: only ONE list of pair is given + # e.g. [A, B] gives [(1, 2), (2, 3), (5,6), ...] (only one list of several tuples) + if len(list_atoms_index) == 1: + + # - avoiding duplicates + for pair in list_atoms_index[0]: + atoms_index = [pair[0], pair[1]] + atoms_index_rev = [pair[1], pair[0]] + + if atoms_index not in duplicates_list: + duplicates_list.append(atoms_index) + duplicates_list.append(atoms_index_rev) + index_to_return.append(tuple(atoms_index)) + + return index_to_return + + # - Angle: [A, B, C] we'd have TWO list of several tuple, one for [A, B] and another for [B, C] + # first list has a key atom (pivot); 'B' is pivot atom (which defines the angle) + for first_pair in list_atoms_index[0]: + # for [A, B] (first_pair), left_atom: 'A', pivot_atom: 'B' + left_atom = first_pair[0] + pivot_atom = first_pair[1] + + # - looking for connection through pivot atom. + for pair1 in list_atoms_index[1]: + + # - for pair [B, C], then pivot must be iqual to 'B' + # and left_atom must not be iqual to C + if (pivot_atom == pair1[0] and left_atom != pair1[1]): + atoms_index = [left_atom, pivot_atom, pair1[1]] + atoms_index_rev = [pair1[1], pivot_atom, left_atom] + + # - avoiding duplicates + if atoms_index not in duplicates_list: + duplicates_list.append(atoms_index) + duplicates_list.append(atoms_index_rev) + index_to_return.append(tuple(atoms_index)) + + # - at this point we have triplets for angles + if len(list_atoms_index) > 2: + # - if we ask for dihedrals + # - clearing variables for dihedrals + duplicates_list = [] + triplet_index = list(index_to_return) + index_to_return = [] + else: + # - no dihedrals, then returns triplet to get only bond angle + return index_to_return + + # - Dihedral: [A, B, C, D] we'd have THREE list of several tuple, + # one for [A, B], one for [B, C] and another one for [B, D] + # 'B' is pivot atom (which defines the angle) + for triplet in triplet_index: + # - triplets: [A, B, C] + left = triplet[0] + pivot = triplet[1] + right = triplet[2] + + for pair in list_atoms_index[2]: + if (pivot == pair[0] and left != pair[1] and right != pair[1]): + atoms_index = [left, pivot, right, pair[1]] + atoms_index_rev = [left, pivot, pair[1], right] + + # - avoiding duplicates + if atoms_index not in duplicates_list: + duplicates_list.append(atoms_index) + duplicates_list.append(atoms_index_rev) + index_to_return.append(tuple(atoms_index)) + + return index_to_return +# --------------------------------------------------------------------------------------- + + +def atoms_index_dict(distances_dict, input_list, grid): + """ + + Args: + + Return: + + """ + # - loop over each XYZ file to get atoms index + index_dict = {} + for xyz in distances_dict: + distances = distances_dict[xyz] + + # - getting atoms list to compute distance, angle or dihedral + atoms_index = atoms_index_list(distances, input_list, grid) + + # - dictionary with atoms index according to input list + index_dict[xyz] = atoms_index + + return index_dict +# --------------------------------------------------------------------------------------- diff --git a/atoms_transfer.py b/atoms_transfer.py new file mode 100644 index 0000000..4e466aa --- /dev/null +++ b/atoms_transfer.py @@ -0,0 +1,99 @@ +#!/usr/bin/env python3 + +# ------------------------------------------------------------------------------------ +# python3.x function to analyse atom transfer according to Stern-Limbach +# +# A - X - B +# r1 = r[AX] and r2 = r[XB] +# +# this function compute q1 = 0.5 * (r1 - r2) and q2 = r1 + r2 +# +# see DOI: 10.1560/IJC.49.2.199 or DOI: 10.1098/rsif.2013.0518 +# +# *** February 2021 by particula94h@gmail.com *** +# ------------------------------------------------------------------------------------ + + +def stern_limbach(index_dict, input_list, distances_dict): + import pandas as pd + import numpy as np + + """ + *** September 2020 by particula94h@gmail.com *** + + python3.x function to analyse atom transfer according to Stern-Limbach + see DOI: 10.1560/IJC.49.2.199 or DOI: 10.1098/rsif.2013.0518 + + for a list of three atoms A - X - B + r1 = r[AX] and r2 = r[XB] + + this function compute q1 = 0.5 * (r1 - r2) and q2 = r1 + r2 + + Args: + transfer_list ([list, str]): List of three atoms A-X-B (order matters!) to make the analysis + header_distance_matrix (list, str): List of atoms for the distance matrix + data_xyz (Pandas data frame): data frame with the symbols and XYZ coordinates for each XYZ file + distance_matrix (numpy matrix, float): distance matrix + + Returns: + natural_bond_coordinates [(q1, q2) type: floats]: list of tuples q1, q2 (floats) + """ + + coordinates_q1 = [] + coordinates_q2 = [] + + for xyz in index_dict: + indexes = index_dict[xyz] + distances_df = distances_dict[xyz] + + # - distances matrix (no atoms or labels) + distances_df = distances_df.loc[:, distances_df.columns != "atoms"] + + for pair in indexes: + r1 = distances_df.iloc[pair[0], pair[1]] + r2 = distances_df.iloc[pair[1], pair[2]] + + # - atoms transfer analysis compute q1 = 0.5 * (r1 - r2) and q2 = r1 + r2 + # q1 = np.abs(0.5 * (r2 - r1)) + # q1 = 0.5 * (r1 - r2) + # q2 = r1 + r2 + + # coordinates_q1.append(-np.abs(0.5 * (r1 - r2))) + coordinates_q1.append(0.5 * (r1 - r2)) + coordinates_q2.append(r1 + r2) + + return {"q1": coordinates_q1, "q2": coordinates_q2} + + +def atom_transfer(index_dict, input_list, distances_dict): + import numpy as np + + """[summary] + """ + + input_list = list(input_list) + + natural_bond_coordinates = stern_limbach(index_dict, input_list, distances_dict) + + triplets = "-".join(input_list) + transfer_name = "transfer_" + "-".join(input_list) + ".dat" + + print(f"") + print( + f"Atoms transfer analysis ({triplets}) according to Stern-Limbach model (q1, q2):" + ) + print( + f"Transfer of atoms {input_list[1]} " + + f"between {input_list[0]} and {input_list[2]}, " + + f"where q1=0.5*(r1-r2) and q2=r1+r2, " + + f"r1: distance[{input_list[0]}{input_list[1]}] and r2: distance[{input_list[1]}{input_list[2]}]" + ) + print(f"") + + np.savetxt( + transfer_name, + natural_bond_coordinates, + delimiter=" ", + header="q1 [Angstrom] q2 [Angstrom]", + fmt="%15.10f %15.10f", + ) diff --git a/aw1s1.xyz b/aw1s1.xyz deleted file mode 100644 index ebf39a5..0000000 --- a/aw1s1.xyz +++ /dev/null @@ -1,6 +0,0 @@ - 4 - file -Hg aaaa 0.0000000026 0.0107392362 -O 1.8213760892 0.0000000800 -0.0901652030 -H -0.7989195366 0.1773102636 -H 2.3259447157 0.7989197348 0.1773102636 diff --git a/bw1s1.xyz b/bw1s1.xyz deleted file mode 100644 index a12b584..0000000 --- a/bw1s1.xyz +++ /dev/null @@ -1,6 +0,0 @@ - 4 - file 'w1s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- -14 -0.2251299774 0.0000000026 0.0107392362 -au 1.8213760892 0.0000000800 -0.0901652030 -100 2.3259447762 -0.7989195366 0.1773102636 -12 2.3259447157 0.7989197348 0.1773102636 diff --git a/ca/ada_O-H-O.dat b/ca/ada_O-H-O.dat new file mode 100644 index 0000000..6acc441 --- /dev/null +++ b/ca/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=69) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 0 +118.108108 0 +123.243243 0 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 0 +148.918919 2 +154.054054 5 +159.189189 10 +164.324324 19 +169.459459 0 +174.594595 20 +179.729730 12 +184.864865 1 +190.000000 0 diff --git a/ca/transfer_O-H-O.dat b/ca/transfer_O-H-O.dat new file mode 100644 index 0000000..058fd7d --- /dev/null +++ b/ca/transfer_O-H-O.dat @@ -0,0 +1,70 @@ +# q1 [Angstrom] q2 [Angstrom] + -0.4107449087 2.7900463260 + 0.4107486827 2.7900543970 + 0.2529334599 2.5425280117 + -0.2801673596 2.5764928551 + -0.2801583503 2.5764815319 + 0.4234789260 2.8096904625 + 0.4233994097 2.8095467340 + -0.2773706667 2.5714364635 + -0.2666519092 2.5583331291 + 0.2666521271 2.5583337570 + -0.2667333801 2.5579940852 + 0.2668012962 2.5580872562 + -0.3058632336 2.6096714675 + -0.3058587508 2.6096640549 + -0.3461529931 2.6842212960 + -0.3461924698 2.6842898162 + 0.3044596634 2.6106376584 + -0.2467566367 2.5368730605 + -0.2467081536 2.5368070026 + -0.4731227403 2.8931508158 + 0.4731710167 2.8932336705 + -0.4306773018 2.8194771132 + -0.4306508642 2.8194309563 + 0.4284991092 2.8172867162 + 0.4274179518 2.8152469828 + -0.2862603990 2.5825197995 + 0.4065442779 2.7788035664 + 0.4904338660 2.9275399284 + -0.4065610983 2.7788345643 + -0.4903986281 2.9274734709 + 0.2892823974 2.5863261007 + -0.2892773752 2.5863194042 + 0.5187448109 2.9810551773 + 0.3905332152 2.7509307090 + -0.3013471495 2.6006385187 + -0.3165237165 2.6270838432 + 0.3605412848 2.7043316333 + 0.3605423562 2.7043410388 + -0.3241805352 2.6379808770 + 0.3138579465 2.6328092644 + 0.4486830351 2.8553939413 + -0.2945235832 2.5911066472 + -0.4133826556 2.7874083921 + 0.2288006390 2.5164878282 + -0.3571803697 2.6871056030 + 0.4133821700 2.7874078652 + -0.2288346942 2.5165243394 + -0.4338446139 2.8216564543 + -0.4392226993 2.8320482946 + -0.3073284311 2.6102392917 + -0.4349157088 2.8256074058 + 0.4352472584 2.8263345535 + 0.3215675461 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2.981938000 0.000201000 -0.163547000 +O 2.226259000 0.000838000 -0.813927000 +H 2.653320000 0.001446000 -1.680435000 +H 1.003837000 1.170932000 -0.549484000 +O 0.104641000 1.538397000 -0.350147000 +H 0.190286000 2.498922000 -0.377581000 +H 4.705605000 0.761114000 1.181592000 +O 4.157546000 -0.000824000 0.965638000 +H 4.705052000 -0.763429000 1.180638000 +H -4.424957000 0.757871000 0.611522000 +O -3.831833000 -0.000547000 0.513119000 +H -4.413272000 -0.759290000 0.664484000 +H 1.003933000 -1.169853000 -0.551654000 +O 0.104658000 -1.537725000 -0.353409000 +H 0.189667000 -2.498161000 -0.385480000 +Ca -1.534279000 -0.000043000 0.018988000 diff --git a/ca/w6s1-Ca.xyz b/ca/w6s1-Ca.xyz new file mode 100644 index 0000000..d4cb263 --- /dev/null +++ b/ca/w6s1-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -2.378790000 -0.950755000 1.719950000 +O -1.538227000 -0.480476000 1.775425000 +H -1.457597000 -0.247084000 2.708065000 +H -1.450444000 -2.037637000 -1.806366000 +O -1.450818000 -1.106010000 -1.555652000 +H -2.167887000 -0.720823000 -2.073560000 +H 0.921553000 -2.735744000 1.088368000 +O 1.130654000 -2.071718000 0.420438000 +H 1.898469000 -2.431281000 -0.039949000 +H -0.920350000 2.736571000 -1.088405000 +O -1.130341000 2.072404000 -0.420890000 +H -1.898651000 2.432009000 0.038647000 +H 1.458438000 0.244168000 -2.707566000 +O 1.539270000 0.477483000 -1.774926000 +H 2.380230000 0.947051000 -1.719448000 +H 2.167279000 0.723567000 2.073357000 +O 1.449797000 1.107917000 1.555399000 +H 1.448549000 2.039616000 1.805843000 +Ca -0.000174000 0.000177000 0.000136000 diff --git a/ca/w6s11-Ca.xyz b/ca/w6s11-Ca.xyz new file mode 100644 index 0000000..b42b712 --- /dev/null +++ b/ca/w6s11-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 3.685512000 -0.000282000 -0.287334000 +O 2.900668000 -0.000027000 -0.898781000 +H 3.284819000 -0.000173000 -1.784705000 +H 1.681191000 -1.175508000 -0.567165000 +O 0.793727000 -1.537461000 -0.321648000 +H 0.877940000 -2.497936000 -0.331040000 +H 5.481766000 0.761217000 0.980210000 +O 4.924783000 -0.000774000 0.789565000 +H 5.481731000 -0.762961000 0.979526000 +H -5.563463000 -0.764464000 -0.642777000 +O -4.990409000 -0.000998000 -0.507884000 +H -5.563763000 0.762064000 -0.643787000 +H 0.878512000 2.498442000 -0.331463000 +O 0.794081000 1.537988000 -0.321880000 +H 1.681446000 1.175794000 -0.567381000 +H -3.779298000 -0.000067000 0.520547000 +O -2.928494000 0.000450000 1.050628000 +H -3.212227000 0.000821000 1.972688000 +Ca -0.844451000 0.000481000 0.119134000 diff --git a/ca/w6s14-Ca.xyz b/ca/w6s14-Ca.xyz new file mode 100644 index 0000000..30914f7 --- /dev/null +++ b/ca/w6s14-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -0.224409000 4.220008000 0.704863000 +O -0.465630000 3.657815000 -0.039192000 +H -0.526597000 4.257963000 -0.790277000 +H 4.752263000 0.313112000 1.272813000 +O 4.240367000 -0.443673000 0.969546000 +H 4.825354000 -1.197799000 1.096350000 +H 2.707123000 -0.242511000 -1.677930000 +O 2.282939000 -0.338761000 -0.816396000 +H 3.036929000 -0.368755000 -0.172613000 +H 0.909688000 0.876983000 -0.423829000 +O -0.019564000 1.087800000 -0.204974000 +H -0.105033000 2.077152000 -0.155823000 +H -4.379261000 -0.154220000 0.726685000 +O -3.740064000 -0.852071000 0.526783000 +H -4.267243000 -1.661389000 0.578706000 +H 0.446750000 -2.950211000 -0.609752000 +O 0.278632000 -2.008615000 -0.490526000 +H 1.142739000 -1.541288000 -0.656698000 +Ca -1.446587000 -0.622450000 0.027279000 diff --git a/ca/w6s2-Ca.xyz b/ca/w6s2-Ca.xyz new file mode 100644 index 0000000..fcd81d0 --- /dev/null +++ b/ca/w6s2-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -2.194768000 -1.232226000 -2.263267000 +O -1.344542000 -1.290927000 -1.810355000 +H -0.870552000 -1.983340000 -2.287481000 +H 2.112940000 1.335262000 -0.052612000 +O 1.168057000 1.583504000 -0.044305000 +H 1.150910000 2.546866000 -0.059537000 +H 1.480491000 -2.341690000 0.413472000 +O 1.362869000 -1.413885000 0.181150000 +H 2.265031000 -1.045697000 0.112722000 +H -1.297434000 -0.568074000 2.943223000 +O -1.619199000 -0.680933000 2.039749000 +H -2.432083000 -1.190854000 2.146708000 +H 4.163459000 0.222897000 -0.820742000 +O 3.595776000 0.238071000 -0.038930000 +H 4.218124000 0.331421000 0.694392000 +H -2.393995000 2.162067000 -1.143793000 +O -2.240217000 1.606970000 -0.369221000 +H -2.913946000 1.894510000 0.259638000 +Ca -0.533506000 -0.023677000 0.019628000 diff --git a/ca/w6s4-Ca.xyz b/ca/w6s4-Ca.xyz new file mode 100644 index 0000000..c23dfdd --- /dev/null +++ b/ca/w6s4-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -2.769120000 -0.694393000 0.621800000 +O -2.062888000 -0.148906000 1.068194000 +H -2.383729000 -0.020567000 1.968122000 +H 2.182322000 0.892898000 2.121714000 +O 1.881926000 0.464186000 1.311829000 +H 2.627491000 -0.094748000 1.015197000 +H -1.366662000 3.112047000 -0.821031000 +O -0.536840000 2.618550000 -0.852873000 +H 0.060852000 3.201047000 -1.339238000 +H 3.793528000 -2.128816000 0.311946000 +O 3.544686000 -1.276227000 -0.069666000 +H 4.361744000 -0.962620000 -0.480186000 +H 1.999895000 -1.209696000 -1.082499000 +O 1.092034000 -0.939010000 -1.325079000 +H 0.898637000 -1.385772000 -2.157421000 +H -4.635944000 -1.238960000 -0.581355000 +O -3.791275000 -1.574950000 -0.261267000 +H -3.949478000 -2.511198000 -0.096299000 +Ca -0.092034000 0.494582000 0.077507000 diff --git a/ca/w6s5-Ca.xyz b/ca/w6s5-Ca.xyz new file mode 100644 index 0000000..39649e0 --- /dev/null +++ b/ca/w6s5-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -2.786509000 3.358292000 0.541570000 +O -2.351747000 2.884858000 -0.175789000 +H -2.724588000 3.264059000 -0.978882000 +H -1.766560000 1.361831000 -0.057307000 +O -1.300419000 0.488185000 0.013343000 +H -1.987586000 -0.197279000 0.038820000 +H 1.781548000 1.148019000 2.676141000 +O 2.135039000 0.737560000 1.876058000 +H 3.086161000 0.696317000 2.040673000 +H -3.053589000 -2.404825000 0.828623000 +O -2.546857000 -2.105353000 0.062482000 +H -3.066335000 -2.418058000 -0.689690000 +H -0.783872000 -2.417689000 0.051192000 +O 0.184383000 -2.256500000 0.051504000 +H 0.597122000 -3.124548000 0.125600000 +H 2.396437000 -0.185162000 -2.642529000 +O 2.292811000 0.365949000 -1.855638000 +H 2.850340000 1.133499000 -2.038584000 +Ca 0.907587000 -0.056602000 0.016434000 diff --git a/ca/w6s6-Ca.xyz b/ca/w6s6-Ca.xyz new file mode 100644 index 0000000..c5b9933 --- /dev/null +++ b/ca/w6s6-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 3.500566000 -2.477345000 -0.403239000 +O 2.648567000 -2.635118000 0.018023000 +H 2.756252000 -3.474733000 0.478324000 +H -1.783443000 -0.155143000 2.858864000 +O -1.550401000 -0.698436000 2.094818000 +H -1.666589000 -1.604103000 2.409872000 +H -0.418533000 2.983784000 0.125726000 +O 0.060893000 2.149229000 0.072091000 +H 1.023024000 2.414976000 0.057524000 +H 1.249757000 -2.136227000 -0.607890000 +O 0.380505000 -1.764049000 -0.926426000 +H 0.156516000 -2.295837000 -1.698671000 +H 3.100358000 3.019759000 0.789389000 +O 2.605650000 2.708787000 0.023182000 +H 3.047386000 3.111295000 -0.732717000 +H -3.649182000 -0.118444000 -1.022995000 +O -2.775738000 0.225818000 -1.250519000 +H -2.919792000 0.687313000 -2.086939000 +Ca -0.767606000 0.007743000 -0.020830000 diff --git a/ca/w6s8-Ca.xyz b/ca/w6s8-Ca.xyz new file mode 100644 index 0000000..ebf7028 --- /dev/null +++ b/ca/w6s8-Ca.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 3.214751000 3.329590000 0.763281000 +O 2.813176000 2.900372000 -0.000020000 +H 3.214961000 3.329507000 -0.763257000 +H -2.545004000 2.094254000 0.001341000 +O -2.383896000 1.143244000 0.000627000 +H -3.296452000 0.730852000 0.000446000 +H 2.451387000 -0.176638000 0.000175000 +O 1.767157000 0.512592000 -0.000055000 +H 2.237302000 1.390790000 -0.000015000 +H 1.194394000 -2.420344000 0.000101000 +O 0.227656000 -2.241628000 -0.000114000 +H -0.203418000 -3.104374000 -0.000086000 +H -5.237076000 -0.159328000 -0.763227000 +O -4.650232000 -0.110613000 -0.000001000 +H -5.236901000 -0.160409000 0.763290000 +H 3.457962000 -2.432175000 -0.758837000 +O 2.949096000 -2.118423000 0.000428000 +H 3.457673000 -2.432047000 0.759941000 +Ca -0.424662000 -0.033702000 -0.000504000 diff --git a/check_format.xyz b/check_format.xyz deleted file mode 100644 index 0953bb2..0000000 --- a/check_format.xyz +++ /dev/null @@ -1,8 +0,0 @@ -6 - -h 0.000 0.000 0.000 -o 1.000 0.000 0.200 -hg 1.000 3.000 0.300 -c 2.000 0.500 0.400 -n 1.500 3.300 0.500 -f 3.500 0.000 0.600 \ No newline at end of file diff --git a/dada_C52-C53-C54-H13.dat b/dada_C52-C53-C54-H13.dat new file mode 100644 index 0000000..8749a52 --- /dev/null +++ b/dada_C52-C53-C54-H13.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=0) +0.000000 0 +5.070423 0 +10.140845 0 +15.211268 0 +20.281690 0 +25.352113 0 +30.422535 0 +35.492958 0 +40.563380 0 +45.633803 0 +50.704225 0 +55.774648 0 +60.845070 0 +65.915493 0 +70.985915 0 +76.056338 0 +81.126761 0 +86.197183 0 +91.267606 0 +96.338028 0 +101.408451 0 +106.478873 0 +111.549296 0 +116.619718 0 +121.690141 0 +126.760563 0 +131.830986 0 +136.901408 0 +141.971831 0 +147.042254 0 +152.112676 0 +157.183099 0 +162.253521 0 +167.323944 0 +172.394366 0 +177.464789 0 +182.535211 0 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/dada_H3-C57-C58-H8.dat b/dada_H3-C57-C58-H8.dat new file mode 100644 index 0000000..ffd6ed8 --- /dev/null +++ b/dada_H3-C57-C58-H8.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.070423 0 +10.140845 0 +15.211268 0 +20.281690 0 +25.352113 0 +30.422535 0 +35.492958 0 +40.563380 0 +45.633803 0 +50.704225 0 +55.774648 1 +60.845070 0 +65.915493 0 +70.985915 0 +76.056338 0 +81.126761 0 +86.197183 0 +91.267606 0 +96.338028 0 +101.408451 0 +106.478873 0 +111.549296 0 +116.619718 0 +121.690141 0 +126.760563 0 +131.830986 0 +136.901408 0 +141.971831 0 +147.042254 0 +152.112676 0 +157.183099 0 +162.253521 0 +167.323944 0 +172.394366 0 +177.464789 0 +182.535211 0 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/dada_H5-C59-C57-C58.dat b/dada_H5-C59-C57-C58.dat new file mode 100644 index 0000000..78bc45c --- /dev/null +++ b/dada_H5-C59-C57-C58.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.070423 0 +10.140845 0 +15.211268 0 +20.281690 0 +25.352113 0 +30.422535 0 +35.492958 0 +40.563380 0 +45.633803 0 +50.704225 0 +55.774648 0 +60.845070 0 +65.915493 0 +70.985915 0 +76.056338 1 +81.126761 0 +86.197183 0 +91.267606 0 +96.338028 0 +101.408451 0 +106.478873 0 +111.549296 0 +116.619718 0 +121.690141 0 +126.760563 0 +131.830986 0 +136.901408 0 +141.971831 0 +147.042254 0 +152.112676 0 +157.183099 0 +162.253521 0 +167.323944 0 +172.394366 0 +177.464789 0 +182.535211 0 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/dada_Hg-O-H-H.dat b/dada_Hg-O-H-H.dat new file mode 100644 index 0000000..754867b --- /dev/null +++ b/dada_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.070423 0 +10.140845 0 +15.211268 0 +20.281690 0 +25.352113 0 +30.422535 0 +35.492958 0 +40.563380 0 +45.633803 0 +50.704225 0 +55.774648 0 +60.845070 0 +65.915493 0 +70.985915 0 +76.056338 0 +81.126761 0 +86.197183 0 +91.267606 0 +96.338028 0 +101.408451 0 +106.478873 0 +111.549296 0 +116.619718 0 +121.690141 0 +126.760563 0 +131.830986 0 +136.901408 0 +141.971831 0 +147.042254 0 +152.112676 0 +157.183099 0 +162.253521 0 +167.323944 0 +172.394366 0 +177.464789 0 +182.535211 1 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/dada_N40-C39-H20-H19.dat b/dada_N40-C39-H20-H19.dat new file mode 100644 index 0000000..63610a1 --- /dev/null +++ b/dada_N40-C39-H20-H19.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=1) +0.000000 0 +5.070423 0 +10.140845 0 +15.211268 0 +20.281690 0 +25.352113 0 +30.422535 0 +35.492958 0 +40.563380 0 +45.633803 0 +50.704225 0 +55.774648 0 +60.845070 0 +65.915493 0 +70.985915 0 +76.056338 0 +81.126761 0 +86.197183 0 +91.267606 0 +96.338028 0 +101.408451 0 +106.478873 0 +111.549296 0 +116.619718 1 +121.690141 0 +126.760563 0 +131.830986 0 +136.901408 0 +141.971831 0 +147.042254 0 +152.112676 0 +157.183099 0 +162.253521 0 +167.323944 0 +172.394366 0 +177.464789 0 +182.535211 0 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/dihedral.py b/dihedral.py new file mode 100644 index 0000000..6e57166 --- /dev/null +++ b/dihedral.py @@ -0,0 +1,46 @@ +#!/usr/bin/python3.8 + +def dihedral(p1, p2, p3, p4): + """ ------------------------------------------ + August 2020 + cesar.ibarguen@udea.edu.co + + computing DIHEDRAL angle + p3 + / + p1----p2 + \ + p4 + - order matters! + # ------------------------------------------ + """ + # # LIBRERIES + import numpy as np + # import math + + #--------------- Body ------------ + + # Calculate coordinates for vectors q1, q2 and q3 + q1 = np.subtract(p2, p1) # b - a + q2 = np.subtract(p3, p2) # c - b + q3 = np.subtract(p4, p3) # d - c + + # Calculate cross vectors + q1_x_q2 = np.cross(q1, q2) + q2_x_q3 = np.cross(q2, q3) + + # - protecting for and zero division + if np.linalg.norm(q1_x_q2) < 0.1 or \ + np.linalg.norm(q2_x_q3) < 0.1: + return 0 + + # Calculate normal vectors + n1 = q1_x_q2 / np.linalg.norm(q1_x_q2) + n2 = q2_x_q3 / np.linalg.norm(q2_x_q3) + + cos_theta = np.dot(n1, n2) + + theta = np.arccos(cos_theta) + theta_deg = abs(np.degrees(theta)) + + return theta_deg \ No newline at end of file diff --git a/distance_matrix.py b/distance_matrix.py new file mode 100644 index 0000000..dc0a063 --- /dev/null +++ b/distance_matrix.py @@ -0,0 +1,81 @@ +#!/usr/bin/env python3 +# ------------------------------------------------------------------------------------ +# July 2020 +# +# python3.x script by: +# +# name: Edison Florez (github.com/e-florez/) +# email: edisonffh@gmail.com + +# ------------------------------------------------------------------------------------ +# Main body +# ------------------------------------------------------------------------------------ + +def distance_matrix(distances, grid): + import numpy as np + import pandas as pd + """ + + Args: + + Return: + + """ + + ro, rf, dr = grid + + matrix_d = {} + + for xyz in distances: + data_xyz = distances[xyz] + + num_atoms = data_xyz.shape[0] + + # - distance matrix + # upper triangular matrix. It means that the diagonal and the lower triangular portion are zeros + # The upper triangular part has the distance between every atom for a given XYZ file + distance_matrix = np.zeros((num_atoms, num_atoms), dtype=float) + + # - the header for the distnces matrix + header_distance_matrix = [] + + # -------------------------------------------------------------------- + # - Computing the Radial Distribution Function + coordinates_a = np.zeros(3, dtype=float) + coordinates_b = np.zeros(3, dtype=float) + + for atom_a in range(0, num_atoms): + coordinates_a[0] = float(data_xyz.iloc[atom_a, 1]) + coordinates_a[1] = float(data_xyz.iloc[atom_a, 2]) + coordinates_a[2] = float(data_xyz.iloc[atom_a, 3]) + + # - the header for the distnces matrix + header_distance_matrix.append(data_xyz.iloc[atom_a, 0]) + + for atom_b in range(atom_a + 1, num_atoms): + coordinates_b[0] = float(data_xyz.iloc[atom_b, 1]) + coordinates_b[1] = float(data_xyz.iloc[atom_b, 2]) + coordinates_b[2] = float(data_xyz.iloc[atom_b, 3]) + + # - computing euclidean distance + distance = np.linalg.norm(coordinates_a - coordinates_b) + + # ------------------------------------------------ + # - computing distance matrix + distance_matrix[atom_a, atom_b] = distance + distance_matrix[atom_b, atom_a] = distance + + # ------------------------------------------------ + + df = pd.DataFrame(distance_matrix) + + # # - inserting columns' name + # df.columns = header_distance_matrix + + # - inserting rows' name + df.insert(0, 'atoms', header_distance_matrix, True) + + matrix_d[xyz] = df + # matrix_d[xyz] = distance_matrix + + return matrix_d diff --git a/files_xyz/b2plypd3/log_files/geometry_log2xyz.sh b/files_xyz/b2plypd3/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/camb3lyp/log_files/geometry_log2xyz.sh b/files_xyz/camb3lyp/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/ccsd/geometry_log2xyz.sh b/files_xyz/ccsd/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/dirac/nonrel/geometry_out2xyz.sh b/files_xyz/dirac/nonrel/geometry_out2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/dirac/x2c/geometry_out2xyz.sh b/files_xyz/dirac/x2c/geometry_out2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/hf/log_files/geometry_log2xyz.sh b/files_xyz/hf/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/lan/hf/log_files/geometry_log2xyz.sh b/files_xyz/lan/hf/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/lan/mp2/log_files/geometry_log2xyz.sh b/files_xyz/lan/mp2/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/lan/pbe0/log_files/geometry_log2xyz.sh b/files_xyz/lan/pbe0/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/mp2/ada_O-H-O.dat b/files_xyz/mp2/ada_O-H-O.dat new file mode 100644 index 0000000..068806f --- /dev/null +++ b/files_xyz/mp2/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=100) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 2 +107.837838 1 +112.972973 2 +118.108108 0 +123.243243 0 +128.378378 0 +133.513514 1 +138.648649 2 +143.783784 4 +148.918919 0 +154.054054 0 +159.189189 3 +164.324324 1 +169.459459 3 +174.594595 14 +179.729730 67 +184.864865 0 +190.000000 0 diff --git a/files_xyz/mp2/get_geo_xyz.sh b/files_xyz/mp2/get_geo_xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/mp2/transfer_O-H-O.dat b/files_xyz/mp2/transfer_O-H-O.dat index 2dcc1c0..e27898d 100644 --- a/files_xyz/mp2/transfer_O-H-O.dat +++ b/files_xyz/mp2/transfer_O-H-O.dat @@ -1,129 +1,101 @@ # q1 [Angstrom] q2 [Angstrom] - -0.2477649863 2.5523770902 - -0.1614331329 2.4642412041 - -0.2171385294 2.5151515606 - 0.0000000000 1.9418154125 + 0.1614331329 2.4642412041 + 0.2477649863 2.5523770902 + 0.2171385294 2.5151515606 -0.1302088107 2.4272957498 -0.1284163489 2.4262642880 - 0.0000000000 1.9310307161 - 0.0000000000 1.9310325668 - -0.3832519946 2.7083467447 - -0.4393247767 2.8359322732 -0.0086493187 2.3920137484 - 0.0000000000 1.9304723926 - -0.0794011845 2.4075380140 - 0.0000000000 1.9354837591 + 0.4393247767 2.8359322732 -0.0793466393 2.4076587516 + 0.0794011845 2.4075380140 -0.1126242374 2.4192434229 - -0.1197111861 2.4208223869 -0.3139502511 2.6277146783 + -0.1197111861 2.4208223869 + 0.1121446717 2.4189938214 -0.1205027875 2.4213480741 - -0.1121446717 2.4189938214 -0.3150072625 2.6294100225 - 0.0000000000 1.9373307141 - -0.0540810330 2.3980988885 - 0.0000000000 1.9345287585 + 0.0540810330 2.3980988885 -0.1947644158 2.4756566781 -0.1946149719 2.4754894603 - 0.0000000000 1.9279262454 - 0.0000000000 1.9286923786 -0.1148577301 2.4174197197 + -0.6759789591 3.2903733212 -0.0270270570 2.3896505511 - 0.0000000000 1.9344714211 - 0.0000000000 1.9343398961 -0.1044321165 2.4164555253 - 0.0000000000 1.9319487224 - 0.0000000000 1.9321733571 -0.1052789869 2.4168546763 - 0.0000000000 1.9321401342 - 0.0000000000 1.9319218255 -0.1294188278 2.4282596019 - 0.0000000000 1.9285935396 - 0.0000000000 1.9296892644 - -0.3009053077 2.6102246400 -0.2888933934 2.5909656976 - -0.1496821191 2.4408845297 + 0.3009053077 2.6102246400 + 0.1496821191 2.4408845297 + 0.1647279976 2.4497881163 -0.2793521486 2.5812157977 - -0.1647279976 2.4497881163 - -0.2586270928 2.5556176679 - -0.1732196861 2.4581328229 - -0.1731620270 2.4580865969 - -0.2283613719 2.5135916450 - 0.0000000000 1.9329140595 + -0.6123897323 3.1597258125 + 0.2586270928 2.5556176679 + 0.5970064804 3.1307895410 + 0.1731620270 2.4580865969 + 0.1732196861 2.4581328229 -0.2282972762 2.5135220367 - 0.0000000000 1.9329135669 - -0.2920118993 2.5951911694 + -0.2283613719 2.5135916450 + 0.1319406319 2.4275310043 + 0.2920118993 2.5951911694 + 0.2260410503 2.5060388142 -0.2263285827 2.5064102776 - -0.2260410503 2.5060388142 - -0.1319406319 2.4275310043 -0.1898914693 2.4711024595 -0.2157016926 2.4967409877 - -0.1674563441 2.4519871210 - 0.0000000000 1.9282507777 - 0.0000000000 1.9289340850 -0.4799510837 2.9020564708 - 0.0000000000 1.9382328509 + -0.1674563441 2.4519871210 -0.2279553780 2.5075870429 -0.2270962474 2.5066429789 - -0.1441082878 2.4356134969 -0.3688672320 2.7089998050 + -0.1441082878 2.4356134969 -0.2007460951 2.4799775156 -0.1997121966 2.4789769744 -0.2007737060 2.4800075576 -0.1997130614 2.4789808983 - 0.0000000000 1.9275171775 - 0.0000000000 1.9283181349 + 0.3131914995 2.6237383682 -0.1502920083 2.4389821782 - -0.3131914995 2.6237383682 - -0.2265945615 2.5111449668 + 0.2265945615 2.5111449668 -0.1724586766 2.4576643657 - 0.0000000000 1.9268518099 - 0.0000000000 1.9279110357 -0.1551531225 2.4453550389 - 0.0000000000 1.9277441612 - 0.0000000000 1.9284538098 -0.2545643523 2.5462254997 - 0.0000000000 1.9348793828 - -0.1832441205 2.4685670887 - -0.1506240301 2.4416117423 - -0.2368929493 2.5263734099 + 0.1832441205 2.4685670887 + 0.6546494339 3.2386261371 + 0.2368929493 2.5263734099 + 0.1506240301 2.4416117423 -0.2600122608 2.5524543929 + 0.2186277618 2.5002916081 + 0.2172423546 2.4996377326 -0.1437803292 2.4384233365 - 0.0000000000 1.9303666800 - 0.0000000000 1.9302541863 - -0.2186277618 2.5002916081 - -0.2172423546 2.4996377326 + -0.5874892958 3.1084014128 + 0.2888901286 2.5920544417 + 0.2042391122 2.4831912057 -0.1368985448 2.4322319620 - -0.2042391122 2.4831912057 - -0.2888901286 2.5920544417 + 0.1993828921 2.4784807633 -0.1544068493 2.4444265211 -0.2964622784 2.6023053039 - -0.1993828921 2.4784807633 - -0.1859391712 2.4699053575 - -0.1692515825 2.4561593995 + -0.5652357205 3.0657570966 + 0.1859391712 2.4699053575 + 0.1692515825 2.4561593995 + 0.2855813323 2.5891925364 + 0.5609573338 3.0579407154 -0.1938411628 2.4779457056 - -0.2855813323 2.5891925364 - -0.2310246255 2.5151524346 + 0.6478259265 3.2384211387 + 0.2310246255 2.5151524346 -0.2271658235 2.5105051226 - 0.0000000000 1.9271887593 - 0.0000000000 1.9279882178 - -0.2120962385 2.4927109497 + 0.2120962385 2.4927109497 -0.3182827813 2.6359285329 - 0.0000000000 1.9319775039 - 0.0000000000 1.9325948676 + -0.6713411525 3.2844901366 + 0.5621895351 3.0620337371 -0.3777441251 2.7275868943 - 0.0000000000 1.9324669658 - 0.0000000000 1.9328257985 - -0.4378530074 2.8310658641 + 0.4378530074 2.8310658641 -0.1328024565 2.4259457970 + 0.7574310096 3.4539403764 -0.4340016471 2.8189710054 -0.4187077171 2.7981554387 - 0.0000000000 1.9325638254 - 0.0000000000 1.9319550309 -0.4177532583 2.7965123116 -0.4350716244 2.8208566446 - -0.1340519957 2.4267089810 + 0.1340519957 2.4267089810 + 0.7588041060 3.4566394473 -0.4741882634 2.8957645007 - -0.1508781913 2.4415762736 + 0.1508781913 2.4415762736 -0.4743436361 2.8960633125 - -0.1510259009 2.4416718348 + 0.1510259009 2.4416718348 diff --git "a/files_xyz/others/ion-water/2021_Cooperativity and anticooperativity in ion\342\200\220water interactions. Implications in the aqueous solvation of ions.pdf" "b/files_xyz/others/ion-water/2021_Cooperativity and anticooperativity in ion\342\200\220water interactions. Implications in the aqueous solvation of ions.pdf" new file mode 100644 index 0000000..7908f17 Binary files /dev/null and "b/files_xyz/others/ion-water/2021_Cooperativity and anticooperativity in ion\342\200\220water interactions. Implications in the aqueous solvation of ions.pdf" differ diff --git