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.

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.

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.

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.

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

The MIT License (MIT) Copyright (c) 2011-2018 Nephics AB

See the LICENSE.txt file.