|
1
|
|
|
#!/usr/bin/env python |
|
2
|
|
|
# -*- coding: utf-8 -*- |
|
3
|
|
|
|
|
4
|
|
|
# Copyright (c) 2014-2018 Adam.Dybbroe |
|
5
|
|
|
|
|
6
|
|
|
# Author(s): |
|
7
|
|
|
|
|
8
|
|
|
# Adam.Dybbroe <[email protected]> |
|
9
|
|
|
|
|
10
|
|
|
# This program is free software: you can redistribute it and/or modify |
|
11
|
|
|
# it under the terms of the GNU General Public License as published by |
|
12
|
|
|
# the Free Software Foundation, either version 3 of the License, or |
|
13
|
|
|
# (at your option) any later version. |
|
14
|
|
|
|
|
15
|
|
|
# This program is distributed in the hope that it will be useful, |
|
16
|
|
|
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|
17
|
|
|
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|
18
|
|
|
# GNU General Public License for more details. |
|
19
|
|
|
|
|
20
|
|
|
# You should have received a copy of the GNU General Public License |
|
21
|
|
|
# along with this program. If not, see <http://www.gnu.org/licenses/>. |
|
22
|
|
|
|
|
23
|
|
|
"""Testing the radiance to brightness temperature conversion""" |
|
24
|
|
|
|
|
25
|
|
|
from pyspectral.radiance_tb_conversion import RadTbConverter |
|
26
|
|
|
from pyspectral.radiance_tb_conversion import SeviriRadTbConverter |
|
27
|
|
|
from pyspectral.utils import get_central_wave |
|
28
|
|
|
import unittest |
|
29
|
|
|
import numpy as np |
|
30
|
|
|
from mock import patch |
|
31
|
|
|
|
|
32
|
|
|
TEST_TBS = np.array([200., 270., 300., 302., 350.], dtype='float32') |
|
33
|
|
|
|
|
34
|
|
|
TRUE_RADS = np.array([856.937353205, 117420.385297, |
|
35
|
|
|
479464.582505, 521412.9511, 2928735.18944], |
|
36
|
|
|
dtype='float64') |
|
37
|
|
|
TRUE_RADS_SEVIRI = np.array([2.391091e-08, |
|
38
|
|
|
2.559173e-06, |
|
39
|
|
|
9.797091e-06, |
|
40
|
|
|
1.061431e-05, |
|
41
|
|
|
5.531423e-05], |
|
42
|
|
|
dtype='float64') |
|
43
|
|
|
|
|
44
|
|
|
TEST_RSR = {'20': {}} |
|
45
|
|
|
TEST_RSR['20']['det-1'] = {} |
|
46
|
|
|
TEST_RSR['20']['det-1']['wavelength'] = np.array([ |
|
47
|
|
|
3.6123999, 3.6163599, 3.6264927, 3.6363862, 3.646468, |
|
48
|
|
|
3.6564937, 3.6664478, 3.6765388, 3.6865413, 3.6964585, |
|
49
|
|
|
3.7065142, 3.716509, 3.7264658, 3.7364102, 3.7463682, |
|
50
|
|
|
3.7563652, 3.7664226, 3.7763396, 3.7863384, 3.7964207, |
|
51
|
|
|
3.8063589, 3.8163606, 3.8264089, 3.8364836, 3.8463381, |
|
52
|
|
|
3.8563975, 3.8664163, 3.8763755, 3.8864797, 3.8964978, |
|
53
|
|
|
3.9064275, 3.9164873, 3.9264729, 3.9364026, 3.9465107, |
|
54
|
|
|
3.9535347], dtype='double') |
|
55
|
|
|
|
|
56
|
|
|
TEST_RSR['20']['det-1']['response'] = np.array([ |
|
57
|
|
|
0.01, 0.0118, 0.01987, 0.03226, 0.05028, 0.0849, |
|
58
|
|
|
0.16645, 0.33792, 0.59106, 0.81815, 0.96077, 0.92855, |
|
59
|
|
|
0.86008, 0.8661, 0.87697, 0.85412, 0.88922, 0.9541, |
|
60
|
|
|