a/files_xyz/others/ion-water/aguas/dimeroAgua.xyz b/files_xyz/others/ion-water/aguas/dimeroAgua.xyz new file mode 100644 index 0000000..7d84e4b --- /dev/null +++ b/files_xyz/others/ion-water/aguas/dimeroAgua.xyz @@ -0,0 +1,9 @@ + 6 + + O -1.49810700 -0.00777300 0.12120700 + H -0.55222400 0.01257500 -0.07104600 + H -1.93252100 0.04722900 -0.73065300 + O 1.38504100 0.00720500 -0.11503200 + H 1.70702400 0.73434100 0.42231500 + H 1.68224600 -0.78960500 0.32998100 + diff --git a/files_xyz/others/ion-water/aguas/heptameroAgua.xyz b/files_xyz/others/ion-water/aguas/heptameroAgua.xyz new file mode 100644 index 0000000..21431d9 --- /dev/null +++ b/files_xyz/others/ion-water/aguas/heptameroAgua.xyz @@ -0,0 +1,24 @@ + 21 + + O -2.74254000 1.33700100 0.20563200 + H -2.70043400 0.35947600 0.29655600 + H -3.65572800 1.55514200 0.01071400 + O -0.65250300 2.83099900 -0.63629900 + H -0.71706800 2.85252700 -1.59330500 + H -1.40976100 2.29140200 -0.32054500 + O 1.80681500 2.39836100 0.38846200 + H 1.85751100 2.91491800 1.19502500 + H 0.90631600 2.54056500 0.02070300 + O 3.09042900 0.05008300 0.07987600 + H 3.75123100 0.25919800 -0.58361400 + H 2.59047800 0.88176200 0.23555500 + O -2.72145900 -1.35209600 0.44236400 + H -1.98073400 -1.87461800 0.06337400 + H -2.89528600 -1.73269300 1.30594200 + O -0.68654600 -2.86415700 -0.47991800 + H 0.25335700 -2.65140100 -0.28691800 + H -0.70027000 -3.28350400 -1.34234300 + O 1.91700800 -2.37710000 0.02532200 + H 2.30401300 -2.82265400 0.78192200 + H 2.30674300 -1.47484700 0.01341500 + diff --git a/files_xyz/others/ion-water/aguas/hexameroAgua.xyz b/files_xyz/others/ion-water/aguas/hexameroAgua.xyz new file mode 100644 index 0000000..7f120a5 --- /dev/null +++ b/files_xyz/others/ion-water/aguas/hexameroAgua.xyz @@ -0,0 +1,21 @@ + 18 + + O -2.68626800 0.01244900 0.13281600 + H -3.21312200 -0.09921400 0.92524100 + H -2.18981900 -0.82632700 0.02185700 + O 1.33182900 -2.33086700 0.13245800 + H 1.81109700 -1.48229300 0.02049400 + H 1.69038100 -2.72994900 0.92628900 + O -1.33186800 2.33086800 -0.13293600 + H -1.69041800 2.73012600 -0.92667700 + H -1.81109000 1.48226800 -0.02104300 + O 2.68635100 -0.01243800 -0.13247500 + H 2.18978200 0.82629100 -0.02167100 + H 3.21411500 0.09972400 -0.92422300 + O 1.35320900 2.31841100 0.13274500 + H 1.51950600 2.82875500 0.92639800 + H 0.37861800 2.30812500 0.02149100 + O -1.35332200 -2.31849600 -0.13263600 + H -1.51979900 -2.82877600 -0.92629300 + H -0.37869300 -2.30814900 -0.02163400 + diff --git a/files_xyz/others/ion-water/aguas/monomeroAgua.xyz b/files_xyz/others/ion-water/aguas/monomeroAgua.xyz new file mode 100644 index 0000000..0b9da4e --- /dev/null +++ b/files_xyz/others/ion-water/aguas/monomeroAgua.xyz @@ -0,0 +1,6 @@ + 3 + + O 0.00000000 0.11665600 0.00000000 + H 0.76081800 -0.46662600 0.00000000 + H -0.76081800 -0.46662500 0.00000000 + diff --git a/files_xyz/others/ion-water/aguas/octameroAgua.xyz b/files_xyz/others/ion-water/aguas/octameroAgua.xyz new file mode 100644 index 0000000..68b64fa --- /dev/null +++ b/files_xyz/others/ion-water/aguas/octameroAgua.xyz @@ -0,0 +1,27 @@ + 24 + + O 0.77668800 -1.34171200 -1.18283100 + H 1.75912600 -1.28314800 -1.09453200 + H 0.59153700 -1.81807400 -1.99589600 + O -0.25379600 1.27171400 -0.68213800 + H -0.22670300 1.28400500 0.28967800 + H 0.06007700 0.38191000 -0.92821400 + O -2.94146500 1.27277500 -1.16230700 + H -3.18204500 1.44881500 -2.07393200 + H -1.97108000 1.39374200 -1.08988500 + O -3.17865100 -1.04465400 0.26441800 + H -3.97505900 -1.03670300 0.79921300 + H -3.20130700 -0.23526300 -0.28616500 + O 3.36712100 -0.84157900 -0.83554000 + H 3.22712700 0.02184000 -0.38440400 + H 3.99146000 -1.34261100 -0.30666100 + O 2.54147000 1.44997100 0.32407100 + H 1.97348500 1.22412100 1.08163900 + H 1.92527400 1.83568000 -0.31204100 + O 0.40720400 0.77316400 2.02025600 + H 0.01041700 -0.12996100 1.87298000 + H 0.16551000 1.06482700 2.90169200 + O -0.64588000 -1.50290900 1.26527600 + H -0.15382700 -1.71071300 0.45533900 + H -1.57551600 -1.39263100 0.98154600 + diff --git a/files_xyz/others/ion-water/aguas/pentameroAgua.xyz b/files_xyz/others/ion-water/aguas/pentameroAgua.xyz new file mode 100644 index 0000000..0e805eb --- /dev/null +++ b/files_xyz/others/ion-water/aguas/pentameroAgua.xyz @@ -0,0 +1,18 @@ + 15 + + O -2.15983100 0.78767200 -0.06581500 + H -2.77153400 1.19843900 0.54612700 + H -1.36225000 1.35878200 -0.07400500 + O 0.08908300 2.29298900 -0.06517100 + H 0.25565200 2.81909700 -0.84869900 + H 0.87872900 1.72120900 0.04369700 + O 2.20861400 0.62913000 0.16196900 + H 2.73540600 0.63737000 0.96220500 + H 1.91250900 -0.29850400 0.04198400 + O 1.28612100 -1.89326800 -0.14464800 + H 1.48958400 -2.34648300 -0.96408900 + H 0.30825600 -1.90126000 -0.06857500 + O -1.41162100 -1.82397900 0.05202900 + H -1.80496800 -2.22776800 0.82660500 + H -1.74031300 -0.90123300 0.02783800 + diff --git 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-0.08967700 -0.00070100 + H -1.39920100 0.82583700 -0.00002800 + diff --git a/files_xyz/others/ion-water/fluoruro/octamero_A.xyz b/files_xyz/others/ion-water/fluoruro/octamero_A.xyz new file mode 100644 index 0000000..d56f5e8 --- /dev/null +++ b/files_xyz/others/ion-water/fluoruro/octamero_A.xyz @@ -0,0 +1,28 @@ + 25 + + F 0.551716 0.872279 -0.885907 + O -3.576841 -0.199253 -0.965253 + H -3.088305 0.639306 -0.919436 + H -2.872195 -0.843048 -1.110515 + O -2.122833 -0.391082 1.580060 + H -3.011450 -0.305980 1.214999 + H -1.653073 -0.829771 0.841810 + O -1.813041 1.939054 -0.256474 + H -1.838464 1.470749 0.586792 + H -0.934297 1.698018 -0.610496 + O 2.811759 1.825604 0.396102 + H 2.468038 1.459293 1.218402 + H 2.035315 1.768265 -0.185735 + O 1.485996 -2.351687 0.460540 + H 1.296123 -1.638967 1.090108 + H 2.069631 -1.912758 -0.182155 + O 2.791213 -0.565377 -1.308095 + H 3.271124 0.040159 -0.729278 + H 1.931560 -0.108631 -1.379274 + O -0.888158 -1.356140 -0.721529 + H -0.176956 -1.947480 -0.421242 + H -0.410025 -0.526795 -0.935192 + O 0.745814 0.172738 1.657789 + H 0.619024 0.440736 0.719155 + H -0.142774 0.155533 2.030105 + diff --git a/files_xyz/others/ion-water/fluoruro/pentameroF.xyz b/files_xyz/others/ion-water/fluoruro/pentameroF.xyz new file mode 100644 index 0000000..55a7ab1 --- /dev/null +++ b/files_xyz/others/ion-water/fluoruro/pentameroF.xyz @@ -0,0 +1,19 @@ + 16 + + F -0.25225100 -1.37012800 -0.42809500 + O -2.68640100 -0.13605100 0.07245000 + H -2.29306500 0.58286800 -0.44217000 + H -2.03020500 -0.83669700 -0.08176000 + O -0.60111200 1.08912800 -1.49573300 + H -0.43876000 0.14992300 -1.27769100 + H 0.07344900 1.53882000 -0.96792400 + O 1.54405500 1.61396100 0.42222700 + H 0.91599000 1.21366200 1.04741600 + H 1.95717500 0.83090900 0.02324200 + O 2.25505800 -1.03685400 -0.45444800 + H 1.27345900 -1.22911200 -0.51301100 + H 2.51240100 -1.41273700 0.38869600 + O -0.29755100 -0.04539300 1.82165100 + H -1.21069600 0.24426300 1.71639500 + H -0.20188400 -0.62907400 1.03048700 + diff --git a/files_xyz/others/ion-water/fluoruro/tetrameroF_A.xyz b/files_xyz/others/ion-water/fluoruro/tetrameroF_A.xyz new file mode 100644 index 0000000..8105ad8 --- /dev/null +++ b/files_xyz/others/ion-water/fluoruro/tetrameroF_A.xyz @@ -0,0 +1,16 @@ + 13 + + F 0.00008700 -1.51922700 -0.50940200 + O 0.00008500 1.92371800 -0.22670900 + H 0.76331400 1.38425700 -0.49343400 + H -0.76308500 1.38426600 -0.49361300 + O 2.04448100 -0.05597300 -0.58359100 + H 1.26691500 -0.69041000 -0.65287400 + H 2.22261300 -0.05939000 0.36021300 + O -2.04434300 -0.05593400 -0.58393400 + H -1.26679600 -0.69037500 -0.65314900 + H -2.22244200 -0.05926000 0.35988000 + O -0.00034200 -0.23463200 1.85053200 + H -0.00017900 -0.84515200 1.08443200 + H -0.00017400 0.63168000 1.42277900 + diff --git a/files_xyz/others/ion-water/fluoruro/tetrameroF_B.xyz b/files_xyz/others/ion-water/fluoruro/tetrameroF_B.xyz new file mode 100644 index 0000000..7470487 --- /dev/null +++ b/files_xyz/others/ion-water/fluoruro/tetrameroF_B.xyz @@ -0,0 +1,16 @@ + 13 + + F -0.27415100 -0.11101000 -1.08966600 + O 1.14158900 1.74237600 0.21689500 + H 1.89437800 1.14459600 0.14980500 + H 0.49264100 1.26980600 -0.34578500 + O 2.12177100 -1.01535300 -0.40837000 + H 1.29601700 -0.74388800 -0.86782200 + H 1.77647400 -1.25664200 0.45710300 + O -2.80893500 0.01583500 -0.24435000 + H -1.96185000 0.00489100 -0.73525700 + H -2.51020400 -0.15672500 0.65248400 + O -0.24486800 -0.61170900 1.47860900 + H -0.33458600 -0.56636000 0.49677800 + H 0.13803100 0.25422600 1.65741200 + diff --git a/files_xyz/others/ion-water/fluoruro/trimeroF.xyz b/files_xyz/others/ion-water/fluoruro/trimeroF.xyz new file mode 100644 index 0000000..44cf416 --- /dev/null +++ b/files_xyz/others/ion-water/fluoruro/trimeroF.xyz @@ -0,0 +1,13 @@ + 10 + + F -0.00708800 -0.00133700 -1.44450100 + O 1.35935300 1.10802700 0.46912900 + H 0.91709100 0.83345800 -0.37378600 + H 1.41998400 0.25414700 0.90975600 + O -1.63672100 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-1.08273700 + O -2.09639000 -0.11336300 -1.26930000 + H -2.09170900 0.71391100 -0.75900500 + H -2.75581400 -0.02034600 -1.96129400 + O -1.46637500 -2.01904700 0.62623700 + H -1.98589600 -1.51238200 -0.02082600 + H -2.04944900 -2.66791100 1.02723800 + O -1.50711500 1.90813900 0.55573700 + H -2.07398400 2.52573500 1.02491100 + H -1.08240900 1.33814200 1.21695700 + diff --git a/files_xyz/others/ion-water/litio/hexameroLi_A.xyz b/files_xyz/others/ion-water/litio/hexameroLi_A.xyz new file mode 100644 index 0000000..ce1f30c --- /dev/null +++ b/files_xyz/others/ion-water/litio/hexameroLi_A.xyz @@ -0,0 +1,21 @@ +19 +hexameroLi1 E(RM062X) = -466.065018517 +Li 0.000001 0.000128 -0.000120 +O -1.297844 1.004489 -0.977838 +H -1.215993 1.682689 -1.649890 +H -2.240303 0.848994 -0.828303 +O 3.765422 -0.000110 0.000116 +H 4.345309 -0.548517 0.536876 +H 4.345696 0.548078 -0.536446 +O 1.297728 0.978038 1.004242 +H 2.240209 0.828470 0.848927 +H 1.215773 1.649970 1.682547 +O -3.765422 -0.000136 0.000116 +H -4.345484 0.536532 0.548422 +H -4.345518 -0.536837 -0.548122 +O -1.297616 -1.004431 0.977827 +H -2.240123 -0.849079 0.828423 +H -1.215566 -1.682709 1.649774 +O 1.297729 -0.977829 -1.004474 +H 1.215819 -1.649885 -1.682662 +H 2.240200 -0.828263 -0.849099 diff --git a/files_xyz/others/ion-water/litio/hexameroLi_B.xyz b/files_xyz/others/ion-water/litio/hexameroLi_B.xyz new file mode 100644 index 0000000..e0f4793 --- /dev/null +++ b/files_xyz/others/ion-water/litio/hexameroLi_B.xyz @@ -0,0 +1,23 @@ + 19 + + Li -0.00028900 0.96651600 0.00172600 + O -2.26441500 -1.17682900 -0.03036700 + H -1.71292100 -1.29784100 0.75494900 + H -2.94313000 -1.85669000 -0.01747000 + O 0.02215300 -0.43962500 1.42433000 + H 0.04151500 -0.18810000 2.35201500 + H 0.86210900 -0.89470800 1.23768000 + O -1.79320400 1.56305500 0.03500100 + H -2.40686700 0.81639900 0.00256200 + H -2.30536600 2.37142200 0.09117100 + O 2.26486500 -1.17635400 0.02848500 + H 1.71525200 -1.29693500 -0.75814000 + H 2.94544900 -1.85431700 0.01518900 + O -0.02192100 -0.43596700 -1.42445800 + H -0.04226800 -0.18018300 -2.35097400 + H -0.86144400 -0.89244100 -1.23921000 + O 1.79229000 1.56370800 -0.03379300 + H 2.40628100 0.81730200 -0.00194400 + H 2.30410400 2.37264200 -0.08459400 + + diff --git a/files_xyz/others/ion-water/litio/monomeroLi.xyz b/files_xyz/others/ion-water/litio/monomeroLi.xyz new file mode 100644 index 0000000..591f210 --- /dev/null +++ b/files_xyz/others/ion-water/litio/monomeroLi.xyz @@ -0,0 +1,7 @@ + 4 + + Li -1.49186200 -0.00007800 0.00022400 + O 0.33127400 -0.00001800 -0.00034700 + H 0.91227500 0.76917900 0.00105200 + H 0.91311800 -0.76880300 0.00105200 + diff --git a/files_xyz/others/ion-water/litio/octameroLi_A.xyz b/files_xyz/others/ion-water/litio/octameroLi_A.xyz new file mode 100644 index 0000000..7819424 --- /dev/null +++ b/files_xyz/others/ion-water/litio/octameroLi_A.xyz @@ -0,0 +1,28 @@ + 25 + + Li 0.574142 0.705376 -0.860641 + O 3.403704 -0.711183 1.047367 + H 3.875166 -0.183028 1.698658 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0.173995 -0.880569 +H -2.451679 1.091261 -0.815994 +H -3.491128 0.183117 -1.517908 + diff --git a/files_xyz/others/ion-water/potasio/pentameroK_A.xyz b/files_xyz/others/ion-water/potasio/pentameroK_A.xyz new file mode 100644 index 0000000..75a7332 --- /dev/null +++ b/files_xyz/others/ion-water/potasio/pentameroK_A.xyz @@ -0,0 +1,19 @@ + 16 + + K -1.85093300 0.04027100 0.34492600 + O 1.99519600 -1.35582100 -0.38263900 + H 2.28070400 -0.45647900 -0.60688700 + H 2.75067200 -1.93620500 -0.50378200 + O -0.65611400 1.96107900 -0.90119700 + H 0.31046500 1.94854200 -0.83593500 + H -0.87659000 2.65891200 -1.52144800 + O 2.00140900 1.42909800 -0.12809200 + H 2.69940600 2.08442700 -0.04478700 + H 1.68317100 1.23252200 0.76510100 + O -0.70395400 -1.91505600 -0.89041300 + H 0.26339200 -1.86528500 -0.91817200 + H -0.95452500 -2.63532000 -1.47241900 + O 0.52601300 -0.19223800 1.65298100 + H 0.65628500 -0.34977100 2.59208700 + H 1.05435100 -0.86299300 1.18751500 + diff --git a/files_xyz/others/ion-water/potasio/pentameroK_B.xyz b/files_xyz/others/ion-water/potasio/pentameroK_B.xyz new file mode 100644 index 0000000..2bbe219 --- /dev/null +++ b/files_xyz/others/ion-water/potasio/pentameroK_B.xyz @@ -0,0 +1,19 @@ + 16 + + K 0.99368800 0.14346400 0.12443500 + O 3.65154800 -0.09192300 -0.12275100 + H 4.14030000 -0.41579100 -0.88386900 + H 4.32727800 0.16857400 0.50870100 + O -0.67251800 2.09312800 -0.14131700 + H -1.57684300 1.75513600 -0.21304300 + H -0.72601500 3.04669400 -0.22869500 + O -1.09088400 -0.97649100 1.50129000 + H -1.88246800 -0.48527200 1.23070000 + H -1.25450800 -1.29428200 2.39231200 + O -2.80309500 0.30331200 -0.28309100 + H -3.74061200 0.39155600 -0.47240700 + H -2.42417000 -0.28163200 -0.95491800 + O -0.82402100 -1.51174700 -1.15352400 + H -1.01355700 -1.95158300 -0.31348600 + H -0.81772600 -2.18943600 -1.83440700 + diff --git a/files_xyz/others/ion-water/potasio/tetrameroK_A.xyz b/files_xyz/others/ion-water/potasio/tetrameroK_A.xyz new file mode 100644 index 0000000..1d354fc --- /dev/null +++ b/files_xyz/others/ion-water/potasio/tetrameroK_A.xyz @@ -0,0 +1,16 @@ + 13 + + K -0.67032600 0.19963700 0.13158600 + O 1.25719100 -1.00132400 -1.36172300 + H 1.75506900 -0.18458900 -1.49625700 + H 1.42614000 -1.56321100 -2.12205900 + O -3.31818800 -0.04546800 -0.02783400 + H -3.83902800 -0.84036800 0.11471800 + H -3.96336300 0.63358600 -0.24272200 + O 1.70166100 1.48373200 -0.21488600 + H 2.10838700 1.06209200 0.55342700 + H 2.13937100 2.32984900 -0.33696400 + O 1.53760600 -0.77577100 1.38264500 + H 1.88756000 -1.19432900 2.17293400 + H 1.79590100 -1.32548700 0.63116700 + diff --git a/files_xyz/others/ion-water/potasio/trimeroK_A.xyz b/files_xyz/others/ion-water/potasio/trimeroK_A.xyz new file mode 100644 index 0000000..3dab575 --- /dev/null +++ b/files_xyz/others/ion-water/potasio/trimeroK_A.xyz @@ -0,0 +1,13 @@ + 10 + + K -1.77613700 0.00000400 0.00026900 + O 0.23190300 1.59131200 -0.00043600 + H 0.35237500 2.54366700 -0.00099300 + H 1.12251900 1.21055800 -0.00038900 + O 0.23204200 -1.59133900 -0.00049400 + H 0.35205300 -2.54373400 -0.00057000 + H 1.12282500 -1.21097600 -0.00038300 + O 2.59250100 0.00000800 0.00038900 + H 3.17313700 0.00006200 -0.76698700 + H 3.17211300 0.00050900 0.76853700 + diff --git a/files_xyz/others/ion-water/potasio/trimeroK_B.xyz b/files_xyz/others/ion-water/potasio/trimeroK_B.xyz new file mode 100644 index 0000000..05badcf --- /dev/null +++ b/files_xyz/others/ion-water/potasio/trimeroK_B.xyz @@ -0,0 +1,13 @@ + 10 + + K -0.37309000 0.09970800 -0.24895900 + O 2.05665300 1.28008800 0.14646700 + H 2.33722200 1.70911400 0.96048800 + H 2.60079000 1.67856300 -0.53950700 + O -2.97937900 0.06671100 0.19645200 + H -3.62346800 0.76408000 0.04556400 + H -3.49322900 -0.66805100 0.54314500 + O 1.55788100 -1.57741500 0.07925800 + H 1.84204300 -2.49323100 0.12666400 + H 2.34411100 -1.03999500 0.21644500 + diff --git a/files_xyz/others/ion-water/sodio/dimeroNa_A.xyz b/files_xyz/others/ion-water/sodio/dimeroNa_A.xyz new file mode 100644 index 0000000..578be03 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/dimeroNa_A.xyz @@ -0,0 +1,10 @@ + 7 + + Na -0.00000200 0.00039600 0.00001300 + O -2.22353900 -0.00018500 -0.00001000 + H -2.80887000 0.59490800 -0.47794100 + H -2.80852100 -0.59559900 0.47799900 + O 2.22354400 -0.00019600 -0.00000200 + H 2.80853600 -0.59559400 -0.47799200 + H 2.80884000 0.59498500 0.47789000 + diff --git a/files_xyz/others/ion-water/sodio/dimeroNa_B.xyz b/files_xyz/others/ion-water/sodio/dimeroNa_B.xyz new file mode 100644 index 0000000..b18a8b7 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/dimeroNa_B.xyz @@ -0,0 +1,10 @@ + 7 + + Na -1.95785000 -0.45853600 -0.00000200 + O 2.17081400 -0.35940800 -0.00000600 + H 2.74833800 -0.39492400 -0.76733700 + H 2.74822500 -0.39501900 0.76740700 + O -0.23236900 0.81045300 0.00000100 + H 0.68505700 0.45848500 -0.00006300 + H -0.15282000 1.76699200 0.00005300 + diff --git a/files_xyz/others/ion-water/sodio/heptameroNa.xyz b/files_xyz/others/ion-water/sodio/heptameroNa.xyz new file mode 100644 index 0000000..bb8f5ba --- /dev/null +++ b/files_xyz/others/ion-water/sodio/heptameroNa.xyz @@ -0,0 +1,25 @@ + 22 + + Na -0.170045 -0.825142 -0.666417 + O 0.750832 1.344726 -1.176173 + H 1.037979 1.624204 -2.049517 + H 1.554384 1.290261 -0.626420 + O -2.347237 0.002580 -0.764487 + H -2.281753 0.896825 -0.388469 + H -3.029324 0.040121 -1.438996 + O -1.333951 2.303579 0.371378 + H -1.600650 3.207760 0.553306 + H -0.588164 2.326915 -0.251079 + O 0.033003 0.161285 1.478737 + H -0.532681 0.948325 1.487067 + H -0.438394 -0.536533 1.947186 + O 2.613952 0.665376 0.737840 + H 1.897036 0.515774 1.375369 + H 3.346104 1.076263 1.203493 + O 1.945826 -1.581988 -0.758441 + H 2.533981 -0.993975 -0.263984 + H 2.449583 -2.367429 -0.978435 + O -1.474808 -2.162013 0.761748 + H -1.661267 -3.064924 1.028993 + H -2.317271 -1.755381 0.527240 + diff --git a/files_xyz/others/ion-water/sodio/hexameroNa_A.xyz b/files_xyz/others/ion-water/sodio/hexameroNa_A.xyz new file mode 100644 index 0000000..3100c74 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/hexameroNa_A.xyz @@ -0,0 +1,23 @@ + 19 + + Na -0.00009900 -0.00001000 -0.00017400 + O 1.68230400 -0.90655900 1.20286900 + H 1.72205600 -1.49977600 1.95503800 + H 2.59633700 -0.71652300 0.95070100 + O -4.10687500 -0.00057800 0.00163300 + H -4.69101100 0.45754000 -0.60973300 + H -4.68180800 -0.46333600 0.61845600 + O -1.68275600 1.20462000 0.90397300 + H -2.59664300 0.95405900 0.71122700 + H -1.72292900 1.95865300 1.49481500 + O 4.10716400 0.00042100 0.00130900 + H 4.68662100 0.61333100 0.46335800 + H 4.68685300 -0.61134700 -0.46217400 + O 1.68346200 0.90484200 -1.20297900 + H 2.59698200 0.71501700 -0.94913000 + H 1.72426500 1.49473300 -1.95771900 + O -1.68321500 -1.20235900 -0.90660700 + H -1.72336900 -1.95558500 -1.49839100 + H -2.59694500 -0.94975900 -0.71611100 + + diff --git a/files_xyz/others/ion-water/sodio/monomeroNa.xyz b/files_xyz/others/ion-water/sodio/monomeroNa.xyz new file mode 100644 index 0000000..8cd2d07 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/monomeroNa.xyz @@ -0,0 +1,7 @@ + 4 + + Na 1.10389300 0.00000600 0.00000900 + O -1.09715300 0.00001600 -0.00005900 + H -1.68263300 -0.76391700 0.00018500 + H -1.68297200 0.76372400 0.00018500 + diff --git a/files_xyz/others/ion-water/sodio/octameroNa.xyz b/files_xyz/others/ion-water/sodio/octameroNa.xyz new file mode 100644 index 0000000..55de5b6 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/octameroNa.xyz @@ -0,0 +1,29 @@ + 25 + + Na -0.036375 -0.693783 -0.792634 + O 0.069376 0.356087 1.332885 + H 0.162992 1.304831 1.156511 + H 0.929067 0.071920 1.677627 + O -1.909349 -1.967616 -0.556937 + H -2.422112 -1.628592 0.189871 + H -2.140615 -2.892537 -0.658578 + O -2.618471 -0.094821 1.366984 + H -3.265128 0.085566 2.053016 + H -1.732738 0.002371 1.754889 + O 1.729352 0.885002 -1.172111 + H 1.339276 1.746385 -0.938624 + H 2.223246 1.009812 -1.986654 + O -1.747277 1.038746 -0.994954 + H -2.280927 0.749306 -0.231761 + H -2.340701 1.041507 -1.750793 + O 1.575029 -2.200969 -0.322279 + H 2.226550 -1.836971 0.293840 + H 1.704693 -3.150230 -0.344119 + O 2.810307 -0.237720 1.171937 + H 3.651568 -0.058558 1.598200 + H 2.768360 0.293648 0.361496 + O 0.117965 2.800866 -0.076818 + H 0.069047 3.751016 0.050577 + H -0.707915 2.505521 -0.496178 + + diff --git a/files_xyz/others/ion-water/sodio/pentameroNa_A.xyz b/files_xyz/others/ion-water/sodio/pentameroNa_A.xyz new file mode 100644 index 0000000..4c2d6ae --- /dev/null +++ b/files_xyz/others/ion-water/sodio/pentameroNa_A.xyz @@ -0,0 +1,19 @@ + 16 + + Na -0.88694200 -0.13652200 0.11001200 + O 0.74446600 0.97048200 -1.06630900 + H 0.73919800 1.32121600 -1.95977200 + H 1.65103300 0.67411500 -0.89689700 + O -1.25572900 1.97443800 0.77679000 + H -0.53333700 2.49808900 0.41882700 + H -1.73786400 2.54417900 1.37932800 + O -2.72347900 -1.25519600 -0.60056100 + H -2.80892000 -2.19109800 -0.79840300 + H -3.59002100 -0.87821600 -0.77276000 + O 3.16810100 -0.24764400 -0.19654000 + H 3.80412600 0.25896900 0.31760800 + H 3.68949900 -0.79572400 -0.79097000 + O 0.80960000 -1.30590700 1.01386000 + H 0.88849100 -1.92361500 1.74339000 + H 1.71048500 -1.09556200 0.73159700 + diff --git a/files_xyz/others/ion-water/sodio/tetrameroNa_A.xyz b/files_xyz/others/ion-water/sodio/tetrameroNa_A.xyz new file mode 100644 index 0000000..2343874 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/tetrameroNa_A.xyz @@ -0,0 +1,15 @@ +13 +tetrameroNa_A E(RM062X) = -467.889413631 +Na 0.520345 -0.026585 -0.000082 +O -1.054895 1.453242 0.775813 +H -1.163792 2.219303 1.345198 +H -1.588572 1.615112 -0.009734 +O -1.121398 -1.383401 0.858443 +H -1.260007 -2.251081 1.246903 +H -1.639812 -0.762815 1.382081 +O 2.779900 -0.014681 -0.002182 +H 3.356952 0.751645 0.057131 +H 3.371351 -0.769918 -0.061082 +O -1.096569 -0.031422 -1.632578 +H -1.653123 -0.773918 -1.374055 +H -1.203087 0.074204 -2.581508 diff --git a/files_xyz/others/ion-water/sodio/tetrameroNa_B.xyz b/files_xyz/others/ion-water/sodio/tetrameroNa_B.xyz new file mode 100644 index 0000000..d45a69b --- /dev/null +++ b/files_xyz/others/ion-water/sodio/tetrameroNa_B.xyz @@ -0,0 +1,16 @@ + 13 + + Na 1.01548000 -0.00007200 0.00013800 + O 3.27105100 0.00001800 -0.00013200 + H 3.85507700 -0.00084200 0.76316100 + H 3.85481500 0.00091600 -0.76362600 + O -0.60204700 1.52706800 0.00011300 + H -1.51714600 1.21004200 0.00010400 + H -0.64186700 2.48559300 0.00019300 + O -0.60214600 -1.52707500 0.00003400 + H -0.64207500 -2.48559500 0.00004600 + H -1.51720500 -1.20993900 -0.00003600 + O -2.99358200 0.00005400 -0.00012900 + H -3.57392500 0.00014600 -0.76768000 + H -3.57416500 -0.00005400 0.76724100 + diff --git a/files_xyz/others/ion-water/sodio/trimeroNa_A.xyz b/files_xyz/others/ion-water/sodio/trimeroNa_A.xyz new file mode 100644 index 0000000..470f694 --- /dev/null +++ b/files_xyz/others/ion-water/sodio/trimeroNa_A.xyz @@ -0,0 +1,12 @@ +10 +trimeroNa_A E(RM062X) = -391.436516397 +Na -0.004997 0.001040 -0.001365 +O 1.245742 1.869864 0.000450 +H 1.092161 2.677007 -0.498492 +H 2.049865 2.032528 0.501390 +O 1.008764 -2.006561 0.000508 +H 1.787931 -2.267328 -0.498402 +H 0.754678 -2.788837 0.497996 +O -2.250012 0.135824 0.000452 +H -2.868012 -0.408401 -0.495429 +H -2.797603 0.750576 0.496671 diff --git a/files_xyz/others/ion-water/sodio/trimeroNa_B.xyz b/files_xyz/others/ion-water/sodio/trimeroNa_B.xyz new file mode 100644 index 0000000..36a1adb --- /dev/null +++ b/files_xyz/others/ion-water/sodio/trimeroNa_B.xyz @@ -0,0 +1,14 @@ + 10 + + Na 1.78869800 0.00063700 -0.00009400 + O 0.23433400 -1.55250400 0.00006700 + H 0.19671500 -2.51141400 0.00026800 + H -0.68161600 -1.23509500 -0.00056300 + O 0.23308200 1.55219500 0.00021900 + H 0.19511100 2.51112400 -0.00057100 + H -0.68287200 1.23457700 -0.00019500 + O -2.12802400 -0.00026000 -0.00009800 + H -2.70957900 -0.00066400 -0.76722900 + H -2.70857400 -0.00098000 0.76781600 + + diff --git a/files_xyz/others/ion-water/sulfato/dimeroSO4_A.xyz b/files_xyz/others/ion-water/sulfato/dimeroSO4_A.xyz new file mode 100644 index 0000000..d8e83d4 --- /dev/null +++ b/files_xyz/others/ion-water/sulfato/dimeroSO4_A.xyz @@ -0,0 +1,14 @@ + 11 + + S 0.000017 0.000039 0.000243 +O -0.862708 -0.662192 1.014388 +O 0.862064 -1.014415 -0.662324 +O 0.862840 1.013859 0.662846 +O -0.862183 0.662996 -1.013867 +O -3.358017 -0.000177 -0.000626 +H -2.693268 -0.390966 0.599620 +H -2.693444 0.391058 -0.600755 +O 3.357978 -0.000091 -0.000628 +H 2.693482 -0.600422 -0.391611 +H 2.693172 0.599863 0.390544 + diff --git a/files_xyz/others/ion-water/sulfato/dimeroSO4_B.xyz b/files_xyz/others/ion-water/sulfato/dimeroSO4_B.xyz new file mode 100644 index 0000000..c1eee69 --- /dev/null +++ b/files_xyz/others/ion-water/sulfato/dimeroSO4_B.xyz @@ -0,0 +1,14 @@ + 11 + + S -0.000102 0.646737 0.009697 + O -0.000466 -0.645818 0.777441 + O 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placed in the public domain by the +# contributors. +# +data_1011023 +_chemical_name_systematic 'Dihydrogen oxide' +_chemical_name_mineral 'Ice Ih' +_chemical_formula_structural 'H2 O' +_chemical_formula_sum 'H2 O' +_publ_section_title +; +A Theory of Water and Ionic Solution, with Particular Reference to +Hydrogen and Hydroxyl Ions +; +loop_ +_publ_author_name + 'Bernal, J D' + 'Fowler, R H' +_journal_name_full 'Journal of Chemical Physics' +_journal_coden_ASTM JCPSA6 +_journal_volume 1 +_journal_year 1933 +_journal_page_first 515 +_journal_page_last 548 +_cell_length_a 7.82 +_cell_length_b 7.82 +_cell_length_c 7.36 +_cell_angle_alpha 90 +_cell_angle_beta 90 +_cell_angle_gamma 120 +_cell_volume 389.8 +_cell_formula_units_Z 12 +_exptl_crystal_density_meas 0.92 +_symmetry_space_group_name_H-M 'P 63 c m' +_symmetry_Int_Tables_number 185 +_symmetry_cell_setting hexagonal +loop_ +_symmetry_equiv_pos_as_xyz + 'x,y,z' + '-y,x-y,z' + 'y-x,-x,z' + 'y,x,z' + 'x-y,-y,z' + '-x,y-x,z' + 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9.532580 25.545187 21.896001 + H 1.716490 6.061225 21.896001 + H -11.249070 22.572138 21.896001 + H 17.356491 21.028050 29.256001 + H 4.390930 4.517137 29.256001 + H 25.172580 1.544089 29.256001 + H -1.716490 6.061225 3.496000 + H 11.249070 22.572138 3.496000 + H -9.532580 25.545187 3.496000 + H 6.107420 1.544089 3.496000 + H 13.923510 21.028050 3.496000 + H 26.889071 4.517137 3.496000 + H 9.532580 25.545187 29.256001 + H 1.716490 6.061225 29.256001 + H -11.249070 22.572138 29.256001 + H 5.626490 -0.711093 7.176000 + H -10.013510 27.800369 7.176000 + H -3.429070 4.517137 7.176000 + H 29.082581 5.228230 7.176000 + H 25.653510 -0.711093 10.856000 + H 10.013510 27.800369 10.856000 + H -13.442580 21.861045 10.856000 + H 19.069070 22.572138 10.856000 + H 5.626490 -0.711093 14.536000 + H -10.013510 27.800369 14.536000 + H -3.429070 4.517137 14.536000 + H 29.082581 5.228230 14.536000 + H 25.653510 -0.711093 18.216001 + H 10.013510 27.800369 18.216001 + H -13.442580 21.861045 18.216001 + H 19.069070 22.572138 18.216001 + H 5.626490 -0.711093 21.896001 + H -10.013510 27.800369 21.896001 + H -3.429070 4.517137 21.896001 + H 29.082581 5.228230 21.896001 + H 25.653510 -0.711093 25.576001 + H 10.013510 27.800369 25.576001 + H -13.442580 21.861045 25.576001 + H 19.069070 22.572138 25.576001 + H 5.626490 -0.711093 29.256001 + H -10.013510 27.800369 29.256001 + H -3.429070 4.517137 29.256001 + H 29.082581 5.228230 29.256001 + H 25.653510 -0.711093 3.496000 + H 10.013510 27.800369 3.496000 + H -13.442580 21.861045 3.496000 + H 19.069070 22.572138 3.496000 + H 13.446490 -0.711093 7.176000 + H -2.193510 27.800369 7.176000 + H -7.339070 11.289456 7.176000 + H 25.172580 12.000549 7.176000 + H 17.833510 -0.711093 10.856000 + H 2.193510 27.800369 10.856000 + H -9.532580 15.088726 10.856000 + H 22.979071 15.799820 10.856000 + H 13.446490 -0.711093 14.536000 + H -2.193510 27.800369 14.536000 + H -7.339070 11.289456 14.536000 + H 25.172580 12.000549 14.536000 + H 17.833510 -0.711093 18.216001 + H 2.193510 27.800369 18.216001 + H -9.532580 15.088726 18.216001 + H 22.979071 15.799820 18.216001 + H 13.446490 -0.711093 21.896001 + H -2.193510 27.800369 21.896001 + H -7.339070 11.289456 21.896001 + H 25.172580 12.000549 21.896001 + H 17.833510 -0.711093 25.576001 + H 2.193510 27.800369 25.576001 + H -9.532580 15.088726 25.576001 + H 22.979071 15.799820 25.576001 + H 13.446490 -0.711093 29.256001 + H -2.193510 27.800369 29.256001 + H -7.339070 11.289456 29.256001 + H 25.172580 12.000549 29.256001 + H 17.833510 -0.711093 3.496000 + H 2.193510 27.800369 3.496000 + H -9.532580 15.088726 3.496000 + H 22.979071 15.799820 3.496000 + H 21.266491 -0.711093 7.176000 + H 5.626490 27.800369 7.176000 + H -11.249070 18.061774 7.176000 + H 21.262580 18.772868 7.176000 + H 10.013510 -0.711093 10.856000 + H -5.626490 27.800369 10.856000 + H -5.622580 8.316407 10.856000 + H 26.889071 9.027501 10.856000 + H 21.266491 -0.711093 14.536000 + H 5.626490 27.800369 14.536000 + H -11.249070 18.061774 14.536000 + H 21.262580 18.772868 14.536000 + H 10.013510 -0.711093 18.216001 + H -5.626490 27.800369 18.216001 + H -5.622580 8.316407 18.216001 + H 26.889071 9.027501 18.216001 + H 21.266491 -0.711093 21.896001 + H 5.626490 27.800369 21.896001 + H -11.249070 18.061774 21.896001 + H 21.262580 18.772868 21.896001 + H 10.013510 -0.711093 25.576001 + H -5.626490 27.800369 25.576001 + H -5.622580 8.316407 25.576001 + H 26.889071 9.027501 25.576001 + H 21.266491 -0.711093 29.256001 + H 5.626490 27.800369 29.256001 + H -11.249070 18.061774 29.256001 + H 21.262580 18.772868 29.256001 + H 10.013510 -0.711093 3.496000 + H -5.626490 27.800369 3.496000 + H -5.622580 8.316407 3.496000 + H 26.889071 9.027501 3.496000 + H 29.086491 -0.711093 7.176000 + H 13.446490 27.800369 7.176000 + H -15.159070 24.834093 7.176000 + H 17.352580 25.545187 7.176000 + H 2.193510 -0.711093 10.856000 + H -13.446490 27.800369 10.856000 + H -1.712580 1.544089 10.856000 + H 30.799071 2.255182 10.856000 + H 29.086491 -0.711093 14.536000 + H 13.446490 27.800369 14.536000 + H -15.159070 24.834093 14.536000 + H 17.352580 25.545187 14.536000 + H 2.193510 -0.711093 18.216001 + H -13.446490 27.800369 18.216001 + H -1.712580 1.544089 18.216001 + H 30.799071 2.255182 18.216001 + H 29.086491 -0.711093 21.896001 + H 13.446490 27.800369 21.896001 + H -15.159070 24.834093 21.896001 + H 17.352580 25.545187 21.896001 + H 2.193510 -0.711093 25.576001 + H -13.446490 27.800369 25.576001 + H -1.712580 1.544089 25.576001 + H 30.799071 2.255182 25.576001 + H 29.086491 -0.711093 29.256001 + H 13.446490 27.800369 29.256001 + H -15.159070 24.834093 29.256001 + H 17.352580 25.545187 29.256001 + H 2.193510 -0.711093 3.496000 + H -13.446490 27.800369 3.496000 + H -1.712580 1.544089 3.496000 + H 30.799071 2.255182 3.496000 diff --git a/files_xyz/others/water/w4/I.xyz b/files_xyz/others/water/w4/w4s1.xyz similarity index 100% rename from files_xyz/others/water/w4/I.xyz rename to files_xyz/others/water/w4/w4s1.xyz diff --git a/files_xyz/others/water/w4/II.xyz b/files_xyz/others/water/w4/w4s2.xyz similarity index 100% rename from files_xyz/others/water/w4/II.xyz rename to files_xyz/others/water/w4/w4s2.xyz diff --git a/files_xyz/others/water/w4/III.xyz b/files_xyz/others/water/w4/w4s3.xyz similarity index 100% rename from files_xyz/others/water/w4/III.xyz rename to files_xyz/others/water/w4/w4s3.xyz diff --git a/files_xyz/others/water/w4/IV.xyz b/files_xyz/others/water/w4/w4s4.xyz similarity index 100% rename from files_xyz/others/water/w4/IV.xyz rename to files_xyz/others/water/w4/w4s4.xyz diff --git a/files_xyz/others/water/w4/V.xyz b/files_xyz/others/water/w4/w4s5.xyz similarity index 100% rename from files_xyz/others/water/w4/V.xyz rename to files_xyz/others/water/w4/w4s5.xyz diff --git a/files_xyz/others/water/w4/VI.xyz b/files_xyz/others/water/w4/w4s6.xyz similarity index 100% rename from files_xyz/others/water/w4/VI.xyz rename to files_xyz/others/water/w4/w4s6.xyz diff --git a/files_xyz/others/water/w4/VII.xyz b/files_xyz/others/water/w4/w4s7.xyz similarity index 100% rename from files_xyz/others/water/w4/VII.xyz rename to files_xyz/others/water/w4/w4s7.xyz diff --git a/files_xyz/others/water/w4/VIII.xyz b/files_xyz/others/water/w4/w4s8.xyz similarity index 100% rename from files_xyz/others/water/w4/VIII.xyz rename to files_xyz/others/water/w4/w4s8.xyz diff --git a/files_xyz/others/water/w5/s1.xyz b/files_xyz/others/water/w5/w5s1.xyz similarity index 100% rename from files_xyz/others/water/w5/s1.xyz rename to files_xyz/others/water/w5/w5s1.xyz diff --git a/files_xyz/others/water/w5/s10.xyz b/files_xyz/others/water/w5/w5s10.xyz similarity index 100% rename from files_xyz/others/water/w5/s10.xyz rename to files_xyz/others/water/w5/w5s10.xyz diff --git a/files_xyz/others/water/w5/s11.xyz b/files_xyz/others/water/w5/w5s11.xyz similarity index 100% rename from files_xyz/others/water/w5/s11.xyz rename to files_xyz/others/water/w5/w5s11.xyz diff --git a/files_xyz/others/water/w5/s12.xyz b/files_xyz/others/water/w5/w5s12.xyz similarity index 100% rename from files_xyz/others/water/w5/s12.xyz rename to files_xyz/others/water/w5/w5s12.xyz diff --git a/files_xyz/others/water/w5/s2.xyz b/files_xyz/others/water/w5/w5s2.xyz similarity index 100% rename from files_xyz/others/water/w5/s2.xyz rename to files_xyz/others/water/w5/w5s2.xyz diff --git a/files_xyz/others/water/w5/s3.xyz b/files_xyz/others/water/w5/w5s3.xyz similarity index 100% rename from files_xyz/others/water/w5/s3.xyz rename to files_xyz/others/water/w5/w5s3.xyz diff --git a/files_xyz/others/water/w5/s4.xyz b/files_xyz/others/water/w5/w5s4.xyz similarity index 100% rename from files_xyz/others/water/w5/s4.xyz rename to files_xyz/others/water/w5/w5s4.xyz diff --git a/files_xyz/others/water/w5/s5.xyz b/files_xyz/others/water/w5/w5s5.xyz similarity index 100% rename from files_xyz/others/water/w5/s5.xyz rename to files_xyz/others/water/w5/w5s5.xyz diff --git a/files_xyz/others/water/w5/s6.xyz b/files_xyz/others/water/w5/w5s6.xyz similarity index 100% rename from files_xyz/others/water/w5/s6.xyz rename to files_xyz/others/water/w5/w5s6.xyz diff --git a/files_xyz/others/water/w5/s7.xyz b/files_xyz/others/water/w5/w5s7.xyz similarity index 100% rename from files_xyz/others/water/w5/s7.xyz rename to files_xyz/others/water/w5/w5s7.xyz diff --git a/files_xyz/others/water/w5/s8.xyz b/files_xyz/others/water/w5/w5s8.xyz similarity index 100% rename from files_xyz/others/water/w5/s8.xyz rename to files_xyz/others/water/w5/w5s8.xyz diff --git a/files_xyz/others/water/w5/s9.xyz b/files_xyz/others/water/w5/w5s9.xyz similarity index 100% rename from files_xyz/others/water/w5/s9.xyz rename to files_xyz/others/water/w5/w5s9.xyz diff --git a/files_xyz/others/water/w6/ada_H-O-H.dat b/files_xyz/others/water/w6/ada_H-O-H.dat new file mode 100644 index 0000000..4c5a237 --- /dev/null +++ b/files_xyz/others/water/w6/ada_H-O-H.