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
|
# pylint: disable-msg=W0611, W0612, W0511,R0201
"""Tests suite for maskedArray statistics.
:author: Pierre Gerard-Marchant
:contact: pierregm_at_uga_dot_edu
:version: $Id: test_mstats.py 3153 2007-07-09 15:38:26Z pierregm $
"""
__author__ = "Pierre GF Gerard-Marchant ($Author: pierregm $)"
__version__ = '1.0'
__revision__ = "$Revision: 3153 $"
__date__ = '$Date: 2007-07-09 08:38:26 -0700 (Mon, 09 Jul 2007) $'
import numpy
import maskedarray
from maskedarray import masked, masked_array
import maskedarray.testutils
from maskedarray.testutils import *
from maskedarray.mstats import *
#..............................................................................
class test_quantiles(NumpyTestCase):
"Base test class for MaskedArrays."
def __init__(self, *args, **kwds):
NumpyTestCase.__init__(self, *args, **kwds)
self.a = maskedarray.arange(1,101)
#
def test_1d_nomask(self):
"Test quantiles 1D - w/o mask."
a = self.a
assert_almost_equal(mquantiles(a, alphap=1., betap=1.),
[25.75, 50.5, 75.25])
assert_almost_equal(mquantiles(a, alphap=0, betap=1.),
[25., 50., 75.])
assert_almost_equal(mquantiles(a, alphap=0.5, betap=0.5),
[25.5, 50.5, 75.5])
assert_almost_equal(mquantiles(a, alphap=0., betap=0.),
[25.25, 50.5, 75.75])
assert_almost_equal(mquantiles(a, alphap=1./3, betap=1./3),
[25.41666667, 50.5, 75.5833333])
assert_almost_equal(mquantiles(a, alphap=3./8, betap=3./8),
[25.4375, 50.5, 75.5625])
assert_almost_equal(mquantiles(a), [25.45, 50.5, 75.55])#
#
def test_1d_mask(self):
"Test quantiles 1D - w/ mask."
a = self.a
a[1::2] = masked
assert_almost_equal(mquantiles(a, alphap=1., betap=1.),
[25.5, 50.0, 74.5])
assert_almost_equal(mquantiles(a, alphap=0, betap=1.),
[24., 49., 74.])
assert_almost_equal(mquantiles(a, alphap=0.5, betap=0.5),
[25., 50., 75.])
assert_almost_equal(mquantiles(a, alphap=0., betap=0.),
[24.5, 50.0, 75.5])
assert_almost_equal(mquantiles(a, alphap=1./3, betap=1./3),
[24.833333, 50.0, 75.166666])
assert_almost_equal(mquantiles(a, alphap=3./8, betap=3./8),
[24.875, 50., 75.125])
assert_almost_equal(mquantiles(a), [24.9, 50., 75.1])
#
def test_2d_nomask(self):
"Test quantiles 2D - w/o mask."
a = self.a
b = maskedarray.resize(a, (100,100))
assert_almost_equal(mquantiles(b), [25.45, 50.5, 75.55])
assert_almost_equal(mquantiles(b, axis=0), maskedarray.resize(a,(3,100)))
assert_almost_equal(mquantiles(b, axis=1),
maskedarray.resize([25.45, 50.5, 75.55], (100,3)))
#
def test_2d_mask(self):
"Test quantiles 2D - w/ mask."
a = self.a
a[1::2] = masked
b = maskedarray.resize(a, (100,100))
assert_almost_equal(mquantiles(b), [25., 50., 75.])
assert_almost_equal(mquantiles(b, axis=0), maskedarray.resize(a,(3,100)))
assert_almost_equal(mquantiles(b, axis=1),
maskedarray.resize([24.9, 50., 75.1], (100,3)))
class test_median(NumpyTestCase):
def __init__(self, *args, **kwds):
NumpyTestCase.__init__(self, *args, **kwds)
def test_2d(self):
"Tests median w/ 2D"
(n,p) = (101,30)
x = masked_array(numpy.linspace(-1.,1.,n),)
x[:10] = x[-10:] = masked
z = masked_array(numpy.empty((n,p), dtype=numpy.float_))
z[:,0] = x[:]
idx = numpy.arange(len(x))
for i in range(1,p):
numpy.random.shuffle(idx)
z[:,i] = x[idx]
assert_equal(mmedian(z[:,0]), 0)
assert_equal(mmedian(z), numpy.zeros((p,)))
def test_3d(self):
"Tests median w/ 3D"
x = maskedarray.arange(24).reshape(3,4,2)
x[x%3==0] = masked
assert_equal(mmedian(x,0), [[12,9],[6,15],[12,9],[18,15]])
x.shape = (4,3,2)
assert_equal(mmedian(x,0),[[99,10],[11,99],[13,14]])
x = maskedarray.arange(24).reshape(4,3,2)
x[x%5==0] = masked
assert_equal(mmedian(x,0), [[12,10],[8,9],[16,17]])
#..............................................................................
class test_trimming(NumpyTestCase):
#
def __init__(self, *args, **kwds):
NumpyTestCase.__init__(self, *args, **kwds)
#
def test_trim(self):
"Tests trimming."
x = maskedarray.arange(100)
assert_equal(trim_both(x).count(), 60)
assert_equal(trim_tail(x,tail='r').count(), 80)
x[50:70] = masked
trimx = trim_both(x)
assert_equal(trimx.count(), 48)
assert_equal(trimx._mask, [1]*16 + [0]*34 + [1]*20 + [0]*14 + [1]*16)
x._mask = nomask
x.shape = (10,10)
assert_equal(trim_both(x).count(), 60)
assert_equal(trim_tail(x).count(), 80)
#
def test_trimmedmean(self):
"Tests the trimmed mean."
data = masked_array([ 77, 87, 88,114,151,210,219,246,253,262,
296,299,306,376,428,515,666,1310,2611])
assert_almost_equal(trimmed_mean(data,0.1), 343, 0)
assert_almost_equal(trimmed_mean(data,0.2), 283, 0)
#
def test_trimmed_stde(self):
"Tests the trimmed mean standard error."
data = masked_array([ 77, 87, 88,114,151,210,219,246,253,262,
296,299,306,376,428,515,666,1310,2611])
assert_almost_equal(trimmed_stde(data,0.2), 56.1, 1)
#
def test_winsorization(self):
"Tests the Winsorization of the data."
data = masked_array([ 77, 87, 88,114,151,210,219,246,253,262,
296,299,306,376,428,515,666,1310,2611])
assert_almost_equal(winsorize(data).varu(), 21551.4, 1)
data[5] = masked
winsorized = winsorize(data)
assert_equal(winsorized.mask, data.mask)
#..............................................................................
class test_misc(NumpyTestCase):
def __init__(self, *args, **kwds):
NumpyTestCase.__init__(self, *args, **kwds)
def check_cov(self):
"Tests the cov function."
x = masked_array([[1,2,3],[4,5,6]], mask=[[1,0,0],[0,0,0]])
c = cov(x[0])
assert_equal(c, (x[0].anom()**2).sum())
c = cov(x[1])
assert_equal(c, (x[1].anom()**2).sum()/2.)
c = cov(x)
assert_equal(c[1,0], (x[0].anom()*x[1].anom()).sum())
###############################################################################
#------------------------------------------------------------------------------
if __name__ == "__main__":
NumpyTest().run()
|