0.95687, 0.91037, 0.91058, 0.94256, 0.94719, 0.94808, |
|
61
|
|
|
1., 0.92676, 0.67429, 0.44715, 0.27762, 0.14852, |
|
62
|
|
|
0.07141, 0.04151, 0.02925, 0.02085, 0.01414, 0.01], dtype='double') |
|
63
|
|
|
|
|
64
|
|
|
TEST_RSR['20']['det-1']['central_wavelength'] = get_central_wave(TEST_RSR['20']['det-1']['wavelength'], |
|
65
|
|
|
TEST_RSR['20']['det-1']['response']) |
|
66
|
|
|
|
|
67
|
|
|
|
|
68
|
|
|
SEV_RSR = {'IR3.9': {}} |
|
69
|
|
|
SEV_RSR['IR3.9']['det-1'] = {} |
|
70
|
|
|
WAVN = np.array([2083.33325195, 2091.00048828, 2098.72387695, 2106.50488281, |
|
71
|
|
|
2114.34375, 2122.24121094, 2130.19775391, 2138.21435547, |
|
72
|
|
|
2146.29101562, 2154.42944336, 2162.62963867, 2170.89257812, |
|
73
|
|
|
2179.21899414, 2187.609375, 2196.06494141, 2204.58569336, |
|
74
|
|
|
2213.17285156, 2221.82714844, 2230.54956055, 2239.34082031, |
|
75
|
|
|
2248.20141602, 2257.13256836, 2266.13500977, 2275.20947266, |
|
76
|
|
|
2284.35668945, 2293.57788086, 2302.87402344, 2312.24584961, |
|
77
|
|
|
2321.6940918, 2331.21972656, 2340.82421875, 2350.5078125, |
|
78
|
|
|
2360.27197266, 2370.11743164, 2380.0456543, 2390.05737305, |
|
79
|
|
|
2400.15356445, 2410.33544922, 2420.60449219, 2430.9609375, |
|
80
|
|
|
2441.40625, 2451.94189453, 2462.5690918, 2473.28857422, |
|
81
|
|
|
2484.10180664, 2495.01025391, 2506.01416016, 2517.11645508, |
|
82
|
|
|
2528.31713867, 2539.61816406, 2551.02050781, 2562.52587891, |
|
83
|
|
|
2574.13525391, 2585.8503418, 2597.67236328, 2609.60351562, |
|
84
|
|
|
2621.64453125, 2633.796875, 2646.06274414, 2658.44335938, |
|
85
|
|
|
2670.94018555, 2683.55541992, 2696.28979492, 2709.14624023, |
|
86
|
|
|
2722.12548828, 2735.22973633, 2748.4609375, 2761.82055664, |
|
87
|
|
|
2775.31103516, 2788.93359375, 2802.69042969, 2816.58422852, |
|
88
|
|
|
2830.61621094, 2844.78833008, 2859.10351562, 2873.56323242, |
|
89
|
|
|
2888.17016602, 2902.92626953, 2917.83374023, 2932.89550781, |
|
90
|
|
|
2948.11328125, 2963.48999023, 2979.02758789, 2994.72924805, |
|
91
|
|
|
3010.59741211, 3026.63452148, 3042.84326172, 3059.22705078, |
|
92
|
|
|
3075.78735352, 3092.52880859, 3109.45263672, 3126.56323242, |
|
93
|
|
|
3143.86328125, 3161.35571289, 3179.04394531, 3196.9309082, |
|
94
|
|
|
3215.02050781, 3233.31640625, 3251.82104492, 3270.5390625], |
|
95
|
|
|
dtype='float32') |
|
96
|
|
|
|
|
97
|
|
|
RESP = np.array([5.85991074e-07, 5.05963471e-05, 1.54738867e-04, |
|
98
|
|
|
8.75972546e-07, 2.23005936e-05, 6.17855985e-05, |
|
99
|
|
|
1.41724333e-04, 1.87453145e-06, 3.19355922e-06, |
|
100
|
|
|
1.08511595e-04, 2.12896630e-04, 5.65914146e-04, |
|
101
|
|
|
5.93333738e-04, 2.45316158e-04, 1.77410198e-04, |
|
102
|
|
|
3.18188017e-04, 5.27926895e-05, 1.41405777e-04, |
|
103
|
|
|
1.64295849e-03, 2.69834511e-03, 4.89762053e-03, |
|
104
|
|
|
2.71760323e-03, 2.49398337e-03, 4.83754929e-03, |
