Supporting Functions

This module defines input and output functions.

parseArray(filename, delimiter=None, skiprows=0, usecols=None, dtype=<type 'float'>)[source]

Parse array data from a file.

This function is using numpy.loadtxt() to parse the file. Each row in the text file must have the same number of values.

Parameters:
  • filename (str or file) – File or filename to read. If the filename extension is .gz or .bz2, the file is first decompressed.
  • delimiter (str) – The string used to separate values. By default, this is any whitespace.
  • skiprows (int) – Skip the first skiprows lines, default is 0.
  • usecols (list) – Which columns to read, with 0 being the first. For example, usecols = (1,4,5) will extract the 2nd, 5th and 6th columns. The default, None, results in all columns being read.
  • dtype (numpy.dtype.) – Data-type of the resulting array, default is float().
parseModes(normalmodes, eigenvalues=None, nm_delimiter=None, nm_skiprows=0, nm_usecols=None, ev_delimiter=None, ev_skiprows=0, ev_usecols=None, ev_usevalues=None)[source]

Returns NMA instance with normal modes parsed from normalmodes.

In normal mode file normalmodes, columns must correspond to modes (eigenvectors). Optionally, eigenvalues can be parsed from a separate file. If eigenvalues are not provided, they will all be set to 1.

Parameters:
  • normalmodes (str or file) – File or filename that contains normal modes. If the filename extension is .gz or .bz2, the file is first decompressed.
  • eigenvalues (str or file) – Optional, file or filename that contains eigenvalues. If the filename extension is .gz or .bz2, the file is first decompressed.
  • nm_delimiter (str) – The string used to separate values in normalmodes. By default, this is any whitespace.
  • nm_skiprows (0) – Skip the first skiprows lines in normalmodes. Default is 0.
  • nm_usecols (list) – Which columns to read from normalmodes, with 0 being the first. For example, usecols = (1,4,5) will extract the 2nd, 5th and 6th columns. The default, None, results in all columns being read.
  • ev_delimiter (str) – The string used to separate values in eigenvalues. By default, this is any whitespace.
  • ev_skiprows (0) – Skip the first skiprows lines in eigenvalues. Default is 0.
  • ev_usecols (list) – Which columns to read from eigenvalues, with 0 being the first. For example, usecols = (1,4,5) will extract the 2nd, 5th and 6th columns. The default, None, results in all columns being read.
  • ev_usevalues (list) – Which columns to use after the eigenvalue column is parsed from eigenvalues, with 0 being the first. This can be used if eigenvalues contains more values than the number of modes in normalmodes.

See parseArray() for details of parsing arrays from files.

parseSparseMatrix(filename, symmetric=False, delimiter=None, skiprows=0, irow=0, icol=1, first=1)[source]

Parse sparse matrix data from a file.

This function is using parseArray() to parse the file. Input must have the following format:

1       1    9.958948135375977e+00
1       2   -3.788214445114136e+00
1       3    6.236155629158020e-01
1       4   -7.820609807968140e-01

Each row in the text file must have the same number of values.

Parameters:
  • filename (str or file) – File or filename to read. If the filename extension is .gz or .bz2, the file is first decompressed.
  • symmetric (bool) – Set True if the file contains triangular part of a symmetric matrix, default is False.
  • delimiter (str) – The string used to separate values. By default, this is any whitespace.
  • skiprows (int) – Skip the first skiprows lines, default is 0.
  • irow (int) – Index of the column in data file corresponding to row indices, default is 0.
  • icol (int) – Index of the column in data file corresponding to row indices, default is 0.
  • first (int) – First index in the data file (0 or 1), default is 1.

Data-type of the resulting array, default is float().

writeArray(filename, array, format='%d', delimiter=' ')[source]

Write 1-d or 2-d array data into a delimited text file.

This function is using numpy.savetxt() to write the file, after making some type and value checks. Default format argument is "%d". Default delimiter argument is white space, " ".

filename will be returned upon successful writing.

writeModes(filename, modes, format='%.18e', delimiter=' ')[source]

Write modes (eigenvectors) into a plain text file with name filename. See also writeArray().

saveModel(nma, filename=None, matrices=False, **kwargs)[source]

Save nma model data as filename.nma.npz. By default, eigenvalues, eigenvectors, variances, trace of covariance matrix, and name of the model will be saved. If matrices is True, covariance, Hessian or Kirchhoff matrices are saved too, whichever are available. If filename is None, name of the NMA instance will be used as the filename, after " " (white spaces) in the name are replaced with "_" (underscores). Extension may differ based on the type of the NMA model. For ANM models, it is .anm.npz. Upon successful completion of saving, filename is returned. This function makes use of numpy.savez() function.

loadModel(filename)[source]

Returns NMA instance after loading it from file (filename). This function makes use of numpy.load() function. See also saveModel().

saveVector(vector, filename, **kwargs)[source]

Save vector data as filename.vec.npz. Upon successful completion of saving, filename is returned. This function makes use of numpy.savez() function.

loadVector(filename)[source]

Returns Vector instance after loading it from filename using numpy.load(). See also saveVector().