| Server IP : 217.160.0.135 / Your IP : 216.73.217.85 Web Server : Apache System : Linux www 6.18.52-i1-ampere #1203 SMP Mon Sep 14 18:29:59 CEST 2026 aarch64 User : sws1074145052 ( 1074145052) PHP Version : 8.3.32 Disable Function : NONE MySQL : OFF | cURL : ON | WGET : ON | Perl : ON | Python : OFF | Sudo : OFF | Pkexec : OFF Directory : /lib/python3/dist-packages/scipy/io/matlab/__pycache__/ |
Upload File : |
�
d�c�1 � �� � d Z ddlmZ ddlmZmZ ddlmZmZ ddl m
Z
m Z g d�Z edd �� � Z
dd
�Zedd �� � Zedd�� � Ze dd�� � Zedd�� � Zd
S )z7
Module for reading and writing matlab (TM) .mat files
� )�contextmanager� )�_get_matfile_version� docfiller)�MatFile4Reader�MatFile4Writer)�MatFile5Reader�MatFile5Writer)�mat_reader_factory�loadmat�savemat�whosmat�rbc # � K � t | ||� � \ }} |V � |r|� � � d S d S # |r|� � � w w xY w)N)�
_open_file�close)� file_like� appendmat�mode�f�openeds �6/usr/lib/python3/dist-packages/scipy/io/matlab/_mio.py�_open_file_contextr sk � � � ��9�i��6�6�I�A�v������ � �
�G�G�I�I�I�I�I� � ��6� �
�G�G�I�I�I�I� ���s �6 �Ac � � t |� � t d� � z rdhn
t � � }t |� � t d� � z r|� d� � |� t | � � � � r| dfS t | |� � dfS # t
$ r]}t
| t � � r3|r| � d� � s| dz
} t | |� � dfcY d}~S t d � � |�d}~ww xY w)
a
Open `file_like` and return as file-like object. First, check if object is
already file-like; if so, return it as-is. Otherwise, try to pass it
to open(). If that fails, and `file_like` is a string, and `appendmat` is true,
append '.mat' and try again.
zr+�readzwax+�writeFTz.matNz/Reader needs file name or open file-like object) �set�add�issubset�dir�open�OSError�
isinstance�str�endswith)r r r �reqs�es r r r s' � � �4�y�y�3�t�9�9�,� 7�F�8�8�#�%�%�D�
�4�y�y�3�v�;�;� � � ������� �}�}�S��^�^�$�$� ��%� � � ��I�t�$�$�d�*�*�� � � � � �i�� %� %� ��
$��!3�!3�F�!;�!;�
$��V�#� �� �4�(�(�$�.� .� .� .� .� .� .��A�� ��
����� ���s% � B �
D�(AD �*D�0D � DTc �� � t | |� � \ }}t |� � \ }}|dk rt |fi |��|fS |dk rt |fi |��|fS |dk rt d� � �t d|z � � �)a�
Create reader for matlab .mat format files.
Parameters
----------
%(file_arg)s
%(append_arg)s
%(load_args)s
%(struct_arg)s
Returns
-------
matreader : MatFileReader object
Initialized instance of MatFileReader class matching the mat file
type detected in `filename`.
file_opened : bool
Whether the file was opened by this routine.
r r � z6Please use HDF reader for matlab v7.3 files, e.g. h5pyz Did not recognize version %s)r r r r �NotImplementedError� TypeError)� file_namer �kwargs� byte_stream� file_opened�mjv�mnvs r r r 4 s� � �* *�)�Y� ?� ?� �K��#�K�0�0�H�C��
�a�x�x� �k�4�4�V�4�4�k�A�A� ���� �k�4�4�V�4�4�k�A�A� ����!� #5� 6� 6� 6� �6��<�=�=�=� Nc � � |� dd� � }t | |� � 5 }t |fi |��\ }}|� |� � }ddd� � n # 1 swxY w Y |�|� |� � n|}|S )a
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.
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.
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)
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])
�variable_namesN)�popr r �
get_variables�update) r, �mdictr r- r4 r �MR�_� matfile_dicts r r r V s� � �T �Z�Z� 0�$�7�7�N� �I�y� 1� 1� 8�Q�"�1�/�/��/�/���A��'�'��7�7� �8� 8� 8� 8� 8� 8� 8� 8� 8� 8� 8���� 8� 8� 8� 8�
��
� � �\�"�"�"�"� �� �Ls �&A�A � A �5F�rowc �( � t | |d� � 5 }|dk r"|rt d� � �t ||� � }n*|dk rt ||d||�� � }nt d� � �|� |� � ddd� � dS # 1 swxY w Y dS ) ap
Save a dictionary of names and arrays into a MATLAB-style .mat file.