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=805) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 4 +30.810811 17 +35.945946 17 +41.081081 22 +46.216216 18 +51.351351 42 +56.486486 11 +61.621622 13 +66.756757 4 +71.891892 5 +77.027027 15 +82.162162 21 +87.297297 17 +92.432432 40 +97.567568 29 +102.702703 44 +107.837838 175 +112.972973 37 +118.108108 33 +123.243243 64 +128.378378 59 +133.513514 47 +138.648649 29 +143.783784 15 +148.918919 14 +154.054054 3 +159.189189 5 +164.324324 2 +169.459459 2 +174.594595 1 +179.729730 0 +184.864865 0 +190.000000 0 diff --git a/files_xyz/others/water/w6/ada_O-H-O.dat b/files_xyz/others/water/w6/ada_O-H-O.dat new file mode 100644 index 0000000..5de9f2c --- /dev/null +++ b/files_xyz/others/water/w6/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=345) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 3 +66.756757 21 +71.891892 39 +77.027027 26 +82.162162 32 +87.297297 14 +92.432432 11 +97.567568 8 +102.702703 2 +107.837838 6 +112.972973 3 +118.108108 2 +123.243243 3 +128.378378 1 +133.513514 2 +138.648649 5 +143.783784 7 +148.918919 16 +154.054054 24 +159.189189 23 +164.324324 18 +169.459459 22 +174.594595 16 +179.729730 29 +184.864865 12 +190.000000 0 diff --git a/files_xyz/others/water/w6/get_geo_xyz.sh b/files_xyz/others/water/w6/get_geo_xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/others/water/w6/rda_O-O.dat b/files_xyz/others/water/w6/rda_O-O.dat index 3ead8da..40d3a67 100644 --- a/files_xyz/others/water/w6/rda_O-O.dat +++ b/files_xyz/others/water/w6/rda_O-O.dat @@ -1,58 +1,91 @@ -# distance [\AA] occurrence (total=174) -0.600000 0 -0.651786 0 -0.703571 0 -0.755357 0 -0.807143 0 -0.858929 0 -0.910714 0 -0.962500 0 -1.014286 0 -1.066071 0 -1.117857 0 -1.169643 0 -1.221429 0 -1.273214 0 -1.325000 0 -1.376786 0 -1.428571 0 -1.480357 0 -1.532143 0 -1.583929 0 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files_xyz/others/water/w6/water_hexamer_s17.xyz rename to files_xyz/others/water/w6/w6s17.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s18.xyz b/files_xyz/others/water/w6/w6s18.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s18.xyz rename to files_xyz/others/water/w6/w6s18.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s19.xyz b/files_xyz/others/water/w6/w6s19.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s19.xyz rename to files_xyz/others/water/w6/w6s19.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s2.xyz b/files_xyz/others/water/w6/w6s2.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s2.xyz rename to files_xyz/others/water/w6/w6s2.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s20.xyz b/files_xyz/others/water/w6/w6s20.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s20.xyz rename to files_xyz/others/water/w6/w6s20.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s21.xyz b/files_xyz/others/water/w6/w6s21.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s21.xyz rename to files_xyz/others/water/w6/w6s21.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s22.xyz b/files_xyz/others/water/w6/w6s22.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s22.xyz rename to files_xyz/others/water/w6/w6s22.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s23.xyz b/files_xyz/others/water/w6/w6s23.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s23.xyz rename to files_xyz/others/water/w6/w6s23.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s24.xyz b/files_xyz/others/water/w6/w6s24.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s24.xyz rename to files_xyz/others/water/w6/w6s24.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s3.xyz b/files_xyz/others/water/w6/w6s3.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s3.xyz rename to files_xyz/others/water/w6/w6s3.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s4.xyz b/files_xyz/others/water/w6/w6s4.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s4.xyz rename to files_xyz/others/water/w6/w6s4.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s5.xyz b/files_xyz/others/water/w6/w6s5.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s5.xyz rename to files_xyz/others/water/w6/w6s5.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s6.xyz b/files_xyz/others/water/w6/w6s6.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s6.xyz rename to files_xyz/others/water/w6/w6s6.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s7.xyz b/files_xyz/others/water/w6/w6s7.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s7.xyz rename to files_xyz/others/water/w6/w6s7.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s8.xyz b/files_xyz/others/water/w6/w6s8.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s8.xyz rename to files_xyz/others/water/w6/w6s8.xyz diff --git a/files_xyz/others/water/w6/water_hexamer_s9.xyz b/files_xyz/others/water/w6/w6s9.xyz similarity index 100% rename from files_xyz/others/water/w6/water_hexamer_s9.xyz rename to files_xyz/others/water/w6/w6s9.xyz diff --git a/files_xyz/pbe/log_files/geometry_log2xyz.sh b/files_xyz/pbe/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/pbe0/log_files/geometry_log2xyz.sh b/files_xyz/pbe0/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/pbeqidh/log_files/geometry_log2xyz.sh b/files_xyz/pbeqidh/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/sdd/hf/log_files/geometry_log2xyz.sh b/files_xyz/sdd/hf/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/sdd/mp2/log_files/geometry_log2xyz.sh b/files_xyz/sdd/mp2/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/sdd/pbe0/log_files/geometry_log2xyz.sh b/files_xyz/sdd/pbe0/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/transform_coordinates/xyz_to_input.py b/files_xyz/transform_coordinates/xyz_to_input.py old mode 100755 new mode 100644 diff --git a/files_xyz/uhf/log_files/geometry_log2xyz.sh b/files_xyz/uhf/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/wb97xd_grimmeD2/log_files/geometry_log2xyz.sh b/files_xyz/wb97xd_grimmeD2/log_files/geometry_log2xyz.sh old mode 100755 new mode 100644 diff --git a/files_xyz/zora/so/ada_O-H-O.dat b/files_xyz/zora/so/ada_O-H-O.dat new file mode 100644 index 0000000..264891d --- /dev/null +++ b/files_xyz/zora/so/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=81) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 0 +112.972973 0 +118.108108 0 +123.243243 1 +128.378378 0 +133.513514 1 +138.648649 0 +143.783784 3 +148.918919 1 +154.054054 1 +159.189189 1 +164.324324 1 +169.459459 4 +174.594595 4 +179.729730 63 +184.864865 1 +190.000000 0 diff --git a/files_xyz/zora/so/transfer_O-H-O.dat b/files_xyz/zora/so/transfer_O-H-O.dat index e104ca1..ad8778f 100644 --- a/files_xyz/zora/so/transfer_O-H-O.dat +++ b/files_xyz/zora/so/transfer_O-H-O.dat @@ -1,109 +1,82 @@ # q1 [Angstrom] q2 [Angstrom] - -0.1864311730 2.5115242251 - 0.0000000000 1.9557457370 - -0.1405941895 2.4776340962 - -0.0928604686 2.4449218385 - -0.0476221562 2.4266230131 - 0.0000000000 1.9510943764 + 0.1864311730 2.5115242251 + 0.0928604686 2.4449218385 + 0.1405941895 2.4776340962 -0.0475983928 2.4266818670 - -0.4063420432 2.7687356688 - -0.4321225910 2.8461669837 + 0.0476221562 2.4266230131 -0.0035690796 2.4246543124 - 0.0000000000 1.9489453818 + 0.4321225910 2.8461669837 -0.1134446021 2.4494205112 -0.1066019979 2.4461182534 - 0.0000000000 1.9499358106 - 0.0000000000 1.9504903046 -0.0790820702 2.4375343242 - -0.0834054426 2.4367914682 -0.3094766763 2.6459515713 + -0.0834054426 2.4367914682 + 0.0786908707 2.4374310164 -0.0877604181 2.4384302797 - -0.0786908707 2.4374310164 -0.3078641606 2.6435751970 - 0.0000000000 1.9513059363 -0.0083221550 2.4207020633 -0.1696571046 2.4855445563 -0.1712265439 2.4868373528 - 0.0000000000 1.9469870788 - 0.0000000000 1.9478072567 -0.1717201002 2.4870776435 -0.1697228908 2.4856652022 -0.0028544423 2.4204410582 - 0.0000000000 1.9540279431 - 0.0000000000 1.9545058589 -0.0759144207 2.4370249404 - 0.0000000000 1.9511319134 - 0.0000000000 1.9513090215 -0.0805636886 2.4387416005 - 0.0000000000 1.9514222196 - 0.0000000000 1.9511004409 -0.0971607677 2.4439548481 - 0.0000000000 1.9481779134 - 0.0000000000 1.9493411422 - -0.2748919122 2.5990983520 -0.2783944923 2.6025022216 - -0.1294353746 2.4612137594 + 0.2748919122 2.5990983520 + 0.1294353746 2.4612137594 + 0.1358787355 2.4624031435 -0.2919628007 2.6286426199 - -0.1358787355 2.4624031435 - -0.2805210160 2.6160608679 - -0.4985394008 2.9658458691 - -0.2751835732 2.5972996317 + -0.5649266844 3.0899169603 + 0.2805210160 2.6160608679 + 0.4985394008 2.9658458691 + 0.1065373829 2.4452920460 + 0.2751835732 2.5972996317 + 0.2083000046 2.5178201421 -0.2082575541 2.5177431862 - -0.2083000046 2.5178201421 - -0.1065373829 2.4452920460 -0.1676384961 2.4842530590 -0.1916197780 2.5044937238 - -0.1312233770 2.4592583261 - 0.0000000000 1.9482647184 - 0.0000000000 1.9489998325 -0.4560856133 2.8799225893 - 0.0000000000 1.9521360992 + -0.1312233770 2.4592583261 -0.2088391464 2.5178003548 -0.2083486055 2.5174557541 - -0.1110531336 2.4486493772 -0.3758874596 2.7442384862 - -0.1171567538 2.4511718708 + -0.1110531336 2.4486493772 + 0.2919694735 2.6168512811 + 0.1171567538 2.4511718708 -0.1477715986 2.4711721603 - 0.0000000000 1.9463942878 - 0.0000000000 1.9472022392 - -0.2919694735 2.6168512811 -0.2062276775 2.5169743795 -0.1256536285 2.4582433095 - 0.0000000000 1.9473706996 - 0.0000000000 1.9480686521 -0.2411447295 2.5575430522 - 0.0000000000 1.9489233339 - -0.1502118790 2.4747717584 - -0.1189558318 2.4542066833 - -0.2094383283 2.5276030982 + 0.1502118790 2.4747717584 + 0.7014389560 3.3495226517 + 0.2094383283 2.5276030982 + 0.1189558318 2.4542066833 -0.2508423117 2.5673863116 + 0.2051190680 2.5172232730 + 0.2045895552 2.5172738469 -0.1167478090 2.4541180074 - 0.0000000000 1.9496353766 - 0.0000000000 1.9494641168 - -0.2051190680 2.5172232730 - -0.2045895552 2.5172738469 + -0.5494426918 3.0551055160 + 0.2950775732 2.6297988264 + 0.1856464115 2.4975689449 -0.1099069593 2.4488776253 - -0.1856464115 2.4975689449 - -0.2950775732 2.6297988264 + 0.1822727939 2.4947884731 -0.1129149515 2.4509478079 -0.3047634680 2.6426408538 - -0.1822727939 2.4947884731 - -0.1629045363 2.4835165784 - -0.1381692783 2.4665932978 + -0.5195438486 2.9997406759 + 0.1629045363 2.4835165784 + 0.1381692783 2.4665932978 + 0.6110137712 3.1834918896 + 0.3126011327 2.6554118070 + 0.4654557138 2.9031057608 -0.1687272834 2.4873859576 - -0.3126011327 2.6554118070 - -0.4654557138 2.9031057608 -0.1207145439 2.4561206104 - 0.0000000000 1.9494071252 - 0.0000000000 1.9492319370 - -0.2039241787 2.5170624743 - -0.2057845894 2.5188271931 - -0.1848214766 2.4963786361 + 0.2039241787 2.5170624743 + 0.2057845894 2.5188271931 + 0.1848214766 2.4963786361 -0.2938767202 2.6269353164 -0.1132494060 2.4531179322 - 0.0000000000 1.9499097825 - 0.0000000000 1.9494140216 + 0.5501787175 3.0567806793 -0.3667863614 2.7373447311 - 0.0000000000 1.9505602115 - 0.0000000000 1.9516836775 - -0.4090738726 2.8063162838 + 0.4090738726 2.8063162838 diff --git a/files_xyz/zora/sr/ada_O-H-O.dat b/files_xyz/zora/sr/ada_O-H-O.dat new file mode 100644 index 0000000..89e2bab --- /dev/null +++ b/files_xyz/zora/sr/ada_O-H-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=93) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 0 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 0 +82.162162 0 +87.297297 0 +92.432432 0 +97.567568 0 +102.702703 0 +107.837838 2 +112.972973 0 +118.108108 1 +123.243243 0 +128.378378 0 +133.513514 0 +138.648649 0 +143.783784 1 +148.918919 3 +154.054054 1 +159.189189 1 +164.324324 4 +169.459459 7 +174.594595 8 +179.729730 64 +184.864865 1 +190.000000 0 diff --git a/files_xyz/zora/sr/transfer_O-H-O.dat b/files_xyz/zora/sr/transfer_O-H-O.dat index 97ee657..53f8ebb 100644 --- a/files_xyz/zora/sr/transfer_O-H-O.dat +++ b/files_xyz/zora/sr/transfer_O-H-O.dat @@ -1,124 +1,94 @@ # q1 [Angstrom] q2 [Angstrom] - -0.2777588433 2.6010497663 - -0.2115083765 2.5212723508 - -0.2116495042 2.5217056068 - -0.1044769162 2.4444915493 - -0.1421006932 2.4781328804 - -0.1111180077 2.4515695587 - -0.1333332290 2.4646328620 - -0.3707580985 2.7434052392 - 0.0000000000 1.9507741569 - 0.0000000000 1.9516593832 - -0.4057075248 2.8001157959 - -0.1225941562 2.4543767060 - -0.2932654367 2.6185421825 - -0.2039159901 2.5147045280 - -0.1492385078 2.4722238424 - 0.0000000000 1.9464677793 - 0.0000000000 1.9470748707 - -0.0980627169 2.4443717228 - 0.0000000000 1.9475778704 - 0.0000000000 1.9496764459 - -0.2773543878 2.6021423891 - -0.2780666417 2.6023259876 - -0.2084523254 2.5176264528 - -0.2089017146 2.5179636730 - -0.1162485952 2.4515134630 - -0.3763205739 2.7452307487 + 0.1841800115 2.5099506037 + 0.1111180077 2.4515695587 + 0.1421006932 2.4781328804 + -0.0435541071 2.4251723297 + 0.0433184710 2.4251663283 + -0.0028602341 2.4254152017 + 0.4351693105 2.8522862472 -0.1166176528 2.4514353248 -0.1101726937 2.4482863050 - 0.0000000000 1.9498073341 - 0.0000000000 1.9504764327 -0.0802612587 2.4378458227 - -0.0894874390 2.4392458126 -0.3080828474 2.6440194089 - -0.1897382481 2.5008662008 - -0.1887935935 2.5004945942 - -0.1894628727 2.5008554600 - -0.1886979321 2.5000724081 - 0.0000000000 1.9458654937 - 0.0000000000 1.9467647955 - -0.1721461038 2.4906175719 - -0.3242325374 2.6723320657 - -0.4498311388 2.8742622939 - -0.3732716006 2.7471561260 - 0.0000000000 1.9510074225 - 0.0000000000 1.9524334589 - -0.4031359673 2.7962226512 - -0.1452354518 2.4695578224 - -0.1452354518 2.4695578224 - -0.2176813095 2.5290825180 - 0.0000000000 1.9470983065 - -0.2176813095 2.5290825180 - 0.0000000000 1.9470983065 - -0.2884797276 2.6243452100 - -0.4807411727 2.9344488902 - -0.4034022007 2.7960194472 - -0.4102498991 2.8022891251 - -0.1006535073 2.4421479314 - -0.0433184710 2.4251663283 - 0.0000000000 1.9505439345 - -0.0435541071 2.4251723297 - -0.1863784870 2.4986342090 - -0.2963472122 2.6310713388 - -0.1166266239 2.4549865585 - 0.0000000000 1.9505827627 - 0.0000000000 1.9488811303 - -0.1148619113 2.4515835695 - -0.1865351162 2.4987008562 - -0.3000951420 2.6369967141 + -0.0894874390 2.4392458126 + 0.0795264357 2.4377373762 + -0.0920258320 2.4400604243 + -0.3066924880 2.6423346757 -0.0133169987 2.4210030638 -0.1739266109 2.4892021067 -0.1710810901 2.4868655680 - 0.0000000000 1.9469396457 - 0.0000000000 1.9477694289 -0.1724046710 2.4879446685 -0.1740620649 2.4895765811 -0.0045468421 2.4194977906 - 0.0000000000 1.9536741106 - 0.0000000000 1.9532474218 + -0.0849160462 2.4407670954 + -0.0814360209 2.4393099811 + -0.0980627169 2.4443717228 + -0.2780666417 2.6023259876 + 0.2773543878 2.6021423891 + 0.1333332290 2.4646328620 + 0.1384521967 2.4644252221 -0.3025304821 2.6438384843 - -0.1384521967 2.4644252221 + -0.5341754393 3.0313271633 + 0.2884797276 2.6243452100 + 0.4807411727 2.9344488902 + 0.1452354518 2.4695578224 + 0.1452354518 2.4695578224 + -0.2176813095 2.5290825180 + -0.2176813095 2.5290825180 + 0.1044769162 2.4444915493 + 0.2777588433 2.6010497663 + 0.2116495042 2.5217056068 + -0.2115083765 2.5212723508 + -0.1897382481 2.5008662008 + -0.1887935935 2.5004945942 + -0.1894628727 2.5008554600 + -0.1886979321 2.5000724081 + 0.2932654367 2.6185421825 + -0.1225941562 2.4543767060 + 0.2039159901 2.5147045280 + -0.1492385078 2.4722238424 + -0.1681945327 2.4843887122 + -0.1919076777 2.5047407130 + -0.4600652570 2.8881209537 + -0.1368446249 2.4630833412 + -0.2084523254 2.5176264528 + -0.2089017146 2.5179636730 + -0.3763205739 2.7452307487 + -0.1162485952 2.4515134630 -0.1262656549 2.4588308750 - 0.0000000000 1.9473397434 - 0.0000000000 1.9482912740 -0.2401171662 2.5562143974 - 0.0000000000 1.9485599862 - -0.1572977729 2.4801906260 - -0.1669236619 2.4868760401 - -0.1443717122 2.4712919612 - -0.0920258320 2.4400604243 - -0.0795264357 2.4377373762 - -0.3066924880 2.6423346757 - 0.0000000000 1.9511777674 - -0.4001252693 2.7568287466 - -0.4351693105 2.8522862472 - -0.0028602341 2.4254152017 - 0.0000000000 1.9491900326 + 0.1572977729 2.4801906260 + -0.5412910532 3.0405096375 + 0.3000951420 2.6369967141 + 0.1865351162 2.4987008562 + -0.1148619113 2.4515835695 + 0.1861852343 2.4982921471 + -0.1168668550 2.4534546523 + -0.3085489475 2.6481194382 + -0.5156830568 2.9922038441 + 0.1669236619 2.4868760401 + 0.1443717122 2.4712919612 + 0.6435229588 3.2461583065 + 0.3242325374 2.6723320657 + 0.4498311388 2.8742622939 + -0.1721461038 2.4906175719 + -0.3707580985 2.7434052392 + 0.4057075248 2.8001157959 + 0.1863784870 2.4986342090 + -0.2963472122 2.6310713388 + -0.1166266239 2.4549865585 + 0.5528994463 3.0607589040 + -0.4034022007 2.7960194472 + -0.4102498991 2.8022891251 + 0.1006535073 2.4421479314 + 0.7298496469 3.4179168426 + -0.3732716006 2.7471561260 + 0.4031359673 2.7962226512 -0.1004237487 2.4422105229 + 0.7317983231 3.4216735789 -0.4105999043 2.8027185678 -0.4036287845 2.7963728133 - 0.0000000000 1.9517219211 - 0.0000000000 1.9506420513 -0.4251999548 2.8339726606 - -0.0955667541 2.4435442841 + 0.0955667541 2.4435442841 -0.4735376188 2.9184810388 - -0.1376311529 2.4647770910 - -0.1841800115 2.5099506037 - 0.0000000000 1.9559290494 - -0.0849160462 2.4407670954 - 0.0000000000 1.9512670018 - 0.0000000000 1.9518242717 - -0.0814360209 2.4393099811 - 0.0000000000 1.9516353867 - 0.0000000000 1.9512415484 - -0.1681945327 2.4843887122 - -0.1919076777 2.5047407130 - -0.1368446249 2.4630833412 - 0.0000000000 1.9483426123 - 0.0000000000 1.9491743752 - -0.4600652570 2.8881209537 - 0.0000000000 1.9525554116 - -0.1168668550 2.4534546523 - -0.3085489475 2.6481194382 - -0.1861852343 2.4982921471 + 0.1376311529 2.4647770910 diff --git a/functions.py b/functions.py old mode 100755 new mode 100644 index 5066416..8adab8e --- a/functions.py +++ b/functions.py @@ -143,7 +143,7 @@ def reading_files_xyz(working_dir): count = 0 columns = 4 while count < len(list_xyz): - print(f'\t'.join(list_xyz[count:count + columns])) + print(f'\t' + f'\t'.join(list_xyz[count:count + columns])) count += columns @@ -183,7 +183,7 @@ def what_xyz_files(files_list_xyz, working_dir): input_list = input_list.split(',') if len(input_list[0]) == 0 or input_list[0].lower().strip() == 'all': - return files_list_xyz + files_list = list(files_list_xyz) else: @@ -203,6 +203,16 @@ def what_xyz_files(files_list_xyz, working_dir): # - EXITING with a not empty list if len(files_list) > 0: break + + print(f'\tworking files:') + count = 0 + columns = 4 + while count < len(files_list): + print(f'\t' + f'\t'.join(files_list[count:count + columns])) + + count += columns + + print() return files_list # --------------------------------------------------------------------------------------- @@ -408,7 +418,7 @@ def format_xyz(file_xyz): elif line_number > 2: # - checking length, four fields try: - assert len(values) == 4 + assert len(values) >= 4 except AssertionError as e: error_message += '\n | Not enough data for elements and coordinates.' error_message += '\n It must be: (element, x, y, z)' @@ -450,6 +460,7 @@ def format_xyz(file_xyz): if not error_message: df = pd.read_csv(file_xyz, delim_whitespace=True, + usecols=[0, 1, 2, 3], skiprows=2, header=None, names=["element", "x-coordinate", diff --git a/geo_test_pdb/.dihedral.txt.swp b/geo_test_pdb/.dihedral.txt.swp new file mode 100644 index 0000000..4667b51 Binary files /dev/null and b/geo_test_pdb/.dihedral.txt.swp differ diff --git a/geo_test_pdb/0ZD_model.pdb b/geo_test_pdb/0ZD_model.pdb new file mode 100644 index 0000000..2c13817 --- /dev/null +++ b/geo_test_pdb/0ZD_model.pdb @@ -0,0 +1,225 @@ +ATOM 1 O62 0ZD A 1 -16.202 18.781 -35.336 1.00 10.00 O +ATOM 2 C60 0ZD A 1 -16.663 19.920 -35.553 1.00 10.00 C +ATOM 3 O61 0ZD A 1 -16.903 20.277 -36.716 1.00 10.00 O +ATOM 4 C56 0ZD A 1 -16.953 20.857 -34.410 1.00 10.00 C +ATOM 5 C57 0ZD A 1 -18.450 20.786 -34.033 1.00 10.00 C +ATOM 6 C59 0ZD A 1 -18.804 21.710 -32.879 1.00 10.00 C +ATOM 7 C58 0ZD A 1 -19.029 19.391 -33.818 1.00 10.00 C +ATOM 8 N40 0ZD A 1 -15.967 20.685 -33.315 1.00 10.00 N +ATOM 9 S41 0ZD A 1 -14.862 21.721 -33.178 1.00 10.00 S +ATOM 10 O43 0ZD A 1 -15.375 23.018 -33.550 1.00 10.00 O +ATOM 11 C45 0ZD A 1 -13.666 21.295 -34.178 1.00 10.00 C +ATOM 12 C5A 0ZD A 1 -13.608 21.787 -35.489 1.00 10.00 C +ATOM 13 C49 0ZD A 1 -12.580 21.412 -36.358 1.00 10.00 C +ATOM 14 C48 0ZD A 1 -11.556 20.555 -35.938 1.00 10.00 C +ATOM 15 C50 0ZD A 1 -10.438 20.173 -36.850 1.00 10.00 C +ATOM 16 C55 0ZD A 1 -9.924 18.877 -36.889 1.00 10.00 C +ATOM 17 C54 0ZD A 1 -8.871 18.564 -37.754 1.00 10.00 C +ATOM 18 C53 0ZD A 1 -8.316 19.542 -38.575 1.00 10.00 C +ATOM 19 C52 0ZD A 1 -8.806 20.842 -38.528 1.00 10.00 C +ATOM 20 C51 0ZD A 1 -9.865 21.147 -37.670 1.00 10.00 C +ATOM 21 C47 0ZD A 1 -11.595 20.071 -34.623 1.00 10.00 C +ATOM 22 C46 0ZD A 1 -12.639 20.435 -33.755 1.00 10.00 C +ATOM 23 O42 0ZD A 1 -14.303 21.712 -31.839 1.00 10.00 O +ATOM 24 C39 0ZD A 1 -15.913 19.409 -32.579 1.00 10.00 C +ATOM 25 C38 0ZD A 1 -16.273 19.461 -31.104 1.00 10.00 C +ATOM 26 N37 0ZD A 1 -16.036 18.123 -30.578 1.00 10.00 N +ATOM 27 C35 0ZD A 1 -16.798 17.063 -30.835 1.00 10.00 C +ATOM 28 O36 0ZD A 1 -17.843 17.161 -31.482 1.00 10.00 O +ATOM 29 C33 0ZD A 1 -16.400 15.716 -30.280 1.00 10.00 C +ATOM 30 C32 0ZD A 1 -17.287 14.645 -30.364 1.00 10.00 C +ATOM 31 C31 0ZD A 1 -16.928 13.402 -29.843 1.00 10.00 C +ATOM 32 C30 0ZD A 1 -15.687 13.222 -29.239 1.00 10.00 C +ATOM 33 C34 0ZD A 1 -15.155 15.529 -29.668 1.00 10.00 C +ATOM 34 C29 0ZD A 1 -14.789 14.283 -29.148 1.00 10.00 C +ATOM 35 C27 0ZD A 1 -13.449 14.069 -28.495 1.00 10.00 C +ATOM 36 O28 0ZD A 1 -13.253 13.028 -27.868 1.00 10.00 O +ATOM 37 N26 0ZD A 1 -12.488 14.993 -28.605 1.00 10.00 N +ATOM 38 C25 0ZD A 1 -11.210 14.876 -27.900 1.00 10.00 C +ATOM 39 C24 0ZD A 1 -11.412 15.375 -26.475 1.00 10.00 C +ATOM 40 N16 0ZD A 1 -10.222 15.420 -25.603 1.00 10.00 N +ATOM 41 C17 0ZD A 1 -10.014 14.395 -24.551 1.00 10.00 C +ATOM 42 C21 0ZD A 1 -11.099 14.469 -23.506 1.00 10.00 C +ATOM 43 O23 0ZD A 1 -10.828 14.180 -22.324 1.00 10.00 O +ATOM 44 O22 0ZD A 1 -12.261 14.798 -23.804 1.00 10.00 O +ATOM 45 C18 0ZD A 1 -9.827 12.933 -24.999 1.00 10.00 C +ATOM 46 C20 0ZD A 1 -8.739 12.773 -26.054 1.00 10.00 C +ATOM 47 C19 0ZD A 1 -11.107 12.190 -25.375 1.00 10.00 C +ATOM 48 S13 0ZD A 1 -9.378 16.690 -25.588 1.00 10.00 S +ATOM 49 O14 0ZD A 1 -8.025 16.425 -25.183 1.00 10.00 O +ATOM 50 O15 0ZD A 1 -9.451 17.315 -26.887 1.00 10.00 O +ATOM 51 C10 0ZD A 1 -10.049 17.691 -24.490 1.00 10.00 C +ATOM 52 C9 0ZD A 1 -9.657 17.722 -23.139 1.00 10.00 C +ATOM 53 C8 0ZD A 1 -10.253 18.590 -22.217 1.00 10.00 C +ATOM 54 C11 0ZD A 1 -11.067 18.572 -24.877 1.00 10.00 C +ATOM 55 C12 0ZD A 1 -11.666 19.442 -23.963 1.00 10.00 C +ATOM 56 C7 0ZD A 1 -11.271 19.457 -22.619 1.00 10.00 C +ATOM 57 C1 0ZD A 1 -11.886 20.424 -21.661 1.00 10.00 C +ATOM 58 C6 0ZD A 1 -13.250 20.714 -21.686 1.00 10.00 C +ATOM 59 C5 0ZD A 1 -13.791 21.636 -20.787 1.00 10.00 C +ATOM 60 C4 0ZD A 1 -12.965 22.295 -19.879 1.00 10.00 C +ATOM 61 C3 0ZD A 1 -11.601 22.028 -19.863 1.00 10.00 C +ATOM 62 C2 0ZD A 1 -11.066 21.100 -20.749 1.00 10.00 C +ATOM 63 H1 0ZD A 1 -16.095 18.320 -36.160 1.00 10.00 H +ATOM 64 H2 0ZD A 1 -16.797 21.872 -34.805 1.00 10.00 H +ATOM 65 H3 0ZD A 1 -18.985 21.191 -34.905 1.00 10.00 H +ATOM 66 H4 0ZD A 1 -19.877 21.620 -32.653 1.00 10.00 H +ATOM 67 H5 0ZD A 1 -18.217 21.430 -31.992 1.00 10.00 H +ATOM 68 H6 0ZD A 1 -18.574 22.749 -33.157 1.00 10.00 H +ATOM 69 H7 0ZD A 1 -20.094 19.472 -33.556 1.00 10.00 H +ATOM 70 H8 0ZD A 1 -18.922 18.803 -34.742 1.00 10.00 H +ATOM 71 H9 0ZD A 1 -18.488 18.891 -33.001 1.00 10.00 H +ATOM 72 H10 0ZD A 1 -14.372 22.468 -35.834 1.00 10.00 H +ATOM 73 H11 0ZD A 1 -12.575 21.789 -37.370 1.00 10.00 H +ATOM 74 H12 0ZD A 1 -10.341 18.113 -36.249 1.00 10.00 H +ATOM 75 H13 0ZD A 1 -8.485 17.556 -37.786 1.00 10.00 H +ATOM 76 H14 0ZD A 1 -7.508 19.291 -39.246 1.00 10.00 H +ATOM 77 H15 0ZD A 1 -8.371 21.610 -39.150 1.00 10.00 H +ATOM 78 H16 0ZD A 1 -10.248 22.156 -37.640 1.00 10.00 H +ATOM 79 H17 0ZD A 1 -10.815 19.411 -34.273 1.00 10.00 H +ATOM 80 H18 0ZD A 1 -12.652 20.047 -32.747 1.00 10.00 H +ATOM 81 H19 0ZD A 1 -16.609 18.711 -33.068 1.00 10.00 H +ATOM 82 H20 0ZD A 1 -14.887 19.020 -32.659 1.00 10.00 H +ATOM 83 H21 0ZD A 1 -15.639 20.193 -30.583 1.00 10.00 H +ATOM 84 H22 0ZD A 1 -17.330 19.737 -30.979 1.00 10.00 H +ATOM 85 H23 0ZD A 1 -15.244 17.992 -29.981 1.00 10.00 H +ATOM 86 H24 0ZD A 1 -18.251 14.777 -30.832 1.00 10.00 H +ATOM 87 H25 0ZD A 1 -17.618 12.573 -29.909 1.00 10.00 H +ATOM 88 H26 0ZD A 1 -15.419 12.255 -28.839 1.00 10.00 H +ATOM 89 H27 0ZD A 1 -14.467 16.359 -29.596 1.00 10.00 H +ATOM 90 H28 0ZD A 1 -12.648 15.790 -29.188 1.00 10.00 H +ATOM 91 H29 0ZD A 1 -10.887 13.825 -27.885 1.00 10.00 H +ATOM 92 H30 0ZD A 1 -10.448 15.487 -28.405 1.00 10.00 H +ATOM 93 H31 0ZD A 1 -11.817 16.396 -26.536 1.00 10.00 H +ATOM 94 H32 0ZD A 1 -12.150 14.716 -25.995 1.00 10.00 H +ATOM 95 H33 0ZD A 1 -9.081 14.668 -24.037 1.00 10.00 H +ATOM 96 H34 0ZD A 1 -11.610 14.261 -21.790 1.00 10.00 H +ATOM 97 H35 0ZD A 1 -9.444 12.411 -24.110 1.00 10.00 H +ATOM 98 H36 0ZD A 1 -7.840 13.323 -25.740 1.00 10.00 H +ATOM 99 H37 0ZD A 1 -8.494 11.707 -26.170 1.00 10.00 H +ATOM 100 H38 0ZD A 1 -9.098 13.173 -27.014 1.00 10.00 H +ATOM 101 H39 0ZD A 1 -11.860 12.334 -24.587 1.00 10.00 H +ATOM 102 H40 0ZD A 1 -11.493 12.583 -26.327 1.00 10.00 H +ATOM 103 H41 0ZD A 1 -10.890 11.117 -25.483 1.00 10.00 H +ATOM 104 H42 0ZD A 1 -8.874 17.057 -22.804 1.00 10.00 H +ATOM 105 H43 0ZD A 1 -9.924 18.589 -21.188 1.00 10.00 H +ATOM 106 H44 0ZD A 1 -11.396 18.579 -25.906 1.00 10.00 H +ATOM 107 H45 0ZD A 1 -12.444 20.112 -24.297 1.00 10.00 H +ATOM 108 H46 0ZD A 1 -13.891 20.223 -22.404 1.00 10.00 H +ATOM 109 H47 0ZD A 1 -14.852 21.838 -20.796 1.00 10.00 H +ATOM 110 H48 0ZD A 1 -13.384 23.012 -19.189 1.00 10.00 H +ATOM 111 H49 0ZD A 1 -10.958 22.541 -19.163 1.00 10.00 H +ATOM 112 H50 0ZD A 1 -10.005 20.898 -20.734 1.00 10.00 H +CONECT 1 2 63 +CONECT 2 1 3 4 +CONECT 3 2 +CONECT 4 2 5 8 64 +CONECT 5 4 6 7 65 +CONECT 6 5 66 67 68 +CONECT 7 5 69 70 71 +CONECT 8 4 9 24 +CONECT 9 8 10 11 23 +CONECT 10 9 +CONECT 11 9 12 22 +CONECT 12 11 13 72 +CONECT 13 12 14 73 +CONECT 14 13 15 21 +CONECT 15 14 16 20 +CONECT 16 15 17 74 +CONECT 17 16 18 75 +CONECT 18 17 19 76 +CONECT 19 18 20 77 +CONECT 20 15 19 78 +CONECT 21 14 22 79 +CONECT 22 11 21 80 +CONECT 23 9 +CONECT 24 8 25 81 82 +CONECT 25 24 26 83 84 +CONECT 26 25 27 85 +CONECT 27 26 28 29 +CONECT 28 27 +CONECT 29 27 30 33 +CONECT 30 29 31 86 +CONECT 31 30 32 87 +CONECT 32 31 34 88 +CONECT 33 29 34 89 +CONECT 34 32 33 35 +CONECT 35 34 36 37 +CONECT 36 35 +CONECT 37 35 38 90 +CONECT 38 37 39 91 92 +CONECT 39 38 40 93 94 +CONECT 40 39 41 48 +CONECT 41 40 42 45 95 +CONECT 42 41 43 44 +CONECT 43 42 96 +CONECT 44 42 +CONECT 45 41 46 47 97 +CONECT 46 45 98 99 100 +CONECT 47 45 101 102 103 +CONECT 48 40 49 50 51 +CONECT 49 48 +CONECT 50 48 +CONECT 51 48 52 54 +CONECT 52 51 53 104 +CONECT 53 52 56 105 +CONECT 54 51 55 106 +CONECT 55 54 56 107 +CONECT 56 53 55 57 +CONECT 57 56 58 62 +CONECT 58 57 59 108 +CONECT 59 58 60 109 +CONECT 60 59 61 110 +CONECT 61 60 62 111 +CONECT 62 57 61 112 +CONECT 63 1 +CONECT 64 4 +CONECT 65 5 +CONECT 66 6 +CONECT 67 6 +CONECT 68 6 +CONECT 69 7 +CONECT 70 7 +CONECT 71 7 +CONECT 72 12 +CONECT 73 13 +CONECT 74 16 +CONECT 75 17 +CONECT 76 18 +CONECT 77 19 +CONECT 78 20 +CONECT 79 21 +CONECT 80 22 +CONECT 81 24 +CONECT 82 24 +CONECT 83 25 +CONECT 84 25 +CONECT 85 26 +CONECT 86 30 +CONECT 87 31 +CONECT 88 32 +CONECT 89 33 +CONECT 90 37 +CONECT 91 38 +CONECT 92 38 +CONECT 93 39 +CONECT 94 39 +CONECT 95 41 +CONECT 96 43 +CONECT 97 45 +CONECT 98 46 +CONECT 99 46 +CONECT 100 46 +CONECT 101 47 +CONECT 102 47 +CONECT 103 47 +CONECT 104 52 +CONECT 105 53 +CONECT 106 54 +CONECT 107 55 +CONECT 108 58 +CONECT 109 59 +CONECT 110 60 +CONECT 111 61 +CONECT 112 62 +END diff --git a/geo_test_pdb/0zd.xyz b/geo_test_pdb/0zd.xyz new file mode 100644 index 0000000..23bd9e3 --- /dev/null +++ b/geo_test_pdb/0zd.xyz @@ -0,0 +1,114 @@ + 112 +Chemical Component 0ZD, taken from http://ligand-expo.rcsb.org/reports/0/0ZD/index.html +O62 -16.202 18.781 -35.336 O 1 O62 +C60 -16.663 19.920 -35.553 C 2 C60 +O61 -16.903 20.277 -36.716 O 3 O61 +C56 -16.953 20.857 -34.410 C 4 C56 +C57 -18.450 20.786 -34.033 C 5 C57 +C59 -18.804 21.710 -32.879 C 6 C59 +C58 -19.029 19.391 -33.818 C 7 C58 +N40 -15.967 20.685 -33.315 N 8 N40 +S41 -14.862 21.721 -33.178 S 9 S41 +O43 -15.375 23.018 -33.550 O 10 O43 +C45 -13.666 21.295 -34.178 C 11 C45 +C5A -13.608 21.787 -35.489 C 12 C5A +C49 -12.580 21.412 -36.358 C 13 C49 +C48 -11.556 20.555 -35.938 C 14 C48 +C50 -10.438 20.173 -36.850 C 15 C50 +C55 -9.924 18.877 -36.889 C 16 C55 +C54 -8.871 18.564 -37.754 C 17 C54 +C53 -8.316 19.542 -38.575 C 18 C53 +C52 -8.806 20.842 -38.528 C 19 C52 +C51 -9.865 21.147 -37.670 C 20 C51 +C47 -11.595 20.071 -34.623 C 21 C47 +C46 -12.639 20.435 -33.755 C 22 C46 +O42 -14.303 21.712 -31.839 O 23 O42 +C39 -15.913 19.409 -32.579 C 24 C39 +C38 -16.273 19.461 -31.104 C 25 C38 +N37 -16.036 18.123 -30.578 N 26 N37 +C35 -16.798 17.063 -30.835 C 27 C35 +O36 -17.843 17.161 -31.482 O 28 O36 +C33 -16.400 15.716 -30.280 C 29 C33 +C32 -17.287 14.645 -30.364 C 30 C32 +C31 -16.928 13.402 -29.843 C 31 C31 +C30 -15.687 13.222 -29.239 C 32 C30 +C34 -15.155 15.529 -29.668 C 33 C34 +C29 -14.789 14.283 -29.148 C 34 C29 +C27 -13.449 14.069 -28.495 C 35 C27 +O28 -13.253 13.028 -27.868 O 36 O28 +N26 -12.488 14.993 -28.605 N 37 N26 +C25 -11.210 14.876 -27.900 C 38 C25 +C24 -11.412 15.375 -26.475 C 39 C24 +N16 -10.222 15.420 -25.603 N 40 N16 +C17 -10.014 14.395 -24.551 C 41 C17 +C21 -11.099 14.469 -23.506 C 42 C21 +O23 -10.828 14.180 -22.324 O 43 