from numpy import array, kron, diag from numpy.testing import assert_, assert_equal from scipy.sparse import spfuncs from scipy.sparse import csr_matrix, csc_matrix, bsr_matrix from scipy.sparse._sparsetools import (csr_scale_rows, csr_scale_columns, bsr_scale_rows, bsr_scale_columns) from scipy.sparse.sputils import matrix class TestSparseFunctions(object): def test_scale_rows_and_cols(self): D = matrix([[1,0,0,2,3], [0,4,0,5,0], [0,0,6,7,0]]) #TODO expose through function S = csr_matrix(D) v = array([1,2,3]) csr_scale_rows(3,5,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), diag(v)*D) S = csr_matrix(D) v = array([1,2,3,4,5]) csr_scale_columns(3,5,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), D@diag(v)) # blocks E = kron(D,[[1,2],[3,4]]) S = bsr_matrix(E,blocksize=(2,2)) v = array([1,2,3,4,5,6]) bsr_scale_rows(3,5,2,2,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), diag(v)@E) S = bsr_matrix(E,blocksize=(2,2)) v = array([1,2,3,4,5,6,7,8,9,10]) bsr_scale_columns(3,5,2,2,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), E@diag(v)) E = kron(D,[[1,2,3],[4,5,6]]) S = bsr_matrix(E,blocksize=(2,3)) v = array([1,2,3,4,5,6]) bsr_scale_rows(3,5,2,3,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), diag(v)@E) S = bsr_matrix(E,blocksize=(2,3)) v = array([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]) bsr_scale_columns(3,5,2,3,S.indptr,S.indices,S.data,v) assert_equal(S.todense(), E@diag(v)) def test_estimate_blocksize(self): mats = [] mats.append([[0,1],[1,0]]) mats.append([[1,1,0],[0,0,1],[1,0,1]]) mats.append([[0],[0],[1]]) mats = [array(x) for x in mats] blks = [] blks.append([[1]]) blks.append([[1,1],[1,1]]) blks.append([[1,1],[0,1]]) blks.append([[1,1,0],[1,0,1],[1,1,1]]) blks = [array(x) for x in blks] for A in mats: for B in blks: X = kron(A,B) r,c = spfuncs.estimate_blocksize(X) assert_(r >= B.shape[0]) assert_(c >= B.shape[1]) def test_count_blocks(self): def gold(A,bs): R,C = bs I,J = A.nonzero() return len(set(zip(I//R,J//C))) mats = [] mats.append([[0]]) mats.append([[1]]) mats.append([[1,0]]) mats.append([[1,1]]) mats.append([[0,1],[1,0]]) mats.append([[1,1,0],[0,0,1],[1,0,1]]) mats.append([[0],[0],[1]]) for A in mats: for B in mats: X = kron(A,B) Y = csr_matrix(X) for R in range(1,6): for C in range(1,6): assert_equal(spfuncs.count_blocks(Y, (R, C)), gold(X, (R, C))) X = kron([[1,1,0],[0,0,1],[1,0,1]],[[1,1]]) Y = csc_matrix(X) assert_equal(spfuncs.count_blocks(X, (1, 2)), gold(X, (1, 2))) assert_equal(spfuncs.count_blocks(Y, (1, 2)), gold(X, (1, 2)))