diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 00000000..e73e26af --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1,13 @@ +# This defines "ownership" of files in the repo, which is used for PR review requests among other things. +# Last matching pattern takes precedence. +# The syntax is defined here: https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners + +# Global default +* @AstarVienna/scopesim-devs + +/.github/ @hugobuddel @teutoburg +/irdb/ @teutoburg + +# Specific instrument packages managed by individual people +/MOSAIC/ @oczoske +/NIRCam/ @teutoburg diff --git a/.github/workflows/badge_report.yml b/.github/workflows/badge_report.yml index 006fc78c..462dd712 100644 --- a/.github/workflows/badge_report.yml +++ b/.github/workflows/badge_report.yml @@ -48,7 +48,7 @@ jobs: run: pytest -m "badges" - name: Store badge report files - uses: actions/upload-artifact@v6 + uses: actions/upload-artifact@v7 with: name: badge-report path: _REPORTS diff --git a/.github/workflows/internal_tests.yml b/.github/workflows/internal_tests.yml new file mode 100644 index 00000000..354e284e --- /dev/null +++ b/.github/workflows/internal_tests.yml @@ -0,0 +1,71 @@ +# Any IRDB functionality not related to a specific instrument package. +# Has to be triggered from elsewhere like tests.yml or notebooktests.yml. + +name: Internal functionality tests +on: + # Allows you to run this workflow manually from the Actions tab + workflow_dispatch: + inputs: + from_pypi: + type: boolean + description: "Use plain pip install and ignore branch names below." + required: false + default: false + ScopeSim: + type: string + description: "Branch name to install ScopeSim from." + required: false + default: main + ScopeSim_Templates: + type: string + description: "Branch name to install ScopeSim_Templates from." + required: false + default: main + + # Allow this workflow to be called from other repositories. + workflow_call: + inputs: + from_pypi: + type: boolean + description: "Use plain pip install and ignore branch names below." + required: false + default: false + ScopeSim: + type: string + description: "Branch name to install ScopeSim from." + required: false + default: main + ScopeSim_Templates: + type: string + description: "Branch name to install ScopeSim_Templates from." + required: false + default: main + +jobs: + irdb_test: + name: Run internal tests + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v6 + + - name: Set up Python + uses: actions/setup-python@v6 + with: + # No matrix is used since this is a time-consuming task. + python-version: 3.13 + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -r requirements.github_actions.txt + + - name: Install ScopeSim from repo + if: ${{ inputs.from_pypi == false || inputs.from_pypi == 'false' }} + run: | + echo "Re-installing ScopeSim from source" >> $GITHUB_STEP_SUMMARY + pip uninstall -y scopesim scopesim_templates + pip install git+https://github.com/AstarVienna/ScopeSim.git@${{ inputs.ScopeSim }} + pip install git+https://github.com/AstarVienna/ScopeSim_Templates.git@${{ inputs.ScopeSim_Templates }} + + - name: Run Pytest for internal tests + run: pytest -m "irdb" diff --git a/.github/workflows/markdown_link_check.yml b/.github/workflows/markdown_link_check.yml index 2b8f1c42..3c1b6b25 100644 --- a/.github/workflows/markdown_link_check.yml +++ b/.github/workflows/markdown_link_check.yml @@ -1,23 +1,23 @@ name: Check Markdown links on: - push: - branches: - - main - - master - - dev_master - pull_request: - branches: - - main - - master - - dev_master + # push: + # branches: + # - main + # - master + # - dev_master + # pull_request: + # branches: + # - main + # - master + # - dev_master # Allows you to run this workflow manually from the Actions tab. workflow_dispatch: # Run every day at 5:00 UTC - schedule: - - cron: "0 5 * * *" + # schedule: + # - cron: "0 5 * * *" jobs: markdown-link-check: diff --git a/.github/workflows/notebooktests.yml b/.github/workflows/notebooktests.yml index 8e1362d0..b5e70139 100644 --- a/.github/workflows/notebooktests.yml +++ b/.github/workflows/notebooktests.yml @@ -146,14 +146,40 @@ jobs: PYDEVD_DISABLE_FILE_VALIDATION: 1 run: | echo "## METIS Notebooks tested" >> $GITHUB_STEP_SUMMARY - echo "### Example Notebooks" >> $GITHUB_STEP_SUMMARY for fn in METIS/docs/example_notebooks/*.ipynb do echo "${fn}" echo "- ${fn}" >> $GITHUB_STEP_SUMMARY /usr/bin/time -v jupytext --execute --update "${fn}" done - echo "## Demo Notebooks" >> $GITHUB_STEP_SUMMARY + + metis_demo_notebooks: + name: Run METIS Demo Notebooks + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v6 + - name: Set up Python + uses: actions/setup-python@v6 + with: + # No matrix is used since this is a time-consuming task. + python-version: 3.13 + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -r requirements.github_actions.txt + + - name: Install ScopeSim from repo + if: ${{ inputs.from_pypi == false || inputs.from_pypi == 'false' }} + run: | + echo "Re-installing ScopeSim from source" >> $GITHUB_STEP_SUMMARY + pip uninstall -y scopesim scopesim_templates + pip install git+https://github.com/AstarVienna/ScopeSim.git@${{ inputs.ScopeSim }} + pip install git+https://github.com/AstarVienna/ScopeSim_Templates.git@${{ inputs.ScopeSim_Templates }} + - name: Run Notebooks + env: + PYDEVD_DISABLE_FILE_VALIDATION: 1 + run: | + echo "## METIS Demo Notebooks tested" >> $GITHUB_STEP_SUMMARY for fn in METIS/docs/example_notebooks/demos/*.ipynb do echo "${fn}" diff --git a/.github/workflows/tests_dev.yml b/.github/workflows/tests_dev.yml index 651fe683..e20adb37 100644 --- a/.github/workflows/tests_dev.yml +++ b/.github/workflows/tests_dev.yml @@ -4,15 +4,19 @@ on: branches: - dev_master - # Run every day at 5:00 UTC + # Runs at 05:00 UTC, Monday through Friday schedule: - - cron: "0 5 * * *" + - cron: "0 5 * * MON-FRI" jobs: tests: name: Tests uses: ./.github/workflows/tests.yml + internal_tests: + name: Internal Tests + uses: ./.github/workflows/internal_tests.yml + notebook_tests: name: Notebook tests uses: ./.github/workflows/notebooktests.yml diff --git a/.github/workflows/tests_dev_pr.yml b/.github/workflows/tests_dev_pr.yml index 037bd5c0..a08f9bb1 100644 --- a/.github/workflows/tests_dev_pr.yml +++ b/.github/workflows/tests_dev_pr.yml @@ -25,6 +25,15 @@ jobs: ScopeSim: ${{ needs.determine_branches.outputs.ScopeSim }} ScopeSIM_Templates: ${{ needs.determine_branches.outputs.ScopeSIM_Templates }} + internal_tests: + name: Internal Tests + needs: determine_branches + if: contains(github.event.pull_request.labels.*.name, 'irdb functionality') + uses: ./.github/workflows/internal_tests.yml + with: + ScopeSim: ${{ needs.determine_branches.outputs.ScopeSim }} + ScopeSIM_Templates: ${{ needs.determine_branches.outputs.ScopeSIM_Templates }} + notebook_tests: name: Notebook tests needs: determine_branches diff --git a/.github/workflows/tests_main_pr.yml b/.github/workflows/tests_main_pr.yml index a7af7476..9dbc4191 100644 --- a/.github/workflows/tests_main_pr.yml +++ b/.github/workflows/tests_main_pr.yml @@ -11,6 +11,12 @@ jobs: with: from_pypi: true + internal_tests: + name: Internal Tests + uses: ./.github/workflows/internal_tests.yml + with: + from_pypi: true + notebook_tests: name: Notebook tests uses: ./.github/workflows/notebooktests.yml diff --git a/.readthedocs.yaml b/.readthedocs.yaml index ef066b29..35efb924 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -5,9 +5,14 @@ version: 2 build: - os: ubuntu-20.04 + os: "ubuntu-24.04" tools: - python: "3.9" + python: "3.11" + jobs: + post_install: + - pytest ./MICADO/test_micado/ -m validation --junit-xml=./MICADO/test_micado/validation_results.xml --tb=line -o junit_suite_name=MICADO || true + # - pytest ./METIS/tests/ -m validation --junit-xml=./METIS/tests/validation_results.xml --tb=line -o junit_suite_name=METIS || true + # - pytest ./MOSAIC/tests/ -m validation --junit-xml=./MOSAIC/tests/validation_results.xml --tb=line -o junit_suite_name=MOSAIC || true sphinx: configuration: conf.py diff --git a/ELT/tests/test_TER_properties.py b/ELT/tests/test_TER_properties.py index 0f9824a7..198a2d0f 100644 --- a/ELT/tests/test_TER_properties.py +++ b/ELT/tests/test_TER_properties.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- """Unit tests for irdb/ELT""" # pylint: disable=no-self-use, missing-class-docstring # pylint: disable=missing-function-docstring @@ -35,8 +36,6 @@ def test_eso_vs_scopesim_throughput(): plt.show() -## .todo: the values are not correct -@pytest.mark.xfail(reason="Does fail with ScopeSim 0.7.1. TODO: Remove mark when 0.8.0 is released.") def test_eso_vs_scopesim_emission(): cmds = UserCommands(properties={ "!ATMO.temperature": 0., @@ -45,9 +44,11 @@ def test_eso_vs_scopesim_emission(): }) slist = sim.effects.SurfaceList(filename="LIST_mirrors_ELT.tbl", cmds=cmds) - ter = sim.effects.TERCurve(filename="TER_ELT_5_mirror.dat", - temperature="!ATMO.temperature", - cmds=cmds) + ter = sim.effects.TERCurve( + filename="TER_ELT_5_mirror.dat", + temperature="!ATMO.temperature", + cmds=cmds, + ) wave = np.linspace(0.3, 12.5, 100) * u.um sl_flux = slist.emission(wave) @@ -82,9 +83,11 @@ def fixture_elt_configs(): "TER_ELT_6_mirror_field_track.dat" slist_6f = sim.effects.SurfaceList(filename="LIST_ELT_combined.tbl") - return {'5 mirror': slist_5, - '6 mirror pupil': slist_6p, - '6 mirror field': slist_6f} + return { + "5 mirror": slist_5, + "6 mirror pupil": slist_6p, + "6 mirror field": slist_6f, + } class TestELTConfigurations: diff --git a/HAWKI/TC_dichroic.dat b/HAWKI/TC_dichroic.dat index 5ac09329..e59663e3 100644 --- a/HAWKI/TC_dichroic.dat +++ b/HAWKI/TC_dichroic.dat @@ -1,4 +1,4 @@ -# wavelength_unit : micron +# wavelength_unit : um wavelength throughput 0.5 1 2.5 1 diff --git a/HAWKI/VLT-MAN-ESO-14800-3486_v110.pdf b/HAWKI/VLT-MAN-ESO-14800-3486_v110.pdf deleted file mode 100644 index 37fa3720..00000000 Binary files a/HAWKI/VLT-MAN-ESO-14800-3486_v110.pdf and /dev/null differ diff --git a/HAWKI/default.yaml b/HAWKI/default.yaml index a7a76be6..5dc7f076 100644 --- a/HAWKI/default.yaml +++ b/HAWKI/default.yaml @@ -21,6 +21,7 @@ yamls: - HAWKI_H2RG.yaml properties : + instrument: HAWKI filter_name : Ks airmass : 1.2 declination : -30 diff --git a/HAWKI/test_hawki/test_full_package_hawki.py b/HAWKI/test_hawki/test_full_package_hawki.py index 1d1ff844..77930b01 100644 --- a/HAWKI/test_hawki/test_full_package_hawki.py +++ b/HAWKI/test_hawki/test_full_package_hawki.py @@ -9,19 +9,21 @@ """ # integration test using everything and the HAWKI package -import pytest -from pytest import approx import os import os.path as pth +import pytest +from pytest import approx + import numpy as np from astropy import units as u -from astropy.io import ascii +from astropy.io import ascii as ioascii import scopesim import scopesim.source.source_templates from scopesim.tests.mocks.py_objects.source_objects import _single_table_source from scopesim import rc +from scopesim.optics.image_plane_utils import calc_footprint from matplotlib import pyplot as plt from matplotlib.colors import LogNorm @@ -41,29 +43,27 @@ "VLT": "telescopes/VLT.zip", "HAWKI": "instruments/HAWKI.zip"} +# pylint: disable=missing-class-docstring,missing-function-docstring -class TestInit: - def test_all_packages_are_available(self): - rc_local_path = rc.__config__["!SIM.file.local_packages_path"] - print("irdb" not in rc_local_path) - for pkg_name in PKGS: - assert os.path.isdir(os.path.join(rc_local_path, pkg_name)) - +def test_all_packages_are_available(): + rc_local_path = rc.__config__["!SIM.file.local_packages_path"] + print("irdb" not in rc_local_path) + for pkg_name in PKGS: + assert os.path.isdir(os.path.join(rc_local_path, pkg_name)) -class TestLoadUserCommands: - def test_user_commands_loads_without_throwing_errors(self, capsys): - cmd = scopesim.UserCommands(use_instrument="HAWKI") - assert isinstance(cmd, scopesim.UserCommands) - for key in ["SIM", "OBS", "ATMO", "TEL", "INST", "DET"]: - assert key in cmd and len(cmd[key]) > 0 +def test_user_commands_loads_without_throwing_errors(capsys): + cmd = scopesim.UserCommands(use_instrument="HAWKI") + assert isinstance(cmd, scopesim.UserCommands) + for key in ["SIM", "OBS", "ATMO", "TEL", "INST", "DET"]: + assert key in cmd and len(cmd[key]) > 0 - stdout = capsys.readouterr() - assert len(stdout.out) == 0 + stdout = capsys.readouterr() + assert len(stdout.out) == 0 @pytest.mark.slow class TestMakeOpticalTrain: - def test_works_seamlessly_for_hawki_package(self, capsys): + def test_works_seamlessly_for_hawki_package(self): cmd = scopesim.UserCommands(use_instrument="HAWKI") opt = scopesim.OpticalTrain(cmd) opt["detector_1024_window"].include = False @@ -80,7 +80,7 @@ def test_works_seamlessly_for_hawki_package(self, capsys): # test that we have a system throughput wave = np.linspace(0.7, 2.5, 181) * u.um - tc = opt.optics_manager.system_transmission + tc = opt.optics_manager.system_transmission() # ec = opt.optics_manager.surfaces_table.emission # ..todo:: something super wierd is going on here when running pytest in the top directory # ..todo:: perhaps this is has to be relaxed due to different filter @@ -102,7 +102,6 @@ def test_works_seamlessly_for_hawki_package(self, capsys): if PLOTS: fovs = opt.fov_manager.fovs - from scopesim.optics.image_plane_utils import calc_footprint plt.subplot(121) for fov in fovs: x, y = calc_footprint(fov.hdu.header) @@ -143,7 +142,7 @@ def test_works_seamlessly_for_hawki_package(self, capsys): def test_system_transmission_is_similar_to_eso_etc(self): """ - A ~20% discrepency between the ESO and ScopeSim system throughputs + A ~20% discrepancy between the ESO and ScopeSim system throughputs """ for filt_name in ["Y", "J", "H", "Ks", "BrGamma", "CH4"]: @@ -158,9 +157,9 @@ def test_system_transmission_is_similar_to_eso_etc(self): opt.observe(src) if PLOTS: - fname = "hawki_eso_etc/TER_system_{}.dat".format(filt_name) + fname = f"hawki_eso_etc/TER_system_{filt_name}.dat" dname = os.path.dirname(__file__) - etc_tbl = ascii.read(os.path.join(dname, fname)) + etc_tbl = ioascii.read(os.path.join(dname, fname)) etc_wave = etc_tbl["wavelength"] * 1e-3 * u.um etc_thru = etc_tbl["transmission"] * 1e-2 # plt.plot(etc_wave, etc_thru, c="b", label="ESO/ETC") @@ -267,8 +266,9 @@ def test_background_is_similar_to_online_etc(self, filter_name, bg_level): if PLOTS: wave = np.arange(0.7, 2.5, 0.001) * u.um specs = opt._last_source.spectra - for i in range(len(specs)): - flux = specs[i](wave) + #for i in range(len(specs)): + for spec in specs: + flux = spec(wave) plt.plot(wave, flux) plt.show() diff --git a/METIS/LIST_ifu_apertures.dat b/METIS/LIST_ifu_apertures.dat deleted file mode 100644 index 150d7dda..00000000 --- a/METIS/LIST_ifu_apertures.dat +++ /dev/null @@ -1,19 +0,0 @@ -# name : METIS IFU aperture list -# author : Kieran Leschinski -# sources: -# date_created : 2019-10-16 -# date_modified : 2019-10-16 -# type : aperture_list -# left_unit : arcsec -# right_unit : arcsec -# top_unit : arcsec -# bottom_unit : arcsec -# angle_unit : deg -# -# changes: -# - 2019-16-10 (KL) created first aperture list -# -id left right top bottom angle shape conserve_image -0 -3 3 0.3 0.1 0 rect True -1 -3 3 0.1 -0.1 0 rect True -2 -3 3 -0.1 -0.3 0 rect True \ No newline at end of file diff --git a/METIS/METIS_DET_IFU.yaml b/METIS/METIS_DET_IFU.yaml index 420281df..69539f10 100644 --- a/METIS/METIS_DET_IFU.yaml +++ b/METIS/METIS_DET_IFU.yaml @@ -17,6 +17,7 @@ properties: dit: "!OBS.dit" ndit: "!OBS.ndit" mindit: 1.3 # seconds, Roy van Boekel, pers. communication + include_prnu: False full_well: 1.e+5 # electrons, E-TNT-MPIA-1004, v1-0 gain: 1: 2.0 # electrons/ADU, email B.Serra 2024-10-09 @@ -69,6 +70,14 @@ effects: description: Summing up sky signal for all DITs and NDITs class: ExposureIntegration + - name: prnu + description: Pixel-to-pixel response non-uniformity + class: PixelResponseNonUniformity + include: "!DET.include_prnu" + kwargs: + prnu_std: 0.005 + prnu_seed: 42 + - name: dark_current description: METIS LMS dark current class: DarkCurrent diff --git a/METIS/METIS_DET_IFU_SMPL.yaml b/METIS/METIS_DET_IFU_SMPL.yaml index bf5171c6..9cf7820c 100644 --- a/METIS/METIS_DET_IFU_SMPL.yaml +++ b/METIS/METIS_DET_IFU_SMPL.yaml @@ -15,7 +15,7 @@ properties: temperature: -233 dit: "!OBS.dit" ndit: "!OBS.ndit" - mindit: 1.3 # seconds, Roy van Boekel, pers. communication + mindit: 1.3 # seconds, Roy van Boekel, pers. communication full_well: 1.e+5 # electrons, E-TNT-MPIA-1004, v1-0 gain: 2 dark_current: 0.1 # [e-/s] diff --git a/METIS/METIS_DET_IMG_LM.yaml b/METIS/METIS_DET_IMG_LM.yaml index 1fef13a7..6a5aa872 100644 --- a/METIS/METIS_DET_IMG_LM.yaml +++ b/METIS/METIS_DET_IMG_LM.yaml @@ -19,6 +19,7 @@ properties: temperature: -230 dit: "!OBS.dit" ndit: "!OBS.ndit" + include_prnu: False layout: file_name: "FPA_metis_img_lm_layout.dat" qe_curve: @@ -82,6 +83,14 @@ effects: description: Summing up sky signal for all DITs and NDITs class: ExposureIntegration + - name: prnu + description: Pixel-to-pixel response non-uniformity + class: PixelResponseNonUniformity + include: "!DET.include_prnu" + kwargs: + prnu_std: 0.005 + prnu_seed: 42 + - name: dark_current description: METIS LM dark current class: DarkCurrent diff --git a/METIS/METIS_DET_IMG_N_Aquarius.yaml b/METIS/METIS_DET_IMG_N_Aquarius.yaml index 1cfd440a..4c8394a7 100644 --- a/METIS/METIS_DET_IMG_N_Aquarius.yaml +++ b/METIS/METIS_DET_IMG_N_Aquarius.yaml @@ -16,6 +16,7 @@ properties: temperature: -265 dit: "!OBS.dit" ndit: "!OBS.ndit" + include_prnu: False mindit: 0.008 # seconds, E-REP-NOVA-MET-1191, v2-0 full_well: 1.e+6 # electrons, low-capacity mode dark_current: 13 # [e-/s] E-REP-NOVA-MET-1191, v2-0 @@ -69,6 +70,14 @@ effects: description: Summing up sky signal for all DITs and NDITs class: ExposureIntegration + - name: prnu + description: Pixel-to-pixel response non-uniformity + class: PixelResponseNonUniformity + include: "!DET.include_prnu" + kwargs: + prnu_std: 0.001 + prnu_seed: 42 + - name: dark_current description: METIS Aquarius dark current class: DarkCurrent diff --git a/METIS/METIS_DET_IMG_N_GeoSnap.yaml b/METIS/METIS_DET_IMG_N_GeoSnap.yaml index 86dfce0c..5f5eb98f 100644 --- a/METIS/METIS_DET_IMG_N_GeoSnap.yaml +++ b/METIS/METIS_DET_IMG_N_GeoSnap.yaml @@ -21,6 +21,7 @@ properties: temperature: -240 dit: "!OBS.dit" ndit: "!OBS.ndit" + include_prnu: False border: [28, 28, 28, 28] layout: file_name: "FPA_metis_img_n_geosnap_layout.dat" @@ -86,6 +87,14 @@ effects: description: Summing up sky signal for all DITs and NDITs class: ExposureIntegration + - name: prnu + description: Pixel-to-pixel response non-uniformity + class: PixelResponseNonUniformity + include: "!DET.include_prnu" + kwargs: + prnu_std: 0.001 + prnu_seed: 42 + - name: dark_current description: METIS GeoSnap dark current class: DarkCurrent diff --git a/METIS/METIS_IMG_LM.yaml b/METIS/METIS_IMG_LM.yaml index a8679bf6..1f18a166 100644 --- a/METIS/METIS_IMG_LM.yaml +++ b/METIS/METIS_IMG_LM.yaml @@ -18,6 +18,7 @@ properties: pixel_scale: 0.00547 # arcsec / pixel, METIS_1097 plate_scale: 0.30389 # arcsec / mm filter_file_format: "filters/TC_filter_{}.dat" + include_illumination: False effects: - name: img_lm_optics @@ -33,6 +34,7 @@ effects: filter_names: # 18 positions (E-REP-MPIA-MET-1008_1-0) - open + - closed - Lp - short-L - L_spec @@ -63,6 +65,7 @@ effects: # 11 positions (E-REP-MPIA-MET-1008_1-0) # OD = optical density, transmissivity 10^{-OD}. - open + - closed - ND_OD1 - ND_OD2 - ND_OD3 @@ -92,6 +95,11 @@ effects: kwargs: filename: headers/FITS_img_lm_keywords.yaml + - name: illumination + description: Large-scale illumination variation across the image plane + class: Illumination + include: "!INST.include_illumination" + --- ### default simulation parameters needed for a METIS simulation object: simulation diff --git a/METIS/METIS_IMG_N.yaml b/METIS/METIS_IMG_N.yaml index 7adc500d..e4a13d11 100644 --- a/METIS/METIS_IMG_N.yaml +++ b/METIS/METIS_IMG_N.yaml @@ -16,6 +16,7 @@ properties: pixel_scale: 0.00679 # arcsec / pixel, METIS-1097 plate_scale: 0.377222222222 # arcsec / mm filter_file_format: "filters/TC_filter_{}.dat" + include_illumination: False effects: - name: img_n_optics @@ -31,6 +32,7 @@ effects: filter_names: # 18 positions (E-REP-MPIA-MET-1008_1-0) - open + - closed - N1 - N2 - N3 @@ -57,6 +59,7 @@ effects: # 11 positions (E-REP-MPIA-MET-1008_1-0) # OD = optical density, transmissivity 10^{-OD} - open + - closed - ND_OD1 - ND_OD2 - ND_OD3 @@ -84,8 +87,12 @@ effects: include: True kwargs: filename: headers/FITS_img_n_keywords.yaml - - + + - name: illumination + description: Large-scale illumination variation across the image plane + class: Illumination + include: "!INST.include_illumination" + --- ### default simulation parameters needed for a METIS simulation object: simulation diff --git a/METIS/METIS_LMS.yaml b/METIS/METIS_LMS.yaml index 6a3c7641..fb2a871c 100644 --- a/METIS/METIS_LMS.yaml +++ b/METIS/METIS_LMS.yaml @@ -15,6 +15,7 @@ properties: plate_scale: 0.455555555556 # arcsec / mm fp2_platescale: 0.303 # arcsec / mm decouple_detector_from_sky_headers: True # needed for spectroscopy + filter_file_format: "filters/TC_filter_{}.dat" effects: - name: metis_lms_surfaces @@ -23,6 +24,22 @@ effects: kwargs: filename: LIST_METIS_mirrors_lms.dat + - name: lms-pp1 + description: LMS-PP1 Pupil mask wheel + class: FilterWheel + kwargs: + filter_names: + # only filters; pupil masks only in wcu (METIS-3639) + - open + - closed + - ND-2.8 + - ND-1.4 + filename_format: "!INST.filter_file_format" + current_filter: "!OBS.nd_filter_name" + minimum_throughput: 0. + outer: 19.9 # E-REP-ATC-MET-1003_3-0 + outer_unit: "mm" + - name: lms_efficiency description: grating efficiency of METIS LMS class: MetisLMSEfficiency diff --git a/METIS/TER_lms_predisperser_prism.dat b/METIS/TER_lms_predisperser_prism.dat index ad09f9aa..d4ccc0e8 100644 --- a/METIS/TER_lms_predisperser_prism.dat +++ b/METIS/TER_lms_predisperser_prism.dat @@ -1,7 +1,7 @@ # author : Oliver Czoske # source : E-SPE-NOVA-MET-1049_4-0 (METIS transmission budget) # date_created : 2020-04-13 -# date_modified : 2022-05-11 +# date_modified : 2026-03-31 # status : version 4.0 # type : prism:transmission # wavelength_unit : um @@ -9,8 +9,19 @@ # comment : extracted from excel sheet "CFO+LMS" # changes : # - 2022-05-11 (OC) updated to 4.0 +# - 2026-03-31 (OC) extend below 2.7um for order 41 # wavelength transmission reflection emissivity +2.60 0.867 0.133 0 +2.61 0.867 0.133 0 +2.62 0.867 0.133 0 +2.63 0.867 0.133 0 +2.64 0.867 0.133 0 +2.65 0.867 0.133 0 +2.66 0.867 0.133 0 +2.67 0.867 0.133 0 +2.68 0.867 0.133 0 +2.69 0.867 0.133 0 2.70 0.867 0.133 0 2.71 0.867 0.133 0 2.72 0.867 0.133 0 diff --git a/METIS/default.yaml b/METIS/default.yaml index ecba7e1e..ae377944 100644 --- a/METIS/default.yaml +++ b/METIS/default.yaml @@ -6,7 +6,7 @@ alias: OBS name: METIS_default_configuration description: default parameters needed for a METIS simulation status: development -needs_scopesim: "v0.11.1a1" +needs_scopesim: "v0.11.3" date_modified: 2025-10-09 changes: - 2021-12-16 (OC) chopnod defaults to perpendicular @@ -22,6 +22,7 @@ changes: - 2025-08-26 (OC) modes for Leiden sky observations - 2025-09-29 (OC) version bump - 2025-10-09 (OC) proper MJD value + - 2026-03-31 (OC) set wave_min to 2.65um for bluest LMS settings packages: - Armazones @@ -534,7 +535,7 @@ properties: seed: None # 9001 spectral: - wave_min: 2.85 + wave_min: 2.65 wave_mid: 8.425 wave_max: 14.0 diff --git a/METIS/docs/README.md b/METIS/docs/README.md new file mode 100644 index 00000000..b248958a --- /dev/null +++ b/METIS/docs/README.md @@ -0,0 +1,108 @@ +```{image} metis_scopesim_logo.png +:width: 600px +:alt: METIS + ScopeSim +:align: center +``` + +# METIS + ScopeSim + +## Introduction + +The METIS data simulator is based on the generic simulator ScopeSim, a +descendant of the older SimCado/SimMETIS interface. METIS itself is handled +as an instrument package containing configuration files for the various +instrument modes and data files describing the instrument components. + +The simulator currently supports imaging and long-slit spectroscopy modes. +The LM-band high-resolution IFU (LMS) mode is under development. + +```{note} +**Bug reports and help desk** + +If you come across a bug or get stuck with ScopeSim or the METIS package, +please [open an issue on GitHub](https://github.com/AstarVienna/irdb/issues) +or contact us by email (see below). + +**Your feedback is the only way we know** what needs to be +changed or improved with the package and the simulator. + +Please always include the output of `scopesim.bug_report()` from your +installation. +``` + +## Downloading the METIS instrument package + +Once ScopeSim is installed, download the METIS instrument package into your +working directory: + +```python +import scopesim +scopesim.download_packages(["Armazones", "ELT", "METIS"]) +``` + +This installs the packages into the subdirectory `./inst_pkgs/`. + +Your working directory should look like this afterwards: + +``` +my_simulations/ +├── .ipynb +└── inst_pkgs/ + ├── Armazones/ + ├── ELT/ + └── METIS/ + └── docs/ + └── example_notebooks/ + └── .ipynb ← copy to working dir before running +``` + +```{include} ../../docs/ScopeSim_guide.md +``` + +## Example notebooks + +Find the notebooks locally in `inst_pkgs/METIS/docs/example_notebooks/` +after downloading the package, or download them from the +[GitHub repository](https://github.com/AstarVienna/irdb/tree/dev_master/METIS/docs/example_notebooks). + +```{warning} +Run notebooks in your working directory, **not** inside `inst_pkgs/`. +Copy the desired notebook out first. +``` + +### Introductory notebooks + +```{toctree} +:maxdepth: 1 + +example_notebooks/Introduction_to_Scopesim_for_METIS +example_notebooks/METIS_IFU-01-Source_cube +example_notebooks/METIS_IFU-02-Simulation +example_notebooks/METIS_WCU +``` + +### Scientific use-case notebooks + +```{toctree} +:maxdepth: 1 + +example_notebooks/IMG_L_N-examples +example_notebooks/LSS-YSO_model_simulation +example_notebooks/LSS_AGN-01_preparation +example_notebooks/LSS_AGN-02_simulation +``` + +### Effect demonstration notebooks + +These notebooks are in `docs/example_notebooks/demos/`. + +```{toctree} +:maxdepth: 1 +:glob: + +example_notebooks/demos/* +``` + +### Instrument homepage + +[METIS at Leiden Observatory](https://metis.strw.leidenuniv.nl/) diff --git a/METIS/docs/example_notebooks/IFU-example.ipynb b/METIS/docs/example_notebooks/IFU-example.ipynb deleted file mode 100644 index dfb3f312..00000000 --- a/METIS/docs/example_notebooks/IFU-example.ipynb +++ /dev/null @@ -1,468 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "f915a497-1261-4344-b407-666a0c0bff29", - "metadata": {}, - "outputs": [], - "source": [ - "import scopesim as sim\n", - "from astropy import units as u\n", - "from matplotlib import pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7b3bfcc-63ab-48a2-8016-358c735709c0", - "metadata": {}, - "outputs": [], - "source": [ - "cmd = sim.UserCommands(\n", - " use_instrument=\"METIS\",\n", - " set_modes=['lms'],\n", - " properties={\n", - " \"!OBS.wavelen\": 3.555,\n", - "\n", - " # These !SIM.spectral_* properties make the simulation faster, but less precise.\n", - " # Comment them out for your final simulations.\n", - " # \"!SIM.spectral_bin_width\": 1e-3,\n", - " # \"!SIM.spectral_resolution\": 1000,\n", - " \n", - " })\n", - "\n", - "lms = sim.OpticalTrain(cmd)\n", - "src = sim.source.source_templates.star(flux=0.01 * u.Jy, x=0, y=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "2579348d-3c45-4709-9d4c-309fa72904f7", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " FOVs: 0%| | 0/1 [00:00" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ip = lms.image_planes[0]\n", - "\n", - "plt.imshow(ip.data)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "720373cf-e383-42d5-818f-73e9d4828352", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[32mastar.scopesim.effects.electronic - Requested exposure time: 3600.000 s\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.electronic - Exposure parameters: DIT=1800.000 s NDIT=2\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.electronic - Total exposure time: 3600.000 s\u001b[0m\n", - "\u001b[32mastar.scopesim.detector.detector_array - Extracting from 4 detectors...\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.electronic - Requested exposure time: 3600.000 s\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.electronic - Exposure parameters: DIT=1800.000 s NDIT=2\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.electronic - Total exposure time: 3600.000 s\u001b[0m\n" - ] - } - ], - "source": [ - "hdul = lms.readout(exptime=3600.)[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "2abde4cd-de93-4bd7-af67-caaeb044ab8f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(hdul)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "67c4d285-308a-49d7-8c90-841de71f89c2", - "metadata": {}, - "outputs": [], - "source": [ - "data_raw = hdul[1].data" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6647fcce-6f82-46f3-8c76-588926ec8e53", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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"\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 3\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 4\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 5\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 6\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 7\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 8\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 9\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 10\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 11\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 12\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 13\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 14\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 15\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 16\u001b[0m\n", - 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"\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 20\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 21\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 22\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 23\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 24\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 25\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 26\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 27\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 28\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n" - ] - } - ], - "source": [ - "rectified = lms[\"lms_spectral_traces\"].rectify_cube(hdul)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "c24cabac-fc7c-4175-b115-72fe7b454d47", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(5517, 28, 110)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "rectified.data.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "6f244780-d0fc-41da-9580-c04dcdb4912c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.imshow(rectified.data[:,:,3])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b2b798af-2bbd-455e-b42b-b4738e36100c", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/METIS/docs/example_notebooks/IFU_Template.ipynb b/METIS/docs/example_notebooks/IFU_Template.ipynb deleted file mode 100644 index a7153cf3..00000000 --- a/METIS/docs/example_notebooks/IFU_Template.ipynb +++ /dev/null @@ -1,1211 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "f51b9870", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import sys\n", - "import matplotlib.pyplot as plt\n", - "from astropy.io import fits\n", - "from astropy import units as u\n", - "from astropy.modeling.models import BlackBody\n", - "from scipy.interpolate import interp1d" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "c09323fa", - "metadata": {}, - "outputs": [], - "source": [ - "def donut_array_ellipse(a1, b1, ecc, inc, width, height):\n", - " array = np.zeros((height, width), dtype=np.float32)\n", - " \n", - " x0 = width // 2\n", - " y0 = height // 2\n", - " \n", - " # Outer ellipse\n", - " inc_rad = np.radians(inc)\n", - " cos_inc = np.cos(inc_rad)\n", - " sin_inc = np.sin(inc_rad)\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a1\n", - " norm_y = (y - y0) / b1\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " array[y, x] = 1\n", - " \n", - " ratio = b1 / a1\n", - " a2 = a1 * ratio\n", - " b2 = b1 * ratio\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a2\n", - " norm_y = (y - y0) / b2\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " array[y, x] = 0\n", - " \n", - " return array" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "0fda5400", - "metadata": {}, - "outputs": [], - "source": [ - "draw_donut_ellipse = donut_array_ellipse(800, 500, 0.8, 30, 2000, 2000)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "6ec704ed", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 6))\n", - "plt.imshow(draw_donut_ellipse, cmap='hot', origin='lower')\n", - "plt.title('Ellipse Donut')\n", - "plt.xlabel('X')\n", - "plt.ylabel('Y')\n", - "plt.colorbar()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "b112ae67", - "metadata": {}, - "outputs": [], - "source": [ - "def donut_array_ellipse_flux(a1, b1, ecc, inc, width, height):\n", - " array = np.zeros((height, width), dtype=np.float32)\n", - " \n", - " x0 = width // 2\n", - " y0 = height // 2\n", - " \n", - " # Outer ellipse\n", - " inc_rad = np.radians(inc)\n", - " cos_inc = np.cos(inc_rad)\n", - " sin_inc = np.sin(inc_rad)\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a1\n", - " norm_y = (y - y0) / b1\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " \n", - " dist = np.sqrt((x - x0)**2+ (y - y0)**2)\n", - " \n", - " intensity = 50 + 200 * np.exp(-dist**2 / (2 * (0.1 * width)**2))\n", - " \n", - " array[y, x] = intensity\n", - " \n", - " ratio = b1 / a1\n", - " a2 = a1 * ratio\n", - " b2 = b1 * ratio\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a2\n", - " norm_y = (y - y0) / b2\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " array[y, x] = 0\n", - " \n", - " return array" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "90e0e8c2", - "metadata": {}, - "outputs": [], - "source": [ - "draw_donut_ellipse_flux = donut_array_ellipse_flux(800, 500, 0.8, 30, 2000, 2000)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "77ae9b86", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 6))\n", - "plt.imshow(draw_donut_ellipse_flux, cmap='hot', origin='lower')\n", - "plt.title('Ellipse Donut with Flux variation')\n", - "plt.xlabel('X')\n", - "plt.ylabel('Y')\n", - "plt.colorbar()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "333dddd1", - "metadata": {}, - "outputs": [], - "source": [ - "def donut_array_ellipse_bb(a1, b1, ecc, inc, temp_disk, width, height):\n", - " array = np.zeros((height, width), dtype=np.float32)\n", - " \n", - " x0 = width // 2\n", - " y0 = height // 2\n", - " \n", - " # Outer ellipse\n", - " inc_rad = np.radians(inc)\n", - " cos_inc = np.cos(inc_rad)\n", - " sin_inc = np.sin(inc_rad)\n", - " \n", - " temp_disk = temp_disk * u.K\n", - " wav = np.linspace(1e-6, 100e-6, 1000) * u.meter\n", - " bb_disk = BlackBody(temperature=temp_disk)\n", - " fd_disk = bb_disk(wav)\n", - " interp_fd_disk = interp1d(np.arange(len(fd_disk)), fd_disk)(np.linspace(0, len(fd_disk) - 1, num=array.shape[0]))\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a1\n", - " norm_y = (y - y0) / b1\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " \n", - " dist = np.sqrt((x - x0)**2+ (y - y0)**2)\n", - " \n", - " intensity = 50 + 200 * np.exp(-dist**2 / (2 * (0.1 * width)**2))\n", - " \n", - " array[y, x] = intensity + interp_fd_disk[y]\n", - " \n", - " ratio = b1 / a1\n", - " a2 = a1 * ratio\n", - " b2 = b1 * ratio\n", - " \n", - " for y in range(height):\n", - " for x in range(width):\n", - " norm_x = (x - x0) / a2\n", - " norm_y = (y - y0) / b2\n", - " transformed_x = norm_x * cos_inc - norm_y * sin_inc\n", - " transformed_y = norm_x * sin_inc + norm_y * cos_inc\n", - " if transformed_x**2 / (1 -ecc**2) + transformed_y**2 <= 1:\n", - " array[y, x] = 0\n", - " \n", - " return array" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "42392aba", - "metadata": {}, - "outputs": [], - "source": [ - "draw_donut_ellipse_bb = donut_array_ellipse_bb(800, 500, 0.8, 30, 500, 2000, 2000)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "de614f0d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 6))\n", - "plt.imshow(draw_donut_ellipse_bb, cmap='hot', origin='lower')\n", - "plt.title('Ellipse Donut with Spectrum')\n", - "plt.xlabel('X')\n", - "plt.ylabel('Y')\n", - "plt.colorbar()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "0f8ea1aa", - "metadata": {}, - "outputs": [], - "source": [ - "filename = 'donut_ellipse.fits'\n", - "hdu = fits.PrimaryHDU(draw_donut_ellipse_bb)\n", - "hdu.writeto(filename, overwrite=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "c950323b", - "metadata": {}, - "outputs": [], - "source": [ - "from scopesim.source import source_templates as sim_tp" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "e3ed29e9", - "metadata": {}, - "outputs": [], - "source": [ - "src_star = sim_tp.star(flux=10*u.ABmag)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "ff638457", - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import datetime\n", - " \n", - "import shutil\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.colors import LogNorm\n", - "from astropy import units as u\n", - "from astropy.io import fits\n", - "from astropy.wcs import WCS\n", - "\n", - "import scopesim as sim\n", - "import scopesim_templates as sim_tp" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "424feba1", - "metadata": {}, - "outputs": [], - "source": [ - "hdul = fits.open('donut_ellipse.fits') #Donut\n", - "hdul[0].header[\"CDELT1\"] = (0.0057 / 3600) / 10 #CD1_1 \n", - "hdul[0].header[\"CDELT2\"] = (0.0057 / 3600) / 10 #CD2_2 #für metis 0.0057 / 3600\n", - "hdul[0].header[\"CRVAL1\"] = 0\n", - "hdul[0].header[\"CRVAL2\"] = 0\n", - "hdul[0].header[\"CRPIX1\"] = 1000.5 #(Naxis +1) /2\n", - "hdul[0].header[\"CRPIX2\"] = 1000.5\n", - "hdul[0].header[\"CUNIT1\"] = \"deg\"\n", - "hdul[0].header[\"CUNIT2\"] = \"deg\"\n", - "\n", - "#hdul[0].data -= 0.9 * np.median(hdul[0].data)\n", - "src_disk = sim.Source(image_hdu=hdul[0], flux=1e-6*u.Jy)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "fb3a19a8", - "metadata": {}, - "outputs": [], - "source": [ - "src = src_star + src_disk" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "2a50d522", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "src.plot()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "e34db6b4", - "metadata": {}, - "outputs": [], - "source": [ - "cmd_l = sim.UserCommands(use_instrument='METIS', set_modes=['img_lm'], \n", - " properties={\"!OBS.exptime\": 3600})\n", - "metis = sim.OpticalTrain(cmd_l)\n", - "metis['skycalc_atmosphere'].include=False\n", - "metis['detector_linearity'].include=False" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "2471b1cc", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " FOVs: 0%| | 0/1 [00:00" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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AMAzZnqnKfvaqXJPymI7m5mY1Nzc73l5TUxNz/bnnntOcOXP0t3/7tzH7R48ePeTYiPfee0+bNm3Stm3bNH36dEnSww8/rJkzZ2r37t06//zzU202AAAAgCzxdEzHgQMH9MILL2jx4sVDbtuwYYMqKyt14YUXauXKlTp69Gj0tq1btyoYDEYDDkmaMWOGgsGgtmzZYvtcPT096urqitkAAAAAZJ+ns1c99thjKisr07XXXhuz/6abbtL48eNVU1OjnTt3atWqVfrd736n1tZWSVJnZ6eqqqqGPF5VVZU6Ozttn2vNmjW6++673X8RAAAAKGDMXuUGT4OOX/ziF7rppps0cuTImP1LliyJXm5oaNCECRM0bdo07dixQ1OmTJEUHpBuZRiG7X5JWrVqlZYvXx693tXVpfr6ejdeBgAAAIBh8CzoeO2117R792499dRTCY+dMmWKiouLtWfPHk2ZMkU1NTU6cODAkOM+/vhjVVdX2z5GaWmpSktLh91uAAAAAO7ybEzH+vXrNXXqVE2ePDnhsbt27VJfX59qa2slSTNnzlQoFNKbb74ZPeaNN95QKBTSrFmzvGoyAAAAYNGv7M9WZd4KpLyqu7tb77//fvR6R0eH2tvbVVFRobPPPltSuLTp3/7t3/TP//zPQ+7/pz/9SRs2bNDVV1+tyspKvfvuu1qxYoUuuugiffnLX5YkXXDBBZo7d66WLFkSnUr3lltu0bx585i5CgAAAMgxKWc63nrrLV100UW66KKLJEnLly/XRRddpH/8x3+MHrNx40YZhqFvfvObQ+5fUlKi//t//6+uuuoqnX/++brjjjvU1NSkzZs3q6ioKHrchg0bNGnSJDU1NampqUlf+MIX9MQTT6TzGgEAAABkUcAwDD8Nx3dNV1eXgsGgRkmyH3oOAACAbDIkHZcUCoVUXl6e7ebEiPQlQ6F6lZd7uspESrq6BhQM7vPlOYvHP2cQAAAAQF4i6AAAAADgKU/X6QAAAABy20n563f6gWw3IC1+OoMAAAAA8hBBBwAAAABPUV4FAAAAOKK8yg1+OoMAAAAA8hBBBwAAAABPUV4FAAAAOKK8yg1+OoMAAAAA8hBBBwAAAABPUV4FAAAAOOqXv0qajGw3IC1kOgAAAAB4iqADAAAAgKcorwIAAAAcnZQUyHYjTCivAgAAAIAhCDoAAAAAeIqgAwAAAHB00oeb1NjYqIkTJ2rdunUevnb3MKYDAAAAyDFtbW0qLy/PdjOSRqYDAAAAgKcIOgAAAAB4ivIqAAAAwBFT5rqBTAcAAAAATxF0AAAAAPAU5VUAAACAE2PAXxVNfmpLCsh0AAAAAPAUQQcAAAAAT1FeBQAAADgZGNz8wk9tSQGZDgAAAACeIugAAAAA4CnKqwAAAAAn/YObX/ipLSkg0wEAAADAUwQdAAAAADxFeRUAAADghPIqV5DpAAAAAOApgg4AAAAAnqK8CgAAAHDC4oCuINMBAAAAwFMEHQAAAAA8RXkVAAAA4ITZq1xBpgMAAACApwg6AAAAAHiK8ioAAADACbNXuYJMBwAAAABPEXQAAAAA8BTlVQAAAICTAflrxijKqwAAAABgKIIOAAAAAJ6ivAoAAABwwuKAriDTAQAAAMBTBB0AAAAAPEV5FQAAAOCExQFdQaYDAAAAgKcIOgAAAAB4ivIqAAAAwAmzV7mCTAcAAAAATxF0AAAAAPAU5VUAAACAE8qrXEGmAwAAAMgxjY2NmjhxotatW5ftpiSFTAcAAACQY9ra2lReXp7tZiSNoAMAAABwwuKArqC8CgAAAICnCDoAAAAAeIryKgAAAMAJs1e5IuVMx6uvvqprrrlGdXV1CgQCevbZZ2Nuv/nmmxUIBGK2GTNmxBzT09OjpUuXqrKyUmPGjNH8+fP14Ycfxhxz+PBhtbS0KBgMKhgMqqWlRUeOHEn5BQIAAADIrpSDjmPHjmny5Mlau3at4zFz587V/v37o9uLL74Yc/uyZcv0zDPPaOPGjXr99dfV3d2tefPmqb//VOi2cOFCtbe3a9OmTdq0aZPa29vV0tKSanMBAAAAZFnK5VXNzc1qbm6Oe0xpaalqampsbwuFQlq/fr2eeOIJXXHFFZKkJ598UvX19dq8ebOuuuoqvffee9q0aZO2bdum6dOnS5IefvhhzZw5U7t379b555+farMBAACA1Bny14xRRrYbkB5PBpK//PLLqqqq0nnnnaclS5bo4MGD0du2b9+uvr4+NTU1RffV1dWpoaFBW7ZskSRt3bpVwWAwGnBI0owZMxQMBqPHAAAAAMgNrg8kb25u1vXXX69x48apo6NDd911ly677DJt375dpaWl6uzsVElJic4444yY+1VXV6uzs1OS1NnZqaqqqiGPXVVVFT3GqqenRz09PdHrXV1dLr4qAAAAAOlyPehYsGBB9HJDQ4OmTZumcePG6YUXXtC1117reD/DMBQIBKLXzZedjjFbs2aN7r777mG0HAAAALBg9ipXeL5OR21trcaNG6c9e/ZIkmpqatTb26vDhw/HHHfw4EFVV1dHjzlw4MCQx/r444+jx1itWrVKoVAouu3bt8/lVwIAAAAgHZ4HHYcOHdK+fftUW1srSZo6daqKi4vV2toaPWb//v3auXOnZs2aJUmaOXOmQqGQ3nzzzegxb7zxhkKhUPQYq9LSUpWXl8dsAAAAALIv5fKq7u5uvf/++9HrHR0dam9vV0VFhSoqKrR69Wpdd911qq2t1V/+8hf98Ic/VGVlpb7xjW9IkoLBoBYvXqwVK1Zo7Nixqqio0MqVKzVp0qTobFYXXHCB5s6dqyVLluihhx6SJN1yyy2aN28eM1cBAAAgcyivckXKQcdbb72lOXPmRK8vX75ckrRo0SI9+OCDeuedd/T444/ryJEjqq2t1Zw5c/TUU0+prKwsep/7779fI0aM0A033KDjx4/r8ssv16OPPqqioqLoMRs2bNAdd9wRneVq/vz5cdcGAQAAAOBPAcMwcnS23/i6uroUDAY1SpL90HMAAABkkyHpuMLruPmtND7Slwxtk8o/l+3WnNLVLQVn+POcxeP67FUAAABA3hiQvxYH9FNbUuD5QHIAAAAAhY2gAwAAAICnKK8CAAAAnDB7lSvIdAAAAADwFEEHAAAAAE9RXgUAAAA4obzKFWQ6AAAAAHiKoAMAAACApyivAgAAAJywOKAryHQAQJ4qynYDAAAYRNABAHkqR8caAgDyEOVVAJCnIpkOgg8AGIYB+euDlPIqAEC6vC6FotQKAJBNZDoAwKesgUKyP7QVmY71049zAIDCRdABAD4QCQ7sMhL9pv3mgMLMer8im/1O9wUAxMHsVa4g6ACALLOOvYgEGeYAwXpbOgg4AADZwpgOAPAJu+yE3e1mqQQSjOsAAGQLmQ4AyKJ4gYD5Nqfyq1QCCTIdAJCGfvnrA9RPbUkBQQcAZFg6GQc3shRMoQsAyBbKqwAgw7Ld6afMCgCQaWQ6AKBA2A1QBwAkQHmVK8h0AECBIMMBAMgWMh0AkEF0/AEAhYigAwAyKN4igAAAH2JxQFdQXgUAGUbAAQAoNAQdAJBBfgg4/NAGAEBhobwKADLEL539HJ34BACyg9mrXEGmAwAAAICnCDoAAAAAeIryKgAoMCwQCAApoLzKFWQ6AKAA+WV8CQCgMBB0AEABytEfygAAOYryKgDIADILAJCjDPlrQT4j2w1ID5kOAMgAP2UW/NQWAEBhIOgAAAAA4CmCDgAoMJR6AUAK+n24SWpsbNTEiRO1bt067167ixjTAQAZQEcfAOCmtrY2lZeXZ7sZSSPTAQAFiCAIAJBJZDoAAAAAJwPy1+xVfmpLCsh0AECBItsBAMgUgg4AcFkudOZNYxEBAPAc5VUA4LJ+hQMPOvUAkAf89iuNn9qSAjIdAOCBSOAh5UbmAwAALxF0AIBH+i1//SSZQIhgCQDgFsqrAMAF1nKqXCivsmszAMCC8ipXEHQAQIrMnfXIZafvAL935M3t67fZBwCAGwg6ACBF/Q6XpdgOe6513iPtJfgAALiNoAMAEnAqlYrst3bWzftyjTWgSvTaE+0DgJzH4oCuIOgAgAScOtJ2HXQpdwMOyb7cyrzfbnC89TYAAKwIOgAgCYkGXedyoOEk2SCKYAMAkAhBBwCkyG4gubXUKtek0nan10rwASAvMXuVK1inAwAScBq7YQ4+cjngkFILOCJ/zd/DTuM+AACQCDoAIEa8jrI52CiyuVxorOfBKkd/jAMAeIDyKgAwccpiRPY5KZTAw66sTKZ9dscAQE4bkL8+zHJ09ioyHQAKnlPAUMhZDCdO2Q2772M/fUcDALKLoANAwUvUYU6m5KrQWTMeBGsAADPKqwAUtGQXuYuXDUFi8Wb8AgBfY3FAV5DpAJD3kgkMrCVDBBPJcwocrDNdWW8j4ACAwkGmA0Deizedq7WMKtenvs2GeDNXxRtoDgAoHAQdAAqeXccYwxMvk0HwASCnsDigKyivAlAQnH6NJ8jIjhz9zgQApImgA0DecppFiXEb2ZXMuicAgPxCeRWAvBVvBiqyHN5zKluznncGmgPwNWavcgWZDgA5K1HQYM1o+K0sF/ZZJ4JBAMg/KQcdr776qq655hrV1dUpEAjo2Wefjd7W19en73//+5o0aZLGjBmjuro6/f3f/70++uijmMeYPXu2AoFAzHbjjTfGHHP48GG1tLQoGAwqGAyqpaVFR44cSetFAshPTgv4WVfNNgcblFb5Q7/lr/U2gkMAyC8pBx3Hjh3T5MmTtXbt2iG3ffbZZ9qxY4fuuusu7dixQ08//bT++Mc/av78+UOOXbJkifbv3x/dHnrooZjbFy5cqPb2dm3atEmbNm1Se3u7WlpaUm0ugAIRr/PKCtn+45ThKLJc5t8NQNb1+3DLQSmP6WhublZzc7PtbcFgUK2trTH7/uf//J/60pe+pL179+rss8+O7h89erRqampsH+e9997Tpk2btG3bNk2fPl2S9PDDD2vmzJnavXu3zj///FSbDSCPJVv/TwfW/xKNtWGsBwDkJs/HdIRCIQUCAZ1++ukx+zds2KDKykpdeOGFWrlypY4ePRq9bevWrQoGg9GAQ5JmzJihYDCoLVu22D5PT0+Purq6YjYAhcNu9Wt+Kc9d1vKrXFjbg/caADjzdPaqEydO6Ac/+IEWLlyo8vLy6P6bbrpJ48ePV01NjXbu3KlVq1bpd7/7XTRL0tnZqaqqqiGPV1VVpc7OTtvnWrNmje6++25vXggAX+BX7vyXbJYj2+8Fu5nQeG8CecpvJU1+aksKPAs6+vr6dOONN2pgYEAPPPBAzG1LliyJXm5oaNCECRM0bdo07dixQ1OmTJEkBQKBIY9pGIbtfklatWqVli9fHr3e1dWl+vp6N14KgAQy1eGKNwWu+Tq/OOc+u8yV+Xo2vnOdsi0EHACQmCflVX19fbrhhhvU0dGh1tbWmCyHnSlTpqi4uFh79uyRJNXU1OjAgQNDjvv4449VXV1t+xilpaUqLy+P2QB4z67j71VZk920qn77AcpNp1ku231gO+2zbrnMrrOfzcAy3oKTAAB7rn8XRQKOPXv2aPPmzRo7dmzC++zatUt9fX2qra2VJM2cOVOhUEhvvvlm9Jg33nhDoVBIs2bNcrvJAIbBOn7CqRZ/OJwyGubr+RJ4WAOFyOXI2lR2wUQ+BRjxZPrfuUiJg+gcn0wGQDIGfLjloJTLq7q7u/X+++9Hr3d0dKi9vV0VFRWqq6vT3/3d32nHjh36j//4D/X390fHYFRUVKikpER/+tOftGHDBl199dWqrKzUu+++qxUrVuiiiy7Sl7/8ZUnSBRdcoLlz52rJkiXRqXRvueUWzZs3j5mrgCyLdPycOmHJLvaWaifNWm5jfZ5c/6U5UbCQz8FEPNYxHObyKi8Gl+f6+wgA/CpgGIaRyh1efvllzZkzZ8j+RYsWafXq1Ro/frzt/V566SXNnj1b+/bt03/6T/9JO3fuVHd3t+rr6/XVr35VP/rRj1RRURE9/tNPP9Udd9yh559/XpI0f/58rV27dsgsWE66uroUDAY1SpL9KBAAbnCrk+Y0XiPROI5cl41gIkd/JIuyBr1uBR2pvrfIbgDDZ0g6rvBsp34rjY/0JUP3SuWjst2aU7qOS8Hv+fOcxZNy0JErCDoA73jd8Xeq3Tf/0p0PwUc2sxe5Gnh4keFI571EwAG4IyeCjp9K5SOz3ZpTuk5IwR/485zFU6gZewApsnb+++Ncd+u58mmsRoRfxl5k+/nTZbeCebwSu3hlgOlOeJBv70kAyARP1+kAkD8SdbTczjxYAw67cRy5Jlc7+n6WaHyRX2a8AoBCR9ABICl2WYdIh8+rzlyiwei5xI8BR6RNuVpqZWW3ernb2TKyHEAB8tuMUX5qSwr8+D0IwGecylbysfzJC37/oPVLyVc6zGN8rGM9zJmx4QSt1mmgAQCpI9MBICG7zpab63Dkq1zsxOciL6bOtSLgAIDhIegAkBaCDWfZCDasJUVmqXSYc7nkyov3JMEGAN+tAOqntqSAoAMAXOJlsJFsh9qpFC7V76jIKuiFym58iN11M6fzTBkiABB0AEhDvF/VC02kc+5FwOHmuaXjmxy7yRLSva+U39M/A0AqCDoApMzrWatyxWmWv27w8pym0vGNBFKFlu1wWozSepvTfZ0CcQIOIIdRXuUKxjkCSIm1U2b+i/QMZ6G6dJ4rGV4EVLnK+m8Tb3asQg/EAcAJ3ycAEkrmF95C4fb0srlw7nJ1Ot1kxfsRM165FUE3ACSP8iqgQNmt1mztPEX20dFyv9OdC8GGld05yIfyq3grmtvtS2UsU6H9PwHyEosDuiKff7wCYCPeIPB4U61ay0cKaUxHvn1Quvnvlm/nJhECDgBID5kOoMDYZS2slyXnX3mdbstHXnWoC+X85SP+7QAgPQQdACQNLa8y/6LrtOBcPnfA8iHgyMRK3VLstME5mvV3FRkOIM8we5UrCDoADFlLIFHZldO+fOHHkqHhnO9MrBFhne2qEIOPHO0HAEBGEHQAiAk0Uh0omy8yEWikek5zdXFAAg4AgBVBBwBJQwMPZEemFgdkhWz3cB6BPEd5lSsIOgDEKLQsR6ZKqVKZljXXFdIYjxz97geAjPNj6TKALCm0NTjy/QPQ7vVlKsjJ94DDbz98AoDfkekAUJCyHXCk2/lPtjOfzMBur0usEp3jXA1KCDaAAmPIXx9YRrYbkB6CDgC2zLX/+SaTAcdwz59dW+MFHk6vzY+ZB3Nb/dY2q0jZIQEHAKSHoANAwfBLsJEoEEmmncN5LX4cUO7HoMjML+cJAHIVQQeAuMwdrVzNevgl2HDiZfvMnWWnjn2mFhFMxG+BR7bPBwCf8NsgLj+1JQUEHQCSlmiV8nyU6DWm+tlvfTyvA47I32Ta6Yfgwy+BR45+pwOAbxF0AEhJLo31SLdDn8prG855SKd9yQQQ8dqUTKferVIicztSebxsBx4EHADgPoIOACnJldr2TAQcw3nsRO2zjrtwepxUnjuVf7d0/p0TjWPx8/vGz20DkGUD8kcKNsJPbUkBQQeAlJjX8siFbEcqsvV6MrVwYKoDyBOVW6XavlQCj0xnO/xQWgYA+YygA0Da/DjIPN2SpUwyt9HL53aakjbVDn2ybXS7457pwIOAAwC8Q9ABIG94HXCkcmwqA7dTkerigF6Kl6HxewfemqljHQ4Ajpi9yhUEHQBckUsDzCO8HDDudHyiYMApqDjN5nKi4yLt6Dc97nDX6MjGv68XGY9cep8CQD4g6ABQkDI1Q5WZXVlVpENtF1Sk8nhWRZbL5sAjFalM8ZvMY6ca6HidsbG2hWwHAHiDoAOAZzI52DyVzqmbAUeqnWK7Gazc7lgn8/rMmY8Ip2xVMu1LdYyIXzr21rb4pV0AfITyKlcQdABwlbnjmqmFBL36NdyrgGM463PYDdZONPuVdbyCU6ffaUpfp8cfzveeHwKPyHmh1AoAvJeJsYYACpAfZ7aSUp+JyUky62xYt9NM97O7vSjObYpzjNNzW19LpA3xXlNks2u3031zdMr4Iecu20EQAKSisbFREydO1Lp167LdlKSQ6QDgOvOv2Lm4nke6AUeilcDNx9gdm+hcWe+baPC+ecC5XWbBbtC53X47yazxkWudeKfMEIAC59PFAdva2lReXp7dtqSAoAOAZzLRaXN7LIebJVV2nfrhlFhF7hf57kt2hiy78RtO94lXSpXOIPR47wE/dOytJWdF8ke7ACDfEHQAcIW502Y3diAXMh7DCTgS3dcu4LDeJ9nF9ZIp7bJjF3jYlWFF9Fv+Wve7IdsrgTOQHAAyg6ADgCucOqjxyomGy80sh9sBh3Ugtjng8PKcxGuTeepcp0HjUmxGo99mn1W8qXiTzRpkM7tg/vfot/kLoMAxe5UrCDoAuC4Ts1ZlchaM4QQc1v3JDOq22z9gui1RAOC032mKXCXYlwwvFvDLJOt7lYADANxF0AHAdX4rpRpOW1IdNO40ONu6z5ptSKRYicdy2D2/VeQxrIsFRn7Is163k2qHfLjZjkwEM3algAQeAOAegg4ArrKO6ci24Qwe9yLgsN6WaAC33WMlWmPDqT1SuANvDTisnXrr4yfb6U9UZuX0+In2Z4KX41YA5LjIB6df5GhamaADgKv8lOVwY7aqZI+PF3CYMxvmsirzPrvHizcuI1GbzMGMeVxGv2Lbmsz3qHnq3XjtiByb6PswlcHjmfpuzfaAdgDIdwQdAFxlHoSb7XYMh12WYDgBh/V2uyDEabxHokHo8dpqDjh6JfWZricqn0q3vMguSEnEL519gg8A8AZBBwBX2E29mq3gI9nndKNtyQ4yNwcY1oDDHEgUmx43sr/YdJvdfezaZB6b0Te4mYOBSPBRpNjgwJqpMAce8W6zk8ysWNbL2cJsVQAc+XRxwFxD0AHAFdZxHH7IdsQznMHYTsfYBV7m48zBhl22w/y3WFLJ4PViSSNN152Oizxnn8Ln/8Tg5RODWyRoiGQ5IgPH7cqtrGNz4gUe5vs5cQo4/MLP71UAyAcEHQBcYy7L8boTZ+0sJyvddqUy0Nt6rDXQkGKDBrsgIhJojJRUOrhvpKTRkk6XVCGpbHAbY3ocSTom6ejg9qmkzsEtZGpTv2mT7LMdqfzy73R+4t0/2fEkmfxRj2wHAHiDoAOAa/yy+rjT8yfTpuEGMnZjLazjNiJbsU6VU0WCikiwMVqngo7TJdUNbvWDW0mdpHGDV84cfMCgwj30TklHJP1Z0rvSH3qkdyX9QdIHg88XyXJExnokGlxuzXZExAsI7AIav3foze0jAAEgicUBXULQAWBYrAPHc/SzUFLqU+Q6HWc3CNyazYhsRToVXBQrnLUYPfi3QtLfSpog6fOnSZom6WJJUwZvqB48cKROnfg+hVMdJxROc+yTPv+W9PnnpPb3pTck/U5DAwHrdbtsh10nPN5ChlZ+G8dhx/wa/dpGAMhFBB0AhiVeB83rjEeqJVZ27Ul0/2TXv3C6n3XweGSMRqSMKlI+ZQ02JkiaLOnsaklXSZovaYakvymRVCPpc4PPcHJwOxG79Q5If2N6oK9IX/zfUt2G8HO/oXCGI5JZiTAHGk6Bhx1rVsPpuvWyH1iDKjIcAOA+gg4Aw2LtoMUb2+C2eJ1/NwKeZO5vnUXKmuUwDxaPBBpFih2jERmXEZR0rqSLJJ1XKelaSd+U9BVJI6YonNoYqfBH90nTFkltdA9uJ6SSbqnkhDRyIHyXcklnSlVjpav/h/TZ4D0ig8qtM1xJQwMPWW5z6pxb1wXxO7vXFtmfC+0H4DFmr3IFQQeAYfFzp2w4gUcya3I4HWMdSG+dpSqSXSgzbTWKJiQUuE7StyXNPU3SpZLOUjizYQ04BgMMjTA944jB/YNKIqGFwiVZN0g1ndJF/yr9VeHgI5LxsGYjzBkPM7sgJLI/UcCR7rof2fiO9fN7GwByDUEHAFdlexB5Ional0ywYT3OLssRuW4XbIzRqWDjdIVjgZmSzhsv6XZJ/6+kMy5ROO9RqXAOJPJxfVJSj6RPFA44/qrwqHGzkbFXiz87dble0tekL78o7eyWPhp8lB6dCjLszpE1CLEbE2I3cNwqnexBpmevkgg4AMBtBB0Ahi2Xg4xE40JSXY8jXpYjMlDcHHA0KJzLqGqS9D1Jl1cN7jlH0liFMxyR7MYRSX+S9IbU9W50dip1KZwqqZF0vqQzKnQqMyIpcFIq7g2fjNGDx1wpjXtGekfhqXWLFc54RNpuzVTYBQvmtT7sBqPb8XPAYUUAAkASs1e5hKADgKv8mOlId+HCZAMOu+tOWY7ROrXWxmRJV0gqXyxphaQLvjC49xyFA45IOdUnkn4rdf9/0mZJL0lqV3j+248VHoxRqvDUubMkfeNT6epPpVF1g/cfORh4DIQHk5RJOj88zvz0wYeIjDdx6uQPWC6nE3CkIxulVTn6fQ4AvkbQAWBYrDP++C3gcGJuazKzYCUKMMz7rVPjRgaNj9GpTMdEDQYct0i6U9LZX1I4BXGOTgUcJyT9Vur6N+lJSc9J2iEd/iQcb3yqcJKjT9LIPqmiW/p8hzR2h8Lpi0UfSYG6wcc6KRV9Fm7cSEn14RhltGKn8LUbw2Geocwu4PBSJgIOpymfCT4AwD0EHQDSlo9rGqQaOJnLqqz7rWVVkSxHNOD4e4VLqs7+gsLjN2oGj5TCYcVD0qOfSv8i6Q3pjyHpfYXjich8VZFOebHCawIekDTrPanmXyRNl3SBFP6oHyEFTpOKBqKNOk3hgCgyo5Z5MLk1oIgXcOTS4n927ALKXHwdADxCeZUrCDoApM36uef3LIc1oHDKdkT222VAnFYcj/y1K6uKBBtjFB40frGksdcpHHCc+7cKLy1eqWhGQm9Ie/9FulfSc9LeD6WdCo/oMK/9Zw4CSgaf46jCoz5q3pX0oQaDjsjjnpCKBsd2fBw+NpLZiAQcfabHjZwD8/MkGjSeqMOeaoc+0+VVBBwA4A2CDgDDkuuDbc3jPVJZbDBewBFZaTxSVhXZqiU1SjpnmqQ7JF1YofB0uKfr1GDxt6Rt/0f6sWT8H+l1Sfs0ZOm/aHAQeQ2RthcrPA2uTkRaOiJ26+8N3/mjcBBzQkMHv0v2gYYbcuF9kuvvaQDwI4IOAMOSaKXqXGHNbjhdN7MLOKzjOSJjOU5XuKyqMSjpNoVXF4+WU41QuPu/XXr5VelH0qFXpdcUzkZEFvKLrO0RuV6i2MAg0t6RGjxwtHRqMLrp4/6IpHfDA8hPaGhgYc5iWMussjGbVKayHQQZAGyxOKArCDoAuCKXBpEn4hR4SLGv0/qazYGHdbaqOklflKRFkq6UVFKlU9PhnpD0obT9VekuqfN1aYvCsUH/4N/pCgctRYPX/0PhoMEc4BQpOkY8fPAEKRzuRBYSHHyqPZK2nAo6Iq/ZHMD0yr4Tbg0AMhEQZOr7lQwHAHgn2UoCAHCUjc5aOh9eiYIiu1/0E81mZB3HEZmtKjKWI5KdmCDpnPGSmhWus4pZXfyI9Emr9M9S12DAcUjhLMfHCudCpkiq+pk0NiSde1Y4COkbbEMkwDlN4YDjnKCkeZKqztapTIoknQhHLK9Iu3rCg877Brde0+VEA8Mjrzcd6dyPLyoAyH18lgMYtmyUWGXi12/rmAk5XJeGBh7msRw1CicedO3ghRElOhVwnJD0O+lxSc9Jbyg8C9VnCg8Y75Hpg/qbksrvkiaeemxzCVeNwsGI5klaKEkXKmYl896B8Ij058PJjkimI1Ku1af4YzjMYz9Os1z2UqYrCfIlYwfAJdZUcLa3HC2vIugAMGy5UpYynPYlWpfCXFYVCQQif+sknVMp6SuSKqToSuE6KemYtP8j6f9If/wsPGi8z7T1K7wex6eS9AVJV/8XHfu19JHC6wFWKFxAVTH48GMukbRSUvmVih2gfkL6q6TnpD98FF7M/KhiB6b3yjnwcPqysAs83O60Z+KLivU5AMBbjOkAMGzmTEemxnZk6heTZBcONG/FpsuRDISmKzxfbknkXicVLa3aIak9vDJHpMN/TIOL/g1eflrSrANSxf8Jr9XxB4UX94uUb82SVPUVSf8o6YuXSPp/FB7HMTieo/fT8ErmT0rvKBy0WLMcdquLO73eyFS7AzbXc5X1fQwAcE/K39uvvvqqrrnmGtXV1SkQCOjZZ5+Nud0wDK1evVp1dXUaNWqUZs+erV27dsUc09PTo6VLl6qyslJjxozR/Pnz9eGHH8Ycc/jwYbW0tCgYDCoYDKqlpUVHjhxJ+QUCyKxMlaZkq3Nrft5IdiOyRa6bjdbgEI4vKpx4kHQq4DghqTs8uOLTcHARmSQlch77FI5TjkraLOl5hbMUpysc0PyNpKskVV0h6b9KuvxKhSOcSIbjmKTO8ECRtdJve6TdOrXAYCS4iWQ6zIGH0xgW81/rfqfFEv0sEijnSsYOQIZlu5zKbstBKQcdx44d0+TJk7V27Vrb2++9917dd999Wrt2rdra2lRTU6Mrr7xSR48ejR6zbNkyPfPMM9q4caNef/11dXd3a968eervP3UWFy5cqPb2dm3atEmbNm1Se3u7Wlpa0niJADIl05+F2Zq+NfLXnN2wipyHMQpnJHSWwimQqJOntsFeb2QAemQbrVMz30Yep1pSUOFyqmmSLquURt0s6X9IuuR6SZfq1GKARyR1Sru6pLXSH9+W3lbsWI5IsGEONMwBR+Sv07mO9yWSK4FHkcNlAIB7Ui6vam5uVnNzs+1thmHoZz/7me68805de+21kqTHHntM1dXV+uUvf6nvfOc7CoVCWr9+vZ544gldccUVkqQnn3xS9fX12rx5s6666iq999572rRpk7Zt26bp06dLkh5++GHNnDlTu3fv1vnnn5/u6wXggWyVo2SixMr8y7010DA//4DpbyQ70a9w8HBGscIRQ7RHawo4pPCUU2dJdR2nVh0v1qnZqSKzYBUrHIScK2nSaQonNL4paelpkv5B4ZXNT0gKKfxIf5U6/iz9d+ngv0tbJf1F4eyGXVmV3YB5OeyzniOnMis33hteB5fm9kX+bXP0h0QA8C1Xv7M7OjrU2dmppqam6L7S0lJdeuml2rJliyRp+/bt6uvrizmmrq5ODQ0N0WO2bt2qYDAYDTgkacaMGQoGg9FjrHp6etTV1RWzAfCWXTlKrv9S7FRSZA44rFPGRjrs5oHYkVKlSOAQ07M3enWqvGpkOGXxNemLo6XJCscgYxWOU2oGr0+QdLGkr5dKk76k8NiNDZKWXinpHkmRH2OOSfpE0p+kv/5e+qnU9Wh4OMcfdGqxQXNZlV2wkWzA4STewHK/vUfMgWQOVy4A8MqAD7cc5OpA8s7OTklSdXV1zP7q6mp98MEH0WNKSkp0xhlnDDkmcv/Ozk5VVVUNefyqqqroMVZr1qzR3XffPezXACB51s5ZpjuTyQzytko00N1psb94AYfVaQpnOnoV7twf7JOqOhU7NdSIE4quFF5ZId3+qVQmXfgf0oW7pd7PTg0kLwoqHHlMVLh6qlnS+EskXabBYeoKBzCHJH0o6XfSn3ZI/1069vPwWJB3FTuO44ROlVWZAw/z63EKOOJ1yp2yBLmUPciltgJArvBk9qpAIBBz3TCMIfusrMfYHR/vcVatWqXly5dHr3d1dam+vj6VZgNIkd9+sR6uZAIOM6cfm4oU7tD3KFzktE9S1QcK9/bLFI5IjF4pEAk8PiedO1L6x4+kv5P0rlTycXhTjcJVUxMknVeucNTxRYVHd0QGi3frVMDxW+m3e6V7pcPPhzMc7wy24zPTlkxZld31VLMd8c6R3zr21nEskj/bCQC5yNWgo6Ym/ItbZ2enamtro/sPHjwYzX7U1NSot7dXhw8fjsl2HDx4ULNmzYoec+DAgSGP//HHHw/JokSUlpaqtLTUtdcCIDnmaUZzQaJ2Oo3hsN7f2hEd0Klx4ubZoD5VeLapqa8pnKE4ffDA0xSb7dBIacR50hdGSF8YHOuhEwpHHX8jqXJwGxM+VicUMzuV3pd6X5Iek/Q/pL/sDE9YtWewDUd1al0Op7U47Mqq4gUcyWT4443vSLZDn82peAk4AEQHq/lFjn4wuXoKx48fr5qaGrW2tkb39fb26pVXXokGFFOnTlVxcXHMMfv379fOnTujx8ycOVOhUEhvvvlm9Jg33nhDoVAoegyA7LNONZrLzJkMuzIqKf6itFJsiVIk8DiicNDR+aakVxSOACKphpMDik6bqxODjzJC4eBinMIjPM4dvB6ZkeqYwlmNvyo8+e1bkv5d2vaS9B1JS6VtO6UXFS6pigQc5rIqczutgYeUOOBwKilOZjxEOuM7MhVwJJoOGACQvpQzHd3d3Xr//fej1zs6OtTe3q6KigqdffbZWrZsme655x5NmDBBEyZM0D333KPRo0dr4cKFkqRgMKjFixdrxYoVGjt2rCoqKrRy5UpNmjQpOpvVBRdcoLlz52rJkiV66KGHJEm33HKL5s2bx8xVgM/kwyByu4DDibUDfJqGdrRP06mg44TCQcdvJC1cp3Di4tLBA0dLGtmbxCfxScUeFCmnape2fyb9b0lPSXs7wiFIZMB4ZNC4OcMRCTYiA90jnAKQyG0RTgHAcH54y3YJUyR4tiuvsrsOAEhdykHHW2+9pTlz5kSvR8ZRLFq0SI8++qi+973v6fjx4/rud7+rw4cPa/r06fr1r3+tsrKy6H3uv/9+jRgxQjfccIOOHz+uyy+/XI8++qiKik51WTZs2KA77rgjOsvV/PnzHdcGAZA91nKjRAO1/STegnaJBotHjokMZrd2zPsV7uifpnC24XeSyj6VrvmxpNslzVF4cHiZwoHHyMgYj25Jnxv8O1Knyq80+IifSIcPhlcx/4/wduj98OO/q/AaHMd0KrvRo1ODxvtMfyOvy2kRQKcOuJ1UO+V2QUY2Aw9rhoMgA0AMv80Y5ae2pCBgGIaR7UZ4oaurS8FgUKMkxR/CDmA4zB21bAQbqdSI2gUV1oAjmcdzehzzgPNihceLR9bYKJP0t5IaFU50jL1C4TEekxXOfpwuqVSnVgiMPFCfwtHDxwqnTHZKek3SVmnvp+ECqz2DN0emwo2swRHJbkQCDbuVxyPjOyKsQUiiLEe8Dnq878V4gU4qj+M2Ag4gswxJxyWFQiGVl5dnuzkxIn3J0NVSeXHi4zOlq08KvujPcxaPJ7NXASgs1l/FMxl8JDttbrKrTtt1cK2PbxdgWe8XySaYg5oPFA4EOiVN3CxN3iydcb7CgcffKjxGPDLIPPLT/0cKT3/1vqQ90sHPwo+zb3D7VKcCjMiYjT7FDhhPJuBINaCId3uO/ghHwAEAHiLoADAs2V6rYzgBh11ZlR1zJzpyH/M4ALtSrMiMS5HgI5K4OKBwJuIjhcuh6nZLZ+4OJzrGKHYAe//gsUcUDi4ODf49othMhvly5LrdoHanjEa6CwCmK9XnyOTsVZRYARiC2atcQdABwDXZKK9KZ4FAWe4Tb8xGMiKBh7ktdpmPE6bj+3RqOt0xCldWWWcCi4wLMWctIoGMXcmUNXNhnhq333L/RAFHoulx08ly+P17MtsD2gEgnxF0AHBdJsd3JAo4ki2rsuNURmXNdtjdz/qcvYod93FscN8JhTMXTuxmmIrMQmUulbIGG+bjB0y3JTNDk13HO5lsg5cBh9fZjlyaAAEAchFBB4Bhs0436pfOW7yAw27qWzuJXo+1zMou82K+LRIQ9Gno4oOJBleb18+wTm8bOa7Pct0uKLFmOVLJcDi1M5czHFLsDFa50F4AGUR5lSsIOgAMmx8//6yBQqLgIdJptvtesd7XGljEe2zzd1VvnOOT6exH2mdX6uQ0INwcoCQKapJtg9v88v7xU8AMAPmGoAOAK/ya7TBLpl1OY0QSBR7xHj9SCuW00nWiaWnNnIIOJ+aAw7oKeby1ONxaBNAvAUWyzJkrAIB7CDoAuMLaWcvG9LkRicqhEh2X7uD0eNkO6+UiDS2FSlW87Ey6WQovVhyPJ5ude6cAg4ADQAxD/poLPEdX2CPoAOCqZFbydstwS2xTzcg4HW8el2Gd8jbCGiCYp9Id7nlK5v7JlFelYzhjOVJ5bi++71mJHAAyh6ADgGus2Y1slVi5Ud6VzqKD5ue3u2y+T+R+qWYW4gV1yWR44o3vcHPFcTdl4nkIOADAWwQdANJi9wu9n8Z1eB14OO1PtNCe+Vf1ROVYRRoayJkHjdvdL9FjOrXP7YAjVzrxudJOAFnULymQ7UaY5OgHF0EHgLQ4BRx+GkCezLiS4bTZKesQr6wqFYke0+o0JRcoWAOXVAOORJK5r5++M62BoJ/aBgD5gqADQE5yc8r0ZAMP87iNyP3s2K1/Yb1fohXM02EeJ2J+TrsFBtN9zkyvx+F1aRXjOQAgMwg6ALgi0TgGt6Uyw5QbGZhk1viIPJd1vzUDYV1M0MruF/dUBuibMzzW8RvJBByJgqlU7jPcYzPB/P7wW9sA+ADlVa4g6ADgOj+VWCXLLjBJddyGU6fcaTHBeJ3ddKZxtb6GRMGGW7NHefX9l6mB6pRUAYD3CDoAuMpuHIUfxnoMtw1O9f7xFupzWigwkvmI19lNNDNVsvezPneiY7zm1849gQcAeIugA4AnzJ18rwKOdBfxS4bTquSR57Xbb3d8KsFXvE6v3YxWqbALOOwyCamOMfGqrMpP63ABKHAD8teHkp/akgKCDgCe8UOGwyyV9rg1JazToHFztiPVx0u2jdYAItlSsGTlY8DB2A4A8AZBBwBP5XLgYXdft58/1UHb1tmo4kkUWCQzpbAbcqUDX2RzebgZJgBAGEEHAFdler0OL0us3Opk2p0Pu3YnE0ykmwWIN2uV0+tMZcasRM+bLL9UDaQzkB9AnmL2KlcQdADIeW4FHukuapdKydZpca5nUiYW8MvVgENyJ+ACAJxC0AHAVfnUQUt13EYqj2uX+XCD3WNn498kV8ZwJINxHgAwfAQdAFyTzbEb5oX4EokXJKTTsRxOSVmyM2GZn8t8rF2HOJ3F/dxApxxAXmL2KlcQdABwhR8Gi6dSquRmB7nf9DdeMJPoHKUzg1U6ryOV0qpEAdVwz2MufXeS8QCA9GWrnBhAnvBDsBHhhw5sog6p0wJ96QQcqUhl3Q27oKbfYRsOP/x7pcNulisAQHxkOgCkzevF/9KRSpmVVxKtSu5Hmfz1PpsD6N1C1gMoIMxe5QqCDgBp8Xtn2i8dWy9Lk5Jlzij4ZSrYXM1yAADSQ9ABIGV+DzgizB1bPwQgbrKucG4V77Zs8VNb3MLUugCQHIIOACnJlYDDKtEK35kISiJZj3jPl6hjbl6RPN6xqSwCmAn5GHAAKBAD8tevCjn6gUrQASChXA00kpGtMqxsrUieaJ/bcvS7EQDgMoIOAAXP68Hn6a7h4SU//WiXL/ywKCMA+BVBBwBbfuskey2b2Y58W7Sv0LMbBBtAnhmQv2avytEP2XwbWwkAacnUgrPWDqmXz+nGWhpIXaEF7ACQDDIdAKLoLHk3xiNTJVaprDbuhRz9AS5l5n9P8+rtAAB7BB0AMsKP4xqc5OIYD69XNE+kUIKNCOu/nzkAKRrcyDIBecJv/5n91p4kEXQAkDT8TnCijnSuBBxmmV7dPN73iB/XgyiUQMOa1bC7HLludxkAQNABFDy3goFcDCqyyVySk6mSKDrC6bEGGXYBtvk2zjMADEXQARQwAoXkeZX1yFQH1c3nKZQMh5Xd/xeyG0AB8Nt/br+1J0kEHQBsJfpV18ypxCRfgpoBm8u5NPWfG99PhRpoWPVb/gIAkkPQARQYa4BgnYHH6XinQMPcCSuy3JbPzJ3wZAOQbAymp3PsLnMgzrkFgOQRdAAFyNpZitd5SnSbOdDIpRmq3JTKNLt+mjo3GWQ4TqGUCihQLA7oilyqEADgkmRnQkrmtnwsp0pHKt8BXndY3SqnytHvtWGzCy7MU+GaFfJ7HgBSQaYDKDCpdkiTKSPxYnG0XMyaDDfjYQ3gUjmvZDa8kWg8ExkPAEgOQQeAuBJ1qrxc5K6QAo9kskqJOsDpItBIHWM6gALit//sfmtPkgg6AKTNjYDAblBuPnTokg0+nF6n3X63zwnBhj2n9zVjOgAgfQQdALLCrgNn/dU/17IcEQOWv34cPEfAEV+uvwcBwG8IOgCkbDgdsWRLpujseSMfgg2vA4JcLOsD4CFmr3KFH3+AA+BTww027C4nuk8+lLH44fsh12ejspbfeTW+JfL45sfNh/cgAGQbQQeApAxn4b9kV3G2dvDy6dfmXO7w+4HTgHsvggK7hTCLLNcBAKmhvAqAJ4bbEXQaSJ3LHb5UZrZy6/nySaLZvuyChXTYBRgMIgcKmN8+TP3WniQRdABIKJXOm1cdMmuHM1dXQDd/V5wm9web5+h3UdKS+TePvDcSBSHJjg0hyACA4aO8CoCjZBelS7Z8Kt02OP3KnGsBh5U14Eg3YBhQ7o/ZsBNvOuF45X7x7mddYdzpGPOxuf4+AwA/INMBIG2ZKjmxy3DkU4dwwHL5NOVfAJGseAGF+X0wnEDXujZMvECWLAcA9Usyst0Ikxz9giDTASAuu05YJmf0ifd8+RBw2MnR7xNXOAUDMu1za1HKePsL6f0GAJlA0AFgiMhsPdbOvl9+9TXPJuRlaRcyzxpU2L3/vP63dnoe3mMAkD7KqwAMEa/jl23W0piIXB1Yjlh2/7YAkFV+Sz/7rT1JItMBwJafO35OazVQj59bzBkFp38rp5moAAC5haADgG+lm7XIp0Hm+S5R+R7BBgDkB8qrAPhWKh1Ou7Icyq38yzpjFGNzAPgWs1e5gkwHgLyQqLNKZ9YfrNMdxxvDQcAIAPmDoANA3rAOfjd3aBmg7A/Wmcfi/Zvw7wUA+YPyKgB5w2mKU2vgYV1sEN4wB35Os6ERDALwPcqrXEGmA0DeKnK47Nf1R/KFXQbDadVvzj0AFAaCDgB5y24WK7vLZDuGxymAy/Zq9gAA/3A96DjnnHMUCASGbLfddpsk6eabbx5y24wZM2Ieo6enR0uXLlVlZaXGjBmj+fPn68MPP3S7qQAKRL/sO7yJfpFHcuzK1VIpYSPoA+BrAz7ccpDrQUdbW5v2798f3VpbWyVJ119/ffSYuXPnxhzz4osvxjzGsmXL9Mwzz2jjxo16/fXX1d3drXnz5qm/n+4AAHfEK7eCvWTPkXUAv1uPCwDIXa4PJD/zzDNjrv/0pz/Vueeeq0svvTS6r7S0VDU1Nbb3D4VCWr9+vZ544gldccUVkqQnn3xS9fX12rx5s6666iq3mwyggDgNXKbUKjG7c2M3WNw6cxgAAJ6O6ejt7dWTTz6pb33rWwoEAtH9L7/8sqqqqnTeeedpyZIlOnjwYPS27du3q6+vT01NTdF9dXV1amho0JYtW7xsLoAC4LQInVMHmY5zmFM2yCm4iBfYAUBOGdDQOt1sbjlaXuXplLnPPvusjhw5optvvjm6r7m5Wddff73GjRunjo4O3XXXXbrsssu0fft2lZaWqrOzUyUlJTrjjDNiHqu6ulqdnZ2Oz9XT06Oenp7o9a6uLtdfD4D8lmjgeSFzynLYXU8lEAEAFAZPg47169erublZdXV10X0LFiyIXm5oaNC0adM0btw4vfDCC7r22msdH8swjJhsidWaNWt09913u9NwAHkvXplVKuMRMBTBBQDAyrPyqg8++ECbN2/Wt7/97bjH1dbWaty4cdqzZ48kqaamRr29vTp8+HDMcQcPHlR1dbXj46xatUqhUCi67du3b/gvAkDeSracqtDW80j0Gp2mvSVAA5C3sj1TFbNXxffII4+oqqpKX/3qV+Med+jQIe3bt0+1tbWSpKlTp6q4uDg665Uk7d+/Xzt37tSsWbMcH6e0tFTl5eUxGwAMh9P4j3wWL3iIDBA3b+bbAABw4kl51cDAgB555BEtWrRII0aceoru7m6tXr1a1113nWpra/WXv/xFP/zhD1VZWalvfOMbkqRgMKjFixdrxYoVGjt2rCoqKrRy5UpNmjQpOpsVAGSCeTYm8/VEklmbwq+cXqs5AGNmKgBAqjwJOjZv3qy9e/fqW9/6Vsz+oqIivfPOO3r88cd15MgR1dbWas6cOXrqqadUVlYWPe7+++/XiBEjdMMNN+j48eO6/PLL9eijj6qoKFe/xgHkonilVfE+jXL9k8oug2EONAg4ABSUfknOw4ozz8h2A9ITMAwjR5seX1dXl4LBoEbJX+8TALnNaaXtXM5u2Ek0E5UZmQ8A6TIkHVd4nTa/lcZH+pKhz0nlPupMdhlSsNuf5yweT2evAoB849S5zoeAI91Zuwg4AACJEHQAQJqsq3HbrcqdC6zBRqKyMoIMAAWF8ipXeLoiOQDkE2sQkS8dcPNMVMlMmQsAQKrIdABAkuKt4WG3zy4D4icEEACATCHTAQAuSLS6uZ/ZBUR+DJIAICuyvRCgTxYH7Ojo0Jw5czRx4kRNmjRJx44dS+n+ZDoAwCPpDszOhEQrredCsAQAyJybb75ZP/nJT3TxxRfr008/VWlpaUr3J+gAAI/5sbwqV7IwAIDs27Vrl4qLi3XxxRdLkioqKlJ+DMqrAMAjRZa/fuLHQAgAfKnfh1uKXn31VV1zzTWqq6tTIBDQs88+O+SYBx54QOPHj9fIkSM1depUvfbaa9Hb9uzZo8997nOaP3++pkyZonvuuSflNhB0AIAL7Drwfl3B22/tAQB469ixY5o8ebLWrl1re/tTTz2lZcuW6c4779Tbb7+tiy++WM3Nzdq7d68kqa+vT6+99prWrVunrVu3qrW1Va2trSm1gaADAFyQS1PNJjs9LgDAv7q6umK2np4ex2Obm5v1k5/8RNdee63t7ffdd58WL16sb3/727rgggv0s5/9TPX19XrwwQclSWeddZYaGxtVX1+v0tJSXX311Wpvb0+pvQQdAJABlDIBQI7KdimVQ3lVfX29gsFgdFuzZk1aL6+3t1fbt29XU1NTzP6mpiZt2bJFktTY2KgDBw7o8OHDGhgY0KuvvqoLLrggpedhIDkAZABjKAAAbtq3b5/Ky8uj11OdTSrik08+UX9/v6qrq2P2V1dXq7OzU5I0YsQI3XPPPbrkkktkGIaampo0b968lJ6HoAMAAADIMeXl5TFBx3AFAoGY64ZhxOxrbm5Wc3Nz2o9P0AEAGeCnLId5/RDGdQBAAsbglqcqKytVVFQUzWpEHDx4cEj2YzgY0wEAGeDHzr0f2wQAyKySkhJNnTp1yGxUra2tmjVrlmvPQ6YDAAAAyGPd3d16//33o9c7OjrU3t6uiooKnX322Vq+fLlaWlo0bdo0zZw5Uz//+c+1d+9e3Xrrra61gaADAAAAcJDmenyeSactb731lubMmRO9vnz5cknSokWL9Oijj2rBggU6dOiQfvzjH2v//v1qaGjQiy++qHHjxrnUailgGEZeVql1dXUpGAxqlKRAwqMBwHt+GNfhpy9OADAkHZcUCoVcHRTthkhf8lNJfmpZl6QK+fOcxcOYDgDIAL8N2vZDAAQAKByUVwFABvhtnQ4/BUAA4Gf5UF7lB2Q6ACBD/PBF4afABwBQOAg6ACBD6PADAAoV5VUAkCHZLrHK9vMDQC4aGNz8wk9tSQWZDgAoEAQcAIBsIegAgAzyw7gOAAAyjfIqAMigbJdXAQBSw+xV7iDTAQA+k+wXSq5+8QAACg9BBwBkUCqBQr/pr90vbalmTRjTAQDIFsqrAMBnzMFBZMYp88xT6cxCRVYEANLD7FXuINMBABk0nOxEv2lfMkGE3+qQAQCFi6ADADIomUDAfEzkcpFigw1r8NJv85dyKgDIX42NjZo4caLWrVuX7aYkhfIqAPAJczBil82wBhLWAMQu8LA+LgAgNX7LGkfa0tbWpvLy8qy2JRVkOgDAR6wBhPU2py8+u6wGmQ4AgF+Q6QAAH3EKKvrjHJPMfQAAyCaCDgDIguHORpXsYHIAwPAMyF+ft7k6exVBBwBkSbzsRSr3BQDA7xjTAQAAAMBTZDoAAAAABywO6A4yHQAAAAA8RdABAAAAwFOUVwEAAAAO/Lo4YK4h0wEAAADAUwQdAAAAADxFeRUAAADggPIqd5DpAAAAAOApgg4AAAAAnqK8CgAAAHDA4oDuINMBAAAAwFMEHQAAAAA8RXkVAAAA4IDZq9xBpgMAAACApwg6AAAAgBzT2NioiRMnat26ddluSlIorwIAAAAc+HX2qra2NpWXl2e1Lakg0wEAAADAUwQdAAAAADxFeRUAAADgYED+mjHKT6VeqSDTAQAAAMBTBB0AAAAAPEV5FQAAAOCAxQHdQaYDAAAAgKcIOgAAAAB4ivIqAAAAwIFfFwfMNWQ6AAAAAHiKoAMAAACApyivAgAAABwwe5U7XM90rF69WoFAIGarqamJ3m4YhlavXq26ujqNGjVKs2fP1q5du2Ieo6enR0uXLlVlZaXGjBmj+fPn68MPP3S7qQAAAAAywJPyqgsvvFD79++Pbu+88070tnvvvVf33Xef1q5dq7a2NtXU1OjKK6/U0aNHo8csW7ZMzzzzjDZu3KjXX39d3d3dmjdvnvr7czW2AwAAAAqXJ+VVI0aMiMluRBiGoZ/97Ge68847de2110qSHnvsMVVXV+uXv/ylvvOd7ygUCmn9+vV64okndMUVV0iSnnzySdXX12vz5s266qqrvGgyAAAAMATlVe7wJNOxZ88e1dXVafz48brxxhv15z//WZLU0dGhzs5ONTU1RY8tLS3VpZdeqi1btkiStm/frr6+vphj6urq1NDQED3GTk9Pj7q6umI2AAAAANnnetAxffp0Pf744/rVr36lhx9+WJ2dnZo1a5YOHTqkzs5OSVJ1dXXMfaqrq6O3dXZ2qqSkRGeccYbjMXbWrFmjYDAY3err611+ZQAAAADS4Xp5VXNzc/TypEmTNHPmTJ177rl67LHHNGPGDElSIBCIuY9hGEP2WSU6ZtWqVVq+fHn0eldXF4EHAAAAhoXFAd3h+TodY8aM0aRJk7Rnz57oOA9rxuLgwYPR7EdNTY16e3t1+PBhx2PslJaWqry8PGYDAAAAkH2eBx09PT167733VFtbq/Hjx6umpkatra3R23t7e/XKK69o1qxZkqSpU6equLg45pj9+/dr586d0WMAAAAA5A7Xy6tWrlypa665RmeffbYOHjyon/zkJ+rq6tKiRYsUCAS0bNky3XPPPZowYYImTJige+65R6NHj9bChQslScFgUIsXL9aKFSs0duxYVVRUaOXKlZo0aVJ0NisAAAAgE5i9yh2uBx0ffvihvvnNb+qTTz7RmWeeqRkzZmjbtm0aN26cJOl73/uejh8/ru9+97s6fPiwpk+frl//+tcqKyuLPsb999+vESNG6IYbbtDx48d1+eWX69FHH1VRUZHbzQUAAADgsYBhGEa2G+GFrq4uBYNBjZIUf4g6AAAAssGQdFxSKBTy3XjcSF/yN5I+l+3GmHRLukz+PGfxeD6mAwAAAMhVhk7NYOWHLZItaGxs1MSJE7Vu3TrPXrubPFmRHAAAAIB32trayHQAAAAAQASZDgAAAMABs1e5g0wHAAAAAE8RdAAAAADwFOVVAAAAgAPKq9xBpgMAAACApwg6AAAAAHiK8ioAAADAQWRRPr/wU1tSQaYDAAAAgKcIOgAAAAB4ivIqAAAAwAGzV7mDTAcAAAAATxF0AAAAAPAU5VUAAACAA8qr3EGmAwAAAICnCDoAAAAAeIryKgAAAMABiwO6g0wHAAAAAE8RdAAAAADwFOVVAAAAgIMB+WvGKMqrAAAAAMAGQQcAAAAAT1FeBQAAADhg9ip3kOkAAAAA4CmCDgAAAACeIugAAAAA4CmCDgAAAMBBvw83SWpsbNTEiRO1bt06z167mxhIDgAAAOSYtrY2lZeXZ7sZSSPTAQAAAMBTZDoAAAAAB+aSJj/wU1tSQaYDAAAAgKcIOgAAAAB4ivIqAAAAwAErkruDTAcAAAAATxF0AAAAAPAU5VUAAACAA2avcgeZDgAAAACeIugAAAAA4CnKqwAAAAAHlFe5g0wHAAAAAE8RdAAAAADwFOVVAAAAgAND/lqQz8h2A9JEpgMAAACApwg6AAAAAHiK8ioAAADAAbNXuYNMBwAAAABPEXQAAAAA8BTlVQAAAICDAflr9io/tSUVZDoAAAAAeIqgAwAAAICnKK8CAAAAHDB7lTvIdAAAAADwFEEHAAAAAE9RXgUAAAA4oLzKHWQ6AAAAAHiKoAMAAACApyivAgAAABywOKA7yHQAAAAA8BRBBwAAAABPUV4FAAAAOGD2KneQ6QAAAAByTGNjoyZOnKh169ZluylJIdMBAAAA5Ji2tjaVl5dnuxlJI+gAAAAAHAzIXyVNzF41aM2aNWpsbFRZWZmqqqr09a9/Xbt374455uabb1YgEIjZZsyYEXNMT0+Pli5dqsrKSo0ZM0bz58/Xhx9+6HZzAQAAAHjM9aDjlVde0W233aZt27aptbVVJ0+eVFNTk44dOxZz3Ny5c7V///7o9uKLL8bcvmzZMj3zzDPauHGjXn/9dXV3d2vevHnq7/dTrAkAAAAgEdfLqzZt2hRz/ZFHHlFVVZW2b9+uSy65JLq/tLRUNTU1to8RCoW0fv16PfHEE7riiiskSU8++aTq6+u1efNmXXXVVW43GwAAABiCxQHd4fnsVaFQSJJUUVERs//ll19WVVWVzjvvPC1ZskQHDx6M3rZ9+3b19fWpqakpuq+urk4NDQ3asmWL7fP09PSoq6srZgMAAACQfZ4GHYZhaPny5frKV76ihoaG6P7m5mZt2LBBv/nNb/TP//zPamtr02WXXaaenh5JUmdnp0pKSnTGGWfEPF51dbU6Ozttn2vNmjUKBoPRrb6+3rsXBgAAACBpns5edfvtt+v3v/+9Xn/99Zj9CxYsiF5uaGjQtGnTNG7cOL3wwgu69tprHR/PMAwFAgHb21atWqXly5dHr3d1dRF4AAAAYFhYHNAdnmU6li5dqueff14vvfSSzjrrrLjH1tbWaty4cdqzZ48kqaamRr29vTp8+HDMcQcPHlR1dbXtY5SWlqq8vDxmAwAAAJB9rgcdhmHo9ttv19NPP63f/OY3Gj9+fML7HDp0SPv27VNtba0kaerUqSouLlZra2v0mP3792vnzp2aNWuW200GAAAA4CHXy6tuu+02/fKXv9Rzzz2nsrKy6BiMYDCoUaNGqbu7W6tXr9Z1112n2tpa/eUvf9EPf/hDVVZW6hvf+Eb02MWLF2vFihUaO3asKioqtHLlSk2aNCk6mxUAAADgNWavcofrQceDDz4oSZo9e3bM/kceeUQ333yzioqK9M477+jxxx/XkSNHVFtbqzlz5uipp55SWVlZ9Pj7779fI0aM0A033KDjx4/r8ssv16OPPqqioiK3mwwAAADAQwHDMIxsN8ILXV1d4eyKJPuh5wAAAMgmQ9JxhZdY8Nt43Ehf8m5JI7PdGJMTkn4kf56zeDydvQoAAADIZcxe5Q7PFwcEAAAAUNgIOgAAAAB4ivIqAAAAwAHlVe4g0wEAAADAUwQdAAAAADxFeRUAAADggMUB3UGmAwAAAICnCDoAAAAAeIryKgAAAMDBgPw1YxTlVQAAAABgg6ADAAAAgKcorwIAAAAcsDigO8h0AAAAAPAUQQcAAAAAT1FeBQAAADhgcUB3kOkAAAAA4CmCDgAAAACeorwKAAAAcMDsVe4g0wEAAADAUwQdAAAAADxFeRUAAADggNmr3EGmAwAAAICnCDoAAAAAeIryKgAAAMABs1e5g0wHAAAAAE8RdAAAAADwFEEHAAAA4KDfh5skNTY2auLEiVq3bp1nr91NjOkAAAAAckxbW5vKy8uz3YykkekAAAAA4CkyHQAAAIADQ/5akM/IdgPSRKYDAAAAgKcIOgAAAAB4ivIqAAAAwAGLA7qDTAcAAAAATxF0AAAAAPAU5VUAAACAA8qr3EGmAwAAAICnCDoAAAAAeIryKgAAAMDBgPy1OKCf2pIKMh0AAAAAPEXQAQAAAMBTlFcBAAAADpi9yh1kOgAAAAB4iqADAAAAgKcorwIAAAAcMHuVO8h0AAAAAPAUQQcAAAAAT1FeBQAAADhg9ip3kOkAAAAA4CmCDgAAAACeorwKAAAAcDAgf5U0MXsVAAAAANgg6AAAAADgKcqrAAAAAAcsDugOMh0AAAAAPEXQAQAAAMBTlFcBAAAADvrlr1/p/TSTVir8dA4BAAAA5CGCDgAAAACeorwKAAAAcEB5lTv8dA4BAAAA5CGCDgAAAACeorwKAAAAcMDigO7wfabjgQce0Pjx4zVy5EhNnTpVr732WrabBAAAACAFvg46nnrqKS1btkx33nmn3n77bV188cVqbm7W3r17s900AAAAAEkKGIZhZLsRTqZPn64pU6bowQcfjO674IIL9PWvf11r1qyJe9+uri4Fg0GNkhTwuJ0AAABInSHpuKRQKKTy8vJsNydGpC95laTibDfGpE/Sr+TPcxaPbzMdvb292r59u5qammL2NzU1acuWLVlqFQAAAIBU+XYg+SeffKL+/n5VV1fH7K+urlZnZ+eQ43t6etTT0xO9HgqFJIUjaAAAAPhPpJ/m48IbuMS3QUdEIBBbHGUYxpB9krRmzRrdfffdQ/af8KxlAAAAcMPRo0cVDAaz3QxbzF7lDt8GHZWVlSoqKhqS1Th48OCQ7IckrVq1SsuXL49eP3LkiMaNG6e9e/f69k3sJ11dXaqvr9e+fftyqj4wWzhfyeNcpYbzlRrOV/I4V6nhfKUm3fNlGIaOHj2quro6D1sHP/Bt0FFSUqKpU6eqtbVV3/jGN6L7W1tb9bWvfW3I8aWlpSotLR2yPxgM8mGRgvLycs5XCjhfyeNcpYbzlRrOV/I4V6nhfKUmnfPFj8OFwbdBhyQtX75cLS0tmjZtmmbOnKmf//zn2rt3r2699dZsNw0AAAAFYEBSf7YbYUJ5lQcWLFigQ4cO6cc//rH279+vhoYGvfjiixo3bly2mwYAAAAgSb4OOiTpu9/9rr773e+mfL/S0lL96Ec/si25wlCcr9RwvpLHuUoN5ys1nK/kca5Sw/lKDecLifh6cUAAAAAgGyKLA86Wv36lPynpZbE4IAAAAADEIOgAAAAA4Ck/ZYsAAAAAX2FxQHeQ6QAAAAByTGNjoyZOnKh169ZluylJydug44EHHtD48eM1cuRITZ06Va+99lq2m5Rxa9asUWNjo8rKylRVVaWvf/3r2r17d8wxN998swKBQMw2Y8aMmGN6enq0dOlSVVZWasyYMZo/f74+/PDDTL4Uz61evXrIeaipqYnebhiGVq9erbq6Oo0aNUqzZ8/Wrl27Yh6jEM5TxDnnnDPkfAUCAd12222SeF+9+uqruuaaa1RXV6dAIKBnn3025na33k+HDx9WS0uLgsGggsGgWlpadOTIEY9fnfvina++vj59//vf16RJkzRmzBjV1dXp7//+7/XRRx/FPMbs2bOHvOduvPHGmGPy4Xwlem+59X8vH86VlPh82X2OBQIB/dM//VP0mEJ5byXTZ+Czy1/a2tr07rvvRr97/S4vg46nnnpKy5Yt05133qm3335bF198sZqbm7V3795sNy2jXnnlFd12223atm2bWltbdfLkSTU1NenYsWMxx82dO1f79++Pbi+++GLM7cuWLdMzzzyjjRs36vXXX1d3d7fmzZun/n4/LZUzfBdeeGHMeXjnnXeit91777267777tHbtWrW1tammpkZXXnmljh49Gj2mUM6TFP6gM5+r1tZWSdL1118fPaaQ31fHjh3T5MmTtXbtWtvb3Xo/LVy4UO3t7dq0aZM2bdqk9vZ2tbS0eP763BbvfH322WfasWOH7rrrLu3YsUNPP/20/vjHP2r+/PlDjl2yZEnMe+6hhx6KuT0fzlei95bkzv+9fDhXUuLzZT5P+/fv1y9+8QsFAgFdd911MccVwnsrmT5DoX529ftwy0lGHvrSl75k3HrrrTH7Pv/5zxs/+MEPstQifzh48KAhyXjllVei+xYtWmR87Wtfc7zPkSNHjOLiYmPjxo3RfX/961+N0047zdi0aZOXzc2oH/3oR8bkyZNtbxsYGDBqamqMn/70p9F9J06cMILBoPG//tf/MgyjcM6Tk3/4h38wzj33XGNgYMAwDN5XZpKMZ555JnrdrffTu+++a0gytm3bFj1m69athiTjD3/4g8evyjvW82XnzTffNCQZH3zwQXTfpZdeavzDP/yD433y8XzZnSs3/u/l47kyjOTeW1/72teMyy67LGZfIb63DGNon6EQP7tCoZAhyfiyZFzqo+3LkiHJCIVC2T5FKcm7TEdvb6+2b9+upqammP1NTU3asmVLllrlD6FQSJJUUVERs//ll19WVVWVzjvvPC1ZskQHDx6M3rZ9+3b19fXFnM+6ujo1NDTk3fncs2eP6urqNH78eN14443685//LEnq6OhQZ2dnzDkoLS3VpZdeGj0HhXSerHp7e/Xkk0/qW9/6lgKBQHQ/7yt7br2ftm7dqmAwqOnTp0ePmTFjhoLBYN6fw1AopEAgoNNPPz1m/4YNG1RZWakLL7xQK1eujPn1tZDO13D/7xXSuTI7cOCAXnjhBS1evHjIbYX43rL2GfjswnDl3exVn3zyifr7+1VdXR2zv7q6Wp2dnVlqVfYZhqHly5frK1/5ihoaGqL7m5ubdf3112vcuHHq6OjQXXfdpcsuu0zbt29XaWmpOjs7VVJSojPOOCPm8fLtfE6fPl2PP/64zjvvPB04cEA/+clPNGvWLO3atSv6Ou3eUx988IEkFcx5svPss8/qyJEjuvnmm6P7eF85c+v91NnZqaqqqiGPX1VVldfn8MSJE/rBD36ghQsXxiyKddNNN2n8+PGqqanRzp07tWrVKv3ud7+Llv4Vyvly4/9eoZwrq8cee0xlZWW69tprY/YX4nvLrs9QyJ9d/ZICCY/KnFwtr8q7oCPC/IurFP4PZN1XSG6//Xb9/ve/1+uvvx6zf8GCBdHLDQ0NmjZtmsaNG6cXXnhhyAevWb6dz+bm5ujlSZMmaebMmTr33HP12GOPRQdhpvOeyrfzZGf9+vVqbm5WXV1ddB/vq8TceD/ZHZ/P57Cvr0833nijBgYG9MADD8TctmTJkujlhoYGTZgwQdOmTdOOHTs0ZcoUSYVxvtz6v1cI58rqF7/4hW666SaNHDkyZn8hvrec+gwSn11IX96VV1VWVqqoqGhItHzw4MEh0XmhWLp0qZ5//nm99NJLOuuss+IeW1tbq3HjxmnPnj2SpJqaGvX29urw4cMxx+X7+RwzZowmTZqkPXv2RGexiveeKtTz9MEHH2jz5s369re/Hfc43lenuPV+qqmp0YEDB4Y8/scff5yX57Cvr0833HCDOjo61NraGpPlsDNlyhQVFxfHvOcK6XxFpPN/rxDP1Wuvvabdu3cn/CyT8v+95dRn4LMLw5V3QUdJSYmmTp0aTXtGtLa2atasWVlqVXYYhqHbb79dTz/9tH7zm99o/PjxCe9z6NAh7du3T7W1tZKkqVOnqri4OOZ87t+/Xzt37szr89nT06P33ntPtbW10bS6+Rz09vbqlVdeiZ6DQj1PjzzyiKqqqvTVr3417nG8r05x6/00c+ZMhUIhvfnmm9Fj3njjDYVCobw7h5GAY8+ePdq8ebPGjh2b8D67du1SX19f9D1XSOfLLJ3/e4V4rtavX6+pU6dq8uTJCY/N1/dWoj5DIX92Dfhwy0kZHrieERs3bjSKi4uN9evXG++++66xbNkyY8yYMcZf/vKXbDcto/7zf/7PRjAYNF5++WVj//790e2zzz4zDMMwjh49aqxYscLYsmWL0dHRYbz00kvGzJkzjb/5m78xurq6oo9z6623GmeddZaxefNmY8eOHcZll11mTJ482Th58mS2XprrVqxYYbz88svGn//8Z2P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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,10))\n", - "plt.imshow(hdus[0][1].data, norm=LogNorm(), origin='lower', cmap='hot')\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "446bb3e8", - "metadata": {}, - "outputs": [], - "source": [ - "cmd_n = sim.UserCommands(use_instrument='METIS', set_modes=['img_n'], \n", - " properties={\"!OBS.exptime\": 3600})\n", - "metis_n = sim.OpticalTrain(cmd_n)\n", - "metis_n['skycalc_atmosphere'].include=False\n", - "metis_n['detector_linearity'].include=False\n", - "metis_n['chop_nod'].include=False\n", - "metis_n['detector_readout_parameters'].include=False" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "5065793a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Table length=21\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
elementnameclassincluded
str23str27str28bool
armazonesskycalc_atmosphereSkycalcTERCurveFalse
ELTtelescope_reflectionSurfaceListTrue
METIScommon_fore_opticsSurfaceListTrue
METISadc_wheel : [False]ADCWheelFalse
METISslit_wheel : [False]SlitWheelFalse
METIScold_stopPupilTransmissionTrue
METIScommon_fits_keywordsExtraFitsKeywordsTrue
METIS_IMG_Nimg_n_opticsSurfaceListTrue
METIS_IMG_Nfilter_wheel : [N2]FilterWheelTrue
METIS_IMG_Nnd_filter_wheel : [open]FilterWheelTrue
METIS_IMG_NpsfFieldConstantPSFTrue
METIS_DET_IMG_N_GeoSnapdetector_arrayDetectorListTrue
METIS_DET_IMG_N_GeoSnapdetector_readout_parametersDetectorModePropertiesSetterFalse
METIS_DET_IMG_N_GeoSnapquantum_efficiencyQuantumEfficiencyCurveTrue
METIS_DET_IMG_N_GeoSnapauto_exposureAutoExposureTrue
METIS_DET_IMG_N_GeoSnapsummed_exposureSummedExposureTrue
METIS_DET_IMG_N_GeoSnapdark_currentDarkCurrentTrue
METIS_DET_IMG_N_GeoSnapshot_noiseShotNoiseTrue
METIS_DET_IMG_N_GeoSnapdetector_linearityLinearityCurveFalse
METIS_DET_IMG_N_GeoSnapreadout_noiseBasicReadoutNoiseTrue
METIS_DET_IMG_N_GeoSnapchop_nodChopNodCombinerFalse
" - ], - "text/plain": [ - "\n", - " element name ... included\n", - " str23 str27 ... bool \n", - "----------------------- --------------------------- ... --------\n", - " armazones skycalc_atmosphere ... False\n", - " ELT telescope_reflection ... True\n", - " METIS common_fore_optics ... True\n", - " METIS adc_wheel : [False] ... False\n", - " METIS slit_wheel : [False] ... False\n", - " METIS cold_stop ... True\n", - " METIS common_fits_keywords ... True\n", - " METIS_IMG_N img_n_optics ... True\n", - " METIS_IMG_N filter_wheel : [N2] ... True\n", - " METIS_IMG_N nd_filter_wheel : [open] ... True\n", - " METIS_IMG_N psf ... True\n", - "METIS_DET_IMG_N_GeoSnap detector_array ... True\n", - "METIS_DET_IMG_N_GeoSnap detector_readout_parameters ... False\n", - "METIS_DET_IMG_N_GeoSnap quantum_efficiency ... True\n", - "METIS_DET_IMG_N_GeoSnap auto_exposure ... True\n", - "METIS_DET_IMG_N_GeoSnap summed_exposure ... True\n", - "METIS_DET_IMG_N_GeoSnap dark_current ... True\n", - "METIS_DET_IMG_N_GeoSnap shot_noise ... True\n", - "METIS_DET_IMG_N_GeoSnap detector_linearity ... False\n", - "METIS_DET_IMG_N_GeoSnap readout_noise ... True\n", - "METIS_DET_IMG_N_GeoSnap chop_nod ... False" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metis_n.effects" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "88ec413f", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " FOVs: 0%| | 0/3 [00:00" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,10))\n", - "plt.imshow(hdus_n[0][1].data, norm=LogNorm(), origin='lower', cmap='hot')\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "03adf529", - "metadata": {}, - "outputs": [], - "source": [ - "cmd_n_chop = sim.UserCommands(use_instrument='METIS', set_modes=['img_n'], \n", - " properties={\"!OBS.exptime\": 3600})\n", - "metis_n_chop = sim.OpticalTrain(cmd_n_chop)\n", - "metis_n_chop['skycalc_atmosphere'].include=False\n", - "metis_n_chop['detector_linearity'].include=False\n", - "metis_n_chop['chop_nod'].include=True\n", - "metis_n_chop['detector_readout_parameters'].include=False" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "e3dae69f", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " FOVs: 0%| | 0/3 [00:00" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,10))\n", - "plt.imshow(hdus_n_chop[0][1].data, origin='lower', cmap='hot')\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "6247d466", - "metadata": {}, - "outputs": [], - "source": [ - "cmd_lms = sim.UserCommands(\n", - " use_instrument=\"METIS\",\n", - " set_modes=['lms'],\n", - " properties={\n", - " \"!OBS.wavelen\": 3.555,\n", - "\n", - " # These !SIM.spectral_* properties make the simulation faster, but less precise.\n", - " # Comment them out for your final simulations.\n", - " #\"!SIM.spectral_bin_width\": 1e-3,\n", - " #\"!SIM.spectral_resolution\": 1000,\n", - " \n", - " })\n", - "\n", - "metis_lms = sim.OpticalTrain(cmd_lms)\n", - "metis_lms['skycalc_atmosphere'].include=False" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "5012f61b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Table length=20\n", - "
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elementnameclassincluded
str24str20str25bool
armazonesskycalc_atmosphereSkycalcTERCurveFalse
ELTtelescope_reflectionSurfaceListTrue
METIScommon_fore_opticsSurfaceListTrue
METISadc_wheel : [False]ADCWheelFalse
METISslit_wheel : [False]SlitWheelFalse
METIScold_stopPupilTransmissionTrue
METIScommon_fits_keywordsExtraFitsKeywordsTrue
METIS_LMSmetis_lms_surfacesSurfaceListTrue
METIS_LMSlms_efficiencyMetisLMSEfficiencyTrue
METIS_LMSlms_image_slicerMetisLMSImageSlicerTrue
METIS_LMSpsfFieldConstantPSFTrue
METIS_LMSlms_spectral_tracesMetisLMSSpectralTraceListTrue
metis_lms_detector_arraydetector_array_listDetectorListTrue
metis_lms_detector_arrayquantum_efficiencyQuantumEfficiencyCurveTrue
metis_lms_detector_arrayauto_exposureAutoExposureTrue
metis_lms_detector_arrayexposure_actionSummedExposureTrue
metis_lms_detector_arraydark_currentDarkCurrentTrue
metis_lms_detector_arrayshot_noiseShotNoiseTrue
metis_lms_detector_arraydetector_linearityLinearityCurveTrue
metis_lms_detector_arrayreadout_noiseBasicReadoutNoiseTrue
" - ], - "text/plain": [ - "\n", - " element name class included\n", - " str24 str20 str25 bool \n", - "------------------------ -------------------- ------------------------- --------\n", - " armazones skycalc_atmosphere SkycalcTERCurve False\n", - " ELT telescope_reflection SurfaceList True\n", - " METIS common_fore_optics SurfaceList True\n", - " METIS adc_wheel : [False] ADCWheel False\n", - " METIS slit_wheel : [False] SlitWheel False\n", - " METIS cold_stop PupilTransmission True\n", - " METIS common_fits_keywords ExtraFitsKeywords True\n", - " METIS_LMS metis_lms_surfaces SurfaceList True\n", - " METIS_LMS lms_efficiency MetisLMSEfficiency True\n", - " METIS_LMS lms_image_slicer MetisLMSImageSlicer True\n", - " METIS_LMS psf FieldConstantPSF True\n", - " METIS_LMS lms_spectral_traces MetisLMSSpectralTraceList True\n", - "metis_lms_detector_array detector_array_list DetectorList True\n", - "metis_lms_detector_array quantum_efficiency QuantumEfficiencyCurve True\n", - "metis_lms_detector_array auto_exposure AutoExposure True\n", - "metis_lms_detector_array exposure_action SummedExposure True\n", - "metis_lms_detector_array dark_current DarkCurrent True\n", - "metis_lms_detector_array shot_noise ShotNoise True\n", - "metis_lms_detector_array detector_linearity LinearityCurve True\n", - "metis_lms_detector_array readout_noise BasicReadoutNoise True" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metis_lms.effects" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "959d132d", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " FOVs: 0%| | 0/1 [00:00" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ip = metis_lms.image_planes[0]\n", - "\n", - "plt.imshow(ip.data, norm=LogNorm())" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "f7531ef0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[35mastar.scopesim.effects.electronic - WARNING: DIT = 1.000 s < MINDIT = 1.300 s\u001b[0m\n", - "\u001b[32mastar.scopesim.detector.detector_array - Extracting from 4 detectors...\u001b[0m\n", - "\u001b[35mastar.scopesim.effects.electronic - WARNING: DIT = 1.000 s < MINDIT = 1.300 s\u001b[0m\n" - ] - } - ], - "source": [ - "hdul_lms = metis_lms.readout(exptime=3600.)[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "f5c8cd18", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(hdul_lms)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "18853d11", - "metadata": {}, - "outputs": [], - "source": [ - "data_raw = hdul_lms[1].data" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "f7750e3a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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"\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 3\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 4\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 5\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 6\u001b[0m\n", - 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"\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 10\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 11\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 12\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 13\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 14\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 15\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 16\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 17\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 18\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 19\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 20\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 21\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 22\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 23\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 24\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 25\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 26\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 27\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Rectifying Slice 28\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - 3.53 .. 3.58 um\u001b[0m\n", - "\u001b[32mastar.scopesim.effects.spectral_trace_list_utils - Bin width 1e-05 um\u001b[0m\n" - ] - } - ], - "source": [ - "rectified = metis_lms[\"lms_spectral_traces\"].rectify_cube(hdul_lms)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "f04fdd52", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(5517, 28, 110)" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "rectified.data.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "6bdb08d1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.imshow(rectified.data.sum(axis=0), aspect=2.6, origin='lower')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5fd8bbd8", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.9.19" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/METIS/docs/example_notebooks/METIS_IFU-01-Source_cube.ipynb b/METIS/docs/example_notebooks/METIS_IFU-01-Source_cube.ipynb new file mode 100644 index 00000000..46e8daee --- /dev/null +++ b/METIS/docs/example_notebooks/METIS_IFU-01-Source_cube.ipynb @@ -0,0 +1,540 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0011d317-3bf9-4959-bd77-4c3af2b87f80", + "metadata": {}, + "source": [ + "The purpose of this notebook is to create a spectral cube that can be used as a `Source` for METIS IFU (a.k.a. LMS) simulations with Scopesim. The goal is not to create a realistic astrophysical source nor to probe any signal-to-noise limits, but to demonstrate the formal requirements on a FITS file that can be used by Scopesim, and maybe hint at some of the capabilities of the METIS IFU. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "182b83b8-f516-43de-9fbb-c62b0ceecb74", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from astropy.io import fits\n", + "from astropy import units as u\n", + "from astropy.wcs import WCS" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c0d0811-2655-4bd1-9ae7-635cb5b3e966", + "metadata": {}, + "outputs": [], + "source": [ + "# A function to set background colour of individual cells\n", + "from IPython.display import HTML, display\n", + "\n", + "def set_background(color): \n", + " script = (\n", + " \"var cell = this.closest('.jp-CodeCell');\"\n", + " \"var editor = cell.querySelector('.jp-Editor');\"\n", + " \"editor.style.background='{}';\"\n", + " \"this.parentNode.removeChild(this)\"\n", + " ).format(color)\n", + " \n", + " display(HTML(''.format(script)))" + ] + }, + { + "cell_type": "markdown", + "id": "8ad081b7-cf7e-4ceb-ab08-5e98ca9c781a", + "metadata": {}, + "source": [ + "The idea is to use an (ALMA) image of HL Tau and turn it into a spectral cube including Doppler shifts due to disk rotation. The image is taken for our server." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29cba8db-114d-422a-953c-c8a2b6728d62", + "metadata": {}, + "outputs": [], + "source": [ + "import scopesim as sim\n", + "path = sim.download_example_data(\"HL_Tau_prep_for_Scopesim.fits\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "137fbb5e-4104-45e1-9862-c420ffc365ea", + "metadata": {}, + "outputs": [], + "source": [ + "hdul = fits.open(path[0])\n", + "hdul.info()" + ] + }, + { + "cell_type": "markdown", + "id": "e2a8958d-16c5-449f-976b-4098e7da45f5", + "metadata": {}, + "source": [ + "Any fits file that is to be used as source for Scopesim needs to have `BUNIT` keyword, which specifies the units of the data values, as well as the WCS keywords, from which Scopesim takes the pixel scale." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0d3a574b-2d44-4c21-944d-3b861a03ca6f", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Data unit (BUNIT):\", hdul[1].header[\"BUNIT\"]) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0baf75d3-e5b9-4e1f-ad20-3196fb5e1ee3", + "metadata": {}, + "outputs": [], + "source": [ + "pixscale = np.abs(hdul[1].header['CDELT1'] * u.Unit(hdul[1].header['CUNIT1']))\n", + "print(f\"Pixel scale: {pixscale.to(u.mas)}\")" + ] + }, + { + "cell_type": "markdown", + "id": "5bccc85f-e203-4426-a525-a42b38017b2d", + "metadata": {}, + "source": [ + "HL Tau is at a distance of 140 pc, but we will place it at 50 pc, which gives a scale of 20 mas per AU:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "54e6315a-0c80-49b9-9f95-b3ce78f20c35", + "metadata": {}, + "outputs": [], + "source": [ + "au_mas = 1000 * u.mas / 50 # 1 AU is 1 arcsec at 1 pc\n", + "print(f\"1 AU at 50 pc: {au_mas}\")" + ] + }, + { + "cell_type": "markdown", + "id": "51823a95-f1c7-447a-9698-90178bb54516", + "metadata": {}, + "source": [ + "We shall model the rotation of the disk as Keplerian with a reference rotational velocity of 30 km/s at 1 AU, which gives a velocity shift of \n", + "$$\\frac{\\Delta\\lambda}{\\lambda} = \\frac{v}{c} = 10^{-4} \\left(\\frac{R_\\mathrm{ell}}{20\\,\\mathrm{mas}}\\right)^{-1},$$\n", + "where $R_\\mathrm{ell}$ is the projected radius in the disk onto the plane of the sky. The disk appears elliptical with $e = b/a\\approx 0.75$ at a position angle of $\\phi\\approx 45^\\circ$, so\n", + "$$R_\\mathrm{ell} = \\sqrt{ x'^2 + (y'/e)^2}$$\n", + "with\n", + "$$x' = x \\cos\\phi - y \\sin\\phi$$\n", + "$$y' = x\\sin\\phi + y \\cos\\phi$$" + ] + }, + { + "cell_type": "markdown", + "id": "c1a2c22f-59aa-4549-8883-74415eed9154", + "metadata": {}, + "source": [ + "To implement this, we first cut the image to a size that is a little larger than the field of view of the image slicer of the METIS IFU, which is roughly $0.9\\,\\mathrm{arcsec}\\times 0.6\\,\\mathrm{arcsec}$. The following numbers have been determined by inspection of the original image such that the disk is centred in the new image." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bece4ea7-2900-4bbc-9991-19ba91a2827c", + "metadata": {}, + "outputs": [], + "source": [ + "npix = int(0.9 / pixscale.to(u.arcsec).value) # number of pixels needed to cover slice length (0.9 arcsec)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e231b06-c8df-45b8-a9c9-6264056d1efd", + "metadata": {}, + "outputs": [], + "source": [ + "# cut image around disk centre\n", + "x1 = int(802.5 - npix / 2)\n", + "x2 = int(802.5 + npix / 2) + 1\n", + "y1 = int(839.5 - npix / 2)\n", + "y2 = int(839.5 + npix / 2) + 1\n", + "img_cut = hdul[1].data[y1:y2, x1:x2]" + ] + }, + { + "cell_type": "markdown", + "id": "a37e04a5-9c0e-4bbe-9500-d71991432240", + "metadata": {}, + "source": [ + "The WCS has to be adapted to the new image size by moving the reference point `CRPIXi`. For simplicity we change the projection from the original sine to a simple linear projection. With that we can proceed to updating the HDU list with the new data section and new WCS." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30a0d56f-79b4-4829-a603-bfca2ae8b7af", + "metadata": {}, + "outputs": [], + "source": [ + "wcs = WCS(hdul[1].header)\n", + "wcs.wcs.crpix = [89.5, 89.5]\n", + "wcs.wcs.crval = [0., 0.]\n", + "wcs.wcs.ctype = [\"LINEAR\", \"LINEAR\"]" + ] + }, + { + "cell_type": "markdown", + "id": "5b80ffeb-7dc8-498f-8e93-57fd2fd525c0", + "metadata": {}, + "source": [ + "
Note: The following cell is a temporary workaround to avoid a bug in Scopesim v0.11.2 and earlier. The bug will be fixed in the next release and cdelt can then be negative.
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9532583e-8402-4157-952c-fb2c57502a94", + "metadata": {}, + "outputs": [], + "source": [ + "set_background(\"lightblue\")\n", + "wcs.wcs.cdelt[0] = np.abs(wcs.wcs.cdelt[0])\n", + "wcs.wcs.cdelt[1] = np.abs(wcs.wcs.cdelt[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ed9ebd83-2f67-4913-b7c9-51b716dbeb6f", + "metadata": {}, + "outputs": [], + "source": [ + "hdul[1].data = img_cut\n", + "hdul[1].header.update(wcs.to_header())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ac719bc4-a5ba-40b5-9c10-0a2ad9a9772e", + "metadata": {}, + "outputs": [], + "source": [ + "hdul.writeto(\"HL_Tau_img_cut.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "a6ce9feb-d7a1-4889-81ea-31f0d3aee94e", + "metadata": {}, + "source": [ + "Next, we set the velocity field derived above. We start by creating numpy arrays for the coordinates $x$ and $y$ and then transform them to $x'$ and $y'$, $R_\\mathrm{ell}$ and finally to $\\Delta \\lambda/\\lambda$ (i.e. `dloglambda`)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f46dbb73-0848-412f-a5cf-714e7fe2e0c9", + "metadata": {}, + "outputs": [], + "source": [ + "# Derive two images for the world coordinates from that\n", + "ny, nx = img_cut.shape\n", + "i, j = np.meshgrid(np.arange(nx), np.arange(ny))\n", + "x, y = wcs.all_pix2world(i, j, 0)\n", + "x = (x * u.Unit(wcs.wcs.cunit[0]) << u.mas).value \n", + "y = (y * u.Unit(wcs.wcs.cunit[1]) << u.mas).value" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "890d6ba5-2cf4-41db-b58c-9a6b96865077", + "metadata": {}, + "outputs": [], + "source": [ + "phi = -45 * np.pi / 180\n", + "xx = x * np.cos(phi) - y * np.sin(phi)\n", + "yy = x * np.sin(phi) + y * np.cos(phi)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa856f46-901b-4581-ac3d-a2e62a7bb7fd", + "metadata": {}, + "outputs": [], + "source": [ + "inc = 45 * np.pi / 180\n", + "ell = np.cos(inc)\n", + "R_ell = np.sqrt(xx**2 + (yy/ell)**2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d3eee78-6eb1-49bf-a379-742bce7ea6f3", + "metadata": {}, + "outputs": [], + "source": [ + "plt.imshow(hdul[1].data, origin='lower', norm='log')\n", + "plt.contour(R_ell)\n", + "plt.title(r\"Contours of $R_{\\mathrm{ell}}$ overlaid on HL Tau\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c4ebd5c0-d26e-49e6-8ba7-371956974b96", + "metadata": {}, + "outputs": [], + "source": [ + "v_los = 30 * xx * au_mas.value / R_ell**2 * np.sin(inc)\n", + "dloglambda = v_los / 2.998e6" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5cece75e-82f1-415a-9924-343eb22799e7", + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib.colors import SymLogNorm\n", + "from matplotlib.cm import coolwarm\n", + "plt.imshow(v_los, norm=SymLogNorm(linthresh=13), cmap=coolwarm, origin='lower')\n", + "plt.colorbar(label=\"line-of-sight velocity [km/s]\")\n", + "plt.title(\"Line-of-sight velocity field\");" + ] + }, + { + "cell_type": "markdown", + "id": "95421950-acc9-4570-b6b1-77b0f4202d94", + "metadata": {}, + "source": [ + "## Spectral dimension\n", + "We choose a central wavelength of 3.5$\\,\\mu$m. The LMS covers a wavelength range from 3.472 to 3.526$\\,\\mu$m (these values can be obtained from `metis['lms_spectral_traces'].meta['wave_min']` and `metis['lms_spectral_traces'].meta['wave_max']` when `metis` is set up as an `OpticalTrain` at the given central wavelength). \n", + "A data cube used as `Source` for a Scopesim simulation should cover this wavelength range (a smaller range should work but fills the detector images only partially) at a wavelength sampling that is comparable to or better than the dispersion (in microns per pixel) on the LMS detectors.An indication is given by the scopesim parameter `!SIM.spectral.spectral_bin_width`, which is set to $10^{-5}\\,\\mu$m for the LMS (and should not be changed by the user). \n", + "The following cell creates the wavelength vector and expands the image WCS that we created above a third, spectral dimension that describes this vector." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3fa69c64-bb87-4585-935a-a877ee913237", + "metadata": {}, + "outputs": [], + "source": [ + "wave_min, wave_max = 3.472, 3.526 # microns\n", + "dwave = 1e-5 \n", + "wavelength = np.arange(wave_min, wave_max, dwave)\n", + "nwave = len(wavelength)\n", + "\n", + "wcs_cube = wcs.sub([1, 2, 0]) # extend image wcs to cube wcs\n", + "wcs_cube.wcs.ctype[2] = \"WAVE\"\n", + "wcs_cube.wcs.crpix[2] = 1\n", + "wcs_cube.wcs.crval[2] = wave_min\n", + "wcs_cube.wcs.cdelt[2] = dwave\n", + "wcs_cube.wcs.cunit[2] = \"um\"" + ] + }, + { + "cell_type": "markdown", + "id": "61e9df57-9b23-4302-ac9f-c4f2f28cfcf0", + "metadata": {}, + "source": [ + "For the flux vector we choose a series of narrow emission lines that are equally spaced in wavelength, on a slowly varying continuum. Note that emission lines need to be Nyquist sampled in the input spectrum! Failing this, scopesim may miss them.\n", + "As we want to Doppler shift the flux vector we define it on a slightly longer wavelength vector and compute an interpolation function." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "309daf3b-0b8a-47cc-8a03-b19a23d152f1", + "metadata": {}, + "outputs": [], + "source": [ + "lwavelength = np.arange(0.9*wave_min, 1.1*wave_max, dwave)\n", + "flux = np.zeros_like(lwavelength)\n", + "sigma = 1.5 * dwave\n", + "for lamc in [3.48, 3.49, 3.5, 3.51, 3.52]:\n", + " flux += 0.2 * np.exp(-(lwavelength - lamc)**2/(2 * sigma**2))\n", + "flux += 0.4 - ((lwavelength - lamc)/0.3)**2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "13f172bb-51cb-4fb1-b43e-f0c73ebae371", + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.interpolate import interp1d\n", + "iflux = interp1d(lwavelength, flux)" + ] + }, + { + "cell_type": "markdown", + "id": "1fb5c190-6a5d-43d0-92e7-f86544bf4f77", + "metadata": {}, + "source": [ + "The following cell is rather compact and does several things:\n", + "- `np.outer()` creates a cube from the `wavelength` vector and the `dloglambda` image. The values in this cube are $\\lambda/(1+v/c)$, i.e. a shifted wavelength vector at each image position.\n", + "- These \"wavelengths\" are given as an argument to the flux interpolation function, thus filling the cube with values $f(\\lambda/(1+v/c))$. This has the effect of shifting the emission lines to observed wavelength $\\lambda_0 (1+v/c)$.\n", + "- Finally, the cube is multiplied by the image of HL Tau to scale the spectra. This then is our final data cube." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d96f778-63dd-4974-b535-d498aef69bb6", + "metadata": {}, + "outputs": [], + "source": [ + "cube = img_cut[None, :, :] * iflux( np.outer(wavelength, (1./(1+dloglambda))).reshape(nwave, ny, nx) )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5b314576-eb5d-4d02-b3a5-5b41c8d41f94", + "metadata": {}, + "outputs": [], + "source": [ + "_, axes = plt.subplots(1, 2, figsize=(9, 4))\n", + "axes[0].imshow(cube[802,] - cube[800,], origin='lower')\n", + "axes[0].text(10, 170, \"difference layers 802 and 800\", color='white')\n", + "axes[1].plot(cube[:, 90, 91], label=\"Pixel (91, 90)\")\n", + "axes[1].plot(cube[:, 90, 89], label=\"Pixel (89, 90)\")\n", + "plt.legend()\n", + "axes[1].set_xlim(700, 920);" + ] + }, + { + "cell_type": "markdown", + "id": "6d570ccf-f228-4e6a-b80f-203994d0f9e2", + "metadata": {}, + "source": [ + "We finally adjust the data values somewhat arbitrarily, by looking at the minimum and maximum values in the cube:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "59d9160e-9c31-4b03-b07d-cc28d23371ae", + "metadata": {}, + "outputs": [], + "source": [ + "print(cube.min(), cube.max())" + ] + }, + { + "cell_type": "markdown", + "id": "c1ff36df-83fe-49c6-9b2e-f248bcdf7d32", + "metadata": {}, + "source": [ + "Real circumstellar disks have total fluxes of around 100 mJy (optimistically), so we need to scale our cube by about a factor of 50. We'll make it 100 so SNR won't be an issue later on." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "877f1b57-03ba-4863-8cdc-8ed5c713693a", + "metadata": {}, + "outputs": [], + "source": [ + "cube *= 100" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "71ecba35-5bca-4963-b212-8e4acc4ec73f", + "metadata": {}, + "outputs": [], + "source": [ + "total_spec = cube.sum(axis=(1, 2))\n", + "\n", + "plt.plot(wavelength, total_spec)\n", + "plt.xlabel(\"Wavelength [um]\")\n", + "plt.ylabel(\"Jy\")\n", + "plt.title(\"Integrated spectrum\");" + ] + }, + { + "cell_type": "markdown", + "id": "c10d893b-25d3-4d7b-b845-2848205f30e9", + "metadata": {}, + "source": [ + "We finally put the cube into a fits file. The essential metadata are the WCS, which describes the spatial as well as the spectral dimensions, and the `BUNIT` keyword. For the latter we stick with `Jy`, although this is somewhat incongruous as the values are spatially integrated over one pixel, whereas spectrally they are taken per Hz (i.e. a spectral density). Many units are possible as long as they make it clear whether (photon or energy) flux is taken per spatial pixel or solid angle and per spectral bin or wavelength or frequency interval. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d9976f62-01cc-4ff1-923a-cf52c416446b", + "metadata": {}, + "outputs": [], + "source": [ + "hdr = wcs_cube.to_header()\n", + "hdr['BUNIT'] = \"Jy\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c13d1a76-15e0-46e1-a406-0164d2516fd6", + "metadata": {}, + "outputs": [], + "source": [ + "hdu_cube = fits.PrimaryHDU(header=hdr, data=cube.astype(np.float32))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ec4b8120-bb3d-4403-ba1f-fa67945bf913", + "metadata": {}, + "outputs": [], + "source": [ + "hdu_cube.writeto(\"our_first_cube.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "4d3fa521-9664-4190-aec3-16df452f809c", + "metadata": {}, + "source": [ + "In the next notebook, `METIS_IFU-02-Simulation.ipynb`, we will use this cube as the Source object for METIS-LMS observations." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/METIS/docs/example_notebooks/METIS_IFU-02-Simulation.ipynb b/METIS/docs/example_notebooks/METIS_IFU-02-Simulation.ipynb new file mode 100644 index 00000000..e6c44de2 --- /dev/null +++ b/METIS/docs/example_notebooks/METIS_IFU-02-Simulation.ipynb @@ -0,0 +1,600 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d6459b98-1019-4152-9b28-12ffc312b3ed", + "metadata": {}, + "source": [ + "This notebook shows how to use the METIS LMS mode in Scopesim. The LM Spectrograph (LMS) is the integral-field unit within METIS. Strictly speaking LMS refers to the hardware subsystem and the instrument mode had better been called \"IFU\". The use of LMS versus IFU is somewhat inconsistent, it has grown historically and it would be hard to change it now." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4218592c-e22a-42a5-956e-9e87d37be5c3", + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib import pyplot as plt\n", + "from matplotlib.colors import Normalize" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3086d4b-8568-42a7-ad26-591b3524f76d", + "metadata": {}, + "outputs": [], + "source": [ + "import scopesim as sim\n", + "import numpy as np\n", + "from astropy.io import fits\n", + "from astropy.wcs import WCS\n", + "from astropy import units as u" + ] + }, + { + "cell_type": "markdown", + "id": "91c1a5c8-01f5-47dd-a568-cb51615d1551", + "metadata": {}, + "source": [ + "In addition to scopesim we need the configuration and data files that describe the atmosphere, telescope and instrument. These are downloaded from our server with" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1f5328a-5884-4355-aa19-6b734a88a876", + "metadata": {}, + "outputs": [], + "source": [ + "# Edit this path if you have a custom install directory, otherwise comment it out. [For ReadTheDocs only]\n", + "sim.link_irdb(\"../../../\")\n", + "\n", + "# If you want/need to download the instrument packages uncomment the fol\n", + "#sim.download_packages([\"Armazones\", \"ELT\", \"METIS\"])" + ] + }, + { + "cell_type": "markdown", + "id": "302a079d-c0eb-49e8-b820-fa9f65a5f310", + "metadata": {}, + "source": [ + "The following command gives the versions of python packages that are used by Scopesim as well as of instrument packages (called IRDB packages). We ask to include the output of this command in any communication with us, in particular in bug reports." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb27dfb0-e9bb-48fd-9efd-a10830df9cbe", + "metadata": {}, + "outputs": [], + "source": [ + "sim.bug_report()" + ] + }, + { + "cell_type": "markdown", + "id": "00144738-6b36-4d08-b1c2-b3b448a37c9f", + "metadata": {}, + "source": [ + "# Setting up the instrument\n", + "\n", + "The first step is to set up the instrument in the desired configuration. There are currently two modes that use the LM spectrograph and that are of interest for simulating science observations:\n", + "- `lms`: This is the nominal lms/ifu mode that produces raw two-dimensional detector images in the way that METIS will do. To analyse these data requires a data reduction pipeline, which is not currently available. Scopesim includes a function that allows rectifying these images into a data cube with well-defined spatial and spectral dimensions as we shall demonstrate later in this notebook. This cube corresponds to a single exposure and under-samples the spatial PSF in the across-slice direction. \n", + "- `lms_cube`: This is a convenience mode that directly simulates spectra in a data cube with square spatial pixels that properly sample the spatial PSF. Such a cube will be the result of a procedure that combines a series of dithered and rotated exposures in order to reconstruct the PSF, which is under-sampled in individual exposures. While the simulation contains many of the noise contributions present in real data it cannot include the uncertainties related to an actual data reduction procedure and is therefore rather optimistic.\n", + "\n", + "The extended or spectral IFU mode is not yet available in Scopesim.\n", + "\n", + "We start by setting up a `UserCommands` object in which we specify the instrument to be used (`METIS`), the instrument mode (`lms`) as well as other parameters needed to uniquely specify the instrument setup. For the LMS, a parameter that will always have to be set is the target wavelength. In Scopesim, this can be given simply as a float (units of micrometers). " + ] + }, + { + "cell_type": "markdown", + "id": "7c81a867-2ac1-48ea-a533-d38615665f19", + "metadata": {}, + "source": [ + "# Using the nominal LMS mode" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f565d3b3-33fb-41c0-be22-81c4f1819882", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=[\"lms\"], properties={\"!OBS.wavelen\": 3.5})" + ] + }, + { + "cell_type": "markdown", + "id": "df5dba32-a398-4a63-8c5c-99951680d6c2", + "metadata": {}, + "source": [ + "Further parameters can be set either in the command above or separately as in" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bea03220-b9da-4d9f-9948-f08a5ff10434", + "metadata": {}, + "outputs": [], + "source": [ + "cmd[\"!OBS.interp_psf\"] = False # only scale PSF to the central wavelength" + ] + }, + { + "cell_type": "markdown", + "id": "3c3f9858-4628-4e82-9a55-0e465bd54e3b", + "metadata": {}, + "source": [ + "The reason for doing this will be explained below.\n", + "\n", + "The `OpticalTrain` (consisting of atmosphere + telescope + instrument) is then built from the `UserCommands` object (DeprecationWarnings can be ignored):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b49a0ffe-3630-4340-8a0e-c5270606773f", + "metadata": {}, + "outputs": [], + "source": [ + "metis = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "markdown", + "id": "00b72a1e-f596-4a69-9bae-c2b5b76dee5d", + "metadata": {}, + "source": [ + "An `OpticalTrain` consists of a list of `Effect` objects, which can be listed as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7eedfdf-3a3b-4f6e-919d-7aaeb87b5921", + "metadata": {}, + "outputs": [], + "source": [ + "metis.effects.pprint_all()" + ] + }, + { + "cell_type": "markdown", + "id": "9315931c-e959-413b-8b00-c537ba5ade65", + "metadata": {}, + "source": [ + "## Observation of blank sky\n", + "We start by simply observing a piece of blank sky. This way we don't have to worry about setting up an astronomical source, which we will however do shortly. IFU simulations are fairly complex and therefore need some time. Much of that time is spent on PSF convolution, which has no effect when the target fills the field of view homogeneously as blank sky does. One could turn off PSF convolution entirely by doing `metis['psf'].include = False` but one needs to be careful to turn it back on again when observing an actual source. Another way to speed things up is not to scale the PSF by wavelength - this is indeed admissable in LMS observations which cover a short wavelength range (one should not do in long-slit simulations where the PSF at the red end is nearly twice as large as at the blue end). We have already switched off PSF scaling (except to the central wavelength) above. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3acb8cad-7412-4337-8f4c-f95e640655d1", + "metadata": {}, + "outputs": [], + "source": [ + "metis.observe()" + ] + }, + { + "cell_type": "markdown", + "id": "c599df55-dd20-4431-95e7-be2547a1d92d", + "metadata": {}, + "source": [ + "The result of `observe()` is an `ImagePlane` object. This is a noise-free image of the spectral layout in the detector plane. The units are photons per second (per pixel). A `readout()` is needed to put this image onto the detector array and add photon noise, dark current and other detector effects to it. We first look at the `ImagePlane`, then create a readout with exposure time 600 seconds." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "274dce45-1db3-4a74-a99f-3b69821d4b7b", + "metadata": {}, + "outputs": [], + "source": [ + "sky_implane = metis.image_planes[0].hdu\n", + "sky_implane.writeto(\"sky_implane.fits\", overwrite=True)\n", + "plt.imshow(sky_implane.data, origin=\"lower\")\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "markdown", + "id": "0b9bf83b-95f0-4d98-b457-f4c2780497cd", + "metadata": {}, + "source": [ + "The `ImagePlane` then needs to be read out by the detectors to add all the relevant noise components. This can be repeated as often as desired, for testing different exposure times or for creating exposure sequences with the same exposure time. `readout()` also applies gain conversion, so the output of a readout is ADU. The gain for the LMS detectors is currently set at 2 electrons/ADU." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0721157a-78b5-42b9-bdec-479e1e4a768f", + "metadata": {}, + "outputs": [], + "source": [ + "sky_read = metis.readout(dit=600, ndit=1)[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "53622217-141b-4bf7-a2bf-1f23718d7400", + "metadata": {}, + "outputs": [], + "source": [ + "norm = Normalize(vmin=np.min([hdu.data for hdu in sky_read[1:]]),\n", + " vmax=np.max([hdu.data for hdu in sky_read[1:]]))\n", + "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(6, 6))\n", + "axes[0, 0].imshow(sky_read[1].data, origin='lower', norm=norm)\n", + "axes[0, 1].imshow(sky_read[2].data, origin='lower', norm=norm)\n", + "axes[1, 0].imshow(sky_read[3].data, origin='lower', norm=norm)\n", + "axes[1, 1].imshow(sky_read[4].data, origin='lower', norm=norm)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b57ff645-cfeb-4700-8664-4399aa57684b", + "metadata": {}, + "outputs": [], + "source": [ + "# Save the sky observation for later use\n", + "sky_read.writeto(\"sky_lms-3.5um-600s.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "4b117404-1e3e-49cc-ad9e-02326f8e8335", + "metadata": {}, + "source": [ + "## Observation of a source\n", + "\n", + "We take the source from the fits file that we created in the previous notebook, `METIS_IFU-01-Source_cube.ipynb`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d0eb604-8439-4c7e-b59a-ae60425f9221", + "metadata": {}, + "outputs": [], + "source": [ + "cubefits = \"our_first_cube.fits\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "542ca8cd-440f-4323-994c-c37e6bb315db", + "metadata": {}, + "outputs": [], + "source": [ + "with fits.open(cubefits) as hdul:\n", + " src = sim.Source(cube=hdul)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c6df160-ed6e-4efd-a38f-720ea2f9b595", + "metadata": {}, + "outputs": [], + "source": [ + "metis.observe(src)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b9a3ac4-6bac-4718-a9cd-971d95d1b331", + "metadata": {}, + "outputs": [], + "source": [ + "src_implane = metis.image_planes[0].hdu\n", + "src_implane.writeto(\"src_implane.fits\", overwrite=True)\n", + "plt.imshow(src_implane.data - sky_implane.data, origin='lower')\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6dc82a77-6750-48e5-aed8-25e3967ac56e", + "metadata": {}, + "outputs": [], + "source": [ + "src_read = metis.readout(dit=600, ndit=1)[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e1060c3-bbb3-4587-b14b-33e38a4422de", + "metadata": {}, + "outputs": [], + "source": [ + "# If src and sky had been read out with different dit/ndit settings, sky would have to be scaled\n", + "for i in range(1, 5):\n", + " src_read[i].data = src_read[i].data - sky_read[i].data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7265c02c-cb61-4039-ab38-22aec662c2aa", + "metadata": {}, + "outputs": [], + "source": [ + "norm = Normalize(vmin=np.min([hdu.data for hdu in src_read[1:]]),\n", + " vmax=np.max([hdu.data for hdu in src_read[1:]]))\n", + "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(6, 6))\n", + "axes[0, 0].imshow(src_read[1].data, origin='lower', norm=norm)\n", + "axes[0, 1].imshow(src_read[2].data, origin='lower', norm=norm)\n", + "axes[1, 0].imshow(src_read[3].data, origin='lower', norm=norm)\n", + "axes[1, 1].imshow(src_read[4].data, origin='lower', norm=norm)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "309b759e-3d1e-42cd-b711-89252c5fe9ec", + "metadata": {}, + "outputs": [], + "source": [ + "src_read.writeto(\"hl_tau_lms_600s.fits\", overwrite=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "40e98513-2a52-49cd-99f8-ee42e0dcfb3d", + "metadata": {}, + "outputs": [], + "source": [ + "rectified = metis['lms_spectral_traces'].rectify_cube(src_read)" + ] + }, + { + "cell_type": "markdown", + "id": "22b97bcd-ae90-4e7b-bd20-5062eacbde29", + "metadata": {}, + "source": [ + "We first show an image reconstruction of the cube by summing over the wavelength axis. Since the spatial pixels are rectangular we have to use the `aspect` keyword to get the correct aspect ratio. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "61a1855f-dedf-4e74-ae40-ecd986d0a760", + "metadata": {}, + "outputs": [], + "source": [ + "wcs = WCS(rectified.header)\n", + "wcs.sub(2) # celestial part of the WCS (linear for now)\n", + "fig, ax = plt.subplots(subplot_kw=dict(projection=wcs.sub(2)), figsize=(6, 3))\n", + "# `aspect` is needed because pixels are rectangular!\n", + "img = ax.imshow(rectified.data.sum(axis=0), origin=\"lower\", aspect=20.7/8.2)\n", + "fig.colorbar(img, label=\"ADU\");" + ] + }, + { + "cell_type": "markdown", + "id": "b43f859a-4ee1-4eaf-9858-00c2372777ea", + "metadata": {}, + "source": [ + "The global spectrum is obtained by summing over the spatial axes. The wavelength values are obtained via the spectral part of the WCS." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60645273-9fe1-4b44-9a24-ca42e45c11a2", + "metadata": {}, + "outputs": [], + "source": [ + "swcs = wcs.spectral\n", + "wavelength = swcs.all_pix2world(np.arange(rectified.data.shape[0]), 0)[0]\n", + "wavelength *= u.Unit(swcs.wcs.cunit[0]).to(u.um)\n", + "plt.plot(wavelength, rectified.data.sum(axis=(1, 2)))\n", + "plt.xlabel(\"Wavelength [um]\")\n", + "plt.ylabel(\"ADU\");" + ] + }, + { + "cell_type": "markdown", + "id": "2f3ed1e9-225c-4bd9-b795-755058cc008b", + "metadata": {}, + "source": [ + "## Using the LMS Cube mode\n", + "The rectified spectral cube shown above has rectangular spaxels, with detector pixels of 8.2 mas along the x-direction and slices of 20.7 mas along the y-direction. When METIS is on sky a sequence of dithered and rotated exposures will be taken, which will allow reconstruction of the fully sampled field on 8.2 mas pixels in both directions. \n", + "For convenience, Scopesim provides a mode `lms_cube` that simulates these reconstructed cubes directly. The noise levels are realistic, but the uncertainties connected to the reconstruction procedure are not." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9fab2533-9de2-452b-8856-f20163950de2", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=['lms_cube'], properties={\"!OBS.wavelen\": 3.5})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe8d6a69-2bb7-491d-ab3b-573bde5a342a", + "metadata": {}, + "outputs": [], + "source": [ + "cmd[\"!SIM.spectral.spectral_bin_width\"] = 1e-5\n", + "cmd[\"!OBS.interp_psf\"] = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d7fcd46-6da8-4a25-a213-6086da08b21c", + "metadata": {}, + "outputs": [], + "source": [ + "metis = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "markdown", + "id": "5ded5e6c-6b6c-4ab1-bdf7-086138fde525", + "metadata": {}, + "source": [ + "