O23 +O22 -12.261 14.798 -23.804 O 44 O22 +C18 -9.827 12.933 -24.999 C 45 C18 +C20 -8.739 12.773 -26.054 C 46 C20 +C19 -11.107 12.190 -25.375 C 47 C19 +S13 -9.378 16.690 -25.588 S 48 S13 +O14 -8.025 16.425 -25.183 O 49 O14 +O15 -9.451 17.315 -26.887 O 50 O15 +C10 -10.049 17.691 -24.490 C 51 C10 +C9 -9.657 17.722 -23.139 C 52 C9 +C8 -10.253 18.590 -22.217 C 53 C8 +C11 -11.067 18.572 -24.877 C 54 C11 +C12 -11.666 19.442 -23.963 C 55 C12 +C7 -11.271 19.457 -22.619 C 56 C7 +C1 -11.886 20.424 -21.661 C 57 C1 +C6 -13.250 20.714 -21.686 C 58 C6 +C5 -13.791 21.636 -20.787 C 59 C5 +C4 -12.965 22.295 -19.879 C 60 C4 +C3 -11.601 22.028 -19.863 C 61 C3 +C2 -11.066 21.100 -20.749 C 62 C2 +H1 -16.095 18.320 -36.160 H 63 H1 +H2 -16.797 21.872 -34.805 H 64 H2 +H3 -18.985 21.191 -34.905 H 65 H3 +H4 -19.877 21.620 -32.653 H 66 H4 +H5 -18.217 21.430 -31.992 H 67 H5 +H6 -18.574 22.749 -33.157 H 68 H6 +H7 -20.094 19.472 -33.556 H 69 H7 +H8 -18.922 18.803 -34.742 H 70 H8 +H9 -18.488 18.891 -33.001 H 71 H9 +H10 -14.372 22.468 -35.834 H 72 H10 +H11 -12.575 21.789 -37.370 H 73 H11 +H12 -10.341 18.113 -36.249 H 74 H12 +H13 -8.485 17.556 -37.786 H 75 H13 +H14 -7.508 19.291 -39.246 H 76 H14 +H15 -8.371 21.610 -39.150 H 77 H15 +H16 -10.248 22.156 -37.640 H 78 H16 +H17 -10.815 19.411 -34.273 H 79 H17 +H18 -12.652 20.047 -32.747 H 80 H18 +H19 -16.609 18.711 -33.068 H 81 H19 +H20 -14.887 19.020 -32.659 H 82 H20 +H21 -15.639 20.193 -30.583 H 83 H21 +H22 -17.330 19.737 -30.979 H 84 H22 +H23 -15.244 17.992 -29.981 H 85 H23 +H24 -18.251 14.777 -30.832 H 86 H24 +H25 -17.618 12.573 -29.909 H 87 H25 +H26 -15.419 12.255 -28.839 H 88 H26 +H27 -14.467 16.359 -29.596 H 89 H27 +H28 -12.648 15.790 -29.188 H 90 H28 +H29 -10.887 13.825 -27.885 H 91 H29 +H30 -10.448 15.487 -28.405 H 92 H30 +H31 -11.817 16.396 -26.536 H 93 H31 +H32 -12.150 14.716 -25.995 H 94 H32 +H33 -9.081 14.668 -24.037 H 95 H33 +H34 -11.610 14.261 -21.790 H 96 H34 +H35 -9.444 12.411 -24.110 H 97 H35 +H36 -7.840 13.323 -25.740 H 98 H36 +H37 -8.494 11.707 -26.170 H 99 H37 +H38 -9.098 13.173 -27.014 H 100 H38 +H39 -11.860 12.334 -24.587 H 101 H39 +H40 -11.493 12.583 -26.327 H 102 H40 +H41 -10.890 11.117 -25.483 H 103 H41 +H42 -8.874 17.057 -22.804 H 104 H42 +H43 -9.924 18.589 -21.188 H 105 H43 +H44 -11.396 18.579 -25.906 H 106 H44 +H45 -12.444 20.112 -24.297 H 107 H45 +H46 -13.891 20.223 -22.404 H 108 H46 +H47 -14.852 21.838 -20.796 H 109 H47 +H48 -13.384 23.012 -19.189 H 110 H48 +H49 -10.958 22.541 -19.163 H 111 H49 +H50 -10.005 20.898 -20.734 H 112 H50 diff --git a/geo_test_pdb/angle.txt b/geo_test_pdb/angle.txt new file mode 100644 index 0000000..069b4a0 --- /dev/null +++ b/geo_test_pdb/angle.txt @@ -0,0 +1,141 @@ +Bond Angles for 0ZD +Atom_I Atom_J Atom_K Angle_(Experimental_Model) +C53 C52 C51 119.5 +C52 C53 H14 120.1 +C53 C52 H15 120.2 +C53 C54 H13 119.7 +C51 C52 H15 120.3 +C52 C51 H16 119.3 +C54 C55 H12 119.9 +C50 C48 C47 120.4 +O61 C60 C56 119.7 +C49 C48 C47 118.2 +C48 C49 H11 119.4 +C49 C5A H10 119.4 +C48 C47 C46 120.7 +C48 C47 H17 119.7 +C60 O62 H1 109.5 +C60 C56 C57 110.1 +C60 C56 N40 111.1 +C60 C56 H2 105.9 +C5A C45 C46 117.8 +C45 C46 C47 121.0 +C46 C47 H17 119.6 +C47 C46 H18 119.5 +C57 C56 N40 117.3 +C56 C57 C58 116.4 +C56 C57 C59 112.5 +C57 C56 H2 105.5 +C56 C57 H3 105.1 +C56 N40 S41 118.1 +C56 N40 C39 119.6 +N40 C56 H2 106.1 +C45 C46 H18 119.5 +C45 S41 O42 106.5 +C59 C57 C58 111.1 +C58 C57 H3 105.3 +C57 C58 H7 109.5 +C57 C58 H8 109.5 +C57 C58 H9 109.5 +C59 C57 H3 105.3 +C57 C59 H4 109.5 +C57 C59 H5 109.5 +C57 C59 H6 109.5 +O43 S41 O42 112.4 +S41 N40 C39 121.2 +N40 S41 O42 111.0 +N40 C39 C38 116.5 +N40 C39 H19 107.7 +N40 C39 H20 107.7 +C39 C38 N37 106.3 +C38 C39 H19 107.7 +C38 C39 H20 107.7 +C39 C38 H21 110.3 +C39 C38 H22 110.3 +O36 C35 C33 119.1 +N37 C38 H21 110.3 +N37 C38 H22 110.2 +C38 N37 H23 117.7 +C35 N37 H23 117.7 +C35 C33 C34 120.9 +C32 C33 C34 119.3 +C32 C31 C30 120.5 +C31 C32 H24 120.0 +C32 C31 H25 119.8 +C33 C34 C29 120.9 +C33 C34 H27 119.5 +C31 C30 C29 120.3 +C30 C31 H25 119.8 +C31 C30 H26 119.8 +C30 C29 C34 119.0 +C34 C29 C27 121.4 +C29 C34 H27 119.5 +C30 C29 C27 119.6 +C29 C30 H26 119.8 +C29 C27 O28 118.9 +N26 C25 C24 108.0 +C25 N26 H28 118.9 +N26 C25 H29 109.8 +N26 C25 H30 109.8 +C25 C24 N16 117.1 +C24 C25 H29 109.8 +C24 C25 H30 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C20 H38 109.5 +H39 C19 H40 109.5 +H39 C19 H41 109.5 +H40 C19 H41 109.4 diff --git a/geo_test_pdb/bond_distance.txt b/geo_test_pdb/bond_distance.txt new file mode 100644 index 0000000..6df9055 --- /dev/null +++ b/geo_test_pdb/bond_distance.txt @@ -0,0 +1,118 @@ +Bond Distances for 0ZD +Atom_I Atom_J Distance_(Experimental_Model) +C53 C52 1.390 +C53 C54 1.392 +C52 C51 1.397 +C54 C55 1.398 +C51 C50 1.396 +C55 C50 1.395 +C50 C48 1.493 +O61 C60 1.240 +C49 C48 1.400 +C49 C5A 1.397 +C48 C47 1.402 +C60 O62 1.248 +C60 C56 1.506 +C5A C45 1.401 +C47 C46 1.406 +C56 C57 1.545 +C56 N40 1.484 +C45 C46 1.405 +C45 S41 1.616 +C57 C58 1.526 +C57 C59 1.520 +O43 S41 1.444 +N40 S41 1.521 +N40 C39 1.474 +S41 O42 1.451 +C39 C38 1.519 +O36 C35 1.233 +C38 N37 1.457 +C35 N37 1.331 +C35 C33 1.510 +C32 C33 1.393 +C32 C31 1.395 +C33 C34 1.400 +C31 C30 1.392 +C34 C29 1.399 +C30 C29 1.393 +C29 C27 1.506 +N26 C27 1.338 +N26 C25 1.464 +C27 O28 1.231 +C25 C24 1.523 +O15 S13 1.443 +C24 N16 1.476 +C20 C18 1.524 +N16 S13 1.525 +N16 C17 1.483 +S13 O14 1.437 +S13 C10 1.630 +C19 C18 1.527 +C18 C17 1.540 +C11 C10 1.401 +C11 C12 1.397 +C17 C21 1.508 +C10 C9 1.407 +C12 C7 1.401 +O22 C21 1.244 +C21 O23 1.247 +C9 C8 1.400 +C7 C8 1.396 +C7 C1 1.494 +C6 C1 1.395 +C6 C5 1.397 +C1 C2 1.400 +C5 C4 1.393 +C2 C3 1.390 +C4 C3 1.390 +O62 H1 0.950 +C56 H2 1.100 +C57 H3 1.100 +C59 H4 1.100 +C59 H5 1.100 +C59 H6 1.100 +C58 H7 1.100 +C58 H8 1.100 +C58 H9 1.100 +C5A H10 1.080 +C49 H11 1.080 +C55 H12 1.080 +C54 H13 1.080 +C53 H14 1.080 +C52 H15 1.080 +C51 H16 1.080 +C47 H17 1.080 +C46 H18 1.080 +C39 H19 1.100 +C39 H20 1.100 +C38 H21 1.100 +C38 H22 1.100 +N37 H23 1.000 +C32 H24 1.080 +C31 H25 1.081 +C30 H26 1.080 +C34 H27 1.080 +N26 H28 1.000 +C25 H29 1.100 +C25 H30 1.100 +C24 H31 1.100 +C24 H32 1.100 +C17 H33 1.100 +O23 H34 0.950 +C18 H35 1.100 +C20 H36 1.100 +C20 H37 1.100 +C20 H38 1.100 +C19 H39 1.099 +C19 H40 1.100 +C19 H41 1.100 +C9 H42 1.081 +C8 H43 1.080 +C11 H44 1.080 +C12 H45 1.080 +C6 H46 1.081 +C5 H47 1.080 +C4 H48 1.080 +C3 H49 1.080 +C2 H50 1.080 diff --git a/geo_test_pdb/dihedral.txt b/geo_test_pdb/dihedral.txt new file mode 100644 index 0000000..975410a --- /dev/null +++ b/geo_test_pdb/dihedral.txt @@ -0,0 +1,434 @@ +Torsion Angles for 0ZD +Atom_I Atom_J Atom_K Atom_L Angle_(Experimental_Model) +C52 C53 C54 H13 180.4 +C51 C52 C53 H15 180.0 +C53 C52 C51 H16 180.4 +C53 C54 C55 H12 180.6 +C51 C52 C53 H14 179.0 +C53 C52 C51 H15 180.0 +C51 C50 C48 C47 222.4 +C55 C50 C48 C47 40.9 +C49 C48 C50 C47 179.2 +C50 C48 C49 H11 1.4 +C50 C48 C47 C46 179.5 +C50 C48 C47 H17 359.5 +O61 C60 O62 H1 360.0 +O61 C60 C56 C57 81.9 +O61 C60 C56 N40 213.5 +O61 C60 C56 H2 328.3 +C50 C48 C49 C47 180.8 +C48 C49 C5A H10 178.6 +C49 C48 C47 C46 0.2 +C49 C48 C47 H17 180.2 +C49 C5A C45 C46 1.4 +C47 C48 C49 H11 180.6 +C45 C46 C47 C48 359.8 +C46 C47 C48 H17 180.0 +C48 C47 C46 H18 179.7 +C56 C60 O62 H1 178.9 +C57 C56 C60 N40 228.4 +C60 C56 C57 C58 50.0 +C60 C56 C57 C59 179.8 +C57 C56 C60 H2 113.6 +C60 C56 C57 H3 294.0 +C60 C56 N40 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C38 N37 H23 227.1 +H23 N37 C38 H21 348.1 +H23 N37 C38 H22 227.1 +H24 C32 C33 C34 179.9 +H24 C32 C31 C30 179.9 +H24 C32 C31 H25 360.0 +C32 C31 H25 C30 180.0 +H25 C31 C32 H24 360.0 +H25 C31 C30 C29 180.0 +H25 C31 C30 H26 360.0 +C31 C30 H26 C29 180.0 +H26 C30 C31 H25 360.0 +H26 C30 C29 C34 180.2 +H26 C30 C29 C27 0.2 +C33 C34 H27 C29 180.0 +H27 C34 C29 C27 359.6 +H28 N26 C25 C24 97.9 +H28 N26 C25 H29 217.6 +H28 N26 C25 H30 338.1 +N26 C25 H29 C24 241.4 +H29 C25 N26 H28 217.6 +N26 C25 H29 H30 120.7 +H29 C25 C24 N16 63.7 +C24 C25 H29 H30 239.3 +H29 C25 C24 H31 184.8 +H29 C25 C24 H32 302.6 +N26 C25 H30 C24 118.6 +H30 C25 N26 H28 338.1 +N26 C25 H30 H29 239.3 +H30 C25 C24 N16 303.3 +C24 C25 H30 H29 120.7 +H30 C25 C24 H31 64.4 +H30 C25 C24 H32 182.1 +C25 C24 H31 N16 233.1 +H31 C24 C25 H29 184.8 +H31 C24 C25 H30 64.4 +C25 C24 H31 H32 116.5 +H31 C24 N16 S13 328.3 +H31 C24 N16 C17 134.9 +N16 C24 H31 H32 243.4 +C25 C24 H32 N16 126.9 +H32 C24 C25 H29 302.6 +H32 C24 C25 H30 182.1 +C25 C24 H32 H31 243.5 +H32 C24 N16 S13 210.4 +H32 C24 N16 C17 17.1 +N16 C24 H32 H31 116.5 +H33 C17 N16 S13 347.8 +N16 C17 H33 C21 118.0 +H33 C17 C21 O23 327.1 +H35 C18 C17 H33 47.8 +H36 C20 C18 H35 293.7 +H37 C20 H36 H38 120.0 +H37 C20 C18 H35 53.6 +H36 C20 H37 H38 240.0 +H38 C20 C18 H35 173.6 +H36 C20 H38 H37 120.0 +H39 C19 C18 H35 66.3 +H40 C19 H39 H41 120.0 +H40 C19 C18 H35 186.3 +H39 C19 H40 H41 240.0 +H41 C19 C18 H35 306.3 +H39 C19 H41 H40 120.0 +C10 C9 H42 C8 180.0 +H42 C9 C8 H43 0.2 +H43 C8 C9 H42 0.2 +H44 C11 C12 C7 179.7 +H44 C11 C12 H45 359.7 +C11 C12 H45 C7 180.0 +H45 C12 C11 H44 359.7 +H45 C12 C7 C1 357.9 +H46 C6 C1 C2 178.2 +H46 C6 C5 C4 181.5 +H46 C6 C5 H47 1.5 +C6 C5 H47 C4 180.0 +H47 C5 C6 H46 1.5 +H47 C5 C4 C3 179.6 +H47 C5 C4 H48 359.6 +C5 C4 H48 C3 180.0 +H48 C4 C5 H47 359.6 +H48 C4 C3 H49 359.7 +H49 C3 C4 H48 359.7 +C1 C2 H50 C3 180.0 +H50 C2 C3 H49 359.9 diff --git a/histogram.py b/histogram.py new file mode 100644 index 0000000..dd72dad --- /dev/null +++ b/histogram.py @@ -0,0 +1,170 @@ +#!/usr/bin/env python3 +# ------------------------------------------------------------------------------------ +# July 2020 +# +# python3.x script by: +# +# name: Edison Florez (github.com/e-florez/) +# email: edisonffh@gmail.com + +# ------------------------------------------------------------------------------------ +# Main body +# ------------------------------------------------------------------------------------ + + +def rda(index_dict, distances_dict, grid, nbins): + import pandas as pd + import numpy as np + + """ + Args: + Return: + """ + + rmin, rmax, dr = grid + + occurrences = np.zeros(nbins, dtype=int) + + for xyz in index_dict: + indexes = index_dict[xyz] + distances_df = distances_dict[xyz] + + # - distances matrix (no atoms or labels) + distances_df = distances_df.loc[:, distances_df.columns != "atoms"] + + for pair in indexes: + distance = distances_df.iloc[pair[0], pair[1]] + + distance_hit = int(round((distance - rmin) / dr)) + if distance_hit > 0 and distance_hit < nbins: + occurrences[distance_hit] += 1 + + return occurrences + + +# --------------------------------------------------------------------------------------- + + +def angle(atom_A, atom_B, atom_C): + import numpy as np + + """ + Computing plane angle between three atoms A-B-C + + Args: + + Return: + + """ + # - Distance between each side atoms and the central one + d_AB = np.subtract(atom_A, atom_B) + d_BC = np.subtract(atom_C, atom_B) + + # - norm + n_AB = np.linalg.norm(d_AB) + n_BC = np.linalg.norm(d_BC) + + # - cosine throuth dot product + Cos = np.dot(d_AB, d_BC) / n_AB / n_BC + + # - angle in rad + angle = np.arccos(Cos) + + return np.degrees(angle) + + +# --------------------------------------------------------------------------------------- + + +def ada(index_dict, coordinates_XYZ, delta_angle, nbins): + import pandas as pd + import numpy as np + + """ + + Args: + + Return: + + """ + + occurrences = np.zeros(nbins, dtype=int) + + for xyz in index_dict: + indexes = index_dict[xyz] + df = coordinates_XYZ[xyz] + + # - distances matrix (no atoms or labels) + coordinates = df.loc[:, df.columns != "element"] + + for pair in indexes: + coordinates_A = coordinates.iloc[pair[0]] + atom_A = coordinates_A.to_numpy() + + coordinates_B = coordinates.iloc[pair[1]] + atom_B = coordinates_B.to_numpy() + + coordinates_C = coordinates.iloc[pair[2]] + atom_C = coordinates_C.to_numpy() + + # - computing angle A-B-C (using dot product) + angle_deg = angle(atom_A, atom_B, atom_C) + + angle_hit = int(round((angle_deg) / delta_angle)) + if angle_hit > 0 and angle_hit < nbins: + occurrences[angle_hit] += 1 + + return occurrences + + +# --------------------------------------------------------------------------------------- + + +def tda(index_dict, coordinates_XYZ, delta_angle, nbins): + import pandas as pd + import numpy as np + import dihedral + + """ + + Args: + + Return: + + """ + + occurrences = np.zeros(nbins, dtype=int) + + for xyz in index_dict: + indexes = index_dict[xyz] + df = coordinates_XYZ[xyz] + + # - distances matrix (no atoms or labels) + coordinates = df.loc[:, df.columns != "element"] + + for pair in indexes: + coordinates_A = coordinates.iloc[pair[0]] + atom_A = coordinates_A.to_numpy() + + coordinates_B = coordinates.iloc[pair[1]] + atom_B = coordinates_B.to_numpy() + + coordinates_C = coordinates.iloc[pair[2]] + atom_C = coordinates_C.to_numpy() + + coordinates_D = coordinates.iloc[pair[3]] + atom_D = coordinates_D.to_numpy() + + # - computing dihedral angle A-B-C-D + angle_deg = dihedral.dihedral(atom_A, atom_B, atom_C, atom_D) + + # print(angle_deg) + + angle_hit = int(round((angle_deg) / delta_angle)) + if angle_hit > 0 and angle_hit < nbins: + occurrences[angle_hit] += 1 + + return occurrences + + +# --------------------------------------------------------------------------------------- diff --git a/main.py b/main.py old mode 100755 new mode 100644 index e7d9d22..3e604f7 --- a/main.py +++ b/main.py @@ -19,6 +19,11 @@ # ------ Preamble # ------------------------------------------------------------------------------------ # Description: +import functions # module with all the individuals function to do analysis +import sys # module to recognise input argument form terminal (sys.argv) +import matrix_r # module to calculate of matriz distance +import numpy as np + message = """ @@ -41,8 +46,6 @@ # ------------------------------------------------------------------------------------ # ------ modules # ------------------------------------------------------------------------------------ -import functions # module with all the individuals function to do analysis -import sys # module to recognise input argument form terminal (sys.argv) # ------------------------------------------------------------------------------------ # ------ Main body @@ -50,7 +53,7 @@ if __name__ == '__main__': - # - Working directory: checking permission and existence + # - Working directory: checking permission and existence working_dir = functions.working_directory(sys.argv) # - Function to check if XYZ files exist, list and sort them in working directory @@ -59,27 +62,117 @@ # - Choosing XYZ files (by default all in working directory) files_xyz = functions.what_xyz_files(list_files_XYZ, working_dir) - # - Checking if those files has the XYZ format - # to create a dictionary 'coordinates_XYZ' with all the XYZ file + # - Checking if those files has the XYZ format + # to create a dictionary 'coordinates_XYZ' with all the XYZ file # with their coordinates in a pandas data frame coordinates_XYZ = functions.dict_coordinates_xyz(files_xyz) - #----------------------------------------------------------------------- + # ----------------------------------------------------------------------- # At this point we have loaded all coordinates as a pandas dataframe, # for those XYZ file with a right format. - - # - CESAR: define a grid for each histogram: bond, angle and dihedral angle - - - - # - ANDY: Computing matrix distance for each XYZ and create a - # dictionary whit a panda data frame with all distances between + # - ANDY: Computing matrix distance for each XYZ and create a + # dictionary whit a panda data frame with all distances between # all possible atomic pairs - - - + # R_Matrix = matrix_r.Distance_Matrix(files_xyz, coordinates_XYZ) # - EDISON: Multihistogram analysis for bond ditribution + + # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ + + # - grid to do a histogram analysis, rmin, rmax and bin width + grid = (1.5, 10.0, 0.05) + + # - number of bins for the accurences + rmin, rmax, dr = grid + nbins = int((rmax - rmin) / dr) + + # - distance matrix + import distance_matrix + distances_dict = distance_matrix.distance_matrix(coordinates_XYZ, grid) + + # - atomic pairs + input_list = ['O', 'O'] + # input_list = ['O', 'H'] + # input_list = ['Hg', 'O', 'H'] + # input_list = ['O', 'Hg', 'O'] + # input_list = ['O', 'H', 'O'] # Stern-Limbach + # input_list = ['Hg', 'O', 'H', 'H'] + + # - getting atoms list to compute distance, angle or dihedral + import atoms_index_list + index_dict = atoms_index_list.atoms_index_dict(distances_dict, input_list, grid) + + # ----------------------------------------------------------- + # - histogram analysis + import histogram + if len(input_list) == 2: + + # - radial (bond) distribution analysis (RDA); i.e., input_list = [A, B] + histogram = histogram.rda(index_dict, distances_dict, grid, nbins) + + # - saving histogram + distribution = np.linspace(rmin, rmax, nbins) + pair = f'-'.join(input_list) + + # if sum(histogram) > 0: + histogram_name = 'rda_' + pair + '.dat' + np.savetxt(histogram_name, np.transpose([distribution, histogram]), + delimiter=' ', + header='distance [Angstrom] occurrence (total=%i)' + % sum(histogram), + fmt='%.6f %28i') + + elif len(input_list) == 3: + # - anglular distribution analysis (ADA); i.e., input_list = [A, B, C] + + # - grid = 0.1 --> 1800 = (180 - 0)/0.1 + delta_angle = 5.0 + min_angle = 0 + max_angle = 190 + nbins = int((max_angle - min_angle) / delta_angle) + + histogram = histogram.ada( + index_dict, coordinates_XYZ, delta_angle, nbins) + + # - saving histogram + distribution = np.linspace(min_angle, max_angle, nbins) + pair = f'-'.join(input_list) + + histogram_name = 'ada_' + pair + '.dat' + np.savetxt(histogram_name, np.transpose([distribution, histogram]), + delimiter=' ', + header='angle [Degrees] occurrence (total=%i)' + % sum(histogram), + fmt='%.6f %28i') + + #------------------------------------------------ + # - Stern-Limbach analisys for atom tranfers + import atoms_transfer as transfer + transfer.atom_transfer(index_dict, input_list, distances_dict) + + + elif len(input_list) == 4: + # - dihedral analysis; i.e., input_list = [A, B, C, D] + + # grid = 0.1 --> 3600 = (3600 - 0)/0.1 + delta_angle = 5.0 + min_angle = 0 + max_angle = 360 + + nbins = int((max_angle - min_angle) / delta_angle) + + histogram = histogram.dada(index_dict, coordinates_XYZ, delta_angle, nbins) + + # - saving histogram + distribution = np.linspace(min_angle, max_angle, nbins) + pair = f'-'.join(input_list) + + histogram_name = 'dada_' + pair + '.dat' + np.savetxt(histogram_name, np.transpose([distribution, histogram]), + delimiter=' ', + header='angle [Degrees] occurrence (total=%i)' + % sum(histogram), + fmt='%.6f %28i') diff --git a/matrix_r.py b/matrix_r.py new file mode 100644 index 0000000..25068a1 --- /dev/null +++ b/matrix_r.py @@ -0,0 +1,61 @@ +#!/usr/bin/env python3 + +#---------------------------------------------------------# +# -Start: Build Distance Matrix to each .xyz # +#---------------------------------------------------------# +def Distance_Matrix(files_xyz, coordinates_XYZ): + import pandas as pd + import numpy as np + """[summary] + Computing distance matrix for each XYZ and create a dictionary whit + a panda data frame with all distances between all possible atomic pair + Args: + files_xyz (list) : It is a list with those XYZ file's names to analyse + coordinates_XYZ (dictionary) : KEY: file.xyz (str), + VALUES: pandas dataframe (element, x, y, z) + coordinates_xyz = {file.xyz: (element, x, y, z)} + Return: + R_Matrix (dictonary) : KEY: file.xyz (str), + VALUES: pandas dataframe (Distance between atoms) + R_Matrix = {file.xyz: ( iatom + jatom distance_jatom_iatom)} + """ + nfiles_xyz = len(files_xyz) # Number of files .xyz + R_Matrix = {} # Dictonary with distances matrix + for ifile in range(nfiles_xyz): + natoms = len(coordinates_XYZ[files_xyz[ifile]] + ['x-coordinate']) # Number of atoms + temporal_R_Matrix = np.zeros((natoms, natoms), dtype=float) + label = [] + # Computing distance matrix + for iatom in range(natoms): # Colums + # Labels of columns and rows + label.append(coordinates_XYZ[files_xyz[ifile]]['element'][iatom]) + jatom = iatom + while jatom < natoms: # Rows + distance_ab_x = coordinates_XYZ[files_xyz[ifile]]['x-coordinate'][jatom]\ + - coordinates_XYZ[files_xyz[ifile]]['x-coordinate'][iatom] + distance_ab_x *= distance_ab_x + distance_ab_y = coordinates_XYZ[files_xyz[ifile]]['y-coordinate'][jatom]\ + - coordinates_XYZ[files_xyz[ifile]]['y-coordinate'][iatom] + distance_ab_y *= distance_ab_y + distance_ab_z = coordinates_XYZ[files_xyz[ifile]]['z-coordinate'][jatom]\ + - coordinates_XYZ[files_xyz[ifile]]['z-coordinate'][iatom] + distance_ab_z *= distance_ab_z + # Distance between atoms + temporal_R_Matrix[jatom][iatom] =\ + np.sqrt(distance_ab_x+distance_ab_y+distance_ab_z) + # Symmetric term + temporal_R_Matrix[iatom][jatom] = temporal_R_Matrix[jatom][iatom] + jatom += 1 + # Dateframe with distances + df = pd.DataFrame(temporal_R_Matrix, columns=[label]) + # First column of df + df.insert(loc=0, column='atom', value=np.transpose(label)) + # Save df in dictonary + R_Matrix[files_xyz[ifile]] = df + print(R_Matrix[files_xyz[ifile]]) + return R_Matrix +#---------------------------------------------------------# +# -End: Build Distance Matrix to each .xyz # +#---------------------------------------------------------# diff --git a/mg/transfer_O-H-O.dat b/mg/transfer_O-H-O.dat new file mode 100644 index 0000000..c636952 --- /dev/null +++ b/mg/transfer_O-H-O.dat @@ -0,0 +1,91 @@ +# q1 [Angstrom] q2 [Angstrom] + -0.1518868065 2.4457501866 + 0.1247715443 2.4232311071 + 0.3050077103 2.6215260798 + -0.2175119543 2.5022997779 + -0.2175104798 2.5022973031 + -0.4120036226 2.7944336476 + -0.4126540005 2.7955961423 + 0.2195002983 2.5031471719 + -0.1821232582 2.4680321272 + -0.1821305712 2.4680383792 + -0.2492919759 2.5355144948 + -0.2493251530 2.5355508064 + 0.1827918901 2.4648009770 + 0.2151355758 2.5074758123 + -0.1785684421 2.4674676144 + -0.1785385289 2.4674413125 + -0.4594653430 2.8708599259 + 0.4594663386 2.8708583276 + 0.4189277285 2.8016468503 + 0.4189327938 2.8016546425 + -0.2281887889 2.5114362276 + -0.4173532189 2.8016985836 + -0.4151060118 2.7976970004 + 0.2335741904 2.5168793607 + -0.2335786324 2.5168844524 + 0.2253893337 2.5080624841 + -0.4161353273 2.7991384783 + -0.4163270959 2.7994785480 + 0.6038198013 3.1482322168 + 0.3407237137 2.6718626760 + 0.2505609077 2.5341713615 + 0.2808346244 2.5724645419 + 0.0300087811 2.3914608452 + -0.2076964668 2.4875808541 + -0.1689387783 2.4626354130 + -0.2125724786 2.4947061010 + -0.3945859538 2.7578612132 + 0.1544001276 2.4485132358 + -0.3425800127 2.6652114343 + 0.3947186502 2.7580821112 + -0.1546135016 2.4486707862 + -0.4209888655 2.7994445888 + -0.4267387548 2.8107314300 + 0.4248133339 2.8099887423 + 0.4247515678 2.8098788725 + 0.4247612596 2.8098949807 + 0.4248058432 2.8099750067 + -0.2678673544 2.5571292299 + -0.4213641958 2.8037997342 + -0.4249185956 2.8101634176 + 0.2865836090 2.5782291272 + -0.5223452870 2.9873260319 + 0.3796712172 2.7316694654 + 0.2726341932 2.5618507083 + -0.2719969044 2.5619813494 + 0.3128747164 2.6217766516 + -0.3553269653 2.6958739267 + -0.3565528061 2.6979226764 + 0.2641928591 2.5496520227 + -0.2438101140 2.5279019642 + -0.5587298590 3.0590796268 + -0.3628562002 2.7057252788 + 0.3460543868 2.6802460464 + 0.6207331882 3.1769514886 + -0.2542290849 2.5382419515 + -0.5379700293 3.0208614061 + 0.4192041451 2.7984816488 + 0.3200008050 2.6399118857 + 0.5726924222 3.0970695649 + -0.2436436656 2.5270983199 + -0.2393926974 2.5241191873 + -0.3062038606 2.6124924714 + 0.3498730058 2.6896082854 + 0.3502001724 2.6901409604 + 0.2342309137 2.5169591386 + 0.2336983064 2.5164257637 + 0.3056382451 2.6117519302 + -0.3494073858 2.6889829919 + 0.3493061560 2.6888034087 + -0.4432941335 2.8364702108 + 0.2261069620 2.5067899043 + -0.4432785542 2.8364429683 + 0.2261358550 2.5068183565 + 0.2691216448 2.5551149934 + 0.3175988953 2.6283349858 + 0.4878677459 2.9289213204 + 0.2869267459 2.5953134410 + -0.2773741880 2.5661394892 + -0.2779403392 2.5668859840 + -0.2153261263 2.5028140119 diff --git a/mg/w3s1-Mg.xyz b/mg/w3s1-Mg.xyz new file mode 100644 index 0000000..a4df78e --- /dev/null +++ b/mg/w3s1-Mg.xyz @@ -0,0 +1,12 @@ + 10 + DOI10.1007/s00894-012-1716-5 +H -2.223140000 -1.448303000 -0.481754000 +O -1.380598000 -1.438901000 0.000067000 +H -1.355864000 -2.281225000 0.481727000 +H -1.303144000 2.311553000 0.477582000 +O -0.557282000 1.914239000 0.000149000 +H -0.141917000 2.650496000 -0.476825000 +H 2.655137000 -0.026632000 0.475359000 +O 1.937378000 -0.474971000 0.000045000 +H 2.366435000 -1.204454000 -0.475227000 +Mg 0.000543000 -0.000364000 -0.000245000 diff --git a/mg/w3s3-Mg.xyz b/mg/w3s3-Mg.xyz new file mode 100644 index 0000000..4a0282f --- /dev/null +++ b/mg/w3s3-Mg.xyz @@ -0,0 +1,12 @@ + 10 + DOI10.1007/s00894-012-1716-5 +H -1.792425000 0.220517000 0.000117000 +O -0.895203000 0.805332000 0.000212000 +H -1.176020000 1.732311000 0.001211000 +H -3.457333000 -0.710167000 -0.773138000 +O -2.885139000 -0.613717000 -0.000052000 +H -3.456676000 -0.711323000 0.773375000 +H 3.363315000 -0.583502000 -0.771842000 +O 2.799018000 -0.407243000 0.000219000 +H 3.362550000 -0.583986000 0.772728000 +Mg 0.917265000 0.196765000 -0.000457000 diff --git a/mg/w3s5-Mg.xyz b/mg/w3s5-Mg.xyz new file mode 100644 index 0000000..500112c --- /dev/null +++ b/mg/w3s5-Mg.xyz @@ -0,0 +1,12 @@ + 10 + DOI10.1007/s00894-012-1716-5 +H 3.645766000 -0.701880000 -0.839496000 +O 3.080205000 -0.600762000 -0.063095000 +H 3.643114000 -0.712044000 0.713390000 +H 0.269458000 0.517215000 0.113330000 +O -1.206945000 0.000698000 0.518496000 +H -1.120484000 -0.213646000 1.456571000 +H 1.313856000 1.768304000 0.143442000 +O 1.161680000 0.871970000 -0.186057000 +H 2.033012000 0.228918000 -0.093891000 +Mg -2.838686000 -0.255176000 -0.304009000 diff --git a/mg/w3s6-Mg.xyz b/mg/w3s6-Mg.xyz new file mode 100644 index 0000000..5806c31 --- /dev/null +++ b/mg/w3s6-Mg.xyz @@ -0,0 +1,12 @@ + 10 + DOI10.1007/s00894-012-1716-5 +H -0.843048000 -0.440047000 0.000001000 +O 0.000001000 0.158013000 0.000000000 +H 0.843051000 -0.440046000 -0.000006000 +H 2.478504000 -1.613398000 -0.768241000 +O 2.133847000 -1.140621000 -0.000006000 +H 2.478175000 -1.613356000 0.768404000 +H 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-0.345510000 +H 0.798287000 -2.149805000 1.337485000 +O 0.653411000 -1.504453000 0.635924000 +H -0.267309000 -1.684946000 0.217609000 +H -4.245065000 -0.181727000 0.736118000 +O -3.647242000 -0.000443000 -0.000962000 +H -4.244660000 0.180644000 -0.738419000 +H 4.297280000 0.769294000 0.011655000 +O 3.709892000 -0.000593000 -0.001105000 +H 4.296356000 -0.771172000 -0.014650000 +Mg 1.704055000 0.000390000 0.000321000 diff --git a/mg/w6s14-Mg.xyz b/mg/w6s14-Mg.xyz new file mode 100644 index 0000000..2c8af97 --- /dev/null +++ b/mg/w6s14-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 1.530481000 3.804937000 -0.728341000 +O 1.635058000 3.193274000 0.009370000 +H 1.878527000 3.744239000 0.762093000 +H -4.406207000 1.065738000 -1.115765000 +O -4.018354000 0.220555000 -0.865679000 +H -4.718847000 -0.423117000 -1.015914000 +H -2.421077000 0.029228000 1.720913000 +O -2.043001000 -0.085220000 0.839473000 +H -2.812497000 0.040857000 0.218885000 +H -0.447325000 0.963929000 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-0.451771000 +H -3.935771000 -2.080195000 -1.266776000 +H -3.733570000 2.679649000 -0.071539000 +O -3.206379000 2.210389000 0.583474000 +H -3.559710000 2.481259000 1.437607000 +H 4.505743000 1.054731000 -0.385238000 +O 3.557874000 1.245466000 -0.361918000 +H 3.480608000 2.190238000 -0.557877000 +Mg 2.005180000 -0.029646000 -0.162131000 diff --git a/mg/w6s2-Mg.xyz b/mg/w6s2-Mg.xyz new file mode 100644 index 0000000..2aab706 --- /dev/null +++ b/mg/w6s2-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 0.803780000 -1.607602000 -2.208766000 +O 1.301131000 -1.006916000 -1.639566000 +H 2.200041000 -1.001328000 -1.990868000 +H -1.831164000 1.268187000 -0.035142000 +O -0.868173000 1.442745000 -0.025295000 +H -0.748937000 2.398854000 -0.033516000 +H -1.995037000 -1.003994000 0.056463000 +O -1.069622000 -1.320660000 0.088719000 +H -1.101363000 -2.270874000 0.247000000 +H 2.387284000 1.858716000 -0.937434000 +O 2.086854000 1.383012000 -0.152595000 +H 2.568181000 1.780400000 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-1.396716000 1.022495000 1.017024000 +H -2.346166000 0.849733000 0.845376000 +H -1.339299000 -1.705537000 -1.695949000 +O -1.396501000 -1.022451000 -1.017093000 +H -2.345989000 -0.849911000 -0.845458000 +Mg 0.000000000 0.000125000 0.000021000 diff --git a/mg/w6s4-Mg.xyz b/mg/w6s4-Mg.xyz new file mode 100644 index 0000000..d0060d8 --- /dev/null +++ b/mg/w6s4-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -2.015498000 0.335864000 1.840426000 +O -1.742954000 0.114493000 0.942340000 +H -2.457593000 -0.496693000 0.571865000 +H 1.948484000 1.177088000 1.892109000 +O 1.666486000 0.631493000 1.148295000 +H 2.391550000 0.002606000 0.947712000 +H -4.338218000 -1.099505000 -0.433003000 +O -3.482642000 -1.432685000 -0.109784000 +H -3.649066000 -2.336472000 0.210719000 +H 1.633994000 -1.204728000 -0.984772000 +O 0.748767000 -0.830789000 -1.177807000 +H 0.414049000 -1.258893000 -1.974627000 +H 3.369247000 -2.169214000 0.434912000 +O 3.183572000 -1.325156000 -0.018746000 +H 4.011091000 -1.099537000 -0.484807000 +H 0.231563000 2.866336000 -1.372789000 +O -0.377987000 2.326793000 -0.852125000 +H -1.213491000 2.812071000 -0.841766000 +Mg -0.024004000 0.549824000 0.061387000 diff --git a/mg/w6s5-Mg.xyz b/mg/w6s5-Mg.xyz new file mode 100644 index 0000000..2b63c2e --- /dev/null +++ b/mg/w6s5-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 3.397022000 -2.365666000 0.475467000 +O 2.814285000 -2.041403000 -0.220257000 +H 3.252213000 -2.282311000 -1.044179000 +H 1.829170000 -0.822763000 -0.055061000 +O 1.133982000 -0.108821000 0.054797000 +H 1.579467000 0.754271000 0.063367000 +H -0.976854000 -1.574263000 2.346430000 +O -1.504813000 -1.299962000 1.584458000 +H -2.404860000 -1.597286000 1.773335000 +H 1.726296000 3.238871000 0.823724000 +O 1.380899000 2.760469000 0.057907000 +H 1.747493000 3.241821000 -0.696096000 +H -0.319426000 2.366971000 0.028834000 +O -1.125223000 1.798641000 0.014319000 +H -1.893022000 2.370379000 0.130113000 +H -2.229536000 -0.467326000 -2.281750000 +O -1.898575000 -0.957760000 -1.517092000 +H -2.100878000 -1.885343000 -1.698616000 +Mg -0.834294000 -0.182223000 0.028448000 diff --git a/mg/w6s6-Mg.xyz b/mg/w6s6-Mg.xyz new file mode 100644 index 0000000..6b81685 --- /dev/null +++ b/mg/w6s6-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 3.288285000 -2.096476000 -0.375105000 +O 2.430324000 -2.343966000 -0.012351000 +H 2.549966000 -3.240148000 0.322251000 +H -1.554336000 -0.180187000 2.611671000 +O -1.391282000 -0.696557000 1.811162000 +H -1.420554000 -1.621797000 2.088232000 +H -0.612850000 2.653467000 0.203121000 +O -0.116186000 1.832324000 0.110340000 +H 0.856742000 2.097385000 0.075380000 +H 1.082253000 -1.807565000 -0.567802000 +O 0.199011000 -1.430499000 -0.874976000 +H -0.003810000 -1.867948000 -1.710037000 +H 2.878220000 2.715933000 0.779652000 +O 2.373835000 2.423217000 0.011876000 +H 2.779504000 2.871403000 -0.739229000 +H -3.488327000 -0.182499000 -0.766654000 +O -2.638217000 0.202044000 -1.018973000 +H -2.812649000 0.706124000 -1.825005000 +Mg -0.866861000 0.004984000 -0.026091000 diff --git a/mg/w6s7-Mg.xyz b/mg/w6s7-Mg.xyz new file mode 100644 index 0000000..57965f2 --- /dev/null +++ b/mg/w6s7-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -4.762242000 1.050290000 0.414868000 +O -4.196209000 0.643046000 -0.249514000 +H -4.756181000 0.557378000 -1.028458000 +H 3.804220000 -0.920025000 0.557747000 +O 2.959358000 -1.113400000 0.129163000 +H 3.019658000 -2.036784000 -0.152292000 +H -0.014701000 -0.965321000 -2.203308000 +O 0.000990000 -0.770222000 -1.259362000 +H -0.909289000 -0.920969000 -0.893381000 +H -0.927518000 -0.183836000 1.255668000 +O -0.023982000 0.170295000 1.463246000 +H 0.014771000 0.370174000 2.405566000 +H -2.501155000 -1.739760000 0.568862000 +O -2.138826000 -0.890358000 0.284927000 +H -2.940719000 -0.329455000 0.089002000 +H 2.867831000 2.132795000 -0.896823000 +O 2.100743000 1.897755000 -0.357253000 +H 1.719850000 2.739398000 -0.071036000 +Mg 1.314073000 0.062433000 -0.011339000 diff --git a/mg/w6s8-Mg.xyz b/mg/w6s8-Mg.xyz new file mode 100644 index 0000000..55afa33 --- /dev/null +++ b/mg/w6s8-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H -3.088526000 3.148801000 -0.765388000 +O -2.670859000 2.739154000 0.000856000 +H -3.088636000 3.148337000 0.767285000 +H 1.983969000 2.051678000 -0.002376000 +O 1.932045000 1.087632000 -0.001228000 +H 2.892961000 0.745101000 -0.000640000 +H -2.239024000 -0.281528000 -0.001982000 +O -1.585012000 0.435925000 -0.000772000 +H -2.072465000 1.321232000 -0.000096000 +H -0.706051000 -2.364529000 0.000877000 +O 0.205511000 -1.978307000 0.001068000 +H 0.845694000 -2.700090000 0.001838000 +H 4.843992000 0.126260000 0.767543000 +O 4.259337000 0.107638000 0.000396000 +H 4.844279000 0.124246000 -0.766579000 +H -2.874024000 -2.751944000 0.759922000 +O -2.421767000 -2.361786000 -0.000613000 +H -2.872689000 -2.753875000 -0.760949000 +Mg 0.314707000 -0.004645000 0.000240000 diff --git a/mg/w6s9-Mg.xyz b/mg/w6s9-Mg.xyz new file mode 100644 index 0000000..71942fe --- /dev/null +++ b/mg/w6s9-Mg.xyz @@ -0,0 +1,21 @@ + 19 + DOI10.1007/s00894-012-1716-5 +H 4.279188000 -0.194491000 0.803159000 +O 3.692288000 -0.214305000 0.023667000 +H 4.294546000 -0.181379000 -0.743748000 +H -2.608326000 -0.537599000 -0.000580000 +O -1.730561000 -0.028338000 -0.014269000 +H -1.916479000 0.926184000 -0.012851000 +H -1.226545000 3.325701000 -0.772851000 +O -1.015893000 2.765961000 -0.002315000 +H -1.236108000 3.318968000 0.770780000 +H 1.697156000 -2.793048000 -0.025462000 +O 1.613446000 -1.831543000 -0.016005000 +H 2.521632000 -1.427623000 -0.001197000 +H 0.641190000 2.017115000 0.004592000 +O 1.131501000 1.168553000 0.001502000 +H 2.089374000 1.305943000 0.012858000 +H -4.422019000 -1.523833000 0.809474000 +O -3.863359000 -1.400710000 0.022376000 +H -4.436934000 -1.541358000 -0.750783000 +Mg 0.141995000 -0.530961000 -0.017754000 diff --git a/mp2_xyz/ada_H-O-H.dat b/mp2_xyz/ada_H-O-H.dat new file mode 100644 index 0000000..843a61c --- /dev/null +++ b/mp2_xyz/ada_H-O-H.