1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
|
#!/usr/bin/env python
#
""" Test functions for UMFPACK wrappers
"""
from numpy import transpose, array, arange
import random
from numpy.testing import *
set_package_path()
from scipy import linsolve, rand, matrix, diag, eye
from scipy.sparse import csc_matrix, dok_matrix, spdiags
import numpy as nm
import scipy.linsolve.umfpack as um
restore_path()
class test_solvers(ScipyTestCase):
"""Tests inverting a sparse linear system"""
def check_solve_complex_without_umfpack(self):
"""Solve: single precision complex"""
linsolve.use_solver( {'useUmfpack' : False} )
a = self.a.astype('F')
b = self.b
x = linsolve.spsolve(a, b)
#print x
#print "Error: ", a*x-b
assert_array_almost_equal(a*x, b)
def check_solve_without_umfpack(self):
"""Solve: single precision"""
linsolve.use_solver( {'useUmfpack' : False} )
a = self.a.astype('f')
b = self.b
x = linsolve.spsolve(a, b.astype('f'))
#print x
#print "Error: ", a*x-b
assert_array_almost_equal(a*x, b)
def check_solve_complex_umfpack(self):
"""Solve with UMFPACK: double precision complex"""
linsolve.use_solver( {'useUmfpack' : True} )
a = self.a.astype('D')
b = self.b
x = linsolve.spsolve(a, b)
#print x
#print "Error: ", a*x-b
assert_array_almost_equal(a*x, b)
def check_solve_umfpack(self):
"""Solve with UMFPACK: double precision"""
linsolve.use_solver( {'useUmfpack' : True} )
a = self.a.astype('d')
b = self.b
x = linsolve.spsolve(a, b)
#print x
#print "Error: ", a*x-b
assert_array_almost_equal(a*x, b)
def setUp(self):
self.a = spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]], [0, 1], 5, 5)
#print "The sparse matrix (constructed from diagonals):"
#print self.a
self.b = array([1, 2, 3, 4, 5])
class test_factorization(ScipyTestCase):
"""Tests factorizing a sparse linear system"""
def check_complex_lu(self):
"""Getting factors of complex matrix"""
umfpack = um.UmfpackContext("zi")
for A in self.complex_matrices:
umfpack.numeric(A)
(L,U,P,Q,R,do_recip) = umfpack.lu(A)
L = L.todense()
U = U.todense()
A = A.todense()
if not do_recip: R = 1.0/R
R = matrix(diag(R))
P = eye(A.shape[0])[P,:]
Q = eye(A.shape[1])[:,Q]
assert_array_almost_equal(P*R*A*Q,L*U)
def check_real_lu(self):
"""Getting factors of real matrix"""
umfpack = um.UmfpackContext("di")
for A in self.real_matrices:
umfpack.numeric(A)
(L,U,P,Q,R,do_recip) = umfpack.lu(A)
L = L.todense()
U = U.todense()
A = A.todense()
if not do_recip: R = 1.0/R
R = matrix(diag(R))
P = eye(A.shape[0])[P,:]
Q = eye(A.shape[1])[:,Q]
assert_array_almost_equal(P*R*A*Q,L*U)
def setUp(self):
random.seed(0) #make tests repeatable
self.real_matrices = []
self.real_matrices.append(spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]],
[0, 1], 5, 5))
self.real_matrices.append(spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]],
[0, 1], 4, 5))
self.real_matrices.append(spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]],
[0, 2], 5, 5))
self.real_matrices.append(csc_matrix(rand(3,3)))
self.real_matrices.append(csc_matrix(rand(5,4)))
self.real_matrices.append(csc_matrix(rand(4,5)))
self.complex_matrices = [x.astype(nm.complex128)
for x in self.real_matrices]
if __name__ == "__main__":
ScipyTest().run()
|
