loadtable.py

jcmwave.loadtable(file_name, format='named')

Loads data from .jcm file stored in JCM table format.

Parameters:
  • file_name (filepath) – path to a .jcm table file
  • format (str) – output format of the loaded table (see below).
Returns:

The output depends on the optional format specification

format==’named’

The output is a python dictionary with entries

’title’

title of the table

’header’

nested dictionary containing meta-information.

’<Data1>’, … ‘<DataN>’

fields containing the table’s data. <Data1>, …, <DataN> are the column names as found in the .jcm file. A column is not necessarily a (n_row x 1) vector. For example, the xyz-components of n_rows wave vectors are stored as a (n_row x 3) numpy-matrix. Numbered data of the same type are stored in dictionaries with integer keys (see the example of a Fourier table below).

format==’list’

returns data as a list ordered as above

table[0]: title
table[1]: header
table[2 : N+1]: {<Data1>, …, <DataN>}

format==’matrix’

drops title and header entry, returns complete table data as a (n_row x ?) numpy-matrix.

format==’legacy’

same as named, but data is not converted to numpy arrays and remains as column vectors

Examples:

  1. Load table containing computed eigenvalues of a resonance mode or propagating mode problem:

    >>> ev = jcmwave.loadtable('project_results/eigenvalues.jcm')

    In case of a propagating mode problem, the dictionary ev will contain the following fields (in given order)

    ‘title’: title of the table
    ‘effective_refractive_index’: computed propagating modes
    ‘precision’: estimated accuracy of the computed modes

  2. Load Fourier coefficient table as produced by post-process FourierTransform for a electromagnetic field scattering problem:

    >>> ft = jcmwave.loadtable('project_results/fourier_transform.jcm')

    When the electric field components were computed, ft is a dictionary with the following fields (in given order):

    ‘title’:

    title of the table

    ‘header’:

    header containing meta-information, i.e. incoming field specification, permittivities of the lower and upper half space, reciprocal grid vectors for periodic problem, etc.

    ‘K’:

    k-vectors of the sampling in k-space (n_row x 3) matrix

    ‘N1’, ‘N2’:

    diffractions order with respect to first and second reciprocal grid vectors as given in the header (only present for periodic problems)

    ‘ElectricFieldStrength’:

    electric field vectors of the Fourier modes. This is dictionary with integer keys, where ft.ElectricFieldStrength[iF] refers to the (iF+1)-th computed electric field.

  3. Load Fourier coefficients in matrix form:

    >>> ft = loadtable('project_results/fourier_transform.jcm',
       format='matrix')

    This yields a (n_row x ?) numpy-matrix containing the data as in 2.:

    >>> 
ft = [ft.N1; 
      ft.N2;
      ft.ElectricFieldStrength[0]; 
      ...
      ft.ElectricFieldStrength[nF-1]]

    where nF is the number of computed electric fields.