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"""test sparse matrix construction functions"""
import numpy as np
from numpy import array, matrix
from numpy.testing import *
from scipy.sparse import csr_matrix, coo_matrix
from scipy.sparse.construct import *
sparse_formats = ['csr','csc','coo','bsr','dia','lil','dok']
#TODO check whether format=XXX is respected
class TestConstructUtils(TestCase):
def test_spdiags(self):
diags1 = array( [[ 1, 2, 3, 4, 5]] )
diags2 = array( [[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9,10]] )
diags3 = array( [[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9,10],
[11,12,13,14,15]] )
cases = []
cases.append( (diags1, 0, 1, 1, [[1]]) )
cases.append( (diags1, [0], 1, 1, [[1]]) )
cases.append( (diags1, [0], 2, 1, [[1],[0]]) )
cases.append( (diags1, [0], 1, 2, [[1,0]]) )
cases.append( (diags1, [1], 1, 2, [[0,2]]) )
cases.append( (diags1,[-1], 1, 2, [[0,0]]) )
cases.append( (diags1, [0], 2, 2, [[1,0],[0,2]]) )
cases.append( (diags1,[-1], 2, 2, [[0,0],[1,0]]) )
cases.append( (diags1, [3], 2, 2, [[0,0],[0,0]]) )
cases.append( (diags1, [0], 3, 4, [[1,0,0,0],[0,2,0,0],[0,0,3,0]]) )
cases.append( (diags1, [1], 3, 4, [[0,2,0,0],[0,0,3,0],[0,0,0,4]]) )
cases.append( (diags1, [2], 3, 5, [[0,0,3,0,0],[0,0,0,4,0],[0,0,0,0,5]]) )
cases.append( (diags2, [0,2], 3, 3, [[1,0,8],[0,2,0],[0,0,3]]) )
cases.append( (diags2, [-1,0], 3, 4, [[6,0,0,0],[1,7,0,0],[0,2,8,0]]) )
cases.append( (diags2, [2,-3], 6, 6, [[0,0,3,0,0,0],
[0,0,0,4,0,0],
[0,0,0,0,5,0],
[6,0,0,0,0,0],
[0,7,0,0,0,0],
[0,0,8,0,0,0]]) )
cases.append( (diags3, [-1,0,1], 6, 6, [[ 6,12, 0, 0, 0, 0],
[ 1, 7,13, 0, 0, 0],
[ 0, 2, 8,14, 0, 0],
[ 0, 0, 3, 9,15, 0],
[ 0, 0, 0, 4,10, 0],
[ 0, 0, 0, 0, 5, 0]]) )
cases.append( (diags3, [-4,2,-1], 6, 5, [[ 0, 0, 8, 0, 0],
[11, 0, 0, 9, 0],
[ 0,12, 0, 0,10],
[ 0, 0,13, 0, 0],
[ 1, 0, 0,14, 0],
[ 0, 2, 0, 0,15]]) )
for d,o,m,n,result in cases:
assert_equal( spdiags(d,o,m,n).todense(), result )
def test_identity(self):
assert_equal(identity(1).toarray(), [[1]])
assert_equal(identity(2).toarray(), [[1,0],[0,1]])
I = identity(3, dtype='int8', format='dia')
assert_equal( I.dtype, np.dtype('int8') )
assert_equal( I.format, 'dia' )
for fmt in sparse_formats:
I = identity( 3, format=fmt )
assert_equal( I.format, fmt )
assert_equal( I.toarray(), [[1,0,0],[0,1,0],[0,0,1]])
def test_eye(self):
assert_equal(eye(1,1).toarray(), [[1]])
assert_equal(eye(2,3).toarray(), [[1,0,0],[0,1,0]])
assert_equal(eye(3,2).toarray(), [[1,0],[0,1],[0,0]])
assert_equal(eye(3,3).toarray(), [[1,0,0],[0,1,0],[0,0,1]])
assert_equal(eye(3,3,dtype='int16').dtype, np.dtype('int16'))
for m in [3, 5]:
for n in [3, 5]:
for k in range(-5,6):