Note: `observe()` in cube mode requires a lot of memory for PSF convolution. Since the PSF is not crucial for our extended source we turn it off here. You can include it by changing `False` to `True` in the following cell.
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5aa659c-1351-4cd2-a3be-c494f47dbbdf", + "metadata": {}, + "outputs": [], + "source": [ + "metis[\"psf\"].include = False\n", + "metis.observe(src)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "953f3f95-ce35-4403-9c2c-3989f23869aa", + "metadata": {}, + "outputs": [], + "source": [ + "metis.image_planes[0].data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "402384a0-b651-47bd-8156-cf228e30bd89", + "metadata": {}, + "outputs": [], + "source": [ + "src_cube = metis.readout(dit=600, ndit=1)[0][1]" + ] + }, + { + "cell_type": "markdown", + "id": "17b820fb-b2d5-458a-be38-90845119ac2a", + "metadata": {}, + "source": [ + "`readout()` results in a 3D FITS cube with a linear wavelength scale and two spatial dimensions. We will look at the spatial and spectral dimensions, respectively summed over the remaining dimensions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d1994f6b-11b2-46e4-a9a0-d42d98f5affd", + "metadata": {}, + "outputs": [], + "source": [ + "wcs = WCS(src_cube)\n", + "fig, ax = plt.subplots(subplot_kw=dict(projection=wcs.sub(2)))\n", + "img = ax.imshow(src_cube.data.sum(axis=0), origin='lower')\n", + "fig.colorbar(img, label=\"ADU\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4259f445-048c-4cff-814e-6503254e89a4", + "metadata": {}, + "outputs": [], + "source": [ + "swcs = wcs.spectral\n", + "wavelength_cube = swcs.all_pix2world(np.arange(src_cube.data.shape[0]), 0)[0]\n", + "wavelength_cube *= u.Unit(swcs.wcs.cunit[0]).to(u.um)\n", + "\n", + "_, ax = plt.subplots(figsize=(10, 6))\n", + "ax.plot(wavelength_cube, src_cube.data.sum(axis=(1, 2)))\n", + "ax.set_xlabel(\"Wavelength [µm]\")\n", + "ax.set_ylabel(\"ADU\");" + ] + }, + { + "cell_type": "markdown", + "id": "d6b5860b-4fe3-40ea-8fbb-e732d4e82575", + "metadata": {}, + "source": [ + "Simulate an empty sky observation for background subtraction. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4de43b9-48c7-4876-bc89-579dab6f1675", + "metadata": {}, + "outputs": [], + "source": [ + "metis.observe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22fd1523-fe42-4cb3-8b34-23613c4db6c5", + "metadata": {}, + "outputs": [], + "source": [ + "sky_cube = metis.readout(dit=600, ndit=1)[0][1]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cfe7728c-036b-48d8-9937-f62085e1d7bb", + "metadata": {}, + "outputs": [], + "source": [ + "_, ax = plt.subplots(figsize=(12, 6))\n", + "ax.plot(wavelength_cube, (src_cube.data - sky_cube.data).sum(axis=(1, 2)), label=\"Cube mode\")\n", + "ax.plot(wavelength, rectified.data.sum(axis=(1, 2)), label=\"Nominal mode\")\n", + "ax.legend()\n", + "ax.set_xlabel(\"Wavelength [µm]\")\n", + "ax.set_ylabel(\"ADU\");" + ] + }, + { + "cell_type": "markdown", + "id": "c0de8591-75b0-4a0d-8994-f080df8dc071", + "metadata": {}, + "source": [ + "The signal in cube mode is higher than that in the nominal mode as the field of view is larger ($0.9\\times 0.9$ arcsec$^2$ compared to $0.9\\times0.6$ arcsec$^2$. The detector gap at 3.5 um is not taken into account in cube mode. The continuum is modified by the instrumental transmission (in particular the grating efficiency); atmospheric absorption lines are clearly visible throughout. Correction of these effects would require simulation of flux and telluric standard stars. " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/METIS/docs/example_notebooks/demos/demo_Leiden_sky.ipynb b/METIS/docs/example_notebooks/demos/demo_Leiden_sky.ipynb new file mode 100644 index 00000000..a21fd97a --- /dev/null +++ b/METIS/docs/example_notebooks/demos/demo_Leiden_sky.ipynb @@ -0,0 +1,391 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "e50a4189-3f1d-423d-915a-97f322b0aa3d", + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib import pyplot as plt\n", + "import numpy as np\n", + "from astropy import units as u" + ] + }, + { + "cell_type": "markdown", + "id": "61e31623-0ce1-44d1-a0fe-d46273016be9", + "metadata": {}, + "source": [ + "METIS AIT activities in Leiden will use bespoke relay optics to observe the sky above the integration hall with METIS. Scopesim can simulate these observations for the spectroscopic modes. Emission and transmission spectra for the sky above Leiden were calculated by Wolfgang Kausch for 50 values of precipital water vapour (PWV). The data are stored on the Astar server in Vienna and will be downloaded the first time you use them." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93347b06-0726-40c1-871d-ad0a6ca71ed5", + "metadata": {}, + "outputs": [], + "source": [ + "import scopesim as sim\n", + "\n", + "# Edit this path if you have a custom install directory, otherwise comment it out.\n", + "sim.link_irdb(\"../../../../\")\n", + "\n", + "# If you haven't got the instrument packages yet, uncomment the following line.\n", + "#sim.download_packages([\"METIS\"])" + ] + }, + { + "cell_type": "markdown", + "id": "cfb44995-bf3f-4958-bfaf-f44c0071229f", + "metadata": {}, + "source": [ + "The available modes using the Leiden sky are `leiden_lss_l`, `leiden_lss_m`, `leiden_lss_n` and `leiden_lms`. We will simulate an LSS_M observation, using a PWV value of 10 mm. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f42951c7-c651-457a-8a3a-b521c663aeae", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=['leiden_lss_m'])\n", + "cmd[\"!ATMO.pwv\"] = 10 # could also use properties={\"!ATMO.pwv\": 10} in UserCommands" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b77fa0a2-d7dc-455c-a020-ff4afc9181fc", + "metadata": {}, + "outputs": [], + "source": [ + "metis = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95cb7c31-30ec-446a-8a1a-e9ef578e92ff", + "metadata": {}, + "outputs": [], + "source": [ + "metis.effects.pprint_all()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "1af39ad0-7706-4615-a5cb-faeab1f83bed", + "metadata": {}, + "source": [ + "The `leiden_` modes replace the `ELT` and `Armazones` packages with two effects, `leiden_sky`, which creates the background source using the atmospheric spectra for the selected PWV, and `telescope`, which models the relay optics. \n", + "\n", + "`telescope` has no user-modifiable parameters; its configuration can be inspected as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a9201c83-9966-4bb6-84ce-879e6b3108ec", + "metadata": {}, + "outputs": [], + "source": [ + "metis['telescope'].table" + ] + }, + { + "cell_type": "markdown", + "id": "fbe32a5a-9f11-4463-bd15-1a19c0230377", + "metadata": {}, + "source": [ + "The atmospheric emission is provided by the effect `leiden_sky`. It has one parameter, the precipitable water vapour:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce6e2317-d269-488f-83ce-193a9168ce2f", + "metadata": {}, + "outputs": [], + "source": [ + "print(metis[\"leiden_sky\"])" + ] + }, + { + "cell_type": "markdown", + "id": "49c58cb0-0374-4b41-9911-5b431723b706", + "metadata": {}, + "source": [ + "The transmission and emission spectra can be plotted as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07305c38-57a8-40cb-b9b0-392563dbad29", + "metadata": {}, + "outputs": [], + "source": [ + "metis['leiden_sky'].plot(which=\"te\", wavelength=np.linspace(3, 6, 1001)*u.um);" + ] + }, + { + "cell_type": "markdown", + "id": "80c3334c-0a97-4626-9b47-79c6bd4251c8", + "metadata": {}, + "source": [ + "An observation is done as usual with the `.observe()` method. No `Source` object is required." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c26dab8-2453-4265-8213-f30b22fdfa3b", + "metadata": {}, + "outputs": [], + "source": [ + "metis.observe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9fd2bbb-5b1e-4a95-ae16-b26fe370bfd1", + "metadata": {}, + "outputs": [], + "source": [ + "plt.imshow(metis.image_planes[0].data, norm=\"log\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e03e8caa-a004-4894-aca1-29a6181e3468", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(metis.image_planes[0].data[:, 1000])\n", + "plt.xlabel(\"Row number (~ wavelength)\")\n", + "plt.ylabel(\"Photons/second (ImagePlane)\");" + ] + }, + { + "cell_type": "markdown", + "id": "c885e30f-dd8d-4956-8822-c5c9262c8291", + "metadata": {}, + "source": [ + "The plots show the `ImagePlane`. After a `readout`, the `metis[spectral_traces].rectify_traces()` method could be used to show the simulation on a linear wavelength scale." + ] + }, + { + "cell_type": "markdown", + "id": "87f75df4-c0dd-49af-9ac1-b36ad39bcd87", + "metadata": {}, + "source": [ + "**Not yet**: The `leiden_sky` effect (or rather the underlying `AtmoLibraryTERCurve` effect) has an update method, which allows to change the PWV value. This does not work yet! We recommend creating a new `OpticalTrain` after setting `cmd[\"!ATMO.pwv\"]` to a new value. This will hopefully be fixed soon." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0d1cfdf4-d5fe-46f6-b0c0-239bf73944ce", + "metadata": {}, + "outputs": [], + "source": [ + "metis['leiden_sky'].update(pwv=50)\n", + "metis['leiden_sky'].plot(which=\"te\", wavelength=np.linspace(3, 6, 1001)*u.um);" + ] + }, + { + "cell_type": "markdown", + "id": "f66f972e-eeab-45e1-aa21-caee8eaa462e", + "metadata": {}, + "source": [ + "# Comparison to Armazones/ELT\n", + "The following compares the Leiden spectrum with a spectrum of the Armazones sky and METIS at the ELT." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da3baa54-3d48-4e28-80b7-482920caa615", + "metadata": {}, + "outputs": [], + "source": [ + "cmd_elt = sim.UserCommands(use_instrument=\"METIS\", set_modes=[\"lss_m\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c558bce-64f2-466f-b881-40ed4365da76", + "metadata": {}, + "outputs": [], + "source": [ + "elt = sim.OpticalTrain(cmd_elt)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b102df8-0e50-4904-a836-0deeadc4633c", + "metadata": {}, + "outputs": [], + "source": [ + "elt.observe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2859605-935c-4590-93cd-05821d74e4b3", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(elt.image_planes[0].data[:, 1000]/(36.9**2 - 10.95**2) * (0.66**2 * np.cos(np.pi/4)), label=\"Armazones\")\n", + "#plt.plot(elt.image_planes[0].data[:, 1000] / 975.2347899768369 * 0.34, label=\"Armazones 2\")\n", + "plt.plot(metis.image_planes[0].data[:, 1000], label=\"Leiden\")\n", + "plt.xlabel(\"Row number (~ wavelength)\")\n", + "plt.ylabel(\"Photons/second (ImagePlane)\")\n", + "#plt.ylim(0, 10)\n", + "plt.legend();" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "785b241d-cdcb-4a30-944f-dd5b03446f6e", + "metadata": {}, + "outputs": [], + "source": [ + "leiden = metis['leiden_sky']\n", + "armazones = elt[\"skycalc_atmosphere\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "19ec7934-5a13-434b-9ef0-73b6c3ef5cd7", + "metadata": {}, + "outputs": [], + "source": [ + "lam = np.linspace(4, 5, 1001)*u.um\n", + "f_leiden = leiden.emission(lam)\n", + "f_armazones = armazones.emission(lam)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b271a01a-ce69-43cf-b90c-699fdff0417b", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(lam, f_armazones, label=\"Armazones\", lw=1)\n", + "plt.plot(lam, f_leiden, label=\"Leiden\", lw=1)\n", + "#plt.semilogy()\n", + "plt.xlabel(\"Wavelength [um]\")\n", + "plt.ylabel(\"PHOTLAM\")\n", + "plt.xlim(4.6, 4.8)\n", + "plt.legend();" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f9d196b7-64a6-4095-8a2c-7cd5696882e2", + "metadata": {}, + "outputs": [], + "source": [ + "lam_leiden = leiden.surface.emission.waveset.to(u.um)\n", + "lam_armazones = armazones.surface.emission.waveset.to(u.um)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "843e625d-12b2-4d95-8e98-4796f7e85c1f", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(lam_armazones, armazones.surface.emission(lam_armazones), label=\"Armazones\")\n", + "plt.plot(lam_leiden, leiden.surface.emission(lam_leiden), label=\"Leiden\")\n", + "plt.xlim(3.2, 3.4)\n", + "plt.ylim(0, 0.5)\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8b778f3f-ae11-4529-9b2b-1bbe591311a5", + "metadata": {}, + "outputs": [], + "source": [ + "rlam_leiden = lam_leiden[(lam_leiden > 4.6*u.um) * (lam_leiden < 4.8*u.um)] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "807c7b3f-8bab-41d2-aa2b-6eec26a7507a", + "metadata": {}, + "outputs": [], + "source": [ + "leiden.emission.integrate(wavelengths=rlam_leiden)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5a2bffda-dcfa-49d3-91ce-a5875a01be83", + "metadata": {}, + "outputs": [], + "source": [ + "rlam_arm = lam_armazones[(lam_armazones > 4.6*u.um) * (lam_armazones < 4.8*u.um)]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "845ff1a9-d89b-4351-be02-a807ec3d146f", + "metadata": {}, + "outputs": [], + "source": [ + "armazones.emission.integrate(wavelengths=rlam_arm)" + ] + }, + { + "cell_type": "markdown", + "id": "3411e7b5-8661-461e-8056-b644c549dc94", + "metadata": {}, + "source": [ + "As expected, the Leiden sky is brighter (in the M band) than the sky above Armazones. Note that this is just an exemplary comparison, and we have not tried to match the atmospheric parameters in much detail. A similar exercise in the L band results in Armazones being brighter than Leiden. It should be borne in mind that the Leiden sky model only includes atmospheric emission and neglects scattered moon light, zodiacal light and other effects that are taken into account in the more sophisticated `skycalc` model used for Armazones." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/METIS/docs/example_notebooks/demos/demo_chopping_and_nodding.ipynb b/METIS/docs/example_notebooks/demos/demo_chopping_and_nodding.ipynb index a39aaf43..2e865af5 100644 --- a/METIS/docs/example_notebooks/demos/demo_chopping_and_nodding.ipynb +++ b/METIS/docs/example_notebooks/demos/demo_chopping_and_nodding.ipynb @@ -48,7 +48,8 @@ "source": [ "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=[\"img_n\"])\n", "metis = sim.OpticalTrain(cmd)\n", - "metis[\"chop_nod\"].include = True" + "metis[\"chop_nod\"].include = True\n", + "metis[\"reference_pixel_mask\"].include = False # Hack: this would mess up the chop/nod results" ] }, { diff --git a/METIS/docs/example_notebooks/demos/demo_skycalc.ipynb b/METIS/docs/example_notebooks/demos/demo_skycalc.ipynb new file mode 100644 index 00000000..819c3465 --- /dev/null +++ b/METIS/docs/example_notebooks/demos/demo_skycalc.ipynb @@ -0,0 +1,266 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "54686e5f-f108-4633-bf8d-d13205e07f92", + "metadata": {}, + "source": [ + "# The `SkycalcTERCurve` effect in ScopeSim\n", + "\n", + "This notebook demonstrates how to work with the skycalc effect, `SkycalcTERCurve`. This effect provides the atmospheric emission and transmission that are applied to a source object in ScopeSim. The effect is based on `skycalc_ipy`, a python wrapper to ESO’s SkyCalc tool." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2c01ec5f-9e28-41f2-b047-8e4aef3e1b88", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from astropy import units as u" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c64d3cf-75f7-4174-b1c7-6bb202b58fe6", + "metadata": {}, + "outputs": [], + "source": [ + "import scopesim as sim\n", + "\n", + "# If you have not done so already, please download the relevant instrument packages by uncommenting the following line:\n", + "# sim.download_packages([\"Armazones\", \"ELT\", \"METIS\"])" + ] + }, + { + "cell_type": "markdown", + "id": "431dfc2a-a822-43fc-8bdb-f7762b8b6583", + "metadata": {}, + "source": [ + "We use the `SkycalcTERCurve` in the context of METIS/LMS, although sky mode of any other instrument would do as well. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "27271168-1d50-4fa2-8970-ae5caca56a87", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=[\"lms\"])\n", + "cmd[\"!OBS.wavelen\"] = 3.5" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f2f28719-eeb7-41f9-8ee7-d748d39ea5dd", + "metadata": {}, + "outputs": [], + "source": [ + "metis = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "markdown", + "id": "04d263d1-306a-4a5a-8625-34471fea65d8", + "metadata": {}, + "source": [ + "The METIS optical train includes the `SkycalcTERCurve` effect under the name `skycalc_atmosphere`. We assign it to a variable for convenience." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d65b08f-5384-456e-b6da-696eb2c8740a", + "metadata": {}, + "outputs": [], + "source": [ + "sky = metis['skycalc_atmosphere']" + ] + }, + { + "cell_type": "markdown", + "id": "991e9b1c-00e5-4622-a813-542c90887664", + "metadata": {}, + "source": [ + "## Inspecting and modifying sky parameters\n", + "\n", + "The list of parameters that are sent to the ESO skycalc server when requesting a sky spectrum can be obtained by simply printing the effect object:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8d3eac4-af5d-4cfc-aa15-20476fbb3ccf", + "metadata": {}, + "outputs": [], + "source": [ + "print(sky)" + ] + }, + { + "cell_type": "markdown", + "id": "e9136d40-f4ae-420c-bb48-3f12ab8215b7", + "metadata": {}, + "source": [ + "The emission and transmission spectra are returned as columns in `sky.skycalc_table` and can be plotted as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85df87ea-d8a4-4bf9-8638-bec13981a99c", + "metadata": {}, + "outputs": [], + "source": [ + "tbl = sky.skycalc_table\n", + "\n", + "# Extract columns and restrict to a smaller wavelength range\n", + "wavelength = tbl['wavelength'].to(u.um)\n", + "idx = (wavelength > 3.4*u.um) * (wavelength < 3.6*u.um)\n", + "transmission = tbl['transmission']\n", + "emission = tbl['emission']\n", + "\n", + "_, axes = plt.subplots(2, 1, figsize=(8, 8), sharex=True)\n", + "axes[0].plot(wavelength[idx], transmission[idx])\n", + "axes[0].set_ylabel(\"Transmission\")\n", + "axes[0].set_xlim(3.4, 3.6)\n", + "axes[1].plot(wavelength[idx], emission[idx])\n", + "axes[1].set_xlabel(f\"Wavelength [{wavelength.unit}]\")\n", + "axes[1].set_ylabel(f\"Radiance [{emission.unit}]\");" + ] + }, + { + "cell_type": "markdown", + "id": "f5e5a8fc-175e-444a-a827-afdf4aa2f675", + "metadata": {}, + "source": [ + "The effect has an `update()` method that can be used to change parameter values. The names of the available parameters can be obtained from the list printed above." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "099a72d2-09d6-4b0c-8e6f-73a54945adcd", + "metadata": {}, + "outputs": [], + "source": [ + "sky.update(airmass=3., pwv=20.)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8b1fddf-ac55-4742-8391-34b1a0799153", + "metadata": {}, + "outputs": [], + "source": [ + "tbl2 = sky.skycalc_table\n", + "\n", + "# Extract columns and restrict to a smaller wavelength range\n", + "wavelength2 = tbl2['wavelength'].to(u.um)\n", + "idx2 = (wavelength2 > 3.4*u.um) * (wavelength2 < 3.6*u.um)\n", + "transmission2 = tbl2['transmission']\n", + "emission2 = tbl2['emission']\n", + "\n", + "_, axes = plt.subplots(2, 1, figsize=(8, 8), sharex=True)\n", + "axes[0].plot(wavelength[idx], transmission[idx], lw=1)\n", + "axes[0].plot(wavelength2[idx2], transmission2[idx2], lw=1)\n", + "axes[0].set_ylabel(\"Transmission\")\n", + "axes[0].set_xlim(3.4, 3.6)\n", + "axes[1].plot(wavelength[idx], emission[idx], lw=1)\n", + "axes[1].plot(wavelength2[idx2], emission2[idx2], lw=1)\n", + "axes[1].set_xlabel(f\"Wavelength [{wavelength.unit}]\")\n", + "axes[1].set_ylabel(f\"Radiance [{emission.unit}]\");" + ] + }, + { + "cell_type": "markdown", + "id": "f9f76808-b785-4201-874c-3a74ff8c2431", + "metadata": {}, + "source": [ + "## Use in simulations\n", + "As an example of how the sky parameters affect observations we simulate METIS N-band images for a number of values of PWV (precipitable water vapour) and record the median background level in the (noiseless) `ImagePlane`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6f4c1421-b576-4242-b342-c920e621beb7", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=[\"img_n\"])\n", + "metis = sim.OpticalTrain(cmd)\n", + "metis['detector_linearity'].include = False # to avoid saturation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "547b5167-deb9-4611-b5d5-adfdfa59e160", + "metadata": {}, + "outputs": [], + "source": [ + "sky = metis['skycalc_atmosphere']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c736631-1935-4624-b2bc-89e5c1723502", + "metadata": {}, + "outputs": [], + "source": [ + "pwv_values = [0.5, 5, 10, 20]\n", + "bg_level = []\n", + "plt.figure()\n", + "lam = np.linspace(7, 12, 1001) * u.um\n", + "for pwv in pwv_values:\n", + " sky.update(pwv=pwv)\n", + " plt.plot(sky.surface.table['wavelength'].to(u.um), sky.surface.table['emission'], label=f\"pwv = {pwv}\", alpha=0.7) \n", + " metis.observe()\n", + " bg_level.append(np.median(metis.image_planes[0].data))\n", + "plt.legend();" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e03144ee-156d-4150-849d-80889e1b83f9", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(pwv_values, bg_level, '-o')\n", + "plt.ylim(0, 3e8)\n", + "plt.xlabel(\"PWV [mm]\")\n", + "plt.ylabel(\"ImagePlane level [e/s]\");" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/METIS/docs/readme.rst b/METIS/docs/readme.rst deleted file mode 100644 index e1cb7ad5..00000000 --- a/METIS/docs/readme.rst +++ /dev/null @@ -1,184 +0,0 @@ -.. |pic1| image:: metis_scopesim_logo.png - :width: 600px - :alt: METIS + ScopeSim - -|pic1| -====== - -Introduction ------------- -The METIS data simulator is based on the generic simulator software Scopesim, a descendant of the older SimCado/SimMETIS interface. METIS itself is handled as an instrument package that contains configuration files for the various instrument modes as well as data files describing the components of the instruments. -The new METIS data simulator currently supports the imaging and long-slit modes. The LM-band high-resolution IFU (LMS) mode will be offered soon. - - -Prerequisites -------------- - -- A working installation of a recent Python version -- A working installation of Jupyter if you want to run the simulator from notebooks. This is necessary to run the example notebooks contained in the instrument package. -- A working installation of the Python package installer pip - -.. note:: - - If you come across a bug or get stuck with a certain aspect of ScopeSim or - the METIS package, please get in touch with us (email addresses below). - - **Your feedback is the only way we know** what needs to be changed/improved - with the package and the simulator. - - Please always provide the output of the command ``scopesim.bug_report()`` run on your installation. - - -Installation & setup --------------------- - -This is a short overview of the installation and setup procedure; for a more detailed presentation see `Introduction_to_Scopesim_for_METIS `_. - -1. Install ``scopesim`` in your python environment:: - - $ pip install scopesim - - To upgrade an existing installation do:: - - $ pip install -U scopesim - -2. Create a working directory where you want to run simulations, e.g.:: - - $ mkdir ~/path/to/playing_with_scopesim/ - $ cd ~/path/to/playing_with_scopesim - -3. Install relevant irdb packages into this directory:: - - $ python - >> import scopesim - >> scopesim.download_packages(["METIS", "ELT", "Armazones"]) - - This will install the packages in the subdirectory ``./inst_pkgs``. - -4. The METIS package includes a number of tutorial notebooks in the directory ``./inst_pkgs/METIS/docs/example_notebooks/`` (see `Python notebooks`_). - - Copy notebooks to the working directory (i.e. ``./``) to run them.:: - - $ cp ./inst_pkgs/METIS/docs/example_notebooks/ . - -5. In a terminal, execute the notebook by calling:: - - $ jupyter notebook - -6. Follow instructions and explanations in the notebook. Some notebooks use example data; the commands to download these data from the scopesim server are included in the notebooks. - -You can then edit the notebooks and use them as a starting point for your own simulations. - - -Python notebooks ----------------- - -These notebooks can be found either: - -- [locally] in the METIS instrument package in ``docs/example_notebooks``, or -- [download] in the `METIS/docs section of the IRDB Github repository `_ - - -.. warning:: - Notebooks should be run in your working directory, **NOT** directly in the - ``docs/example_notebooks`` folder. Please copy the desired notebook out of - this folder. - -Ideally your folder structure should look like this:: - - working-dir - |- .iypnb - | - |- inst_pkgs - |- METIS - | |- docs - | |- example_notebooks - | |- .iypnb # copy out to working-dir - |- ELT - |- Armazones - - -Introductory notebooks -++++++++++++++++++++++ - -.. list-table:: - :widths: 25 75 - :width: 900px - :header-rows: 1 - - * - Name - - Description - * - | `Introduction_to_Scopesim_for_METIS.ipynb `_ - | `Introduction_to_Scopesim_for_METIS.pdf `_ - - Introductory overview of how to run simulations in Scopesim - -Scientific use-case notebooks -+++++++++++++++++++++++++++++ - -.. list-table:: - :widths: 25 75 - :width: 900px - :header-rows: 1 - - * - Name - - Description - * - `IMG_L_N-examples.ipynb `_ - - Imaging observations of HL Tau and an AGN model in the L and N band - * - `LSS-YSO_model_simulation.ipynb `_ - - Long-slit spectroscopy in the L-band of three models of a young stellar object - * - | `LSS_AGN-01_preparation.ipynb `_ - | `LSS_AGN-02_simulation.ipynb `_ - - | Long-slit spectroscopy in the N-band of an AGN model. The first notebook describes - | how the input data are prepared for Scopesim, the second runs the simulation. - -Notebooks on individual effects -+++++++++++++++++++++++++++++++ - -These notebooks can be found in ``docs/example_notebooks/demos``. - -.. list-table:: - :widths: 25 75 - :width: 900px - :header-rows: 1 - - * - Name - - Description - * - `demo_adc_wheel.ipynb `_ - - How to use the atmospheric dispersion correctors. - * - `demo_auto_exposure.ipynb `_ - - How to select `dit`/`ndit` automatically. - * - `demo_chopping_and_nodding.ipynb `_ - - How to produce chop-nod difference images in the N band. - * - `demo_detector_modes.ipynb `_ - - How to set detector readout modes. - * - `demo_filter_wheel.ipynb `_ - - How to use the filter wheel(s). - * - `demo_lss_simple.ipynb `_ - - Basic procedure for long-slit spectroscopy. - * - `demo_grating_efficiency.ipynb `_ - - Demonstration of spectral (grating) efficiency. - * - `demo_slit_wheel.ipynb `_ - - How to use the slit wheel for spectroscopy (and imaging) - * - `demo_rectify_traces.ipynb `_ - - How to obtain wavelength-calibrated and rectified 2D spectra. - -Documentation and useful references ------------------------------------ - -- `ScopeSim documentation `_ -- `Sky Object Templates documentation `_ -- `METIS homepage `_ -- For experts: GitHub repositories: - - + `simulator package ScopeSim `_ - + `instrument-specific packages irdb `_. - - -Contact points --------------- -`ScopeSim Slack `_ - -Email: - -- scopesim@univie.ac.at -- kieran.leschinski@univie.ac.at diff --git a/METIS/filters/TC_filter_ND-1.4.dat b/METIS/filters/TC_filter_ND-1.4.dat new file mode 100644 index 00000000..191e5d9b --- /dev/null +++ b/METIS/filters/TC_filter_ND-1.4.dat @@ -0,0 +1,16 @@ +# author : Oliver Czoske +# source : E-REP-ATC-MET-1003_3-0 +# date_created : 2026-03-16 +# date_modified : 2026-03-16 +# status : neutral density filter (3.5 mag attenuation = 3.98% transmission) +# type : filter:transmission +# wavelength_unit : um +# blue_cutoff : 2.55 +# red_cutoff : 5.45 +# changes : +# +wavelength transmission +2.5 0.0 +2.6 0.0398 +5.4 0.0398 +5.5 0.0 diff --git a/METIS/filters/TC_filter_ND-2.8.dat b/METIS/filters/TC_filter_ND-2.8.dat new file mode 100644 index 00000000..6328f4cc --- /dev/null +++ b/METIS/filters/TC_filter_ND-2.8.dat @@ -0,0 +1,16 @@ +# author : Oliver Czoske +# source : E-REP-ATC-MET-1003_3-0 +# date_created : 2026-03-16 +# date_modified : 2026-03-16 +# status : neutral density filter (7 mag attenuation = 0.158% transmission) +# type : filter:transmission +# wavelength_unit : um +# blue_cutoff : 2.55 +# red_cutoff : 5.45 +# changes : +# +wavelength transmission +2.5 0.0 +2.6 0.00158 +5.4 0.00158 +5.5 0.0 diff --git a/METIS/filters/TC_filter_closed.dat b/METIS/filters/TC_filter_closed.dat new file mode 100644 index 00000000..8d095bec --- /dev/null +++ b/METIS/filters/TC_filter_closed.dat @@ -0,0 +1,19 @@ +# author : Oliver Czoske +# source : Oliver Czoske +# date_created : 2026-03-16 +# date_modified : 2026-03-16 +# status : Closed filter (0% transmission) +# type : filter:transmission +# wavelength_unit : um +# center : 11.3 +# width : 17.5 +# blue_cutoff : 2.5 +# red_cutoff : 20.1 +# comment : for closed positions of filter wheels +# changes : +# +wavelength transmission +2.5 0.0 +2.6 1.e-32 +20.0 1.e-32 +20.1 0.0 diff --git a/METIS/headers/FITS_lms_keywords.yaml b/METIS/headers/FITS_lms_keywords.yaml index 3749fbed..6507841c 100644 --- a/METIS/headers/FITS_lms_keywords.yaml +++ b/METIS/headers/FITS_lms_keywords.yaml @@ -27,7 +27,7 @@ ID: ["lms-pwa", "LMS_PWA ID"] NAME: [" ", "LMS_PWA NAME"] POS: [0, "LMS_PWA position"] # TODO - POSNAME: ["open", "LMS_PWA named position"] + POSNAME: ["#lms-pp1.current_filter", "LMS_PWA named position"] STAT: ["Standstill", "LMS_PWA status"] OPTI6: # LMS spectral IFU mechanism diff --git a/METIS/headers/FITS_lss_keywords.yaml b/METIS/headers/FITS_lss_keywords.yaml index 0ccecf78..82059b3a 100644 --- a/METIS/headers/FITS_lss_keywords.yaml +++ b/METIS/headers/FITS_lss_keywords.yaml @@ -29,3 +29,6 @@ POS: [0, "IMG_N_PW position"] # TODO POSNAME: ["!OBS.grism_opti12", "IMG_N_PW named position"] STAT: ["Standstill", "IMG_N_PW status"] + + DRS: + SLIT: ["#slit_wheel.current_slit!", "Slit name"] diff --git a/METIS/metis_wcu_config.yaml b/METIS/metis_wcu_config.yaml index 29b06ec4..7cab7204 100644 --- a/METIS/metis_wcu_config.yaml +++ b/METIS/metis_wcu_config.yaml @@ -23,3 +23,4 @@ diam_is_out: 100 # [mm] diameter if integrating sphere output port rho_is: 0.95 # [] reflectivity of integrating sphere rho_tube: 0.95 # [] reflectivity of tube between BB and IS emiss_mask: 1.00 # [] emissivity of focal-plane mask +fibre_transmission: 0.1 # [] transmission of fibres injecting laser into IS diff --git a/MICADO/FITS_extra_keywords.yaml b/MICADO/FITS_extra_keywords.yaml index 558d09d3..7a84cb1f 100644 --- a/MICADO/FITS_extra_keywords.yaml +++ b/MICADO/FITS_extra_keywords.yaml @@ -22,7 +22,7 @@ MASK: NAME: "!OBS.fits_ins_mask" SLIT: - NAME: "!OBS.fits_ins_slit" + NAME: "#slit_wheel.current_slit!" CORO: NAME: "!OBS.fits_ins_coro" STOP: diff --git a/MICADO/MASK_slit_15000x50.dat b/MICADO/MASK_slit_15000x50.dat deleted file mode 100644 index 583588de..00000000 --- a/MICADO/MASK_slit_15000x50.dat +++ /dev/null @@ -1,19 +0,0 @@ -# description : Slit mask for the long, wide slit (15 arcsec x 50 mas) -# author : Kieran Leschinski -# source : My imagination -# date_created : 2019-07-10 -# date_modified : 2023-07-24 -# status : Guess - in the train on the way home from CM13 -# type : aperture:slit_geometry -# x_unit : arcsec -# y_unit : arcsec -# changes : -# - 2019-07-10 (KL) Created the file -# - 2020-03-24 (KL) Changed geometry to 15000x50mas -# - 2023-07-24 (OC) x position changed to design -# -x y --5.0 -0.025 -10.0 -0.025 -10.0 0.025 --5.0 0.025 diff --git a/MICADO/MASK_slit_3000x20.dat b/MICADO/MASK_slit_3000x20.dat deleted file mode 100644 index 37733d41..00000000 --- a/MICADO/MASK_slit_3000x20.dat +++ /dev/null @@ -1,18 +0,0 @@ -# description : Slit mask for the short, narrow slit (3 arcsec x 20 mas) -# author : Kieran Leschinski -# source : My imagination -# date_created : 2019-07-10 -# date_modified : 2019-07-10 -# status : Guess - in the train on the way home from CM13 -# type : aperture:slit_geometry -# x_unit : arcsec -# y_unit : arcsec -# changes : -# - 2019-07-10 (KL) Created the file -# - 2020-03-24 (KL) Changed geometry to 3000x20mas -# -x y --1.5 -0.01 -1.5 -0.01 -1.5 0.01 --1.5 0.01 diff --git a/MICADO/MASK_slit_3000x50.dat b/MICADO/MASK_slit_3000x50.dat deleted file mode 100644 index 8146ce27..00000000 --- a/MICADO/MASK_slit_3000x50.dat +++ /dev/null @@ -1,18 +0,0 @@ -# description : Slit mask for the short, wide slit (3 arcsec x 50 mas) -# author : Kieran Leschinski -# source : My imagination -# date_created : 2019-07-10 -# date_modified : 2019-07-10 -# status : Guess - in the train on the way home from CM13 -# type : aperture:slit_geometry -# x_unit : arcsec -# y_unit : arcsec -# changes : -# - 2019-07-10 (KL) Created the file -# - 2020-03-24 (KL) Changed geometry to 3000x50mas -# -x y --1.5 -0.025 -1.5 -0.025 -1.5 0.025 --1.5 0.025 diff --git a/MICADO/MASK_slit_15000x20.dat b/MICADO/MASK_slit_Long.dat similarity index 100% rename from MICADO/MASK_slit_15000x20.dat rename to MICADO/MASK_slit_Long.dat diff --git a/MICADO/MASK_slit_Long_offset.dat b/MICADO/MASK_slit_Long_offset.dat new file mode 100644 index 00000000..d1ec03b6 --- /dev/null +++ b/MICADO/MASK_slit_Long_offset.dat @@ -0,0 +1,21 @@ +# description : Slit mask for the offset long slit (15 arcsec x 20 mas) +# author : Kieran Leschinski, Oliver Czoske +# source : ELT-TRE-MCD-56300-0014_3.0 +# date_created : 2026-02-03 +# date_modified : 2026-02-03 +# status : FDR design +# type : aperture:slit_geometry +# x_unit : arcsec +# y_unit : arcsec +# changes : +# - 2019-07-10 (KL) Created the file +# - 2020-03-24 (KL) Changed geometry to 15000x50mas +# - 2023-07-13 (OC) Changed geometry to 15000x20mas +# - 2023-07-24 (OC) Position in x corrected +# - 2026-02-03 (OC) Initialised from MASK_slit_15000x20.dat +# +x y +-5.0 1.190 +10.0 1.190 +10.0 1.210 +-5.0 1.210 diff --git a/MICADO/MASK_slit_3000x16.dat b/MICADO/MASK_slit_Short.dat similarity index 100% rename from MICADO/MASK_slit_3000x16.dat rename to MICADO/MASK_slit_Short.dat diff --git a/MICADO/MASK_slit_Short_offset.dat b/MICADO/MASK_slit_Short_offset.dat new file mode 100644 index 00000000..252042d0 --- /dev/null +++ b/MICADO/MASK_slit_Short_offset.dat @@ -0,0 +1,20 @@ +# description : Slit mask for the offset short, narrow slit (3 arcsec x 16 mas) +# author : Kieran Leschinski, Oliver Czoske +# source : ELT-TRE-MCD-56300-0014_3.0 +# date_created : 2026-02-03 +# date_modified : 2026-02-03 +# status : FDR design +# type : aperture:slit_geometry +# x_unit : arcsec +# y_unit : arcsec +# changes : +# - 2019-07-10 (KL) Created the file +# - 2020-03-24 (KL) Changed geometry to 3000x20mas +# - 2023-07-13 (OC) Changed geometry to 3000x16mas +# - 2026-02-03 (OC) Initialised from MASK_slit_3000x16.dat +# +x y +-1.5 1.192 +1.5 1.192 +1.5 1.208 +-1.5 1.208 diff --git a/MICADO/MASK_slit_3000x48.dat b/MICADO/MASK_slit_Wide.dat similarity index 100% rename from MICADO/MASK_slit_3000x48.dat rename to MICADO/MASK_slit_Wide.dat diff --git a/MICADO/MASK_slit_Wide_offset.dat b/MICADO/MASK_slit_Wide_offset.dat new file mode 100644 index 00000000..450b4b98 --- /dev/null +++ b/MICADO/MASK_slit_Wide_offset.dat @@ -0,0 +1,20 @@ +# description : Slit mask for the offset short, wide slit (3 arcsec x 48 mas) +# author : Kieran Leschinski, Oliver Czoske +# source : ELT-TRE-MCD-56300-0014_3.0 +# date_created : 2026-02-03 +# date_modified : 2026-02-03 +# status : FDR design +# type : aperture:slit_geometry +# x_unit : arcsec +# y_unit : arcsec +# changes : +# - 2019-07-10 (KL) Created the file +# - 2020-03-24 (KL) Changed geometry to 3000x50mas +# - 2023-07-13 (OC) Changed geometry to 3000x48mas +# - 2026-02-03 (OC) Initialised from MASK_slit_3000x48.dat +# +x y +-1.5 1.176 +1.5 1.176 +1.5 1.224 +-1.5 1.224 diff --git a/MICADO/MICADO.yaml b/MICADO/MICADO.yaml index 64e93c48..19f147e2 100644 --- a/MICADO/MICADO.yaml +++ b/MICADO/MICADO.yaml @@ -31,6 +31,22 @@ effects: pixel_scale : "!INST.pixel_scale" filename : "INST_MICADO_wavefront_error_budget.dat" + +- name: slit_wheel + description: collection of field masks and slits + class: SlitWheel + kwargs: + slit_names: + - Short + - Short_offset + - Wide + - Wide_offset + - Long + - Long_offset + filename_format: MASK_slit_{}.dat + current_slit: "!OBS.slit" + include: "!OBS.slit" + - name: filter_wheel_1 description: upper filter wheel class: FilterWheel @@ -75,7 +91,7 @@ effects: - xY1 filename_format: "!INST.filter_file_format" current_filter: "!OBS.filter_name_fw2" - minimum_throughput: 1.01e-4 + minimum_throughput: 1.01e-33 outer: 0.2 outer_unit: "m" diff --git a/MICADO/MICADO_H4RG.yaml b/MICADO/MICADO_H4RG.yaml index 0e3767ea..9e3fc291 100644 --- a/MICADO/MICADO_H4RG.yaml +++ b/MICADO/MICADO_H4RG.yaml @@ -52,7 +52,7 @@ effects: class: DarkCurrent # [e-/s] level of dark current for each detector kwargs: - value: 0.1 + value: 0.01 # ELT-TRE-MCD-56300-0173_1-4 - name: shot_noise description: apply poisson shot noise to images @@ -67,6 +67,7 @@ effects: - name: border_reference_pixels description: Blanks the signal on N edge row and column pixels class: ReferencePixelBorder + include: False kwargs: border: [0, 0, 0, 0] diff --git a/MICADO/MICADO_SPEC.yaml b/MICADO/MICADO_SPEC.yaml index dad84b46..076bc829 100644 --- a/MICADO/MICADO_SPEC.yaml +++ b/MICADO/MICADO_SPEC.yaml @@ -10,17 +10,6 @@ properties : decouple_detector_from_sky_headers: True # needed for slit spectroscopy effects : -- name : spec_mode_optics - description : list of extra mirrors needed for the spectroscopy mode - class : SurfaceList - kwargs : - filename : LIST_MICADO_mirrors_spec.dat - -- name : spectroscopic_slit_aperture - class : ApertureMask - kwargs : - filename : "!OBS.slit_file" - - name : grating_efficiency description : grating efficiency for spectral orders class : SpectralEfficiency @@ -58,4 +47,4 @@ name : SPEC properties : obs_mode: "SPEC" fits_ins_mode: "SPE" - fits_ins_mask: "" \ No newline at end of file + fits_ins_mask: "Small" diff --git a/MICADO/default.yaml b/MICADO/default.yaml index 3bf9c7d5..6f5937f9 100644 --- a/MICADO/default.yaml +++ b/MICADO/default.yaml @@ -6,7 +6,7 @@ alias: OBS name: MICADO_default_configuration description: default parameters needed for a MICADO simulation status: development -needs_scopesim: "v0.10.0b4" +needs_scopesim: "v0.11.3" date_modified: 2025-10-09 changes: - 2023-07-13 (OC) add modes for FDR slits, deprecate pre-FDR slits @@ -14,6 +14,7 @@ changes: - 2025-10-09 (OC) proper MJD value - 2025-10-17 (JB) add parametes for FITS keywords, tplstart as MJD - 2026-01-02 (OC) random seed to None + - 2026-04-09 (OC) new SPEC mode, rename slits packages: - Armazones @@ -34,6 +35,7 @@ properties : declination : -30 hour_angle : 0 pupil_angle : 0 + slit: false # overridden in spectroscopic modes dit : 60 ndit : 1 catg : SCIENCE @@ -106,113 +108,70 @@ mode_yamls : yamls : - MICADO_IMG_HCI.yaml +- object: observation + alias: OBS + name: SPEC + description: "spectrograph: all slits" + status: development + yamls: + - MICADO_SPEC.yaml + properties: # Todo: these parameters all need to be changeable + trace_file: TRACE_MICADO.fits + slit: Short + filter_name_fw1: Spec_IJ + filter_name_fw2: open + filter_name_pupil: open + tech: SPEC + fits_ins_mode: SPE + fits_ins_filt: Spec_IJ + - object : observation alias: OBS name : SPEC_15000x20 description : "spectrograph : slit size 15000x20mas" - status: development + status: deprecated + deprecate: "Deprecated mode, use SPEC with '!OBS.slit'='Long' instead" yamls : - MICADO_SPEC.yaml properties : trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_15000x20.dat + slit : Long filter_name_fw1 : Spec_HK filter_name_fw2 : open filter_name_pupil : open fits_ins_filt : Spec_HK - fits_ins_slit : "Long" - object : observation alias: OBS name : SPEC_3000x48 description : "spectrograph : slit size 3000x48mas" - status: development + status: deprecated + deprecate: "Deprecated mode, use SPEC with '!OBS.slit'='Wide' instead" yamls : - MICADO_SPEC.yaml properties : trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_3000x48.dat + slit : Wide filter_name_fw1 : Spec_HK filter_name_fw2 : open filter_name_pupil : open fits_ins_filt : Spec_HK - fits_ins_slit : "Wide" - object : observation alias : OBS name : SPEC_3000x16 description : "spectrograph : slit size 3000x16mas" - status: development + status: deprecated + deprecate: "Deprecated mode, use SPEC with '!OBS.slit'='Short' instead" yamls : - MICADO_SPEC.yaml properties : trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_3000x16.dat + slit: Short filter_name_fw1 : Spec_IJ filter_name_fw2 : open filter_name_pupil : open fits_ins_filt : Spec_IJ - fits_ins_slit : "Short" - -- object : observation - alias: OBS - name : SPEC_15000x50 - description : "spectrograph : slit size 15000x50mas" - status: deprecated - deprecate : "Deprecated instrument mode. For spectroscopy use - - SPEC_3000x16 - - SPEC_3000x48 - - SPEC_15000x20" - yamls : - - MICADO_SPEC.yaml - properties : - trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_15000x50.dat - filter_name_fw1: Spec_HK - filter_name_fw2: open - filter_name_pupil: open - fits_ins_filt : Spec_HK - fits_ins_slit : "Long" - -- object : observation - alias: OBS - name : SPEC_3000x50 - description : "spectrograph : slit size 3000x50mas" - status: deprecated - deprecate : "Deprecated instrument mode. For spectroscopy use - - SPEC_3000x16 - - SPEC_3000x48 - - SPEC_15000x20" - yamls : - - MICADO_SPEC.yaml - properties : - trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_3000x50.dat - filter_name_fw1: Spec_HK - filter_name_fw2: open - filter_name_pupil: open - fits_ins_filt : Spec_HK - fits_ins_slit : "Wide" - -- object : observation - alias: OBS - name : SPEC_3000x20 - description : "spectrograph : slit size 3000x20mas" - status: deprecated - deprecate : "Deprecated instrument mode. For spectroscopy use - - SPEC_3000x16 - - SPEC_3000x48 - - SPEC_15000x20" - yamls : - - MICADO_SPEC.yaml - properties : - trace_file : TRACE_MICADO.fits - slit_file : MASK_slit_3000x20.dat - filter_name_fw1: Spec_HK - filter_name_fw2: open - filter_name_pupil: open - fits_ins_filt : Spec_HK - fits_ins_slit : "Short" --- ### default simulation parameters needed for a MICADO simulation @@ -230,6 +189,9 @@ properties : wave_mid : 1.6 wave_max : 2.5 + sub_pixel: + flag: True + computing : preload_field_of_views : True diff --git a/MICADO/docs/README.md b/MICADO/docs/README.md new file mode 100644 index 00000000..3a5df1f6 --- /dev/null +++ b/MICADO/docs/README.md @@ -0,0 +1,101 @@ +```{image} micado_scopesim_logo.png +:width: 600px +:alt: MICADO + ScopeSim +:align: center +``` + +# MICADO + ScopeSim + +## Introduction + +A MICADO data simulator is being developed as part of the generic simulator +ScopeSim, a descendant of the older SimCADO software. MICADO is the +near-infrared camera for the ELT and supports both MCAO (4 mas) and SCAO +(1.5 mas and 4 mas) imaging modes. + +```{note} +**Bug reports and help desk** + +If you come across a bug or get stuck with ScopeSim or the MICADO package, +please [open an issue on GitHub](https://github.com/AstarVienna/irdb/issues) +or contact us by email (see below). + +**Your feedback is the only way we know** what needs to be +changed or improved with the package and the simulator. + +Please always include the output of `scopesim.bug_report()` from your +installation. +``` + +## Downloading the MICADO instrument package + +Once ScopeSim is installed, download the MICADO instrument package into your +working directory: + +```python +import scopesim +scopesim.download_packages(["Armazones", "ELT", "MICADO"]) +``` + +This installs the packages into the subdirectory `./inst_pkgs/`. + +Your working directory should look like this afterwards: + +``` +my_simulations/ +├── .ipynb +└── inst_pkgs/ + ├── Armazones/ + ├── ELT/ + └── MICADO/ + └── docs/ + └── example_notebooks/ + └── .ipynb ← copy to working dir before running +``` + +```{include} ../../docs/ScopeSim_guide.md +``` + +## Example notebooks + +Download the notebooks from the +[GitHub repository](https://github.com/AstarVienna/irdb/tree/dev_master/MICADO/docs/example_notebooks) +or find them locally in `inst_pkgs/MICADO/docs/example_notebooks/` after +downloading the package. + +```{warning} +Run notebooks in your working directory, **not** inside `inst_pkgs/`. +Copy the desired notebook out first. +``` + +### Scientific use-case notebooks + +```{toctree} +:maxdepth: 1 + +example_notebooks/1_scopesim_MCAO_4mas_galaxy +example_notebooks/2_scopesim_SCAO_1.5mas_astrometry +example_notebooks/3_scopesim_SCAO_4mas_fv-psf +example_notebooks/MICADO_FAQs +``` + +| Notebook | Description | +|----------|-------------| +| `1_scopesim_MCAO_4mas_galaxy` | MCAO 4 mas imaging of a galaxy | +| `2_scopesim_SCAO_1.5mas_astrometry` | SCAO 1.5 mas astrometry use case | +| `3_scopesim_SCAO_4mas_fv-psf` | SCAO 4 mas field-varying PSF | +| `MICADO_FAQs` | Frequently asked questions | + +## Validation + +The table below shows limiting-magnitude test results (minimum S/N = 5). +Green = passed, yellow = expected deviation, red = unexpected failure. +**Click** a row to see the test plot. + +```{eval-rst} +.. validation-report:: ./MICADO/test_micado/validation_results.xml +``` + +The test code lives in the +[MICADO/test_micado/](https://github.com/AstarVienna/irdb/tree/dev_master/MICADO/test_micado/) +folder on GitHub. diff --git a/MICADO/docs/example_notebooks/3_scopesim_SCAO_4mas_fv-psf.ipynb b/MICADO/docs/example_notebooks/3_scopesim_SCAO_4mas_fv-psf.ipynb index f8311a02..7bac5559 100644 --- a/MICADO/docs/example_notebooks/3_scopesim_SCAO_4mas_fv-psf.ipynb +++ b/MICADO/docs/example_notebooks/3_scopesim_SCAO_4mas_fv-psf.ipynb @@ -18,16 +18,13 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "unlimited-cliff", "metadata": {}, "outputs": [], "source": [ - "%matplotlib inline\n", - "import datetime\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", - "from matplotlib.colors import LogNorm\n", "from astropy import units as u\n", "\n", "import scopesim as sim\n", @@ -58,7 +55,7 @@ "id": "formed-metabolism", "metadata": {}, "source": [ - "### Set up an open cluster ``Source`` object\n", + "## Set up an open cluster ``Source`` object\n", "\n", "The first step is to create a ``Source`` object. \n", "Here we take advantage of the ``cluster`` function from the ``ScopeSim_Templates.stellar.clusters`` submodule.\n", @@ -74,44 +71,22 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "altered-paris", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[32mimf - sample_imf: Setting maximum allowed mass to 10000\u001b[0m\n", - "\u001b[32mimf - sample_imf: Loop 0 added 1.01e+04 Msun to previous total of 0.00e+00 Msun\u001b[0m\n" - ] - } - ], + "outputs": [], "source": [ "cluster = sim_tp.cluster(mass=10000, core_radius=0.5, distance=8000)" ] }, { "cell_type": "code", - "execution_count": 3, - "id": "universal-qatar", + "execution_count": null, + "id": "9f3f68de-ca2a-470f-928e-6b2c95da4415", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "fig, ax = plt.subplots()\n", - "ax.plot(cluster.fields[0][\"x\"], cluster.fields[0][\"y\"], \".\")\n", - "ax.set_aspect('equal', 'datalim')" + "cluster.plot();" ] }, { @@ -119,29 +94,19 @@ "id": "enhanced-strip", "metadata": {}, "source": [ - "### Set up the MICADO optical system for SCAO and include a field-varying PSF\n", + "## Set up the MICADO optical system for SCAO and include a field-varying PSF\n", "\n", - "The next step is the standard proceedure - set the instrument to ``MICADO`` and the modes to ``SCAO`` and ``IMG_4mas``, then create an ``OpticalTrain`` object." + "The next step is the standard proceedure - set the instrument to ``MICADO`` and the modes to ``SCAO`` and ``IMG_4mas``, then create an ``Simulation`` object." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "continent-springer", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ - "observation_dict = {\n", - " \"!OBS.mjdobs\": datetime.datetime(2022, 1, 1, 2, 30, 0)\n", - "}\n", - "\n", - "cmd = sim.UserCommands(\n", - " use_instrument=\"MICADO\",\n", - " set_modes=[\"SCAO\", \"IMG_4mas\"],\n", - ")\n", - "micado = sim.OpticalTrain(cmd)" + "micado = sim.Simulation(\"MICADO\", [\"SCAO\", \"IMG_4mas\"])" ] }, { @@ -159,75 +124,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "peripheral-monday", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Table length=23\n", - "
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elementnameclassincluded
str13str29str31bool
armazonesskycalc_atmosphereSkycalcTERCurveTrue
ELTtelescope_reflectionSurfaceListTrue
MICADOmicado_static_surfacesSurfaceListTrue
MICADOmicado_ncpas_psfNonCommonPathAberrationTrue
MICADOfilter_wheel_1 : [open]FilterWheelTrue
MICADOfilter_wheel_2 : [Ks]FilterWheelTrue
MICADOpupil_wheel : [open]FilterWheelTrue
MICADO_DETfull_detector_arrayDetectorListFalse
MICADO_DETdetector_windowDetectorWindowTrue
MICADO_DETqe_curveQuantumEfficiencyCurveTrue
............
MICADO_DETdetector_linearityLinearityCurveTrue
MICADO_DETborder_reference_pixelsReferencePixelBorderTrue
MICADO_DETreadout_noisePoorMansHxRGReadoutNoiseTrue
MICADO_DETsource_fits_keywordsSourceDescriptionFitsKeywordsTrue
MICADO_DETextra_fits_keywordsExtraFitsKeywordsTrue
default_rorelay_psfFieldConstantPSFTrue
default_rorelay_surface_listSurfaceListTrue
default_roextra_fits_keywords_roExtraFitsKeywordsTrue
MICADO_IMG_LRmicado_wide_field_mirror_listSurfaceListTrue
MICADO_IMG_LRmicado_adc_3D_shiftAtmosphericDispersionCorrectionFalse
" - ], - "text/plain": [ - "\n", - " element name ... included\n", - " str13 str29 ... bool \n", - "------------- ----------------------------- ... --------\n", - " armazones skycalc_atmosphere ... True\n", - " ELT telescope_reflection ... True\n", - " MICADO micado_static_surfaces ... True\n", - " MICADO micado_ncpas_psf ... True\n", - " MICADO filter_wheel_1 : [open] ... True\n", - " MICADO filter_wheel_2 : [Ks] ... True\n", - " MICADO pupil_wheel : [open] ... True\n", - " MICADO_DET full_detector_array ... False\n", - " MICADO_DET detector_window ... True\n", - " MICADO_DET qe_curve ... True\n", - " ... ... ... ...\n", - " MICADO_DET detector_linearity ... True\n", - " MICADO_DET border_reference_pixels ... True\n", - " MICADO_DET readout_noise ... True\n", - " MICADO_DET source_fits_keywords ... True\n", - " MICADO_DET extra_fits_keywords ... True\n", - " default_ro relay_psf ... True\n", - " default_ro relay_surface_list ... True\n", - " default_ro extra_fits_keywords_ro ... True\n", - "MICADO_IMG_LR micado_wide_field_mirror_list ... True\n", - "MICADO_IMG_LR micado_adc_3D_shift ... False" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "micado.effects" + "micado.optical_train" ] }, { @@ -243,12 +145,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "subjective-parallel", "metadata": {}, "outputs": [], "source": [ - "micado[\"relay_psf\"].include = False" + "micado.optical_train[\"relay_psf\"].include = False" ] }, { @@ -261,28 +163,36 @@ "\n", "A small library of precomputed PSFs can be found on the ScopeSim server: https://scopesim.univie.ac.at/InstPkgSvr/psfs/\n", "\n", - "Once we have downloaded the PSF cube of our choice (in this case the cube corresponding to ESO median atmospheric conditions) we can pass the file path to the ``FieldVaryingPSF`` object." + "Once we have downloaded the PSF cube of our choice (in this case the cube corresponding to ESO median atmospheric conditions) we can pass the file path to the ``FieldVaryingPSF`` object.\n", + "\n", + "
For the purpose of testing this notebook, we're using a much smaller test PSF file. If you'd like to see the real deal, simply uncomment the one below and comment out the test file instead.
" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "c9b0961b", "metadata": {}, "outputs": [], "source": [ "from pooch import retrieve\n", + "# fname = retrieve(\n", + "# \"https://scopesim.univie.ac.at/InstPkgSvr/psfs/AnisoCADO_SCAO_FVPSF_4mas_EsoMedian_20190328.fits\",\n", + "# known_hash=\"a9bd309e5ac025f2aa5f8ded85323465578906e47025ce86501985c9b258474c\",\n", + "# fname=\"AnisoCADO_SCAO_FVPSF_4mas_EsoMedian_20190328.fits\",\n", + "# progressbar=True,\n", + "# )\n", "fname = retrieve(\n", - " \"https://scopesim.univie.ac.at/InstPkgSvr/psfs/AnisoCADO_SCAO_FVPSF_4mas_EsoMedian_20190328.fits\",\n", - " known_hash=\"a9bd309e5ac025f2aa5f8ded85323465578906e47025ce86501985c9b258474c\",\n", - " fname=\"AnisoCADO_SCAO_FVPSF_4mas_EsoMedian_20190328.fits\",\n", + " \"https://scopesim.univie.ac.at/InstPkgSvr/psfs/test_fvpsf.fits\",\n", + " known_hash=\"c13aba82e4faf42568b5996f3d32135ddb69b537a832c753da189b698a7ad48c\",\n", + " fname=\"test_fvpsf.fits\",\n", " progressbar=True,\n", ")" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "improving-august", "metadata": {}, "outputs": [], @@ -300,12 +210,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "elegant-swimming", "metadata": {}, "outputs": [], "source": [ - "micado.optics_manager[\"default_ro\"].add_effect(fv_psf)" + "micado.optical_train.optics_manager[\"default_ro\"].add_effect(fv_psf)" ] }, { @@ -321,17 +231,16 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "revised-paper", "metadata": {}, "outputs": [], "source": [ - "micado.cmds[\"!OBS.dit\"] = 600 # [s]\n", - "micado.cmds[\"!DET.x\"] = 10 # [arcsec]\n", - "micado.cmds[\"!DET.y\"] = 10\n", + "micado.settings[\"!OBS.dit\"] = 600 # [s]\n", + "micado.settings[\"!DET.x\"] = 10 # [arcsec]\n", + "micado.settings[\"!DET.y\"] = 10\n", "\n", - "micado.observe(cluster)\n", - "hdus = micado.readout()" + "hdus = micado(cluster)" ] }, { @@ -347,41 +256,19 @@ "id": "animated-multiple", "metadata": {}, "source": [ - "## !!! It appears" + "## First look at limited FOV" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "prescription-certificate", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "plt.figure(figsize=(20, 20))\n", - "plt.subplot(121)\n", - "im = hdus[0][1].data\n", - "plt.imshow(im, origin=\"lower\", norm=LogNorm(vmin=0.9*np.median(im), vmax=1.1*np.median(im)))" + "_, ax = plt.subplots(figsize=(12, 12))\n", + "img = hdus[1].data\n", + "ax.imshow(img, origin=\"lower\", norm=\"log\", vmin=0.9*np.median(img), vmax=1.1*np.median(img));" ] }, { @@ -389,23 +276,24 @@ "id": "wrong-excuse", "metadata": {}, "source": [ + "## Larger view\n", + "\n", "Alternatively we could re-centre the detector window, but expand the window size to 4096x4096 pixels (16x16 arcsecond) which is the equivalent of the central MICADO detector." ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "romantic-birth", "metadata": {}, "outputs": [], "source": [ - "micado.cmds[\"!DET.x\"] = 0 \n", - "micado.cmds[\"!DET.y\"] = 0\n", - "micado.cmds[\"!DET.width\"] = 4096\n", - "micado.cmds[\"!DET.height\"] = 4096\n", + "micado.settings[\"!DET.x\"] = 0 \n", + "micado.settings[\"!DET.y\"] = 0\n", + "micado.settings[\"!DET.width\"] = 4096\n", + "micado.settings[\"!DET.height\"] = 4096\n", "\n", - "micado.observe(cluster)\n", - "hdus = micado.readout()" + "hdus = micado(cluster)" ] }, { @@ -421,36 +309,14 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "patient-thinking", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "plt.figure(figsize=(20, 20))\n", - "plt.subplot(121)\n", - "im = hdus[0][1].data\n", - "plt.imshow(im, origin=\"lower\", norm=LogNorm(vmin=0.9*np.median(im), vmax=3*np.median(im)))" + "_, ax = plt.subplots(figsize=(12, 12))\n", + "img = hdus[1].data\n", + "ax.imshow(img, origin=\"lower\", norm=\"log\", vmin=0.9*np.median(img), vmax=3*np.median(img));" ] }, { @@ -458,9 +324,9 @@ "id": "quality-scroll", "metadata": {}, "source": [ - "### Swap between a detector window and the full detector array\n", + "## Full detector array\n", "\n", - "**WARNING! It is ONLY recommended to run the full MICADO detector configuration is you have >8 GB of RAM**\n", + "
It is ONLY recommended to run the full MICADO detector configuration is you have >8 GB of RAM
\n", "\n", "While the ``MICADO`` package only has a customisable detector window for simulated observations, the ``MICADO`` package contains a full description of the 9 detectors in the MICADO detector array.\n", "\n", @@ -475,13 +341,13 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "collectible-actress", "metadata": {}, "outputs": [], "source": [ - "# micado[\"full_detector_array\"].include = True\n", - "# micado[\"detector_window\"].include = False" + "# micado.optical_train[\"full_detector_array\"].include = True\n", + "# micado.optical_train[\"detector_window\"].include = False" ] }, { @@ -494,13 +360,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "mounted-burns", "metadata": {}, "outputs": [], "source": [ - "# micado.observe(cluster)\n", - "# micado.readout(filename=\"micado_full_detector.fits\")" + "# micado(cluster, filename=\"micado_full_detector.fits\")" ] } ], @@ -520,7 +385,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.13.5" } }, "nbformat": 4, diff --git a/MICADO/docs/example_notebooks/MICADO_line_lists.ipynb b/MICADO/docs/example_notebooks/MICADO_line_lists.ipynb index 6b7d9776..4a606cf4 100644 --- a/MICADO/docs/example_notebooks/MICADO_line_lists.ipynb +++ b/MICADO/docs/example_notebooks/MICADO_line_lists.ipynb @@ -55,7 +55,7 @@ "metadata": {}, "outputs": [], "source": [ - "cmd = sim.UserCommands(use_instrument=\"MICADO\", set_modes=[\"SCAO\", \"SPEC_3000x50\"])\n", + "cmd = sim.UserCommands(use_instrument=\"MICADO\", set_modes=[\"SCAO\", \"SPEC_3000x48\"])\n", "cmd[\"!OBS.dit\"] = 3600\n", "cmd[\"!OBS.filter_name_fw1\"] = \"Spec_HK\" # Spec_IJ, Spec_HK\n", "cmd[\"!OBS.filter_name_fw2\"] = \"open\"\n", diff --git a/MICADO/docs/extra_notebooks/MICADO_spectro_demo.ipynb b/MICADO/docs/extra_notebooks/MICADO_spectro_demo.ipynb new file mode 100644 index 00000000..92998dfb --- /dev/null +++ b/MICADO/docs/extra_notebooks/MICADO_spectro_demo.ipynb @@ -0,0 +1,478 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "f07c9a9c-5712-4460-8d37-1c5fcdb96c02", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from astropy import units as u\n", + "from astropy.wcs import WCS\n", + "from astropy.io import fits" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b4e44d7-1c5b-44b6-b427-8595fc3de620", + "metadata": {}, + "outputs": [], + "source": [ + "import scopesim as sim" + ] + }, + { + "cell_type": "markdown", + "id": "46bea0e0-6792-44a2-9a67-3907409d7158", + "metadata": {}, + "source": [ + "This notebook shows new features of the MICADO spectroscopy implementation in ScopeSim. In particular, we look at the new spectroscopic mode `SPEC`, which uses a `SlitWheel` effect to allow changing slits easily. The `SlitWheel` (really a focal-plane mask wheel) is now also available in the imaging modes and thus allows through-slit imaging as well as the use of a pinhole-grid mask.\n", + "The previous modes `SPEC_3000x16` etc. are still available. They also use `SlitWheel` but have default settings as advertised by the mode name; scripts and notebooks using these modes should therefore continue to work as before.\n", + "\n", + "If you have not done so already, please download the relevant instrument packages using the following code in a new cell:\n", + "\n", + "```sim.download_packages([\"Armazones\", \"ELT\", \"MICADO\"])```\n", + "\n", + "Alternatively, if you would like to keep the instrument packages in a separate directory, you can set the following config value:\n", + "\n", + "```sim.set_inst_pkgs_path(\"path/to/packages\")```\n", + "\n", + "\n", + "## Imaging of the available slits\n", + "\n", + "To see all the available slits, we instantiate the `OpticalTrain` in imaging mode:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "226ac865-88eb-4594-848f-beba66930c21", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"MICADO\", set_modes=[\"SCAO\", \"IMG_4mas\"])\n", + "mcd = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "markdown", + "id": "bb292d1a-4139-4a3e-895d-395a60838e5d", + "metadata": {}, + "source": [ + "The effects list has the `SlitWheel` effect in the `MICADO` group; as for the `FilterWheel` effects the name of the current slit is given in parentheses. In imaging mode, the default is `False`, i.e. no slit is inserted." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "403e9ca5-2dc2-4a56-b2cd-e30ccdf48450", + "metadata": {}, + "outputs": [], + "source": [ + "mcd.effects.show_in_notebook()" + ] + }, + { + "cell_type": "markdown", + "id": "2f6f8ab1-5fbf-4a67-ad4b-f2638ec7feca", + "metadata": {}, + "source": [ + "The slit wheel holds a number of predefined slits; these can be displayed with" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b4961610-2fdd-4b7a-a137-94c5247571bb", + "metadata": {}, + "outputs": [], + "source": [ + "mcd['slit_wheel'].slits" + ] + }, + { + "cell_type": "markdown", + "id": "d5ce6206-8aed-4c9e-a479-240e800ece3f", + "metadata": {}, + "source": [ + "In addition to the nominal slits (centred at 0, 0), there are offset slits shifted by 1.2 arcsec in the dispersion direction. They are meant to fill in the gaps in the spectra due to the gaps between the chips in the detector array.\n", + "\n", + "To change the slit, use `mcd['slit_wheel'].change_filter()`. We'll do imaging observations with all slits, using a blank-sky background." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8563486-17a7-4486-ba04-6bb77d43bcd2", + "metadata": {}, + "outputs": [], + "source": [ + "_, axes = plt.subplots(3, 2, figsize=(7, 10))\n", + "for slit, ax in zip(mcd['slit_wheel'].slits, axes.flatten()):\n", + " mcd['slit_wheel'].change_slit(slit)\n", + " mcd.observe()\n", + " ax.imshow(mcd.image_planes[0].data, origin='lower')\n", + " ax.text(1000, 1000, slit, va='top', ha='right', c='white') " + ] + }, + { + "cell_type": "markdown", + "id": "c87edabd-5dec-427b-b1c0-3aac27011a0b", + "metadata": {}, + "source": [ + "Note that these simulations used a detector window of 1024x1024 pixels rather than the full MICADO array. The long slit extends over 15000mas/4mas = 3750 pixels in is therefore cut in these image." + ] + }, + { + "cell_type": "markdown", + "id": "efa6c546-efda-4d2f-800b-4bb185051787", + "metadata": {}, + "source": [ + "## Through-slit imaging of a source\n", + "Through-slit images are taken for target acquisition but can also be used to investigate slit losses due to parts of the PSF falling outside the slits. Here we observe a point source." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd44ee2a-5e84-4db7-8861-5018d06b3e89", + "metadata": {}, + "outputs": [], + "source": [ + "star = sim.source.source_templates.star(flux=15*u.mag)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d6089da-b9b3-4e79-8c52-8078df93326d", + "metadata": {}, + "outputs": [], + "source": [ + "mcd['slit_wheel'].change_slit(\"3000x48\")\n", + "mcd.observe(star)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "abbdb5cc-83b3-450d-ae7e-a6ef48aaef37", + "metadata": {}, + "outputs": [], + "source": [ + "plt.imshow(mcd.image_planes[0].data, norm='log', origin='lower')\n", + "plt.xlim(480, 550)\n", + "plt.ylim(500, 526);" + ] + }, + { + "cell_type": "markdown", + "id": "28c783a6-9f68-484b-b01d-1134f9c70104", + "metadata": {}, + "source": [ + "For the offset slit the source has to be shifted by 1.2 arcseconds in the y-direction." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e950440b-eb74-4ff7-bd9a-228178c68963", + "metadata": {}, + "outputs": [], + "source": [ + "star.shift(dy=1.2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0962d1f7-974b-4537-9491-f8697ea6f548", + "metadata": {}, + "outputs": [], + "source": [ + "mcd['slit_wheel'].change_slit(\"3000x48_offset\")\n", + "mcd.observe(star)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "369a86b1-44fe-4a3d-b753-9b4e60ba4d6f", + "metadata": {}, + "outputs": [], + "source": [ + "plt.imshow(mcd.image_planes[0].data, norm='log', origin='lower')\n", + "plt.xlim(480, 550)\n", + "plt.ylim(800, 826); # shift by 300 pixels (=1.2 arcsec)" + ] + }, + { + "cell_type": "markdown", + "id": "aa7cdc05-783c-4013-a7e7-84983fc1904e", + "metadata": {}, + "source": [ + "## Spectroscopy with nominal and offset slits\n", + "For spectroscopy, we instantiate the `OpticalTrain` in the `SPEC` mode; the default slit is `3000x16`, the default band is `IJ`. For simplicity, we will observe blank sky here; observation of a source should be straightforward." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "136ec471-66e4-46e4-a219-8f81df4699dd", + "metadata": {}, + "outputs": [], + "source": [ + "cmd = sim.UserCommands(use_instrument=\"MICADO\", set_modes=[\"SCAO\", \"SPEC\"])\n", + "mcd = sim.OpticalTrain(cmd)" + ] + }, + { + "cell_type": "markdown", + "id": "e21059b0-82e0-421b-b587-134a81611bb3", + "metadata": {}, + "source": [ + "We are going to simulate the full detector array now. Beware that spectroscopic simulations take a long time to run; as we're observing blank sky we can save a little time by switching off the PSF effects, which do no affect flat fields anyway. We set the slit explicitely and switch to the HK band." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80bec523-dfea-4cc4-bbe0-97e43733d434", + "metadata": {}, + "outputs": [], + "source": [ + "mcd['full_detector_array'].include = True\n", + "mcd['detector_window'].include = False\n", + "mcd['relay_psf'].include = False\n", + "mcd['micado_ncpas_psf'].include = False\n", + "\n", + "mcd['slit_wheel'].change_slit(\"3000x16\")\n", + "mcd['filter_wheel_1'].change_filter(\"Spec_HK\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "974c2db3-4dfd-45cf-afdd-f466bea5cf06", + "metadata": {}, + "outputs": [], + "source": [ + "mcd.effects.show_in_notebook()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a2a39a3a-b054-4ca8-811e-b79621bab60c", + "metadata": {}, + "outputs": [], + "source": [ + "mcd.observe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9818c7a6-e032-4e3f-80d2-bdc2ebf84f4b", + "metadata": {}, + "outputs": [], + "source": [ + "readout = mcd.readout(dit=100, ndit=100)[0]\n", + "readout.writeto(\"readout_nominal.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "aaca2f57-4223-42aa-aa81-77b4c021992a", + "metadata": {}, + "source": [ + "Rectification should be done immediately after the readout. When the slit is changed to an offset one, the spectral traces are recomputed and rectification will give a wrong result when applied to a nominal slit!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "24c5a6a6-9530-425d-85db-f6784d6d6bda", + "metadata": {}, + "outputs": [], + "source": [ + "with fits.open(\"readout_nominal.fits\") as readout_nominal:\n", + " rectified = mcd['micado_spectral_traces'].rectify_traces(readout_nominal, -1.5, 1.5)\n", + " rectified.writeto(\"rect_nominal.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "ddc097a6-68db-4c21-8398-08f6ccb70d0b", + "metadata": {}, + "source": [ + "The rectified spectra that we have just created have no data at wavelengths that fall between the detectors in the detector array. To fill in these regions we perform another simulation, this time with the offset slit." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b76051c6-766b-447a-b158-cfcb8b1b1b8c", + "metadata": {}, + "outputs": [], + "source": [ + "mcd['slit_wheel'].change_slit(\"3000x16_offset\")\n", + "mcd.observe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "949de8b8-5a92-4147-a8da-e4b51c3504a8", + "metadata": {}, + "outputs": [], + "source": [ + "readout = mcd.readout(dit=100, ndit=100)[0]\n", + "readout.writeto(\"readout_offset.fits\", overwrite=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "887d4259-c66e-4193-8e0c-ab871b3d437d", + "metadata": {}, + "outputs": [], + "source": [ + "with fits.open(\"readout_offset.fits\") as readout_offset:\n", + " rectified = mcd['micado_spectral_traces'].rectify_traces(readout_offset, -1.5, 1.5)\n", + " rectified.writeto(\"rect_offset.fits\", overwrite=True)" + ] + }, + { + "cell_type": "markdown", + "id": "2f249f97-f5aa-409e-ad32-2537d1de4362", + "metadata": {}, + "source": [ + "Careful comparison of the sky lines in the detector images reveals the offset between the simulations with the nominal and the offset slit, respectively." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a43afb1-0e1e-4c57-ae90-01adadd231c3", + "metadata": {}, + "outputs": [], + "source": [ + "with fits.open(\"readout_nominal.fits\") as readout_nominal:\n", + " with fits.open(\"readout_offset.fits\") as readout_offset:\n", + " _, (ax_nom, ax_off) = plt.subplots(1, 2, sharey=True)\n", + " ax_nom.imshow(readout_nominal[5].data, origin='lower')\n", + " ax_off.imshow(readout_offset[5].data, origin='lower')" + ] + }, + { + "cell_type": "markdown", + "id": "8b8c221e-0d61-4c19-b514-18db70a89bb2", + "metadata": {}, + "source": [ + "The rectification placed the spectra on the correct linear wavelength grid. We first create the wavelength vectors using the WCS information from the FITS headers and then plot a section of the spectra." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5fe2944-8b84-40ce-b5c1-1ef62a88a184", + "metadata": {}, + "outputs": [], + "source": [ + "with fits.open(\"rect_nominal.fits\") as rect_nominal:\n", + " with fits.open(\"rect_offset.fits\") as rect_offset:\n", + " wcs_nom = WCS(rect_nominal[2].header).spectral\n", + " wcs_off = WCS(rect_offset[2].header).spectral\n", + " lam_nom = wcs_nom.all_pix2world(np.arange(rect_nominal[2].data.shape[1]), 0)[0]\n", + " lam_off = wcs_off.all_pix2world(np.arange(rect_offset[2].data.shape[1]), 0)[0]\n", + " spec_nom = rect_nominal[2].data[350,]\n", + " spec_off = rect_offset[2].data[350,]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38f7678d-0047-4848-a60a-59617d7b8d34", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(lam_nom, spec_nom, label=\"nominal\")\n", + "plt.plot(lam_off, spec_off+4000, label=\"offset (+4000)\")\n", + "plt.xlim(1.6e-6, 1.63e-6)\n", + "plt.ylim(-400, 10000)\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "b07f7f42-a235-4491-b011-e437b7366f8c", + "metadata": {}, + "source": [ + "The gaps in the spectra can be filled in by averaging while masking the gap regions. Here it's done using the `numpy.ma` module:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d92d605f-37eb-43f3-bf55-a6024bdf1796", + "metadata": {}, + "outputs": [], + "source": [ + "mask_nom = (spec_nom == 0)\n", + "mask_off = (spec_off == 0)\n", + "mspec_nom = np.ma.masked_array(spec_nom, mask=mask_nom)\n", + "mspec_off = np.ma.masked_array(spec_off, mask=mask_off)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa13ca5d-7198-4db3-b272-919d7fe17939", + "metadata": {}, + "outputs": [], + "source": [ + "spec_mean = np.ma.array((mspec_nom, mspec_off)).mean(axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5effc479-5782-4609-b19c-292e7443100d", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(lam_nom, mspec_nom, label=\"nominal\")\n", + "plt.plot(lam_off, mspec_off+3000, label=\"offset (+3000)\")\n", + "plt.plot(lam_nom, spec_mean+6000, label=\"average (+6000)\")\n", + "plt.xlim(1.68e-6, 1.73e-6)\n", + "plt.ylim(-400, 10400)\n", + "plt.legend();" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/MICADO/docs/readme.rst b/MICADO/docs/readme.rst deleted file mode 100644 index f961d823..00000000 --- a/MICADO/docs/readme.rst +++ /dev/null @@ -1,106 +0,0 @@ -.. |pic1| image:: micado_scopesim_logo.png - :width: 600px - :alt: MICADO + ScopeSim - -|pic1| -====== - -Introduction ------------- -A new MICADO data simulator is being developed as part of the generic simulator ScopeSim, a descendant of the older SimCADO software. - - -Prerequisites -------------- - -- A working installation of Python 3.6 or newer -- A working installation of Jupyter notebooks if you want to run the simulator from notebooks, i.e. using a graphical interactive interface, rather than just the terminal or scripts (highly recommended) -- A working installation of the Python package installer pip - -.. note:: Bug reports and help-desk - - If you come across a bug or get stuck with a certain aspect of ScopeSim or - the MICADO package, please get in touch with us (emails addresses below). - - **Your feedback is the only way we know** what needs to be changed/improved - with the package and the simulator - - -Installation & setup --------------------- - -1. Install ``scopesim`` in your python environment:: - - $ pip install scopesim - -2. Create a directory where your simulation notebooks will live, e.g. ``~/path/to/playing_with_scopesim/`` -3. Install relevant irdb packages & download example notebooks into this directory:: - - $ python - >> import scopesim - >> scopesim.download_packages(["Armazones", "ELT", "MICADO"]) - -4. Download one of the tutorial notebooks (see `Python notebooks`_) -5. In a Terminal, cd to ~/ScopeSim and execute the notebook by calling:: - - $ cd ~/path/to/playing_with_scopesim/ - $ jupyter notebook filename.ipynb - -6. Follow instruction and explanations in the notebook. - - -Python notebooks ----------------- - -.. note:: - To download a notebook from Github, either: - - - view the raw file and save this disk from the browser, or - - navigate up one level, then right click the file and save as - - -**Download the example notebooks** `from the Github repo -`_ - - -.. toctree:: - :maxdepth: 1 - :caption: List of notebooks for MICADO - - example_notebooks/1_scopesim_MCAO_4mas_galaxy - example_notebooks/2_scopesim_SCAO_1.5mas_astrometry - example_notebooks/3_scopesim_SCAO_4mas_fv-psf - example_notebooks/MICADO_FAQs - - -Scientific use-case notebooks -+++++++++++++++++++++++++++++ - -.. list-table:: Science case notebooks - :widths: 25 75 - :header-rows: 1 - - * - Name - - Description - * - - - - - - -Documentation and useful references ------------------------------------ - -- `ScopeSim documentation `_ -- `Sky Object Templates documentation `_ -- `MICADO homepage `_ -- For experts: GitHub repositories: - - + `simulator package ScopeSim `_ - + `instrument-specific packages irdb `_. - - -Contact points --------------- - -- kieran.leschinski@univie.ac.at -- oliver.czoske@univie.ac.at diff --git a/MICADO/filters/TC_filter_block.dat b/MICADO/filters/TC_filter_block.dat index 4062b944..c4e2f7ae 100644 --- a/MICADO/filters/TC_filter_block.dat +++ b/MICADO/filters/TC_filter_block.dat @@ -1,9 +1,14 @@ # author : Kieran Leschinski # source : Ric Davies # date_created : 2022-03-17 -# date_modified : 2022-03-17 +# date_modified : 2026-05-03 # status : FDR list of filters +# wavelength_unit: um +# changes: +# - 2026-05-03 (OC) change level to 1e-32 # wavelength transmission -0.3 0 +0.3 0.0 +0.35 1.e-32 +2.95 1.e-32 3.0 0 \ No newline at end of file diff --git a/MICADO/test_micado/test_micado_background_flux.py b/MICADO/test_micado/test_micado_background_flux.py index 403f79c9..89e1e2a3 100644 --- a/MICADO/test_micado/test_micado_background_flux.py +++ b/MICADO/test_micado/test_micado_background_flux.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- """ Tests the SCAO background against the values from from Ric's excel doc [Signal_noise_estimator_MICADO_2018.04.03] @@ -12,9 +13,9 @@ # integration test using everything and the MICADO package from pathlib import Path import pytest -from pytest import approx import numpy as np +from numpy import testing as npt import scopesim as sim from scopesim import rc @@ -27,10 +28,15 @@ class TestInit: - @pytest.mark.parametrize("modes", [["SCAO", "IMG_4mas"], - ["SCAO", "IMG_1.5mas"], - ["MCAO", "IMG_4mas"], - ["MCAO", "IMG_1.5mas"]]) + @pytest.mark.parametrize( + "modes", + [ + ["SCAO", "IMG_4mas"], + ["SCAO", "IMG_1.5mas"], + ["MCAO", "IMG_4mas"], + ["MCAO", "IMG_1.5mas"], + ], + ) def test_micado_loads_optical_train(self, modes): cmds = sim.UserCommands(use_instrument="MICADO", set_modes=modes) micado = sim.OpticalTrain(cmds) @@ -40,7 +46,6 @@ def test_micado_loads_optical_train(self, modes): assert len(opt_els) == 6 -@pytest.mark.xfail(reason="Background levels fail due to changes in dev_master.") class TestBackgroundLevels: """ from Ric's excel doc 2018-04-03 @@ -50,35 +55,31 @@ class TestBackgroundLevels: 0.6 5.0 28.4 78.7 """ - @pytest.mark.parametrize("fw1, fw2, bg_flux", - [("J", "open", 5), - ("open", "H", 30), - ("open", "Ks", 79)]) - def test_bg_SCAO_IMG_4mas(self, fw1, fw2, bg_flux): - cmds = sim.UserCommands(use_instrument="MICADO") - micado = sim.OpticalTrain(cmds) - - micado["filter_wheel_1"].change_filter(fw1) - micado["filter_wheel_2"].change_filter(fw2) - src = empty_sky() - micado.observe(src) - implane = micado.image_planes[0].hdu.data # e-/pixel/s - - assert np.median(implane) == approx(bg_flux, rel=0.3) - - @pytest.mark.parametrize("fw1, fw2, bg_flux", - [("J", "open", 5), - ("open", "H", 30), - ("open", "Ks", 79)]) - def test_bg_SCAO_IMG_1_5mas(self, fw1, fw2, bg_flux): - """ - Pixel size is 0.14 of the 4mas version, hence fluxes are lower - """ - bg_flux *= (1.5 / 4)**2 - - cmds = sim.UserCommands(use_instrument="MICADO", - set_modes=["SCAO", "IMG_1.5mas"]) + @pytest.mark.parametrize( + "mode, factor", (("IMG_4mas", 1), ("IMG_1.5mas", (1.5 / 4) ** 2)) + ) + @pytest.mark.parametrize( + "fw1, fw2, bg_flux", [ + pytest.param( + "J", "open", 5, + marks=pytest.mark.xfail( + reason="Fails due to changes in dev_master." + ), + ), + pytest.param( + "open", "H", 30, + marks=pytest.mark.xfail( + reason="Fails due to changes in dev_master." + ), + ), + ("open", "Ks", 79), + ], + ) + def test_bg_SCAO_IMG_4mas(self, mode, factor, fw1, fw2, bg_flux): + cmds = sim.UserCommands( + use_instrument="MICADO", set_modes=["SCAO", mode] + ) micado = sim.OpticalTrain(cmds) micado["filter_wheel_1"].change_filter(fw1) @@ -86,6 +87,8 @@ def test_bg_SCAO_IMG_1_5mas(self, fw1, fw2, bg_flux): src = empty_sky() micado.observe(src) - implane = micado.image_planes[0].hdu.data # e-/pixel/s + implane = micado.image_planes[0].hdu.data # e-/pixel/s - assert np.median(implane) == approx(bg_flux, rel=0.3) + # Pixel size is 0.14 of the 4mas version, hence fluxes are lower + bg_flux *= factor + npt.assert_allclose(np.median(implane), bg_flux, rtol=.3) diff --git a/MICADO/test_micado/test_micado_compiles.py b/MICADO/test_micado/test_micado_compiles.py index 0feed117..4305ce74 100644 --- a/MICADO/test_micado/test_micado_compiles.py +++ b/MICADO/test_micado/test_micado_compiles.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- """ Tests that the MICADO package runs with observe, readout flawlessly @@ -23,7 +24,6 @@ from scopesim import rc from matplotlib import pyplot as plt -from matplotlib.colors import LogNorm PATH_HERE = Path(__file__).parent PATH_IRDB = PATH_HERE.parent.parent @@ -57,14 +57,15 @@ def test_user_commands_loads_mode_files(self): def test_user_commands_can_change_modes(self): cmd = scopesim.UserCommands(use_instrument="MICADO") - cmd.set_modes(["MCAO", "SPEC_3000x50"]) + cmd.set_modes("MCAO", "SPEC_3000x48") assert "MORFEO" in [yd["name"] for yd in cmd.yaml_dicts] assert "MICADO_SPEC" in [yd["name"] for yd in cmd.yaml_dicts] def test_user_commands_can_change_modes_via_init(self): - cmd = scopesim.UserCommands(use_instrument="MICADO", - set_modes=["MCAO", "SPEC_3000x50"]) + cmd = scopesim.UserCommands( + use_instrument="MICADO", set_modes=["MCAO", "SPEC_3000x48"] + ) assert "MORFEO" in [yd["name"] for yd in cmd.yaml_dicts] assert "MICADO_SPEC" in [yd["name"] for yd in cmd.yaml_dicts] @@ -72,9 +73,11 @@ def test_user_commands_can_change_modes_via_init(self): class TestMakeOpticalTrain: def test_works_seamlessly_for_micado_wide_mode(self): - cmd = scopesim.UserCommands(use_instrument="MICADO", - set_modes=["SCAO", "IMG_4mas"], - properties={"!OBS.filter_name": "Ks"}) + cmd = scopesim.UserCommands( + use_instrument="MICADO", + set_modes=["SCAO", "IMG_4mas"], + properties={"!OBS.filter_name": "Ks"}, + ) opt = scopesim.OpticalTrain(cmd) assert isinstance(opt, scopesim.OpticalTrain) @@ -85,10 +88,14 @@ def test_works_seamlessly_for_micado_wide_mode(self): assert isinstance(hdu_list, fits.HDUList) def test_works_seamlessly_for_micado_zoom_mode(self): - cmd = scopesim.UserCommands(use_instrument="MICADO", - set_modes=["SCAO", "IMG_1.5mas"], - properties={"!OBS.filter_name_fw1": "J", - "!OBS.filter_name_fw2": "open"}) + cmd = scopesim.UserCommands( + use_instrument="MICADO", + set_modes=["SCAO", "IMG_1.5mas"], + properties={ + "!OBS.filter_name_fw1": "J", + "!OBS.filter_name_fw2": "open", + }, + ) micado = scopesim.OpticalTrain(cmd) assert isinstance(micado, scopesim.OpticalTrain) @@ -102,9 +109,10 @@ def test_works_seamlessly_for_micado_zoom_mode(self): class TestDetector: @pytest.mark.parametrize("ndit, dit", [(1, 3600)]) def test_returns_ndit_dit_scaled_image(self, ndit, dit): - cmd = scopesim.UserCommands(use_instrument="MICADO", - properties={"!OBS.dit": dit, - "!OBS.ndit": ndit}) + cmd = scopesim.UserCommands( + use_instrument="MICADO", + properties={"!OBS.dit": dit, "!OBS.ndit": ndit}, + ) micado = scopesim.OpticalTrain(cmd) micado["skycalc_atmosphere"].include = False micado["detector_linearity"].include = False @@ -121,11 +129,11 @@ def test_returns_ndit_dit_scaled_image(self, ndit, dit): if PLOTS: plt.subplot(121) - plt.imshow(implane_image, norm=LogNorm()) + plt.imshow(implane_image, norm="log") plt.colorbar() plt.subplot(122) - plt.imshow(readout_image, norm=LogNorm()) + plt.imshow(readout_image, norm="log") plt.colorbar() plt.show() diff --git a/MICADO/test_micado/test_micado_fits_headers.py b/MICADO/test_micado/test_micado_fits_headers.py index 50f400d4..11794ce7 100644 --- a/MICADO/test_micado/test_micado_fits_headers.py +++ b/MICADO/test_micado/test_micado_fits_headers.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- from os import path as p from astropy.io import fits import scopesim as sim diff --git a/MICADO/test_micado/test_micado_imaging.py b/MICADO/test_micado/test_micado_imaging.py index aa98c5a0..1165fcc2 100644 --- a/MICADO/test_micado/test_micado_imaging.py +++ b/MICADO/test_micado/test_micado_imaging.py @@ -1,4 +1,4 @@ - +# -*- coding: utf-8 -*- """ Tests the MCAO limiting magnitudes against the values from from Ric's excel doc [Signal_noise_estimator_MICADO_2018.04.03] @@ -11,27 +11,31 @@ """ -# integration test using everything and the MICADO package +import os from pathlib import Path import pytest from pytest import approx import numpy as np +from scipy.stats import linregress +import matplotlib as mpl +from matplotlib import pyplot as plt import scopesim as sim from scopesim import rc from scopesim.source import source_templates as st -from matplotlib import pyplot as plt -from matplotlib.colors import LogNorm PATH_HERE = Path(__file__).parent PATH_IRDB = PATH_HERE.parent.parent rc.__config__["!SIM.file.local_packages_path"] = str(PATH_IRDB) -PLOTS = False +PLOTS = os.environ.get("READTHEDOCS", False) # Run plots on RTD +if PLOTS: + mpl.style.use("seaborn-v0_8") +@pytest.mark.validation class TestLimiting: """ from Ric's excel doc (Signal_noise_estimator_MICADO_2018.04.03) @@ -62,98 +66,176 @@ class TestLimiting: Tolerance for assert is 0.3 mag (to high?) """ + + @pytest.mark.parametrize("img_mode", ["IMG_4mas"]) + @pytest.mark.parametrize("ao_mode", ["MCAO", "SCAO"]) @pytest.mark.parametrize( - ("fw1", "fw2", "r0", "rics_lim_mag", "abslim"), - [pytest.param("J", "open", 1, 27.9, .3, marks=pytest.mark.xfail(reason="something changed in ScopeSim...")), - pytest.param("open", "H", 2, 27.5, .3, marks=pytest.mark.xfail(reason="something changed in ScopeSim...")), - ("open", "Ks", 2, 27.1, .3)]) - def test_MCAO_IMG_4mas(self, fw1, fw2, r0, rics_lim_mag, abslim, ao_mode="MCAO"): + ("fw1", "fw2", "r0", "rics_lim_mag", "abslim"), [ + pytest.param( + "J", "open", 1, 27.9, 1.0, + marks=pytest.mark.xfail( + reason="most likely PSF contamination of nearby sources" + ), + ), + pytest.param( + "open", "H", 2, 27.5, 0.6, + marks=pytest.mark.xfail( + reason="most likely PSF contamination of nearby sources" + ), + ), + pytest.param( + "open", "Ks", 2, 27.1, 0.3, + marks=pytest.mark.xfail( + reason="most likely PSF contamination of nearby sources" + ), + ), + ], + ) + def test_MCAO_IMG_4mas( + self, record_property, fw1, fw2, r0, rics_lim_mag, abslim, ao_mode, img_mode, + ): + filt = fw1 if fw1 != "open" else fw2 + record_property("filter", filt) + record_property("ao_mode", ao_mode) + record_property("img_mode", img_mode) + record_property("expected", rics_lim_mag) + record_property("tolerance", abslim) n_stars, mmin, mmax = 400, 25, 30 - r1, r2 = 10, 15 # aperture radii r0 (sig), r1-r2 (noise) + r1, r2 = 10, 15 # aperture radii r0 (sig), r1-r2 (noise) src = st.star_field(n_stars, mmin, mmax, width=3, use_grid=True) - cmds = sim.UserCommands(use_instrument="MICADO", - set_modes=[ao_mode, "IMG_4mas"]) + cmds = sim.UserCommands( + use_instrument="MICADO", set_modes=[ao_mode, img_mode] + ) micado = sim.OpticalTrain(cmds) - micado.cmds["!OBS.dit"] = 18000 + micado.cmds["!OBS.dit"] = 18000 # 5 h micado["filter_wheel_1"].change_filter(fw1) micado["filter_wheel_2"].change_filter(fw2) micado["detector_linearity"].include = False micado.observe(src) - hdul = micado.readout()[0] - - det = hdul[1].data + det = micado.readout()[0][1].data imp = micado.image_planes[0].hdu.data # e-/pixel/s - if PLOTS: - plt.subplot(131) - plt.imshow(imp, norm=LogNorm(vmin=np.median(imp), vmax=1.01*np.median(imp))) - plt.subplot(132) - plt.imshow(det, norm=LogNorm(vmin=np.median(det), vmax=1.01*np.median(det))) + if PLOTS: + fig, (img_ax, det_ax, snr_ax) = plt.subplots(1, 3, figsize=(20, 8), layout="constrained") + fig.suptitle(f"MICADO {ao_mode} {img_mode} {filt}-band") + + img_ax.imshow( + imp, + norm="log", + vmin=np.median(imp), + vmax=np.quantile(imp, .995), + origin="lower", + cmap="inferno", + ) + img_ax.set_title("Image Plane") + img_ax.grid(False, which="both") + img_ax.set_xlabel("pixel") + img_ax.set_ylabel("pixel") + det_ax.imshow( + det, + norm="log", + vmin=np.median(det), + vmax=np.quantile(det, .998), + origin="lower", + cmap="inferno", + ) + det_ax.set_title("Detector") + det_ax.grid(False, which="both") + det_ax.set_xlabel("pixel") + det_ax.set_ylabel("pixel") + + midpoint_x = micado.cmds["!DET.width"] // 2 + midpoint_y = micado.cmds["!DET.height"] // 2 + + xpix, ypix = src.fields[0].field["x"].data, src.fields[0].field["y"].data + xpix = (xpix / micado.cmds["!INST.pixel_scale"] + midpoint_x).round(2) + ypix = (ypix / micado.cmds["!INST.pixel_scale"] + midpoint_y).round(2) + + # For some bizzare reason, this is the only way the apertures end up in + # the correct position?? + xpix = np.where( + xpix < midpoint_x, + np.floor(xpix), + np.ceil(xpix) + ).astype(int) + ypix = np.where( + ypix < midpoint_y, + np.floor(ypix), + np.ceil(ypix) + ).astype(int) - xpix, ypix = src.fields[0]["x"].data, src.fields[0]["y"].data - xpix = xpix / 0.004 + 512 - ypix = ypix / 0.004 + 512 mags = np.round(np.linspace(mmin, mmax, n_stars), 1) + snrs = np.array(list(self._photometry(xpix, ypix, mags, r0, r1, r2, det))) - snrs = [] - for x, y, mag in zip(xpix, ypix, mags): - # For some bizzare reason, this is the only way the apertures end - # up in the correct position?? - if x < 512: - x = np.floor(np.round(x, 2)).astype(int) - else: - x = np.ceil(np.round(x, 2)).astype(int) - if y < 512: - y = np.floor(np.round(y, 2)).astype(int) - else: - y = np.ceil(np.round(y, 2)).astype(int) - - sig_im = np.copy(det[y-r0:y+r0+1, x-r0:x+r0+1]) - bg_im = np.copy(det[y-r2:y+r2+1, x-r2:x+r2+1]) - bg_im[r1:-r1, r1:-r1] = 0 - - bg_median = np.median(bg_im[bg_im > 0]) - bg_std = np.std(bg_im[bg_im > 0]) - # bg_std = np.sqrt(bg_median) - noise = bg_std * np.sqrt(np.prod(sig_im.shape)) * np.sqrt(2) # sqrt(2) comes from BG subtraction (see Rics doc) - signal = np.sum(sig_im - bg_median) - snr = signal/noise - snrs += [snr] - - if PLOTS: - plt.plot([x-r0, x+r0, x+r0, x-r0, x-r0], - [y-r0, y-r0, y+r0, y+r0, y-r0], "g") - plt.plot([x-r1, x+r1, x+r1, x-r1, x-r1], - [y-r1, y-r1, y+r1, y+r1, y-r1], "y") - plt.plot([x-r2, x+r2, x+r2, x-r2, x-r2], - [y-r2, y-r2, y+r2, y+r2, y-r2], "r") - - plt.text(x+r2, y+r2, str(round(snr, 1)), color="w") - plt.text(x-r2, y-r2, str(mag), color="w") - - from scipy.stats import linregress - snrs = np.array(snrs) - results = linregress(mags[snrs > 5], np.log10(snrs[snrs > 5])) - m, c = results[:2] - sigma = 5 - lim_mag = (np.log10(sigma) - c) / m + snr_limit = 5 + lin_fit = linregress(mags[snrs > snr_limit], np.log10(snrs[snrs > snr_limit])) + lim_mag = (np.log10(snr_limit) - lin_fit.intercept) / lin_fit.slope if PLOTS: - plt.subplot(133) - plt.plot(mags, snrs, ".", alpha=0.3) - plt.plot(mags, 10 ** (m * mags + c), "r") - - plt.axhline(sigma) - plt.axvline(lim_mag) - plt.text(lim_mag, sigma, str(lim_mag), - horizontalalignment="left", - verticalalignment="bottom") + snr_ax.plot(mags, snrs, ".", alpha=0.5, label="Measurements") + snr_ax.plot(mags, 10 ** (lin_fit.slope * mags + lin_fit.intercept), label="Fit") + + snr_ax.axhline(snr_limit, linestyle=":", color="#64B5CD", alpha=.7, label=f"S/N={snr_limit} limit") + snr_ax.axvline(lim_mag, linestyle="--", color="#C44E52", alpha=.7, label=f"Limiting Mag.e @ S/N={snr_limit}") + snr_ax.axvline(rics_lim_mag, color="#CCB974", alpha=.8, zorder=-1, label=f"Expected value\n{rics_lim_mag} +/- {abslim} mag") + snr_ax.axvspan(rics_lim_mag - abslim, rics_lim_mag + abslim, color="#CCB974", alpha=.2) + snr_ax.text( + lim_mag + .1, + snr_limit + .5, + f"{lim_mag:.2f}", + horizontalalignment="left", + verticalalignment="bottom", + fontsize=16, + color="#C44E52", + ) + snr_ax.set_xlabel("mag") + snr_ax.set_ylabel("S/N") + snr_ax.legend() + snr_ax.set_title(f"S/N for MICADO {ao_mode} {img_mode}") + + fig_path = PATH_IRDB / f"docs/source/_static/plots/MICADO/limmag/{ao_mode}_{img_mode}_{filt}.pdf" + fig_path.parent.mkdir(parents=True, exist_ok=True) + fig.savefig(fig_path) + record_property("link", str(fig_path.relative_to(PATH_IRDB / "docs/source"))) plt.show() - # J-band fails because ScopeSIm is 0.5 mags lower Ric's estimate. Why?!? print(f"expected: {rics_lim_mag:.2f}, obtained: {lim_mag:.2f}, delta: {lim_mag-rics_lim_mag:.3f}") + record_property("obtained", round(lim_mag, 2)) + record_property("difference", round(lim_mag-rics_lim_mag, 3)) + + lim_mag = round(lim_mag, 4) # for nicer output msg assert lim_mag == approx(rics_lim_mag, abs=abslim) + + @staticmethod + def _photometry(xpix, ypix, mags, r0, r1, r2, det): + for x, y, mag in zip(xpix, ypix, mags): + sig_im = np.copy(det[y-r0:y+r0+1, x-r0:x+r0+1]) + bkg_im = np.copy(det[y-r2:y+r2+1, x-r2:x+r2+1]) + bkg_im[r1:-r1, r1:-r1] = 0 # use masked array? + + bg_median = np.median(bkg_im[bkg_im > 0]) + bg_std = np.std(bkg_im[bkg_im > 0]) + # bg_std = np.sqrt(bg_median) + noise = bg_std * np.sqrt(np.prod(sig_im.shape)) * np.sqrt(2) # sqrt(2) comes from BG subtraction (see Rics doc) + signal = np.sum(sig_im - bg_median) + snr = signal / noise + + if PLOTS: + # Can't pass det_ax as an argument if it doesn't always exits. + # Whatever, this works... + _, det_ax, _ = plt.gcf().get_axes() + det_ax.plot([x-r0, x+r0, x+r0, x-r0, x-r0], + [y-r0, y-r0, y+r0, y+r0, y-r0], "g") + det_ax.plot([x-r1, x+r1, x+r1, x-r1, x-r1], + [y-r1, y-r1, y+r1, y+r1, y-r1], "y") + det_ax.plot([x-r2, x+r2, x+r2, x-r2, x-r2], + [y-r2, y-r2, y+r2, y+r2, y-r2], "r") + + det_ax.text(x+r2, y+r2, f"{snr:.1f}", color="w") + det_ax.text(x-r2, y-r2, f"{mag:.1f}", color="w") + + yield snr diff --git a/MICADO/test_micado/test_micado_spec.py b/MICADO/test_micado/test_micado_spec.py index 1d7ae879..a4fd4b91 100644 --- a/MICADO/test_micado/test_micado_spec.py +++ b/MICADO/test_micado/test_micado_spec.py @@ -1,3 +1,4 @@ +# -*- coding: utf-8 -*- """ Tests the SPEC mode, that it compiles and runs. @@ -21,7 +22,6 @@ from scopesim.source import source_templates as st from matplotlib import pyplot as plt -from matplotlib.colors import LogNorm PATH_HERE = Path(__file__).parent PATH_IRDB = PATH_HERE.parent.parent @@ -30,17 +30,18 @@ PLOTS = False -# if rc.__config__["!SIM.tests.run_integration_tests"] is False: pytestmark = pytest.mark.skip("Takes too much memory") class TestInit: - @pytest.mark.parametrize("modes", [["SCAO", "SPEC_3000x16"], - ["SCAO", "SPEC_3000x48"], - ["SCAO", "SPEC_15000x20"], - ["SCAO", "SPEC_3000x20"], - ["SCAO", "SPEC_3000x50"], - ["SCAO", "SPEC_15000x50"]]) + @pytest.mark.parametrize( + "modes", + [ + ["SCAO", "SPEC_3000x16"], + ["SCAO", "SPEC_3000x48"], + ["SCAO", "SPEC_15000x20"], + ], + ) def test_loads_optical_train(self, modes): cmds = sim.UserCommands(use_instrument="MICADO", set_modes=modes) micado = sim.OpticalTrain(cmds) @@ -50,20 +51,22 @@ def test_loads_optical_train(self, modes): assert len(opt_els) == 6 @pytest.mark.skip(reason="This test runs out of memory and hangs.") - def test_runs_spec_hk_15000x50(self): + def test_runs_spec_hk_15000x20(self): src = st.empty_sky() - cmds_img = sim.UserCommands(use_instrument="MICADO", - set_modes=["SCAO", "IMG_4mas"]) + cmds_img = sim.UserCommands( + use_instrument="MICADO", set_modes=["SCAO", "IMG_4mas"] + ) micado_img = sim.OpticalTrain(cmds_img) micado_img.observe(src) img_av_flux = np.median(micado_img.image_planes[0].data) - cmds = sim.UserCommands(use_instrument="MICADO", - set_modes=["SCAO", "SPEC_15000x50"]) - cmds.cmds["!OBS.trace_file"] = "TRACE_MICADO.fits" # Old, missing x=0 + cmds = sim.UserCommands( + use_instrument="MICADO", set_modes=["SCAO", "SPEC_15000x20"] + ) + cmds.cmds["!OBS.trace_file"] = "TRACE_MICADO.fits" # Old, missing x=0 cmds.cmds["!DET.dit"] = 3600 cmds.cmds["!OBS.filter_name_fw1"] = "open" cmds.cmds["!OBS.filter_name_fw2"] = "Ks" @@ -78,17 +81,16 @@ def test_runs_spec_hk_15000x50(self): if PLOTS: plt.subplot(121) - plt.imshow(micado.image_planes[0].data, norm=LogNorm(), - origin="lower") + plt.imshow(micado.image_planes[0].data, norm="log", origin="lower") plt.subplot(122) - plt.imshow(hdul[1].data, norm=LogNorm(), origin="lower") + plt.imshow(hdul[1].data, norm="log", origin="lower") plt.show() spec_int_flux = np.sum(micado.image_planes[0].data, axis=0) spec_av_flux = np.median(spec_int_flux[40:2600]) - slit_width = 50 / 4. # [pixels] + slit_width = 50 / 4.0 # [pixels] grating_efficiency = 0.6**2 scale_factor = slit_width * grating_efficiency diff --git a/MICADO_Sci/MICADO_Sci.yaml b/MICADO_Sci/MICADO_Sci.yaml deleted file mode 100644 index 502ac42b..00000000 --- a/MICADO_Sci/MICADO_Sci.yaml +++ /dev/null @@ -1,157 +0,0 @@ -# name: micado_sci_default -# description: default observation parameters for MICADO-Sci -# author: Kieran Leschinski -# date_created: 09.07.2020 -# date_modified: 2022-01-12 -# changes: -# - 2022-01-12 (OC) changed spectral_resolution to _bin_width -# -# contains: -# - System transmission -# - AtmosphericTERCurve -# - FilterCurve - - -### Config file for the Armazones optical element -object : atmosphere -alias : ATMO -name : armazones -description : Atmosphere and location details for Cerro Armazones - -properties : - altitude : 3060 # m - longitude : -70.1918 # deg - latitude : -24.5899 # deg - temperature : 7 # deg C - humidity : 0.1 # [0..1] - pressure : 0.755 # [bar] - pwv : 2.5 # [mm] - airmass : "!OBS.airmass" - pupil_angle : "!OBS.pupil_angle" - pixel_scale : "!INST.pixel_scale" - season: 0 # As per skycalc definition - 0=all year - time: 0 # As per skycalc definition - 0=all night - background: - filter_name: Ks - value: 13.6 - unit: mag - -effects : -- name : armazones_atmo_default_ter_curve - description : atmospheric emission and transmission - class : AtmosphericTERCurve - include : True - kwargs : - filename: "TER_armazones_default_NIR_IMG.dat" - area: "!TEL.area" - rescale_emission: - filter_name: "Ks" - filename_format: "!INST.filter_file_format" - value: 13.6 - unit: mag - -#- name: armazones_atmo_skycalc_ter_curve -# description: atmospheric spectra pulled from the skycalc server -# class: SkycalcTERCurve -# include: False -# kwargs: -# observatory: "armazones" -# wmin: "!SIM.spectral.wave_min" -# wmax: "!SIM.spectral.wave_max" -# wunit: um -# wdelta: "!SIM.spectral.spectral_bin_width" - - ---- - -### Config file for the ELT -object : telescope -alias : TEL -name : ELT -description : ELT system transmission - -properties : - temperature : 0 - area : 978 - -effects: -- name : elt_system_transmission - description : full 5 mirror transmission curve - class : SurfaceList - kwargs : - array_dict: - name: [ELT_full] - area: [978] - angle: [0] - temperature: ["!TEL.temperature"] - action: [reflection] - filename: [TER_ELT_5_mirror.dat] - area_unit : m2 - angle_unit: degree - temperature_unit: deg_C - ---- - -### Config file for common MICADO elements -object : instrument -alias : INST -name : MICADO_Sci -description : base configuration for MICADO - -properties : - temperature : -190 - filter_file_format : "filters/TC_filter_{}.dat" - -effects: -- name: micado_common_optics - description : combined transmission for MICADO common optics - class: TERCurve - kwargs: - filename: TER_MICADO_IMG_common.dat - -- name: filter_wheel - class: FilterWheel - kwargs: - filter_names: - # Filter wheel 1 - - I-long - - Y - - J - - H - - Ks - - J-short - - J-long - - H-short - - H-long - - K-short - - K-mid - - Spec_IJ - - Spec_HK - # Filter wheel 2 - - xI1 - - xI2 - - xY1 - - xY2 - - xJ1 - - xJ2 - - xH1 - - xH2 - - xK1 - - xK2 - - blank - # Pupil wheel - - H-cont - - FeII - - H2_1-0S1 - - Br-gamma - - K-cont - - K-long - - He-I - - Pa-beta - - ND1 - - ND3 - filename_format: "!INST.filter_file_format" - current_filter: "!OBS.filter_name" - minimum_throughput: 1.01e-4 - outer: 0.2 - outer_unit: "m" diff --git a/MICADO_Sci/MICADO_Sci_MCAO.yaml b/MICADO_Sci/MICADO_Sci_MCAO.yaml deleted file mode 100644 index 88b45f68..00000000 --- a/MICADO_Sci/MICADO_Sci_MCAO.yaml +++ /dev/null @@ -1,46 +0,0 @@ -# -##### MCAO -#* MORFEO TER -#* Detector Window -#* PSF -# * MCAO StrehlPSF (max SR JHK-13/30/50) - -object : instrument -alias : INST -name : MICADO_MCAO -description : "MICADO MCAO mode effects" - -properties: - psf: - strehl: 0.4 - wavelength: "!OBS.filter_name" - -effects: -- name: morfeo_mms_ter - description: Combined TER curve for MORFEO MMS relay optics module - class: TERCurve - kwargs: - filename: TER_MORFEO_MMS.dat - -- name: morfeo_const_psf - description: field constant PSF as produced by MORFEO - class: AnisocadoConstPSF - kwargs: - filename: "MICADO_AnisoCADO_rms_map.fits" - strehl: "!INST.psf.strehl" - wavelength: "!INST.psf.wavelength" - psf_side_length: 256 - offset: [0,0] - rounded_edges: True - convolve_mode: full - ---- - -object : detector -alias : DET -name : MICADO_Sci_MCAO_detector_override -description : A settable window on the detector plane - -properties : - width : 4096 - height : 4096 \ No newline at end of file diff --git a/MICADO_Sci/MICADO_Sci_SCAO.yaml b/MICADO_Sci/MICADO_Sci_SCAO.yaml deleted file mode 100644 index 84ba1f2c..00000000 --- a/MICADO_Sci/MICADO_Sci_SCAO.yaml +++ /dev/null @@ -1,46 +0,0 @@ -##### SCAO -#* RO TER -#* Detector Window -#* PSF -# * SCAO FVPSF -# * SCAO AnisoCADO ConstPSF - -object : instrument -alias : INST -name : MICADO_SCAO -description : "MICADO SCAO mode effects" - -properties: - psf: - strehl: 0.8 - wavelength: 2.15 - -effects: -- name: scao_relay_optics_ter - description: Combined TER curve for stand-alone relay optics module - class: TERCurve - kwargs: - filename: TER_MICADO_RO.dat - -- name: scao_const_psf - description: field constant PSF as produced by stand-alone SCAO - class: AnisocadoConstPSF - kwargs: - filename: "MICADO_AnisoCADO_rms_map.fits" - strehl: "!INST.psf.strehl" - wavelength: "!INST.psf.wavelength" - psf_side_length: 256 - offset: [0,0] - rounded_edges: True - convolve_mode: full - ---- - -object : detector -alias : DET -name : MICADO_Sci_SCAO_detector_override -description : A settable window on the detector plane - -properties : - width : 1024 - height : 1024 diff --git a/MICADO_Sci/MICADO_Sci_SPEC.yaml b/MICADO_Sci/MICADO_Sci_SPEC.yaml deleted file mode 100644 index f611b99f..00000000 --- a/MICADO_Sci/MICADO_Sci_SPEC.yaml +++ /dev/null @@ -1,76 +0,0 @@ -##### SCAO -#* RO TER -#* Detector Window -#* PSF -# * SCAO FVPSF -# * SCAO AnisoCADO ConstPSF - -#### SPEC -#* RO TER -#* SPEC TER -#* SkyCalcTERCurve -#* Detector Window -# -#* ApertureMask -# * filename_format -# * mask_name -# -#* XiLamConverter -#* XiLamStrehlPSF (max SR JHK-40/60/80) -#* BasicTraceMap -#* AtmopshericDiffraction - - -object : instrument -alias : INST -name : MICADO_SPEC -description : "MICADO SPEC mode effects" - -properties: - psf: - wavelength: "!SIM.spectral.wave_mid" - strehl: 0.6 - aperture: - x: 0 - y: 0 - width: 3 - height: 0.05 - -effects: -- name : micado_adjustable_slit - class : RectangularApertureMask - kwargs : - width: "!INST.aperture.width" - height: "!INST.aperture.height" - x: "!INST.aperture.x" - y: "!INST.aperture.y" - -- name : spectral_trace_3000x50mas - class : SpectralTraceList - kwargs : - filename : "TRACE_SCI_3arcsec.fits" - center_on_wave_mid: True - x_colname : "x0" - y_colname : "y0" - s_colname : "s0" - ---- - -object : detector -alias : DET -name : MICADO_Sci_SPEC_detector_override -description : A settable window on the detector plane - -properties : - width : 800 - height : 1024 - ---- - -object : observation -alias : OBS -name : MICADO_Sci_SPEC_obs_override -description : Setting the filter to spec_IJ filter - -properties : - filter_name: Spec_HK diff --git a/MICADO_Sci/MICADO_Sci_detector.yaml b/MICADO_Sci/MICADO_Sci_detector.yaml deleted file mode 100644 index b16170a4..00000000 --- a/MICADO_Sci/MICADO_Sci_detector.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# name: micado_sci_detector -# description: H4RG DETECTOR -# author : Kieran Leschinski -# date_created : 09.07.2020 -# date_modified : 09.07.2020 -# -# contains: -# - DetectorWindow -# - QuantumEfficiencyCurve -# - ExposureIntegration -# - DarkCurrent -# - LinearityCurve -# - ShotNoise -# - PoorMansHxRGReadoutNoise - -object : detector -alias : DET -name : micado_sci_detector -description : List of MICADO detector effects relevant for astronomers - -properties : - image_plane_id : 0 - temperature : -230 - dit : "!OBS.dit" - ndit : "!OBS.ndit" - width : 1024 - height : 1024 - x: 0 - y: 0 - -effects: -- name: micado_detector_window - class: DetectorWindow - description: Cut-out of the focal plane image with custom dimensions and coordinates - kwargs: - image_plane_id: 0 - pixel_size: 0.015 - x: "!DET.x" - y: "!DET.y" - width: "!DET.width" - height: "!DET.height" - units: pixel - -- name : qe_curve - description : Quantum efficiency curves for each detector - class : QuantumEfficiencyCurve - kwargs : - filename : QE_detector_H2RG.dat - -- name: exposure_integration - description: Summing up sky signal for all DITs and NDITs - class: ExposureIntegration - -- name: dark_current - fits_alias: DAR - description : MICADO dark current - class: DarkCurrent - # [e-/s] level of dark current for each detector - kwargs: - value: 0.1 - -- name: shot_noise - description : apply poisson shot noise to images - class: ShotNoise - -- name: detector_linearity - description : Linearity characteristics of H4RG chips - class: LinearityCurve - include: False - kwargs: - filename : FPA_linearity.dat - -- name : readout_noise - description : Readout noise frames - class : PoorMansHxRGReadoutNoise - kwargs : - noise_std : 12 - n_channels : 64 diff --git a/MICADO_Sci/README.md b/MICADO_Sci/README.md deleted file mode 100644 index 4d908172..00000000 --- a/MICADO_Sci/README.md +++ /dev/null @@ -1,4 +0,0 @@ -# MICADO Science package - -> [!CAUTION] -> The MICADO_Sci package is **NO LONGER SUPPORTED**!! Use the MICADO package instead. MICADO_Sci will be removed soon! diff --git a/MICADO_Sci/TER_MICADO_IMG_common.dat b/MICADO_Sci/TER_MICADO_IMG_common.dat deleted file mode 100644 index 2b86bd97..00000000 --- a/MICADO_Sci/TER_MICADO_IMG_common.dat +++ /dev/null @@ -1,1810 +0,0 @@ -# author : Auto-compiled from source -# source : LIST_MICADO_mirrors_static.dat -# description : SurfaceList collapsed into single TERCurve -# date_created : 2020-08-25 -# date_modified : 2020-08-25 -# area : 0.19634954084936207 -# area_unit : m2 -# wavelength_unit : um -# emission_unit : photlam - wavelength transmission emission - 0.7 0.7048043980956935 3.480663855167995e-27 - 0.701 0.7048043980956941 3.853244105083572e-27 - 0.702 0.7048043980956935 4.2644360617549465e-27 - 0.703 0.7048043980956942 4.7181081765553466e-27 - 0.704 0.704804398095694 5.2185029966246055e-27 - 0.705 0.7048043980956926 5.770272021286584e-27 - 0.706 0.7048043980956934 6.378513681422168e-27 - 0.707 0.7048043980956942 7.048814710233854e-27 - 0.708 0.7048043980956934 7.787295195920267e-27 - 0.709 0.7048043980956935 8.600657630585976e-27 - 0.71 0.7048043980956941 9.496240295385715e-27 - 0.711 0.7048043980956926 1.0482075349576296e-26 - 0.712 0.7048043980956926 1.1566952020971726e-26 - 0.713 0.7048043980956935 1.2760485327417307e-26 - 0.714 0.7048043980956926 1.4073190793509894e-26 - 0.715 0.7048043980956934 1.5516565664049364e-26 - 0.716 0.7048043980956941 1.7103177155812796e-26 - 0.717 0.7048043980956934 1.884675833242056e-26 - 0.718 0.7048043980956941 2.0762312233505643e-26 - 0.719 0.7048043980956942 2.2866224939368665e-26 - 0.72 0.7048043980956925 2.5176388306033552e-26 - 0.721 0.7048043980956934 2.7712333163388455e-26 - 0.722 0.7048043980956933 3.0495373831206304e-26 - 0.723 0.7048043980956934 3.354876487456566e-26 - 0.724 0.7048043980956933 3.6897871091889916e-26 - 0.725 0.7048043980956935 4.057035180585434e-26 - 0.726 0.7048043980956926 4.4596360610072e-26 - 0.727 0.7048043980956935 4.900876181328431e-26 - 0.728 0.7048043980956934 5.384336491806816e-26 - 0.729 0.7048043980956927 5.913917857330981e-26 - 0.73 0.7048043980956935 6.49386855494251e-26 - 0.731 0.7048043980956941 7.128814040292221e-26 - 0.732 0.7048043980956934 7.823789162312426e-26 - 0.733 0.7048043980956934 8.584273018907775e-26 - 0.734 0.7048043980956934 9.41622666096388e-26 - 0.735 0.7048043980956925 1.0326133867509889e-25 - 0.736 0.7048043980956934 1.1321045231510005e-25 - 0.737 0.704804398095694 1.2408625813578456e-25 - 0.738 0.7048043980956926 1.3597206640003283e-25 - 0.739 0.7048043980956926 1.4895840341892895e-25 - 0.74 0.7048043980956933 1.6314361254121495e-25 - 0.741 0.7048043980956925 1.7863450316156785e-25 - 0.742 0.7048043980956934 1.9554705141881654e-25 - 0.743 0.7048043980956934 2.1400715652295787e-25 - 0.744 0.7048043980956934 2.3415145693608534e-25 - 0.745 0.7048043980956934 2.5612821093856315e-25 - 0.746 0.7048043980956942 2.8009824643877475e-25 - 0.747 0.7048043980956925 3.0623598523443993e-25 - 0.748 0.7048043980956926 3.3473054730703715e-25 - 0.749 0.7048043980956933 3.6578694112970525e-25 - 0.75 0.7048043980956934 3.9962734639520055e-25 - 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2.4970000000000017 0.8555073405834523 1.067571527147259e-05 - 2.4980000000000016 0.855517679259383 1.0748124112795595e-05 - 2.4990000000000014 0.8555280179977837 1.0820957746534146e-05 diff --git a/MICADO_Sci/TRACE_SCI_15arcsec.fits b/MICADO_Sci/TRACE_SCI_15arcsec.fits deleted file mode 100644 index 258f25a2..00000000 Binary files a/MICADO_Sci/TRACE_SCI_15arcsec.fits and /dev/null differ diff --git a/MICADO_Sci/TRACE_SCI_3arcsec.fits b/MICADO_Sci/TRACE_SCI_3arcsec.fits deleted file mode 100644 index 1391ec3a..00000000 Binary files a/MICADO_Sci/TRACE_SCI_3arcsec.fits and /dev/null differ diff --git a/MICADO_Sci/code/__init__.py b/MICADO_Sci/code/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/MICADO_Sci/code/compile.py b/MICADO_Sci/code/compile.py deleted file mode 100644 index b960bbb3..00000000 --- a/MICADO_Sci/code/compile.py +++ /dev/null @@ -1,102 +0,0 @@ -from os import path as pth -from datetime import date - -import numpy as np -import matplotlib.pyplot as plt -from astropy import units as u -from astropy.table import Table -from astropy.io import fits - -import anisocado as aniso -from scopesim import rc -from scopesim.effects import SurfaceList - -PLOTS = False - -MORFEO_DIR = pth.abspath(pth.join(pth.dirname(__file__), "../../MORFEO/")) -rc.__search_path__.insert(0, MORFEO_DIR) -MICADO_DIR = pth.abspath(pth.join(pth.dirname(__file__), "../../MICADO/")) -rc.__search_path__.insert(0, MICADO_DIR) -MICADO_SCI_DIR = pth.abspath(pth.join(pth.dirname(__file__), "../")) - - -def compress_surface_list_to_ter(f_in, f_out, header_list=[], **kwargs): - """ - A TERCurve (~5ms) is 100x faster than a SurfaceList (~500ms) - - Parameters - ---------- - f_in, f_out : str - header_list: list - kwargs : dict - params to pass to SurfaceList - - """ - - sl = SurfaceList(filename=f_in, **kwargs) - wave = np.arange(0.7, 2.5, 0.001) * u.um - thru = sl.throughput(wave) - flux = sl.emission(wave) - flux[flux < 1e-32 * flux.unit] = 0. - - comments = ["author : Auto-compiled from source", - "source : {}".format(f_in), - "description : SurfaceList collapsed into single TERCurve", - "date_created : {}".format(str(date.today())), - "date_modified : {}".format(str(date.today())), - "area : {}".format(sl.area.value), - "area_unit : m2", - "wavelength_unit : um", - "emission_unit : photlam"] - comments += header_list - - tbl = Table(data=(wave, thru, flux), - names=("wavelength", "transmission", "emission")) - tbl.meta["comments"] = comments - tbl.write(filename=pth.join(MICADO_SCI_DIR, f_out), - format="ascii.fixed_width", delimiter=" ") - - -rc.