FileRead

Read Gaussian trajectory log file based on regex patterns and then do proper processing.

• Initialization: FileRead(n_atom=-1)
  The initialization of this object will attempt to determine the number of atoms in the molecule and set up a pattern dictionary, partially based on the number of atoms.

  • Parameters:
    • n_atom: integer
      optional, default=-1, which is a flag to signify this value was not directly passed in. This gives the number of atoms in the molecule for the Gaussian log files to read.

• FileRead.pattern_dict =

    {
        "Electric Field": r"An electric field of +([\-+]*[.\d]+D*[\-+]*[\d]*) +([\-+]*[.\d]+D*[\-+]*[\d]*) +"
                          r"([\-+]*[.\d]+D*[\-+]*[\d]*)|Standard basis: .+(?:\n.+){1,2} basis functions,",
        "Electric Field Alt": r"Electric field = +([\-+]*[.\d]+D*[\-+]*[\d]*) +([\-+]*[.\d]+D*[\-+]*[\d]*) +"
                              r"([\-+]*[.\d]+D*[\-+]*[\d]*)|Standard basis: .+(?:\n.+){1,2} basis functions,",
        "Cartesian Coordinates #VarRow": r"Cartesian coordinates.+\n"
                                         + r".+ X= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                                           r" +Y= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                                           r" +Z= +([\-+]*[.\d]+D*[\-+]*[\d]*)\n" * self.n_atom,
        "Mass Weighted Velocity #VarRow": r"MW [cC]artesian velocity:.*\n"
                                          + r" I= +\d+ X= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                                            r" +Y= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                                            r" +Z= +([\-+]*[.\d]+D*[\-+]*[\d]*)\n" * self.n_atom,
        "Time": r"Time \(fs\) +([\-+]*[.\d]+D*[\-+]*[\d]*)",
        "Total Energy": r"ETot += +([\-+]*[.\d]+D*[\-+]*[\d]*)",
        "Kinetic Energy": r"EKin = +([\-+]*[.\d]+D*[\-+]*[\d]*);",
        "Potential Energy": r"EPot = +([\-+]*[.\d]+D*[\-+]*[\d]*);",
        "Total Angular Momentum": r"Jtot = +([\-+]*[.\d]+D*[\-+]*[\d]*) H-BAR",
        "Angular Momemtum Components": r"Angular momentum \(instantaneous\)\n +JX ="
                                       r" +([\-+]*[.\d]+D*[\-+]*[\d]*) +JY = +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                                       r" +JZ = +([\-+]*[.\d]+D*[\-+]*[\d]*)",
        "Mulliken Charges #VarRow": r"(?<=\n) Mulliken charges(?::| and spin densities:)(?! with)\n.+\n"
                                    + r" +\d+ +\S+ +([\-+]*[.\d]+)(?:\n| +[\-+]*[.\d]+\n)" * self.n_atom,
        "Dipole Moment": r" Dipole moment .+:\n +X= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
                         r" +Y= +([\-+]*[.\d]+D*[\-+]*[\d]*) +Z= +([\-+]*[.\d]+D*[\-+]*[\d]*)"
    }
  

  • There are three types of patterns:
    1. Fixed dimension:
       for example, "Time": r"Time (fs) +([-+][.\d]+D[-+][\d])" This means a 1-dimensional array will be read from every data block at each time step.
    2. Variable row number:
       for example, "Mulliken Charges #VarRow": r"(?<=\n) Mulliken charges(?::| and spin densities:)(?! with)\n.+\n"
       • r" +\d+ +\S+ +([-+][.\d]+)(?:\n| +[-+][.\d]+\n)" * self.n_atom This means a 2-dimensional array will be read from every data block at each time step. In order to preserve the shape of such array, the regex pattern is generated by a variable, self.n_atom, which is the number of atoms determined previously. "#VarRow" in the key of this dictionary entry signifies the follow-up method to treat such data type accordingly.
    3. Variable column number:
       similar to Variable row number type. Right now there is not any data type needed in this category, but the functionality is built in already.
  • So far the only variable in the above mentioned variable type patterns is the number of atoms, and can only be the number of atoms.

• FileRead.findall(file_str, data_type)
  The method to extract the data from a log file.

  • Parameters:

    • file_str: string, python File object
      first argument. The raw string of a log file or the file handle of said file to be read from.
    • data_type: string
      second argument. The string of the key in the pattern_dict dictionary. An error will be raised if such entry was not added before using this method.

  • Returns: numpy array.

  • Example:
    Suppose all the Cartesian coordinates are to be extracted from a log file. The following lines will do the job:

      fh = open("trajectory.log", "r")
      reader = FileRead(file_str=fh)
      cts = reader.findall(fh, "Cartesian Coordinates #VarRow")
      fh.close()
    

    Array cts is now a multi-dimensional array containing such data. cts[points, n_atoms, xyz]