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=1663) +0.000000 0 +5.135135 3 +10.270270 57 +15.405405 156 +20.540541 56 +25.675676 22 +30.810811 91 +35.945946 4 +41.081081 9 +46.216216 12 +51.351351 24 +56.486486 8 +61.621622 16 +66.756757 6 +71.891892 8 +77.027027 6 +82.162162 10 +87.297297 14 +92.432432 6 +97.567568 15 +102.702703 28 +107.837838 233 +112.972973 225 +118.108108 235 +123.243243 218 +128.378378 98 +133.513514 25 +138.648649 12 +143.783784 4 +148.918919 9 +154.054054 9 +159.189189 9 +164.324324 9 +169.459459 12 +174.594595 8 +179.729730 6 +184.864865 0 +190.000000 0 diff --git a/mp2_xyz/ada_O-Hg-O.dat b/mp2_xyz/ada_O-Hg-O.dat new file mode 100644 index 0000000..d7d2bd1 --- /dev/null +++ b/mp2_xyz/ada_O-Hg-O.dat @@ -0,0 +1,39 @@ +# angle [Degrees] occurrence (total=150) +0.000000 0 +5.135135 0 +10.270270 0 +15.405405 0 +20.540541 0 +25.675676 0 +30.810811 0 +35.945946 0 +41.081081 0 +46.216216 1 +51.351351 0 +56.486486 0 +61.621622 0 +66.756757 0 +71.891892 0 +77.027027 5 +82.162162 13 +87.297297 10 +92.432432 31 +97.567568 17 +102.702703 5 +107.837838 11 +112.972973 5 +118.108108 5 +123.243243 1 +128.378378 1 +133.513514 0 +138.648649 3 +143.783784 0 +148.918919 0 +154.054054 1 +159.189189 1 +164.324324 0 +169.459459 7 +174.594595 7 +179.729730 19 +184.864865 7 +190.000000 0 diff --git a/mp2_xyz/dada_Hg-O-H-H.dat b/mp2_xyz/dada_Hg-O-H-H.dat new file mode 100644 index 0000000..4922a9a --- /dev/null +++ b/mp2_xyz/dada_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# angle [Degrees] occurrence (total=365) +0.000000 0 +5.070423 2 +10.140845 6 +15.211268 1 +20.281690 1 +25.352113 7 +30.422535 1 +35.492958 4 +40.563380 2 +45.633803 2 +50.704225 0 +55.774648 3 +60.845070 5 +65.915493 15 +70.985915 10 +76.056338 16 +81.126761 13 +86.197183 12 +91.267606 16 +96.338028 9 +101.408451 10 +106.478873 9 +111.549296 18 +116.619718 17 +121.690141 9 +126.760563 12 +131.830986 11 +136.901408 11 +141.971831 15 +147.042254 11 +152.112676 25 +157.183099 18 +162.253521 20 +167.323944 15 +172.394366 16 +177.464789 15 +182.535211 8 +187.605634 0 +192.676056 0 +197.746479 0 +202.816901 0 +207.887324 0 +212.957746 0 +218.028169 0 +223.098592 0 +228.169014 0 +233.239437 0 +238.309859 0 +243.380282 0 +248.450704 0 +253.521127 0 +258.591549 0 +263.661972 0 +268.732394 0 +273.802817 0 +278.873239 0 +283.943662 0 +289.014085 0 +294.084507 0 +299.154930 0 +304.225352 0 +309.295775 0 +314.366197 0 +319.436620 0 +324.507042 0 +329.577465 0 +334.647887 0 +339.718310 0 +344.788732 0 +349.859155 0 +354.929577 0 +360.000000 0 diff --git a/mp2_xyz/rda_H-O.dat b/mp2_xyz/rda_H-O.dat new file mode 100644 index 0000000..d27140a --- /dev/null +++ b/mp2_xyz/rda_H-O.dat @@ -0,0 +1,58 @@ +# distance [Angstrom] occurrence (total=862) +0.600000 0 +0.651786 0 +0.703571 0 +0.755357 0 +0.807143 0 +0.858929 0 +0.910714 0 +0.962500 317 +1.014286 28 +1.066071 43 +1.117857 17 +1.169643 2 +1.221429 3 +1.273214 1 +1.325000 7 +1.376786 16 +1.428571 11 +1.480357 15 +1.532143 11 +1.583929 4 +1.635714 6 +1.687500 4 +1.739286 1 +1.791071 1 +1.842857 2 +1.894643 4 +1.946429 2 +1.998214 1 +2.050000 0 +2.101786 0 +2.153571 3 +2.205357 2 +2.257143 1 +2.308929 2 +2.360714 2 +2.412500 0 +2.464286 0 +2.516071 0 +2.567857 3 +2.619643 1 +2.671429 1 +2.723214 0 +2.775000 0 +2.826786 0 +2.878571 7 +2.930357 6 +2.982143 3 +3.033929 37 +3.085714 40 +3.137500 58 +3.189286 70 +3.241071 33 +3.292857 17 +3.344643 16 +3.396429 32 +3.448214 15 +3.500000 17 diff --git a/mp2_xyz/rda_HgO.png b/mp2_xyz/rda_HgO.png new file mode 100644 index 0000000..9e9b568 Binary files /dev/null and b/mp2_xyz/rda_HgO.png differ diff --git a/mp2_xyz/rda_O-H.dat b/mp2_xyz/rda_O-H.dat new file mode 100644 index 0000000..d27140a --- /dev/null +++ b/mp2_xyz/rda_O-H.dat @@ -0,0 +1,58 @@ +# distance [Angstrom] occurrence (total=862) +0.600000 0 +0.651786 0 +0.703571 0 +0.755357 0 +0.807143 0 +0.858929 0 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+2.950000 0 +2.955000 0 +2.960000 0 +2.965000 0 +2.970000 0 +2.975000 0 +2.980000 0 +2.985000 0 +2.990000 0 +2.995000 0 diff --git a/mp2_xyz/rda_w4_Hg-O.dat b/mp2_xyz/rda_w4_Hg-O.dat new file mode 100644 index 0000000..69d2f05 --- /dev/null +++ b/mp2_xyz/rda_w4_Hg-O.dat @@ -0,0 +1,301 @@ +# distance [Angstrom] occurrence (total=10) +1.500000 0 +1.505000 0 +1.510000 0 +1.515000 0 +1.520000 0 +1.525000 0 +1.530000 0 +1.535000 0 +1.540000 0 +1.545000 0 +1.550000 0 +1.555000 0 +1.560000 0 +1.565000 0 +1.570000 0 +1.575000 0 +1.580000 0 +1.585000 0 +1.590000 0 +1.595000 0 +1.600000 0 +1.605000 0 +1.610000 0 +1.615000 0 +1.620000 0 +1.625000 0 +1.630000 0 +1.635000 0 +1.640000 0 +1.645000 0 +1.650000 0 +1.655000 0 +1.660000 0 +1.665000 0 +1.670000 0 +1.675000 0 +1.680000 0 +1.685000 0 +1.690000 0 +1.695000 0 +1.700000 0 +1.705000 0 +1.710000 0 +1.715000 0 +1.720000 0 +1.725000 0 +1.730000 0 +1.735000 0 +1.740000 0 +1.745000 0 +1.750000 0 +1.755000 0 +1.760000 0 +1.765000 0 +1.770000 0 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b/mp2_xyz/rda_w5_Hg-O.dat new file mode 100644 index 0000000..02e23cd --- /dev/null +++ b/mp2_xyz/rda_w5_Hg-O.dat @@ -0,0 +1,301 @@ +# distance [Angstrom] occurrence (total=30) +1.500000 0 +1.505000 0 +1.510000 0 +1.515000 0 +1.520000 0 +1.525000 0 +1.530000 0 +1.535000 0 +1.540000 0 +1.545000 0 +1.550000 0 +1.555000 0 +1.560000 0 +1.565000 0 +1.570000 0 +1.575000 0 +1.580000 0 +1.585000 0 +1.590000 0 +1.595000 0 +1.600000 0 +1.605000 0 +1.610000 0 +1.615000 0 +1.620000 0 +1.625000 0 +1.630000 0 +1.635000 0 +1.640000 0 +1.645000 0 +1.650000 0 +1.655000 0 +1.660000 0 +1.665000 0 +1.670000 0 +1.675000 0 +1.680000 0 +1.685000 0 +1.690000 0 +1.695000 0 +1.700000 0 +1.705000 0 +1.710000 0 +1.715000 0 +1.720000 0 +1.725000 0 +1.730000 0 +1.735000 0 +1.740000 0 +1.745000 0 +1.750000 0 +1.755000 0 +1.760000 0 +1.765000 0 +1.770000 0 +1.775000 0 +1.780000 0 +1.785000 0 +1.790000 0 +1.795000 0 +1.800000 0 +1.805000 0 +1.810000 0 +1.815000 0 +1.820000 0 +1.825000 0 +1.830000 0 +1.835000 0 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(total=71) +1.500000 0 +1.505000 0 +1.510000 0 +1.515000 0 +1.520000 0 +1.525000 0 +1.530000 0 +1.535000 0 +1.540000 0 +1.545000 0 +1.550000 0 +1.555000 0 +1.560000 0 +1.565000 0 +1.570000 0 +1.575000 0 +1.580000 0 +1.585000 0 +1.590000 0 +1.595000 0 +1.600000 0 +1.605000 0 +1.610000 0 +1.615000 0 +1.620000 0 +1.625000 0 +1.630000 0 +1.635000 0 +1.640000 0 +1.645000 0 +1.650000 0 +1.655000 0 +1.660000 0 +1.665000 0 +1.670000 0 +1.675000 0 +1.680000 0 +1.685000 0 +1.690000 0 +1.695000 0 +1.700000 0 +1.705000 0 +1.710000 0 +1.715000 0 +1.720000 0 +1.725000 0 +1.730000 0 +1.735000 0 +1.740000 0 +1.745000 0 +1.750000 0 +1.755000 0 +1.760000 0 +1.765000 0 +1.770000 0 +1.775000 0 +1.780000 0 +1.785000 0 +1.790000 0 +1.795000 0 +1.800000 0 +1.805000 0 +1.810000 0 +1.815000 0 +1.820000 0 +1.825000 0 +1.830000 0 +1.835000 0 +1.840000 0 +1.845000 0 +1.850000 0 +1.855000 0 +1.860000 0 +1.865000 0 +1.870000 0 +1.875000 0 +1.880000 0 +1.885000 0 +1.890000 0 +1.895000 0 +1.900000 0 +1.905000 0 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2.4711024595 + -0.2157016926 2.4967409877 + -0.4799510837 2.9020564708 + -0.1674563441 2.4519871210 + -0.2279553780 2.5075870429 + -0.2270962474 2.5066429789 + -0.3688672320 2.7089998050 + -0.1441082878 2.4356134969 + -0.2007460951 2.4799775156 + -0.1997121966 2.4789769744 + -0.2007737060 2.4800075576 + -0.1997130614 2.4789808983 + 0.3131914995 2.6237383682 + -0.1502920083 2.4389821782 + 0.2265945615 2.5111449668 + -0.1724586766 2.4576643657 + -0.1551531225 2.4453550389 + -0.2545643523 2.5462254997 + 0.1832441205 2.4685670887 + 0.6546494339 3.2386261371 + 0.2368929493 2.5263734099 + 0.1506240301 2.4416117423 + -0.2600122608 2.5524543929 + 0.2186277618 2.5002916081 + 0.2172423546 2.4996377326 + -0.1437803292 2.4384233365 + -0.5874892958 3.1084014128 + 0.2888901286 2.5920544417 + 0.2042391122 2.4831912057 + -0.1368985448 2.4322319620 + 0.1993828921 2.4784807633 + -0.1544068493 2.4444265211 + -0.2964622784 2.6023053039 + -0.5652357205 3.0657570966 + 0.1859391712 2.4699053575 + 0.1692515825 2.4561593995 + 0.7738138595 3.4842086632 + 0.2855813323 2.5891925364 + 0.5609573338 3.0579407154 + -0.1938411628 2.4779457056 + 0.6478259265 3.2384211387 + 0.2310246255 2.5151524346 + -0.2271658235 2.5105051226 + 0.2120962385 2.4927109497 + -0.3182827813 2.6359285329 + -0.6713411525 3.2844901366 + 0.5621895351 3.0620337371 + -0.3777441251 2.7275868943 + 0.4378530074 2.8310658641 + -0.1328024565 2.4259457970 + 0.7574310096 3.4539403764 + -0.4340016471 2.8189710054 + -0.4187077171 2.7981554387 + -0.4177532583 2.7965123116 + -0.4350716244 2.8208566446 + 0.1340519957 2.4267089810 + 0.7588041060 3.4566394473 + -0.4741882634 2.8957645007 + 0.1508781913 2.4415762736 + -0.4743436361 2.8960633125 + 0.1510259009 2.4416718348 diff --git a/w1s1.xyz b/mp2_xyz/w1s1.xyz similarity index 100% rename from w1s1.xyz rename to mp2_xyz/w1s1.xyz diff --git a/w2s1.xyz b/mp2_xyz/w2s1.xyz similarity index 100% rename from w2s1.xyz rename to mp2_xyz/w2s1.xyz diff --git a/mp2_xyz/w3s1.xyz b/mp2_xyz/w3s1.xyz new file mode 100644 index 0000000..a109605 --- /dev/null +++ b/mp2_xyz/w3s1.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg -0.7408153572 -0.1665417846 0.0005265718 +O 1.3059831023 2.6439937137 -0.0000355661 +H 1.5670431221 3.1585725126 0.7743967382 +H 1.5669403673 3.1586971739 -0.7744191007 +O 1.1843550066 0.1841042029 -0.0000689965 +H 2.3253303693 -0.8261480309 -0.0001765674 +H 1.2775190974 1.2507307088 -0.0001440881 +O 3.0581723715 -1.5476725211 -0.0000146775 +H 3.6140009812 -1.5481658971 -0.7999421727 +H 3.6139709396 -1.5478420782 0.7999358591 diff --git a/mp2_xyz/w3s2.xyz b/mp2_xyz/w3s2.xyz new file mode 100644 index 0000000..3bf66c7 --- /dev/null +++ b/mp2_xyz/w3s2.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s2.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg 0.0906070664 -0.1593004296 0.0028947029 +O -1.8064320621 -0.9598233520 0.0783236686 +H -2.0107607837 -1.9048801539 -0.0244121388 +H -2.5682244851 -0.4358993707 -0.2206685738 +O 2.1211150192 0.1165310457 -0.0813481207 +H 2.7488020617 -0.6267086364 -0.0723630725 +H 2.5549982071 0.8918623584 0.3136584710 +O -0.9710607193 1.9141381730 -0.0141111776 +H -0.9906190437 2.5370183945 -0.7552992187 +H -1.2309482606 2.4280999710 0.7644014597 diff --git a/mp2_xyz/w3s3.xyz b/mp2_xyz/w3s3.xyz new file mode 100644 index 0000000..e096c6a --- /dev/null +++ b/mp2_xyz/w3s3.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s3.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg 0.3825568519 -0.0440846969 -0.0003116735 +O 2.2864606155 0.6394884897 -0.0001927212 +H 2.8506812864 0.5827392720 -0.7901824108 +H 2.8501877184 0.5834763478 0.7902000392 +O -1.4803385792 -0.5921676287 -0.0001886206 +H -2.7896808874 0.0863637932 0.0001643821 +H -1.5394368776 -1.5612749889 -0.0004879542 +O -3.6857662328 0.6150799030 0.0001183695 +H -4.2265120964 0.4814649772 -0.7979119993 +H -4.2269647989 0.4809505317 0.7977545889 diff --git a/mp2_xyz/w4s1.xyz b/mp2_xyz/w4s1.xyz new file mode 100644 index 0000000..281991e --- /dev/null +++ b/mp2_xyz/w4s1.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq geom=check'--- +H 1.4651912220 -0.1686880478 -2.4701333318 +O 1.5517215415 -0.1605370221 -1.5058544324 +H 2.3828823390 -0.6093816320 -1.2943790194 +H -2.6998881727 -0.9517935121 0.5095647241 +O -2.2295229791 -0.3657306141 -0.1020915861 +H -2.7554882187 -0.3170634400 -0.9145151090 +H 1.2697899505 -1.8509410768 1.8284478325 +O 1.2517336128 -0.9337106569 1.5206163015 +H 1.6068501501 -0.3969215118 2.2432613327 +H -0.3932700779 2.6685937597 0.9810525873 +O 0.2441515061 2.0884093267 0.5424153604 +H 0.9000058774 2.6695232066 0.1335246960 +Hg -0.1040092815 -0.0758847002 -0.0582188607 diff --git a/mp2_xyz/w4s2.xyz b/mp2_xyz/w4s2.xyz new file mode 100644 index 0000000..6c0704a --- /dev/null +++ b/mp2_xyz/w4s2.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s2.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +H 3.7391056708 0.0867207449 -0.7946543248 +O 3.2121669812 -0.1123290447 -0.0025667493 +H 3.7402668522 0.0933194570 0.7870577086 +H -1.2730233531 0.9311475198 0.0001367328 +O -0.7362137996 -0.0099558326 -0.0002982238 +H -1.2862552794 -0.9448674412 0.0014369470 +H -2.3363543817 2.4595507852 0.7764908820 +O -1.8588538245 2.1405909550 0.0003020739 +H -2.3375000533 2.4589747852 -0.7754191898 +H -2.3605822696 -2.4625919861 0.7801599879 +O -1.8823177268 -2.1467238831 0.0031720374 +H -2.3623434353 -2.4637966961 -0.7722387208 +Hg 1.1934586190 -0.0299993632 -0.0014391612 diff --git a/mp2_xyz/w4s3.xyz b/mp2_xyz/w4s3.xyz new file mode 100644 index 0000000..f7379fb --- /dev/null +++ b/mp2_xyz/w4s3.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s3.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +H 4.5532482937 1.2804713574 -0.4229196525 +O 4.1192597332 0.6848153133 0.2039291151 +H 4.8013263647 0.2122513909 0.7006218343 +H -0.2966084789 -0.8303010143 1.4970873527 +O -0.3122478771 -0.4751992449 0.5935684186 +H 1.3767925516 -0.4627720041 -0.1787770551 +H -4.4746189057 1.2546447765 -0.0352616159 +O -4.0227562632 0.4815678015 -0.4102057148 +H -4.6900072881 -0.1936991356 -0.6133426538 +H 3.2006972541 0.0592030932 -0.2140066294 +O 2.2262130560 -0.4875384289 -0.6641741525 +H 2.3593645597 -1.3686375917 -1.0351402655 +Hg -2.1395920001 -0.0319473132 0.1723810186 diff --git a/mp2_xyz/w4s4.xyz b/mp2_xyz/w4s4.xyz new file mode 100644 index 0000000..b274652 --- /dev/null +++ b/mp2_xyz/w4s4.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s4.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq geom=(checkpoint,newdefinition)'--- +H 3.4586835151 -2.8972513963 -0.1611796088 +O 3.1733031246 -2.1607027132 0.4010704627 +H 3.9533705871 -1.7549540832 0.8096064990 +H -3.2477136264 -0.1615041955 0.0020696606 +O -2.1123530014 0.1719741159 0.4983298820 +H -2.1715319814 0.8029203981 1.2297182759 +H -4.7449366433 0.2019722540 -0.8769909690 +O -4.2130418545 -0.4971484516 -0.4666385062 +H -4.7851112997 -1.0374277346 0.0998635294 +H 1.8860958934 -0.1199357145 -1.3060171998 +O 1.5621635172 -0.6605524638 -0.5716293733 +H 2.4449229382 -1.4461467738 -0.0715113167 +Hg -0.2689463840 -0.2169555926 -0.0368056362 diff --git a/mp2_xyz/w5s1.xyz b/mp2_xyz/w5s1.xyz new file mode 100644 index 0000000..2fa4cc9 --- /dev/null +++ b/mp2_xyz/w5s1.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +H -3.0911102727 1.7744491343 -0.5517650151 +O -2.9612380747 0.8170456236 -0.5387994859 +H -3.8770986351 0.2579441585 -0.3107458877 +H 3.0614460545 -1.7565751043 -0.5014396369 +O 2.8546006501 -0.8146145836 -0.4308499584 +H 3.7508433584 -0.2115287438 -0.2803076601 +H -5.3988789001 -0.8875687620 -0.8502445367 +O -4.9419652925 -0.4958532506 -0.0958440094 +H -5.6132936454 -0.2520689863 0.5525231103 +H -0.8049116600 0.2168576334 1.6997132497 +O -0.7446516863 0.2112241236 0.7329543579 +H -2.1399298431 0.5778959398 -0.0210404666 +H 5.2585258045 0.9136062927 -0.9191755998 +O 4.7864179578 0.6102158266 -0.1335198722 +H 5.4468739930 0.4586521907 0.5538187763 +Hg 1.0445111916 -0.3139904926 0.2129316348 diff --git a/mp2_xyz/w5s10.xyz b/mp2_xyz/w5s10.xyz new file mode 100644 index 0000000..49d08ae --- /dev/null +++ b/mp2_xyz/w5s10.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s10.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg -0.4632242035 -0.3626567789 -0.4977703549 +O 3.1058594121 0.9503217856 -0.4178494438 +H 3.5783393952 1.3687895827 0.3151826899 +H 3.6927667418 1.0518827987 -1.1796930687 +O -1.4549331878 -0.7486481232 1.6377521924 +H -2.0503037480 -0.1353838406 2.0894335632 +H -0.9995369128 -1.2233341402 2.3457384030 +O 0.6079515881 1.4066907542 -0.5576130911 +H 1.6239639876 1.3271018377 -0.5683755216 +H 0.3217027644 2.1458371805 -1.1128044941 +O 1.5238368965 -1.5147680358 -0.0328133121 +H 1.7144176480 -2.4603440661 -0.0713619847 +H 2.3754066196 -1.0553196660 -0.0716988185 +O -1.7981839585 -1.9327836850 -0.9617425554 +H -2.1749538510 -2.0939053775 -1.8401190583 +H -2.4757981917 -2.1354842260 -0.2987061451 diff --git a/mp2_xyz/w5s2.xyz b/mp2_xyz/w5s2.xyz new file mode 100644 index 0000000..dcdfae8 --- /dev/null +++ b/mp2_xyz/w5s2.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s2.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +H -5.5240509719 -0.8958084257 0.4753818291 +O -4.8546005219 -0.7147063808 -0.1950959423 +H -5.2745912929 -0.8203182045 -1.0575205968 +H 3.3422339358 1.5007599614 -0.1086713692 +O 2.8646118907 0.6886210999 -0.3265595054 +H 3.5443545095 -0.1399168424 -0.5264299724 +H -3.9512758156 0.2365745208 -0.0344547470 +O -3.1610638409 0.9955227273 0.0267383180 +H -3.4591044735 1.8262860839 0.4200205819 +H 4.6115097673 -1.3053663654 -1.7304431805 +O 4.2933227414 -1.1991027914 -0.8250994407 +H 5.0049226616 -1.4848235671 -0.2389143201 +H -2.2855634824 0.7122066916 0.4174130358 +O -0.8110240282 0.3058060040 0.9800265571 +H -0.8207171107 -0.0762286480 1.8701210143 +Hg 1.0235970319 0.4845911363 0.3885597385 diff --git a/mp2_xyz/w5s3.xyz b/mp2_xyz/w5s3.xyz new file mode 100644 index 0000000..52aa066 --- /dev/null +++ b/mp2_xyz/w5s3.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s3.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg 0.3585317057 -2.3836653796 1.2484225121 +O 1.7786302225 -3.4176079703 0.3789803133 +H 2.0435654717 -3.6170243957 -0.8294808553 +H 2.3845076373 -3.8522137700 0.9951221285 +O -1.0850481941 -1.3333436843 2.0354825947 +H -0.8618287075 -0.4036071844 2.4523104364 +H -1.8964486580 -1.8319862620 2.4610464084 +O -3.0114258050 -2.5990934315 2.9301166250 +H -3.1594446890 -2.8117901328 3.8585967945 +H -3.8842686272 -2.4857278364 2.5360896940 +O -0.4778598115 0.8988526018 2.9089157292 +H -0.8593294766 1.6898661893 2.5104978295 +H -0.3172457189 1.1131460266 3.8349321267 +O 2.2336412342 -3.7617803286 -1.9492440388 +H 2.1366544931 -4.6663791791 -2.2826357158 +H 3.0608569233 -3.3903212629 -2.2906935823 diff --git a/mp2_xyz/w5s4.xyz b/mp2_xyz/w5s4.xyz new file mode 100644 index 0000000..e4b8ff1 --- /dev/null +++ b/mp2_xyz/w5s4.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s4.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg -0.2138906233 0.9855450683 1.7722390667 +O 1.6527167764 0.5730543939 1.2525347009 +H 2.2399962267 0.9824381124 0.4254795032 +H 1.9061270535 -0.3238370162 1.5184907096 +O -2.0464234080 1.5482478352 2.2415170257 +H -2.5893636197 2.5640865809 2.0490585924 +H -2.5522673311 0.9296532508 2.7850805272 +O 0.2906770747 -1.3178594567 2.8564184311 +H 0.5558391182 -1.4590834821 3.7743031985 +H -0.0568648840 -2.1740695934 2.5760338291 +O -3.1013709833 3.6448873194 1.7987760607 +H -3.8680789556 3.6511765005 1.2091454550 +H -3.2878325878 4.2389925728 2.5388360085 +O 2.9276835340 1.5743895572 -0.5381131594 +H 3.7461192132 2.0343379791 -0.3122612729 +H 3.0720953962 1.1367573778 -1.3861966763 diff --git a/mp2_xyz/w5s5.xyz b/mp2_xyz/w5s5.xyz new file mode 100644 index 0000000..ca702b0 --- /dev/null +++ b/mp2_xyz/w5s5.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s5.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg -0.9145576447 -2.6439732982 0.6864426514 +O 0.7126828963 -3.6997468258 2.2259813925 +H 1.1082190819 -4.5761441818 2.1507515284 +H 1.0864331072 -3.3247794054 3.0321392812 +O -2.3543123171 -2.6794615708 2.0628710776 +H -2.7032101313 -3.6014593345 2.5594143964 +H -3.0849806335 -2.0567377326 1.9381102104 +O -3.0415698734 -4.7065135457 3.1818642607 +H -3.8220795456 -5.2020299132 2.9019095364 +H -3.0413144891 -4.7029307568 4.1479442620 +O 0.4312929790 -2.5474709309 -0.7793804829 +H 0.0835058932 -2.4670036244 -1.6792732931 +H 1.4008689805 -2.0298789829 -0.6847377993 +O 2.5756858976 -1.4678898801 -0.5121174987 +H 3.3632293442 -1.9836756328 -0.7289855498 +H 2.7340314547 -0.5673153842 -0.8235219734 diff --git a/mp2_xyz/w5s6.xyz b/mp2_xyz/w5s6.xyz new file mode 100644 index 0000000..1339c07 --- /dev/null +++ b/mp2_xyz/w5s6.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s6.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg 1.8181242509 -1.3743992862 -0.7094680060 +O -2.1843738446 -0.4708730917 -1.1284763720 +H -2.5758831377 -0.7400979990 -1.9696307803 +H -2.9211891102 -0.3264347833 -0.3456362001 +O -3.7717068951 -0.0653038739 0.6611175253 +H -4.5477129578 -0.6117357449 0.8316902700 +H -4.0225126831 0.8487022570 0.8417121367 +O 0.1205013383 -4.3620835397 -0.0220636607 +H -0.0583473761 -4.7305587783 0.8498227617 +H -0.0339239812 -5.0867927446 -0.6377005643 +O -0.0423671358 -1.8363798290 -0.6279747716 +H -0.0774491819 -2.8124080823 -0.3943729259 +H -1.3785829571 -1.0325167418 -0.9082951110 +O 3.7664361772 -0.7739384803 -0.8207947400 +H 4.3355667980 -1.0317792499 -1.5628841091 +H 4.3183106961 -0.6894590320 -0.0274944527 diff --git a/mp2_xyz/w5s7.xyz b/mp2_xyz/w5s7.xyz new file mode 100644 index 0000000..acdbfea --- /dev/null +++ b/mp2_xyz/w5s7.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s7.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg 0.9042129517 -0.0087511077 0.3014187633 +O -0.5803516165 1.0547659587 -1.2298920646 +H -1.5349243687 1.0272420395 -1.0824491072 +H -0.4191773918 1.8798010838 -1.7070204555 +O 0.7625097084 -1.4708143190 -1.2703725405 +H 1.4590951910 -2.1050193651 -1.4963931253 +H 0.3801523365 -1.1473296984 -2.1001487822 +O 4.3327179901 1.3060419978 1.6559122229 +H 4.8715309782 0.8530402613 2.3160389823 +H 4.7628218688 2.1529604411 1.4834469699 +O 1.8966289398 1.2095119001 1.6040823047 +H 2.9641871517 1.2442195362 1.6791964443 +H 1.4895830768 1.3942401125 2.4609193102 +O -1.0755418721 -1.0387337850 1.0370876764 +H -1.5626786849 -0.8833226460 1.8567712558 +H -1.3053868224 -1.9379925266 0.7691197733 diff --git a/mp2_xyz/w5s8.xyz b/mp2_xyz/w5s8.xyz new file mode 100644 index 0000000..947ae66 --- /dev/null +++ b/mp2_xyz/w5s8.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s8.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq geom=check'--- +H -0.7952909094 2.7394718451 -0.4840969798 +O -0.0150748124 2.2174873724 -0.2546738184 +H 0.7580861157 2.7501078731 -0.4835350189 +H 3.0052713959 0.0201936662 -0.0692802411 +O 2.2507817093 0.0168683203 -0.6722764349 +H 2.6226808775 0.0219110624 -1.5636765134 +H -0.0053290490 0.7657332876 2.8143585354 +O 0.0000647331 -0.0060743741 2.2343138019 +H 0.0054842514 -0.7805902764 2.8107385660 +H -3.0052763994 -0.0200022059 -0.0692381607 +O -2.2508176290 -0.0133115769 -0.6722450938 +H -2.6227598571 -0.0138116265 -1.5636413335 +H -0.7581317545 -2.7483498700 -0.4992851123 +O 0.0150575151 -2.2169471095 -0.2677150441 +H 0.7952738064 -2.7377176356 -0.4998700044 +Hg 0.0000016694 -0.0003806021 -0.0571474660 diff --git a/mp2_xyz/w5s9.xyz b/mp2_xyz/w5s9.xyz new file mode 100644 index 0000000..371fd2e --- /dev/null +++ b/mp2_xyz/w5s9.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s9.log' was gotten at: ---' #p mp2=full gen pseudo=Read geom=check freq'--- +Hg 0.4540010009 -0.2304908876 0.0519605200 +O -2.9265482426 -2.0404620059 -0.1191733967 +H -3.4406018777 -2.3999470323 0.6139746343 +H -3.4256013528 -2.2248567604 -0.9234997478 +O -1.5081796830 -0.0822278890 0.2543833847 +H -1.8847572112 0.8424815127 0.0939462319 +H -2.1591023721 -0.8955072565 0.0573341543 +O 2.4684088697 -0.6310880679 -0.0659965524 +H 2.8538231530 -1.3901794671 0.4013654512 +H 2.9407760249 -0.5314843336 -0.9083347762 +O 0.7624176773 2.1354944993 -0.0493942993 +H -0.0198760518 2.7033441167 -0.0889881833 +H 1.5157282021 2.7152302096 0.1171269212 +O -2.1872427558 2.3749175600 -0.0639043525 +H -2.6330967019 2.8009414087 0.6806072727 +H -2.6575316792 2.6922453933 -0.8461942621 diff --git a/mp2_xyz/w6s1.xyz b/mp2_xyz/w6s1.xyz new file mode 100644 index 0000000..0f93556 --- /dev/null +++ b/mp2_xyz/w6s1.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s1-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg -0.0000946814 -0.1060793553 0.0038919705 +O 5.8543184421 -0.3932331444 0.3659647562 +H 6.5058200794 -0.7002108949 -0.2738776177 +H 6.3170421562 -0.2832931461 1.2042029079 +O -5.8547330633 -0.3993503671 -0.3502000646 +H -6.5064191559 -0.6885607389 0.2976812574 +H -6.3173962244 -0.3118258748 -1.1911068262 +O -3.9312378685 1.0562435347 0.1134449950 +H -4.1356077611 1.8073937490 0.6851325557 +H -4.7747927280 0.4409716310 -0.0436154740 +O 3.9318346923 1.0505798236 -0.1368042691 +H 4.7750213723 0.4392015770 0.0367990767 +H 4.1366769968 1.7859735460 -0.7284583454 +O 1.7825774235 -0.0756146357 -0.7888808120 +H 3.0709675768 0.5665317895 -0.4236539325 +H 1.8294541383 -0.6851002253 -1.5374588507 +O -1.7827326162 -0.0533012810 0.7955834085 +H -3.0706420748 0.5795213445 0.4131923924 +H -1.8300327041 -0.6426183318 1.5601138720 diff --git a/mp2_xyz/w6s10.xyz b/mp2_xyz/w6s10.xyz new file mode 100644 index 0000000..fdca120 --- /dev/null +++ b/mp2_xyz/w6s10.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s10-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +Hg -0.1044900000 0.2704300000 -0.1252100000 +O 2.9429800000 2.4546700000 0.3059400000 +H 3.2669800000 2.8918000000 1.1017200000 +H 3.5272900000 2.7343600000 -0.4073700000 +O 3.0298500000 -1.8571700000 0.1157600000 +H 3.6111000000 -2.0316700000 -0.6330400000 +H 3.4274700000 -2.3088600000 0.8689600000 +O -1.9742600000 0.3908000000 -0.8185100000 +H -2.8280600000 0.3999900000 -0.1646800000 +H -2.1294300000 0.9562900000 -1.5879500000 +O -0.8773800000 -1.7218600000 1.1824700000 +H -0.9186300000 -1.8046500000 2.1421100000 +H -1.0135700000 -2.6164500000 0.8498300000 +O -3.8888600000 0.3463400000 0.6894700000 +H -4.5490100000 -0.3459300000 0.5608500000 +H -4.3716900000 1.1450100000 0.9353800000 +O 1.7652700000 0.2620100000 0.4995300000 +H 2.3031200000 1.1351800000 0.3885300000 +H 2.3245800000 -0.5866900000 0.3176100000 diff --git a/mp2_xyz/w6s11.xyz b/mp2_xyz/w6s11.xyz new file mode 100644 index 0000000..32691fd --- /dev/null +++ b/mp2_xyz/w6s11.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s11-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +Hg 0.2833450139 -0.0184282020 -0.9504447408 +O 1.0419653111 -0.3815503391 1.3504014762 +H 0.5020885861 -0.9012496494 1.9611196600 +H 1.8798036654 -0.2213329474 1.7994560374 +O -1.3431729653 -1.9849249163 1.8745529895 +H -1.2606015963 -2.9286176294 2.0641871389 +H -2.0359130463 -1.6722578098 2.4703192052 +O -3.1518966108 -1.2671747938 -2.1357509704 +H -3.3547760815 -2.0444324398 -2.6688075391 +H -3.9906303621 -0.8180361487 -1.9830675434 +O 1.7627866771 1.2094535161 -1.5010963186 +H 2.1251977857 1.2697143070 -2.5158559453 +H 1.8004708062 2.0729702160 -1.0669949395 +O -1.1961409233 -1.2938385476 -0.6113337461 +H -2.0518932163 -1.2819198522 -1.1975542220 +H -1.3500809485 -1.5674528166 0.3456212283 +O 2.5990593259 1.2214499665 -3.7822579752 +H 3.5281090007 1.0034499856 -3.9280326982 +H 2.3618925784 1.8888931010 -4.4374860970 diff --git a/mp2_xyz/w6s12.xyz b/mp2_xyz/w6s12.xyz new file mode 100644 index 0000000..1b0bd5e --- /dev/null +++ b/mp2_xyz/w6s12.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s12-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +H -3.6352684305 2.6275930282 -0.8506862178 +O -3.1363487302 2.4319384857 -0.0498138180 +H -3.6434898636 2.7998438500 0.6829692448 +H 2.4837274921 2.1674418978 -0.0454315139 +O 2.2204958394 1.2525728809 -0.2142968885 +H 3.0339234470 0.5774686078 -0.0633655147 +H -2.0101514131 -0.4286931498 0.1521809318 +O -1.6460839872 0.4919125320 0.3234784355 +H -2.3137915931 1.2657877767 0.1322004773 +H -0.2600350952 -2.2162359356 -0.0797726404 +O 0.5393166466 -1.6709289834 -0.0766480628 +H 1.2849326546 -2.2784042305 -0.1347044218 +H 4.5629211602 -0.4119954782 0.8561707916 +O 4.0289366352 -0.3667299770 0.0529130926 +H 4.6421715957 -0.4682915031 -0.6865179455 +H -2.7803453977 -2.4071626212 0.7435448445 +O -2.3438640737 -1.9829522203 -0.0068412918 +H -2.8249205273 -2.2982199445 -0.7827469264 +Hg 0.3013156408 0.7543549843 0.0467694237 diff --git a/mp2_xyz/w6s13.xyz b/mp2_xyz/w6s13.xyz new file mode 100644 index 0000000..e68dd53 --- /dev/null +++ b/mp2_xyz/w6s13.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s13-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +Hg -0.1314503131 -0.1582476257 0.0138332434 +O 3.0566672995 -2.0128615154 -1.3740744023 +H 3.5479380399 -2.7545642539 -1.0016402614 +H 3.5335811706 -1.7440188438 -2.1675583126 +O -0.3706372708 -0.4401291147 2.4549288234 +H 0.2615933312 -0.9056582906 3.0155385446 +H -1.1990238212 -0.4611671225 2.9488981931 +O -3.2326323562 -1.8663763512 -1.5702821078 +H -3.4423543221 -1.8357286015 -2.5111315091 +H -3.9531587693 -2.3470862652 -1.1453364908 +O 0.6102399986 2.0705712626 0.8484260582 +H 0.7198991110 2.9278530655 0.4185322882 +H 0.4901206034 2.2717813290 1.7846552754 +O 1.8654868905 -0.4873825319 0.1562399454 +H 2.4027714875 -1.0929357383 -0.5108881646 +H 2.3534993325 0.3255225745 0.3527484257 +O -2.1242789062 -0.0602444770 -0.3333134636 +H -2.6213794376 -0.8023132720 -0.9019451081 +H -2.4891197184 0.8113353623 -0.5392015869 diff --git a/mp2_xyz/w6s14.xyz b/mp2_xyz/w6s14.xyz new file mode 100644 index 0000000..bbf865a --- /dev/null +++ b/mp2_xyz/w6s14.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s14-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +Hg 0.4338592270 -0.1863853164 -0.2093464008 +O -2.9100031754 -1.1046098124 1.5495627823 +H -3.6500284868 -1.6599106809 1.2698005732 +H -3.0914794149 -0.9015297614 2.4766347434 +O 1.8424479937 1.2116204696 -0.7437950589 +H 1.6169673782 2.2321289046 -0.7484075968 +H 2.7444653600 1.0857722868 -0.4189878629 +O -0.5744319588 -1.7773916205 0.6896195293 +H -1.4696209461 -1.5874431513 1.1146694050 +H -0.0936124794 -2.4222194127 1.2263741789 +O 0.3455107583 -1.1277344535 -2.4027589620 +H -0.2029763765 -1.8640352167 -2.6975117084 +H 0.9607646175 -0.9599672169 -3.1262357038 +O -1.7133373924 0.8082897613 -0.2685614385 +H -2.4444569582 0.4883355981 0.2792913961 +H -2.0662887873 1.5066100746 -0.8311795452 +O 1.2208095990 3.6052566074 -0.8510493478 +H 1.3487092619 4.2288843903 -0.1264647458 +H 1.4276430482 4.0910210788 -1.6587359813 diff --git a/mp2_xyz/w6s15.xyz b/mp2_xyz/w6s15.xyz new file mode 100644 index 0000000..6935ea6 --- /dev/null +++ b/mp2_xyz/w6s15.