__currsys__["!ATMO.temperature"] = 0 -kwargs = {"etendue": 978*u.m**2 * (0.004*u.arcsec)**2} - -# MICADO common optics -compress_surface_list_to_ter(f_in="LIST_MICADO_mirrors_static.dat", - f_out="TER_MICADO_IMG_common.dat", **kwargs) - -# RO common optics -compress_surface_list_to_ter(f_in="LIST_RO_SCAO_mirrors.dat", - f_out="TER_MICADO_RO.dat", **kwargs) - -# MORFEO common optics -compress_surface_list_to_ter(f_in="LIST_mirrors_morfeo_mms.tbl", - f_out="TER_MORFEO_MMS.dat", **kwargs) - - -def generate_anisocado_strehl_map_for_micado(): - # 310 nm --> 40 in Ks, 18 in H, 6 in J - nmRms = np.linspace(0, 700, 36) - waves = np.linspace(0.8, 2.4, 9) - offset = [0, 0] - psfs = [] - srs = np.zeros((len(nmRms), len(waves))) - for y, wave in enumerate(waves): - sr = 1 - for x, rms in enumerate(nmRms): - if sr > 0.001: - psf = aniso.AnalyticalScaoPsf(pixelSize=0.004, N=256, - wavelength=wave, nmRms=rms) - psf.shift_off_axis(offset[0], offset[1]) - psfs += [psf.hdu] - sr = psf.strehl_ratio - - srs[x, y] = sr - - print(wave, rms, srs[x, y]) - - hdu = fits.ImageHDU(data=srs) - hdu.writeto("AnisoCADO_rms_map.fits", clobber=True) - - plt.imshow(srs) - plt.colorbar() - plt.show() diff --git a/MICADO_Sci/code/make_simplified_trace_files.py b/MICADO_Sci/code/make_simplified_trace_files.py deleted file mode 100644 index 3571e607..00000000 --- a/MICADO_Sci/code/make_simplified_trace_files.py +++ /dev/null @@ -1,103 +0,0 @@ -from astropy.io import fits -from astropy.table import Table -from astropy import units as u -import numpy as np -import matplotlib.pyplot as plt - - -def make_waves_and_ys(): - waves = {int(np.round(wave, 2) * 1000): None for wave in np.arange(0.60, 2.51, 0.01)} - hdulist = fits.open("../../MICADO/TRACE_3arcsec.fits") - for ext in hdulist[2:]: - for i, lam in enumerate(ext.data["lam"][:-1]): - dy = -np.diff(ext.data["y2"][i:i + 2])[0] - w = int(np.round(lam, 2) * 1000) - if dy > 0: - if waves[w] is None: - waves[w] = dy - elif dy < waves[w]: # flip < if we want best case scenario - waves[w] = dy - - ws = np.array(list(waves.keys())) / 1000. - dys = np.array(list(waves.values())) - - dys[0] = 0 - for i in range(1, len(dys)): - if dys[i] is None: - dys[i] = dys[i-1] - - ys = np.cumsum(np.array(dys)) - - # plt.plot(ws[ws>=0.78], dys[ws>=0.78]) - - return ws, ys - - -def make_trace_table(wave_min, wave_max, width=3): - - waves, ys = make_waves_and_ys() - mask = (waves >= wave_min) * (waves <= wave_max) - waves = waves[mask] * u.um - ys = ys[mask] * u.mm - - n = len(waves) - xs = np.ones(n) / 0.004 * 0.015 * u.mm - ss = np.ones(n) * u.arcsec - - names = ["wavelength", - "s0", "s1", - "x0", "x1", - "y0", "y1"] - data = [waves, - -0.5 * width * ss, 0.5 * width * ss, - -0.5 * width * xs, 0.5 * width * xs, - ys, ys] - tbl = Table(names=names, data=data) - - return tbl - - -def make_hdulist_fits_file(width=3): - pri_hdu = fits.PrimaryHDU() - meta = {"ECAT": 1, - "EDATA": 2} - pri_hdu.header.update(meta) - - # names = ["description", "extension_id", "aperture_id", "image_plane_id"] - # data = [["IJ", "HK"], [2, 3], [0, 0], [0, 0]] - # cat_tbl = Table(names=names, data=data) - # cat_hdu = fits.table_to_hdu(cat_tbl) - # cat_hdu.header["EXTNAME"] = "CAT_TRAC" - - # ij_tbl = make_trace_table(0.75, 1.5, width) - # ij_hdu = fits.table_to_hdu(ij_tbl) - # ij_hdu.header["EXTNAME"] = "IJ_TRACE" - # - # hk_tbl = make_trace_table(1.40, 2.5, width) - # hk_hdu = fits.table_to_hdu(hk_tbl) - # hk_hdu.header["EXTNAME"] = "HK_TRACE" - # - # hdu_list = fits.HDUList([pri_hdu, cat_hdu, ij_hdu, hk_hdu]) - - names = ["description", "extension_id", "aperture_id", "image_plane_id"] - data = [["IJHK"], [2], [0], [0]] - cat_tbl = Table(names=names, data=data) - cat_hdu = fits.table_to_hdu(cat_tbl) - cat_hdu.header["EXTNAME"] = "CAT_TRAC" - - ijhk_tbl = make_trace_table(0.75, 2.5, width) - ijhk_hdu = fits.table_to_hdu(ijhk_tbl) - ijhk_hdu.header["EXTNAME"] = "IJHK" - - hdu_list = fits.HDUList([pri_hdu, cat_hdu, ijhk_hdu]) - - return hdu_list - - -# for width in [3, 15]: -# hdu_list = make_hdulist_fits_file(width) -# hdu_list.writeto(f"TRACE_SCI_{width}arcsec.fits", overwrite=True) - -waves, ys = make_waves_and_ys() -plt.plot(waves[1:], np.diff(ys)) -plt.show() diff --git a/MICADO_Sci/default.yaml b/MICADO_Sci/default.yaml deleted file mode 100644 index e3ed7297..00000000 --- a/MICADO_Sci/default.yaml +++ /dev/null @@ -1,93 +0,0 @@ -# name: micado_sci_default -# description: default observation parameters for MICADO-Sci -# author : Kieran Leschinski -# date_created : 2020-07-09 -# date_modified : 2022-01-12 -# changes: -# - 2022-01-12 (OC) changed spectral_resolution to _bin_width -object : configuration -alias : OBS -name : MICADO_sci_default_configuration -description : default parameters needed for a MICADO-Sci simulation -status : deprecated - -packages : -- Armazones -- ELT -- MORFEO -- MICADO -- MICADO_Sci - -yamls : -- MICADO_Sci.yaml -- MICADO_Sci_detector.yaml - -properties : - modes : ["SCAO", "IMG_4mas"] - dit : 60 - ndit : 1 - airmass : 1.2 - pupil_angle : 0 - filter_name : Ks - -mode_yamls : -- object : instrument - alias : INST - name : SCAO - description : "SCAO optical system" - yamls : - - MICADO_Sci_SCAO.yaml - -- object : instrument - alias : INST - name : MCAO - description : "MCAO optical system" - yamls : - - MICADO_Sci_MCAO.yaml - -- object : instrument - alias : INST - name : IMG_4mas - description : "wide-field imager : 4mas/pix" - properties : - pixel_scale : 0.004 # arcsec / pixel - plate_scale : 0.26666666666 # arcsec / mm - -- object : instrument - alias : INST - name : IMG_1.5mas - description : "zoom imager : 1.5mas/pix" - properties : - pixel_scale : 0.0015 # arcsec / pixel - plate_scale : 0.1 # arcsec / mm - -- object : instrument - alias : INST - name : SPEC - description : "Spectroscopy" - yamls : - - MICADO_Sci_SPEC.yaml - properties : - pixel_scale : 0.004 # arcsec / pixel - plate_scale : 0.26666666666 # arcsec / mm - - ---- -### default simulation parameters needed for a MICADO simulation -object : simulation -alias : SIM -name : MICADO_sci_simulation_parameters -description : RC simulation parameters that need to change for a MICADO-Sci run - -properties : - random : - seed : None # 9001 - - spectral : - wave_min : 0.7 - wave_mid : 1.6 - wave_max : 2.5 - spectral_bin_width : 0.001 - - computing : - preload_field_of_view : True diff --git a/MICADO_Sci/test_micado_sci/__init__.py b/MICADO_Sci/test_micado_sci/__init__.py deleted file mode 100644 index c57a0040..00000000 --- a/MICADO_Sci/test_micado_sci/__init__.py +++ /dev/null @@ -1,7 +0,0 @@ -from os import path as pth -import sys - -if pth.exists("C:/Work/ScopeSim/"): - sys.path.insert(0, "C:/Work/ScopeSim/") - -import scopesim diff --git a/MICADO_Sci/test_micado_sci/test_micado_sci.py b/MICADO_Sci/test_micado_sci/test_micado_sci.py deleted file mode 100644 index a82bfa8b..00000000 --- a/MICADO_Sci/test_micado_sci/test_micado_sci.py +++ /dev/null @@ -1,153 +0,0 @@ -import pytest -from os import path as pth - -import numpy as np -import astropy.units as u -import matplotlib.pyplot as plt -from matplotlib.colors import LogNorm - -import scopesim as sim -from scopesim import rc - -pytest.skip(allow_module_level=True) - -TOP_PATH = pth.abspath(pth.join(pth.dirname(__file__), "../../")) -rc.__config__["!SIM.file.local_packages_path"] = TOP_PATH - -PLOTS = False - - -class TestUserCommands: - def test_reads_in_default_yaml(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci") - isinstance(cmd, sim.UserCommands) - - def test_throws_error_if_wrong_mode_names_passed(self): - with pytest.raises(ValueError): - sim.UserCommands(use_instrument="MICADO_Sci", set_modes=["DODGY_MODE_NAME"]) - - def test_elt_ter_curve_reads_in(self): - filename = pth.join(TOP_PATH, "ELT", "TER_ELT_System_20190611.dat") - elt = sim.effects.TERCurve(filename=filename) - - if PLOTS: - wave = np.arange(0.3, 2.5, 0.001) * u.um - plt.plot(wave, elt.surface.reflection(wave)) - plt.show() - - assert isinstance(elt, sim.effects.TERCurve) - - -class TestOpticalTrain: - def test_makes_mcao_4mas_optical_train(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["MCAO", "IMG_4mas"]) - opt = sim.OpticalTrain(cmd) - print(opt) - assert isinstance(opt, sim.OpticalTrain) - - def test_makes_scao_1_5mas_optical_train(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SCAO", "IMG_1.5mas"]) - opt = sim.OpticalTrain(cmd) - print(opt) - assert isinstance(opt, sim.OpticalTrain) - - def test_makes_spec_3000x50_optical_train(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SPEC"]) - opt = sim.OpticalTrain(cmd) - print(opt) - assert isinstance(opt, sim.OpticalTrain) - - -class TestObserve: - def test_grid_with_scao_4mas(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SCAO", "IMG_4mas"]) - cmd["!OBS.dit"] = 3600 - cmd["!OBS.ndit"] = 5 - - opt = sim.OpticalTrain(cmd) - src = sim.source.source_templates.star_field(100, 20, 30, 3, use_grid=True) - opt.observe(src) - hdus = opt.readout() - im = hdus[0][1].data - - assert im.shape == (1024, 1024) - assert np.median(im) > 0 - - sys_trans = opt.optics_manager.system_transmission - effects = opt.optics_manager.get_z_order_effects(100) - - for effect in effects: - print(effect) - - if PLOTS: - plt.subplot(121) - wave = np.linspace(0.5, 2.5, 1000) * u.um - plt.plot(wave, sys_trans(wave)) - - plt.subplot(122) - im = opt.image_planes[0].image - plt.imshow(im, norm=LogNorm(), - vmin=0.99*np.average(im), vmax=1.1*np.average(im)) - plt.show() - - def test_star_field_with_mcao_4mas(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SCAO", "IMG_4mas"]) - opt = sim.OpticalTrain(cmd) - - src = sim.source.source_templates.star_field(100, 20, 30, 3, use_grid=True) - opt.observe(src) - hdus = opt.readout() - im = hdus[0][1].data - - assert im.shape == (1024, 1024) - assert np.median(im) > 0 - - if PLOTS: - plt.imshow(opt.image_planes[0].image, norm=LogNorm()) - plt.show() - - @pytest.mark.skip(reason="Takes too much memory, can get killed by OOM killer in ScopeSIM 0.4.0. Works in 0.1.4.") - def test_star_field_with_spec(self): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["MCAO", "SPEC"]) - opt = sim.OpticalTrain(cmd) - - src = sim.source.source_templates.star_field(100, 20, 30, 3, use_grid=True) - opt.observe(src) - - if PLOTS: - plt.imshow(opt.image_planes[0].image, norm=LogNorm()) - plt.show() - - @pytest.mark.skip(reason="Takes too much memory, can get killed by OOM killer in ScopeSIM 0.4.0. Works in 0.1.4.") - def test_spec_for_a_specific_wavelength_range_works(self): - n = 11 - src = sim.source.source_templates.star_field(n, 15, 25, 3, use_grid=False) - src.fields[0]["x"] = np.linspace(-1.5, 1.5, n) - src.fields[0]["y"] = [0] * n - # src needs to be shifted to prevent an error from astropy.units: - # "TypeError: None is not a valid Unit - src.shift() - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SCAO", "SPEC"]) - cmd["!OBS.dit"] = 3600 # sec - cmd["!SIM.spectral.wave_mid"] = 1.95 # um - cmd["!INST.aperture.width"] = 3 # arcsec - cmd["!INST.aperture.height"] = 0.05 # arcsec - cmd["!DET.width"] = int((cmd["!INST.aperture.width"] / 0.004) * 1.1) # pixel - cmd["!DET.height"] = 128 # pixel - - opt = sim.OpticalTrain(cmd) - opt.observe(src) - hdu = opt.readout()[0] - # hdu.writeto("spec_scao_massive.TEST.fits", overwrite=True) - - if PLOTS: - plt.imshow(hdu[1].data, norm=LogNorm()) - plt.show() - diff --git a/MICADO_Sci/test_micado_sci/test_radiometry.py b/MICADO_Sci/test_micado_sci/test_radiometry.py deleted file mode 100644 index ec6485e0..00000000 --- a/MICADO_Sci/test_micado_sci/test_radiometry.py +++ /dev/null @@ -1,138 +0,0 @@ -""" ELT ETC results: -1100m2, 5mas/pix --> 978m2 MICADO @ 4mas = 57% of ESO ETC -1100m2, 5mas/pix --> 978m2 MICADO @ 1.5mas = 8% of ESO ETC -1100m2, 5mas/pix --> 978m2 METIS LM @ 5.25mas = 98% of ESO ETC -1100m2, 5mas/pix --> 978m2 METIS N @ 6.8mas = 165% of ESO ETC - -ESO ETC -I (19 mag): BG = 3 ph/s --> 1.7 (MIC@4mas), 0.2 (MIC@1.5mas) (Ohio: 0.8 @4mas, 0.1 @1.5mas) -J (16 mag): BG = 27 ph/s --> 15 (MIC@4mas), 2 (MIC@1.5mas) (Ohio: 11 @4mas, 2 @1.5mas) -H (14 mag): BG = 107 ph/s --> 61 (MIC@4mas), 9 (MIC@1.5mas) (Ohio: 54 @4mas, 8 @1.5mas) -K (13 mag): BG = 147 ph/s --> 84 (MIC@4mas), 12 (MIC@1.5mas) (Ohio: 82 @4mas, 12 @1.5mas) -L (5.3 mag): BG = 41052 ph/s --> 40.000 (MET@5.25mas) -M (1.3 mag/arcsec2): BG = 920959 ph/s --> 903.000 (MET@5.25mas) -N (-3.7mag/arcsec2): BG = 140093628 ph/s --> 231.000.000 (MET@6.8mas) - -* ESO assumes 50% throughput, Ohio adjusted to use 50% -* Ohio using the MICADO filter widths from Ric and the ESO ETC sky backgrounds - -# Cuby et al from https://www.eso.org/sci/facilities/eelt/science/drm/tech_data/background/ -# J (18 mag) 8 (MIC@4mas), 1 (MIC@1.5mas) based on 1200 ph s-1 m-2 um-1 arcsec-2 -# H == K -# H, K (16.5, 15.7 mag) 15 (MIC@4mas), 2 (MIC@1.5mas) based on 2300 ph s-1 m-2 um-1 arcsec-2 -# H, K (14.4, 13.6 mag) 103 (MIC@4mas), 14 (MIC@1.5mas) based on 2300 ph s-1 m-2 um-1 arcsec-2 - - -""" - -import pytest -from pytest import approx -from os import path as pth - -import numpy as np -import astropy.units as u -import matplotlib.pyplot as plt -from matplotlib.colors import LogNorm - -import scopesim as sim -from scopesim import rc - -pytest.skip(allow_module_level=True) - -TOP_PATH = pth.abspath(pth.join(pth.dirname(__file__), "../../")) -rc.__config__["!SIM.file.local_packages_path"] = TOP_PATH - -PLOTS = False - - -class TestMicadoSciRadiometry: - @pytest.mark.xfail(reason="Apparently we don't reach this accuracy") - @pytest.mark.parametrize("filt, bg, ph", - [("Ks", 13, 12), ("H", 14, 8), ("J", 16, 1)]) - def test_scao_zoom_bg_levels_are_similar_to_ETC(self, filt, bg, ph): - self.inner_scao_zoom_bg_levels_are_similar_to_ETC(filt, bg, ph, 0.7) - - @pytest.mark.parametrize("filt, bg, ph", - [("Ks", 13, 12), ("H", 14, 8), ("J", 16, 1)]) - def test_scao_zoom_bg_levels_are_similar_to_ETC_loose(self, filt, bg, ph): - self.inner_scao_zoom_bg_levels_are_similar_to_ETC(filt, bg, ph, 2.6) - - def inner_scao_zoom_bg_levels_are_similar_to_ETC(self, filt, bg, ph, rel): - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["SCAO", "IMG_1.5mas"]) - cmd["!OBS.dit"] = 1 - cmd["!OBS.ndit"] = 1 - cmd["!DET.width"] = 128 - cmd["!DET.height"] = 128 - cmd["!ATMO.background.value"] = bg - cmd["!OBS.filter_name"] = filt - cmd["!INST.psf.strehl"] = 0.6 - - opt = sim.OpticalTrain(cmd) - src = sim.source.source_templates.empty_sky() - opt.observe(src) - sim_ph = np.average(opt.image_planes[0].image) - - print("Sim", sim_ph, "ETC", ph) - assert sim_ph == approx(ph, rel=rel) - - @pytest.mark.xfail(reason="Apparently this level of accuracy isn't met.") - @pytest.mark.parametrize("filt, bg, ph", - [("Ks", 13, 12), ("H", 14, 8), ("J", 16, 1)]) - def test_mcao_wide_bg_levels_are_similar_to_ETC(self, filt, bg, ph): - self.inner_mcao_wide_bg_levels_are_similar_to_ETC(filt, bg, ph, 0.7) - - @pytest.mark.parametrize("filt, bg, ph", - [("Ks", 13, 12), ("H", 14, 8), ("J", 16, 1)]) - def test_mcao_wide_bg_levels_are_similar_to_ETC_loose(self, filt, bg, ph): - self.inner_mcao_wide_bg_levels_are_similar_to_ETC(filt, bg, ph, 2.6) - - def inner_mcao_wide_bg_levels_are_similar_to_ETC(self, filt, bg, ph, rel): - """Inner test of test_mcao_wide_bg_levels_are_similar_to_ETC.""" - cmd = sim.UserCommands(use_instrument="MICADO_Sci", - set_modes=["MCAO", "IMG_1.5mas"]) - cmd["!OBS.dit"] = 1 - cmd["!OBS.ndit"] = 1 - cmd["!DET.width"] = 128 - cmd["!DET.height"] = 128 - cmd["!ATMO.background.value"] = bg - cmd["!OBS.filter_name"] = filt - cmd["!INST.psf.strehl"] = 0.6 - - opt = sim.OpticalTrain(cmd) - src = sim.source.source_templates.empty_sky() - opt.observe(src) - sim_ph = np.average(opt.image_planes[0].image) - - print("Sim", sim_ph, "ETC", ph) - assert sim_ph == approx(ph, rel=rel) - - # - # - # im = opt.image_planes[0].image - # # im = hdu[1].data - # - # print(np.average(im)) - # - # sys_trans = opt.optics_manager.system_transmission - # effects = opt.optics_manager.get_z_order_effects(100) - # - # for effect in effects: - # print(effect) - # - # if PLOTS: - # wave = np.linspace(0.5, 2.5, 1000) * u.um - # plt.plot(wave, sys_trans(wave)) - # plt.show() - # - # if PLOTS: - # plt.imshow(im, norm=LogNorm(), - # vmin=0.9 * np.average(im), - # vmax=1.1 * np.average(im)) - # plt.show() - # - # - # - # - # - diff --git a/MICADO_Sci/test_micado_sci/test_spectral_trace_files.py b/MICADO_Sci/test_micado_sci/test_spectral_trace_files.py deleted file mode 100644 index efc7629f..00000000 --- a/MICADO_Sci/test_micado_sci/test_spectral_trace_files.py +++ /dev/null @@ -1,61 +0,0 @@ -import os.path as pth - -import pytest -from astropy.io import fits -from astropy.wcs import WCS -from matplotlib import pyplot as plt - -from scopesim.effects import SpectralTraceList -from scopesim.tests.mocks.py_objects import header_objects as ho -from scopesim import rc - -pytest.skip(allow_module_level=True) - -PLOTS = False -DATA_DIR = pth.abspath(pth.join(pth.dirname(__file__), "../")) -rc.__search_path__.insert(0, DATA_DIR) - - -class TestInit: - def test_initialises_with_a_hdulist(self): - spt = SpectralTraceList( - filename="TRACE_SCI_3arcsec.fits", - x_colname="x0", - y_colname="y0", - s_colname="s0", - ) - assert isinstance(spt, SpectralTraceList) - assert spt.get_data(2, fits.BinTableHDU) - - @pytest.mark.xfail(reason="butchered by changes in spectral_trace_list[_utils].py") - def test_gets_headers_from_real_file(self): - slit_hdr = ho._long_micado_slit_header() - # slit_hdr = ho._short_micado_slit_header() - wave_min = 0.8 - wave_max = 2.5 - spt = SpectralTraceList( - filename="TRACE_SCI_15arcsec.fits", - x_colname="x0", - y_colname="y0", - s_colname="s0", - ) - - params = {"wave_min": wave_min, "wave_max": wave_max, - "pixel_scale": 0.004, "plate_scale": 0.266666667} - hdrs = spt.get_fov_headers(slit_hdr, **params) - assert isinstance(spt, SpectralTraceList) - - print(len(hdrs)) - - if PLOTS: - spt.plot(wave_min, wave_max) - - # pixel coords - for hdr in hdrs[::300]: - xp = [0, hdr["NAXIS1"], hdr["NAXIS1"], 0] - yp = [0, 0, hdr["NAXIS2"], hdr["NAXIS2"]] - wcs = WCS(hdr, key="D") - # world coords - xw, yw = wcs.all_pix2world(xp, yp, 1) - plt.plot(xw, yw, alpha=0.2) - plt.show() diff --git a/MORFEO/MORFEO.yaml b/MORFEO/MORFEO.yaml index d567959c..7dde679d 100644 --- a/MORFEO/MORFEO.yaml +++ b/MORFEO/MORFEO.yaml @@ -6,7 +6,7 @@ description : MORFEO AO relay module properties : temperature : "!ATMO.temperature" - + psf_file : "PSF_MCAO_ConstPSF_40_18_6.fits" effects : - name: morfeo_surface_list @@ -20,7 +20,7 @@ effects : description : MORFEO field varying MCAO PSF class : FieldConstantPSF kwargs: - filename : PSF_MCAO_ConstPSF_40_18_6.fits + filename : "!RO.psf_file" warning : "Default PSF is not Field Varying. See Documentation" diff --git a/MOSAIC/docs/README.md b/MOSAIC/docs/README.md new file mode 100644 index 00000000..201b5474 --- /dev/null +++ b/MOSAIC/docs/README.md @@ -0,0 +1,80 @@ +```{image} mosaic_scopesim_logo.png +:width: 600px +:alt: MOSAIC + ScopeSim +:align: center +``` + +# MOSAIC + ScopeSim + +## Introduction + +The MOSAIC ETC is built on the generic simulator ScopeSim. MOSAIC is handled +as an instrument package containing configuration files for the various +instrument modes and data files describing the instrument components. + +MOSAIC supports twelve observation modes across visual (VIS) and near-infrared +(NIR) multi-object spectroscopy and NIR integral-field unit (mIFU) operations. + +```{note} +**Bug reports and help desk** + +If you come across a bug or get stuck with ScopeSim or the MOSAIC package, +please [open an issue on GitHub](https://github.com/AstarVienna/irdb/issues) +or contact us by email (see below). + +**Your feedback is the only way we know** what needs to be +changed or improved with the package and the simulator. + +Please always include the output of `scopesim.bug_report()` from your +installation. +``` + +## Downloading the MOSAIC instrument package + +Once ScopeSim is installed, download the MOSAIC instrument package into your +working directory: + +```python +import scopesim +scopesim.download_packages(["Armazones", "ELT", "MOSAIC"]) +``` + +This installs the packages into the subdirectory `./inst_pkgs/`. + +Your working directory should look like this afterwards: + +``` +my_simulations/ +├── .ipynb +└── inst_pkgs/ + ├── Armazones/ + ├── ELT/ + └── MOSAIC/ + └── docs/ + └── example_notebooks/ + └── .ipynb ← copy to working dir before running +``` + +```{include} ../../docs/ScopeSim_guide.md +``` + +## Example notebooks + +Find the notebooks locally in `inst_pkgs/MOSAIC/docs/example_notebooks/` +after downloading the package, or download them from the +[GitHub repository](https://github.com/AstarVienna/irdb/tree/dev_master/MOSAIC/docs/example_notebooks). + +```{warning} +Run notebooks in your working directory, **not** inside `inst_pkgs/`. +Copy the desired notebook out first. +``` + +### Introductory notebooks + +| Notebook | Description | +|----------|-------------| +| [`MOSAIC_demo.ipynb`](example_notebooks/MOSAIC_demo.ipynb) | Introductory overview of how to run MOSAIC simulations in ScopeSim | + +### Instrument homepage + +[MOSAIC at mosaic-elt.eu](https://mosaic-elt.eu/index.php/instrument/) diff --git a/MOSAIC/docs/readme.rst b/MOSAIC/docs/readme.rst deleted file mode 100644 index e92b638f..00000000 --- a/MOSAIC/docs/readme.rst +++ /dev/null @@ -1,133 +0,0 @@ -.. |pic1| image:: mosaic_scopesim_logo.png - :width: 600px - :alt: MOSAIC + ScopeSim - -|pic1| -====== - -Introduction ------------- -The MOSAIC ETC is built on the generic simulator software Scopesim. -MOSAIC itself is handled as an instrument package that contains configuration files for the various instrument modes as well as data files describing the components of the instruments. - - -Prerequisites -------------- - -- A working installation of a recent Python version -- A working installation of Jupyter if you want to run the simulator from notebooks. This is necessary to run the example notebooks contained in the instrument package. -- A working installation of the Python package installer ``pip`` - -.. note:: - - If you come across a bug or get stuck with a certain aspect of ScopeSim or - the MOSAIC package, please get in touch with us (GitHub issue, or email addresses below). - - **Your feedback is the only way we know** what needs to be changed/improved - with the package and the simulator. - - Please always provide the output of the command ``scopesim.bug_report()`` run on your installation. - - -Installation & setup --------------------- - -This is a short overview of the installation and setup procedure; for a more detailed presentation see `Introduction_to_Scopesim_for_MOSAIC `_. - -1. Install ``scopesim`` in your python environment:: - - $ pip install scopesim - - To upgrade an existing installation do:: - - $ pip install -U scopesim - -2. Create a working directory where you want to run simulations, e.g.:: - - $ mkdir ~/path/to/playing_with_scopesim/ - $ cd ~/path/to/playing_with_scopesim - -3. Install relevant irdb packages into this directory:: - - $ python - >> import scopesim - >> scopesim.download_packages(["MOSAIC", "ELT", "Armazones"]) - - This will install the packages in the subdirectory ``./inst_pkgs``. - -4. The MOSAIC package includes a number of tutorial notebooks in the directory ``./inst_pkgs/MOSAIC/docs/example_notebooks/`` (see `Python notebooks`_). - - Copy notebooks to the working directory (i.e. ``./``) to run them.:: - - $ cp ./inst_pkgs/MOSAIC/docs/example_notebooks/ . - -5. In a terminal, execute the notebook by calling:: - - $ jupyter notebook - -6. Follow instructions and explanations in the notebook. Some notebooks use example data; the commands to download these data from the scopesim server are included in the notebooks. - -You can then edit the notebooks and use them as a starting point for your own simulations. - - -Python notebooks ----------------- - -These notebooks can be found either: - -- [locally] in the MOSAIC instrument package in ``docs/example_notebooks``, or -- [download] in the `MOSAIC/docs section of the IRDB Github repository `_ - - -.. warning:: - Notebooks should be run in your working directory, **NOT** directly in the - ``docs/example_notebooks`` folder. Please copy the desired notebook out of - this folder. - -Ideally your folder structure should look like this:: - - working-dir - |- .iypnb - | - |- inst_pkgs - |- MOSAIC - | |- docs - | |- example_notebooks - | |- .iypnb # copy out to working-dir - |- ELT - |- Armazones - - -Introductory notebooks -++++++++++++++++++++++ - -.. list-table:: - :widths: 25 75 - :width: 900px - :header-rows: 1 - - * - Name - - Description - * - | `MOSAIC_demo.ipynb `_ - - Introductory overview of how to run simulations in Scopesim - -Documentation and useful references ------------------------------------ - -- `ScopeSim documentation `_ -- `Sky Object Templates documentation `_ -- `MOSAIC homepage `_ -- For experts: GitHub repositories: - - + `simulator package ScopeSim `_ - + `instrument-specific packages irdb `_. - - -Contact points --------------- -`ScopeSim Slack `_ - -Email: - -- scopesim@univie.ac.at -- kieran.leschinski@univie.ac.at diff --git a/OSIRIS/tests/test_compiles.py b/OSIRIS/tests/test_compiles.py index 9e4c0f93..45b5409c 100644 --- a/OSIRIS/tests/test_compiles.py +++ b/OSIRIS/tests/test_compiles.py @@ -1,3 +1,4 @@ +"""Tests for the OSIRIS instrument""" from pathlib import Path import pytest @@ -13,6 +14,7 @@ PLOTS = False +# pylint: disable=missing-class-docstring,missing-function-docstring class TestOsirisImagingCompiles: def test_everything_is_read_in_nicely(self): @@ -31,13 +33,13 @@ def test_system_throughput_is_not_zero(self): cmds = sim.UserCommands(use_instrument="OSIRIS") osiris = sim.OpticalTrain(cmds) wave = np.arange(0.3, 1.0, 0.001) * u.um - trans = osiris.optics_manager.system_transmission(wave) + trans = osiris.optics_manager.system_transmission() if PLOTS: - plt.plot(wave, trans) + plt.plot(wave, trans(wave)) plt.show() - assert trans.sum() > 0 + assert trans(wave).sum() > 0 @pytest.mark.slow def test_run_imaging_simulation(self): diff --git a/WFC3/test_wfc3/test_full_package_wfc3_ir.py b/WFC3/test_wfc3/test_full_package_wfc3_ir.py index 5a851f26..9db7aa4e 100644 --- a/WFC3/test_wfc3/test_full_package_wfc3_ir.py +++ b/WFC3/test_wfc3/test_full_package_wfc3_ir.py @@ -1,15 +1,18 @@ -# integration test using everything and the HAWKI package -import pytest -from pytest import approx +"""Integration test using everything and the WFC3 package""" + import os from os import path as pth +import pytest +from pytest import approx + import numpy as np from astropy import units as u import scopesim import scopesim.source.source_templates from scopesim import rc +from scopesim.optics.image_plane_utils import calc_footprint from matplotlib import pyplot as plt @@ -24,28 +27,26 @@ PLOTS = False +# pylint: disable=missing-class-docstring,missing-function-docstring -class TestInit: - def test_all_packages_are_available(self): - rc_local_path = rc.__config__["!SIM.file.local_packages_path"] - print("irdb" not in rc_local_path) - for pkg_name in PKGS: - assert os.path.isdir(os.path.join(rc_local_path, pkg_name)) +def test_all_packages_are_available(): + rc_local_path = rc.__config__["!SIM.file.local_packages_path"] + print("irdb" not in rc_local_path) + for pkg_name in PKGS: + assert os.path.isdir(os.path.join(rc_local_path, pkg_name)) +def test_user_commands_loads_without_throwing_errors(capsys): + cmd = scopesim.UserCommands(use_instrument="WFC3") + assert isinstance(cmd, scopesim.UserCommands) + for key in ["SIM", "OBS", "TEL", "INST", "DET"]: + assert key in cmd and len(cmd[key]) > 0 -class TestLoadUserCommands: - def test_user_commands_loads_without_throwing_errors(self, capsys): - cmd = scopesim.UserCommands(use_instrument="WFC3") - assert isinstance(cmd, scopesim.UserCommands) - for key in ["SIM", "OBS", "TEL", "INST", "DET"]: - assert key in cmd and len(cmd[key]) > 0 - - stdout = capsys.readouterr() - assert len(stdout.out) == 0 + stdout = capsys.readouterr() + assert len(stdout.out) == 0 class TestMakeOpticalTrain: - def test_works_seamlessly_for_wfc3_package(self, capsys): + def test_works_seamlessly_for_wfc3_package(self): cmd = scopesim.UserCommands(use_instrument="WFC3") opt = scopesim.OpticalTrain(cmd) @@ -59,9 +60,9 @@ def test_works_seamlessly_for_wfc3_package(self, capsys): # test that we have a system throughput wave = np.linspace(0.7, 1.8, 111) * u.um - tc = opt.optics_manager.system_transmission + tc = opt.optics_manager.system_transmission() # ec = opt.optics_manager.surfaces_table.emission - # ..todo:: something super wierd is going on here when running pytest in the top directory + # ..todo:: something super weird is going on here when running pytest in the top directory assert 0.4 < np.max(tc(wave)) < 0.6 if PLOTS: @@ -77,7 +78,6 @@ def test_works_seamlessly_for_wfc3_package(self, capsys): if PLOTS: fovs = opt.fov_manager.fovs - from scopesim.optics.image_plane_utils import calc_footprint plt.subplot(121) for fov in fovs: x, y = calc_footprint(fov.hdu.header) diff --git a/_REPORTS/badge_report_log.txt b/_REPORTS/badge_report_log.txt index de0280a4..b73fa2ed 100644 --- a/_REPORTS/badge_report_log.txt +++ b/_REPORTS/badge_report_log.txt @@ -1,165 +1,369 @@ -ERROR::LFOA/filters/old_filters/TC_filter_Halpha_wide_old.dat ValeError dictionary update sequence element #0 has length 49; 2 is required -ERROR::OSIRIS/traces/TRACE_R500B.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R500R.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R2500R.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R1000R.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R300R.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R2000B.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R2500V.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R300B.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R2500U.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R1000B.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::OSIRIS/traces/TRACE_R2500I.dat ValeError dictionary update sequence element #0 has length 1; 2 is required -ERROR::METIS/code/2023-06-20-spectra_Grism-M_band.dat ValeError dictionary update sequence element #0 has length 32; 2 is required -ERROR::METIS/code/2023-06-20-spectra_Grism-L_band.dat ValeError dictionary update sequence element #0 has length 32; 2 is required -ERROR::METIS/code/2023-06-20-spectra_Grism-N_band.dat ValeError dictionary update sequence element #0 has length 32; 2 is required -ERROR::NACO/filters/NB_4.05.dat ValeError dictionary update sequence element #0 has length 85; 2 is required -ERROR::NACO/filters/NB_3.74.dat ValeError chr() arg not in range(0x110000) -ERROR::HST/TER_ELT_mirror_mgf2agal.dat ValeError date_last_change=2019-07-25 not equal to date_modified=2018-11-19 -ERROR::HST/wfc3_ir_primary_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::HST/wfc3_ir_secondary_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::MORFEO/TER_MORFEO_mirror_aluminium.dat ValeError date_last_change=2019-07-25 not equal to date_modified=2018-11-19 -ERROR::MORFEO/TER_mirror_silver.dat ValeError date_last_change=2020-06-23 not equal to date_modified=2020-06-22 -ERROR::MORFEO/TER_MORFEO_mirror_mgf2agal.dat ValeError date_last_change=2020-08-25 not equal to date_modified=2018-11-19 -ERROR::MORFEO/TER_MORFEO_entrance_window.dat Unexpected Exception '<' not supported between instances of 'datetime.date' and 'int' -ERROR::LFOA/TER_mirror_aluminium.dat ValeError date_last_change=2019-07-25 not equal to date_modified=2018-11-19 -ERROR::LFOA/TER_focal_reducer.dat ValeError Modified date set but no changes listed. -ERROR::LFOA/filters/old_filters/TC_filter_Halpha_wide_old.dat Error reading dat file expected '', but found '' - in "", line 2, column 1: - wavelength_unit : nm - ^ -ERROR::VLT/TC_mirror_aluminium.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-11-19 -ERROR::VLT/LIST_VLT_mirrors.dat ValeError date_last_change=2020-10-06 not equal to date_modified=2019-08-13 -ERROR::ELT/TER_ELT_mirror_mgf2agal.dat ValeError date_last_change=2020-08-25 not equal to date_modified=2018-11-19 -ERROR::ELT/TER_ELT_5_mirror_clean.dat ValeError date_last_change=2020-08-17 not equal to date_modified=2019-06-11 -ERROR::ELT/TER_ELT_mirror_aluminium.dat ValeError date_last_change=2020-08-25 not equal to date_modified=2018-11-19 -ERROR::MICADO/QE_detector_H4RG.dat Error reading dat file 'NoneType' object is not iterable -ERROR::MICADO/MASK_slit_3000x50.dat ValeError date_last_change=2020-03-24 not equal to date_modified=2019-07-10 -ERROR::MICADO/TER_SCAO_dichroic.dat ValeError date_last_change=2023-07-04 not equal to date_modified=2023-06-13 -ERROR::MICADO/TER_entrance_window.dat ValeError Changes listed but no modified date set. -ERROR::MICADO/TER_mirror_gold.dat ValeError date_last_change=2023-07-13 not equal to date_modified=2023-07-23 -ERROR::MICADO/TER_MICADO_mirror_mgf2agal.dat ValeError date_last_change=2019-07-25 not equal to date_modified=2018-11-19 -ERROR::MICADO/FPA_linearity.dat ValeError date_last_change=2022-03-17 not equal to date_modified=2018-11-19 -ERROR::MICADO/MASK_slit_3000x20.dat ValeError date_last_change=2020-03-24 not equal to date_modified=2019-07-10 -ERROR::MICADO/filters/TC_filter_ND1.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_stop_K.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_Ks2.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_block.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_open.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_ND3.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_blank.dat ValeError Modified date set but no changes listed. -ERROR::MICADO/filters/TC_filter_stop_IJH.dat ValeError Modified date set but no changes listed. -ERROR::test_package/TC_filter_Ks.dat ValeError date_last_change=2019-11-09 not equal to date_modified=2018-01-28 -ERROR::OSIRIS/QE_OSIRIS_old_detector_plus_M3.dat ValeError Modified date set but no changes listed. -ERROR::OSIRIS/unity.dat ValeError date_last_change=2022-03-02 not equal to date_modified=22022-03-02 -ERROR::OSIRIS/QE_OSIRIS_new_detector.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R500B.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R500B.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R500R.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R500R.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R2500R.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R2500R.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R1000R.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R1000R.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R300R.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R300R.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R2000B.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R2000B.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R2500V.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R2500V.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R300B.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R300B.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R2500U.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R2500U.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R1000B.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R1000B.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/traces/TRACE_R2500I.dat Error reading dat file string indices must be integers, not 'str' -ERROR::OSIRIS/traces/TRACE_R2500I.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/code/OSIRIS_stitchedArc.dat Error reading dat file 'comments' -ERROR::OSIRIS/code/OSIRIS_stitchedArc.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/tests/test_data/OSIRIS_stitchedArc.dat Error reading dat file 'comments' -ERROR::OSIRIS/tests/test_data/OSIRIS_stitchedArc.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::OSIRIS/tests/test_data/fg191b2b.dat Error reading dat file 'comments' -ERROR::OSIRIS/tests/test_data/fg191b2b.dat ValeError date_last_change=2022-06-14 not equal to date_modified=2022-03-12 -ERROR::METIS/TER_lms_grism_min.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/FPA_metis_img_nq_aquarius_layout.dat ValeError date_last_change=2022-04-22 not equal to date_modified=2022-04-26 -ERROR::METIS/FPA_metis_img_n_geosnap_layout.dat ValeError date_last_change=2022-02-26 not equal to date_modified=2022-04-26 -ERROR::METIS/TER_img_dichroic.dat ValeError Modified date set but no changes listed. -ERROR::METIS/TER_ADC_const_90.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/FPA_linearity_GeoSnap_low_capacity.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/LIST_METIS_mirrors_img_n.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/TER_mirror_gold.dat ValeError Modified date set but no changes listed. -ERROR::METIS/FPA_linearity_HxRG.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/FPA_linearity_HxRG.dat ValeError Modified date set but no changes listed. -ERROR::METIS/FPA_metis_img_lm_layout.dat ValeError date_last_change=2022-04-22 not equal to date_modified=2020-02-04 -ERROR::METIS/QE_detector_H2RG_METIS.dat ValeError date_last_change=2020-07-23 not equal to date_modified=2020-07-14 -ERROR::METIS/TER_lms_grism_max.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/LIST_ifu_apertures.dat Error reading dat file month must be in 1..12 -ERROR::METIS/QE_detector_geosnap.dat ValeError date_last_change=2020-07-23 not equal to date_modified=2020-07-14 -ERROR::METIS/filters/TC_filter_ND_OD2.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/filters/TC_filter_L.dat Error reading dat file 'dict' object has no attribute 'split' -ERROR::METIS/filters/TC_filter_ND_OD5.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/filters/TC_filter_Q1.dat Error reading dat file 'dict' object has no attribute 'split' -ERROR::METIS/filters/TC_filter_ND_OD3.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/filters/TC_filter_ND_OD4.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/filters/TC_filter_HCI_M.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/filters/TC_filter_ND_OD1.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/wcu/fp_mask_grid_lm.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/wcu/fp_mask_pinhole_n.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/wcu/fp_mask_pinhole_lm.dat Error reading dat file 'NoneType' object is not iterable -ERROR::METIS/code/2023-06-20-spectra_Grism-M_band.dat Error reading dat file mapping values are not allowed here - in "", line 10, column 50: - ... n of coordinates at the detector: Detector sensitive surface, bo ... - ^ -ERROR::METIS/code/2023-06-20-spectra_Grism-L_band.dat Error reading dat file mapping values are not allowed here - in "", line 10, column 50: - ... n of coordinates at the detector: Detector sensitive surface, bo ... - ^ -ERROR::METIS/code/2023-06-20-spectra_Grism-N_band.dat Error reading dat file mapping values are not allowed here - in "", line 10, column 50: - ... n of coordinates at the detector: Detector sensitive surface, bo ... - ^ -ERROR::WFC3/wfc3_ir_win_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F110W.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F127M.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F126N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F139M.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F140W.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F128N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F130N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F098M.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F164N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_dn_002_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F105W.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_fold_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F153M.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_mir1_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_rcp_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F160W.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F132N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_mask_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_mir2_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F167N.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_qe_003_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_cor_004_syn.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/TER_filter_F125W.dat ValeError Modified date set but no changes listed. -ERROR::WFC3/wfc3_ir_csm_001_syn.dat ValeError Modified date set but no changes listed. -ERROR::Armazones/TER_armazones_default_NIR_IMG.dat ValeError date_last_change=2020-10-29 not equal to date_modified=2019-08-09 -ERROR::HAWKI/TER_window.dat ValeError date_last_change=2020-10-06 not equal to date_modified=2018-11-19 -ERROR::HAWKI/TER_mirror_gold.dat ValeError date_last_change=2020-10-06 not equal to date_modified=2019-01-28 -ERROR::HAWKI/FPA_hawki_layout.dat ValeError date_last_change=2018-11-19 not equal to date_modified=2019-08-13 -ERROR::HAWKI/LIST_HAWKI_mirrors.dat ValeError date_last_change=2020-10-06 not equal to date_modified=2019-08-13 -ERROR::HAWKI/filters/TC_filter_NB1190.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_NB1060.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_NB2090.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_H2.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_H.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_J.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_CH4.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_Ks.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_BrGamma.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::HAWKI/filters/TC_filter_Y.dat ValeError date_last_change=2019-08-13 not equal to date_modified=2018-03-21 -ERROR::GTC/unity.dat ValeError Modified date set but no changes listed. -ERROR::MICADO_Sci/TER_MICADO_RO.dat ValeError Modified date set but no changes listed. -ERROR::MICADO_Sci/TER_MICADO_IMG_common.dat ValeError Modified date set but no changes listed. -ERROR::MICADO_Sci/TER_MORFEO_MMS.dat ValeError Modified date set but no changes listed. +ERROR::Armazones\TER_armazones_default_FULL_IMG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::Armazones\TER_armazones_default_MIR_IMG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::Armazones\TER_armazones_default_NIR_IMG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::Armazones\TER_armazones_default_OPT_IMG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['Armazones\\TER_armazones_default_FULL_IMG.dat', 'Armazones\\TER_armazones_default_MIR_IMG.dat', 'Armazones\\TER_armazones_default_NIR_IMG.dat', 'Armazones\\TER_armazones_default_OPT_IMG.dat']} +ERROR::ELT\TER_ELT_5_mirror.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_5_mirror_clean.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_6_mirror_field_track.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_6_mirror_field_track_clean.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_6_mirror_pupil_track.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_6_mirror_pupil_track_clean.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_mirror_aluminium.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ELT\TER_ELT_mirror_mgf2agal.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['ELT\\TER_ELT_5_mirror.dat', 'ELT\\TER_ELT_5_mirror_clean.dat', 'ELT\\TER_ELT_6_mirror_field_track.dat', 'ELT\\TER_ELT_6_mirror_field_track_clean.dat', 'ELT\\TER_ELT_6_mirror_pupil_track.dat', 'ELT\\TER_ELT_6_mirror_pupil_track_clean.dat', 'ELT\\TER_ELT_mirror_aluminium.dat', 'ELT\\TER_ELT_mirror_mgf2agal.dat']} +ERROR::GTC\reflectivity_GTC.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::GTC\unity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['GTC\\reflectivity_GTC.dat', 'GTC\\unity.dat']} +ERROR::HAWKI\FPA_hawki_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\FPA_linearity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\LIST_HAWKI_mirrors.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\QE_detector_H2RG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\TC_dichroic.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\TER_mirror_gold.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\TER_window.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_BrGamma.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_CH4.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_H2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_Ks.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_NB1060.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_NB1190.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_NB2090.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\filters\TC_filter_Y.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\BG_total_BrGamma.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\BG_total_J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\BG_total_Ks.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\ESO_ETC_bg_fluxes.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_BrGamma.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_CH4.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_Ks.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HAWKI\test_hawki\hawki_eso_etc\TER_system_Y.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['HAWKI\\FPA_hawki_layout.dat', 'HAWKI\\FPA_linearity.dat', 'HAWKI\\LIST_HAWKI_mirrors.dat', 'HAWKI\\QE_detector_H2RG.dat', 'HAWKI\\TC_dichroic.dat', 'HAWKI\\TER_mirror_gold.dat', 'HAWKI\\TER_window.dat', 'HAWKI\\filters\\TC_filter_BrGamma.dat', 'HAWKI\\filters\\TC_filter_CH4.dat', 'HAWKI\\filters\\TC_filter_H.dat', 'HAWKI\\filters\\TC_filter_H2.dat', 'HAWKI\\filters\\TC_filter_J.dat', 'HAWKI\\filters\\TC_filter_Ks.dat', 'HAWKI\\filters\\TC_filter_NB1060.dat', 'HAWKI\\filters\\TC_filter_NB1190.dat', 'HAWKI\\filters\\TC_filter_NB2090.dat', 'HAWKI\\filters\\TC_filter_Y.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\BG_total_BrGamma.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\BG_total_J.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\BG_total_Ks.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\ESO_ETC_bg_fluxes.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_BrGamma.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_CH4.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_H.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_J.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_Ks.dat', 'HAWKI\\test_hawki\\hawki_eso_etc\\TER_system_Y.dat']} +ERROR::HST\TER_ELT_mirror_mgf2agal.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HST\wfc3_ir_primary_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::HST\wfc3_ir_secondary_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['HST\\TER_ELT_mirror_mgf2agal.dat', 'HST\\wfc3_ir_primary_001_syn.dat', 'HST\\wfc3_ir_secondary_001_syn.dat']} +ERROR::JWST\TER_mirror_gold.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['JWST\\TER_mirror_gold.dat']} +ERROR::LaPalma\orm_extinct.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['LaPalma\\orm_extinct.dat']} +ERROR::LFOA\LIST_LFOA_mirrors_static.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\QE_SBIG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\TER_atmosphere.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\TER_focal_reducer.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\TER_mirror_aluminium.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\Halpha_narrow.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\Halpha_wide.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\Hbeta.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\I.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\OIII.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\SII.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\sloan_g.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\sloan_i.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\sloan_r.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\sloan_u.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\sloan_z.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\U.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\V.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\old_filters\TC_filter_Halpha_narrow_old.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\old_filters\TC_filter_Halpha_wide_old.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\old_filters\TC_filter_Hbeta_old.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\old_filters\TC_filter_OIII_old.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::LFOA\filters\old_filters\TC_filter_SII_old.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['LFOA\\LIST_LFOA_mirrors_static.dat', 'LFOA\\QE_SBIG.dat', 'LFOA\\TER_atmosphere.dat', 'LFOA\\TER_focal_reducer.dat', 'LFOA\\TER_mirror_aluminium.dat', 'LFOA\\filters\\B.dat', 'LFOA\\filters\\Halpha_narrow.dat', 'LFOA\\filters\\Halpha_wide.dat', 'LFOA\\filters\\Hbeta.dat', 'LFOA\\filters\\I.dat', 'LFOA\\filters\\OIII.dat', 'LFOA\\filters\\R.dat', 'LFOA\\filters\\SII.dat', 'LFOA\\filters\\sloan_g.dat', 'LFOA\\filters\\sloan_i.dat', 'LFOA\\filters\\sloan_r.dat', 'LFOA\\filters\\sloan_u.dat', 'LFOA\\filters\\sloan_z.dat', 'LFOA\\filters\\U.dat', 'LFOA\\filters\\V.dat', 'LFOA\\filters\\old_filters\\TC_filter_Halpha_narrow_old.dat', 'LFOA\\filters\\old_filters\\TC_filter_Halpha_wide_old.dat', 'LFOA\\filters\\old_filters\\TC_filter_Hbeta_old.dat', 'LFOA\\filters\\old_filters\\TC_filter_OIII_old.dat', 'LFOA\\filters\\old_filters\\TC_filter_SII_old.dat']} +ERROR::METIS\FPA_linearity_GeoSnap_high_capacity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_linearity_GeoSnap_low_capacity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_linearity_HxRG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_metis_img_lm_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_metis_img_nq_aquarius_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_metis_img_n_geosnap_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_metis_lms_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\FPA_metis_lms_smpl_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_ifu_apertures.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_METIS_mirrors_cfo.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_METIS_mirrors_img_lm.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_METIS_mirrors_img_n.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_METIS_mirrors_lms.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\LIST_METIS_mirrors_wcu.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\MASK_slit_A-19_0.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\MASK_slit_B-28_6.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\MASK_slit_C-38_1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\MASK_slit_D-57_1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\MASK_slit_E-114_2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\QE_detector_geosnap.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\QE_detector_H2RG_METIS.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_ADC_const_90.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_entrance_window.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_img_dichroic.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_lms_grism_max.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_lms_grism_min.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_lms_predisperser_prism.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_mirror_aluminium.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_mirror_gold.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\TER_sca_dichroic.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\code\2023-06-20-spectra_Grism-L_band.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\code\2023-06-20-spectra_Grism-M_band.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\code\2023-06-20-spectra_Grism-N_band.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Br_alpha.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Br_alpha_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_CO_1-0_ice.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_CO_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_H2O-ice.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_HCI_L_long.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_HCI_L_short.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_HCI_M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_IB_4.05.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_L.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Lp.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_L_spec.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Mp.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_M_spec.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_N1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_N2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_N3.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_ND_OD1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_ND_OD2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_ND_OD3.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_ND_OD4.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_ND_OD5.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Ne_II.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Ne_II_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_N_spec.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_open.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_11.25.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_11.25_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_3.3.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_3.3_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_8.6.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_PAH_8.6_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_Q1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_short-L.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_S_IV.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\filters\TC_filter_S_IV_ref.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\wcu\fp_mask_grid_lm.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\wcu\fp_mask_pinhole_lm.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::METIS\wcu\fp_mask_pinhole_n.