# -*- coding: UTF-8 -*-
# Copyright (c) 2018, Dirk Gütlin & Thomas Hartmann
# All rights reserved.
#
# This file is part of the pymatreader Project, see:
# https://gitlab.com/obob/pymatreader
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
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import scipy.io
import os
try:
from scipy.io.matlab import matfile_version
except ImportError:
from scipy.io.matlab.miobase import get_matfile_version as matfile_version
from .utils import _import_h5py, _hdf5todict, _check_for_scipy_mat_struct
__all__ = 'read_mat'
"""
This is a small module intended to facilitate reading .mat files containing
large data structures into python, disregarding of the underlying .mat
file version.
"""
[docs]def read_mat(filename, variable_names=None, ignore_fields=None,
uint16_codec=None):
"""This function reads .mat files of version <7.3 or 7.3 and returns the
contained data structure as a dictionary of nested substructure similar
to scipy.io.loadmat style.
Parameters
----------
filename: str
Path and filename of the .mat file containing the data.
variable_names: list of strings, optional
Reads only the data contained in the specified dict key or
variable name. Default is None.
ignore_fields: list of strings, optional
Ignores every dict key/variable name specified in the list within the
entire structure. Only works for .mat files v 7.3. Default is [].
uint16_codec : str | None
If your file contains non-ascii characters, sometimes reading
it may fail and give rise to error message stating that "buffer is
too small". ``uint16_codec`` allows to specify what codec (for example:
'latin1' or 'utf-8') should be used when reading character arrays and
can therefore help you solve this problem.
Returns
-------
dict
A structure of nested dictionaries, with variable names as keys and
variable data as values.
"""
if not os.path.exists(filename):
raise IOError('The file %s does not exist.' % (filename,))
if ignore_fields is None:
ignore_fields = []
try:
with open(filename, 'rb') as fid: # avoid open file warnings on error
mjv, _ = matfile_version(fid)
extra_kwargs = {}
if mjv == 1:
extra_kwargs['uint16_codec'] = uint16_codec
raw_data = scipy.io.loadmat(fid, struct_as_record=True,
squeeze_me=True, mat_dtype=False,
variable_names=variable_names,
**extra_kwargs)
data = _check_for_scipy_mat_struct(raw_data)
except NotImplementedError:
ignore_fields.append('#refs#')
h5py = _import_h5py()
with h5py.File(filename, 'r') as hdf5_file:
data = _hdf5todict(hdf5_file, variable_names=variable_names,
ignore_fields=ignore_fields)
return data