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s15-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +H -1.0965300000 2.5957000000 -1.0693900000 +O -1.0885000000 1.6470600000 -1.2446100000 +H -1.6193700000 1.5147300000 -2.0391800000 +H 1.6196500000 2.1236600000 1.3937600000 +O 0.7918900000 1.6336100000 1.4667400000 +H 0.3588500000 1.9527600000 2.2675600000 +H 2.0218000000 0.8678300000 -2.0567000000 +O 1.9048400000 0.2575100000 -1.3187900000 +H 2.7370600000 -0.2224700000 -1.2310200000 +H -2.0190900000 -0.8701100000 2.0594600000 +O -1.9064300000 -0.2598100000 1.3208800000 +H -2.7394900000 0.2194300000 1.2371200000 +H 1.6172700000 -1.5182900000 2.0372300000 +O 1.0871500000 -1.6464400000 1.2414700000 +H 1.0915800000 -2.5946900000 1.0640300000 +H -0.3537800000 -1.9476100000 -2.2666200000 +O -0.7888900000 -1.6320000000 -1.4655200000 +H -1.6166500000 -2.1226700000 -1.3967800000 +Hg -0.0015200000 0.0022100000 0.0011500000 diff --git a/mp2_xyz/w6s16.xyz b/mp2_xyz/w6s16.xyz new file mode 100644 index 0000000..4261240 --- /dev/null +++ b/mp2_xyz/w6s16.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s16-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg 0.2641473657 -0.1178510008 -0.1979039169 +O 1.8201687843 1.7410166543 0.3591957518 +H 2.2186086150 1.7337061136 1.2390088689 +H 1.7726561580 2.6734795207 0.1118424833 +O -2.6110298165 2.3734593586 0.0465127926 +H -3.1390153225 2.6583770694 -0.7078079656 +H -2.9771392357 2.8358395009 0.8093346246 +O 1.3953021503 -0.9717005522 1.7938268348 +H 2.1017248248 -1.6293166611 1.7800035424 +H 0.9933006718 -1.0590123168 2.6669280408 +O 2.0974527438 -0.5401916907 -1.1202819686 +H 2.1801825458 -0.9541244158 -1.9926563553 +H 2.6961642192 0.2236575209 -1.0794521314 +O -1.6376589509 0.0830318915 0.3860426376 +H -2.0822814398 0.9918395250 0.2122965637 +H -2.2636495349 -0.7020109545 0.1651221563 +O -3.0547481363 -1.9309878498 -0.0825531579 +H -3.6204837005 -2.0718814695 -0.8497600321 +H -3.4836459415 -2.3914382438 0.6477322311 diff --git a/mp2_xyz/w6s18.xyz b/mp2_xyz/w6s18.xyz new file mode 100644 index 0000000..f53021d --- /dev/null +++ b/mp2_xyz/w6s18.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s18-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +H 3.9141500000 -1.6426800000 0.7589300000 +O 3.2511400000 -1.7027800000 0.0623400000 +H 3.6854800000 -2.1313500000 -0.6840600000 +H 2.1850300000 -0.7324300000 -0.1588200000 +O 1.3628700000 -0.1362300000 -0.3545000000 +H 1.5730900000 0.8410900000 -0.3504700000 +H -2.0349100000 -1.9251700000 2.2447900000 +O -2.0830300000 -1.3370200000 1.4762400000 +H -2.7792500000 -1.6542000000 0.8784700000 +H 2.1369200000 2.9738600000 0.1964300000 +O 1.5523900000 2.4767200000 -0.3903500000 +H 1.6825800000 2.8796900000 -1.2589100000 +H -0.4332100000 2.3597400000 0.2617400000 +O -1.1064100000 1.7027600000 0.4937000000 +H -1.7645300000 2.1596900000 1.0308600000 +H -2.6929100000 -0.1372500000 -1.5890400000 +O -2.2238200000 -0.9054500000 -1.2389700000 +H -2.2281000000 -1.5461400000 -1.9619600000 +Hg -0.4241200000 -0.5965500000 0.4517200000 diff --git a/mp2_xyz/w6s19.xyz b/mp2_xyz/w6s19.xyz new file mode 100644 index 0000000..210998d --- /dev/null +++ b/mp2_xyz/w6s19.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s19-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg 0.2197808924 0.0433229583 -0.0719314608 +O 1.7287756973 -0.6487546183 -1.6304350830 +H 1.6716397511 -0.5443831645 -2.5889530469 +H 2.3054303963 -1.4073614694 -1.4728588983 +O -1.4081544795 1.5231527946 0.0607290614 +H -1.3835667365 2.4076639063 -0.3239509706 +H -2.3370199224 1.1933009648 0.0342710780 +O -3.7055159429 0.1173969187 0.0852832440 +H -4.3644396584 0.1795214154 -0.6186821156 +H -4.2244883553 0.1134344900 0.9005168462 +O 1.2846607936 -1.2826224752 1.4701508232 +H 0.8510276745 -1.9907345870 1.9632272312 +H 1.9910053619 -0.9512436761 2.0391373282 +O -1.4697199503 -1.5084596146 -0.1148616082 +H -2.3884044192 -1.1751972364 -0.0863472458 +H -1.4820555426 -2.3562087644 -0.5749374405 +O 1.8365517476 1.6341012861 0.5093523091 +H 2.6058626980 1.8393982659 -0.0363178614 +H 1.7527799943 2.3628516058 1.1370708099 diff --git a/mp2_xyz/w6s2.xyz b/mp2_xyz/w6s2.xyz new file mode 100644 index 0000000..8d2a4dd --- /dev/null +++ b/mp2_xyz/w6s2.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s2-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +H 6.0328000000 0.6476300000 -0.0444600000 +O 5.2899500000 0.3867100000 -0.6020800000 +H 5.6581500000 -0.0306600000 -1.3892300000 +H 1.1111700000 1.4848500000 1.3001400000 +O 1.1125000000 1.0437900000 0.4380500000 +H 2.4646100000 1.4439700000 -0.2957800000 +H -2.6055600000 -3.8401000000 0.7408200000 +O -2.5294900000 -2.9952600000 1.1979800000 +H -3.0216400000 -3.0925900000 2.0202700000 +H -3.0833500000 -0.3484100000 -0.3364600000 +O -2.2369000000 -0.8878300000 -0.1196100000 +H -2.4170000000 -1.7330000000 0.4353100000 +H 3.2382000000 2.4213400000 -1.3534200000 +O 3.3423400000 1.8317200000 -0.5965100000 +H 4.2051800000 1.1815100000 -0.6520000000 +H -4.9037300000 0.8296100000 -0.1650900000 +O -4.2134400000 0.5095600000 -0.7557500000 +H -4.6344800000 0.3838600000 -1.6133600000 +Hg -0.5689900000 0.1026400000 0.2125400000 diff --git a/mp2_xyz/w6s21.xyz b/mp2_xyz/w6s21.xyz new file mode 100644 index 0000000..25fec90 --- /dev/null +++ b/mp2_xyz/w6s21.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s21-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +Hg 0.0885354897 0.0757103351 0.0808436837 +O -1.1101784897 1.8127871025 -0.9355626429 +H -1.7304186496 1.7659605477 -1.6740000599 +H -1.4040013517 2.5549405603 -0.3922099644 +O -1.8063887713 -1.2253863397 0.5288279663 +H -2.6083050465 -0.9789742454 1.0067284938 +H -2.0791769767 -1.8875250836 -0.1188652066 +O 0.2026512069 1.6971333743 1.7670697814 +H -0.1457782359 1.6575741043 2.6666294408 +H 0.9798032313 2.2684928766 1.8109940758 +O 0.3422892302 -1.5981890507 -1.5382711786 +H 0.9039915553 -2.3575183210 -1.3376191504 +H 0.3520846937 -1.5107866738 -2.4997505407 +O 1.0502242850 -1.6178337443 1.3826467088 +H 0.4706161465 -2.2030188745 1.8866004140 +H 1.8916385121 -1.6099344074 1.8560778529 +O 1.8569720362 1.3845017767 -0.7230420305 +H 2.7756902640 1.1293995584 -0.8748806038 +H 1.6665412006 2.0775166142 -1.3678808398 diff --git a/mp2_xyz/w6s22.xyz b/mp2_xyz/w6s22.xyz new file mode 100644 index 0000000..7a03489 --- /dev/null +++ b/mp2_xyz/w6s22.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s22-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +Hg 0.7039300000 -0.5464200000 -0.1537300000 +O -0.5817500000 -1.9709600000 0.5232400000 +H -0.5665100000 -2.8352000000 0.0896900000 +H -1.5908500000 -1.6559200000 0.7451300000 +O 1.5709800000 0.8579600000 1.6148600000 +H 1.9707500000 0.5296100000 2.4310900000 +H 1.1408300000 1.6864200000 1.8624100000 +O -2.7721100000 -1.1200100000 1.1036500000 +H -3.2599200000 -0.5459500000 0.4839200000 +H -3.4009200000 -1.6235900000 1.6328700000 +O -0.7263500000 1.1906500000 -0.8269600000 +H -1.7050300000 1.1413500000 -0.8566300000 +H -0.4692800000 1.8832400000 -1.4467200000 +O -3.4917600000 0.8422400000 -0.7067200000 +H -3.9788800000 1.5767600000 -0.3106200000 +H -3.9795200000 0.6437600000 -1.5165400000 +O 2.3529500000 0.4286900000 -1.0711300000 +H 2.9548900000 0.8644300000 -0.4483900000 +H 2.8867000000 0.0386400000 -1.7794700000 diff --git a/mp2_xyz/w6s23.xyz b/mp2_xyz/w6s23.xyz new file mode 100644 index 0000000..9435ab4 --- /dev/null +++ b/mp2_xyz/w6s23.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s23-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg 0.5854007474 -0.1965271570 -0.2486446625 +O -0.7861907974 1.6811907761 0.0739880118 +H -0.4993328034 2.5860439080 -0.0958347179 +H -1.7650821952 1.6852806328 0.0179448463 +O -2.9284314504 -1.2317285704 0.5088862980 +H -3.3889355212 -0.4039729465 0.2763409994 +H -3.5805406878 -1.9162471545 0.6966126293 +O 1.4491954816 0.0571220525 1.9955837745 +H 1.8241312601 -0.6594353617 2.5245642474 +H 1.0337530926 0.6496565235 2.6350861581 +O -0.7471322559 -1.7255233129 -0.4186423368 +H -1.7519816808 -1.5406402038 -0.0708065357 +H -0.7441196184 -2.2380245486 -1.2386756439 +O 2.2769288640 1.0602558414 -0.5194589357 +H 2.8771953694 1.0910229510 0.2412604871 +H 2.8146963429 1.0780737900 -1.3252140751 +O -3.5596976202 1.4097729943 -0.0186776799 +H -4.0349664208 1.6775613935 -0.8158720265 +H -4.0367111064 1.8461103923 0.6994981620 diff --git a/mp2_xyz/w6s24.xyz b/mp2_xyz/w6s24.xyz new file mode 100644 index 0000000..31dd4cc --- /dev/null +++ b/mp2_xyz/w6s24.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s24-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +H -2.2906300000 1.6486400000 0.1093200000 +O -1.6086800000 2.3236000000 0.2750100000 +H -2.0340800000 3.1737500000 0.4316800000 +H 1.1581900000 2.4280500000 -0.9120100000 +O 0.7592600000 1.9796200000 -0.1510300000 +H -0.2775700000 2.2186600000 -0.0390000000 +H -2.0331400000 -3.1742400000 -0.4314200000 +O -1.6079300000 -2.3239800000 -0.2748300000 +H -2.2900600000 -1.6492400000 -0.1090200000 +H 1.1597600000 -2.4273400000 0.9106400000 +O 0.7602000000 -1.9790700000 0.1499000000 +H -0.2764900000 -2.2185500000 0.0384700000 +H -3.8687600000 -0.0292700000 0.7604800000 +O -3.2721900000 -0.0003000000 0.0002700000 +H -3.8690100000 0.0284300000 -0.7597600000 +H 4.0311300000 0.5186000000 0.5652100000 +O 3.4454100000 -0.0003400000 0.0001400000 +H 4.0311800000 -0.5190800000 -0.5650700000 +Hg 1.0296700000 0.0003600000 -0.0006000000 diff --git a/mp2_xyz/w6s3.xyz b/mp2_xyz/w6s3.xyz new file mode 100644 index 0000000..a5e430f --- /dev/null +++ b/mp2_xyz/w6s3.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s3-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +Hg -0.7491900000 -0.4976000000 -0.0894800000 +O 5.4923900000 1.6009700000 -0.4449100000 +H 5.7228300000 2.4352700000 -0.0179900000 +H 6.3429400000 1.0418600000 -0.6844200000 +O 3.6741900000 0.3622700000 0.7337000000 +H 3.7664900000 0.0234100000 1.6286100000 +H 4.7530700000 1.0975200000 0.0711800000 +O 7.4505300000 0.2451000000 -1.0971000000 +H 8.2289300000 0.0757800000 -0.5563300000 +H 7.7436900000 0.2433900000 -2.0145800000 +O -2.2727000000 -1.6925200000 -0.5899900000 +H -3.0349900000 -1.9490000000 0.0982200000 +H -2.6233800000 -1.6314500000 -1.4885400000 +O -3.9445300000 -2.3199500000 1.0865700000 +H -4.8035400000 -1.8935200000 1.1855500000 +H -4.0734500000 -3.2534400000 1.2919300000 +O 0.8016300000 0.5348300000 0.3935400000 +H 2.7228400000 0.4152700000 0.5463100000 +H 0.5058700000 1.4273600000 0.6282800000 diff --git a/mp2_xyz/w6s4.xyz b/mp2_xyz/w6s4.xyz new file mode 100644 index 0000000..00de8ba --- /dev/null +++ b/mp2_xyz/w6s4.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s4-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +H -3.3029500000 0.5424300000 0.6790200000 +O -2.6759600000 -0.1605900000 0.2728300000 +H -3.1219500000 -0.7599400000 -0.4307400000 +H 3.7183800000 0.8662300000 1.5922400000 +O 3.3859700000 0.2558600000 0.9201700000 +H 4.1869100000 -0.1619900000 0.3398900000 +H -0.2481300000 1.4364200000 -1.1733700000 +O -0.2468100000 0.7898600000 -0.4520300000 +H -1.8124500000 0.2116400000 -0.0225800000 +H -3.9627200000 -2.6030900000 -1.1434200000 +O -3.7072300000 -1.7115100000 -1.4021300000 +H -4.2669400000 -1.4764200000 -2.1489200000 +H -4.7701700000 2.1439300000 0.9378000000 +O -4.1579200000 1.5380100000 1.3670800000 +H -4.5118100000 1.3762000000 2.2478500000 +H 5.5242500000 -1.6027300000 -0.1180400000 +O 5.1284200000 -0.7786600000 -0.4269800000 +H 5.8267300000 -0.2809300000 -0.8688200000 +Hg 1.5614000000 0.5791400000 0.1893500000 diff --git a/mp2_xyz/w6s5.xyz b/mp2_xyz/w6s5.xyz new file mode 100644 index 0000000..c005d5b --- /dev/null +++ b/mp2_xyz/w6s5.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s5-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg 0.0000471007 0.1099667560 0.0007745327 +O -1.9431260146 0.1454111509 0.1782115712 +H -2.4316559251 -0.6278765524 0.6715572578 +H -2.5085039722 0.6611369940 -0.5257126821 +O -3.0097929909 -1.6938775536 1.4494494836 +H -3.4632496786 -2.4495941922 1.0593674700 +H -3.4643683000 -1.5053830206 2.2786034163 +O 1.9432495265 0.1451126562 -0.1764943749 +H 2.4311816466 -0.6257720922 -0.6741469595 +H 2.5089390266 0.6562170113 0.5305450467 +O 3.1899583729 1.4672630334 1.5050827550 +H 3.6570149083 1.1072685758 2.2673771867 +H 3.6755842234 2.2563067304 1.2382864191 +O 3.0085446737 -1.6878434699 -1.4580449659 +H 3.4631467799 -1.4950167390 -2.2861878152 +H 3.4615301595 -2.4460542920 -1.0722792527 +O -3.1889267757 1.4784330148 -1.4954294609 +H -3.6563730615 1.1232589077 -2.2597438191 +H -3.6738466995 2.2663340814 -1.2240138086 diff --git a/mp2_xyz/w6s6.xyz b/mp2_xyz/w6s6.xyz new file mode 100644 index 0000000..b95d653 --- /dev/null +++ b/mp2_xyz/w6s6.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s6-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=check'--- +Hg -0.5509814266 -0.1066552179 -0.1613526362 +O 1.1435548427 3.0238320421 0.1189234640 +H 1.5092717136 3.5347374446 -0.6106188727 +H 1.1137170456 3.6342458936 0.8629528344 +O -2.3789493108 -0.7416678451 -0.6398984077 +H -3.2325879831 -0.6333606088 -0.0052668342 +H -2.6297339434 -0.7585147597 -1.5730140348 +O 1.2348475775 0.4168938981 0.3297441586 +H 1.2884204809 1.4124028346 0.2710158092 +H 2.4307943635 -0.3667119450 0.7202468047 +O -4.2613529821 -0.5398000912 0.8942856880 +H -4.9375349169 0.1442899329 0.8230417642 +H -4.7070248329 -1.3427542378 1.1903317865 +O 3.2173612318 -0.9638832628 1.0092010272 +H 4.0856654891 -0.9326780937 0.4083691548 +H 3.4226721248 -0.8514526681 1.9460891304 +O 5.1907117758 -0.9703425180 -0.4524851698 +H 5.9428822389 -0.3730597936 -0.3771033692 +H 5.5377725118 -1.8163070041 -0.7576132973 diff --git a/mp2_xyz/w6s8.xyz b/mp2_xyz/w6s8.xyz new file mode 100644 index 0000000..8e16799 --- /dev/null +++ b/mp2_xyz/w6s8.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s8-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +Hg 0.3534100000 -0.4223100000 -0.1312500000 +O -3.6149800000 0.5554200000 0.6326400000 +H -4.4521300000 0.1552300000 0.1047800000 +H -3.8398800000 0.7931000000 1.5416500000 +O -5.4905800000 -0.3222000000 -0.6647000000 +H -6.1504300000 -0.9406700000 -0.3313200000 +H -5.9420200000 0.2632800000 -1.2836900000 +O -1.4353600000 -0.7583300000 0.5769100000 +H -2.7573200000 0.0069700000 0.6000400000 +H -1.5366700000 -1.7033100000 0.7577100000 +O 4.0688300000 0.3858100000 0.5456600000 +H 4.7008500000 -0.2766200000 0.8485000000 +H 4.5775500000 1.1886800000 0.3829600000 +O 0.7477200000 1.9482700000 0.7383800000 +H 0.7923700000 2.2310800000 1.6582200000 +H 0.7558500000 2.7658800000 0.2286100000 +O 2.1704300000 -0.1346400000 -0.9425600000 +H 2.9952700000 0.0625100000 -0.3217100000 +H 2.4366200000 -0.7317500000 -1.6554200000 diff --git a/mp2_xyz/w6s9.xyz b/mp2_xyz/w6s9.xyz new file mode 100644 index 0000000..28f754e --- /dev/null +++ b/mp2_xyz/w6s9.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s9-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq'--- +Hg 0.3318200000 0.0717000000 -0.2604900000 +O 4.1209800000 1.0564700000 -0.0671600000 +H 4.5904600000 1.7606200000 -0.5332200000 +H 4.8109200000 0.4967100000 0.3114800000 +O -5.5329600000 1.0067900000 -0.3460200000 +H -5.9799000000 1.3081600000 -1.1455700000 +H -6.1874000000 1.0125700000 0.3615800000 +O -3.7358300000 -0.6287700000 -0.5646700000 +H -3.9966300000 -1.5385400000 -0.3711800000 +H -4.5419000000 0.0629100000 -0.4338300000 +O 1.5177100000 1.7328500000 1.2201400000 +H 1.1477800000 2.4374800000 1.7633700000 +H 2.4747900000 1.8208900000 1.3027400000 +O 2.1021700000 0.0957100000 -1.2380700000 +H 2.9519800000 0.4415600000 -0.7781900000 +H 2.3204000000 -0.6291500000 -1.8389800000 +O -1.4790000000 -0.0395500000 0.4684000000 +H -1.4387300000 0.0213000000 1.4327500000 +H -2.8551900000 -0.3934100000 -0.1154800000 diff --git a/old_tools/Cesar_tools/DH_Angle.py b/old_tools/Cesar_tools/DH_Angle.py old mode 100755 new mode 100644 diff --git a/old_tools/atoms_transfer.py b/old_tools/atoms_transfer.py index f865f70..b25ffda 100644 --- a/old_tools/atoms_transfer.py +++ b/old_tools/atoms_transfer.py @@ -135,6 +135,18 @@ def atom_transfer(transfer_list, header_distance_matrix, data_xyz, distance_matr q1 = 0.5 * (r1 - r2) q2 = r1 + r2 + if q1 > -0.00001 and q1 < 0.00001: + pass + # print(file_xyz) + # print(coordinates_first) + # print(coordinates_central) + # print(coordinates_second) + # print(r1, r2) + + # print(q1, q2) + print(r1, r2) + # print() + natural_bond_coordinates.append((q1, q2)) return natural_bond_coordinates diff --git a/old_tools/compare_xyz/compare_xyz.py b/old_tools/compare_xyz/compare_xyz.py old mode 100755 new mode 100644 diff --git a/old_tools/compare_xyz/dihedral.py b/old_tools/compare_xyz/dihedral.py old mode 100755 new mode 100644 diff --git a/old_tools/dihedral.py b/old_tools/dihedral.py old mode 100755 new mode 100644 diff --git a/old_tools/dihedral2.py b/old_tools/dihedral2.py old mode 100755 new mode 100644 diff --git a/old_tools/plot_rda.py b/old_tools/plot_rda.py old mode 100755 new mode 100644 diff --git a/old_tools/radial_distribution_analisys.py b/old_tools/radial_distribution_analisys.py old mode 100755 new mode 100644 index 02d25c3..3dc7151 --- a/old_tools/radial_distribution_analisys.py +++ b/old_tools/radial_distribution_analisys.py @@ -14,12 +14,13 @@ # ------------------------------------------------------------------------------------ # ------ moules # ------------------------------------------------------------------------------------ +import functions as fn import sys # to get System-specific parameters import os # - to check id a file or dir exits -> os.path.exists() # - to smooth out your data from scipy.interpolate import make_interp_spline, BSpline import glob # - Unix style pathname pattern expansion -#from natsort import natsorted # Simple yet flexible natural sorting in Python. +# from natsort import natsorted # Simple yet flexible natural sorting in Python. # - complete data analysis tool (it can replace matplotlib or numpy, as it is built on top of both) import pandas as pd import numpy as np # - arrays and matrix manipulation @@ -28,13 +29,12 @@ from matplotlib import rc rc('text', usetex=True) # --- enable TeX mode for matplotlib -import functions as fn # ------------------------------------------------------------------------------------ # ------ body # ------------------------------------------------------------------------------------ print(f'\n****************************************************') print(f'* Radial, Angle, and Dihedral *') -print(f'* Distribution Analisys for XYZ files *') #Borrar lo de Radial +print(f'* Distribution Analisys for XYZ files *') # Borrar lo de Radial print(f'* "RADDA" *') print(f'****************************************************') @@ -42,14 +42,14 @@ # print(f"\nCurrent working directory: {os.getcwd()}") -#Get path of Working Directory or Ask +# Get path of Working Directory or Ask working_dir = fn.working_path(sys.argv) -#Chage to Working Directory +# Chage to Working Directory fn.cd_path(working_dir) -##########################Lineas transladadas a functions.py -#if len(sys.argv) <= 1: +# Lineas transladadas a functions.py +# if len(sys.argv) <= 1: # tmp_dir = input(f'\nDirectory (whit the XYZ files) to make the RDA [default: empty]: ') # tmp_dir = tmp_dir.strip() @@ -57,18 +57,18 @@ # working_dir = os.getcwd() # else: # working_dir = os.getcwd() + '/' + tmp_dir -#else: +# else: # working_dir = os.getcwd() + '/' + sys.argv[1] # print(f'\nWorking directiry: {working_dir}') # Check if the working dir exists -#if os.path.exists(working_dir) : +# if os.path.exists(working_dir) : # Change the current working Directory # os.chdir(working_dir) -#else: +# else: # print(f'\n*** ERROR ***') # exit(f"Can't change the Working Directory, {working_dir} doesn't exist") -##########################Lineas transladadas a functions.py +# Lineas transladadas a functions.py # - reading files repited_list_xyz = [] # repited files (if any) @@ -83,7 +83,7 @@ if unique_input_xyz not in list_xyz: list_xyz.append(unique_input_xyz) -list_xyz = ["w3s2.xyz"] +# list_xyz = ["w3s2.xyz"] # list_xyz = ["w1s1.xyz", "w2s1.xyz"] # list_xyz = ["w1s1.xyz", "w2s1.xyz", "w3s1.xyz"] @@ -112,20 +112,19 @@ # ------------------------------------------------------------------------------- # - Elements list to do radial distribution analisys -###############################Filas transladadas a functions.py -#def all_elements(file_xyz): +# Filas transladadas a functions.py +# def all_elements(file_xyz): # """ Function to get atomic pairs from a XYZ file """ # elements = pd.read_csv(list_xyz[0], delim_whitespace=True, # skiprows=2, header=None, # names=["element", "x-coordinate", "y-coordinate", "z-coordinate"]) - # - if XYZ file has no coordinates (by mistake) # if elements.shape[0] <= 1: # elements = [] # print(f'\n*** WARNING *** \nNo coordinates found in {file_xyz}') # return elements - # return '*** WARNING *** No coordinates found in ', file_xyz + # return '*** WARNING *** No coordinates found in ', file_xyz # elements = elements['element'].tolist() @@ -151,12 +150,11 @@ # return element_list -#def sort_input_pairs(elements): +# def sort_input_pairs(elements): # """sorting uniques atomic pair A-B from an input list """ # - deleting comma used to split atomic pairs (if any) # elements = [pair.replace(',','') for pair in elements] - # - creating a list of lists to capitalize each atom # elements = [pair.split('-') for pair in elements] @@ -170,7 +168,7 @@ # pair += 2 # return element_list -###############################Filas transladadas a functions.py +# Filas transladadas a functions.py # -------------------------------------------------------------------------- @@ -642,7 +640,7 @@ # print() # -------------------------------------------------------------------- - # atom transfer according to Stern-limbach model + # - atom transfer according to Stern-limbach model transfer_list = ["O", "H", "O"] @@ -696,41 +694,46 @@ # --------------------------------------------------------------------------- # - Stern-Limbach plot fig = plt.figure(figsize=(10, 8)) # inches WxH -fig.suptitle(f'Stern-Limbach for {transfer_list[0]}-{transfer_list[1]}---{transfer_list[2]}', fontsize=20) #, fontweight='bold') +# , fontweight='bold') +fig.suptitle(f'Stern-Limbach for {transfer_list[0]}-{transfer_list[1]}---{transfer_list[2]}', fontsize=20) ax1 = plt.subplot(111) ax1.grid() # - legends for the main plot -plt.xlabel('q1=(r1-r2)/2 [Angstrom]', fontsize=18) #, fontweight='bold') -plt.ylabel('q2=r1+r2 [Angstrom]', fontsize=18) #, fontweight='bold') +plt.xlabel('q1=(r1-r2)/2 [Angstrom]', fontsize=18) # , fontweight='bold') +plt.ylabel('q2=r1+r2 [Angstrom]', fontsize=18) # , fontweight='bold') # - loading files to read and plot them x, y = [], [] for q1, q2 in natural_bond_coordinates: x.append(q1) y.append(q2) + + if q1 > -0.00001 and q1 < 0.00001: + print(file_xyz) + # print(q1, q2) -ax1.plot(x, y, 'o', label='Transfer %s--%s-----%s' %(transfer_list[0], transfer_list[1], transfer_list[2])) +ax1.plot(x, y, 'o', label='Transfer %s--%s-----%s' % + (transfer_list[0], transfer_list[1], transfer_list[2])) ax1.xaxis.set_major_locator(plt.MaxNLocator(12)) -# ----------------------------------------------------------- -# - Ending the plot +# # ----------------------------------------------------------- +# # - Ending the plot -plt.legend(loc=0) -# Put a legend below current axis -# plt.legend(loc='lower center', bbox_to_anchor=(1.32, 0.6, 0.0, 0.0), - # fancybox=True, shadow=True, ncol=1, fontsize=11) +# plt.legend(loc=0) +# # Put a legend below current axis +# # plt.legend(loc='lower center', bbox_to_anchor=(1.32, 0.6, 0.0, 0.0), +# # fancybox=True, shadow=True, ncol=1, fontsize=11) -# - Shrink current axis's height by 10% on the bottom -# box = ax1.get_position() -# ax1.set_position([box.x0, box.y0, box.width * 0.7, box.height]) - -# --------------------------------------------------------------------------------------------------------- -# - ENDING the plots -plt.show() +# # - Shrink current axis's height by 10% on the bottom +# # box = ax1.get_position() +# # ax1.set_position([box.x0, box.y0, box.width * 0.7, box.height]) +# # --------------------------------------------------------------------------------------------------------- +# # - ENDING the plots +# plt.show() # --------------------------------------------------------------------------------------- @@ -772,7 +775,8 @@ print(f' {dihedral_list[3]}') print(f'') -bond_angle = np.linspace(min_dihedral_angle, max_dihedral_angle, nbins_dihedral_angle) +bond_angle = np.linspace( + min_dihedral_angle, max_dihedral_angle, nbins_dihedral_angle) total_dihedral_angles = sum(occurrences_dihedral_angle) diff --git a/open_0zd.xyz b/open_0zd.xyz new file mode 100644 index 0000000..b46ba7a --- /dev/null +++ b/open_0zd.xyz @@ -0,0 +1,114 @@ + 112 +Chemical Component 0ZD, taken from http://ligand-expo.rcsb.org/reports/0/0ZD/index.html +O -16.202 18.781 -35.336 +C -16.663 19.920 -35.553 +O -16.903 20.277 -36.716 +C -16.953 20.857 -34.410 +C -18.450 20.786 -34.033 +C -18.804 21.710 -32.879 +C -19.029 19.391 -33.818 +N -15.967 20.685 -33.315 +S -14.862 21.721 -33.178 +O -15.375 23.018 -33.550 +C -13.666 21.295 -34.178 +C -13.608 21.787 -35.489 +C -12.580 21.412 -36.358 +C -11.556 20.555 -35.938 +C -10.438 20.173 -36.850 +C -9.924 18.877 -36.889 +C -8.871 18.564 -37.754 +C -8.316 19.542 -38.575 +C -8.806 20.842 -38.528 +C -9.865 21.147 -37.670 +C -11.595 20.071 -34.623 +C -12.639 20.435 -33.755 +O -14.303 21.712 -31.839 +C -15.913 19.409 -32.579 +C -16.273 19.461 -31.104 +N -16.036 18.123 -30.578 +C -16.798 17.063 -30.835 +O -17.843 17.161 -31.482 +C -16.400 15.716 -30.280 +C -17.287 14.645 -30.364 +C -16.928 13.402 -29.843 +C -15.687 13.222 -29.239 +C -15.155 15.529 -29.668 +C -14.789 14.283 -29.148 +C -13.449 14.069 -28.495 +O -13.253 13.028 -27.868 +N -12.488 14.993 -28.605 +C -11.210 14.876 -27.900 +C -11.412 15.375 -26.475 +N -10.222 15.420 -25.603 +C -10.014 14.395 -24.551 +C -11.099 14.469 -23.506 +O -10.828 14.180 -22.324 +O -12.261 14.798 -23.804 +C -9.827 12.933 -24.999 +C -8.739 12.773 -26.054 +C -11.107 12.190 -25.375 +S -9.378 16.690 -25.588 +O -8.025 16.425 -25.183 +O -9.451 17.315 -26.887 +C -10.049 17.691 -24.490 +C -9.657 17.722 -23.139 +C -10.253 18.590 -22.217 +C -11.067 18.572 -24.877 +C -11.666 19.442 -23.963 +C -11.271 19.457 -22.619 +C -11.886 20.424 -21.661 +C -13.250 20.714 -21.686 +C -13.791 21.636 -20.787 +C -12.965 22.295 -19.879 +C -11.601 22.028 -19.863 +C -11.066 21.100 -20.749 +H -16.095 18.320 -36.160 +H -16.797 21.872 -34.805 +H -18.985 21.191 -34.905 +H -19.877 21.620 -32.653 +H -18.217 21.430 -31.992 +H -18.574 22.749 -33.157 +H -20.094 19.472 -33.556 +H -18.922 18.803 -34.742 +H -18.488 18.891 -33.001 +H -14.372 22.468 -35.834 +H -12.575 21.789 -37.370 +H -10.341 18.113 -36.249 +H -8.485 17.556 -37.786 +H -7.508 19.291 -39.246 +H -8.371 21.610 -39.150 +H -10.248 22.156 -37.640 +H -10.815 19.411 -34.273 +H -12.652 20.047 -32.747 +H -16.609 18.711 -33.068 +H -14.887 19.020 -32.659 +H -15.639 20.193 -30.583 +H -17.330 19.737 -30.979 +H -15.244 17.992 -29.981 +H -18.251 14.777 -30.832 +H -17.618 12.573 -29.909 +H -15.419 12.255 -28.839 +H -14.467 16.359 -29.596 +H -12.648 15.790 -29.188 +H -10.887 13.825 -27.885 +H -10.448 15.487 -28.405 +H -11.817 16.396 -26.536 +H -12.150 14.716 -25.995 +H -9.081 14.668 -24.037 +H -11.610 14.261 -21.790 +H -9.444 12.411 -24.110 +H -7.840 13.323 -25.740 +H -8.494 11.707 -26.170 +H -9.098 13.173 -27.014 +H -11.860 12.334 -24.587 +H -11.493 12.583 -26.327 +H -10.890 11.117 -25.483 +H -8.874 17.057 -22.804 +H -9.924 18.589 -21.188 +H -11.396 18.579 -25.906 +H -12.444 20.112 -24.297 +H -13.891 20.223 -22.404 +H -14.852 21.838 -20.796 +H -13.384 23.012 -19.189 +H -10.958 22.541 -19.163 +H -10.005 20.898 -20.734 diff --git a/plot_rda.py b/plot_rda.py new file mode 100644 index 0000000..ae35e34 --- /dev/null +++ b/plot_rda.py @@ -0,0 +1,168 @@ +#!/usr/bin/python3.8 + +# --------------------------------------------------------------------------------------------------------- +# ------ moules +# --------------------------------------------------------------------------------------------------------- +import matplotlib.pyplot as plt +import matplotlib.ticker as plticker # - ticks +import numpy as np +import sys # to get System-specific parameters +import os # contains some useful functions on pathnames +import glob # - Unix style pathname pattern expansion +from scipy.interpolate import make_interp_spline, BSpline # - to smooth out your data + +# --------------------------------------------------------------------------------------------------------- +# ------ body +# --------------------------------------------------------------------------------------------------------- +print(f"\nPlotting Radial Distribution Analisys (RDA)\n") + +# ----------------------------------------------------------- +# - working directory +print(f"\nCurrent working directory: {os.getcwd()}") + +##### if uncomment the section to change the working dir, must change +##### len(sys.argv) < 3 +##### input_arguments = + +# if len(sys.argv) <= 1: +# tmp_dir = input(f'\nDirectory (whit the XYZ files) to make the RDA [default: empty]: ') +# tmp_dir = tmp_dir.strip() + +# if tmp_dir == '.' or len(tmp_dir) < 1: +# working_dir = os.getcwd() +# else: +# working_dir = os.getcwd() + '/' + tmp_dir +# else: +# working_dir = os.getcwd() + '/' + sys.argv[1] + +# print(f'\nWorking directiry: {working_dir}') + +# # Check if New path exists +# if os.path.exists(working_dir) : +# # Change the current working Directory +# os.chdir(working_dir) +# else: +# print(f'\n*** ERROR ***') +# exit(f"Can't change the Working Directory, {working_dir} doesn't exist") +# ----------------------------------------------------------- +# - RDA files to plot +rda_files = [] +if len(sys.argv) < 2: + input_files = input( + f"List of files to plot RDA, **separated by space** [Default: all '.dat']: " + ) + + # - by default reading elements for the first XYZ file + if len(input_files.split()) < 1: + for file_rda in glob.glob("*.dat"): + rda_files.append(file_rda) + else: + rda_files = input_files.split() +else: + input_arguments = 1 + while input_arguments < len(sys.argv): + rda_files.append(sys.argv[input_arguments]) + input_arguments += 1 + +# - checking if there is any file to plot +if len(rda_files) > 0: + # print(f'\nList of files:\n\n{rda_files}\n') + print(f"\nList of files:\n") + print("\n".join(rda_files)) + for file_rda in rda_files: + if not os.path.exists(file_rda): + exit(f"\n*** Warinnig ***\n file {file_rda} does not exits \n") +else: + exit(f"\n *** ERROR ***\n No files found to plot\n") + +# ----------------------------------------------------------- +# - plotting: defining frames and designing the area to plot +fig = plt.figure(figsize=(10, 8)) # inches WxH +fig.suptitle("Distribution Analisys", fontsize=20) # , fontweight='bold') + +ax1 = plt.subplot(111) +ax1.grid() + +# - legends for the main plot +plt.ylabel("Relative Number of Ocurrences", fontsize=12) # , fontweight='bold') +# plt.xlabel('Bond Distance [Angstrom]', fontsize=12) #, fontweight='bold') + +# ----------------------------------------------------------- +# - loading files to read and plot them +for rda in rda_files: + x, y = [], [] + for line in open(rda, "r"): + # skipping the header + if line.startswith("#"): + label = [header.title() for header in line.split()] + label_x = " ".join(label[1:3]) + continue + + values = [float(s) for s in line.split()] + x.append(values[0]) + y.append(values[1]) + + # total number of distances + total = sum(y) + + # - to smooth the curve (BSpline) + smooth_x = np.linspace(x[0], x[-1], len(x) * 100) + + # smooth curve BSpline, degree k=3, cubic + smooth = make_interp_spline(x, y, k=3) + smooth_y = smooth(smooth_x) + + # - Bspline fitting + ax1.plot( + smooth_x, + smooth_y / total, + "-", + # color="black", + # label=" %s \n Total= %i" % (rda, total), + label="%s" % (rda), + ) + # ax1.plot( + # x, + # [i / total for i in y], + # ".", + # color="black", + # # label=" %s \n Total= %i" % (rda, total), + # ) + + # - raw data, no Bspline fitting + # ax1.plot(x, y, "o", label="%s" % rda) + +# - ticks for the x-axis +# delta_x = (x[-1] - x[0]) / 10 +# ax1.xaxis.set_major_locator(plticker.MultipleLocator(base=delta_x)) +ax1.xaxis.set_major_locator(plt.MaxNLocator(12)) + +if len(label_x) < 1: + label_x = input(f"Please, insert a name for x-axis: ") + +plt.xlabel(label_x, fontsize=12) # , fontweight='bold') +# ----------------------------------------------------------- +# - Ending the plot + +# plt.legend(loc=0) +# Put a legend below current axis +plt.legend( + loc="lower right", + bbox_to_anchor=(1.5, 0.0, 0.0, 0.0), + fancybox=True, + shadow=True, + ncol=1, + fontsize=11, +) + +# - Shrink current axis's height by 10% on the bottom +box = ax1.get_position() +ax1.set_position([box.x0, box.y0, box.width * 0.7, box.height]) + +# --------------------------------------------------------------------------------------------------------- +# - ENDING the plots +plt.show(block=True) + +print(f"\n *** DONE ***\n") +# ---------------------------- END +exit() diff --git a/plot_stern-limbach.py b/plot_stern-limbach.py new file mode 100644 index 0000000..54116e9 --- /dev/null +++ b/plot_stern-limbach.py @@ -0,0 +1,131 @@ +#!