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['METIS\\FPA_linearity_GeoSnap_high_capacity.dat', 'METIS\\FPA_linearity_GeoSnap_low_capacity.dat', 'METIS\\FPA_linearity_HxRG.dat', 'METIS\\FPA_metis_img_lm_layout.dat', 'METIS\\FPA_metis_img_nq_aquarius_layout.dat', 'METIS\\FPA_metis_img_n_geosnap_layout.dat', 'METIS\\FPA_metis_lms_layout.dat', 'METIS\\FPA_metis_lms_smpl_layout.dat', 'METIS\\LIST_ifu_apertures.dat', 'METIS\\LIST_METIS_mirrors_cfo.dat', 'METIS\\LIST_METIS_mirrors_img_lm.dat', 'METIS\\LIST_METIS_mirrors_img_n.dat', 'METIS\\LIST_METIS_mirrors_lms.dat', 'METIS\\LIST_METIS_mirrors_wcu.dat', 'METIS\\MASK_slit_A-19_0.dat', 'METIS\\MASK_slit_B-28_6.dat', 'METIS\\MASK_slit_C-38_1.dat', 'METIS\\MASK_slit_D-57_1.dat', 'METIS\\MASK_slit_E-114_2.dat', 'METIS\\QE_detector_geosnap.dat', 'METIS\\QE_detector_H2RG_METIS.dat', 'METIS\\TER_ADC_const_90.dat', 'METIS\\TER_entrance_window.dat', 'METIS\\TER_img_dichroic.dat', 'METIS\\TER_lms_grism_max.dat', 'METIS\\TER_lms_grism_min.dat', 'METIS\\TER_lms_predisperser_prism.dat', 'METIS\\TER_mirror_aluminium.dat', 'METIS\\TER_mirror_gold.dat', 'METIS\\TER_sca_dichroic.dat', 'METIS\\code\\2023-06-20-spectra_Grism-L_band.dat', 'METIS\\code\\2023-06-20-spectra_Grism-M_band.dat', 'METIS\\code\\2023-06-20-spectra_Grism-N_band.dat', 'METIS\\filters\\TC_filter_Br_alpha.dat', 'METIS\\filters\\TC_filter_Br_alpha_ref.dat', 'METIS\\filters\\TC_filter_CO_1-0_ice.dat', 'METIS\\filters\\TC_filter_CO_ref.dat', 'METIS\\filters\\TC_filter_H2O-ice.dat', 'METIS\\filters\\TC_filter_HCI_L_long.dat', 'METIS\\filters\\TC_filter_HCI_L_short.dat', 'METIS\\filters\\TC_filter_HCI_M.dat', 'METIS\\filters\\TC_filter_IB_4.05.dat', 'METIS\\filters\\TC_filter_L.dat', 'METIS\\filters\\TC_filter_Lp.dat', 'METIS\\filters\\TC_filter_L_spec.dat', 'METIS\\filters\\TC_filter_Mp.dat', 'METIS\\filters\\TC_filter_M_spec.dat', 'METIS\\filters\\TC_filter_N1.dat', 'METIS\\filters\\TC_filter_N2.dat', 'METIS\\filters\\TC_filter_N3.dat', 'METIS\\filters\\TC_filter_ND_OD1.dat', 'METIS\\filters\\TC_filter_ND_OD2.dat', 'METIS\\filters\\TC_filter_ND_OD3.dat', 'METIS\\filters\\TC_filter_ND_OD4.dat', 'METIS\\filters\\TC_filter_ND_OD5.dat', 'METIS\\filters\\TC_filter_Ne_II.dat', 'METIS\\filters\\TC_filter_Ne_II_ref.dat', 'METIS\\filters\\TC_filter_N_spec.dat', 'METIS\\filters\\TC_filter_open.dat', 'METIS\\filters\\TC_filter_PAH_11.25.dat', 'METIS\\filters\\TC_filter_PAH_11.25_ref.dat', 'METIS\\filters\\TC_filter_PAH_3.3.dat', 'METIS\\filters\\TC_filter_PAH_3.3_ref.dat', 'METIS\\filters\\TC_filter_PAH_8.6.dat', 'METIS\\filters\\TC_filter_PAH_8.6_ref.dat', 'METIS\\filters\\TC_filter_Q1.dat', 'METIS\\filters\\TC_filter_short-L.dat', 'METIS\\filters\\TC_filter_S_IV.dat', 'METIS\\filters\\TC_filter_S_IV_ref.dat', 'METIS\\wcu\\fp_mask_grid_lm.dat', 'METIS\\wcu\\fp_mask_pinhole_lm.dat', 'METIS\\wcu\\fp_mask_pinhole_n.dat']} +ERROR::MICADO\FPA_array_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\FPA_linearity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\INST_MICADO_wavefront_error_budget.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\LIST_MICADO_mirrors_spec.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\LIST_MICADO_mirrors_static.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\LIST_MICADO_mirrors_wide.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\LIST_MICADO_mirrors_zoom.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\LIST_RO_SCAO_mirrors.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\MASK_slit_15000x20.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\MASK_slit_3000x16.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\MASK_slit_3000x48.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\QE_detector_H2RG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\QE_detector_H4RG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_coating_antireflection.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_entrance_window.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_full_adc.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_grating.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_MICADO_mirror_mgf2agal.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_mirror_gold.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\TER_SCAO_dichroic.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_blank.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_block.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Br-gamma.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_FeII.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_H-cont.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_H-long.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_H-short.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_H2_1-0S1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_He-I.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_I-long.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_J-long.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_J-short.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_K-cont.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_K-long.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_K-mid.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_K-short.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Ks.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Ks2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_ND1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_ND3.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_open.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Pa-beta.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Spec_HK.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Spec_IJ.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_stop_IJH.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_stop_K.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xH1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xH2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xI1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xI2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xJ1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xJ2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xK1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xK2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xY1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_xY2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MICADO\filters\TC_filter_Y.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['MICADO\\FPA_array_layout.dat', 'MICADO\\FPA_linearity.dat', 'MICADO\\INST_MICADO_wavefront_error_budget.dat', 'MICADO\\LIST_MICADO_mirrors_spec.dat', 'MICADO\\LIST_MICADO_mirrors_static.dat', 'MICADO\\LIST_MICADO_mirrors_wide.dat', 'MICADO\\LIST_MICADO_mirrors_zoom.dat', 'MICADO\\LIST_RO_SCAO_mirrors.dat', 'MICADO\\MASK_slit_15000x20.dat', 'MICADO\\MASK_slit_3000x16.dat', 'MICADO\\MASK_slit_3000x48.dat', 'MICADO\\QE_detector_H2RG.dat', 'MICADO\\QE_detector_H4RG.dat', 'MICADO\\TER_coating_antireflection.dat', 'MICADO\\TER_entrance_window.dat', 'MICADO\\TER_full_adc.dat', 'MICADO\\TER_grating.dat', 'MICADO\\TER_MICADO_mirror_mgf2agal.dat', 'MICADO\\TER_mirror_gold.dat', 'MICADO\\TER_SCAO_dichroic.dat', 'MICADO\\filters\\TC_filter_blank.dat', 'MICADO\\filters\\TC_filter_block.dat', 'MICADO\\filters\\TC_filter_Br-gamma.dat', 'MICADO\\filters\\TC_filter_FeII.dat', 'MICADO\\filters\\TC_filter_H-cont.dat', 'MICADO\\filters\\TC_filter_H-long.dat', 'MICADO\\filters\\TC_filter_H-short.dat', 'MICADO\\filters\\TC_filter_H.dat', 'MICADO\\filters\\TC_filter_H2_1-0S1.dat', 'MICADO\\filters\\TC_filter_He-I.dat', 'MICADO\\filters\\TC_filter_I-long.dat', 'MICADO\\filters\\TC_filter_J-long.dat', 'MICADO\\filters\\TC_filter_J-short.dat', 'MICADO\\filters\\TC_filter_J.dat', 'MICADO\\filters\\TC_filter_K-cont.dat', 'MICADO\\filters\\TC_filter_K-long.dat', 'MICADO\\filters\\TC_filter_K-mid.dat', 'MICADO\\filters\\TC_filter_K-short.dat', 'MICADO\\filters\\TC_filter_Ks.dat', 'MICADO\\filters\\TC_filter_Ks2.dat', 'MICADO\\filters\\TC_filter_ND1.dat', 'MICADO\\filters\\TC_filter_ND3.dat', 'MICADO\\filters\\TC_filter_open.dat', 'MICADO\\filters\\TC_filter_Pa-beta.dat', 'MICADO\\filters\\TC_filter_Spec_HK.dat', 'MICADO\\filters\\TC_filter_Spec_IJ.dat', 'MICADO\\filters\\TC_filter_stop_IJH.dat', 'MICADO\\filters\\TC_filter_stop_K.dat', 'MICADO\\filters\\TC_filter_xH1.dat', 'MICADO\\filters\\TC_filter_xH2.dat', 'MICADO\\filters\\TC_filter_xI1.dat', 'MICADO\\filters\\TC_filter_xI2.dat', 'MICADO\\filters\\TC_filter_xJ1.dat', 'MICADO\\filters\\TC_filter_xJ2.dat', 'MICADO\\filters\\TC_filter_xK1.dat', 'MICADO\\filters\\TC_filter_xK2.dat', 'MICADO\\filters\\TC_filter_xY1.dat', 'MICADO\\filters\\TC_filter_xY2.dat', 'MICADO\\filters\\TC_filter_Y.dat']} +ERROR::MORFEO\TER_mirror_silver.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_entrance_window.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_lgs_dichroic.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_mirror_aluminium.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_mirror_gold.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_mirror_mgf2agal.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MORFEO\TER_MORFEO_mirror_silver.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['MORFEO\\TER_mirror_silver.dat', 'MORFEO\\TER_MORFEO_entrance_window.dat', 'MORFEO\\TER_MORFEO_lgs_dichroic.dat', 'MORFEO\\TER_MORFEO_mirror_aluminium.dat', 'MORFEO\\TER_MORFEO_mirror_gold.dat', 'MORFEO\\TER_MORFEO_mirror_mgf2agal.dat', 'MORFEO\\TER_MORFEO_mirror_silver.dat']} +ERROR::MOSAIC\FPA_linearity_HxRG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\FPA_mosaic_NIR_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\FPA_mosaic_VIS_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\QE_detector_NIR.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\QE_VIS_ML2_depleted.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\QE_VIS_ML2_standard.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_grating_VIS_LR_B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mIFU_HR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mIFU_LR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mIFU_LR-J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mos_HR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mos_LR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_mos_LR-J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_spec_HR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_spec_LR-H.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_spec_LR-J.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-HR-B1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-HR-B2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-HR-R1.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-HR-R2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-LR-B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::MOSAIC\TER_sys_MOS-LR-R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['MOSAIC\\FPA_linearity_HxRG.dat', 'MOSAIC\\FPA_mosaic_NIR_layout.dat', 'MOSAIC\\FPA_mosaic_VIS_layout.dat', 'MOSAIC\\QE_detector_NIR.dat', 'MOSAIC\\QE_VIS_ML2_depleted.dat', 'MOSAIC\\QE_VIS_ML2_standard.dat', 'MOSAIC\\TER_grating_VIS_LR_B.dat', 'MOSAIC\\TER_mIFU_HR-H.dat', 'MOSAIC\\TER_mIFU_LR-H.dat', 'MOSAIC\\TER_mIFU_LR-J.dat', 'MOSAIC\\TER_mos_HR-H.dat', 'MOSAIC\\TER_mos_LR-H.dat', 'MOSAIC\\TER_mos_LR-J.dat', 'MOSAIC\\TER_spec_HR-H.dat', 'MOSAIC\\TER_spec_LR-H.dat', 'MOSAIC\\TER_spec_LR-J.dat', 'MOSAIC\\TER_sys_MOS-HR-B1.dat', 'MOSAIC\\TER_sys_MOS-HR-B2.dat', 'MOSAIC\\TER_sys_MOS-HR-R1.dat', 'MOSAIC\\TER_sys_MOS-HR-R2.dat', 'MOSAIC\\TER_sys_MOS-LR-B.dat', 'MOSAIC\\TER_sys_MOS-LR-R.dat']} +ERROR::NACO\filters\H_CONICA.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.00.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.03.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.06.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.09.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.12.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.15.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.18.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.21.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.24.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.27.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.30.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.33.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.36.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.39.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.42.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.45.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\IB_2.48.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\J_CONICA.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\Ks_CONICA.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\L_prime.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\M_prime.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.04.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.08.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.09.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.24.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.26.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.28.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.64.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_1.75.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_2.12.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_2.17.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_3.74.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NACO\filters\NB_4.05.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['NACO\\filters\\H_CONICA.dat', 'NACO\\filters\\IB_2.00.dat', 'NACO\\filters\\IB_2.03.dat', 'NACO\\filters\\IB_2.06.dat', 'NACO\\filters\\IB_2.09.dat', 'NACO\\filters\\IB_2.12.dat', 'NACO\\filters\\IB_2.15.dat', 'NACO\\filters\\IB_2.18.dat', 'NACO\\filters\\IB_2.21.dat', 'NACO\\filters\\IB_2.24.dat', 'NACO\\filters\\IB_2.27.dat', 'NACO\\filters\\IB_2.30.dat', 'NACO\\filters\\IB_2.33.dat', 'NACO\\filters\\IB_2.36.dat', 'NACO\\filters\\IB_2.39.dat', 'NACO\\filters\\IB_2.42.dat', 'NACO\\filters\\IB_2.45.dat', 'NACO\\filters\\IB_2.48.dat', 'NACO\\filters\\J_CONICA.dat', 'NACO\\filters\\Ks_CONICA.dat', 'NACO\\filters\\L_prime.dat', 'NACO\\filters\\M_prime.dat', 'NACO\\filters\\NB_1.04.dat', 'NACO\\filters\\NB_1.08.dat', 'NACO\\filters\\NB_1.09.dat', 'NACO\\filters\\NB_1.24.dat', 'NACO\\filters\\NB_1.26.dat', 'NACO\\filters\\NB_1.28.dat', 'NACO\\filters\\NB_1.64.dat', 'NACO\\filters\\NB_1.75.dat', 'NACO\\filters\\NB_2.12.dat', 'NACO\\filters\\NB_2.17.dat', 'NACO\\filters\\NB_3.74.dat', 'NACO\\filters\\NB_4.05.dat']} +ERROR::NIRCam\DET_LW_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\DET_LW_layout_simple.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\DET_SW_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F250M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F277W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F300M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F322W2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F323N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F335M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F356W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F360M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F405N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F410M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F430M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F444W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F460M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F466N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F470N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\long_wl\TC_filter_F480M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F070W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F090W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F115W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F140M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F150W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F150W2.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F162M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F164N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F182M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F187N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F200W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F210M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::NIRCam\filters\short_wl\TC_filter_F212N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['NIRCam\\DET_LW_layout.dat', 'NIRCam\\DET_LW_layout_simple.dat', 'NIRCam\\DET_SW_layout.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F250M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F277W.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F300M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F322W2.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F323N.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F335M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F356W.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F360M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F405N.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F410M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F430M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F444W.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F460M.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F466N.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F470N.dat', 'NIRCam\\filters\\long_wl\\TC_filter_F480M.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F070W.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F090W.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F115W.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F140M.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F150W.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F150W2.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F162M.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F164N.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F182M.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F187N.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F200W.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F210M.dat', 'NIRCam\\filters\\short_wl\\TC_filter_F212N.dat']} +ERROR::OSIRIS\GTC_im_efficiency.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\MAAT_APERTURES.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\QE_OSIRIS_new_detector.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\QE_OSIRIS_old_detector_plus_M3.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\unity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\code\OSIRIS_stitchedArc.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R1000B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R1000R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R2000B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R2500I.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R2500R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R2500U.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R2500V.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R300B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R300R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R500B.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\traces\TRACE_R500R.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\tests\test_data\fg191b2b.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::OSIRIS\tests\test_data\OSIRIS_stitchedArc.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['OSIRIS\\GTC_im_efficiency.dat', 'OSIRIS\\MAAT_APERTURES.dat', 'OSIRIS\\QE_OSIRIS_new_detector.dat', 'OSIRIS\\QE_OSIRIS_old_detector_plus_M3.dat', 'OSIRIS\\unity.dat', 'OSIRIS\\code\\OSIRIS_stitchedArc.dat', 'OSIRIS\\traces\\TRACE_R1000B.dat', 'OSIRIS\\traces\\TRACE_R1000R.dat', 'OSIRIS\\traces\\TRACE_R2000B.dat', 'OSIRIS\\traces\\TRACE_R2500I.dat', 'OSIRIS\\traces\\TRACE_R2500R.dat', 'OSIRIS\\traces\\TRACE_R2500U.dat', 'OSIRIS\\traces\\TRACE_R2500V.dat', 'OSIRIS\\traces\\TRACE_R300B.dat', 'OSIRIS\\traces\\TRACE_R300R.dat', 'OSIRIS\\traces\\TRACE_R500B.dat', 'OSIRIS\\traces\\TRACE_R500R.dat', 'OSIRIS\\tests\\test_data\\fg191b2b.dat', 'OSIRIS\\tests\\test_data\\OSIRIS_stitchedArc.dat']} +ERROR::Paranal\TER_paranal_default_NIR_IMG.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['Paranal\\TER_paranal_default_NIR_IMG.dat']} +ERROR::test_package\TC_filter_Ks.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['test_package\\TC_filter_Ks.dat']} +ERROR::ViennaLT\FPA_ViLT_layout.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::ViennaLT\LIST_ViLT_mirrors_static.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['ViennaLT\\FPA_ViLT_layout.dat', 'ViennaLT\\LIST_ViLT_mirrors_static.dat']} +ERROR::VLT\LIST_VLT_mirrors.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::VLT\TC_mirror_aluminium.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['VLT\\LIST_VLT_mirrors.dat', 'VLT\\TC_mirror_aluminium.dat']} +ERROR::WFC3\FPA_linearity.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\LIST_WFC3_mirrors_IR.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_cor_004_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_csm_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_dn_002_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_fold_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_mask_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_mir1_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_mir2_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_qe_003_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_rcp_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\wfc3_ir_win_001_syn.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F098M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F105W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F110W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F125W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F126N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F127M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F128N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F130N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F132N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F139M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F140W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F153M.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F160W.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F164N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +ERROR::WFC3\filters\TER_filter_F167N.dat Unexpected Exception 'WindowsPath' object has no attribute 'lower' +INFO::{'inconsistent_table_error': [], 'value_error': [], 'unexpected_error': ['WFC3\\FPA_linearity.dat', 'WFC3\\LIST_WFC3_mirrors_IR.dat', 'WFC3\\wfc3_ir_cor_004_syn.dat', 'WFC3\\wfc3_ir_csm_001_syn.dat', 'WFC3\\wfc3_ir_dn_002_syn.dat', 'WFC3\\wfc3_ir_fold_001_syn.dat', 'WFC3\\wfc3_ir_mask_001_syn.dat', 'WFC3\\wfc3_ir_mir1_001_syn.dat', 'WFC3\\wfc3_ir_mir2_001_syn.dat', 'WFC3\\wfc3_ir_qe_003_syn.dat', 'WFC3\\wfc3_ir_rcp_001_syn.dat', 'WFC3\\wfc3_ir_win_001_syn.dat', 'WFC3\\filters\\TER_filter_F098M.dat', 'WFC3\\filters\\TER_filter_F105W.dat', 'WFC3\\filters\\TER_filter_F110W.dat', 'WFC3\\filters\\TER_filter_F125W.dat', 'WFC3\\filters\\TER_filter_F126N.dat', 'WFC3\\filters\\TER_filter_F127M.dat', 'WFC3\\filters\\TER_filter_F128N.dat', 'WFC3\\filters\\TER_filter_F130N.dat', 'WFC3\\filters\\TER_filter_F132N.dat', 'WFC3\\filters\\TER_filter_F139M.dat', 'WFC3\\filters\\TER_filter_F140W.dat', 'WFC3\\filters\\TER_filter_F153M.dat', 'WFC3\\filters\\TER_filter_F160W.dat', 'WFC3\\filters\\TER_filter_F164N.dat', 'WFC3\\filters\\TER_filter_F167N.dat']} diff --git a/_REPORTS/badges.md b/_REPORTS/badges.md index 73a533ef..755dc41b 100644 --- a/_REPORTS/badges.md +++ b/_REPORTS/badges.md @@ -1,156 +1,413 @@ # IRDB Packages Report -**Created on UTC 2025-06-30 17:09:04** - For details on errors and conflicts, see badge report log file in this directory. -## HARMONI +## Armazones [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure -* [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() -* [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() +* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents -* [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## UVES +* [![](https://img.shields.io/badge/all_yamls_readable-green)]() +* [![](https://img.shields.io/badge/TER_armazones_default_FULL_IMG.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_armazones_default_MIR_IMG.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_armazones_default_NIR_IMG.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_armazones_default_OPT_IMG.dat-error-red)]() +## ELT +[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() +### Structure +* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() +* [![](https://img.shields.io/badge/#telescope_reflection.filename-missing-red)]() +### Contents +* [![](https://img.shields.io/badge/all_yamls_readable-green)]() +* [![](https://img.shields.io/badge/TER_ELT_5_mirror.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_5_mirror_clean.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_6_mirror_field_track.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_6_mirror_field_track_clean.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_6_mirror_pupil_track.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_6_mirror_pupil_track_clean.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_mirror_aluminium.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ELT_mirror_mgf2agal.dat-error-red)]() +## ERIS [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## KMOS +## FORS [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## HST +## GTC [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_ELT_mirror_mgf2agal.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_primary_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_secondary_001_syn.dat-conflict-orange)]() -## MCIFU +* [![](https://img.shields.io/badge/reflectivity_GTC.dat-error-red)]() +* [![](https://img.shields.io/badge/unity.dat-error-red)]() +## HARMONI [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## MORFEO +## HAWKI +[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() +### Structure +* [![](https://img.shields.io/badge/default_yaml-OK-green)]() +* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() +### Contents +* [![](https://img.shields.io/badge/all_yamls_readable-green)]() +* [![](https://img.shields.io/badge/FPA_hawki_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_linearity.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_HAWKI_mirrors.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_H2RG.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_dichroic.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mirror_gold.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_window.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_BrGamma.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_CH4.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_J.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Ks.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_NB1060.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_NB1190.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_NB2090.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Y.dat-error-red)]() +* [![](https://img.shields.io/badge/BG_total_BrGamma.dat-error-red)]() +* [![](https://img.shields.io/badge/BG_total_J.dat-error-red)]() +* [![](https://img.shields.io/badge/BG_total_Ks.dat-error-red)]() +* [![](https://img.shields.io/badge/ESO_ETC_bg_fluxes.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_BrGamma.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_CH4.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_J.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_Ks.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_system_Y.dat-error-red)]() +## HST [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_MORFEO_mirror_aluminium.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_mirror_silver.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_MORFEO_mirror_mgf2agal.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_MORFEO_entrance_window.dat-error-red)]() -## LFOA -[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() +* [![](https://img.shields.io/badge/TER_ELT_mirror_mgf2agal.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_primary_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_secondary_001_syn.dat-error-red)]() +## JWST +[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure -* [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -* [![](https://img.shields.io/badge/TC_filter_Halpha_wide_old.dat-error-red)]() -### Dates -* [![](https://img.shields.io/badge/TER_mirror_aluminium.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_focal_reducer.dat-conflict-orange)]() -## MUSE +* [![](https://img.shields.io/badge/TER_mirror_gold.dat-error-red)]() +## KMOS [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## VLT +## LaPalma [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TC_mirror_aluminium.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/LIST_VLT_mirrors.dat-conflict-orange)]() -## ERIS +* [![](https://img.shields.io/badge/orm_extinct.dat-error-red)]() +## LFOA +[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() +### Structure +* [![](https://img.shields.io/badge/default_yaml-OK-green)]() +* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() +### Contents +* [![](https://img.shields.io/badge/all_yamls_readable-green)]() +* [![](https://img.shields.io/badge/LIST_LFOA_mirrors_static.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_SBIG.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_atmosphere.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_focal_reducer.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mirror_aluminium.dat-error-red)]() +* [![](https://img.shields.io/badge/B.dat-error-red)]() +* [![](https://img.shields.io/badge/Halpha_narrow.dat-error-red)]() +* [![](https://img.shields.io/badge/Halpha_wide.dat-error-red)]() +* [![](https://img.shields.io/badge/Hbeta.dat-error-red)]() +* [![](https://img.shields.io/badge/I.dat-error-red)]() +* [![](https://img.shields.io/badge/OIII.dat-error-red)]() +* [![](https://img.shields.io/badge/R.dat-error-red)]() +* [![](https://img.shields.io/badge/SII.dat-error-red)]() +* [![](https://img.shields.io/badge/sloan_g.dat-error-red)]() +* [![](https://img.shields.io/badge/sloan_i.dat-error-red)]() +* [![](https://img.shields.io/badge/sloan_r.dat-error-red)]() +* [![](https://img.shields.io/badge/sloan_u.dat-error-red)]() +* [![](https://img.shields.io/badge/sloan_z.dat-error-red)]() +* [![](https://img.shields.io/badge/U.dat-error-red)]() +* [![](https://img.shields.io/badge/V.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Halpha_narrow_old.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Halpha_wide_old.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Hbeta_old.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_OIII_old.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_SII_old.dat-error-red)]() +## MCIFU [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## ELT -[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() +## METIS +[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure +* [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/telescope_reflection.filename-missing-red)]() +* [![](https://img.shields.io/badge/TER_ELT_6_mirror_field_track.dat-missing-red)]() +* [![](https://img.shields.io/badge/Leiden_atmo_ter.fits-missing-red)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_ELT_mirror_mgf2agal.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_ELT_5_mirror_clean.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_ELT_mirror_aluminium.dat-conflict-orange)]() -## LaPalma -[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() +* [![](https://img.shields.io/badge/FPA_linearity_GeoSnap_high_capacity.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_linearity_GeoSnap_low_capacity.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_linearity_HxRG.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_metis_img_lm_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_metis_img_nq_aquarius_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_metis_img_n_geosnap_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_metis_lms_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_metis_lms_smpl_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_ifu_apertures.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_METIS_mirrors_cfo.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_METIS_mirrors_img_lm.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_METIS_mirrors_img_n.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_METIS_mirrors_lms.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_METIS_mirrors_wcu.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_A--19_0.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_B--28_6.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_C--38_1.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_D--57_1.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_E--114_2.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_geosnap.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_H2RG_METIS.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_ADC_const_90.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_entrance_window.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_img_dichroic.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_lms_grism_max.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_lms_grism_min.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_lms_predisperser_prism.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mirror_aluminium.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mirror_gold.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sca_dichroic.dat-error-red)]() +* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--L_band.dat-error-red)]() +* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--M_band.dat-error-red)]() +* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--N_band.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Br_alpha.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Br_alpha_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_CO_1--0_ice.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_CO_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H2O--ice.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_HCI_L_long.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_HCI_L_short.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_HCI_M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_IB_4.05.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_L.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Lp.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_L_spec.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Mp.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_M_spec.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_N1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_N2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_N3.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND_OD1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND_OD2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND_OD3.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND_OD4.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND_OD5.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Ne_II.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Ne_II_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_N_spec.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_open.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_11.25.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_11.25_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_3.3.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_3.3_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_8.6.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_PAH_8.6_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Q1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_short--L.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_S_IV.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_S_IV_ref.dat-error-red)]() +* [![](https://img.shields.io/badge/fp_mask_grid_lm.dat-error-red)]() +* [![](https://img.shields.io/badge/fp_mask_pinhole_lm.dat-error-red)]() +* [![](https://img.shields.io/badge/fp_mask_pinhole_n.dat-error-red)]() +## MICADO +[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure +* [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -## MICADO -[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() +* [![](https://img.shields.io/badge/FPA_array_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_linearity.dat-error-red)]() +* [![](https://img.shields.io/badge/INST_MICADO_wavefront_error_budget.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_MICADO_mirrors_spec.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_MICADO_mirrors_static.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_MICADO_mirrors_wide.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_MICADO_mirrors_zoom.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_RO_SCAO_mirrors.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_15000x20.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_3000x16.dat-error-red)]() +* [![](https://img.shields.io/badge/MASK_slit_3000x48.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_H2RG.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_H4RG.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_coating_antireflection.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_entrance_window.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_full_adc.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_grating.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MICADO_mirror_mgf2agal.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mirror_gold.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_SCAO_dichroic.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_blank.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_block.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Br--gamma.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_FeII.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H--cont.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H--long.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H--short.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_H2_1--0S1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_He--I.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_I--long.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_J--long.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_J--short.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_J.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_K--cont.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_K--long.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_K--mid.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_K--short.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Ks.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Ks2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_ND3.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_open.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Pa--beta.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Spec_HK.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Spec_IJ.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_stop_IJH.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_stop_K.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xH1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xH2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xI1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xI2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xJ1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xJ2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xK1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xK2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xY1.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_xY2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_Y.dat-error-red)]() +## MORFEO +[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure -* [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/MASK_slit_3000x50.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_SCAO_dichroic.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_entrance_window.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_mirror_gold.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_MICADO_mirror_mgf2agal.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/FPA_linearity.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/MASK_slit_3000x20.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_ND1.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_stop_K.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_Ks2.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_block.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_open.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_ND3.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_blank.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_stop_IJH.dat-conflict-orange)]() -## ViennaLT +* [![](https://img.shields.io/badge/TER_mirror_silver.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_entrance_window.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_lgs_dichroic.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_mirror_aluminium.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_mirror_gold.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_mirror_mgf2agal.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_MORFEO_mirror_silver.dat-error-red)]() +## MOSAIC [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure * [![](https://img.shields.io/badge/default_yaml-OK-green)]() -* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/TER_atmosphere.dat-missing-red)]() -* [![](https://img.shields.io/badge/QE_SBIG.dat-missing-red)]() +* [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -## VISIR +* [![](https://img.shields.io/badge/FPA_linearity_HxRG.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_mosaic_NIR_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/FPA_mosaic_VIS_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_detector_NIR.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_VIS_ML2_depleted.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_VIS_ML2_standard.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_grating_VIS_LR_B.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mIFU_HR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mIFU_LR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mIFU_LR--J.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mos_HR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mos_LR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_mos_LR--J.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_spec_HR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_spec_LR--H.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_spec_LR--J.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--HR--B1.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--HR--B2.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--HR--R1.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--HR--R2.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--LR--B.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_sys_MOS--LR--R.dat-error-red)]() +## MUSE [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## test_package +## NACO +[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() +### Structure +* [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() +* [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() +### Contents +* [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() +* [![](https://img.shields.io/badge/H_CONICA.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.00.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.03.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.06.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.09.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.12.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.15.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.18.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.21.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.24.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.27.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.30.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.33.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.36.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.39.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.42.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.45.dat-error-red)]() +* [![](https://img.shields.io/badge/IB_2.48.dat-error-red)]() +* [![](https://img.shields.io/badge/J_CONICA.dat-error-red)]() +* [![](https://img.shields.io/badge/Ks_CONICA.dat-error-red)]() +* [![](https://img.shields.io/badge/L_prime.dat-error-red)]() +* [![](https://img.shields.io/badge/M_prime.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.04.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.08.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.09.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.24.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.26.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.28.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.64.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_1.75.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_2.12.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_2.17.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_3.74.dat-error-red)]() +* [![](https://img.shields.io/badge/NB_4.05.dat-error-red)]() +## NIRCam [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure * [![](https://img.shields.io/badge/default_yaml-OK-green)]() @@ -158,8 +415,38 @@ For details on errors and conflicts, see badge report log file in this directory * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TC_filter_Ks.dat-conflict-orange)]() +* [![](https://img.shields.io/badge/DET_LW_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/DET_LW_layout_simple.dat-error-red)]() +* [![](https://img.shields.io/badge/DET_SW_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F250M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F277W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F300M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F322W2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F323N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F335M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F356W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F360M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F405N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F410M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F430M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F444W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F460M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F466N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F470N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F480M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F070W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F090W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F115W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F140M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F150W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F150W2.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F162M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F164N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F182M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F187N.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F200W.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F210M.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_filter_F212N.dat-error-red)]() ## OSIRIS [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure @@ -168,40 +455,33 @@ For details on errors and conflicts, see badge report log file in this directory * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -* [![](https://img.shields.io/badge/TRACE_R500B.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R500R.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R2500R.dat-error-red)]() +* [![](https://img.shields.io/badge/GTC_im_efficiency.dat-error-red)]() +* [![](https://img.shields.io/badge/MAAT_APERTURES.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_OSIRIS_new_detector.dat-error-red)]() +* [![](https://img.shields.io/badge/QE_OSIRIS_old_detector_plus_M3.dat-error-red)]() +* [![](https://img.shields.io/badge/unity.dat-error-red)]() +* [![](https://img.shields.io/badge/OSIRIS_stitchedArc.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R1000B.dat-error-red)]() * [![](https://img.shields.io/badge/TRACE_R1000R.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R300R.dat-error-red)]() * [![](https://img.shields.io/badge/TRACE_R2000B.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R2500I.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R2500R.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R2500U.dat-error-red)]() * [![](https://img.shields.io/badge/TRACE_R2500V.dat-error-red)]() * [![](https://img.shields.io/badge/TRACE_R300B.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R2500U.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R1000B.dat-error-red)]() -* [![](https://img.shields.io/badge/TRACE_R2500I.dat-error-red)]() -### Dates -* [![](https://img.shields.io/badge/QE_OSIRIS_old_detector_plus_M3.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/unity.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/QE_OSIRIS_new_detector.dat-conflict-orange)]() -## METIS -[![](https://img.shields.io/badge/package_type-observation-blueviolet)]() +* [![](https://img.shields.io/badge/TRACE_R300R.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R500B.dat-error-red)]() +* [![](https://img.shields.io/badge/TRACE_R500R.dat-error-red)]() +* [![](https://img.shields.io/badge/fg191b2b.dat-error-red)]() +## Paranal +[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure -* [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--M_band.dat-error-red)]() -* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--L_band.dat-error-red)]() -* [![](https://img.shields.io/badge/2023--06--20--spectra_Grism--N_band.dat-error-red)]() -### Dates -* [![](https://img.shields.io/badge/FPA_metis_img_nq_aquarius_layout.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/FPA_metis_img_n_geosnap_layout.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_img_dichroic.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_mirror_gold.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/FPA_metis_img_lm_layout.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/QE_detector_H2RG_METIS.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/QE_detector_geosnap.dat-conflict-orange)]() -## WFC3 +* [![](https://img.shields.io/badge/TER_paranal_default_NIR_IMG.dat-error-red)]() +## test_package [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure * [![](https://img.shields.io/badge/default_yaml-OK-green)]() @@ -209,110 +489,73 @@ For details on errors and conflicts, see badge report log file in this directory * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/wfc3_ir_win_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F110W.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F127M.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F126N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F139M.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F140W.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F128N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F130N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F098M.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F164N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_dn_002_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F105W.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_fold_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F153M.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_mir1_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_rcp_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F160W.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F132N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_mask_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_mir2_001_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F167N.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_qe_003_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_cor_004_syn.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_filter_F125W.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/wfc3_ir_csm_001_syn.dat-conflict-orange)]() -## Armazones -[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() -### Structure -* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/no_missing_files-green)]() -### Contents -* [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_armazones_default_NIR_IMG.dat-conflict-orange)]() -## FORS +* [![](https://img.shields.io/badge/TC_filter_Ks.dat-error-red)]() +## UVES [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -## HAWKI +## ViennaLT [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure * [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/no_missing_files-green)]() -### Contents -* [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_window.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_mirror_gold.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/FPA_hawki_layout.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/LIST_HAWKI_mirrors.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_NB1190.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_NB1060.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_NB2090.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_H2.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_H.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_J.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_CH4.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_Ks.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_BrGamma.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TC_filter_Y.dat-conflict-orange)]() -## Paranal -[![](https://img.shields.io/badge/package_type-support-deepskyblue)]() -### Structure -* [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/no_missing_files-green)]() +* [![](https://img.shields.io/badge/TER_atmosphere.dat-missing-red)]() +* [![](https://img.shields.io/badge/QE_SBIG.dat-missing-red)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -## NACO +* [![](https://img.shields.io/badge/FPA_ViLT_layout.