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    Re                     @   s8   d dl Zd dlZddgZeddZd	ddZdd ZdS )
    Nsave_npzload_npzF)Zallow_pickleTc                 C   s   i }|j dv r"|j|j|jd nJ|j dkr<|j|jd n0|j dkrZ|j|j|jd ntd|j  d|j|j d	|j	|j
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 |rtj| fi | ntj| fi | dS )ac   Save a sparse matrix to a file using ``.npz`` format.

    Parameters
    ----------
    file : str or file-like object
        Either the file name (string) or an open file (file-like object)
        where the data will be saved. If file is a string, the ``.npz``
        extension will be appended to the file name if it is not already
        there.
    matrix: spmatrix (format: ``csc``, ``csr``, ``bsr``, ``dia`` or coo``)
        The sparse matrix to save.
    compressed : bool, optional
        Allow compressing the file. Default: True

    See Also
    --------
    scipy.sparse.load_npz: Load a sparse matrix from a file using ``.npz`` format.
    numpy.savez: Save several arrays into a ``.npz`` archive.
    numpy.savez_compressed : Save several arrays into a compressed ``.npz`` archive.

    Examples
    --------
    Store sparse matrix to disk, and load it again:

    >>> import numpy as np
    >>> import scipy.sparse
    >>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
    >>> sparse_matrix
    <2x3 sparse matrix of type '<class 'numpy.int64'>'
       with 2 stored elements in Compressed Sparse Column format>
    >>> sparse_matrix.toarray()
    array([[0, 0, 3],
           [4, 0, 0]], dtype=int64)

    >>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
    >>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')

    >>> sparse_matrix
    <2x3 sparse matrix of type '<class 'numpy.int64'>'
       with 2 stored elements in Compressed Sparse Column format>
    >>> sparse_matrix.toarray()
    array([[0, 0, 3],
           [4, 0, 0]], dtype=int64)
    ZcscZcsrZbsr)indicesindptrdia)offsetscoo)rowcolz4Save is not implemented for sparse matrix of format .ascii)formatshapedataN)r   updater   r   r   r
   r   NotImplementedErrorencoder   r   npZsavez_compressedZsavez)fileZmatrix
compressedZarrays_dict r   K/var/www/sunrise/env/lib/python3.9/site-packages/scipy/sparse/_matrix_io.pyr      s     -



c                 C   s  t j| fi tt}z|d }W n6 tyX } ztd|  d|W Y d}~n
d}~0 0 | }t|tsv|d}zt	t
j| d}W n6 ty } ztd| d|W Y d}~n
d}~0 0 |d	v r||d
 |d |d f|d dW  d   S |dkr0||d
 |d f|d dW  d   S |dkrl||d
 |d |d ff|d dW  d   S td|W d   n1 s0    Y  dS )a   Load a sparse matrix from a file using ``.npz`` format.

    Parameters
    ----------
    file : str or file-like object
        Either the file name (string) or an open file (file-like object)
        where the data will be loaded.

    Returns
    -------
    result : csc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix
        A sparse matrix containing the loaded data.

    Raises
    ------
    OSError
        If the input file does not exist or cannot be read.

    See Also
    --------
    scipy.sparse.save_npz: Save a sparse matrix to a file using ``.npz`` format.
    numpy.load: Load several arrays from a ``.npz`` archive.

    Examples
    --------
    Store sparse matrix to disk, and load it again:

    >>> import numpy as np
    >>> import scipy.sparse
    >>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
    >>> sparse_matrix
    <2x3 sparse matrix of type '<class 'numpy.int64'>'
       with 2 stored elements in Compressed Sparse Column format>
    >>> sparse_matrix.toarray()
    array([[0, 0, 3],
           [4, 0, 0]], dtype=int64)

    >>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
    >>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')

    >>> sparse_matrix
    <2x3 sparse matrix of type '<class 'numpy.int64'>'
        with 2 stored elements in Compressed Sparse Column format>
    >>> sparse_matrix.toarray()
    array([[0, 0, 3],
           [4, 0, 0]], dtype=int64)
    r   z	The file z" does not contain a sparse matrix.Nr   Z_matrixzUnknown matrix format ""r   r   r   r   r   )r   r   r   r	   r
   r   z7Load is not implemented for sparse matrix of format {}.)r   loadPICKLE_KWARGSKeyError
ValueErroritem
isinstancestrdecodegetattrscipysparseAttributeErrorr   r   )r   ZloadedZmatrix_formateclsr   r   r   r   L   s*    1(

(0
*
2)T)	numpyr   Zscipy.sparser#   __all__dictr   r   r   r   r   r   r   <module>   s
   

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