Newer
Older
import ruamel_yaml as yml
import numpy as np
import xarray as xr
from glob import glob
import scene as scn
from tests import CloudTests
# import tests
import ocean_day_tests as odt
Paolo Veglio
committed
import restoral
Paolo Veglio
committed
# #################################################################### #
# TEST CASE
# data:
_datapath = '/ships19/hercules/pveglio/mvcm_viirs_hires'
Paolo Veglio
committed
_fname_mod02 = glob(f'{_datapath}/VNP02MOD.A2022173.1454.001.*.uwssec_bowtie_restored.nc')[0]
_fname_mod03 = glob(f'{_datapath}/VNP03MOD.A2022173.1454.001.*.uwssec.nc')[0]
Paolo Veglio
committed
_fname_img02 = glob(f'{_datapath}/VNP02IMG.A2022173.1454.001.*.uwssec_bowtie_restored.nc')[0]
_fname_img03 = glob(f'{_datapath}/VNP03IMG.A2022173.1454.001.*.uwssec.nc')[0]
Paolo Veglio
committed
# thresholds:
_threshold_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'
Paolo Veglio
committed
# ancillary files:
_geos_atm_1 = 'GEOS.fpit.asm.inst3_2d_asm_Nx.GEOS5124.20220622_1200.V01.nc4'
_geos_atm_2 = 'GEOS.fpit.asm.inst3_2d_asm_Nx.GEOS5124.20220622_1500.V01.nc4'
_geos_land = 'GEOS.fpit.asm.tavg1_2d_lnd_Nx.GEOS5124.20220622_1430.V01.nc4'
_geos_ocean = 'GEOS.fpit.asm.tavg1_2d_ocn_Nx.GEOS5124.20220622_1430.V01.nc4'
Paolo Veglio
committed
_geos_constants = 'GEOS.fp.asm.const_2d_asm_Nx.00000000_0000.V01.nc4'
_ndvi_file = 'NDVI.FM.c004.v2.0.WS.00-04.177.hdf'
_sst_file = 'oisst.20220622'
_eco_file = 'goge1_2_img.v1'
Paolo Veglio
committed
# #################################################################### #
Paolo Veglio
committed
def main(*, data_path=_datapath, mod02=_fname_mod02, mod03=_fname_mod03,
img02=_fname_img02, img03=_fname_img03, threshold_file=_threshold_file,
geos_atm_1=_geos_atm_1, geos_atm_2=_geos_atm_2, geos_land=_geos_land,
geos_ocean=_geos_ocean, geos_constants=_geos_constants, ndvi_file=_ndvi_file, sst_file=_sst_file):
# datapath = '/ships19/hercules/pveglio/neige_data/snpp_test_input'
# fname_l1b = 'VNP02MOD.A2014213.1548.001.2017301015346.uwssec.bowtie_restored_scaled.nc'
# fname_geo = 'VNP03MOD.A2014213.1548.001.2017301015705.uwssec.nc'
# thresh_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'
file_names = {'MOD02': f'{mod02}',
'MOD03': f'{mod03}',
'IMG02': f'{img02}',
'IMG03': f'{img03}',
'GEOS_atm_1': f'{geos_atm_1}',
'GEOS_atm_2': f'{geos_atm_2}',
'GEOS_land': f'{geos_land}',
'GEOS_ocean': f'{geos_ocean}',
'GEOS_constants': f'{geos_constants}',
'NDVI': f'{ndvi_file}',
'SST': f'{sst_file}',
'ANC_DIR': f'{data_path}/ancillary'
}
Paolo Veglio
committed
with open(threshold_file) as f:
text = f.read()
thresholds = yml.safe_load(text)
sunglint_angle = thresholds['Sun_Glint']['bounds'][3]
viirs_data = rd.get_data(file_names, sunglint_angle)
# scene_xr = xr.Dataset()
# for s in scn._scene_list:
# scene_xr[s] = (('number_of_lines', 'number_of_pixels'), scn.scene_id[s])
# scene_xr['latitude'] = viirs_xr.latitude
# scene_xr['longitude'] = viirs_xr.longitude
#
# viirs_data = xr.Dataset(viirs_xr, coords=scene_xr)
# viirs_data.drop_vars(['latitude', 'longitude'])
cmin_G1 = np.ones(viirs_data.M01.shape)
cmin_G2 = np.ones(viirs_data.M01.shape)
# cmin_test = {'Ocean_Day': np.ones(viirs_data.M01.shape),
# 'Polar_Ocean_Day': np.ones(viirs_data.M01.shape),
# 'Polar_Ocean_Night': np.ones(viirs_data.M01.shape)
# }
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
# cmin2 = np.ones(viirs_data.M01.shape)
# cmin3 = np.ones(viirs_data.M01.shape)
# cmin4 = np.ones(viirs_data.M01.shape)
# ------------------- #
# ### Testing Setup ###
# ------------------- #
perform = {'11um BT Test': False,
'CO2 High Clouds Test': False,
'Water Vapor High Clouds Test': False,
'Surface Temperature Test': False,
'SST Test': False,
'8.6-11um BT Difference Test': False,
'11-12um BTD Thin Cirrus Test': True,
'11-4um BT Difference Test': False,