assert_equal(eye(m, n, k=k).toarray(), np.eye(m, n, k=k))
def test_kron(self):
cases = []
cases.append(array([[ 0]]))
cases.append(array([[-1]]))
cases.append(array([[ 4]]))
cases.append(array([[10]]))
cases.append(array([[0],[0]]))
cases.append(array([[0,0]]))
cases.append(array([[1,2],[3,4]]))
cases.append(array([[0,2],[5,0]]))
cases.append(array([[0,2,-6],[8,0,14]]))
cases.append(array([[5,4],[0,0],[6,0]]))
cases.append(array([[5,4,4],[1,0,0],[6,0,8]]))
cases.append(array([[0,1,0,2,0,5,8]]))
cases.append(array([[0.5,0.125,0,3.25],[0,2.5,0,0]]))
for a in cases:
for b in cases:
result = kron(csr_matrix(a),csr_matrix(b)).todense()
expected = np.kron(a,b)
assert_array_equal(result,expected)
def test_kronsum(self):
cases = []
cases.append(array([[ 0]]))
cases.append(array([[-1]]))
cases.append(array([[ 4]]))
cases.append(array([[10]]))
cases.append(array([[1,2],[3,4]]))
cases.append(array([[0,2],[5,0]]))
cases.append(array([[0,2,-6],[8,0,14],[0,3,0]]))
cases.append(array([[1,0,0],[0,5,-1],[4,-2,8]]))
for a in cases:
for b in cases:
result = kronsum(csr_matrix(a),csr_matrix(b)).todense()
expected = np.kron(np.eye(len(b)), a) + \
np.kron(b, np.eye(len(a)))
assert_array_equal(result,expected)
def test_vstack(self):
A = coo_matrix([[1,2],[3,4]])
B = coo_matrix([[5,6]])
expected = matrix([[1, 2],
[3, 4],
[5, 6]])
assert_equal( vstack( [A,B] ).todense(), expected )
def test_hstack(self):
A = coo_matrix([[1,2],[3,4]])
B = coo_matrix([[5],[6]])
expected = matrix([[1, 2, 5],
[3, 4, 6]])
assert_equal( hstack( [A,B] ).todense(), expected )
def test_bmat(self):
A = coo_matrix([[1,2],[3,4]])
B = coo_matrix([[5],[6]])
C = coo_matrix([[7]])
expected = matrix([[1, 2, 5],
[3, 4, 6],
[0, 0, 7]])
assert_equal( bmat( [[A,B],[None,C]] ).todense(), expected )
expected = matrix([[1, 2, 0],
[3, 4, 0],
[0, 0, 7]])
assert_equal( bmat( [[A,None],[None,C]] ).todense(), expected )
expected = matrix([[0, 5],
[0, 6],
[7, 0]])
assert_equal( bmat( [[None,B],[C,None]] ).todense(), expected )
#TODO test failure cases
def test_lil_diags(self):
assert_array_equal(lil_diags([[1,2,3],[4,5],[6]],
[0,1,2],(3,3)).todense(),
[[1,4,6],
[0,2,5],
[0,0,3]])
assert_array_equal(lil_diags([[6],[4,5],[1,2,3]],
[2,1,0],(3,3)).todense(),
[[1,4,6],
[0,2,5],
[0,0,3]])
assert_array_equal(lil_diags([[6,7,8],[4,5],[1,2,3]],
[2,1,0],(3,3)).todense(),
[[1,4,6],
[0,2,5],
[0,0,3]])
assert_array_equal(lil_diags([[1,2,3],[4,5],[6]],
[0,-1,-2],(3,3)).todense(),
[[1,0,0],
[4,2,0],
[6,5,3]])
assert_array_equal(lil_diags([[6,7,8],[4,5]],
[-2,-1],(3,3)).todense(),
[[0,0,0],
[4,0,0],
[6,5,0]])
if __name__ == "__main__":
run_module_suite()
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