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_ViLT_mirrors_static.dat-error-red)]() +## VISIR [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-not_found-red)]() * [![](https://img.shields.io/badge/no_files_referenced-yellowgreen)]() ### Contents * [![](https://img.shields.io/badge/no_yaml_files-yellowgreen)]() -* [![](https://img.shields.io/badge/NB_4.05.dat-error-red)]() -* [![](https://img.shields.io/badge/NB_3.74.dat-error-red)]() -### Dates -## GTC +## VLT [![](https://img.shields.io/badge/package_type-support-deepskyblue)]() ### Structure * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() * [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/unity.dat-conflict-orange)]() -## MICADO_Sci +* [![](https://img.shields.io/badge/LIST_VLT_mirrors.dat-error-red)]() +* [![](https://img.shields.io/badge/TC_mirror_aluminium.dat-error-red)]() +## WFC3 [![](https://img.shields.io/badge/package_type-observation-blueviolet)]() ### Structure * [![](https://img.shields.io/badge/default_yaml-OK-green)]() * [![](https://img.shields.io/badge/self_named_yaml-found-green)]() -* [![](https://img.shields.io/badge/MICADO_AnisoCADO_rms_map.fits-missing-red)]() -* [![](https://img.shields.io/badge/TER_armazones_default_NIR_IMG.dat-missing-red)]() -* [![](https://img.shields.io/badge/TER_ELT_5_mirror.dat-missing-red)]() -* [![](https://img.shields.io/badge/QE_detector_H2RG.dat-missing-red)]() -* [![](https://img.shields.io/badge/FPA_linearity.dat-missing-red)]() +* [![](https://img.shields.io/badge/no_missing_files-green)]() ### Contents * [![](https://img.shields.io/badge/all_yamls_readable-green)]() -### Dates -* [![](https://img.shields.io/badge/TER_MICADO_RO.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_MICADO_IMG_common.dat-conflict-orange)]() -* [![](https://img.shields.io/badge/TER_MORFEO_MMS.dat-conflict-orange)]() \ No newline at end of file +* [![](https://img.shields.io/badge/FPA_linearity.dat-error-red)]() +* [![](https://img.shields.io/badge/LIST_WFC3_mirrors_IR.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_cor_004_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_csm_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_dn_002_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_fold_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_mask_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_mir1_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_mir2_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_qe_003_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_rcp_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/wfc3_ir_win_001_syn.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F098M.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F105W.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F110W.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F125W.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F126N.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F127M.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F128N.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F130N.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F132N.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F139M.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F140W.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F153M.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F160W.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F164N.dat-error-red)]() +* [![](https://img.shields.io/badge/TER_filter_F167N.dat-error-red)]() \ No newline at end of file diff --git a/_REPORTS/badges.yaml b/_REPORTS/badges.yaml index 81797ef7..f4cf880d 100644 --- a/_REPORTS/badges.yaml +++ b/_REPORTS/badges.yaml @@ -1,149 +1,408 @@ -HARMONI: +Armazones: package_type: support structure: - self_named_yaml: not found - no_files_referenced: '!NONE' + self_named_yaml: found + no_missing_files: '!OK' contents: - no_yaml_files: '!NONE' -UVES: + all_yamls_readable: '!OK' + TER_armazones_default_FULL_IMG.dat: error + TER_armazones_default_MIR_IMG.dat: error + TER_armazones_default_NIR_IMG.dat: error + TER_armazones_default_OPT_IMG.dat: error +ELT: + package_type: support + structure: + self_named_yaml: found + '#telescope_reflection.filename': missing + contents: + all_yamls_readable: '!OK' + TER_ELT_5_mirror.dat: error + TER_ELT_5_mirror_clean.dat: error + TER_ELT_6_mirror_field_track.dat: error + TER_ELT_6_mirror_field_track_clean.dat: error + TER_ELT_6_mirror_pupil_track.dat: error + TER_ELT_6_mirror_pupil_track_clean.dat: error + TER_ELT_mirror_aluminium.dat: error + TER_ELT_mirror_mgf2agal.dat: error +ERIS: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -KMOS: +FORS: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -HST: +GTC: package_type: support structure: self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - TER_ELT_mirror_mgf2agal.dat: conflict - wfc3_ir_primary_001_syn.dat: conflict - wfc3_ir_secondary_001_syn.dat: conflict -MCIFU: + reflectivity_GTC.dat: error + unity.dat: error +HARMONI: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -MORFEO: +HAWKI: + package_type: observation + structure: + default_yaml: OK + self_named_yaml: found + no_missing_files: '!OK' + contents: + all_yamls_readable: '!OK' + FPA_hawki_layout.dat: error + FPA_linearity.dat: error + LIST_HAWKI_mirrors.dat: error + QE_detector_H2RG.dat: error + TC_dichroic.dat: error + TER_mirror_gold.dat: error + TER_window.dat: error + TC_filter_BrGamma.dat: error + TC_filter_CH4.dat: error + TC_filter_H.dat: error + TC_filter_H2.dat: error + TC_filter_J.dat: error + TC_filter_Ks.dat: error + TC_filter_NB1060.dat: error + TC_filter_NB1190.dat: error + TC_filter_NB2090.dat: error + TC_filter_Y.dat: error + BG_total_BrGamma.dat: error + BG_total_J.dat: error + BG_total_Ks.dat: error + ESO_ETC_bg_fluxes.dat: error + TER_system_BrGamma.dat: error + TER_system_CH4.dat: error + TER_system_H.dat: error + TER_system_J.dat: error + TER_system_Ks.dat: error + TER_system_Y.dat: error +HST: package_type: support structure: self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - TER_MORFEO_mirror_aluminium.dat: conflict - TER_mirror_silver.dat: conflict - TER_MORFEO_mirror_mgf2agal.dat: conflict - TER_MORFEO_entrance_window.dat: error -LFOA: - package_type: observation + TER_ELT_mirror_mgf2agal.dat: error + wfc3_ir_primary_001_syn.dat: error + wfc3_ir_secondary_001_syn.dat: error +JWST: + package_type: support structure: - default_yaml: OK self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - TC_filter_Halpha_wide_old.dat: error - dates: - TER_mirror_aluminium.dat: conflict - TER_focal_reducer.dat: conflict -MUSE: + TER_mirror_gold.dat: error +KMOS: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -VLT: +LaPalma: package_type: support structure: self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - TC_mirror_aluminium.dat: conflict - LIST_VLT_mirrors.dat: conflict -ERIS: + orm_extinct.dat: error +LFOA: + package_type: observation + structure: + default_yaml: OK + self_named_yaml: found + no_missing_files: '!OK' + contents: + all_yamls_readable: '!OK' + LIST_LFOA_mirrors_static.dat: error + QE_SBIG.dat: error + TER_atmosphere.dat: error + TER_focal_reducer.dat: error + TER_mirror_aluminium.dat: error + B.dat: error + Halpha_narrow.dat: error + Halpha_wide.dat: error + Hbeta.dat: error + I.dat: error + OIII.dat: error + R.dat: error + SII.dat: error + sloan_g.dat: error + sloan_i.dat: error + sloan_r.dat: error + sloan_u.dat: error + sloan_z.dat: error + U.dat: error + V.dat: error + TC_filter_Halpha_narrow_old.dat: error + TC_filter_Halpha_wide_old.dat: error + TC_filter_Hbeta_old.dat: error + TC_filter_OIII_old.dat: error + TC_filter_SII_old.dat: error +MCIFU: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -ELT: - package_type: support +METIS: + package_type: observation structure: + default_yaml: OK self_named_yaml: found - '#telescope_reflection.filename': missing + TER_ELT_6_mirror_field_track.dat: missing + Leiden_atmo_ter.fits: missing contents: all_yamls_readable: '!OK' - dates: - TER_ELT_mirror_mgf2agal.dat: conflict - TER_ELT_5_mirror_clean.dat: conflict - TER_ELT_mirror_aluminium.dat: conflict -LaPalma: - package_type: support + FPA_linearity_GeoSnap_high_capacity.dat: error + FPA_linearity_GeoSnap_low_capacity.dat: error + FPA_linearity_HxRG.dat: error + FPA_metis_img_lm_layout.dat: error + FPA_metis_img_nq_aquarius_layout.dat: error + FPA_metis_img_n_geosnap_layout.dat: error + FPA_metis_lms_layout.dat: error + FPA_metis_lms_smpl_layout.dat: error + LIST_ifu_apertures.dat: error + LIST_METIS_mirrors_cfo.dat: error + LIST_METIS_mirrors_img_lm.dat: error + LIST_METIS_mirrors_img_n.dat: error + LIST_METIS_mirrors_lms.dat: error + LIST_METIS_mirrors_wcu.dat: error + MASK_slit_A-19_0.dat: error + MASK_slit_B-28_6.dat: error + MASK_slit_C-38_1.dat: error + MASK_slit_D-57_1.dat: error + MASK_slit_E-114_2.dat: error + QE_detector_geosnap.dat: error + QE_detector_H2RG_METIS.dat: error + TER_ADC_const_90.dat: error + TER_entrance_window.dat: error + TER_img_dichroic.dat: error + TER_lms_grism_max.dat: error + TER_lms_grism_min.dat: error + TER_lms_predisperser_prism.dat: error + TER_mirror_aluminium.dat: error + TER_mirror_gold.dat: error + TER_sca_dichroic.dat: error + 2023-06-20-spectra_Grism-L_band.dat: error + 2023-06-20-spectra_Grism-M_band.dat: error + 2023-06-20-spectra_Grism-N_band.dat: error + TC_filter_Br_alpha.dat: error + TC_filter_Br_alpha_ref.dat: error + TC_filter_CO_1-0_ice.dat: error + TC_filter_CO_ref.dat: error + TC_filter_H2O-ice.dat: error + TC_filter_HCI_L_long.dat: error + TC_filter_HCI_L_short.dat: error + TC_filter_HCI_M.dat: error + TC_filter_IB_4.05.dat: error + TC_filter_L.dat: error + TC_filter_Lp.dat: error + TC_filter_L_spec.dat: error + TC_filter_Mp.dat: error + TC_filter_M_spec.dat: error + TC_filter_N1.dat: error + TC_filter_N2.dat: error + TC_filter_N3.dat: error + TC_filter_ND_OD1.dat: error + TC_filter_ND_OD2.dat: error + TC_filter_ND_OD3.dat: error + TC_filter_ND_OD4.dat: error + TC_filter_ND_OD5.dat: error + TC_filter_Ne_II.dat: error + TC_filter_Ne_II_ref.dat: error + TC_filter_N_spec.dat: error + TC_filter_open.dat: error + TC_filter_PAH_11.25.dat: error + TC_filter_PAH_11.25_ref.dat: error + TC_filter_PAH_3.3.dat: error + TC_filter_PAH_3.3_ref.dat: error + TC_filter_PAH_8.6.dat: error + TC_filter_PAH_8.6_ref.dat: error + TC_filter_Q1.dat: error + TC_filter_short-L.dat: error + TC_filter_S_IV.dat: error + TC_filter_S_IV_ref.dat: error + fp_mask_grid_lm.dat: error + fp_mask_pinhole_lm.dat: error + fp_mask_pinhole_n.dat: error +MICADO: + package_type: observation structure: + default_yaml: OK self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' -MICADO: - package_type: observation + FPA_array_layout.dat: error + FPA_linearity.dat: error + INST_MICADO_wavefront_error_budget.dat: error + LIST_MICADO_mirrors_spec.dat: error + LIST_MICADO_mirrors_static.dat: error + LIST_MICADO_mirrors_wide.dat: error + LIST_MICADO_mirrors_zoom.dat: error + LIST_RO_SCAO_mirrors.dat: error + MASK_slit_15000x20.dat: error + MASK_slit_3000x16.dat: error + MASK_slit_3000x48.dat: error + QE_detector_H2RG.dat: error + QE_detector_H4RG.dat: error + TER_coating_antireflection.dat: error + TER_entrance_window.dat: error + TER_full_adc.dat: error + TER_grating.dat: error + TER_MICADO_mirror_mgf2agal.dat: error + TER_mirror_gold.dat: error + TER_SCAO_dichroic.dat: error + TC_filter_blank.dat: error + TC_filter_block.dat: error + TC_filter_Br-gamma.dat: error + TC_filter_FeII.dat: error + TC_filter_H-cont.dat: error + TC_filter_H-long.dat: error + TC_filter_H-short.dat: error + TC_filter_H.dat: error + TC_filter_H2_1-0S1.dat: error + TC_filter_He-I.dat: error + TC_filter_I-long.dat: error + TC_filter_J-long.dat: error + TC_filter_J-short.dat: error + TC_filter_J.dat: error + TC_filter_K-cont.dat: error + TC_filter_K-long.dat: error + TC_filter_K-mid.dat: error + TC_filter_K-short.dat: error + TC_filter_Ks.dat: error + TC_filter_Ks2.dat: error + TC_filter_ND1.dat: error + TC_filter_ND3.dat: error + TC_filter_open.dat: error + TC_filter_Pa-beta.dat: error + TC_filter_Spec_HK.dat: error + TC_filter_Spec_IJ.dat: error + TC_filter_stop_IJH.dat: error + TC_filter_stop_K.dat: error + TC_filter_xH1.dat: error + TC_filter_xH2.dat: error + TC_filter_xI1.dat: error + TC_filter_xI2.dat: error + TC_filter_xJ1.dat: error + TC_filter_xJ2.dat: error + TC_filter_xK1.dat: error + TC_filter_xK2.dat: error + TC_filter_xY1.dat: error + TC_filter_xY2.dat: error + TC_filter_Y.dat: error +MORFEO: + package_type: support structure: - default_yaml: OK self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - MASK_slit_3000x50.dat: conflict - TER_SCAO_dichroic.dat: conflict - TER_entrance_window.dat: conflict - TER_mirror_gold.dat: conflict - TER_MICADO_mirror_mgf2agal.dat: conflict - FPA_linearity.dat: conflict - MASK_slit_3000x20.dat: conflict - TC_filter_ND1.dat: conflict - TC_filter_stop_K.dat: conflict - TC_filter_Ks2.dat: conflict - TC_filter_block.dat: conflict - TC_filter_open.dat: conflict - TC_filter_ND3.dat: conflict - TC_filter_blank.dat: conflict - TC_filter_stop_IJH.dat: conflict -ViennaLT: + TER_mirror_silver.dat: error + TER_MORFEO_entrance_window.dat: error + TER_MORFEO_lgs_dichroic.dat: error + TER_MORFEO_mirror_aluminium.dat: error + TER_MORFEO_mirror_gold.dat: error + TER_MORFEO_mirror_mgf2agal.dat: error + TER_MORFEO_mirror_silver.dat: error +MOSAIC: package_type: observation structure: default_yaml: OK - self_named_yaml: found - TER_atmosphere.dat: missing - QE_SBIG.dat: missing + self_named_yaml: not found + no_missing_files: '!OK' contents: all_yamls_readable: '!OK' -VISIR: + FPA_linearity_HxRG.dat: error + FPA_mosaic_NIR_layout.dat: error + FPA_mosaic_VIS_layout.dat: error + QE_detector_NIR.dat: error + QE_VIS_ML2_depleted.dat: error + QE_VIS_ML2_standard.dat: error + TER_grating_VIS_LR_B.dat: error + TER_mIFU_HR-H.dat: error + TER_mIFU_LR-H.dat: error + TER_mIFU_LR-J.dat: error + TER_mos_HR-H.dat: error + TER_mos_LR-H.dat: error + TER_mos_LR-J.dat: error + TER_spec_HR-H.dat: error + TER_spec_LR-H.dat: error + TER_spec_LR-J.dat: error + TER_sys_MOS-HR-B1.dat: error + TER_sys_MOS-HR-B2.dat: error + TER_sys_MOS-HR-R1.dat: error + TER_sys_MOS-HR-R2.dat: error + TER_sys_MOS-LR-B.dat: error + TER_sys_MOS-LR-R.dat: error +MUSE: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -test_package: +NACO: + package_type: support + structure: + self_named_yaml: not found + no_files_referenced: '!NONE' + contents: + no_yaml_files: '!NONE' + H_CONICA.dat: error + IB_2.00.dat: error + IB_2.03.dat: error + IB_2.06.dat: error + IB_2.09.dat: error + IB_2.12.dat: error + IB_2.15.dat: error + IB_2.18.dat: error + IB_2.21.dat: error + IB_2.24.dat: error + IB_2.27.dat: error + IB_2.30.dat: error + IB_2.33.dat: error + IB_2.36.dat: error + IB_2.39.dat: error + IB_2.42.dat: error + IB_2.45.dat: error + IB_2.48.dat: error + J_CONICA.dat: error + Ks_CONICA.dat: error + L_prime.dat: error + M_prime.dat: error + NB_1.04.dat: error + NB_1.08.dat: error + NB_1.09.dat: error + NB_1.24.dat: error + NB_1.26.dat: error + NB_1.28.dat: error + NB_1.64.dat: error + NB_1.75.dat: error + NB_2.12.dat: error + NB_2.17.dat: error + NB_3.74.dat: error + NB_4.05.dat: error +NIRCam: package_type: observation structure: default_yaml: OK @@ -151,8 +410,38 @@ test_package: no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - TC_filter_Ks.dat: conflict + DET_LW_layout.dat: error + DET_LW_layout_simple.dat: error + DET_SW_layout.dat: error + TC_filter_F250M.dat: error + TC_filter_F277W.dat: error + TC_filter_F300M.dat: error + TC_filter_F322W2.dat: error + TC_filter_F323N.dat: error + TC_filter_F335M.dat: error + TC_filter_F356W.dat: error + TC_filter_F360M.dat: error + TC_filter_F405N.dat: error + TC_filter_F410M.dat: error + TC_filter_F430M.dat: error + TC_filter_F444W.dat: error + TC_filter_F460M.dat: error + TC_filter_F466N.dat: error + TC_filter_F470N.dat: error + TC_filter_F480M.dat: error + TC_filter_F070W.dat: error + TC_filter_F090W.dat: error + TC_filter_F115W.dat: error + TC_filter_F140M.dat: error + TC_filter_F150W.dat: error + TC_filter_F150W2.dat: error + TC_filter_F162M.dat: error + TC_filter_F164N.dat: error + TC_filter_F182M.dat: error + TC_filter_F187N.dat: error + TC_filter_F200W.dat: error + TC_filter_F210M.dat: error + TC_filter_F212N.dat: error OSIRIS: package_type: observation structure: @@ -161,40 +450,33 @@ OSIRIS: no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - TRACE_R500B.dat: error - TRACE_R500R.dat: error - TRACE_R2500R.dat: error + GTC_im_efficiency.dat: error + MAAT_APERTURES.dat: error + QE_OSIRIS_new_detector.dat: error + QE_OSIRIS_old_detector_plus_M3.dat: error + unity.dat: error + OSIRIS_stitchedArc.dat: error + TRACE_R1000B.dat: error TRACE_R1000R.dat: error - TRACE_R300R.dat: error TRACE_R2000B.dat: error + TRACE_R2500I.dat: error + TRACE_R2500R.dat: error + TRACE_R2500U.dat: error TRACE_R2500V.dat: error TRACE_R300B.dat: error - TRACE_R2500U.dat: error - TRACE_R1000B.dat: error - TRACE_R2500I.dat: error - dates: - QE_OSIRIS_old_detector_plus_M3.dat: conflict - unity.dat: conflict - QE_OSIRIS_new_detector.dat: conflict -METIS: - package_type: observation + TRACE_R300R.dat: error + TRACE_R500B.dat: error + TRACE_R500R.dat: error + fg191b2b.dat: error +Paranal: + package_type: support structure: - default_yaml: OK self_named_yaml: found + no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - 2023-06-20-spectra_Grism-M_band.dat: error - 2023-06-20-spectra_Grism-L_band.dat: error - 2023-06-20-spectra_Grism-N_band.dat: error - dates: - FPA_metis_img_nq_aquarius_layout.dat: conflict - FPA_metis_img_n_geosnap_layout.dat: conflict - TER_img_dichroic.dat: conflict - TER_mirror_gold.dat: conflict - FPA_metis_img_lm_layout.dat: conflict - QE_detector_H2RG_METIS.dat: conflict - QE_detector_geosnap.dat: conflict -WFC3: + TER_paranal_default_NIR_IMG.dat: error +test_package: package_type: observation structure: default_yaml: OK @@ -202,110 +484,73 @@ WFC3: no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - wfc3_ir_win_001_syn.dat: conflict - TER_filter_F110W.dat: conflict - TER_filter_F127M.dat: conflict - TER_filter_F126N.dat: conflict - TER_filter_F139M.dat: conflict - TER_filter_F140W.dat: conflict - TER_filter_F128N.dat: conflict - TER_filter_F130N.dat: conflict - TER_filter_F098M.dat: conflict - TER_filter_F164N.dat: conflict - wfc3_ir_dn_002_syn.dat: conflict - TER_filter_F105W.dat: conflict - wfc3_ir_fold_001_syn.dat: conflict - TER_filter_F153M.dat: conflict - wfc3_ir_mir1_001_syn.dat: conflict - wfc3_ir_rcp_001_syn.dat: conflict - TER_filter_F160W.dat: conflict - TER_filter_F132N.dat: conflict - wfc3_ir_mask_001_syn.dat: conflict - wfc3_ir_mir2_001_syn.dat: conflict - TER_filter_F167N.dat: conflict - wfc3_ir_qe_003_syn.dat: conflict - wfc3_ir_cor_004_syn.dat: conflict - TER_filter_F125W.dat: conflict - wfc3_ir_csm_001_syn.dat: conflict -Armazones: - package_type: support - structure: - self_named_yaml: found - no_missing_files: '!OK' - contents: - all_yamls_readable: '!OK' - dates: - TER_armazones_default_NIR_IMG.dat: conflict -FORS: + TC_filter_Ks.dat: error +UVES: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' -HAWKI: +ViennaLT: package_type: observation structure: default_yaml: OK self_named_yaml: found - no_missing_files: '!OK' - contents: - all_yamls_readable: '!OK' - dates: - TER_window.dat: conflict - TER_mirror_gold.dat: conflict - FPA_hawki_layout.dat: conflict - LIST_HAWKI_mirrors.dat: conflict - TC_filter_NB1190.dat: conflict - TC_filter_NB1060.dat: conflict - TC_filter_NB2090.dat: conflict - TC_filter_H2.dat: conflict - TC_filter_H.dat: conflict - TC_filter_J.dat: conflict - TC_filter_CH4.dat: conflict - TC_filter_Ks.dat: conflict - TC_filter_BrGamma.dat: conflict - TC_filter_Y.dat: conflict -Paranal: - package_type: support - structure: - self_named_yaml: found - no_missing_files: '!OK' + TER_atmosphere.dat: missing + QE_SBIG.dat: missing contents: all_yamls_readable: '!OK' -NACO: + FPA_ViLT_layout.dat: error + LIST_ViLT_mirrors_static.dat: error +VISIR: package_type: support structure: self_named_yaml: not found no_files_referenced: '!NONE' contents: no_yaml_files: '!NONE' - NB_4.05.dat: error - NB_3.74.dat: error - dates: {} -GTC: +VLT: package_type: support structure: self_named_yaml: found no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - unity.dat: conflict -MICADO_Sci: + LIST_VLT_mirrors.dat: error + TC_mirror_aluminium.dat: error +WFC3: package_type: observation structure: default_yaml: OK self_named_yaml: found - MICADO_AnisoCADO_rms_map.fits: missing - TER_armazones_default_NIR_IMG.dat: missing - TER_ELT_5_mirror.dat: missing - QE_detector_H2RG.dat: missing - FPA_linearity.dat: missing + no_missing_files: '!OK' contents: all_yamls_readable: '!OK' - dates: - TER_MICADO_RO.dat: conflict - TER_MICADO_IMG_common.dat: conflict - TER_MORFEO_MMS.dat: conflict + FPA_linearity.dat: error + LIST_WFC3_mirrors_IR.dat: error + wfc3_ir_cor_004_syn.dat: error + wfc3_ir_csm_001_syn.dat: error + wfc3_ir_dn_002_syn.dat: error + wfc3_ir_fold_001_syn.dat: error + wfc3_ir_mask_001_syn.dat: error + wfc3_ir_mir1_001_syn.dat: error + wfc3_ir_mir2_001_syn.dat: error + wfc3_ir_qe_003_syn.dat: error + wfc3_ir_rcp_001_syn.dat: error + wfc3_ir_win_001_syn.dat: error + TER_filter_F098M.dat: error + TER_filter_F105W.dat: error + TER_filter_F110W.dat: error + TER_filter_F125W.dat: error + TER_filter_F126N.dat: error + TER_filter_F127M.dat: error + TER_filter_F128N.dat: error + TER_filter_F130N.dat: error + TER_filter_F132N.dat: error + TER_filter_F139M.dat: error + TER_filter_F140W.dat: error + TER_filter_F153M.dat: error + TER_filter_F160W.dat: error + TER_filter_F164N.dat: error + TER_filter_F167N.dat: error diff --git a/conf.py b/conf.py index f7be7a0a..51292183 100644 --- a/conf.py +++ b/conf.py @@ -1,267 +1,91 @@ -""" -Configuration file for Sphinx and ReadTheDocs - -This file originally lived in docs/source. -It has been moved into the top level so that all package docs are accessible to -sphinx -""" - - -#!/usr/bin/env python3 # -*- coding: utf-8 -*- -# -# Instrument Reference Database documentation build configuration file, created by -# sphinx-quickstart on Fri Jul 12 13:46:11 2019. -# -# This file is execfile()d with the current directory set to its -# containing dir. -# -# Note that not all possible configuration values are present in this -# autogenerated file. -# -# All configuration values have a default; values that are commented out -# serve to show the default. - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -# -# sys.path.insert(0, os.path.abspath('.')) +"""Sphinx configuration for the Instrument Reference Database.""" -import sys import os +import sys from pathlib import Path -sys.path.insert(0, os.path.abspath('/')) -sys.path.insert(0, os.path.abspath('docs')) +sys.path.insert(0, os.path.abspath(".")) +sys.path.insert(0, os.path.abspath("docs")) -# -- General configuration ------------------------------------------------ +project = "Instrument Reference Database" +copyright = "2024, A* Vienna Software Team" +author = "A* Vienna Software Team" -# If your documentation needs a minimal Sphinx version, state it here. -# -# needs_sphinx = '1.0' - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. extensions = [ - 'nbsphinx', - 'sphinx.ext.intersphinx', - 'sphinx.ext.todo', - 'sphinx.ext.coverage', - 'sphinx.ext.mathjax', - 'sphinx.ext.viewcode', - # 'matplotlib.sphinxext.plot_directive', - # 'numpydoc', - # 'sphinx.ext.autodoc', - # 'jupyter_sphinx.execute', - # 'sphinxcontrib.apidoc', + "sphinx.ext.todo", + "sphinx.ext.intersphinx", + "sphinx.ext.mathjax", + "sphinx.ext.napoleon", + "sphinx_copybutton", + "myst_nb", + "sphinx_design", + "docs.source._ext.validation_report", ] -# numpydoc settings -numpydoc_show_class_members = False +myst_enable_extensions = ["colon_fence"] +todo_include_todos = True + +napoleon_numpy_docstring = True +napoleon_use_admonition_for_references = True -# apidoc settings -# apidoc_module_dir = os.path.abspath('irdb/') -# apidoc_output_dir = 'docs/source/reference' -# apidoc_separate_modules = True -# apidoc_excluded_paths = ["tests/", "docs/"] +source_encoding = "utf-8" +source_suffix = { + ".rst": "restructuredtext", + ".myst": "myst-nb", + ".md": "myst-nb", + ".ipynb": "myst-nb", +} -# nbsphinx settings -nbsphinx_allow_errors = True -nbsphinx_execute = "never" +nb_execution_mode = "off" -# add_hidden_cell_to_ipynb_files() +master_doc = "index" -def add_hidden_cell_to_ipynb_files(): - import glob - old_string = '''"cells": [''' - new_string = '''"cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { "nbsphinx": "hidden" }, - "outputs": [], - "source": [ - "import os, scopesim as sim", - "if os.environ.get(\"READTHEDOCS\") == \"True\" or \"F:\" in os.getcwd():", - " sim.rc.__config__[\"!SIM.file.local_packages_path\"] = os.path.abspath(\"../../../\")", - ] - },''' - paths = glob.glob("./**/*.ipynb", recursive=True) - for path in paths: - with open(path, "r+") as f: - contents = f.read() - # check if the hidden cell has already been added to notebook - if 'os.environ.get("READTHEDOCS")' not in contents: - contents = contents.replace(old_string, new_string) - f.seek(0) - f.write(contents) +exclude_patterns = [ + "_build", + "docs/ScopeSim_guide.md", # shared include file, not a standalone page +] +intersphinx_mapping = { + "python": ("https://docs.python.org/3/", None), + "numpy": ("https://numpy.org/doc/stable/", None), + "scipy": ("https://docs.scipy.org/doc/scipy/", None), + "matplotlib": ("https://matplotlib.org/stable/", None), + "astropy": ("https://docs.astropy.org/en/stable/", None), + "synphot": ("https://synphot.readthedocs.io/en/latest/", None), + "scopesim": ("https://scopesim.readthedocs.io/en/latest/", None), + "scopesim_templates": ("https://scopesim-templates.readthedocs.io/en/latest/", None), + "pyckles": ("https://pyckles.readthedocs.io/en/latest/", None), + "anisocado": ("https://anisocado.readthedocs.io/en/latest/", None), +} -# add_hidden_cell_to_ipynb_files() +html_theme = "sphinx_book_theme" +html_theme_options = { + "repository_url": "https://github.com/AstarVienna/irdb", + "use_repository_button": True, + "use_download_button": True, + "home_page_in_toc": True, +} +html_logo = "docs/source/_static/logos/T_favicon.png" +html_favicon = "docs/source/_static/logos/T_favicon.png" +html_sidebars = { + "**": [ + "navbar-logo.html", + "search-field.html", + "sbt-sidebar-nav.html", + ] +} + +html_static_path = ["docs/source/_static"] +html_css_files = ["validation_report.css"] +html_js_files = ["clickable_rows.js"] def remove_inst_pkgs_symlink(): """Remove inst_pkgs symlinks.""" - for path in list(Path(".").rglob('inst_pkgs')): + for path in list(Path(".").rglob("inst_pkgs")): if path.is_symlink(): path.unlink() remove_inst_pkgs_symlink() - -# Matplotlib plot directive config parameters -plot_html_show_source_link = False - -# Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] - -# The suffix(es) of source filenames. -# You can specify multiple suffix as a list of string: -# -# source_suffix = ['.rst', '.md'] -source_suffix = '.rst' - -# The master toctree document. -master_doc = 'index' - -# General information about the project. -project = 'Instrument Reference Database' -copyright = '2019, A*Vienna Software Team' -author = 'Kieran Leschinski, Oliver Czoske' - -# The version info for the project you're documenting, acts as replacement for -# |version| and |release|, also used in various other places throughout the -# built documents. -# -# The short X.Y version. -version = '0' -# The full version, including alpha/beta/rc tags. -release = '1' - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -# -# This is also used if you do content translation via gettext catalogs. -# Usually you set "language" from the command line for these cases. -language = None - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -# This patterns also effect to html_static_path and html_extra_path -exclude_patterns = [] - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = 'sphinx' - - -# -- Options for HTML output ---------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -# -# html_theme = 'alabaster' - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -# -html_theme_options = {"body_max_width": "900px"} - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['docs/source/_static'] # 'METIS/docs/example_notebooks' -html_favicon = 'docs/source/_static/logos/T_favicon.png' - - -# Custom sidebar templates, must be a dictionary that maps document names -# to template names. -# -# This is required for the alabaster theme -# refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars -# html_sidebars = { -# '**': [ -# 'relations.html', # needs 'show_related': True theme option to display -# 'searchbox.html', -# ] -# } - - -# -- Options for HTMLHelp output ------------------------------------------ - -# Output file base name for HTML help builder. -htmlhelp_basename = 'IRDB' - - -# -- Options for LaTeX output --------------------------------------------- - -latex_elements = { - # The paper size ('letterpaper' or 'a4paper'). - # - # 'papersize': 'letterpaper', - - # The font size ('10pt', '11pt' or '12pt'). - # - # 'pointsize': '10pt', - - # Additional stuff for the LaTeX preamble. - # - # 'preamble': '', - - # Latex figure (float) alignment - # - # 'figure_align': 'htbp', -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, -# author, documentclass [howto, manual, or own class]). -latex_documents = [ - (master_doc, 'InstrumentReferenceDatabase.tex', 'Instrument Reference Database Documentation', - 'Kieran Leschinski, Oliver Czoske', 'manual'), -] - - -# -- Options for manual page output --------------------------------------- - -# One entry per manual page. List of tuples -# (source start file, name, description, authors, manual section). -man_pages = [ - (master_doc, 'InstrumentReferenceDatabase', 'Instrument Reference Database Documentation', - [author], 1) -] - - -# -- Options for Texinfo output ------------------------------------------- - -# Grouping the document tree into Texinfo files. List of tuples -# (source start file, target name, title, author, -# dir menu entry, description, category) -texinfo_documents = [ - (master_doc, 'InstrumentReferenceDatabase', 'Instrument Reference Database Documentation', - author, 'InstrumentReferenceDatabase', 'One line description of project.', - 'Miscellaneous'), -] - - - - -# Example configuration for intersphinx: refer to the Python standard library. -intersphinx_mapping = {'python': ('http://docs.python.org/', None), - 'numpy': ('http://docs.scipy.org/doc/numpy/', None), - 'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None), - 'matplotlib': ('http://matplotlib.org/', None), - 'astropy': ('http://docs.astropy.org/en/stable/', None), - 'synphot': ('https://synphot.readthedocs.io/en/latest/', None), - 'scopesim_templates': ('https://scopesim_templates.readthedocs.io/en/latest/', None), - 'pyckles': ('https://pyckles.readthedocs.io/en/latest/', None), - 'anisocado': ('https://anisocado.readthedocs.io/en/latest/', None), - } - - -# -- Options for todo extension ---------------------------------------------- - -# If true, `todo` and `todoList` produce output, else they produce nothing. -todo_include_todos = True diff --git a/docs/ScopeSim_guide.md b/docs/ScopeSim_guide.md new file mode 100644 index 00000000..9eb81bc7 --- /dev/null +++ b/docs/ScopeSim_guide.md @@ -0,0 +1,55 @@ +## Prerequisites + +- A working installation of Python 3.8 or newer +- `pip` (the Python package installer) +- Jupyter, if you want to run the example notebooks (recommended) + +## Installing ScopeSim + +Install the latest release from PyPI: + +```bash +pip install scopesim +``` + +To upgrade an existing installation: + +```bash +pip install -U scopesim +``` + +## Setting up a working directory + +Create a dedicated directory where your simulation notebooks will live and +where the instrument packages will be downloaded: + +```bash +mkdir ~/path/to/my_simulations +cd ~/path/to/my_simulations +``` + +## Running the example notebooks + +The instrument package ships tutorial notebooks inside +`inst_pkgs//docs/example_notebooks/`. +Copy the desired notebook out of that folder before running it — notebooks +should **not** be run in-place, as their output would modify the package files. + +```bash +cp ./inst_pkgs//docs/example_notebooks/ . +jupyter notebook +``` + +## Documentation and useful references + +- [ScopeSim documentation](https://scopesim.readthedocs.io/en/latest/) +- [ScopeSim Templates documentation](https://scopesim-templates.readthedocs.io/en/latest/) +- GitHub repositories: + - [ScopeSim (simulator engine)](https://github.com/AstarVienna/scopesim) + - [IRDB (instrument packages)](https://github.com/AstarVienna/irdb) + +## Contact and support + +- [ScopeSim Slack](https://join.slack.com/t/scopesim/shared_invite/zt-143s42izo-LnyqoG7gH5j~aGn51Z~4IA) +- [GitHub Issues](https://github.com/AstarVienna/irdb/issues) +- Email: scopesim@univie.ac.at · kieran.leschinski@univie.ac.at diff --git a/docs/code/generate_rst_pipeline.py b/docs/code/generate_rst_pipeline.py index fe8491aa..130ff4e3 100644 --- a/docs/code/generate_rst_pipeline.py +++ b/docs/code/generate_rst_pipeline.py @@ -66,25 +66,4 @@ def make_micado_rst_files(): summary_effects(opt_man, filename="pipe_summary.rst") -def make_micado_sci_rst_files(): - all_modes = ["SCAO", "MCAO", "IMG_1.5mas", "IMG_4mas", "SPEC"] - - cmd = sim.UserCommands(use_instrument="MICADO_Sci", set_modes=all_modes) - rc.__currsys__ = cmd - - opt_els = [] - for yaml in cmd.yaml_dicts: - if yaml["alias"] in ["INST", "DET"]: - opt_el = sim.optics.OpticalElement(yaml_dict=yaml) - opt_els += [opt_el] - fname = pth.join(rc.__config__["!SIM.reports.rst_path"], - "sci_{}.rst".format(opt_el.meta["name"])) - opt_el.report(filename=fname) - - opt_man = sim.optics.OpticsManager(None) - opt_man.optical_elements = opt_els - summary_effects(opt_man, filename="sci_summary.rst") - - make_micado_rst_files() -# make_micado_sci_rst_files() diff --git a/MICADO_Sci/__init__.py b/docs/source/_ext/__init__.py similarity index 100% rename from MICADO_Sci/__init__.py rename to docs/source/_ext/__init__.py diff --git a/docs/source/_ext/validation_report.py b/docs/source/_ext/validation_report.py new file mode 100644 index 00000000..0b7fb8cf --- /dev/null +++ b/docs/source/_ext/validation_report.py @@ -0,0 +1,185 @@ +# -*- coding: utf-8 -*- +"""Custom extension to parse pytest report on validation tests.""" + +from pathlib import Path +import xml.etree.ElementTree as ET + +from docutils import nodes +from docutils.parsers.rst import Directive + + +class ValidationReport: + """XML Parser for Validation Report from Pytest.""" + + def __init__(self, xml_path): + tree = ET.parse(Path(xml_path)) + root = tree.getroot() + self.suite = root.find("testsuite") # only one suit per file supported + self.name = self.suite.get("name", "N/A") + self.summary = self._parse_testsuite() + + def __str__(self) -> str: + """Return str(self).""" + return f"Validation Report for {self.name}" + + def iter_testcases(self): + """Iterate over all testcase instances.""" + for testcase in self.suite.findall("testcase"): + yield self._parse_testcase(testcase) + + def _parse_testsuite(self): + summary = { + "errors": int(self.suite.get("errors", -1)), + "failures": int(self.suite.get("failures", -1)), + "skipped": int(self.suite.get("skipped", -1)), + "tests": int(self.suite.get("tests", -1)), + "time": float(self.suite.get("time", -1.)), # [s] + } + return summary + + def _parse_testcase(self, testcase): + data = { + "classname": self._parse_classname(testcase), + "name": testcase.get("name", "N/A"), + "time": float(testcase.get("time", -1.)), + "status": "passed", + "properties": {}, + "message": "", # available for skipped and failed tests and errors + "text": "", # available for failed tests and errors + } + + if (error := testcase.find("error")) is not None: + data["status"] = "error" + data["message"] = error.get("message") + data["text"] = error.text + elif (failure := testcase.find("failure")) is not None: + data["status"] = "failed" + data["message"] = failure.get("message") + data["text"] = failure.text + elif (skipped := testcase.find("skipped")) is not None: + status = skipped.get("type").removeprefix("pytest.") + status = status + "ped" if status == "skip" else status + "ed" + data["status"] = status + data["message"] = skipped.get("message") + # Note: xfail is a type of skip, Xpass looks identical to pass in xml + + if props := testcase.find("properties"): + for prop in props.findall("property"): + data["properties"][prop.get("name")] = prop.get("value") + + return data + + def _parse_classname(self, testcase) -> str: + if (classname := testcase.get("classname")) is None: + return "N/A" + return classname.removeprefix(f"{self.name}.").removeprefix("tests.") + + +class ValidationReportDirective(Directive): + required_arguments = 1 # path to xml + + headers = { + "AO mode": None, + "IMG mode": None, + "Filter": None, + "Expected": "mag", + "Obtained": "mag", + "Difference": "mag", + "Status": None, + } + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.report = ValidationReport(self.arguments[0]) + + def run(self): + summary = nodes.paragraph(text=( + f"Showing results from {self.report.summary['tests']} " + f"tests for {self.report.name}" + )) + + table = nodes.table() + tgroup = nodes.tgroup(cols=len(self.headers)) + table += tgroup + + for _ in self.headers: + tgroup += nodes.colspec(colwidth=1) + + thead = nodes.thead() + tgroup += thead + header_row = nodes.row() + for header, unit in self.headers.items(): + entry = nodes.entry() + entry += nodes.Text(header) + if unit is not None: + self._add_raw_html(entry, "
") + entry += nodes.Text(f"[{unit}]") + header_row += entry + thead += header_row + + tbody = nodes.tbody() + tgroup += tbody + tbody.extend(list(self._collect_rows())) + + footnote = nodes.paragraph(text=( + "Difference is calculated as obtained - expected, meaning a " + "positive difference indicates ScopeSim reached a fainter limiting " + "magnitude than the reference document, while a negative difference" + " means ScopeSim did not reach the reference magnitude in that " + "combination of modes and filter." + )) + + return [summary, table, footnote] + + def _collect_rows(self): + for testcase in self.report.iter_testcases(): + row = nodes.row(classes=[f"pytest-{testcase['status']}"]) + self._add_properties_to_row(row, testcase) + + entry = nodes.entry() + if (url := testcase["properties"].get("link")) is not None: + row["classes"].append("clickable-row") + href_html = ( + "{testcase['status']}" + ) + self._add_raw_html(entry, href_html) + else: + entry += nodes.Text(testcase["status"]) + row += entry + + yield row + + def _add_properties_to_row(self, row, testcase) -> None: + if not testcase["properties"]: + return # skip + self._add_cell_from_properties(row, testcase, "ao_mode") + self._add_cell_from_properties(row, testcase, "img_mode") + self._add_cell_from_properties(row, testcase, "filter") + + entry = nodes.entry(classes=["nowrap"]) + self._add_text_from_properties(entry, testcase, "expected") + self._add_raw_html(entry, " ± ") + self._add_text_from_properties(entry, testcase, "tolerance") + row += entry + + self._add_cell_from_properties(row, testcase, "obtained") + self._add_cell_from_properties(row, testcase, "difference") + + def _add_cell_from_properties(self, row, testcase, key: str) -> None: + entry = nodes.entry(classes=["nowrap"]) + self._add_text_from_properties(entry, testcase, key) + row += entry + + @staticmethod + def _add_text_from_properties(entry, testcase, key: str) -> None: + entry += nodes.Text(testcase["properties"].get(key, "")) + + @staticmethod + def _add_raw_html(entry, html: str) -> None: + entry += nodes.raw("", html, format="html") + + +def setup(app): + app.add_directive("validation-report", ValidationReportDirective) diff --git a/docs/source/_static/clickable_rows.js b/docs/source/_static/clickable_rows.js new file mode 100644 index 00000000..032cae2b --- /dev/null +++ b/docs/source/_static/clickable_rows.js @@ -0,0 +1,17 @@ +document.addEventListener("DOMContentLoaded", function () { + document.querySelectorAll("tr.clickable-row").forEach(function(row) { + row.addEventListener("click", function(e) { + if (e.target.closest("a")) return; + + const link = this.querySelector("a[href]"); + if (!link) return; + + // Respect modifier keys + if (e.metaKey || e.ctrlKey) { + window.open(link.href, "_blank", "noopener"); + } else { + link.click(); + } + }); + }); +}); diff --git a/docs/source/_static/validation_report.css b/docs/source/_static/validation_report.css new file mode 100644 index 00000000..94c987dd --- /dev/null +++ b/docs/source/_static/validation_report.css @@ -0,0 +1,41 @@ +/* Light row backgrounds */ + +tr.pytest-passed { + background-color: #e8f5e9; /* light green */ +} + +tr.pytest-failed { + background-color: #fdecea; /* light red */ +} + +tr.pytest-xfailed { + background-color: #fff8e1; /* light yellow */ +} + +tr.pytest-skipped { + background-color: #aaaaaa; /* light gray */ +} + + + +/* Link on rows */ + +.clickable-row { + cursor: pointer; + transition: background-color 0.15s ease; +} + +.clickable-row:hover { + background-color: #f0f4ff; +} + +.clickable-row a { + color: inherit; + text-decoration: none; +} + +/* Misc */ + +.nowrap { + white-space: nowrap; +} diff --git a/index.md b/index.md new file mode 100644 index 00000000..92761aa9 --- /dev/null +++ b/index.md @@ -0,0 +1,77 @@ +--- +html_theme.sidebar_secondary.remove: true +--- + +```{image} docs/source/_static/logos/logo_irdb.PNG +:width: 600px +:alt: Instrument Reference Database +:align: center +``` + +# Instrument Reference Database + +The **Instrument Reference Database (IRDB)** contains the instrument-specific +configuration and data files used by the +[ScopeSim](https://scopesim.readthedocs.io/en/latest/) astronomical instrument +simulator. + +Each instrument package below ships with example notebooks, mode configuration +files, and the component data (filters, PSFs, detector layouts, etc.) needed to +run realistic end-to-end simulations. + +## Available Instruments + +::::{grid} 1 2 3 3 +:gutter: 3 + +:::{grid-item-card} MICADO +:img-top: MICADO/docs/micado_scopesim_logo.png +:link: MICADO/docs/README +:link-type: doc + +**Near-infrared camera for the ELT** + +Supports MCAO (4 mas) and SCAO (1.5 mas / 4 mas) imaging modes. +::: + +:::{grid-item-card} METIS +:img-top: METIS/docs/metis_scopesim_logo.png +:link: METIS/docs/README +:link-type: doc + +**Thermal-infrared imager and spectrograph for the ELT** + +Supports imaging and long-slit spectroscopy. LMS IFU mode in development. +::: + +:::{grid-item-card} MOSAIC +:img-top: MOSAIC/docs/mosaic_scopesim_logo.png +:link: MOSAIC/docs/README +:link-type: doc + +**Multi-object spectrograph for the ELT** + +12 observation modes across VIS/NIR MOS and NIR mIFU. +::: + +:::: + +## All Instrument Packages + +| Location | Telescope | Instrument | Documented | +|-----------|-----------|------------------------------|------------| +| Armazones | ELT | [MICADO](MICADO/docs/README) | ✓ | +| Armazones | ELT | [METIS](METIS/docs/README) | ✓ | +| Armazones | ELT | [MOSAIC](MOSAIC/docs/README) | ✓ | +| Paranal | VLT | HAWKI | | +| LFOA | - | - | | + +```{toctree} +:hidden: +:maxdepth: 2 +:caption: Instruments + +METIS + ScopeSim +MICADO + ScopeSim +MOSAIC + ScopeSim +``` diff --git a/index.rst b/index.rst deleted file mode 100644 index 0fcf2e17..00000000 --- a/index.rst +++ /dev/null @@ -1,43 +0,0 @@ -.. ReadTheDocs index file. Originally from docs/source/index.rst - Moved here so that all package docs are accessible to Sphinx and RTD - -.. image:: docs/source/_static/logos/logo_irdb.PNG - :width: 600 px - :alt: Welcome to the ScopeSim Documentation! - :align: center - - -The Instrument Reference Database (IRDB) contains the instrument specific -information used by the ScopeSim astronomical instrument data simulator. - -Instrument-Specific "Getting Started" Guides --------------------------------------------- - -.. toctree:: - :maxdepth: 2 - :caption: Contents: - - METIS + ScopeSim - MICADO + ScopeSim - MOSAIC + ScopeSim - - -Instrument Packages in the IRDB -------------------------------- - -+-----------+------------+------------+ -| Locations | Telescopes |Instruments | -+===========+============+============+ -| Armazones | ELT | MICADO | -| | +------------+ -| | | METIS | -| | +------------+ -| | | MOSAIC | -+-----------+------------+------------+ -| Paranal | VLT | HAWKI | -+-----------+------------+------------+ -| | | LFOA | -+-----------+------------+------------+ - - - diff --git a/irdb/badges.py b/irdb/badges.py deleted file mode 100644 index 0479ef60..00000000 --- a/irdb/badges.py +++ /dev/null @@ -1,318 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- -"""Everything to do with report badges and more.""" - -import logging -from pathlib import Path -from typing import TextIO -from numbers import Number -from string import Template -from datetime import datetime as dt, timezone -from collections.abc import Mapping - -import yaml - -from astar_utils import NestedMapping - -# After 3.11, can just import UTC directly from datetime -UTC = timezone.utc - -PKG_DIR = Path(__file__).parent.parent - - -def _fix_badge_str(badge_str: str) -> str: - """Eliminate any spaces and single dashes in badge string.""" - return badge_str.replace(" ", "_").replace("-", "--") - - -class Badge(): - """Base class for markdown report badges. - - Based on the type and (in case of strings) value of the parameter `value`, - the appropriate subclass is returned, which also deals with the colour of - the badge. These subclasses should *not* be instantiated directly, but - rather this base class should always be used. - - In the case of a string-type `value`, the colour of the badge is based on - a set of special strings, e.g. red for 'error' or green for 'found'. - A complete list of these special strings can be accessed via - ``StrBadge.special_strings``. The default colour for any string value not - listed as a special string is lightgrey. - - By default, all badges appear as "key/label-value" badges with a grey label - on the left side and a coloured value on the right side. For simple - messages, it is also possible to produce a "message-only" badge. This can - simply be done by adding a leading '!' to the (string) `value` parameter. - The message of the badge is then only the `key` parameter, while the colour - of the badge is again decided by the special strings, after the leading '!' - is stripped. - - Any spaces or single dashes present in either `key` or `value` are - automatically replaced by underscores or double dashes, respectively, to - comply with the format requirements for the badges. - - It is possible to manually change the colour of any badge after creation - by setting the desired colour (string) for the `colour` attribute. - - Parameters - ---------- - key : str - Dictionary key, become (left-side) label of the badge. - value : str, bool, int or float - Dictionary key, become (right-side) value of the badge. - Subclass dispatch is decided based on type and value of this parameter. - - Attributes - ---------- - colour : str - The (auto-assigned) colour of the badge. - """ - - pattern = Template("[![](https://img.shields.io/badge/$key-$val-$col)]()") - colour = "lightgrey" - - def __new__(cls, key: str, value): - if isinstance(value, bool): - return super().__new__(BoolBadge) - if isinstance(value, Number): - return super().__new__(NumBadge) - if isinstance(value, str): - if value.startswith("!"): - return super().__new__(MsgOnlyBadge) - return super().__new__(StrBadge) - raise TypeError(value) - - def __init__(self, key: str, value): - self.key = _fix_badge_str(key) - self.value = _fix_badge_str(value) if isinstance(value, str) else value - - def write(self, stream: TextIO) -> None: - """Write formatted pattern to I/O stream.""" - _dict = {"key": self.key, "val": self.value, "col": self.colour} - stream.write(self.pattern.substitute(_dict)) - - -class BoolBadge(Badge): - """Key-value Badge for bool values, True -> green, False -> red.""" - - colour = "red" - - def __init__(self, key: str, value: bool): - super().__init__(key, value) - if self.value: - self.colour = "green" - - -class NumBadge(Badge): - """Key-value Badge for numerical values, lightblue.""" - - colour = "lightblue" - - -class StrBadge(Badge): - """Key-value Badge for string values, colour based on special strings.""" - - special_strings = { - "observation": "blueviolet", - "support": "deepskyblue", - "error": "red", - "missing": "red", - "warning": "orange", - "conflict": "orange", - "incomplete": "orange", - "ok": "green", - "found": "green", - "not_found": "red", - "none": "yellowgreen", - } - - def __init__(self, key: str, value: str): - super().__init__(key, value) - self.colour = self.special_strings.get(self.value.lower(), "lightgrey") - - -class MsgOnlyBadge(StrBadge): - """Key-only Badge for string values, colour based on special strings.""" - - pattern = Template("[![](https://img.shields.io/badge/$key-$col)]()") - - def __init__(self, key: str, value: str): - value = value.removeprefix("!") - super().__init__(key, value) - - -class BadgeReport(NestedMapping): - """Context manager class for collection and generation of report badges. - - Intended usage is in a pytest fixture with a scope that covers all tests - that should be included in that report file: - - >>> import pytest - >>> - >>> @pytest.fixture(name="badges", scope="module") - >>> def fixture_badges(): - >>> with BadgeReport() as report: - >>> yield report - - This fixture can then be used inside the tests like a dictionary: - - >>> def test_something(self, badges): - >>> badges[f"!foo.bar.baz"] = "OK" - - Because `BadgeReport` inherits from ``NestedMapping``, the use of '!'-type - "bang-strings" is supported. - - Additionally, any logging generated within a test can be captured and - stored in the report, to be written in a separate log file at teardown: - - >>> import logging - >>> - >>> def test_something_else(self, badges, caplog): - >>> logging.warning("Oh no!") - >>> badges.logs.extend(caplog.records) - - Note the use of ``caplog.records`` to access the ``logging.LogRecord`` - objects rather then the string output, as `BadgeReport` performs very basic - custom formatting. Further note the use of ``logs.extend()``, because - ``caplog.records`` returns a ``list``, to not end up with nested lists. - - The level of logging recorded is controlled by the logging settings in the - test script. `BadgeReport` handles all ``logging.LogRecord`` objects in - the final `.logs` list. - - Parameters - ---------- - filename : str, optional - Name for yaml file, should end in '.yaml. The default is "badges.yaml". - report_filename : str, optional - Name for report file, should end in '.md'. The default is "badges.md". - logs_filename : str, optional - Name for log file. The default is "badge_report_log.txt". - save_logs : bool, optional - Whether to output logs. The default is True. - - Attributes - ---------- - yamlpath : Path - Full path for yaml file. - report_path : Path - Full path for report file. - log_path : Path - Full path for log file. - logs : list of logging.LogRecord - List of logging.LogRecord objects to be saved to `logs_filename`. - """ - - def __init__( - self, - filename: str = "badges.yaml", - report_filename: str = "badges.md", - logs_filename: str = "badge_report_log.txt", - save_logs: bool = True, - ) -> None: - logging.debug("REPORT INIT") - base_path = Path(PKG_DIR, "_REPORTS") - - self.filename = filename - self.yamlpath = base_path / self.filename - self.report_name = report_filename - self.report_path = base_path / self.report_name - - self.save_logs = save_logs - self.logs = [] - logs_name = logs_filename or "badge_report_log.txt" - self.log_path = base_path / logs_name - - super().__init__() - - def __enter__(self): - """Context manager setup.""" - logging.debug("REPORT ENTER") - # try: - # # TODO: WHY do we actually load this first? It caused some issues - # # with 'old' badges that are not cleared. Is there any good - # # reason at all to load the previous yaml file??? - # with self.yamlpath.open(encoding="utf-8") as file: - # self.update(yaml.full_load(file)) - # except FileNotFoundError: - # logging.warning("%s not found, init empty dict", self.yamlpath) - logging.debug("Init emtpy dict.") - return self - - def __exit__(self, exc_type, exc_value, exc_traceback): - """Context manager teardown.""" - logging.debug("REPORT EXIT") - self.write_yaml() - self.generate_report() - if self.save_logs: - self.write_logs() - logging.debug("REPORT DONE") - - def write_logs(self) -> None: - """Dump logs to file (`logs_filename`).""" - with self.log_path.open("w", encoding="utf-8") as file: - for log in self.logs: - file.write(f"{log.levelname}::{log.message}\n") - - def write_yaml(self) -> None: - """Dump dict to yaml file (`filename`).""" - dumpstr = yaml.dump(self.dic, sort_keys=False) - self.yamlpath.write_text(dumpstr, encoding="utf-8") - - def _make_preamble(self) -> str: - preamble = ("# IRDB Packages Report\n\n" - f"**Created on UTC {dt.now(UTC):%Y-%m-%d %H:%M:%S}**\n\n" - "For details on errors and conflicts, see badge report " - "log file in this directory.\n\n") - return preamble - - def generate_report(self) -> None: - """Write markdown badge report to `report_filename`.""" - if not self.report_path.suffix == ".md": - logging.warning(("Expected '.md' suffix for report file name, but " - "found %s. Report file might not be readable."), - self.report_path.suffix) - with self.report_path.open("w", encoding="utf-8") as file: - file.write(self._make_preamble()) - make_entries(file, self.dic) - - -def _get_nested_header(key: str, level: int) -> str: - if level > 2: - return f"* {key}: " - return f"{'#' * (level + 2)} {key.title() if level else key}" - - -def make_entries(stream: TextIO, entry, level=0) -> None: - """ - Recursively write lines of text from a nested dictionary to text stream. - - Parameters - ---------- - stream : TextIO - I/O stream to write the badges to. - - entry : dict, str, bool, float, int - A level from a nested dictionary - - level : int - How far down the rabbit hole we are w.r.t the nested dictionary - - Returns - ------- - None - """ - if not isinstance(entry, Mapping): - return - - for key, value in entry.items(): - stream.write("\n") - stream.write(" " * (level - 2)) - if isinstance(value, Mapping): - stream.write(_get_nested_header(key, level)) - # recursive - make_entries(stream, value, level=level+1) - else: - if level > 1: - stream.write("* ") - Badge(key, value).write(stream) diff --git a/irdb/public_html/index.html b/irdb/public_html/index.html deleted file mode 100644 index 9ccab4ba..00000000 --- a/irdb/public_html/index.html +++ /dev/null @@ -1,59 +0,0 @@ - - - - - - -

