peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/scipy
/sparse
/tests
/test_spfuncs.py
from numpy import array, kron, diag | |
from numpy.testing import assert_, assert_equal | |
from scipy.sparse import _spfuncs as 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) | |
class TestSparseFunctions: | |
def test_scale_rows_and_cols(self): | |
D = array([[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.toarray(), 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.toarray(), 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.toarray(), 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.toarray(), 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.toarray(), 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.toarray(), 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))) | |