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
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
|
from numpy.testing import *
set_package_path()
import numpy.core;reload(numpy.core)
from numpy.core import *
import numpy as np
restore_path()
class TestCtor(NumpyTestCase):
def check_basic(self):
A = array([[1,2],[3,4]])
mA = matrix(A)
assert all(mA.A == A)
B = bmat("A,A;A,A")
C = bmat([[A,A], [A,A]])
D = array([[1,2,1,2],
[3,4,3,4],
[1,2,1,2],
[3,4,3,4]])
assert all(B.A == D)
assert all(C.A == D)
vec = arange(5)
mvec = matrix(vec)
assert mvec.shape == (1,5)
class TestProperties(NumpyTestCase):
def check_sum(self):
"""Test whether matrix.sum(axis=1) preserves orientation.
Fails in NumPy <= 0.9.6.2127.
"""
M = matrix([[1,2,0,0],
[3,4,0,0],
[1,2,1,2],
[3,4,3,4]])
sum0 = matrix([8,12,4,6])
sum1 = matrix([3,7,6,14]).T
sumall = 30
assert_array_equal(sum0, M.sum(axis=0))
assert_array_equal(sum1, M.sum(axis=1))
assert sumall == M.sum()
def check_basic(self):
import numpy.linalg as linalg
A = array([[1., 2.],
[3., 4.]])
mA = matrix(A)
assert allclose(linalg.inv(A), mA.I)
assert all(array(transpose(A) == mA.T))
assert all(array(transpose(A) == mA.H))
assert all(A == mA.A)
B = A + 2j*A
mB = matrix(B)
assert allclose(linalg.inv(B), mB.I)
assert all(array(transpose(B) == mB.T))
assert all(array(conjugate(transpose(B)) == mB.H))
def check_comparisons(self):
A = arange(100).reshape(10,10)
mA = matrix(A)
mB = matrix(A) + 0.1
assert all(mB == A+0.1)
assert all(mB == matrix(A+0.1))
assert not any(mB == matrix(A-0.1))
assert all(mA < mB)
assert all(mA <= mB)
assert all(mA <= mA)
assert not any(mA < mA)
assert not any(mB < mA)
assert all(mB >= mA)
assert all(mB >= mB)
assert not any(mB > mB)
assert all(mA == mA)
assert not any(mA == mB)
assert all(mB != mA)
assert not all(abs(mA) > 0)
assert all(abs(mB > 0))
def check_asmatrix(self):
A = arange(100).reshape(10,10)
mA = asmatrix(A)
A[0,0] = -10
assert A[0,0] == mA[0,0]
def check_noaxis(self):
A = matrix([[1,0],[0,1]])
assert A.sum() == matrix(2)
assert A.mean() == matrix(0.5)
class TestCasting(NumpyTestCase):
def check_basic(self):
A = arange(100).reshape(10,10)
mA = matrix(A)
mB = mA.copy()
O = ones((10,10), float64) * 0.1
mB = mB + O
assert mB.dtype.type == float64
assert all(mA != mB)
assert all(mB == mA+0.1)
mC = mA.copy()
O = ones((10,10), complex128)
mC = mC * O
assert mC.dtype.type == complex128
assert all(mA != mB)
class TestAlgebra(NumpyTestCase):
def check_basic(self):
import numpy.linalg as linalg
A = array([[1., 2.],
[3., 4.]])
