mat4py

The package provides the mat4py module with the functions loadmat and
savemat that allows for reading resp. writing data in the Matlab (TM)
MAT-file format.

Matlab data is loaded into basic Python data types. Matrices are stored row-major using lists of lists. Matlab structs and cells are represented using Python dicts.

The package can be run from the command line, in which case, it provides a routine for converting Matlab MAT-files to/from JSON files.

Load data from MAT-file

The function loadmat loads all variables stored in the MAT-file into
a simple Python data structure, using only Python's dict and list
objects. Numeric and cell arrays are converted to row-ordered nested lists. Arrays are squeezed to eliminate arrays with only one element.
The resulting data structure is composed of simple types that are compatible
with the JSON format.

Example: Load a MAT-file into a Python data structure::

data = loadmat('datafile.mat')

The variable data is a dict with the variables and values contained in the MAT-file.

Save Python data structure to a MAT-file

Python data can be saved to a MAT-file, with the function savemat. Data has
to be structured in the same way as for loadmat, i.e. it should be composed
of simple data types, like dict, list, str, int and float.

Example: Save a Python data structure to a MAT-file::

savemat('datafile.mat', data)

The parameter data shall be a dict with the variables.

Command line usage

The package can be run from the command line, in which case, it provides
a routine for converting Matlab MAT-files to/from JSON files.

Call::

python -m mat4py.cmd -h

to get help with command line usage.

Known limitations

The following Matlab data structures/types are not supported:

Arrays with more than 2 dimensions
Arrays with complex numbers
Sparse arrays
Function arrays
Object classes
Anonymous function classes

License

The MIT License (MIT)
Copyright (c) 2011-2023 Nephics AB

See the LICENSE.txt file.

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