/usr/bin/python3.8 + +# --------------------------------------------------------------------------------------------------------- +# ------ moules +# --------------------------------------------------------------------------------------------------------- +import matplotlib.pyplot as plt +import matplotlib.ticker as plticker # - ticks +import numpy as np +import sys # to get System-specific parameters +import os # contains some useful functions on pathnames +import glob # - Unix style pathname pattern expansion +from scipy.interpolate import make_interp_spline, BSpline # - to smooth out your data + +# --------------------------------------------------------------------------------------------------------- +# ------ body +# --------------------------------------------------------------------------------------------------------- +print(f'\nPlotting Radial Distribution Analisys (RDA)\n') + +# ----------------------------------------------------------- +# - working directory +print(f"\nCurrent working directory: {os.getcwd()}") + +##### if uncomment the section to change the working dir, must change +##### len(sys.argv) < 3 +##### input_arguments = + +# if len(sys.argv) <= 1: +# tmp_dir = input(f'\nDirectory (whit the XYZ files) to make the RDA [default: empty]: ') +# tmp_dir = tmp_dir.strip() + +# if tmp_dir == '.' or len(tmp_dir) < 1: +# working_dir = os.getcwd() +# else: +# working_dir = os.getcwd() + '/' + tmp_dir +# else: +# working_dir = os.getcwd() + '/' + sys.argv[1] + +# print(f'\nWorking directiry: {working_dir}') + +# # Check if New path exists +# if os.path.exists(working_dir) : +# # Change the current working Directory +# os.chdir(working_dir) +# else: +# print(f'\n*** ERROR ***') +# exit(f"Can't change the Working Directory, {working_dir} doesn't exist") +# ----------------------------------------------------------- +# - RDA files to plot +rda_files = [] +if len(sys.argv) < 2: + input_files = input(f"List of files to plot RDA, **separated by space** [Default: all '.dat']: ") + + # - by default reading elements for the first XYZ file + if len(input_files.split()) < 1: + for file_rda in glob.glob('*.dat'): + rda_files.append(file_rda) + else: + rda_files = input_files.split() +else: + input_arguments = 1 + while input_arguments < len(sys.argv): + rda_files.append(sys.argv[input_arguments]) + input_arguments += 1 + +# - checking if there is any file to plot +if len(rda_files) > 0: + # print(f'\nList of files:\n\n{rda_files}\n') + print(f'\nList of files:\n') + print('\n'.join(rda_files)) + for file_rda in rda_files: + if not os.path.exists(file_rda): + exit(f'\n*** Warinnig ***\n file {file_rda} does not exits \n') +else: + exit(f'\n *** ERROR ***\n No files found to plot\n') + + +input_list = ['O', 'H', 'O'] + +# ----------------------------------------------------------- +fig = plt.figure(figsize=(16, 8)) # inches WxH +# , fontweight='bold') +fig.suptitle(f'Stern-Limbach for {input_list[0]}-{input_list[1]}---{input_list[2]}', fontsize=20) + +ax1 = plt.subplot(111) +ax1.grid() + +# - legends for the main plot +plt.xlabel('q1=(r1-r2)/2 [Angstrom]', fontsize=18) +plt.ylabel('q2=r1+r2 [Angstrom]', fontsize=18) # , fontweight='bold') + +# - Extra text on plot +ax1.text(0.0, 3.0, f'A--a----B', + color='black', fontsize=15, + rotation=0, va='center', bbox=dict(facecolor='white', edgecolor='none')) + +# - loading files to read and plot them +for rda in rda_files: + # - loading files to read and plot them + x, y = [], [] + for line in open(rda, 'r'): + # skipping the header + if line.startswith("#"): + continue + + values = [float(s) for s in line.split()] + x.append(values[0]) + y.append(values[1]) + + ax1.plot(x, y, 'o', label='Transfer %s--%s----%s' % + (input_list[0], input_list[1], input_list[2])) + +ax1.xaxis.set_major_locator(plt.MaxNLocator(12)) + +# ----------------------------------------------------------- +# - Ending the plot +plt.legend(loc=0) +# # Put a legend below current axis +# plt.legend(loc='lower center', bbox_to_anchor=(1.32, 0.6, 0.0, 0.0), +# fancybox=True, shadow=True, ncol=1, fontsize=11) + +# # - Shrink current axis's height by 10% on the bottom +# box = ax1.get_position() +# ax1.set_position([box.x0, box.y0, box.width * 0.7, box.height]) + +# --------------------------------------------------------------------------------------------------------- +# - ENDING the plots +plt.show() + +print(f'\n *** DONE ***\n') +# ---------------------------- END +exit() diff --git a/rda_C-H.dat b/rda_C-H.dat new file mode 100644 index 0000000..447531d --- /dev/null +++ b/rda_C-H.dat @@ -0,0 +1,14 @@ +# distance [Angstrom] occurrence (total=46) +0.500000 0 +0.558333 0 +0.616667 0 +0.675000 0 +0.733333 0 +0.791667 0 +0.850000 0 +0.908333 0 +0.966667 0 +1.025000 0 +1.083333 0 +1.141667 0 +1.200000 46 diff --git a/rda_H-O.dat b/rda_H-O.dat new file mode 100644 index 0000000..d0bee0a --- /dev/null +++ b/rda_H-O.dat @@ -0,0 +1,58 @@ +# distance [Angstrom] occurrence (total=25) +0.600000 0 +0.651786 0 +0.703571 0 +0.755357 0 +0.807143 0 +0.858929 0 +0.910714 0 +0.962500 10 +1.014286 1 +1.066071 1 +1.117857 0 +1.169643 0 +1.221429 0 +1.273214 0 +1.325000 0 +1.376786 0 +1.428571 0 +1.480357 1 +1.532143 0 +1.583929 0 +1.635714 1 +1.687500 0 +1.739286 0 +1.791071 0 +1.842857 0 +1.894643 0 +1.946429 0 +1.998214 0 +2.050000 0 +2.101786 0 +2.153571 1 +2.205357 0 +2.257143 0 +2.308929 0 +2.360714 0 +2.412500 0 +2.464286 0 +2.516071 0 +2.567857 0 +2.619643 0 +2.671429 0 +2.723214 0 +2.775000 0 +2.826786 0 +2.878571 1 +2.930357 0 +2.982143 0 +3.033929 1 +3.085714 1 +3.137500 1 +3.189286 1 +3.241071 2 +3.292857 1 +3.344643 0 +3.396429 0 +3.448214 1 +3.500000 1 diff --git a/rda_Hg-O.dat b/rda_Hg-O.dat new file mode 100644 index 0000000..a454d8a --- /dev/null +++ b/rda_Hg-O.dat @@ -0,0 +1,58 @@ +# distance [Angstrom] occurrence (total=1) +0.600000 0 +0.651786 0 +0.703571 0 +0.755357 0 +0.807143 0 +0.858929 0 +0.910714 0 +0.962500 0 +1.014286 0 +1.066071 0 +1.117857 0 +1.169643 0 +1.221429 0 +1.273214 0 +1.325000 0 +1.376786 0 +1.428571 0 +1.480357 0 +1.532143 0 +1.583929 0 +1.635714 0 +1.687500 0 +1.739286 0 +1.791071 0 +1.842857 0 +1.894643 0 +1.946429 0 +1.998214 0 +2.050000 1 +2.101786 0 +2.153571 0 +2.205357 0 +2.257143 0 +2.308929 0 +2.360714 0 +2.412500 0 +2.464286 0 +2.516071 0 +2.567857 0 +2.619643 0 +2.671429 0 +2.723214 0 +2.775000 0 +2.826786 0 +2.878571 0 +2.930357 0 +2.982143 0 +3.033929 0 +3.085714 0 +3.137500 0 +3.189286 0 +3.241071 0 +3.292857 0 +3.344643 0 +3.396429 0 +3.448214 0 +3.500000 0 diff --git a/rda_HgO_gaussian.png b/rda_HgO_gaussian.png new file mode 100644 index 0000000..b6c895d Binary files /dev/null and b/rda_HgO_gaussian.png differ diff --git a/rda_O-H.dat b/rda_O-H.dat new file mode 100644 index 0000000..2fb9bee --- /dev/null +++ b/rda_O-H.dat @@ -0,0 +1,41 @@ +# distance [Angstrom] occurrence (total=8) +0.500000 0 +0.551282 0 +0.602564 0 +0.653846 0 +0.705128 0 +0.756410 0 +0.807692 0 +0.858974 0 +0.910256 0 +0.961538 0 +1.012821 4 +1.064103 0 +1.115385 1 +1.166667 1 +1.217949 0 +1.269231 0 +1.320513 1 +1.371795 0 +1.423077 1 +1.474359 0 +1.525641 0 +1.576923 0 +1.628205 0 +1.679487 0 +1.730769 0 +1.782051 0 +1.833333 0 +1.884615 0 +1.935897 0 +1.987179 0 +2.038462 0 +2.089744 0 +2.141026 0 +2.192308 0 +2.243590 0 +2.294872 0 +2.346154 0 +2.397436 0 +2.448718 0 +2.500000 0 diff --git a/rda_O-O.dat b/rda_O-O.dat new file mode 100644 index 0000000..0984070 --- /dev/null +++ b/rda_O-O.dat @@ -0,0 +1,48 @@ +# distance [Angstrom] occurrence (total=2) +0.600000 0 +0.652174 0 +0.704348 0 +0.756522 0 +0.808696 0 +0.860870 0 +0.913043 0 +0.965217 0 +1.017391 0 +1.069565 0 +1.121739 0 +1.173913 0 +1.226087 0 +1.278261 0 +1.330435 0 +1.382609 0 +1.434783 0 +1.486957 0 +1.539130 0 +1.591304 0 +1.643478 0 +1.695652 0 +1.747826 0 +1.800000 0 +1.852174 0 +1.904348 0 +1.956522 0 +2.008696 0 +2.060870 0 +2.113043 0 +2.165217 0 +2.217391 0 +2.269565 0 +2.321739 0 +2.373913 0 +2.426087 0 +2.478261 0 +2.530435 1 +2.582609 1 +2.634783 0 +2.686957 0 +2.739130 0 +2.791304 0 +2.843478 0 +2.895652 0 +2.947826 0 +3.000000 0 diff --git a/stern_limbach_gaussian.pdf b/stern_limbach_gaussian.pdf new file mode 100644 index 0000000..332884f Binary files /dev/null and b/stern_limbach_gaussian.pdf differ diff --git a/stern_limbach_gaussian.png b/stern_limbach_gaussian.png new file mode 100644 index 0000000..cc48cc9 Binary files /dev/null and b/stern_limbach_gaussian.png differ diff --git a/test_functions/blackbox_reading_files.py b/test_functions/blackbox_reading_files.py old mode 100755 new mode 100644 diff --git a/transfer_O-H-O.dat b/transfer_O-H-O.dat new file mode 100644 index 0000000..5d51b33 --- /dev/null +++ b/transfer_O-H-O.dat @@ -0,0 +1,8 @@ +# q1 [Angstrom] q2 [Angstrom] + -0.6193972645 3.1392639447 + -0.1162757888 4.8431363561 + 0.0590124303 5.8661793471 + 0.1377369020 4.7073695609 + 0.2783815629 4.9474468993 + 0.0731944087 4.8434095753 + -0.6166344681 3.1340487761 diff --git a/w1s1.xyz-old b/w1s1.xyz-old new file mode 100644 index 0000000..844de36 --- /dev/null +++ b/w1s1.xyz-old @@ -0,0 +1,6 @@ + 4 + file 'w1s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- +Hg -0.2251299774 0.0000000026 0.0107392362 +O 1.8213760892 0.0000000800 -0.0901652030 +H 2.3259447762 -0.7989195366 0.1773102636 +H 2.3259447157 0.7989197348 0.1773102636 diff --git a/cw2s1.xyz b/w2s1.xyz-old similarity index 98% rename from cw2s1.xyz rename to w2s1.xyz-old index a419cb9..0da03f0 100644 --- a/cw2s1.xyz +++ b/w2s1.xyz-old @@ -1,4 +1,4 @@ - + 7 file 'w2s1.log' was gotten at: ---' #p mp2=full gen pseudo=Read opt freq'--- Hg 0.0000026668 -0.0168497190 -0.0009253493 O 2.0015531788 -0.0663805205 0.0564370903 @@ -7,6 +7,3 @@ H 2.5320189630 -0.4574182146 -0.6640476515 O -2.0014461936 -0.0606116324 -0.0622201782 H -2.5277674475 0.6630733379 -0.4524786753 H -2.5321508417 -0.5171408960 0.6184161011 - - - diff --git a/w3s3.com b/w3s3.com new file mode 100644 index 0000000..f21f8ba --- /dev/null +++ b/w3s3.com @@ -0,0 +1,17 @@ +%chk=w3s3.chk + +#p hf/cc-pVTZ + + file 'w3s3.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- + +2 0 +Hg -0.6948470000 -0.3997160000 0.0004810000 +O 1.3035710000 2.6479640000 -0.0010920000 +H 1.6496690000 3.1073690000 0.7888160000 +H 1.6587450000 3.1063570000 -0.7872590000 +O 1.2049240000 0.2053020000 -0.0001690000 +H 2.2323150000 -0.7151560000 0.0002380000 +H 1.2685510000 1.3331090000 -0.0005610000 +O 3.0068120000 -1.4937750000 -0.0003070000 +H 3.5716870000 -1.5151740000 -0.8023100000 +H 3.5710710000 -1.5165500000 0.8022210000 diff --git a/w3s3.xyz-old b/w3s3.xyz-old new file mode 100644 index 0000000..83fc06f --- /dev/null +++ b/w3s3.xyz-old @@ -0,0 +1,12 @@ + 10 + file 'w3s3.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg -0.6948470000 -0.3997160000 0.0004810000 +O 1.3035710000 2.6479640000 -0.0010920000 +H 1.6496690000 3.1073690000 0.7888160000 +H 1.6587450000 3.1063570000 -0.7872590000 +O 1.2049240000 0.2053020000 -0.0001690000 +H 2.2323150000 -0.7151560000 0.0002380000 +H 1.2685510000 1.3331090000 -0.0005610000 +O 3.0068120000 -1.4937750000 -0.0003070000 +H 3.5716870000 -1.5151740000 -0.8023100000 +H 3.5710710000 -1.5165500000 0.8022210000 diff --git a/w6s14.xyz-old b/w6s14.xyz-old new file mode 100644 index 0000000..bbf865a --- /dev/null +++ b/w6s14.xyz-old @@ -0,0 +1,21 @@ + 19 + file 'w6s14-Final.log' was gotten at: ---' #p mp2=full gen pseudo=Read freq geom=checkpoint'--- +Hg 0.4338592270 -0.1863853164 -0.2093464008 +O -2.9100031754 -1.1046098124 1.5495627823 +H -3.6500284868 -1.6599106809 1.2698005732 +H -3.0914794149 -0.9015297614 2.4766347434 +O 1.8424479937 1.2116204696 -0.7437950589 +H 1.6169673782 2.2321289046 -0.7484075968 +H 2.7444653600 1.0857722868 -0.4189878629 +O -0.5744319588 -1.7773916205 0.6896195293 +H -1.4696209461 -1.5874431513 1.1146694050 +H -0.0936124794 -2.4222194127 1.2263741789 +O 0.3455107583 -1.1277344535 -2.4027589620 +H -0.2029763765 -1.8640352167 -2.6975117084 +H 0.9607646175 -0.9599672169 -3.1262357038 +O -1.7133373924 0.8082897613 -0.2685614385 +H -2.4444569582 0.4883355981 0.2792913961 +H -2.0662887873 1.5066100746 -0.8311795452 +O 1.2208095990 3.6052566074 -0.8510493478 +H 1.3487092619 4.2288843903 -0.1264647458 +H 1.4276430482 4.0910210788 -1.6587359813 diff --git a/zora_so/ada_HOH.pdf b/zora_so/ada_HOH.pdf new file mode 100644 index 0000000..6e21c8f Binary files /dev/null and b/zora_so/ada_HOH.pdf differ diff --git a/zora_so/ada_HOH.png b/zora_so/ada_HOH.png new file mode 100644 index 0000000..7d8c255 Binary files /dev/null and b/zora_so/ada_HOH.png differ diff --git a/zora_so/ada_w10_H-O-H.dat b/zora_so/ada_w10_H-O-H.dat new file mode 100644 index 0000000..5e84352 --- /dev/null +++ b/zora_so/ada_w10_H-O-H.dat @@ -0,0 +1,361 @@ +# distance [Angstrom] occurrence (total=100) +0.000000 0 +1.000000 0 +2.000000 0 +3.000000 0 +4.000000 0 +5.000000 0 +6.000000 0 +7.000000 0 +8.000000 0 +9.000000 0 +10.000000 0 +11.000000 0 +12.000000 0 +13.000000 0 +14.000000 0 +15.000000 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b/zora_so/ada_w1_H-O-H.dat new file mode 100644 index 0000000..d3d85ad --- /dev/null +++ b/zora_so/ada_w1_H-O-H.dat @@ -0,0 +1,361 @@ +# distance [Angstrom] occurrence (total=68) +0.000000 0 +1.000000 0 +2.000000 0 +3.000000 0 +4.000000 0 +5.000000 0 +6.000000 0 +7.000000 0 +8.000000 0 +9.000000 0 +10.000000 0 +11.000000 0 +12.000000 0 +13.000000 0 +14.000000 0 +15.000000 0 +16.000000 0 +17.000000 0 +18.000000 0 +19.000000 0 +20.000000 0 +21.000000 0 +22.000000 0 +23.000000 0 +24.000000 0 +25.000000 0 +26.000000 0 +27.000000 0 +28.000000 0 +29.000000 0 +30.000000 0 +31.000000 0 +32.000000 0 +33.000000 0 +34.000000 0 +35.000000 0 +36.000000 0 +37.000000 0 +38.000000 0 +39.000000 0 +40.000000 0 +41.000000 0 +42.000000 0 +43.000000 0 +44.000000 0 +45.000000 0 +46.000000 0 +47.000000 0 +48.000000 0 +49.000000 0 +50.000000 0 +51.000000 0 +52.000000 0 +53.000000 0 +54.000000 0 +55.000000 0 +56.000000 0 +57.000000 0 +58.000000 0 +59.000000 0 +60.000000 0 +61.000000 0 +62.000000 0 +63.000000 0 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b/zora_so/rda_OH.pdf differ diff --git a/zora_so/rda_OH.png b/zora_so/rda_OH.png new file mode 100644 index 0000000..0964107 Binary files /dev/null and b/zora_so/rda_OH.png differ diff --git a/zora_so/rda_OO.pdf b/zora_so/rda_OO.pdf new file mode 100644 index 0000000..a15caf0 Binary files /dev/null and b/zora_so/rda_OO.pdf differ diff --git a/zora_so/rda_OO.png b/zora_so/rda_OO.png new file mode 100644 index 0000000..8590bc6 Binary files /dev/null and b/zora_so/rda_OO.png differ diff --git a/zora_so/rda_w10_O-H.dat b/zora_so/rda_w10_O-H.dat new file mode 100644 index 0000000..00d4bd9 --- /dev/null +++ b/zora_so/rda_w10_O-H.dat @@ -0,0 +1,55 @@ +# distance [Angstrom] occurrence (total=203) +0.800000 0 +0.850000 0 +0.900000 0 +0.950000 27 +1.000000 57 +1.050000 5 +1.100000 3 +1.150000 6 +1.200000 4 +1.250000 0 +1.300000 7 +1.350000 2 +1.400000 4 +1.450000 0 +1.500000 0 +1.550000 1 +1.600000 3 +1.650000 2 +1.700000 0 +1.750000 0 +1.800000 0 +1.850000 0 +1.900000 0 +1.950000 0 +2.000000 1 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26 +3.100000 31 +3.150000 24 +3.200000 7 +3.250000 11 +3.300000 10 +3.350000 3 +3.400000 7 +3.450000 5 diff --git a/zora_so/rda_w11_O-O.dat b/zora_so/rda_w11_O-O.dat new file mode 100644 index 0000000..db7c395 --- /dev/null +++ b/zora_so/rda_w11_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence (total=207) +1.500000 0 +1.600000 0 +1.700000 0 +1.800000 0 +1.900000 0 +2.000000 0 +2.100000 0 +2.200000 0 +2.300000 0 +2.400000 5 +2.500000 26 +2.600000 8 +2.700000 2 +2.800000 3 +2.900000 4 +3.000000 6 +3.100000 14 +3.200000 6 +3.300000 1 +3.400000 7 +3.500000 3 +3.600000 2 +3.700000 12 +3.800000 1 +3.900000 5 +4.000000 5 +4.100000 7 +4.200000 4 +4.300000 7 +4.400000 7 +4.500000 3 +4.600000 1 +4.700000 1 +4.800000 9 +4.900000 1 +5.000000 1 +5.100000 1 +5.200000 0 +5.300000 2 +5.400000 1 +5.500000 5 +5.600000 9 +5.700000 12 +5.800000 7 +5.900000 4 +6.000000 1 +6.100000 3 +6.200000 1 +6.300000 2 +6.400000 2 +6.500000 1 +6.600000 0 +6.700000 1 +6.800000 2 +6.900000 2 diff --git a/zora_so/rda_w1_Hg-O-H-H.dat b/zora_so/rda_w1_Hg-O-H-H.dat new file mode 100644 index 0000000..5ccdc23 --- /dev/null +++ b/zora_so/rda_w1_Hg-O-H-H.dat @@ -0,0 +1,301 @@ +# distance [Angstrom] occurrence (total=0) +1.000000 0 +1.010033 0 +1.020067 0 +1.030100 0 +1.040134 0 +1.050167 0 +1.060201 0 +1.070234 0 +1.080268 0 +1.090301 0 +1.100334 0 +1.110368 0 +1.120401 0 +1.130435 0 +1.140468 0 +1.150502 0 +1.160535 0 +1.170569 0 +1.180602 0 +1.190635 0 +1.200669 0 +1.210702 0 +1.220736 0 +1.230769 0 +1.240803 0 +1.250836 0 +1.260870 0 +1.270903 0 +1.280936 0 +1.290970 0 +1.301003 0 +1.311037 0 +1.321070 0 +1.331104 0 +1.341137 0 +1.351171 0 +1.361204 0 +1.371237 0 +1.381271 0 +1.391304 0 +1.401338 0 +1.411371 0 +1.421405 0 +1.431438 0 +1.441472 0 +1.451505 0 +1.461538 0 +1.471572 0 +1.481605 0 +1.491639 0 +1.501672 0 +1.511706 0 +1.521739 0 +1.531773 0 +1.541806 0 +1.551839 0 +1.561873 0 +1.571906 0 +1.581940 0 +1.591973 0 +1.602007 0 +1.612040 0 +1.622074 0 +1.632107 0 +1.642140 0 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distance [Angstrom] occurrence (total=1) +1.500000 0 +1.505000 0 +1.510000 0 +1.515000 0 +1.520000 0 +1.525000 0 +1.530000 0 +1.535000 0 +1.540000 0 +1.545000 0 +1.550000 0 +1.555000 0 +1.560000 0 +1.565000 0 +1.570000 0 +1.575000 0 +1.580000 0 +1.585000 0 +1.590000 0 +1.595000 0 +1.600000 0 +1.605000 0 +1.610000 0 +1.615000 0 +1.620000 0 +1.625000 0 +1.630000 0 +1.635000 0 +1.640000 0 +1.645000 0 +1.650000 0 +1.655000 0 +1.660000 0 +1.665000 0 +1.670000 0 +1.675000 0 +1.680000 0 +1.685000 0 +1.690000 0 +1.695000 0 +1.700000 0 +1.705000 0 +1.710000 0 +1.715000 0 +1.720000 0 +1.725000 0 +1.730000 0 +1.735000 0 +1.740000 0 +1.745000 0 +1.750000 0 +1.755000 0 +1.760000 0 +1.765000 0 +1.770000 0 +1.775000 0 +1.780000 0 +1.785000 0 +1.790000 0 +1.795000 0 +1.800000 0 +1.805000 0 +1.810000 0 +1.815000 0 +1.820000 0 +1.825000 0 +1.830000 0 +1.835000 0 +1.840000 0 +1.845000 0 +1.850000 0 +1.855000 0 +1.860000 0 +1.865000 0 +1.870000 0 +1.875000 0 +1.880000 0 +1.885000 0 +1.890000 0 +1.895000 0 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file mode 100644 index 0000000..5daf8f7 --- /dev/null +++ b/zora_so/rda_w2_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence (total=48) +1.500000 0 +1.600000 0 +1.700000 0 +1.800000 0 +1.900000 0 +2.000000 0 +2.100000 0 +2.200000 0 +2.300000 0 +2.400000 0 +2.500000 0 +2.600000 0 +2.700000 9 +2.800000 11 +2.900000 9 +3.000000 4 +3.100000 0 +3.200000 0 +3.300000 0 +3.400000 0 +3.500000 0 +3.600000 0 +3.700000 0 +3.800000 0 +3.900000 7 +4.000000 1 +4.100000 0 +4.200000 0 +4.300000 0 +4.400000 0 +4.500000 0 +4.600000 1 +4.700000 0 +4.800000 2 +4.900000 0 +5.000000 1 +5.100000 1 +5.200000 2 +5.300000 0 +5.400000 0 +5.500000 0 +5.600000 0 +5.700000 0 +5.800000 0 +5.900000 0 +6.000000 0 +6.100000 0 +6.200000 0 +6.300000 0 +6.400000 0 +6.500000 0 +6.600000 0 +6.700000 0 +6.800000 0 +6.900000 0 diff --git a/zora_so/rda_w3_Hg-O-H-H.dat b/zora_so/rda_w3_Hg-O-H-H.dat new file mode 100644 index 0000000..99ba29a --- /dev/null +++ b/zora_so/rda_w3_Hg-O-H-H.dat @@ -0,0 +1,301 @@ +# distance 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0000000..4359574 --- /dev/null +++ b/zora_so/rda_w4_O-H.dat @@ -0,0 +1,55 @@ +# distance [Angstrom] occurrence (total=953) +0.800000 0 +0.850000 0 +0.900000 0 +0.950000 221 +1.000000 67 +1.050000 0 +1.100000 0 +1.150000 0 +1.200000 0 +1.250000 0 +1.300000 0 +1.350000 0 +1.400000 0 +1.450000 0 +1.500000 0 +1.550000 0 +1.600000 0 +1.650000 2 +1.700000 12 +1.750000 40 +1.800000 13 +1.850000 14 +1.900000 27 +1.950000 26 +2.000000 15 +2.050000 10 +2.100000 6 +2.150000 2 +2.200000 3 +2.250000 0 +2.300000 1 +2.350000 0 +2.400000 1 +2.450000 1 +2.500000 1 +2.550000 0 +2.600000 1 +2.650000 1 +2.700000 4 +2.750000 2 +2.800000 19 +2.850000 16 +2.900000 19 +2.950000 10 +3.000000 16 +3.050000 30 +3.100000 47 +3.150000 54 +3.200000 37 +3.250000 36 +3.300000 56 +3.350000 50 +3.400000 49 +3.450000 44 diff --git a/zora_so/rda_w4_O-O.dat b/zora_so/rda_w4_O-O.dat new file mode 100644 index 0000000..494d15e --- /dev/null +++ b/zora_so/rda_w4_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence 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@@ -0,0 +1,55 @@ +# distance [Angstrom] occurrence (total=2) +0.800000 0 +0.850000 0 +0.900000 0 +0.950000 0 +1.000000 2 +1.050000 0 +1.100000 0 +1.150000 0 +1.200000 0 +1.250000 0 +1.300000 0 +1.350000 0 +1.400000 0 +1.450000 0 +1.500000 0 +1.550000 0 +1.600000 0 +1.650000 0 +1.700000 0 +1.750000 0 +1.800000 0 +1.850000 0 +1.900000 0 +1.950000 0 +2.000000 0 +2.050000 0 +2.100000 0 +2.150000 0 +2.200000 0 +2.250000 0 +2.300000 0 +2.350000 0 +2.400000 0 +2.450000 0 +2.500000 0 +2.550000 0 +2.600000 0 +2.650000 0 +2.700000 0 +2.750000 0 +2.800000 0 +2.850000 0 +2.900000 0 +2.950000 0 +3.000000 0 +3.050000 0 +3.100000 0 +3.150000 0 +3.200000 0 +3.250000 0 +3.300000 0 +3.350000 0 +3.400000 0 +3.450000 0 diff --git a/zora_so/rda_w6_O-O.dat b/zora_so/rda_w6_O-O.dat new file mode 100644 index 0000000..9a89722 --- /dev/null +++ b/zora_so/rda_w6_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence (total=0) +1.500000 0 +1.600000 0 +1.700000 0 +1.800000 0 +1.900000 0 +2.000000 0 +2.100000 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0 +2.750000 0 +2.800000 1 +2.850000 0 +2.900000 0 +2.950000 0 +3.000000 0 +3.050000 6 +3.100000 1 +3.150000 0 +3.200000 0 +3.250000 0 +3.300000 1 +3.350000 0 +3.400000 0 +3.450000 0 diff --git a/zora_so/rda_w8_O-O.dat b/zora_so/rda_w8_O-O.dat new file mode 100644 index 0000000..cdaeacb --- /dev/null +++ b/zora_so/rda_w8_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence (total=9) +1.500000 0 +1.600000 0 +1.700000 0 +1.800000 0 +1.900000 0 +2.000000 0 +2.100000 0 +2.200000 0 +2.300000 0 +2.400000 1 +2.500000 2 +2.600000 0 +2.700000 0 +2.800000 0 +2.900000 0 +3.000000 1 +3.100000 0 +3.200000 0 +3.300000 0 +3.400000 0 +3.500000 0 +3.600000 0 +3.700000 0 +3.800000 0 +3.900000 1 +4.000000 0 +4.100000 1 +4.200000 1 +4.300000 0 +4.400000 0 +4.500000 1 +4.600000 0 +4.700000 0 +4.800000 0 +4.900000 0 +5.000000 0 +5.100000 0 +5.200000 0 +5.300000 0 +5.400000 0 +5.500000 0 +5.600000 0 +5.700000 0 +5.800000 0 +5.900000 0 +6.000000 1 +6.100000 0 +6.200000 0 +6.300000 0 +6.400000 0 +6.500000 0 +6.600000 0 +6.700000 0 +6.800000 0 +6.900000 0 diff --git a/zora_so/rda_w9_O-H.dat b/zora_so/rda_w9_O-H.dat new file mode 100644 index 0000000..42e0904 --- /dev/null +++ b/zora_so/rda_w9_O-H.dat @@ -0,0 +1,55 @@ +# distance [Angstrom] occurrence (total=58) +0.800000 0 +0.850000 0 +0.900000 0 +0.950000 3 +1.000000 24 +1.050000 0 +1.100000 2 +1.150000 2 +1.200000 2 +1.250000 2 +1.300000 0 +1.350000 2 +1.400000 0 +1.450000 0 +1.500000 0 +1.550000 0 +1.600000 0 +1.650000 0 +1.700000 0 +1.750000 0 +1.800000 0 +1.850000 1 +1.900000 0 +1.950000 0 +2.000000 0 +2.050000 0 +2.100000 0 +2.150000 0 +2.200000 0 +2.250000 0 +2.300000 0 +2.350000 0 +2.400000 0 +2.450000 0 +2.500000 0 +2.550000 0 +2.600000 0 +2.650000 0 +2.700000 0 +2.750000 0 +2.800000 0 +2.850000 0 +2.900000 0 +2.950000 1 +3.000000 11 +3.050000 3 +3.100000 0 +3.150000 1 +3.200000 1 +3.250000 1 +3.300000 0 +3.350000 0 +3.400000 1 +3.450000 1 diff --git a/zora_so/rda_w9_O-O.dat b/zora_so/rda_w9_O-O.dat new file mode 100644 index 0000000..2b5d7aa --- /dev/null +++ b/zora_so/rda_w9_O-O.dat @@ -0,0 +1,56 @@ +# distance [Angstrom] occurrence (total=22) +1.500000 0 +1.600000 0 +1.700000 0 +1.800000 0 +1.900000 0 +2.000000 0 +2.100000 0 +2.200000 0 +2.300000 0 +2.400000 5 +2.500000 0 +2.600000 0 +2.700000 0 +2.800000 1 +2.900000 0 +3.000000 0 +3.100000 0 +3.200000 1 +3.300000 0 +3.400000 0 +3.500000 3 +3.600000 0 +3.700000 0 +3.800000 0 +3.900000 0 +4.000000 1 +4.100000 3 +4.200000 1 +4.300000 1 +4.400000 0 +4.500000 0 +4.600000 1 +4.700000 0 +4.800000 0 +4.900000 0 +5.000000 0 +5.100000 0 +5.200000 0 +5.300000 0 +5.400000 0 +5.500000 0 +5.600000 1 +5.700000 1 +5.800000 2 +5.900000 0 +6.000000 0 +6.100000 0 +6.200000 0 +6.300000 0 +6.400000 1 +6.500000 0 +6.600000 0 +6.700000 0 +6.800000 0 +6.900000 0 diff --git a/zora_so/stern_limbach.pdf b/zora_so/stern_limbach.pdf new file mode 100644 index 0000000..0eba48c Binary files /dev/null and b/zora_so/stern_limbach.pdf differ diff --git a/zora_so/stern_limbach.png b/zora_so/stern_limbach.png new file mode 100644 index 0000000..23a8128 Binary files /dev/null and b/zora_so/stern_limbach.png differ diff --git a/zora_so/tda_HgOHH.pdf b/zora_so/tda_HgOHH.pdf new file mode 100644 index 0000000..ae83847 Binary files /dev/null and b/zora_so/tda_HgOHH.pdf differ diff --git a/zora_so/tda_HgOHH.png b/zora_so/tda_HgOHH.png new file mode 100644 index 0000000..caba499 Binary files /dev/null and b/zora_so/tda_HgOHH.png differ diff --git a/zora_so/tda_all_HgOHH.pdf b/zora_so/tda_all_HgOHH.pdf new file mode 100644 index 0000000..598e026 Binary files /dev/null and b/zora_so/tda_all_HgOHH.pdf differ diff --git a/zora_so/tda_w10_Hg-O-H-H.dat b/zora_so/tda_w10_Hg-O-H-H.dat new file mode 100644 index 0000000..4072251 --- /dev/null +++ b/zora_so/tda_w10_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# distance [Angstrom] occurrence (total=106) +0.000000 0 +5.000000 0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 +45.000000 0 +50.000000 0 +55.000000 0 +60.000000 0 +65.000000 0 +70.000000 1 +75.000000 0 +80.000000 3 +85.000000 0 +90.000000 0 +95.000000 0 +100.000000 0 +105.000000 0 +110.000000 0 +115.000000 0 +120.000000 0 +125.000000 1 +130.000000 4 +135.000000 28 +140.000000 27 +145.000000 12 +150.000000 9 +155.000000 4 +160.000000 4 +165.000000 2 +170.000000 1 +175.000000 6 +180.000000 4 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 +250.000000 0 +255.000000 0 +260.000000 0 +265.000000 0 +270.000000 0 +275.000000 0 +280.000000 0 +285.000000 0 +290.000000 0 +295.000000 0 +300.000000 0 +305.000000 0 +310.000000 0 +315.000000 0 +320.000000 0 +325.000000 0 +330.000000 0 +335.000000 0 +340.000000 0 +345.000000 0 +350.000000 0 +355.000000 0 diff --git a/zora_so/tda_w1_Hg-O-H-H.dat b/zora_so/tda_w1_Hg-O-H-H.dat new file mode 100644 index 0000000..c1ca22e --- /dev/null +++ b/zora_so/tda_w1_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# distance [Angstrom] occurrence (total=127) +0.000000 0 +5.000000 0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 +45.000000 0 +50.000000 0 +55.000000 0 +60.000000 0 +65.000000 0 +70.000000 2 +75.000000 2 +80.000000 0 +85.000000 0 +90.000000 0 +95.000000 0 +100.000000 0 +105.000000 0 +110.000000 0 +115.000000 0 +120.000000 0 +125.000000 0 +130.000000 0 +135.000000 0 +140.000000 0 +145.000000 0 +150.000000 0 +155.000000 0 +160.000000 2 +165.000000 11 +170.000000 22 +175.000000 21 +180.000000 67 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 +250.000000 0 +255.000000 0 +260.000000 0 +265.000000 0 +270.000000 0 +275.000000 0 +280.000000 0 +285.000000 0 +290.000000 0 +295.000000 0 +300.000000 0 +305.000000 0 +310.000000 0 +315.000000 0 +320.000000 0 +325.000000 0 +330.000000 0 +335.000000 0 +340.000000 0 +345.000000 0 +350.000000 0 +355.000000 0 diff --git a/zora_so/tda_w2_Hg-O-H-H.dat b/zora_so/tda_w2_Hg-O-H-H.dat new file mode 100644 index 0000000..6f34343 --- /dev/null +++ b/zora_so/tda_w2_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# distance [Angstrom] occurrence (total=134) +0.000000 0 +5.000000 0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 +45.000000 0 +50.000000 0 +55.000000 0 +60.000000 0 +65.000000 0 +70.000000 2 +75.000000 3 +80.000000 2 +85.000000 1 +90.000000 0 +95.000000 0 +100.000000 0 +105.000000 0 +110.000000 0 +115.000000 4 +120.000000 2 +125.000000 0 +130.000000 2 +135.000000 0 +140.000000 9 +145.000000 25 +150.000000 21 +155.000000 18 +160.000000 11 +165.000000 2 +170.000000 3 +175.000000 9 +180.000000 20 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 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0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 +45.000000 0 +50.000000 0 +55.000000 0 +60.000000 0 +65.000000 0 +70.000000 0 +75.000000 0 +80.000000 0 +85.000000 0 +90.000000 0 +95.000000 0 +100.000000 0 +105.000000 0 +110.000000 0 +115.000000 0 +120.000000 0 +125.000000 0 +130.000000 0 +135.000000 0 +140.000000 0 +145.000000 0 +150.000000 0 +155.000000 0 +160.000000 0 +165.000000 0 +170.000000 0 +175.000000 0 +180.000000 0 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 +250.000000 0 +255.000000 0 +260.000000 0 +265.000000 0 +270.000000 0 +275.000000 0 +280.000000 0 +285.000000 0 +290.000000 0 +295.000000 0 +300.000000 0 +305.000000 0 +310.000000 0 +315.000000 0 +320.000000 0 +325.000000 0 +330.000000 0 +335.000000 0 +340.000000 0 +345.000000 0 +350.000000 0 +355.000000 0 diff --git a/zora_so/tda_w6_Hg-O-H-H.dat b/zora_so/tda_w6_Hg-O-H-H.dat new file mode 100644 index 0000000..719fdf7 --- /dev/null +++ b/zora_so/tda_w6_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# distance [Angstrom] occurrence (total=139) +0.000000 0 +5.000000 0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 +45.000000 0 +50.000000 0 +55.000000 0 +60.000000 0 +65.000000 0 +70.000000 0 +75.000000 1 +80.000000 0 +85.000000 1 +90.000000 0 +95.000000 0 +100.000000 0 +105.000000 0 +110.000000 1 +115.000000 1 +120.000000 4 +125.000000 0 +130.000000 0 +135.000000 2 +140.000000 2 +145.000000 11 +150.000000 26 +155.000000 18 +160.000000 23 +165.000000 11 +170.000000 4 +175.000000 11 +180.000000 23 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 +250.000000 0 +255.000000 0 +260.000000 0 +265.000000 0 +270.000000 0 +275.000000 0 +280.000000 0 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1 +130.000000 2 +135.000000 4 +140.000000 12 +145.000000 13 +150.000000 28 +155.000000 25 +160.000000 6 +165.000000 3 +170.000000 6 +175.000000 11 +180.000000 21 +185.000000 0 +190.000000 0 +195.000000 0 +200.000000 0 +205.000000 0 +210.000000 0 +215.000000 0 +220.000000 0 +225.000000 0 +230.000000 0 +235.000000 0 +240.000000 0 +245.000000 0 +250.000000 0 +255.000000 0 +260.000000 0 +265.000000 0 +270.000000 0 +275.000000 0 +280.000000 0 +285.000000 0 +290.000000 0 +295.000000 0 +300.000000 0 +305.000000 0 +310.000000 0 +315.000000 0 +320.000000 0 +325.000000 0 +330.000000 0 +335.000000 0 +340.000000 0 +345.000000 0 +350.000000 0 +355.000000 0 diff --git a/zora_so/tda_w9_Hg-O-H-H.dat b/zora_so/tda_w9_Hg-O-H-H.dat new file mode 100644 index 0000000..ba0e699 --- /dev/null +++ b/zora_so/tda_w9_Hg-O-H-H.dat @@ -0,0 +1,73 @@ +# distance [Angstrom] occurrence (total=123) +0.000000 0 +5.000000 0 +10.000000 0 +15.000000 0 +20.000000 0 +25.000000 0 +30.000000 0 +35.000000 0 +40.000000 0 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b/zora_so/w1s1.xyz @@ -0,0 +1,6 @@ + 4 + file 'w1s1.