mA = matrix(A)
B = identity(2)
for i in xrange(6):
assert allclose((mA ** i).A, B)
B = dot(B, A)
Ainv = linalg.inv(A)
B = identity(2)
for i in xrange(6):
assert allclose((mA ** -i).A, B)
B = dot(B, Ainv)
assert allclose((mA * mA).A, dot(A, A))
assert allclose((mA + mA).A, (A + A))
assert allclose((3*mA).A, (3*A))
class TestMatrixReturn(NumpyTestCase):
def check_instance_methods(self):
a = matrix([1.0], dtype='f8')
methodargs = {
'astype' : ('intc',),
'clip' : (0.0, 1.0),
'compress' : ([1],),
'repeat' : (1,),
'reshape' : (1,),
'swapaxes' : (0,0)
}
excluded_methods = [
'argmin', 'choose', 'dump', 'dumps', 'fill', 'getfield',
'getA', 'getA1', 'item', 'nonzero', 'put', 'putmask', 'resize',
'searchsorted', 'setflags', 'setfield', 'sort', 'take',
'tofile', 'tolist', 'tostring', 'all', 'any', 'sum',
'argmax', 'argmin', 'min', 'max', 'mean', 'var', 'ptp',
'prod', 'std', 'ctypes', 'itemset'
]
for attrib in dir(a):
if attrib.startswith('_') or attrib in excluded_methods:
continue
f = eval('a.%s' % attrib)
if callable(f):
# reset contents of a
a.astype('f8')
a.fill(1.0)
if attrib in methodargs:
args = methodargs[attrib]
else:
args = ()
b = f(*args)
assert type(b) is matrix, "%s" % attrib
assert type(a.real) is matrix
assert type(a.imag) is matrix
c,d = matrix([0.0]).nonzero()
assert type(c) is matrix
assert type(d) is matrix
class TestIndexing(NumpyTestCase):
def check_basic(self):
x = asmatrix(zeros((3,2),float))
y = zeros((3,1),float)
y[:,0] = [0.8,0.2,0.3]
x[:,1] = y>0.5
assert_equal(x, [[0,1],[0,0],[0,0]])
class TestNewScalarIndexing(NumpyTestCase):
def setUp(self):
self.a = matrix([[1, 2],[3,4]])
def check_dimesions(self):
a = self.a
x = a[0]
assert_equal(x.ndim, 2)
def check_array_from_matrix_list(self):
a = self.a
x = array([a, a])
assert_equal(x.shape, [2,2,2])
def check_array_to_list(self):
a = self.a
assert_equal(a.tolist(),[[1, 2], [3, 4]])
def check_fancy_indexing(self):
a = self.a
x = a[1, [0,1,0]]
assert isinstance(x, matrix)
assert_equal(x, matrix([[3, 4, 3]]))
x = a[[1,0]]
assert isinstance(x, matrix)
assert_equal(x, matrix([[3, 4], [1, 2]]))
x = a[[[1],[0]],[[1,0],[0,1]]]
assert isinstance(x, matrix)
assert_equal(x, matrix([[4, 3], [1, 2]]))
## def check_vector_element(self):
## x = matrix([[1,2,3],[4,5,6]])
## assert_equal(x[0][0],1)
## assert_equal(x[0].shape,(1,3))
## assert_equal(x[:,0].shape,(2,1))
## x = matrix(0)
## assert_equal(x[0,0],0)
## assert_equal(x[0],0)
## assert_equal(x[:,0].shape,x.shape)
def check_scalar_indexing(self):
x = asmatrix(zeros((3,2),float))
assert_equal(x[0,0],x[0][0])
def check_row_column_indexing(self):
x = asmatrix(np.eye(2))
assert_array_equal(x[0,:],[[1,0]])
assert_array_equal(x[1,:],[[0,1]])
assert_array_equal(x[:,0],[[1],[0]])
assert_array_equal(x[:,1],[[0],[1]])
def check_boolean_indexing(self):
A = arange(6)
A.shape = (3,2)
x = asmatrix(A)
assert_array_equal(x[:,array([True,False])],x[:,0])
assert_array_equal(x[array([True,False,False]),:],x[0,:])
def check_list_indexing(self):
A = arange(6)
A.shape = (3,2)
x = asmatrix(A)
assert_array_equal(x[:,[1,0]],x[:,::-1])
assert_array_equal(x[[2,1,0],:],x[::-1,:])
if __name__ == "__main__":
NumpyTest().run()
|
