scipy.io.loadmat

scipy.io.loadmat(file_name, mdict=None, appendmat=True, **kwargs)

Load Matlab(tm) file

Parameters :

file_name : string

Name of the mat file (do not need .mat extension if appendmat==True) Can also pass open file-like object

m_dict : dict, optional

dictionary in which to insert matfile variables

appendmat : {True, False} optional

True to append the .mat extension to the end of the given filename, if not already present

byte_order : {None, string}, optional

None by default, implying byte order guessed from mat file. Otherwise can be one of (‘native’, ‘=’, ‘little’, ‘<’, ‘BIG’, ‘>’)

mat_dtype : {False, True} optional

If True, return arrays in same dtype as would be loaded into matlab (instead of the dtype with which they are saved)

squeeze_me : {False, True} optional

whether to squeeze unit matrix dimensions or not

chars_as_strings : {True, False} optional

whether to convert char arrays to string arrays

matlab_compatible : {False, True}

returns matrices as would be loaded by matlab (implies squeeze_me=False, chars_as_strings=False, mat_dtype=True, struct_as_record=True)

struct_as_record : {True, False} optional

Whether to load matlab structs as numpy record arrays, or as old-style numpy arrays with dtype=object. Setting this flag to False replicates the behaviour of scipy version 0.7.x (returning numpy object arrays). The default setting is True, because it allows easier round-trip load and save of matlab files.

Returns :

mat_dict : dict

dictionary with variable names as keys, and loaded matrices as values

Notes

v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported.

You will need an HDF5 python library to read matlab 7.3 format mat files. Because scipy does not supply one, we do not implement the HDF5 / 7.3 interface here.