|
105
|
|
|
1.08462553e-02, 5.53890038e-03, 8.30772892e-03, |
|
106
|
|
|
1.33131407e-02, 2.89320182e-02, 4.69624363e-02, |
|
107
|
|
|
6.85162693e-02, 1.17517754e-01, 2.26854816e-01, |
|
108
|
|
|
3.69935125e-01, 5.16705751e-01, 6.70479536e-01, |
|
109
|
|
|
8.18419516e-01, 9.00036395e-01, 9.59491372e-01, |
|
110
|
|
|
9.60837066e-01, 9.63596582e-01, 9.77563441e-01, |
|
111
|
|
|
9.98380423e-01, 9.98030603e-01, 9.93735969e-01, |
|
112
|
|
|
9.84225452e-01, 9.98880267e-01, 1.00000000e+00, |
|
113
|
|
|
9.90870714e-01, 9.75207090e-01, 9.68391836e-01, |
|
114
|
|
|
9.73213553e-01, 9.75407243e-01, 9.57278728e-01, |
|
115
|
|
|
9.68693912e-01, 9.78199899e-01, 9.73649919e-01, |
|
116
|
|
|
9.81804073e-01, 9.71176386e-01, 9.72167253e-01, |
|
117
|
|
|
9.60459769e-01, 9.40638900e-01, 9.24033165e-01, |
|
118
|
|
|
9.16043043e-01, 8.79902899e-01, 8.11953366e-01, |
|
119
|
|
|
6.69838488e-01, 4.60774124e-01, 2.68200457e-01, |
|
120
|
|
|
1.34857073e-01, 6.40064552e-02, 3.31763141e-02, |
|
121
|
|
|
1.24335978e-02, 6.22070907e-03, 2.53354642e-03, |
|
122
|
|
|
1.81269188e-05, 4.63075470e-03, 1.78873568e-04, |
|
123
|
|
|
1.01367442e-03, 1.28920563e-03, 4.91134451e-05, |
|
124
|
|
|
6.77187869e-04, 2.44393433e-03, 2.62995227e-03, |
|
125
|
|
|
6.38825062e-04, 1.70478446e-03, 1.03909883e-03, |
|
126
|
|
|
1.27910142e-04, 2.95412028e-04, 8.80619162e-04, |
|
127
|
|
|
2.42782771e-04, 7.55985593e-06, 3.55220342e-04, |
|
128
|
|
|
8.71264958e-04, 2.01994626e-04, 8.14358555e-06, |
|
129
|
|
|
2.14082262e-04, 1.07610082e-04, 5.82974189e-06, |
|
130
|
|
|
4.16795141e-04], dtype='float32') |
|
131
|
|
|
|
|
132
|
|
|
SEV_RSR['IR3.9']['det-1']['wavenumber'] = WAVN |
|
133
|
|
|
SEV_RSR['IR3.9']['det-1']['response'] = RESP |
|
134
|
|
|
|
|
135
|
|
|
VIIRS_RSR = {'I04': {}} |
|
136
|
|
|
VIIRS_RSR['I04']['det-1'] = {} |
|
137
|
|
|
I4_WAVELENGTH = np.array([0.0833394, 0.1022195, 0.130236, 0.16001581, 0.19955561, |
|
138
|
|
|
0.24286181, 0.29621401, 0.35013291, 0.41273189, 0.47668689, |
|
139
|
|
|
0.54601961, 0.59299731, 0.64459503, 0.67387378, 0.71287841, |
|
140
|
|
|
0.74619591, 0.7725302, 0.7957828, 0.79547352, 0.82856262, |
|
141
|
|
|
0.82099879, 0.83992928, 0.84202057, 0.84400982, 0.83308381, |
|
142
|
|
|
0.85475749, 0.83983958, 0.84575808, 0.84324688, 0.84332639, |
|
143
|
|
|
0.82304168, 0.83476579, 0.83626682, 0.82226139, 0.82139379, |
|
144
|
|
|
0.81928378, 0.82413059, 0.8331368, 0.84240448, 0.858217, |
|
145
|
|
|
0.86793423, 0.88952613, 0.91635668, 0.92613328, 0.92169321, |
|
146
|
|
|
0.94074869, 0.94403398, 0.95178741, 0.95512831, 0.96271777, |
|
147
|
|
|
0.965684, 0.94473231, 0.95947689, 0.94794488, 0.93577278, |
|
148
|
|
|
0.91731572, 0.8803544, 0.86248928, 0.86056131, 0.86297452, |
|
149
|
|
|
0.88312691, 0.91132039, 0.94761842, 0.96859932, 0.97495008, |
|
150
|
|
|
