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bundles / scipy latest / scipy / io / matlab / _mio / loadmat

function

scipy.io.matlab._mio:loadmat

source: /scipy/io/matlab/_mio.py :86

Signature

def   loadmat ( file_name ,  mdict = None ,  appendmat = True ,  * ,  spmatrix = True ,  ** kwargs )

Summary

Load MATLAB file.

Parameters

file_name : str

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

mdict : dict, optional

Dictionary in which to insert matfile variables.

appendmat : bool, optional

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

spmatrix : bool, optional (default: True)

If True, return sparse matrix. Otherwise return sparse array. Format is COO for MatFile 4 and CSC for MatFile 5. Only relevant for sparse variables.

byte_order : str or None, optional

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

mat_dtype : bool, 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 : bool, optional

Whether to squeeze unit matrix dimensions or not.

chars_as_strings : bool, optional

Whether to convert char arrays to string arrays.

matlab_compatible : bool, optional

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 : bool, 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 behavior 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.

verify_compressed_data_integrity : bool, optional

Whether the length of compressed sequences in the MATLAB file should be checked, to ensure that they are not longer than we expect. It is advisable to enable this (the default) because overlong compressed sequences in MATLAB files generally indicate that the files have experienced some sort of corruption.

variable_names : None or sequence

If None (the default) - read all variables in file. Otherwise, variable_names should be a sequence of strings, giving names of the MATLAB variables to read from the file. The reader will skip any variable with a name not in this sequence, possibly saving some read processing.

simplify_cells : False, optional

If True, return a simplified dict structure (which is useful if the mat file contains cell arrays). Note that this only affects the structure of the result and not its contents (which is identical for both output structures). If True, this automatically sets struct_as_record to False and squeeze_me to True, which is required to simplify cells.

uint16_codec : str, optional

The codec to use for decoding characters, which are stored as uint16 values. The default uses the system encoding, but this can be manually set to other values such as 'ascii', 'latin1', and 'utf-8'. This parameter is relevant only for files stored as v6 and above, and not for files stored as v4.

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.

Examples

from os.path import dirname, join as pjoin
import scipy.io as sio
✓
Get the filename for an example .mat file from the tests/data directory. 
data_dir = pjoin(dirname(sio.__file__), 'matlab', 'tests', 'data')
mat_fname = pjoin(data_dir, 'testdouble_7.4_GLNX86.mat')
✓
Load the .mat file contents. 
mat_contents = sio.loadmat(mat_fname, spmatrix=False)
✓
The result is a dictionary, one key/value pair for each variable: 
sorted(mat_contents.keys())
✓
mat_contents['testdouble']
✗
By default SciPy reads MATLAB structs as structured NumPy arrays where the dtype fields are of type `object` and the names correspond to the MATLAB struct field names. This can be disabled by setting the optional argument `struct_as_record=False`. Get the filename for an example .mat file that contains a MATLAB struct called `teststruct` and load the contents. 
matstruct_fname = pjoin(data_dir, 'teststruct_7.4_GLNX86.mat')
matstruct_contents = sio.loadmat(matstruct_fname)
teststruct = matstruct_contents['teststruct']
teststruct.dtype
✓
The size of the structured array is the size of the MATLAB struct, not the number of elements in any particular field. The shape defaults to 2-D unless the optional argument `squeeze_me=True`, in which case all length 1 dimensions are removed. 
teststruct.size
teststruct.shape
✓
Get the 'stringfield' of the first element in the MATLAB struct. 
teststruct[0, 0]['stringfield']
✗
Get the first element of the 'doublefield'. 
teststruct['doublefield'][0, 0]
✗
Load the MATLAB struct, squeezing out length 1 dimensions, and get the item from the 'complexfield'. 
matstruct_squeezed = sio.loadmat(matstruct_fname, squeeze_me=True)
matstruct_squeezed['teststruct'].shape
matstruct_squeezed['teststruct']['complexfield'].shape
✓
matstruct_squeezed['teststruct']['complexfield'].item()
✗

Aliases

  • scipy.io.loadmat

Referenced by

This package

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