ó ʽ÷Xc@`s{dZddlmZmZmZdZdddgZddlmZd „Z dd d „Z dd d „Z d „Z d S(s.Functions to extract parts of sparse matrices i(tdivisiontprint_functiontabsolute_importsrestructuredtext entfindttrilttriui(t coo_matrixcC`sMt|dtƒ}|jƒ|jdk}|j||j||j|fS(sJReturn the indices and values of the nonzero elements of a matrix Parameters ---------- A : dense or sparse matrix Matrix whose nonzero elements are desired. Returns ------- (I,J,V) : tuple of arrays I,J, and V contain the row indices, column indices, and values of the nonzero matrix entries. Examples -------- >>> from scipy.sparse import csr_matrix, find >>> A = csr_matrix([[7.0, 8.0, 0],[0, 0, 9.0]]) >>> find(A) (array([0, 0, 1], dtype=int32), array([0, 1, 2], dtype=int32), array([ 7., 8., 9.])) tcopyi(RtTruetsum_duplicatestdatatrowtcol(tAtnz_mask((s3/tmp/pip-build-7oUkmx/scipy/scipy/sparse/extract.pyRs cC`s>t|dtƒ}|j||jk}t||ƒj|ƒS(sReturn the lower triangular portion of a matrix in sparse format Returns the elements on or below the k-th diagonal of the matrix A. - k = 0 corresponds to the main diagonal - k > 0 is above the main diagonal - k < 0 is below the main diagonal Parameters ---------- A : dense or sparse matrix Matrix whose lower trianglar portion is desired. k : integer : optional The top-most diagonal of the lower triangle. format : string Sparse format of the result, e.g. format="csr", etc. Returns ------- L : sparse matrix Lower triangular portion of A in sparse format. See Also -------- triu : upper triangle in sparse format Examples -------- >>> from scipy.sparse import csr_matrix, tril >>> A = csr_matrix([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]], ... dtype='int32') >>> A.toarray() array([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]]) >>> tril(A).toarray() array([[1, 0, 0, 0, 0], [4, 5, 0, 0, 0], [0, 0, 8, 0, 0]]) >>> tril(A).nnz 4 >>> tril(A, k=1).toarray() array([[1, 2, 0, 0, 0], [4, 5, 0, 0, 0], [0, 0, 8, 9, 0]]) >>> tril(A, k=-1).toarray() array([[0, 0, 0, 0, 0], [4, 0, 0, 0, 0], [0, 0, 0, 0, 0]]) >>> tril(A, format='csc') <3x5 sparse matrix of type '' with 4 stored elements in Compressed Sparse Column format> R(RtFalseR R t _masked_cootasformat(R tktformattmask((s3/tmp/pip-build-7oUkmx/scipy/scipy/sparse/extract.pyR-s8cC`s>t|dtƒ}|j||jk}t||ƒj|ƒS(sReturn the upper triangular portion of a matrix in sparse format Returns the elements on or above the k-th diagonal of the matrix A. - k = 0 corresponds to the main diagonal - k > 0 is above the main diagonal - k < 0 is below the main diagonal Parameters ---------- A : dense or sparse matrix Matrix whose upper trianglar portion is desired. k : integer : optional The bottom-most diagonal of the upper triangle. format : string Sparse format of the result, e.g. format="csr", etc. Returns ------- L : sparse matrix Upper triangular portion of A in sparse format. See Also -------- tril : lower triangle in sparse format Examples -------- >>> from scipy.sparse import csr_matrix, triu >>> A = csr_matrix([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]], ... dtype='int32') >>> A.toarray() array([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]]) >>> triu(A).toarray() array([[1, 2, 0, 0, 3], [0, 5, 0, 6, 7], [0, 0, 8, 9, 0]]) >>> triu(A).nnz 8 >>> triu(A, k=1).toarray() array([[0, 2, 0, 0, 3], [0, 0, 0, 6, 7], [0, 0, 0, 9, 0]]) >>> triu(A, k=-1).toarray() array([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]]) >>> triu(A, format='csc') <3x5 sparse matrix of type '' with 8 stored elements in Compressed Sparse Column format> R(RRR R RR(R RRR((s3/tmp/pip-build-7oUkmx/scipy/scipy/sparse/extract.pyRjs8cC`sO|j|}|j|}|j|}t|||ffd|jd|jƒS(Ntshapetdtype(R R R RRR(R RR R R ((s3/tmp/pip-build-7oUkmx/scipy/scipy/sparse/extract.pyR§s   N(t__doc__t __future__RRRt __docformat__t__all__tcooRRtNoneRRR(((s3/tmp/pip-build-7oUkmx/scipy/scipy/sparse/extract.pyts ==