0.97335148, 0.9552781, 0.98041701, 0.97318149, 0.97128302, |
|
151
|
|
|
0.9795289, 0.97638869, 0.98553509, 0.97625399, 0.98542649, |
|
152
|
|
|
0.98815048, 0.99496758, 0.98651272, 0.97830129, 0.95645708, |
|
153
|
|
|
0.95295483, 0.91510731, 0.93925321, 0.9297964, 0.93927532, |
|
154
|
|
|
0.942056, 0.95784009, 0.96388292, 0.96057928, 0.97130299, |
|
155
|
|
|
0.98001093, 0.9716453, 0.96652049, 0.97841442, 0.96985549, |
|
156
|
|
|
0.97240448, 1., 0.99910343, 0.99543452, 0.98577332, |
|
157
|
|
|
0.94873059, 0.91984153, 0.85985827, 0.78354579, 0.71279228, |
|
158
|
|
|
0.60751349, 0.50684202, 0.41465551, 0.33605599, 0.2688629, |
|
159
|
|
|
0.2085918, 0.1671019, 0.1307321, 0.1050327, 0.0833778], |
|
160
|
|
|
dtype='float32') |
|
161
|
|
|
I4_RESPONSE = np.array([3.51000977, 3.51399684, 3.51799059, 3.52198982, 3.52599406, |
|
162
|
|
|
3.53000283, 3.53401518, 3.53803015, 3.54204679, 3.54595184, |
|
163
|
|
|
3.54996943, 3.55398607, 3.55800128, 3.56201053, 3.56601906, |
|
164
|
|
|
3.5700233, 3.57402253, 3.57790327, 3.58199954, 3.58597946, |
|
165
|
|
|
3.58995199, 3.59402514, 3.59798145, 3.60203815, 3.60597777, |
|
166
|
|
|
3.60990882, 3.61404991, 3.61796427, 3.62197948, 3.62598753, |
|
167
|
|
|
3.62998843, 3.63398266, 3.63797164, 3.64195538, 3.64604282, |
|
168
|
|
|
3.65001845, 3.65399408, 3.65796638, 3.66193819, 3.66601968, |
|
169
|
|
|
3.66999412, 3.67408037, 3.67806101, 3.68194032, 3.68593097, |
|
170
|
|
|
3.69003725, 3.69404101, 3.69805193, 3.70196342, 3.70599008, |
|
171
|
|
|
3.70991707, 3.71407032, 3.71801329, 3.72207284, 3.72603106, |
|
172
|
|
|
3.7299962, 3.73396754, 3.73805571, 3.74203897, 3.74602699, |
|
173
|
|
|
3.75001884, 3.75401402, 3.75789952, 3.76200795, 3.76600695, |
|
174
|
|
|
3.77000499, 3.77400184, 3.7779963, 3.78209734, 3.78597236, |
|
175
|
|
|
3.7899549, 3.79393172, 3.79801106, 3.80197453, 3.80603933, |
|
176
|
|
|
3.80998778, 3.81403589, 3.81796741, 3.8219986, 3.82602286, |
|
177
|
|
|
3.8300364, 3.83393359, 3.83803844, 3.84202766, 3.84600878, |
|
178
|
|
|
3.84998393, 3.85395193, 3.85802197, 3.86208749, 3.86604047, |
|
179
|
|
|
3.86999369, 3.87394214, 3.87799811, 3.88194633, 3.88600349, |
|
180
|
|
|
3.88995481, 3.89401698, 3.89797616, 3.90193915, 3.90601683, |
|
181
|
|
|
3.90999269, 3.91408467, 3.91796803, 3.92196584, 3.92597222, |
|
182
|
|
|
3.92998838, 3.93401074, 3.93804169, 3.94197202, 3.9459095, |
|
183
|
|
|
3.95007277, 3.95402312, 3.95797944, 3.96194077, 3.96590614], dtype='float32') |
|
184
|
|
|
|
|
185
|
|
|
VIIRS_RSR['I04']['det-1']['wavelength'] = I4_WAVELENGTH |
|
186
|
|
|
VIIRS_RSR['I04']['det-1']['response'] = I4_RESPONSE |
|
187
|
|
|
VIIRS_RSR['I04']['det-1']['central_wavelength'] = 3.7460763637226693 |
|
188
|
|
|
|
|
189
|
|
|
VIIRS_RSR['M12'] = {} |
|
190
|
|
|
VIIRS_RSR['M12']['det-1'] = {} |
|
191
|
|
|