This saves the array objects in the given dictionary to a MATLAB-
style .mat file.
Parameters
----------
file_name : str or file-like object
Name of the .mat file (.mat extension not needed if ``appendmat ==
True``).
Can also pass open file_like object.
mdict : dict
Dictionary from which to save matfile variables.
appendmat : bool, optional
True (the default) to append the .mat extension to the end of the
given filename, if not already present.
format : {'5', '4'}, string, optional
'5' (the default) for MATLAB 5 and up (to 7.2),
'4' for MATLAB 4 .mat files.
long_field_names : bool, optional
False (the default) - maximum field name length in a structure is
31 characters which is the documented maximum length.
True - maximum field name length in a structure is 63 characters
which works for MATLAB 7.6+.
do_compression : bool, optional
Whether or not to compress matrices on write. Default is False.
oned_as : {'row', 'column'}, optional
If 'column', write 1-D NumPy arrays as column vectors.
If 'row', write 1-D NumPy arrays as row vectors.
Examples
--------
>>> from scipy.io import savemat
>>> import numpy as np
>>> a = np.arange(20)
>>> mdic = {"a": a, "label": "experiment"}
>>> mdic
{'a': array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19]),
'label': 'experiment'}
>>> savemat("matlab_matrix.mat", mdic)
�wb�4z6Long field names are not available for version 4 filesr< T)�do_compression�unicode_strings�long_field_names�oned_aszFormat should be '4' or '5'N)r �
ValueErrorr r
�
put_variables) r, r8 r �formatrC rA rD � file_stream�MWs r r
r
� s� � �d
�I�y�$� 7� 7�
�;� �S�=�=� �
[� �!Y�Z�Z�Z� � �W�5�5�B�B�
�s�]�]� � �/=�04�1A�(/� 1� 1� 1�B�B� � :�;�;� ;�
���� � � �
�
�
�
�
�
�
�
�
�
�
�
����
�
�
�
�
�
s �A(B�B �B c � � t | |� � 5 }t |fi |��\ }}|� � � }ddd� � n # 1 swxY w Y |S )a�
List variables inside a MATLAB file.
Parameters
----------
%(file_arg)s
%(append_arg)s
%(load_args)s
%(struct_arg)s
Returns
-------
variables : list of tuples
A list of tuples, where each tuple holds the matrix name (a string),
its shape (tuple of ints), and its data class (a string).
Possible data classes are: int8, uint8, int16, uint16, int32, uint32,
int64, uint64, single, double, cell, struct, object, char, sparse,
function, opaque, logical, unknown.
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 (e.g. h5py). Because SciPy does not supply one, we do not implement the
HDF5 / 7.3 interface here.
.. versionadded:: 0.12.0
Examples
--------
>>> from io import BytesIO
>>> import numpy as np
>>> from scipy.io import savemat, whosmat
Create some arrays, and use `savemat` to write them to a ``BytesIO``
instance.
>>> a = np.array([[10, 20, 30], [11, 21, 31]], dtype=np.int32)
>>> b = np.geomspace(1, 10, 5)
>>> f = BytesIO()
>>> savemat(f, {'a': a, 'b': b})
Use `whosmat` to inspect ``f``. Each tuple in the output list gives
the name, shape and data type of the array in ``f``.
>>> whosmat(f)
[('a', (2, 3), 'int32'), ('b', (1, 5), 'double')]
N)r r �list_variables)r, r r- r �MLr/ � variabless r r r / s� � �h
�I�y� 1� 1� (�Q�,�Q�9�9�&�9�9���K��%�%�'�'� �(� (� (� (� (� (� (� (� (� (� (���� (� (� (� (� �s �%A�A� A)r )T)NT)Tr< FFr= )�__doc__�
contextlibr �_miobaser r �_mio4r r �_mio5r r
�__all__r r r r r
r � r2 r �<module>rU sJ ��� �
&� %� %� %� %� %� 5� 5� 5� 5� 5� 5� 5� 5� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1� 1�
A�
A�
A�� �� � � � ��� � � �6 � >� >� >� �� >�B �S� S� S� ��S�l ��� "� �� > � > � > � ��> �B �6� 6� 6� ��6� 6� 6r2