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
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from ...tests.helper import pytest
from ..stretch import (LinearStretch, SqrtStretch, PowerStretch,
PowerDistStretch, SquaredStretch, LogStretch,
AsinhStretch, SinhStretch, HistEqStretch,
ContrastBiasStretch)
DATA = np.array([0.00, 0.25, 0.50, 0.75, 1.00])
RESULTS = {}
RESULTS[LinearStretch()] = np.array([0.00, 0.25, 0.50, 0.75, 1.00])
RESULTS[SqrtStretch()] = np.array([0., 0.5, 0.70710678, 0.8660254, 1.])
RESULTS[SquaredStretch()] = np.array([0., 0.0625, 0.25, 0.5625, 1.])
RESULTS[PowerStretch(0.5)] = np.array([0., 0.5, 0.70710678, 0.8660254, 1.])
RESULTS[PowerDistStretch()] = np.array([0., 0.004628, 0.030653, 0.177005, 1.])
RESULTS[LogStretch()] = np.array([0., 0.799776, 0.899816, 0.958408, 1.])
RESULTS[AsinhStretch()] = np.array([0., 0.549402, 0.77127, 0.904691, 1.])
RESULTS[SinhStretch()] = np.array([0., 0.082085, 0.212548, 0.46828, 1.])
RESULTS[ContrastBiasStretch(contrast=2., bias=0.4)] = np.array([-0.3, 0.2,
0.7, 1.2,
1.7])
RESULTS[HistEqStretch(DATA)] = DATA
RESULTS[HistEqStretch(DATA[::-1])] = DATA
RESULTS[HistEqStretch(DATA ** 0.5)] = np.array([0., 0.125, 0.25, 0.5674767,
1.])
class TestStretch(object):
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_no_clip(self, stretch):
np.testing.assert_allclose(stretch(DATA, clip=False),
RESULTS[stretch], atol=1.e-6)
@pytest.mark.parametrize('ndim', [2, 3])
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_clip_ndimensional(self, stretch, ndim):
new_shape = DATA.shape + (1,) * ndim
np.testing.assert_allclose(stretch(DATA.reshape(new_shape),
clip=True).ravel(),
np.clip(RESULTS[stretch], 0., 1),
atol=1.e-6)
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_clip(self, stretch):
np.testing.assert_allclose(stretch(DATA, clip=True),
np.clip(RESULTS[stretch], 0., 1),
atol=1.e-6)
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_inplace(self, stretch):
data_in = DATA.copy()
result = np.zeros(DATA.shape)
stretch(data_in, out=result, clip=False)
np.testing.assert_allclose(result, RESULTS[stretch], atol=1.e-6)
np.testing.assert_allclose(data_in, DATA)
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_round_trip(self, stretch):
np.testing.assert_allclose(stretch.inverse(stretch(DATA, clip=False),
clip=False), DATA)
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_inplace_roundtrip(self, stretch):
result = np.zeros(DATA.shape)
stretch(DATA, out=result, clip=False)
stretch.inverse(result, out=result, clip=False)
np.testing.assert_allclose(result, DATA)
@pytest.mark.parametrize('stretch', RESULTS.keys())
def test_double_inverse(self, stretch):
np.testing.assert_allclose(stretch.inverse.inverse(DATA),
stretch(DATA), atol=1.e-6)
def test_inverted(self):
stretch_1 = SqrtStretch().inverse
stretch_2 = PowerStretch(2)
np.testing.assert_allclose(stretch_1(DATA),
stretch_2(DATA))
def test_chaining(self):
stretch_1 = SqrtStretch() + SqrtStretch()
stretch_2 = PowerStretch(0.25)
stretch_3 = PowerStretch(4.)
np.testing.assert_allclose(stretch_1(DATA),
stretch_2(DATA))
np.testing.assert_allclose(stretch_1.inverse(DATA),
stretch_3(DATA))
def test_clip_invalid():
stretch = SqrtStretch()
values = stretch([-1., 0., 0.5, 1., 1.5])
np.testing.assert_allclose(values, [0., 0., 0.70710678, 1., 1.])
values = stretch([-1., 0., 0.5, 1., 1.5], clip=False)
np.testing.assert_allclose(values, [np.nan, 0., 0.70710678, 1., 1.2247448])
|
