Eia8SSKrSSKrSS/r\"SS9rSSjrSrg) Nsave_npzload_npzF) allow_picklec0nURS;a%URURURS9 OURS:XaURURS9 OzURS:XaOUR S:Xa%URUR URS9 O5URURS9 OS URS 3n[U5eURURRS 5URURS 9 [U[RR 5(aURS S9 U(a["R$"U40UD6 g["R&"U40UD6 g)aSave 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 >>> 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 >>> sparse_matrix.toarray() array([[0, 0, 3], [4, 0, 0]], dtype=int64) csccsrbsr)indicesindptrdia)offsetscoo)rowcol)coordsz4Save is not implemented for sparse matrix of format .ascii)formatshapedataT) _is_arrayN)rupdater r rndimrrrNotImplementedErrorencoderr isinstancespsparsesparraynpsavez_compressedsavez)filematrix compressed arrays_dictmsgs T/home/mande/repo/quber/.venv/lib/python3.13/site-packages/scipy/sparse/_matrix_io.pyrr s=\K }}--6>>&--H % 6>>2 %  ;;!    6::6::  >   fmm  4DV]]OSTU!#&&}}##G,ll [[ &"))++,,T* D0K0 %%c[R"U40[D6nURS5nUc[ SUS35eUR 5n[ U[5(dURS5nURS5(aUS-nOUS-n[[RU5nUS ;aU"US US US4USS9sSSS5 $US:XaU"US US4USS9sSSS5 $US:XaASU;aU"US US4USS9sSSS5 $U"US USUS44USS9sSSS5 $[SUS35e![an[ S US 35UeSnAff=f!,(df  g=f)a7Load 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 >>> 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 >>> 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.rr_array_matrixzUnknown format ""rrr r r)rr rrrrrz4Load is not implemented for sparse matrix of format r)r"load PICKLE_KWARGSget ValueErroritemrstrdecodegetattrrr AttributeErrorr)r%loaded sparse_format sparse_typeclses r*rrTsl  ' '6 8,  y/9:; ;%**, ---*009M ::k " "'(2K')3K G")) }6C 1 1vy(96(;KL#G_./ ( '2e #vy(9:&/R5 ( '6e #6!F6NF8,<=VG_U; ( '<vu (FG#G_.= ( 'B&)AANq'RS S G/ }A>?Q F G' ( 'sHA;E1E3E1E19E1 E1E1 E.E))E..E11 E?)T) numpyr"scipyr__all__dictr1rrr+r*rCs/ z "%( F&RXSr+