- - -

- - - -

-SimCADO is currently moving forward -

-

-i.e. we're undertaking a reasonably sized refactor of the code base -

- -

- -simcado.readthedocs.io
-

- - -The old documentation has been moved to readthedocs and is updated automatically when we push to GitHub -

- - -

-This interuption is temporary. -We intend to release the newest version around Christmas 2018.
-Thank you for your patience! -

- -

-Important information: -

-

- -

-WARNING: MORFEO PSFs are subject to strict conditions. Before you publish anything -with these PSFs, please contact either the SimCADO team or the MORFEO team directly -

- - - - - diff --git a/irdb/public_html/index.php b/irdb/public_html/index.php deleted file mode 100644 index 3a56eef8..00000000 --- a/irdb/public_html/index.php +++ /dev/null @@ -1,27 +0,0 @@ - - - - - - - - - - - EzPHP - - -
-

Welcome to your personal web server

-

- -

- -

-

-

- -

-

- - \ No newline at end of file diff --git a/irdb/public_html/index.rst b/irdb/public_html/index.rst deleted file mode 100644 index 97305335..00000000 --- a/irdb/public_html/index.rst +++ /dev/null @@ -1,18 +0,0 @@ -ScopeSim is moving forward -========================== - -2022-07-01: Broken ScopeSim server FTP address ----------------------------------------------- - -.. warning:: July 2022: The downloadable content server was retired and the data migrated to a new server. - - vX.Y and above have been redirected to a new server URL. - Please either upgrade to the latest version (``pip install --upgrade ``), or follow these `instructions to update the server URL `_ in the config file. - - -Sunsetting SimCADO and SimMETIS ---------------------------------- -To all those still using SimCADO or SimMETIS, we thank you for continuing to use the original versions of our simulator software. -The upgrades to the server infrastructure at the University of Vienna now mean that the functions for updating internal data files will no longer work. -We will not be releasing an upgrade to SimCADO or SimMETIS as these packages have been replaced by the new multipurpose -[ScopeSim environment](https://scopesim.readthedocs.io/en/latest/) diff --git a/irdb/publish.py b/irdb/publish.py index 5c5b8dae..5caa6591 100644 --- a/irdb/publish.py +++ b/irdb/publish.py @@ -125,7 +125,8 @@ def make_package(pkg_name: str, stable: bool = False, time = dt.fromisoformat(version_dict["timestamp"]) # Make the zip file - zip_name = db._unparse_package_version(pkg_name, time.date(), suffix) + # zip_name = db._unparse_package_version(pkg_name, time.date(), suffix) + zip_name = f"{pkg_name}.{time.date()}.zip" zip_package_folder(pkg_name, zip_name) logging.info( "[%s]: Compiled package: %s", diff --git a/irdb/repairs/__init__.py b/irdb/repairs/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/irdb/repairs/repair_scripts.py b/irdb/repairs/repair_scripts.py deleted file mode 100644 index 186c2798..00000000 --- a/irdb/repairs/repair_scripts.py +++ /dev/null @@ -1,33 +0,0 @@ -import glob -from astropy.io import fits - - -def repair_fits_headers(filename): - with fits.open(filename, mode="update") as hdulist: - for hdu in hdulist: - - keys = ["CDELT1", "CDELT2", "CDELT1", "CDELT2", "PIXELSCL", "WAVE0"] - keys_inv = ["CD1_1", "CD2_2", "PIXELSCL", "PIXELSCL", "CDELT1", - "WAVELENG"] - for key, key_inv in zip(keys, keys_inv): - if key not in hdu.header and key_inv in hdu.header: - hdu.header[key] = hdu.header[key_inv] - - if isinstance(hdu, (fits.PrimaryHDU, fits.ImageHDU)) and \ - hdu.data is not None: - missing_keys = ["CRVAL1", "CRVAL2", "CTYPE1", "CTYPE2", - "CRPIX1", "CRPIX2", 'CUNIT1', 'CUNIT2'] - missing_vals = [0, 0, "RA---TAN", "DEC--TAN", - hdu.data.shape[0] / 2., hdu.data.shape[1] / 2., - "arcsec", "arcsec"] - - for key, val in zip(missing_keys, missing_vals): - if key not in hdu.header: - hdu.header[key] = val - - hdulist.flush() - - -psf_files = glob.glob("C:\Work\irdb\_PSFs\*.fits") -for fname in psf_files: - repair_fits_headers(fname) diff --git a/irdb/tests/test_badges.py b/irdb/tests/test_badges.py deleted file mode 100644 index 4d134455..00000000 --- a/irdb/tests/test_badges.py +++ /dev/null @@ -1,135 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- -""" -Tests for irdb.badges -""" - -from io import StringIO -from unittest import mock - -import yaml -import pytest - -from irdb.badges import ( - BadgeReport, - Badge, - BoolBadge, - NumBadge, - StrBadge, - MsgOnlyBadge, -) -from astar_utils import NestedMapping - - -@pytest.fixture(name="temp_dir", scope="module") -def fixture_temp_dir(tmp_path_factory): - tmpdir = tmp_path_factory.mktemp("PKG_DIR") - (tmpdir / "_REPORTS").mkdir() - return tmpdir - - -class TestBadgeSubclasses: - def test_bool(self): - assert isinstance(Badge("bogus", True), BoolBadge) - assert isinstance(Badge("bogus", False), BoolBadge) - - def test_num(self): - assert isinstance(Badge("bogus", 7), NumBadge) - assert isinstance(Badge("bogus", 3.14), NumBadge) - - def test_str(self): - assert isinstance(Badge("bogus", "foo"), StrBadge) - - def test_msgonly(self): - assert isinstance(Badge("bogus", "!foo"), MsgOnlyBadge) - - -class TestColours: - @pytest.mark.parametrize("value, colour", [ - ("observation", "blueviolet"), - ("support", "deepskyblue"), - ("error", "red"), - ("missing", "red"), - ("warning", "orange"), - ("conflict", "orange"), - ("incomplete", "orange"), - ("ok", "green"), - ("found", "green"), - ("not_found", "red"), - ("none", "yellowgreen"), - ]) - def test_special_strings(self, value, colour): - assert Badge("bogus", value).colour == colour - - def test_bool(self): - assert Badge("bogus", True).colour == "green" - assert Badge("bogus", False).colour == "red" - - def test_num(self): - assert Badge("bogus", 7).colour == "lightblue" - - -class TestPattern: - def test_simple(self): - with StringIO() as str_stream: - Badge("bogus", "Error").write(str_stream) - pattern = "[![](https://img.shields.io/badge/bogus-Error-red)]()" - assert pattern in str_stream.getvalue() - - def test_msg_only(self): - with StringIO() as str_stream: - Badge("bogus", "!OK").write(str_stream) - pattern = "[![](https://img.shields.io/badge/bogus-green)]()" - assert pattern in str_stream.getvalue() - - -class TestSpecialChars: - def test_space(self): - badge = Badge("bogus foo", "bar baz") - assert badge.key == "bogus_foo" - assert badge.value == "bar_baz" - - def test_dash(self): - badge = Badge("bogus-foo", "bar-baz") - assert badge.key == "bogus--foo" - assert badge.value == "bar--baz" - - -class TestReport: - # TODO: the repeated setup stuff should be a fixture or something I guess - - @pytest.mark.usefixtures("temp_dir") - def test_writes_yaml(self, temp_dir): - with mock.patch("irdb.badges.PKG_DIR", temp_dir): - with BadgeReport("test.yaml", "test.md") as report: - report["!foo.bar"] = "bogus" - assert (temp_dir / "_REPORTS/test.yaml").exists() - - @pytest.mark.usefixtures("temp_dir") - def test_writes_md(self, temp_dir): - with mock.patch("irdb.badges.PKG_DIR", temp_dir): - with BadgeReport("test.yaml", "test.md") as report: - report["!foo.bar"] = "bogus" - assert (temp_dir / "_REPORTS/test.md").exists() - - @pytest.mark.usefixtures("temp_dir") - def test_yaml_content(self, temp_dir): - with mock.patch("irdb.badges.PKG_DIR", temp_dir): - with BadgeReport("test.yaml", "test.md") as report: - report["!foo.bar"] = "bogus" - path = temp_dir / "_REPORTS/test.yaml" - with path.open(encoding="utf-8") as file: - dic = NestedMapping(yaml.full_load(file)) - assert "!foo.bar" in dic - assert dic["!foo.bar"] == "bogus" - - @pytest.mark.usefixtures("temp_dir") - def test_md_content(self, temp_dir): - with mock.patch("irdb.badges.PKG_DIR", temp_dir): - with BadgeReport("test.yaml", "test.md") as report: - report["!foo.bar"] = "bogus" - path = temp_dir / "_REPORTS/test.md" - markdown = path.read_text(encoding="utf-8") - assert "## foo" in markdown - badge = "[![](https://img.shields.io/badge/bar-bogus-lightgrey)]()" - assert badge in markdown diff --git a/irdb/tests/test_package_contents.py b/irdb/tests/test_package_contents.py index 0ad71e1c..a112f873 100644 --- a/irdb/tests/test_package_contents.py +++ b/irdb/tests/test_package_contents.py @@ -1,25 +1,20 @@ -#!/usr/bin/env python3 # -*- coding: utf-8 -*- +"""Runs the badge reports tests.""" + import logging from pathlib import Path import pytest import yaml -from scopesim.effects.data_container import DataContainer from astropy.io.ascii import InconsistentTableError +from scopesim.effects.data_container import DataContainer +from astar_utils import BadgeReport + from irdb.utils import get_packages, recursive_filename_search -from irdb.badges import BadgeReport from irdb.fileversions import IRDBFile -# HACK: This is necessary because scopesim has import side effects that mess up -# logging here, specifically capture. Once that's solved, the following -# lines should be removed! -from importlib import reload -logging.shutdown() -reload(logging) - # Note: This module doesn't need to run always, so mark it. pytestmark = pytest.mark.badges @@ -174,8 +169,7 @@ def test_all_dat_files_readable(self, package, pkg_dir, badges, caplog): for fn_dat in fns_dat: fn_loc = fn_dat.relative_to(pkg_dir) try: - # FIXME: DataContainer should be updated to support Path objects... - _ = DataContainer(str(fn_dat)) + _ = DataContainer(fn_dat) except InconsistentTableError as err: logging.error("%s InconsistentTableError %s", str(fn_loc), err) bad_files.append(str(fn_loc)) diff --git a/irdb/tests/test_publish.py b/irdb/tests/test_publish.py index d6124bb0..08a0126f 100644 --- a/irdb/tests/test_publish.py +++ b/irdb/tests/test_publish.py @@ -65,6 +65,9 @@ # # Put the original values back. # PATH_TEST_PACKAGE_VERSION_YAML.write_bytes(b_yaml_test_package) +# Note: This module doesn't need to run always, so mark it. +pytestmark = pytest.mark.irdb + @pytest.fixture(scope="module") def temp_zipfiles(tmp_path_factory): diff --git a/irdb/tests/test_utils.py b/irdb/tests/test_utils.py index 3057a735..e39847e0 100644 --- a/irdb/tests/test_utils.py +++ b/irdb/tests/test_utils.py @@ -1,4 +1,3 @@ -#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Tests for irdb.utils @@ -13,26 +12,26 @@ from irdb.utils import get_packages +# Note: This module doesn't need to run always, so mark it. +pytestmark = pytest.mark.irdb + + @pytest.fixture(name="packages", scope="class") def fixture_packages(): return dict(get_packages()) class TestGetPackages: - @pytest.mark.usefixtures("packages") def test_includes_various_packages(self, packages): wanted = {"Armazones", "ELT", "METIS", "MICADO", "test_package"} assert all(pkg_name in packages.keys() for pkg_name in wanted) - @pytest.mark.usefixtures("packages") def test_doesnt_includes_specials(self, packages): wanted = {"irdb", "docs", "_REPORTS", ".github"} assert all(pkg_name not in packages.keys() for pkg_name in wanted) - @pytest.mark.usefixtures("packages") def test_values_are_path_objects(self, packages): assert isinstance(packages["test_package"], Path) - @pytest.mark.usefixtures("packages") def test_only_includes_dirs(self, packages): assert all(path.is_dir() for path in packages.values()) diff --git a/irdb/version.py b/irdb/version.py deleted file mode 100644 index 25bacde1..00000000 --- a/irdb/version.py +++ /dev/null @@ -1,11 +0,0 @@ -version = '0.2.0' -date = '2022-04-09 13:00:00 GMT' -yaml_descriptions = """ -- version : 0.2.0 - date : 2022-04-09 - comment : Random updates - changes : - - (KL) re-wrote the publish workflow to include dates and versioning of - packages - -""" diff --git a/pytest.ini b/pytest.ini index 34d8628e..faa06700 100644 --- a/pytest.ini +++ b/pytest.ini @@ -1,8 +1,10 @@ [pytest] # Prevent recursion into MICADO/docs/example_notebooks/inst_pkgs -addopts = --ignore-glob="*/inst_pkgs/*" -p no:randomly -m "not badges" +addopts = --ignore-glob="*/inst_pkgs/*" -p no:randomly -m "not badges and not irdb" # Badge report needs order (at least for now, should be solved by using astar-utils NestedMapping) markers = webtest: mark a test as using network resources. slow: mark test as slow. badges: tests for the badge report + irdb: tests for IRDB functionality (unrelated to a specific instrument package) + validation: tests for validating ScopeSim results (needed for docs) diff --git a/requirements.github_actions.txt b/requirements.github_actions.txt index 9ed7f400..5fb0ee11 100644 --- a/requirements.github_actions.txt +++ b/requirements.github_actions.txt @@ -1,7 +1,7 @@ pytest numpy matplotlib -astropy +astropy[jupyter] pyyaml paramiko astar-utils @@ -10,3 +10,4 @@ scopesim_templates jupytext ipykernel nbconvert +astar-utils diff --git a/requirements.readthedocs.txt b/requirements.readthedocs.txt index a0d06a02..6ff92dca 100644 --- a/requirements.readthedocs.txt +++ b/requirements.readthedocs.txt @@ -5,13 +5,16 @@ astropy docutils pyyaml +pytest astar-utils scopesim +scopesim_templates +paramiko -sphinx>=4.3.0 -sphinx-rtd-theme>=0.5.1 -jupyter_sphinx==0.2.3 -sphinxcontrib-apidoc -nbsphinx +sphinx>=5.0 +sphinx-book-theme +myst-nb +sphinx-design +sphinx-copybutton numpydoc diff --git a/setup.py b/setup.py index 5c66b71f..2692812c 100644 --- a/setup.py +++ b/setup.py @@ -5,10 +5,6 @@ import os from os import path as pth -# Version number -with open('irdb/version.py') as f: - __version__ = f.readline().split("'")[1] - def create_manifest(): pkgs_list = [pkg for pkg in os.listdir("./") if \ @@ -21,7 +17,6 @@ def create_manifest(): def setup_package(): setup(name = 'IRDB', - version = __version__, description = "Instrument package database", author = "Kieran Leschinski", author_email = "kieran.leschinski@unive.ac.at",