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def loadmat(file_name, mdict=None, appendmat=True, *, spmatrix=True, **kwargs)
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 ``coo_matrix``. Otherwise return ``coo_array``.
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())
['__globals__', '__header__', '__version__', 'testdouble']
>>> mat_contents['testdouble']
array([[0. , 0.78539816, 1.57079633, 2.35619449, 3.14159265,
3.92699082, 4.71238898, 5.49778714, 6.28318531]])
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
dtype([('stringfield', 'O'), ('doublefield', 'O'), ('complexfield', 'O')])
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
1
>>> teststruct.shape
(1, 1)
Get the 'stringfield' of the first element in the MATLAB struct.
>>> teststruct[0, 0]['stringfield']
array(['Rats live on no evil star.'],
dtype='<U26')
Get the first element of the 'doublefield'.
>>> teststruct['doublefield'][0, 0]
array([[ 1.41421356, 2.71828183, 3.14159265]])
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()
array([ 1.41421356+1.41421356j, 2.71828183+2.71828183j,
3.14159265+3.14159265j])
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