M12_WAVELENGTH = np.array([3.50669217, 3.51322079, 3.51976728, 3.52643943, 3.53301215, |
|
192
|
|
|
3.53959203, 3.546175, 3.55287051, 3.55944896, 3.56601906, |
|
193
|
|
|
3.57257748, 3.57923317, 3.58575845, 3.59237552, 3.59907913, |
|
194
|
|
|
3.60554028, 3.61219764, 3.6188333, 3.62544608, 3.63204026, |
|
195
|
|
|
3.63861847, 3.64518261, 3.65184593, 3.65839601, 3.6649456, |
|
196
|
|
|
3.67160821, 3.67827654, 3.68485141, 3.69144225, 3.69805193, |
|
197
|
|
|
3.7045753, 3.71122766, 3.71779394, 3.72449064, 3.73098779, |
|
198
|
|
|
3.73761344, 3.74425411, 3.75079513, 3.75745511, 3.76400733, |
|
199
|
|
|
3.77067137, 3.77721882, 3.78386998, 3.79039693, 3.79702044, |
|
200
|
|
|
3.80362248, 3.81020689, 3.81687641, 3.82341433, 3.8300364, |
|
201
|
|
|
3.83652687, 3.84321165, 3.84976912, 3.85630941, 3.86294222], dtype='float32') |
|
202
|
|
|
M12_RESPONSE = np.array([0.0064421, 0.0084001, 0.0109988, 0.0143879, 0.0197545, |
|
203
|
|
|
0.0270981, 0.0370352, 0.0512599, 0.0715467, 0.0987869, |
|
204
|
|
|
0.1393604, 0.195684, 0.26579589, 0.36917099, 0.509821, |
|
205
|
|
|
0.63852757, 0.74241519, 0.82375473, 0.87010688, 0.89455551, |
|
206
|
|
|
0.91357207, 0.92787379, 0.95018548, 0.97198248, 0.98594999, |
|
207
|
|
|
0.99682951, 1., 0.99573219, 0.98468697, 0.98146093, |
|
208
|
|
|
0.97062051, 0.95142138, 0.927858, 0.9119851, 0.89879388, |
|
209
|
|
|
0.89661211, 0.8987267, 0.89272481, 0.87440962, 0.83271909, |
|
210
|
|
|
0.77336842, 0.69556081, 0.60315871, 0.49959281, 0.39389691, |
|
211
|
|
|
0.302542, 0.2273816, 0.16862389, 0.1276994, 0.0968111, |
|
212
|
|
|
0.0743906, 0.0573153, 0.0445903, 0.0345158, 0.0268065], dtype='float32') |
|
213
|
|
|
|
|
214
|
|
|
VIIRS_RSR['M12']['det-1']['wavelength'] = M12_WAVELENGTH |
|
215
|
|
|
VIIRS_RSR['M12']['det-1']['response'] = M12_RESPONSE |
|
216
|
|
|
VIIRS_RSR['M12']['det-1']['central_wavelength'] = 3.6954317366170288 |
|
217
|
|
|
|
|
218
|
|
|
|
|
219
|
|
|
class RSRTestDataModis(object): |
|
220
|
|
|
|
|
221
|
|
|
"""RSR test data for Aqua Modis""" |
|
222
|
|
|
|
|
223
|
|
|
def __init__(self): |
|
224
|
|
|
"""Making a testdata set of relative spectral responses""" |
|
225
|
|
|
|
|
226
|
|
|
self.rsr = TEST_RSR |
|
227
|
|
|
|
|
228
|
|
|
|
|
229
|
|
|
class TestSeviriConversions(unittest.TestCase): |
|
230
|
|
|
|
|
231
|
|
|
"""Testing the conversions between radiances and brightness temperatures""" |
|
232
|
|
|
|
|
233
|
|
|
def setUp(self): |
|
234
|
|
|
"""Set up""" |
|
235
|
|
|
|
|
236
|
|
|
with patch('pyspectral.radiance_tb_conversion.RelativeSpectralResponse') as mymock: |
|
237
|
|
|
instance = mymock.return_value |
|
238
|
|
|
instance.rsr = SEV_RSR |
|
239
|
|
|
instance.unit = 'cm-1' |
|
240
|
|
|
instance.si_scale = 100. |
|
241
|
|
|
|
|
242
|
|
|
self.sev1 = RadTbConverter('Meteosat-9', 'seviri', 'IR3.9', |
|
243
|
|
|
wavespace='wavenumber') |
