+ LV-ja@^RIt^RItRR.t]!RR7tRRltRtR#) Nsave_npzload_npzF) allow_picklecF/pVPR9d)VPVPVPR7MVPR8XdVPVPR7MVPR8XdWVP ^8Xd)VPVP VPR7M8VPVPR7MRVP R2p\V4hVPVPPR 4VPVPR 7\V\PP 4'dVPR R 7V'd\"P$!V3/VBR #\"P&!V3/VBR #)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) )indicesindptrdia)offsetscoo)rowcol)coordsz4Save is not implemented for sparse matrix of format .ascii)formatshapedataT) _is_arrayNcsccsrbsr)rupdaterrr ndimr r rNotImplementedErrorencoderr isinstancespsparsesparraynpsavez_compressedsavez)filematrix compressed arrays_dictmsgs&&& h/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/scipy/sparse/_matrix_io.pyrr s=\K }}--6>>&--H % 6>>2 %  ;;!    6::6::  >   fmm  4DV]]OSTU!#&&}}##G,ll [[ &"))++,,T* D0K0 %%c\P!V3/\B;_uu_4pVPR4pVf\ RV R24hVP 4p\ V\4'gVPR4pVPR4'd VR,pM VR,p\\PV 4pTR9d4T!TR ,TR ,TR ,3TR,R7uuRRR4#TR8Xd,T!TR ,TR,3TR,R7uuRRR4#TR8XdgRT9d,T!TR ,TR,3TR,R7uuRRR4#T!TR ,TR,TR,33TR,R7uuRRR4#\RT R24h \dp\ R T R 24ThRp?ii;i +'giR#;i)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 ""rrrr)rr r r rr r z4Load is not implemented for sparse matrix of format rr)r!load PICKLE_KWARGSget ValueErroritemrstrdecodegetattrrrAttributeErrorr)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' ( ' 'sNA2GG+F./G'G2.G+)GG. G9G  GG G" )T) numpyr!scipyr__all__dictr0rrr*r)rBs/ z "%( F&RXSr*