a CCCfu@s8ddlZddlZddgZeddZd ddZddZdS) Nsave_npzload_npzF)Z allow_pickleTcCsi}|jdvr"|j|j|jdnN|jdkr<|j|jdn4|jdkrZ|j|j|jdnd|jd}t||j|jd |j |j d t |t j jr|jd d |rtj|fi|ntj|fi|d S)a Save a sparse matrix or array 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 or sparray The sparse matrix or array to save. Supported formats: ``csc``, ``csr``, ``bsr``, ``dia`` or ``coo``. 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 as sp >>> sparse_matrix = sp.sparse.csc_matrix([[0, 0, 3], [4, 0, 0]]) >>> sparse_matrix <2x3 sparse matrix of type '' with 2 stored elements in Compressed Sparse Column format> >>> sparse_matrix.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64) >>> sp.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix) >>> sparse_matrix = sp.sparse.load_npz('/tmp/sparse_matrix.npz') >>> sparse_matrix <2x3 sparse matrix of type '' with 2 stored elements in Compressed Sparse Column format> >>> sparse_matrix.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64) ZcscZcsrZbsr)indicesindptrdia)offsetscoo)rowcolz4Save is not implemented for sparse matrix of format .ascii)formatshapedataT) _is_arrayN)rupdaterrrr r NotImplementedErrorencoderr isinstancespsparseZsparraynpZsavez_compressedZsavez)filematrix compressedZ arrays_dictmsgrS/var/www/html/django/DPS/env/lib/python3.9/site-packages/scipy/sparse/_matrix_io.pyr s&.     c Cstj|fitl}|d}|dur8td|d|}t|tsT|d}|drh|d}n|d}zt t j |}Wn6t y}ztd |d |WYd}~n d}~00|d vr||d |d |df|ddWdS|dkr&||d |df|ddWdS|dkrb||d |d|dff|ddWdSt d|dWdn1s0YdS)a Load a sparse array/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_array, csr_array, bsr_array, dia_array or coo_array A sparse array/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 array/matrix to a file using ``.npz`` format. numpy.load: Load several arrays from a ``.npz`` archive. Examples -------- Store sparse array/matrix to disk, and load it again: >>> import numpy as np >>> import scipy as sp >>> sparse_array = sp.sparse.csc_array([[0, 0, 3], [4, 0, 0]]) >>> sparse_array <2x3 sparse array of type '' with 2 stored elements in Compressed Sparse Column format> >>> sparse_array.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64) >>> sp.sparse.save_npz('/tmp/sparse_array.npz', sparse_array) >>> sparse_array = sp.sparse.load_npz('/tmp/sparse_array.npz') >>> sparse_array <2x3 sparse array of type '' with 2 stored elements in Compressed Sparse Column format> >>> sparse_array.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64) In this example we force the result to be csr_array from csr_matrix >>> sparse_matrix = sp.sparse.csc_matrix([[0, 0, 3], [4, 0, 0]]) >>> sp.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix) >>> tmp = sp.sparse.load_npz('/tmp/sparse_matrix.npz') >>> sparse_array = sp.sparse.csr_array(tmp) rNz The file z+ does not contain a sparse array or matrix.r rZ_arrayZ_matrixzUnknown format ""rrrrr)rrrr r r z4Load is not implemented for sparse matrix of format r )rload PICKLE_KWARGSget ValueErroritemrstrdecodegetattrrrAttributeErrorr)rZloadedZ sparse_formatZ sparse_typeclserrrrPs:6     (  )T) numpyrZscipyr__all__dictr!rrrrrrs   E