|
244
|
|
|
|
|
245
|
|
|
self.sev2 = SeviriRadTbConverter('Meteosat-9', 'IR3.9') |
|
246
|
|
|
|
|
247
|
|
|
def test_rad2tb(self): |
|
248
|
|
|
"""Unit testing the radiance to brightness temperature conversion""" |
|
249
|
|
|
res = self.sev1.tb2radiance(TEST_TBS, lut=False) |
|
250
|
|
|
self.assertTrue(np.allclose(TRUE_RADS_SEVIRI, res['radiance'])) |
|
251
|
|
|
|
|
252
|
|
|
def test_conversion_simple(self): |
|
253
|
|
|
"""Test the tb2radiance function to convert radiances to Tb's |
|
254
|
|
|
using tabulated coefficients based on a non-linear approximation |
|
255
|
|
|
|
|
256
|
|
|
""" |
|
257
|
|
|
retv = self.sev2.tb2radiance(TEST_TBS) |
|
258
|
|
|
rads = retv['radiance'] |
|
259
|
|
|
# Units space = wavenumber (cm-1): |
|
260
|
|
|
tbs = self.sev2.radiance2tb(rads) |
|
261
|
|
|
self.assertTrue(np.allclose(TEST_TBS, tbs)) |
|
262
|
|
|
|
|
263
|
|
|
np.random.seed() |
|
264
|
|
|
tbs1 = 200.0 + np.random.random(50) * 150.0 |
|
265
|
|
|
retv = self.sev2.tb2radiance(tbs1) |
|
266
|
|
|
rads = retv['radiance'] |
|
267
|
|
|
tbs = self.sev2.radiance2tb(rads) |
|
268
|
|
|
self.assertTrue(np.allclose(tbs1, tbs)) |
|
269
|
|
|
|
|
270
|
|
|
def test_conversions_methods(self): |
|
271
|
|
|
"""Using the two diferent conversion methods to verify that they give |
|
272
|
|
|
approximately the same results. Conversion from Tb's to Radiances |
|
273
|
|
|
only |
|
274
|
|
|
""" |
|
275
|
|
|
# Units space = wavenumber (cm-1): |
|
276
|
|
|
retv2 = self.sev2.tb2radiance(TEST_TBS) |
|
277
|
|
|
retv1 = self.sev1.tb2radiance(TEST_TBS) |
|
278
|
|
|
|
|
279
|
|
|
rads1 = retv1['radiance'] |
|
280
|
|
|
rads2 = retv2['radiance'] |
|
281
|
|
|
self.assertTrue(np.allclose(rads1, rads2)) |
|
282
|
|
|
|
|
283
|
|
|
def tearDown(self): |
|
284
|
|
|
"""Clean up""" |
|
285
|
|
|
pass |
|
286
|
|
|
|
|
287
|
|
|
|
|
288
|
|
|
class TestRadTbConversions(unittest.TestCase): |
|
289
|
|
|
|
|
290
|
|
|
"""Testing the conversions between radiances and brightness temperatures""" |
|
291
|
|
|
|
|
292
|
|
|
def setUp(self): |
|
293
|
|
|
"""Set up""" |
|
294
|
|
|
# mymock: |
|
295
|
|
|
with patch('pyspectral.radiance_tb_conversion.RelativeSpectralResponse') as mymock: |
|
296
|
|
|
instance = mymock.return_value |
|
297
|
|
|
instance.rsr = TEST_RSR |
|
298
|
|
|
instance.unit = '1e-6 m' |
|
299
|
|
|
instance.si_scale = 1e-6 |
|
300
|
|
|
|
|
301
|
|
|
self.modis = RadTbConverter('EOS-Aqua', 'modis', '20') |
|
302
|
|
|
self.modis2 = RadTbConverter('EOS-Aqua', 'modis', 3.75) |
|
303
|
|
|
|
|
304
|
|
|
@patch('os.path.exists') |
|
305
|
|
|
@patch('os.path.isfile') |
|
306
|
|
|
@patch('pyspectral.rsr_reader.RelativeSpectralResponse.load') |
|
307
|
|
|
@patch('pyspectral.rsr_reader.download_rsr') |
|
308
|
|
|
def test_get_bandname(self, download_rsr, load, isfile, exists): |
|
