98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
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)))
|