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg -0.2251300000 0.0107390000 0.0000000000 +O 1.8213760000 -0.0901650000 0.0000000000 +H 2.3259450000 0.1873100000 0.7989200000 +H 2.3259450000 0.1773100000 -0.7989200000 diff --git a/zora_so/w2s1.xyz b/zora_so/w2s1.xyz new file mode 100644 index 0000000..5cbd12b --- /dev/null +++ b/zora_so/w2s1.xyz @@ -0,0 +1,9 @@ + 7 + file 'w2s1.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg -0.0000820000 -0.0296160000 -0.0018480000 +O 2.0546720000 -0.1159470000 0.1064340000 +H 2.5364260000 0.6527930000 0.4948150000 +H 2.5507250000 -0.4346440000 -0.6848940000 +O -2.0547980000 -0.1063180000 -0.1170750000 +H -2.5369900000 0.6942780000 -0.4339670000 +H -2.5506540000 -0.4959780000 0.6419550000 diff --git a/zora_so/w3s1.xyz b/zora_so/w3s1.xyz new file mode 100644 index 0000000..80aba07 --- /dev/null +++ b/zora_so/w3s1.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s1.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg 0.3853730000 -0.0371550000 -0.0008240000 +O 2.3228030000 0.7122120000 -0.0009910000 +H 2.8789870000 0.5674450000 -0.7973290000 +H 2.8796850000 0.5663170000 0.7948180000 +O -1.5127800000 -0.6135700000 -0.0008690000 +H -2.7829260000 0.0695480000 -0.0002290000 +H -1.5589480000 -1.5903180000 0.0073290000 +O -3.6982830000 0.6223500000 0.0001830000 +H -4.2448430000 0.4911410000 -0.8052110000 +H -4.2478820000 0.4840660000 0.8020850000 diff --git a/zora_so/w3s2.xyz b/zora_so/w3s2.xyz new file mode 100644 index 0000000..56c20a9 --- /dev/null +++ b/zora_so/w3s2.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s2.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg 0.1148120000 0.0121730000 0.0104540000 +O -1.8094020000 -0.9457350000 0.2034290000 +H -1.8983550000 -1.9067870000 0.0254080000 +H -2.5626460000 -0.4866200000 -0.2264420000 +O 2.2355420000 0.1188530000 -0.1586150000 +H 2.7330140000 -0.7272110000 -0.2047960000 +H 2.7201160000 0.7150920000 0.4533980000 +O -1.1939500000 1.9493440000 -0.0741990000 +H -1.0422640000 2.6101640000 -0.7804870000 +H -1.3593890000 2.4617640000 0.7429250000 diff --git a/zora_so/w3s3.xyz b/zora_so/w3s3.xyz new file mode 100644 index 0000000..83fc06f --- /dev/null +++ b/zora_so/w3s3.xyz @@ -0,0 +1,12 @@ + 10 + file 'w3s3.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +Hg -0.6948470000 -0.3997160000 0.0004810000 +O 1.3035710000 2.6479640000 -0.0010920000 +H 1.6496690000 3.1073690000 0.7888160000 +H 1.6587450000 3.1063570000 -0.7872590000 +O 1.2049240000 0.2053020000 -0.0001690000 +H 2.2323150000 -0.7151560000 0.0002380000 +H 1.2685510000 1.3331090000 -0.0005610000 +O 3.0068120000 -1.4937750000 -0.0003070000 +H 3.5716870000 -1.5151740000 -0.8023100000 +H 3.5710710000 -1.5165500000 0.8022210000 diff --git a/zora_so/w4s1.xyz b/zora_so/w4s1.xyz new file mode 100644 index 0000000..a927688 --- /dev/null +++ b/zora_so/w4s1.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s1.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +H 3.5396510000 -2.9049890000 -0.0530600000 +O 3.2518570000 -2.1152200000 0.4472350000 +H 4.0453230000 -1.6518670000 0.7825610000 +H -3.2654820000 -0.1520870000 0.0230690000 +O -2.1564230000 0.0800040000 0.5763100000 +H -2.1919490000 0.7478560000 1.2865240000 +H -4.7831890000 0.3340060000 -0.8519400000 +O -4.2647160000 -0.4228340000 -0.5127100000 +H -4.8625850000 -1.0096730000 -0.0077130000 +H 1.8810930000 -0.1786660000 -1.3622400000 +O 1.5624710000 -0.7632460000 -0.6491910000 +H 2.4650210000 -1.4453690000 -0.0923430000 +Hg -0.2861690000 -0.2936260000 -0.0366180000 diff --git a/zora_so/w4s2.xyz b/zora_so/w4s2.xyz new file mode 100644 index 0000000..b377069 --- /dev/null +++ b/zora_so/w4s2.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s2.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +H 4.5625570000 1.3068870000 -0.4203830000 +O 4.1363750000 0.6988970000 0.2141210000 +H 4.8358420000 0.2079860000 0.6854120000 +H -0.2985180000 -0.8487080000 1.5482970000 +O -0.2928250000 -0.5011440000 0.6341300000 +H 1.3795910000 -0.4808960000 -0.1686180000 +H -4.5012960000 1.2672830000 -0.0353090000 +O -4.0581150000 0.5140650000 -0.4796320000 +H -4.7230860000 -0.1944840000 -0.6108900000 +H 3.2076660000 0.0586110000 -0.2201940000 +O 2.2260350000 -0.4889480000 -0.6838570000 +H 2.3742770000 -1.3805100000 -1.0481900000 +Hg -2.1474320000 -0.0361800000 0.1788730000 diff --git a/zora_so/w4s3.xyz b/zora_so/w4s3.xyz new file mode 100644 index 0000000..6f5d3df --- /dev/null +++ b/zora_so/w4s3.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s3.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +H 3.8244450000 0.1052760000 -0.6671970000 +O 3.3000850000 -0.1682550000 0.1159550000 +H 3.7542360000 0.1591060000 0.9217980000 +H -1.2753850000 0.9492840000 0.0051640000 +O -0.7438650000 -0.0177580000 -0.1260900000 +H -1.2996420000 -0.9770950000 0.0052910000 +H -2.3942160000 2.3743580000 0.8739900000 +O -1.8610750000 2.1495050000 0.0893970000 +H -2.3401500000 2.4841500000 -0.6912480000 +H -2.4408890000 -2.3739460000 0.8724520000 +O -1.9039360000 -2.1586370000 0.0876680000 +H -2.3878120000 -2.4840810000 -0.6940310000 +Hg 1.2226450000 -0.0428320000 0.0163660000 diff --git a/zora_so/w4s4.xyz b/zora_so/w4s4.xyz new file mode 100644 index 0000000..af84fe9 --- /dev/null +++ b/zora_so/w4s4.xyz @@ -0,0 +1,15 @@ + 13 + file 'w4s4.out' was gotten at: ---' ZORA-SR+SO PBE/QZ4P'--- +H 1.4311260000 -0.3660160000 -2.4942740000 +O 1.6257780000 -0.1558080000 -1.5596580000 +H 2.4062740000 -0.6883760000 -1.3097490000 +H -2.7029760000 -0.8714940000 0.4800430000 +O -2.2639200000 -0.2201690000 -0.1034920000 +H -2.6915810000 -0.2981570000 -0.9801470000 +H 1.2439850000 -1.9181560000 1.8278810000 +O 1.4171250000 -1.0198380000 1.4834990000 +H 1.7086610000 -0.4870750000 2.2494140000 +H -0.5796220000 2.6811920000 0.9906980000 +O 0.1993960000 2.1756070000 0.6883010000 +H 0.7380630000 2.7950870000 0.1596770000 +Hg -0.0421610000 -0.0309230000 -0.0185030000 diff --git a/zora_so/w5s1.xyz b/zora_so/w5s1.xyz new file mode 100644 index 0000000..f1ed413 --- /dev/null +++ b/zora_so/w5s1.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s1.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg 1.0562150000 -0.2822650000 0.2375320000 +H -3.1353680000 1.7717150000 -0.5229050000 +O -3.0057620000 0.8057900000 -0.5221760000 +H -3.9590700000 0.2223930000 -0.2991650000 +H 3.0909700000 -1.7363060000 -0.4417570000 +O 2.9018250000 -0.7797260000 -0.4531800000 +H 3.8400120000 -0.1628180000 -0.2875520000 +H -5.4356260000 -0.8892400000 -0.9012940000 +O -5.0013360000 -0.5267200000 -0.1070090000 +H -5.7018080000 -0.2200990000 0.4971060000 +H -0.8251720000 0.2233020000 1.7490020000 +O -0.7739790000 0.2317010000 0.7748580000 +H -2.1748710000 0.5664950000 0.0065380000 +H 5.3366560000 0.8744790000 -0.9697480000 +O 4.8699180000 0.6216510000 -0.1512130000 +H 5.5475380000 0.3853370000 0.5091720000 diff --git a/zora_so/w5s10.xyz b/zora_so/w5s10.xyz new file mode 100644 index 0000000..dda1cae --- /dev/null +++ b/zora_so/w5s10.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s10.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg -0.4060510000 -0.4226200000 -0.2999460000 +O 3.1700540000 0.8922460000 -0.5139400000 +H 3.7030190000 1.2775370000 0.2077530000 +H 3.7049260000 1.0224690000 -1.3203280000 +O -1.6820250000 -0.8223190000 1.6931320000 +H -2.1959480000 -0.0935720000 2.0907700000 +H -1.2468790000 -1.2723790000 2.4424900000 +O 0.6394160000 1.4756630000 -0.4128860000 +H 1.6530410000 1.3629800000 -0.5379560000 +H 0.3054440000 2.1398710000 -1.0454900000 +O 1.6708440000 -1.4783340000 0.0709550000 +H 1.8650500000 -2.3878740000 -0.2194270000 +H 2.4461670000 -0.9184090000 -0.1622170000 +O -1.7944820000 -2.0191460000 -0.9784410000 +H -2.1708830000 -1.9987300000 -1.8803560000 +H -2.5343820000 -2.1693870000 -0.3565550000 diff --git a/zora_so/w5s2.xyz b/zora_so/w5s2.xyz new file mode 100644 index 0000000..8f62f9a --- /dev/null +++ b/zora_so/w5s2.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s2.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg 1.0297340000 0.4773970000 0.4104120000 +H -5.6041210000 -0.8398950000 0.4723470000 +O -4.8986630000 -0.7385760000 -0.1922090000 +H -5.3109660000 -0.8116960000 -1.0727490000 +H 3.3790120000 1.4676350000 -0.0520320000 +O 2.9014090000 0.6743110000 -0.3574410000 +H 3.6063670000 -0.1879030000 -0.5569680000 +H -4.0153080000 0.1989370000 -0.0372360000 +O -3.1902520000 0.9837650000 0.0173880000 +H -3.4870930000 1.8306880000 0.3973940000 +H 4.6699840000 -1.2811370000 -1.7700780000 +O 4.3485200000 -1.2227780000 -0.8509540000 +H 5.1001600000 -1.4341710000 -0.2669500000 +H -2.3065350000 0.7062040000 0.4297530000 +O -0.8408490000 0.3135040000 1.0241570000 +H -0.8388400000 -0.0221870000 1.9402390000 diff --git a/zora_so/w5s3.xyz b/zora_so/w5s3.xyz new file mode 100644 index 0000000..2a57649 --- /dev/null +++ b/zora_so/w5s3.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s3.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg 0.3675190000 -2.3898130000 1.2354400000 +O 1.8670080000 -3.4092530000 0.3613590000 +H 2.0285050000 -3.6716950000 -0.8005000000 +H 2.3375800000 -4.0112150000 0.9671050000 +O -1.1118800000 -1.3120070000 2.0205930000 +H -0.8560150000 -0.3780780000 2.4830710000 +H -1.9385900000 -1.8377090000 2.4562350000 +O -3.0394610000 -2.5981240000 2.9156620000 +H -3.1984400000 -2.7281950000 3.8672380000 +H -3.9100440000 -2.4452080000 2.5067730000 +O -0.4652100000 0.8892260000 2.9690430000 +H -0.8659160000 1.6823170000 2.5705120000 +H -0.3907000000 1.0640860000 3.9237640000 +O 2.1978160000 -3.8584140000 -1.9928230000 +H 2.0829430000 -4.7732560000 -2.3169930000 +H 3.0309480000 -3.5057340000 -2.3630200000 diff --git a/zora_so/w5s4.xyz b/zora_so/w5s4.xyz new file mode 100644 index 0000000..2d10a14 --- /dev/null +++ b/zora_so/w5s4.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s4.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg -0.6361500000 1.2348580000 1.4466370000 +O 1.2168890000 0.5102940000 1.5293730000 +H 1.8839660000 0.7431650000 0.7234110000 +H 1.3585440000 -0.4478170000 1.9914570000 +O -2.4957830000 2.0052900000 1.4683850000 +H -2.9015630000 3.0143410000 1.9926860000 +H -3.0639240000 1.6840200000 0.7442220000 +O 1.4815050000 -1.6575340000 2.7103300000 +H 2.0498930000 -1.6715950000 3.5009570000 +H 1.6213620000 -2.5045800000 2.2514720000 +O -3.2879010000 3.9976870000 2.5887770000 +H -3.5394710000 4.7691770000 2.0446520000 +H -3.9956770000 3.8433270000 3.2447110000 +O 2.7351230000 1.1796720000 -0.3196380000 +H 3.5342630000 1.6843370000 -0.0849280000 +H 2.9866930000 0.5830820000 -1.0465680000 diff --git a/zora_so/w5s5.xyz b/zora_so/w5s5.xyz new file mode 100644 index 0000000..102a4c9 --- /dev/null +++ b/zora_so/w5s5.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s5.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg -0.7932790000 -2.6985490000 0.7784960000 +O 0.6336470000 -3.9479960000 2.4205620000 +H 1.1676280000 -4.7335180000 2.2097050000 +H 1.0454620000 -3.5549270000 3.2098920000 +O -2.2882790000 -2.6904390000 2.1784770000 +H -2.7253790000 -3.6404740000 2.6388110000 +H -2.9919470000 -2.0418800000 1.9884150000 +O -3.1539230000 -4.7174400000 3.2150360000 +H -4.0137760000 -5.0794910000 2.9299030000 +H -3.1523320000 -4.7113170000 4.1906700000 +O 0.5740140000 -2.6185240000 -0.7471580000 +H 0.1579060000 -2.6283460000 -1.6298790000 +H 1.4822170000 -1.9314660000 -0.7466550000 +O 2.5728560000 -1.2257670000 -0.6984350000 +H 3.3949770000 -1.6812040000 -0.9605540000 +H 2.5788210000 -0.3491320000 -1.1264230000 diff --git a/zora_so/w5s6.xyz b/zora_so/w5s6.xyz new file mode 100644 index 0000000..7961573 --- /dev/null +++ b/zora_so/w5s6.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s6.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg 1.8287640000 -1.3704280000 -0.7171760000 +O -2.1652150000 -0.4749130000 -1.1045530000 +H -2.5531260000 -0.7233860000 -1.9629900000 +H -2.9363080000 -0.3202800000 -0.3003660000 +O -3.7731530000 -0.0544560000 0.6840900000 +H -4.6011040000 -0.5621100000 0.7591490000 +H -3.9924190000 0.8826590000 0.8381050000 +O 0.1172570000 -4.4225990000 -0.0172590000 +H -0.1204660000 -4.7709680000 0.8587740000 +H -0.0926840000 -5.1321320000 -0.6482120000 +O -0.0479630000 -1.9056480000 -0.6226120000 +H -0.0623030000 -2.9020390000 -0.3840290000 +H -1.3617700000 -1.0696690000 -0.8878110000 +O 3.8000760000 -0.6519520000 -0.8510520000 +H 4.3641870000 -0.9842430000 -1.5796370000 +H 4.3411160000 -0.6338950000 -0.0348680000 diff --git a/zora_so/w5s7.xyz b/zora_so/w5s7.xyz new file mode 100644 index 0000000..d91c3c3 --- /dev/null +++ b/zora_so/w5s7.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s7.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg 0.6406590000 0.1886130000 0.4733100000 +O -0.7931060000 1.0970070000 -1.2263460000 +H -1.7567070000 1.0122560000 -1.0988570000 +H -0.6507530000 1.9964440000 -1.5762870000 +O 0.8641260000 -1.4727020000 -1.1556970000 +H 1.6972660000 -1.9694900000 -1.2648650000 +H 0.5971920000 -1.1853150000 -2.0502210000 +O 4.3586040000 1.0385300000 1.6681010000 +H 4.7372750000 0.7498000000 2.5188110000 +H 4.9524370000 1.7289360000 1.3189540000 +O 1.9582510000 1.5229550000 1.4459050000 +H 3.0254100000 1.2982420000 1.5983990000 +H 1.5852580000 1.9256740000 2.2522000000 +O -1.1941980000 -1.1377420000 0.9402290000 +H -1.5383500000 -1.2182270000 1.8505630000 +H -1.1379870000 -2.0451200000 0.5835180000 diff --git a/zora_so/w5s8.xyz b/zora_so/w5s8.xyz new file mode 100644 index 0000000..47fb29c --- /dev/null +++ b/zora_so/w5s8.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s8.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg -0.0980720000 0.1009200000 -0.0137840000 +H -0.8386460000 2.9091250000 -0.3714040000 +O -0.1441900000 2.4106530000 0.1000130000 +H 0.6845580000 2.9107030000 -0.0284910000 +H 2.9160550000 -0.0312550000 -0.1381750000 +O 2.1713230000 -0.1837960000 -0.7490790000 +H 2.4918430000 0.0705850000 -1.6341140000 +H -0.0857990000 0.7895940000 2.8902700000 +O 0.2331610000 0.0658790000 2.3202950000 +H 0.1018880000 -0.7576660000 2.8248100000 +H -3.0739710000 0.0552920000 -0.5461180000 +O -2.2503860000 -0.1537400000 -1.0253390000 +H -2.4220740000 0.0550150000 -1.9622930000 +H -0.8609840000 -2.6426320000 -0.4656240000 +O -0.0895720000 -2.2030700000 -0.0593130000 +H 0.7052180000 -2.6223120000 -0.4416530000 diff --git a/zora_so/w5s9.xyz b/zora_so/w5s9.xyz new file mode 100644 index 0000000..23294bc --- /dev/null +++ b/zora_so/w5s9.xyz @@ -0,0 +1,18 @@ + 16 + file 'w5s9.log' was gotten at: ---' #p ZORA-SR+SO PBE QZ4P'--- +Hg -0.4622400000 -0.1859290000 -0.0769840000 +O 2.9031100000 -2.0956700000 0.1756160000 +H 3.4080130000 -2.4826050000 -0.5630280000 +H 3.4666130000 -2.1601380000 0.9675830000 +O 1.5547800000 -0.1080590000 -0.3502370000 +H 1.9216860000 0.8219930000 -0.1366950000 +H 2.1934110000 -0.9547020000 -0.0762330000 +O -2.5463090000 -0.6208730000 0.0500940000 +H -2.8570340000 -1.4781490000 -0.3084110000 +H -2.9782880000 -0.4919170000 0.9200140000 +O -0.7584340000 2.1910100000 0.2382310000 +H 0.0834410000 2.6861980000 0.1576230000 +H -1.4591270000 2.7510080000 -0.1423660000 +O 2.1711740000 2.3960740000 0.0637380000 +H 2.6205500000 2.8360670000 -0.6825360000 +H 2.6485240000 2.6995610000 0.8586040000 diff --git a/zora_so/w6s1.xyz b/zora_so/w6s1.xyz new file mode 100644 index 0000000..b354a58 --- /dev/null +++ b/zora_so/w6s1.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s2.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +H 6.0712440000 0.6657150000 -0.0562890000 +O 5.3255310000 0.3585800000 -0.6032320000 +H 5.7004670000 -0.0021410000 -1.4265800000 +H 1.1231550000 1.5489260000 1.3301510000 +O 1.1470370000 1.0912480000 0.4693990000 +H 2.4855730000 1.4611280000 -0.2711830000 +H -2.6418090000 -3.8420810000 0.7188770000 +O -2.5415830000 -3.0069550000 1.2076020000 +H -3.1006780000 -3.0849500000 1.9995910000 +H -3.1193610000 -0.3371920000 -0.3428590000 +O -2.2571510000 -0.9004860000 -0.1352930000 +H -2.4327300000 -1.7558650000 0.4488990000 +H 3.2648670000 2.4162480000 -1.3718940000 +O 3.3798250000 1.8350960000 -0.5997320000 +H 4.2619190000 1.1538130000 -0.6585720000 +H -4.9580280000 0.7563380000 -0.1431910000 +O -4.2411110000 0.5138620000 -0.7549900000 +H -4.6623260000 0.3446580000 -1.6155960000 +Hg -0.5645210000 0.1234000000 0.2262520000 diff --git a/zora_so/w6s10.xyz b/zora_so/w6s10.xyz new file mode 100644 index 0000000..9c69fc7 --- /dev/null +++ b/zora_so/w6s10.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s13.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg -0.3019880000 -0.3552900000 0.0282070000 +O 2.9937480000 -2.0318450000 -1.4620360000 +H 3.5131430000 -2.7695390000 -1.0947550000 +H 3.5419600000 -1.6310200000 -2.1589530000 +O -0.5629600000 -0.5600850000 2.5149280000 +H 0.0291710000 -1.1120420000 3.0546640000 +H -1.4233630000 -0.5881600000 2.9677270000 +O -3.4337820000 -2.0714430000 -1.6448280000 +H -3.6746410000 -1.9597390000 -2.5824470000 +H -4.1913060000 -2.5036190000 -1.2102140000 +O 0.7929340000 1.9289060000 0.7061860000 +H 0.8512570000 2.7488340000 0.1833170000 +H 0.6730210000 2.2248160000 1.6267290000 +O 1.7507930000 -0.6690230000 0.1970110000 +H 2.3150730000 -1.2136710000 -0.5438480000 +H 2.1361920000 0.2192700000 0.3526990000 +O -2.3468200000 -0.2750410000 -0.3549600000 +H -2.8315630000 -1.0401010000 -0.9705990000 +H -2.6578560000 0.6075670000 -0.6285340000 diff --git a/zora_so/w6s11.xyz b/zora_so/w6s11.xyz new file mode 100644 index 0000000..d1e66bc --- /dev/null +++ b/zora_so/w6s11.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s15.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.3192920000 -0.0815120000 -0.3225220000 +O -2.9644220000 -1.1339560000 1.5103460000 +H -3.6763190000 -1.7470180000 1.2471990000 +H -3.1797920000 -0.8739720000 2.4254790000 +O 1.8482210000 1.3015440000 -0.8594840000 +H 1.6761100000 2.3590710000 -0.7725030000 +H 2.7247920000 1.0909220000 -0.4879770000 +O -0.5387580000 -1.8177710000 0.7328300000 +H -1.4427990000 -1.6338830000 1.1563070000 +H 0.0263500000 -2.2680340000 1.3883940000 +O 0.1735700000 -1.1441490000 -2.5000680000 +H -0.0587850000 -2.0830700000 -2.6085140000 +H 0.8060960000 -0.9416850000 -3.2122430000 +O -1.8519670000 0.8611780000 -0.1609660000 +H -2.5003460000 0.3030490000 0.3294260000 +H -2.3038750000 1.1982240000 -0.9548280000 +O 1.3876800000 3.7416660000 -0.7855490000 +H 1.6285410000 4.2962600000 -0.0220340000 +H 1.6513520000 4.2398300000 -1.5803750000 diff --git a/zora_so/w6s12.xyz b/zora_so/w6s12.xyz new file mode 100644 index 0000000..d26567a --- /dev/null +++ b/zora_so/w6s12.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s17.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +H -1.0205520000 2.1034190000 1.9857300000 +O -1.1379870000 1.8482770000 1.0529130000 +H -2.0935560000 1.9174580000 0.8726010000 +H 2.5840610000 0.6703330000 1.5096800000 +O 2.0008550000 -0.0910310000 1.3383640000 +H 1.9122330000 -0.5606960000 2.1875240000 +H 0.4576800000 2.6853110000 -1.2063730000 +O 0.5665950000 1.7752700000 -1.5390740000 +H 1.3718780000 1.7847110000 -2.0870740000 +H -0.4628450000 -2.6846090000 1.2041040000 +O -0.5674450000 -1.7758440000 1.5408280000 +H -1.3704260000 -1.7851410000 2.0927120000 +H 2.0885770000 -1.9164340000 -0.8784100000 +O 1.1327540000 -1.8432140000 -1.0554990000 +H 1.0110020000 -2.0975200000 -1.9881330000 +H -1.9135600000 0.5558960000 -2.1876920000 +O -2.0032520000 0.0917860000 -1.3350320000 +H -2.5851370000 -0.6719210000 -1.5024630000 +Hg -0.0018720000 0.0009490000 0.0029890000 diff --git a/zora_so/w6s13.xyz b/zora_so/w6s13.xyz new file mode 100644 index 0000000..7886b39 --- /dev/null +++ b/zora_so/w6s13.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s18.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.4863550000 -0.3651320000 -0.7297170000 +O -1.4469700000 -0.2274040000 0.9119130000 +H -2.1074230000 -0.9314100000 1.0346150000 +H -1.3904530000 0.2230630000 1.7728740000 +O -0.9852690000 -0.2944950000 -2.1659470000 +H -1.6199950000 0.6044460000 -2.2894080000 +H -0.7104870000 -0.6366940000 -3.0370710000 +O 2.5460160000 -2.7547360000 1.4313880000 +H 2.5518570000 -2.8895930000 2.3950110000 +H 3.2507440000 -3.3218990000 1.0735660000 +O 3.9266310000 1.1112770000 0.0475090000 +H 4.7580450000 0.8385210000 -0.3768230000 +H 4.1696860000 1.7629720000 0.7282070000 +O -2.4216530000 1.6859420000 -2.3725010000 +H -3.3726660000 1.5452100000 -2.2118280000 +H -2.3495750000 2.2685640000 -3.1504680000 +O 2.0254080000 -0.4446400000 0.5867320000 +H 2.2975920000 -1.4089030000 0.9158350000 +H 2.8598090000 0.1535490000 0.3499220000 diff --git a/zora_so/w6s14.xyz b/zora_so/w6s14.xyz new file mode 100644 index 0000000..8c16370 --- /dev/null +++ b/zora_so/w6s14.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s19.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +H 4.1519120000 -1.4670340000 1.0034610000 +O 3.5340750000 -1.5586060000 0.2573650000 +H 4.0525590000 -1.9045820000 -0.4902710000 +H 2.5202340000 -0.5820880000 -0.0110730000 +O 1.7175360000 0.0638460000 -0.2741250000 +H 1.9331750000 1.0559890000 -0.1807560000 +H -2.0602650000 -1.8316060000 1.4324540000 +O -2.0576230000 -1.1660700000 0.7184080000 +H -2.7674250000 -1.4652030000 -0.0854320000 +H 2.5957410000 3.1014020000 0.4918380000 +O 2.0299920000 2.6603630000 -0.1678530000 +H 2.2631720000 3.0725530000 -1.0204310000 +H -0.0064020000 2.6037410000 0.2448730000 +O -0.7476180000 1.9711820000 0.3306980000 +H -1.4619310000 2.4258630000 0.8080090000 +H -4.4868830000 -1.2438940000 -1.0550030000 +O -3.6334360000 -1.7147330000 -1.0768180000 +H -3.8204570000 -2.6369690000 -1.3309000000 +Hg -0.1829960000 -0.4378530000 0.2736970000 diff --git a/zora_so/w6s15.xyz b/zora_so/w6s15.xyz new file mode 100644 index 0000000..eddc375 --- /dev/null +++ b/zora_so/w6s15.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s21.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg -0.0833990000 -0.1557170000 -0.0097920000 +O -2.0524070000 0.1727250000 1.3123660000 +H -2.6957080000 -0.5590630000 1.3483310000 +H -2.0031620000 0.5362050000 2.2156470000 +O 1.3067010000 -0.0728730000 1.8093590000 +H 1.2611060000 -0.7877880000 2.4706900000 +H 2.2680040000 0.0404500000 1.5508440000 +O -1.2129760000 1.3686720000 -1.4320990000 +H -1.9559710000 1.8623370000 -1.0373350000 +H -0.6957230000 2.0179800000 -1.9433000000 +O -1.4429470000 -1.8108960000 -1.0236760000 +H -1.1728700000 -2.7439520000 -1.1022680000 +H -1.8378420000 -1.5694490000 -1.8825490000 +O 3.7302650000 0.3856020000 0.6822360000 +H 4.4711000000 -0.2440330000 0.7590120000 +H 4.1269810000 1.2601700000 0.8554830000 +O 1.8257110000 0.2476610000 -1.3174370000 +H 2.6580300000 0.2753920000 -0.7745930000 +H 2.0114760000 -0.2949960000 -2.1046170000 diff --git a/zora_so/w6s16.xyz b/zora_so/w6s16.xyz new file mode 100644 index 0000000..f926704 --- /dev/null +++ b/zora_so/w6s16.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s22.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.0890180000 0.0756350000 0.0801840000 +O -1.0698540000 1.8961330000 -1.0099580000 +H -1.7652190000 1.7794810000 -1.6827640000 +H -1.4036570000 2.5736890000 -0.3937340000 +O -1.8180510000 -1.3125950000 0.6101770000 +H -2.6458280000 -0.9809850000 1.0036460000 +H -2.0847960000 -1.9064850000 -0.1152010000 +O 0.1394030000 1.7983070000 1.7758780000 +H -0.1347420000 1.6649060000 2.7016080000 +H 0.9814960000 2.2878380000 1.8133410000 +O 0.2615590000 -1.6786820000 -1.5746020000 +H 0.9002460000 -2.3770200000 -1.3409790000 +H 0.3723160000 -1.5226790000 -2.5302720000 +O 1.1032760000 -1.7181160000 1.3451340000 +H 0.4703710000 -2.2222250000 1.8886270000 +H 1.9058000000 -1.6202160000 1.8893870000 +O 1.9192570000 1.4684360000 -0.6651320000 +H 2.8030770000 1.1328840000 -0.9022020000 +H 1.6731170000 2.0965450000 -1.3688000000 diff --git a/zora_so/w6s2.xyz b/zora_so/w6s2.xyz new file mode 100644 index 0000000..369ac3f --- /dev/null +++ b/zora_so/w6s2.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s5.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg -0.7323490000 -0.4471330000 -0.0463440000 +O 5.4895440000 1.5673830000 -0.4569120000 +H 5.7238060000 2.4122840000 -0.0342460000 +H 6.3644320000 0.9930840000 -0.7003790000 +O 3.6746330000 0.3163050000 0.7289810000 +H 3.7716120000 0.0742600000 1.6641910000 +H 4.7303630000 1.0575950000 0.0803870000 +O 7.4533090000 0.1977870000 -1.1118240000 +H 8.2565770000 0.1178020000 -0.5694180000 +H 7.7425210000 0.2564440000 -2.0387760000 +O -2.2553290000 -1.7186770000 -0.5501200000 +H -3.0585260000 -1.9823410000 0.1512010000 +H -2.6052200000 -1.5980530000 -1.4519560000 +O -3.9697730000 -2.3566050000 1.0900700000 +H -4.8574270000 -1.9553840000 1.0849770000 +H -4.0904820000 -3.3123390000 1.2372160000 +O 0.8328790000 0.6404730000 0.4264240000 +H 2.7150780000 0.4574490000 0.5636210000 +H 0.5179730000 1.5452170000 0.6134570000 diff --git a/zora_so/w6s3.xyz b/zora_so/w6s3.xyz new file mode 100644 index 0000000..18452cb --- /dev/null +++ b/zora_so/w6s3.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s6.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +H -3.3671880000 0.5664910000 0.6917180000 +O -2.7291680000 -0.1524650000 0.2690350000 +H -3.1767950000 -0.7673330000 -0.4554400000 +H 3.7630580000 0.8994640000 1.5299330000 +O 3.4388440000 0.2205660000 0.9099950000 +H 4.2719500000 -0.2062510000 0.3073880000 +H -0.2673270000 1.4818320000 -1.1863890000 +O -0.2725220000 0.8155870000 -0.4736430000 +H -1.8555220000 0.2250730000 -0.0253890000 +H -3.9790520000 -2.6074010000 -1.1339190000 +O -3.7100600000 -1.7222900000 -1.4331920000 +H -4.3335120000 -1.4671440000 -2.1340620000 +H -4.8496150000 2.1128890000 0.9499560000 +O -4.1803620000 1.5658890000 1.3947190000 +H -4.5366270000 1.3558620000 2.2748630000 +H 5.6094830000 -1.6164200000 -0.0558590000 +O 5.2090610000 -0.8093040000 -0.4284000000 +H 5.9343720000 -0.2751700000 -0.8004000000 +Hg 1.5780000000 0.5839850000 0.1582870000 diff --git a/zora_so/w6s4.xyz b/zora_so/w6s4.xyz new file mode 100644 index 0000000..a44b070 --- /dev/null +++ b/zora_so/w6s4.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s7.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.0488990000 1.0924390000 0.7170130000 +O -0.6535660000 -0.8803380000 -2.2647310000 +H -1.4899400000 -0.9309070000 -2.7572150000 +H -0.0036440000 -1.3631650000 -2.8023250000 +O -0.7996550000 4.9275960000 1.0819770000 +H -0.6973820000 5.5793120000 0.3647650000 +H -0.9270840000 5.4296820000 1.9078060000 +O 0.6636690000 2.9696700000 1.2343370000 +H 1.5987380000 3.1626940000 1.0389580000 +H 0.0341910000 3.8763880000 1.1331680000 +O -1.0411320000 -2.5863150000 1.9767320000 +H -1.9967420000 -2.7698950000 2.0133030000 +H -0.4527260000 -3.5006370000 1.9430570000 +O 0.3776900000 -4.6067670000 1.9668090000 +H 0.1220610000 -5.4270680000 1.5097830000 +H 0.7565580000 -4.8679630000 2.8247920000 +O -0.5491780000 -0.7388400000 0.3420480000 +H -0.6063450000 -0.8634340000 -0.6651220000 +H -0.8241220000 -1.8436310000 1.2635860000 diff --git a/zora_so/w6s5.xyz b/zora_so/w6s5.xyz new file mode 100644 index 0000000..b383600 --- /dev/null +++ b/zora_so/w6s5.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s8.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.3440230000 -0.3482610000 -0.0324370000 +O -3.7084510000 0.5499980000 0.5885940000 +H -4.5451710000 0.0987170000 0.0283380000 +H -3.9711600000 0.8197000000 1.4873090000 +O -5.5208840000 -0.4175330000 -0.7570830000 +H -6.2053640000 -0.9932700000 -0.3722750000 +H -5.9694550000 0.1867100000 -1.3754820000 +O -1.4742490000 -0.6826280000 0.7336000000 +H -2.8167150000 0.0201060000 0.6148760000 +H -1.5555500000 -1.6354390000 0.9209950000 +O 4.1812180000 0.3316510000 0.4584090000 +H 4.8351180000 -0.3713900000 0.6218960000 +H 4.6865090000 1.1376180000 0.2493800000 +O 0.8621470000 2.0207770000 0.8687030000 +H 0.7814850000 2.2923310000 1.7985710000 +H 0.8243040000 2.8460020000 0.3563010000 +O 2.1834250000 -0.1002340000 -0.9354460000 +H 3.0739200000 0.0629880000 -0.3335120000 +H 2.3743820000 -0.7514420000 -1.6353270000 diff --git a/zora_so/w6s6.xyz b/zora_so/w6s6.xyz new file mode 100644 index 0000000..cd99c46 --- /dev/null +++ b/zora_so/w6s6.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s9.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.3454210000 0.1049480000 -0.2235540000 +O 4.1766890000 1.0613270000 -0.1279950000 +H 4.6312460000 1.7536630000 -0.6434070000 +H 4.8813090000 0.4779440000 0.2093650000 +O -5.5915400000 1.0115210000 -0.3707150000 +H -6.0320930000 1.2620360000 -1.2024810000 +H -6.2838460000 0.9305110000 0.3092820000 +O -3.7588340000 -0.6049590000 -0.5714730000 +H -4.0070020000 -1.5285420000 -0.3855860000 +H -4.6068710000 0.0965320000 -0.4421110000 +O 1.5485400000 1.7274420000 1.3377590000 +H 1.1694660000 2.4493230000 1.8670390000 +H 2.5142040000 1.8418400000 1.3797420000 +O 2.1390230000 0.1065830000 -1.2721200000 +H 3.0157080000 0.4481990000 -0.7963010000 +H 2.3293770000 -0.7014700000 -1.7841930000 +O -1.5137540000 0.0123820000 0.5074650000 +H -1.4646630000 0.0084550000 1.4803110000 +H -2.8709090000 -0.3614350000 -0.1034280000 diff --git a/zora_so/w6s7.xyz b/zora_so/w6s7.xyz new file mode 100644 index 0000000..af66f3c --- /dev/null +++ b/zora_so/w6s7.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s10.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg -0.1139160000 0.1928540000 -0.0822420000 +O 2.9198070000 2.4660880000 0.3199980000 +H 3.2628870000 2.8742320000 1.1343070000 +H 3.5406200000 2.7090160000 -0.3884930000 +O 3.1478070000 -1.8516500000 0.0468880000 +H 3.7260500000 -1.9509160000 -0.7293160000 +H 3.6244730000 -2.2564030000 0.7927630000 +O -2.0273560000 0.3146570000 -0.8206610000 +H -2.9134740000 0.4040530000 -0.1576420000 +H -2.1204360000 0.9001010000 -1.5947860000 +O -1.0017410000 -1.7577300000 1.2862960000 +H -0.8495390000 -1.8674560000 2.2407670000 +H -1.1134480000 -2.6592510000 0.9382890000 +O -3.9724510000 0.4415080000 0.6687850000 +H -4.6389190000 -0.2603920000 0.5529130000 +H -4.4598300000 1.2795420000 0.7700930000 +O 1.8118050000 0.2207420000 0.5408700000 +H 2.3210120000 1.1333170000 0.4075970000 +H 2.3999090000 -0.6187130000 0.2949740000 diff --git a/zora_so/w6s8.xyz b/zora_so/w6s8.xyz new file mode 100644 index 0000000..9fed66f --- /dev/null +++ b/zora_so/w6s8.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s11.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +Hg 0.3510860000 -0.1028460000 -0.9466820000 +O 0.9595380000 -0.2699700000 1.4564990000 +H 0.4023550000 -0.8702160000 1.9912430000 +H 1.8410270000 -0.2593280000 1.8677840000 +O -1.3573650000 -1.9704970000 1.9095280000 +H -1.2845800000 -2.9176720000 2.1297900000 +H -2.0724520000 -1.6311390000 2.4784000000 +O -3.1609250000 -1.2544550000 -2.1528710000 +H -3.3794880000 -2.0478140000 -2.6731170000 +H -4.0079700000 -0.8446120000 -1.9051700000 +O 1.8909150000 1.1238710000 -1.5346450000 +H 2.1887380000 1.2571530000 -2.6003460000 +H 1.9258250000 1.9708530000 -1.0525870000 +O -1.1808310000 -1.4169770000 -0.6455300000 +H -2.0620470000 -1.3316520000 -1.2341220000 +H -1.3576870000 -1.6248060000 0.3371020000 +O 2.5759920000 1.3041570000 -3.8763960000 +H 3.5046730000 1.0706940000 -4.0608610000 +H 2.3728090000 2.0999710000 -4.4010430000 diff --git a/zora_so/w6s9.xyz b/zora_so/w6s9.xyz new file mode 100644 index 0000000..fd5e678 --- /dev/null +++ b/zora_so/w6s9.xyz @@ -0,0 +1,21 @@ + 19 + file 'w6s12.log' was gotten at: ---'ZORA-SR+SO PBE QZ4P'--- +H -3.6737890000 2.5267720000 -0.8048380000 +O -3.0599640000 2.4542350000 -0.0532290000 +H -3.5024850000 2.8704570000 0.7078190000 +H 2.4698970000 2.0334990000 -0.6043140000 +O 2.3028490000 1.0759130000 -0.5288260000 +H 3.1715940000 0.5679060000 -0.0544860000 +H -2.0371360000 -0.4499440000 0.2637610000 +O -1.6296710000 0.4691520000 0.4141700000 +H -2.2810100000 1.2774830000 0.1757540000 +H -0.4715860000 -2.2870040000 -0.2558460000 +O 0.4026570000 -1.8490370000 -0.3260180000 +H 0.9460330000 -2.3940280000 -0.9201220000 +H 4.6328160000 0.1733590000 1.2550820000 +O 4.2069000000 -0.1276970000 0.4308620000 +H 4.9217540000 -0.3403100000 -0.1977170000 +H -2.7448150000 -2.4369700000 0.9789270000 +O -2.4315590000 -2.0235730000 0.1529860000 +H -3.0635520000 -2.3118170000 -0.5310400000 +Hg 0.3445100000 0.6109040000 -0.1035250000