309
|
|
|
"""Test getting the band name from the wave length |
|
310
|
|
|
""" |
|
311
|
|
|
load.return_code = None |
|
312
|
|
|
download_rsr.return_code = None |
|
313
|
|
|
isfile.return_code = True |
|
314
|
|
|
exists.return_code = True |
|
315
|
|
|
|
|
316
|
|
|
with patch('pyspectral.radiance_tb_conversion.RelativeSpectralResponse') as mymock: |
|
317
|
|
|
instance = mymock.return_value |
|
318
|
|
|
instance.rsr = VIIRS_RSR |
|
319
|
|
|
instance.unit = 'm' |
|
320
|
|
|
instance.si_scale = 1. |
|
321
|
|
|
|
|
322
|
|
|
with self.assertRaises(AttributeError): |
|
323
|
|
|
_ = RadTbConverter('Suomi-NPP', 'viirs', 3.7) |
|
324
|
|
|
|
|
325
|
|
|
def test_rad2tb(self): |
|
326
|
|
|
"""Unit testing the radiance to brightness temperature conversion""" |
|
327
|
|
|
res = self.modis.tb2radiance(TEST_TBS, lut=False) |
|
328
|
|
|
self.assertTrue(np.allclose(TRUE_RADS, res['radiance'])) |
|
329
|
|
|
|
|
330
|
|
|
res = self.modis2.tb2radiance(TEST_TBS, lut=False) |
|
331
|
|
|
self.assertTrue(np.allclose(TRUE_RADS, res['radiance'])) |
|
332
|
|
|
|
|
333
|
|
|
rad = res['radiance'] |
|
334
|
|
|
tbs = self.modis.radiance2tb(rad) |
|
335
|
|
|
self.assertTrue(np.allclose(TEST_TBS, tbs, atol=0.25)) |
|
336
|
|
|
|
|
337
|
|
|
res = self.modis.tb2radiance(TEST_TBS, lut=False, normalized=False) |
|
338
|
|
|
integral = self.modis.rsr_integral |
|
339
|
|
|
self.assertTrue(np.allclose(TRUE_RADS * integral, res['radiance'])) |
|
340
|
|
|
|
|
341
|
|
|
res = self.modis.tb2radiance(237., lut=False) |
|
342
|
|
|
self.assertAlmostEqual(16570.592171157, res['radiance']) |
|
343
|
|
|
|
|
344
|
|
|
res = self.modis.tb2radiance(277., lut=False) |
|
345
|
|
|
self.assertAlmostEqual(167544.3823631, res['radiance']) |
|
346
|
|
|
|
|
347
|
|
|
res = self.modis.tb2radiance(1.1, lut=False) |
|
348
|
|
|
self.assertAlmostEqual(0.0, res['radiance']) |
|
349
|
|
|
|
|
350
|
|
|
res = self.modis.tb2radiance(11.1, lut=False) |
|
351
|
|
|
self.assertAlmostEqual(0.0, res['radiance']) |
|
352
|
|
|
|
|
353
|
|
|
res = self.modis.tb2radiance(100.1, lut=False) |
|
354
|
|
|
self.assertAlmostEqual(5.3940515573e-06, res['radiance']) |
|
355
|
|
|
|
|
356
|
|
|
res = self.modis.tb2radiance(200.1, lut=False) |
|
357
|
|
|
self.assertAlmostEqual(865.09776189, res['radiance']) |
|
358
|
|
|
|
|
359
|
|
|
def tearDown(self): |
|
360
|
|
|
"""Clean up""" |
|
361
|
|
|
pass |
|
362
|
|
|
|
|
363
|
|
|
|
|
364
|
|
|
def suite(): |
|
365
|
|
|
"""The suite for test_reflectance.""" |
|
366
|
|
|
loader = unittest.TestLoader() |
|
367
|
|
|
mysuite = unittest.TestSuite() |
|
368
|
|
|
mysuite.addTest(loader.loadTestsFromTestCase(TestRadTbConversions)) |
|
369
|
|
|
mysuite.addTest(loader.loadTestsFromTestCase(TestSeviriConversions)) |
|
370
|
|
|
|
|
371
|
|
|
return mysuite |
|
372
|
|
|
|
pytroll /
pyspectral