'7.3-11um BT Difference Mid-level Clouds': False,
'Water Vapor Cloud Test': False,
'11um BT Variability Test': False,
'11-4um BTD Oceanic Stratus': False,
'NIR Reflectance Test': False,
'Vis/NIR Ratio Test': False,
'1.6um or 2.1um NIR Reflectance Test': False,
'Visible Reflectance Test': False,
'GEMI Test': False,
'1.38um High Cloud Test': False,
'4-12um BTD Thin Cirrus Test': False
}
# --------------------- #
# ### Group 1 Tests ### #
# --------------------- #
if perform['11um BT Test'] is True:
# 11um BT Test
for scene_name in ['Ocean_Day', 'Ocean_Night', 'Polar_Ocean_Day', 'Polar_Ocean_Night']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G1 = SceneType.single_threshold_test('11um_Test', 'M15', cmin_G1)
if perform['CO2 High Clouds Test'] is True:
# CO2 High Clouds Test
for scene_name in ['Land_Day', 'Land_Night', 'Land_Day_Coast', 'Land_Day_Desert',
'Land_Day_Desert_Coast', 'Ocean_Day', 'Ocean_Night', 'Day_Snow', 'Night_Snow']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G1 = SceneType.single_threshold_test('CO2_High_Clouds_tests', 'bad_data', cmin_G1)
if perform['Water Vapor High Clouds Test'] is True:
# Water Vapor High Clouds Test
for scene_name in ['Land_Day', 'Land_Night', 'Land_Day_Coast', 'Land_Day_Desert',
'Land_Day_Desert_Coast', 'Ocean_Day', 'Ocean_Night', 'Polar_Day_Land',
'Polar_Night_Land', 'Polar_Day_Coast', 'Polar_Day_Desert',
'Polar_Day_Desert_Coast', 'Polar_Day_Snow', 'Polar_Night_Snow', 'Polar_Ocean_Day',
'Polar_Ocean_Night', 'Day_Snow', 'Night_Snow', 'Antarctic_Day']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G1 = SceneType.single_threshold_test('Water_Vapor_High_Clouds_tests', 'bad_data', cmin_G1)
if perform['Surface Temperature Test'] is True:
# Surface Temperature Test
# NOTE: this test requires the thresholds to be preprocessed
for scene_name in ['Land_Night', 'Polar_Night_Land']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G1 = SceneType.single_threshold_test('Surface_Temperature_Test', 'M15-M16', cmin_G1)
if perform['SST Test'] is True:
# SST Test
for scene_name in ['Ocean_Day', 'Ocean_Night', 'Polar_Ocean_Day', 'Polar_Ocean_Night']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G1 = SceneType.single_threshold_test('SST_Test', 'M15-M16', cmin_G1)
# --------------------- #
# ### Group 2 tests ### #
# --------------------- #
if perform['8.6-11um BT Difference Test'] is True:
# 8.6-11um BT Difference Test
for scene_name in ['Ocean_Day', 'Ocean_Night', 'Polar_Ocean_Day', 'Polar_Ocean_Night']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G2 = SceneType.single_threshold_test('8.6-11um_Test', 'M15-M14', cmin_G2)
if perform['11-12um BTD Thin Cirrus Test'] is True:
# 11-12um BT BTD Transmissive Cirrus Test
# NOTE: some of the tests have some differences in how the thresholds are derived
# The commented list scene_name is the complete list, the one currently in use is to test that
# the template code works at least with a subset of scenes that have the same way of deriving the
# thresholds
# for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
# 'Ocean_Day', 'Ocean_Night', 'Polar_Day_Land', 'Polar_Day_Coast',
# 'Polar_Day_Desert', 'Polar_Day_Desert_Coast', 'Polar_Day_Snow', 'Polar_Night_Snow',
# 'Polar_Ocean_Day', 'Polar_Ocean_Night', 'Day_Snow', 'Night_Snow']:
for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
'Ocean_Day', 'Ocean_Night', 'Polar_Ocean_Day', 'Polar_Ocean_Night']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G2 = SceneType.single_threshold_test('11-12um_Cirrus_Test', 'M15-M16', cmin_G2)
if perform['11-4um BT Difference Test'] is True:
# 11-4um BT Difference Test
for scene_name in ['Ocean_Night', 'Polar_Ocean_Night']:
pass
if perform['7.3-11um BT Difference Mid-level Clouds'] is True:
for scene_name in ['Land_Night', 'Polar_Night_Land', 'Polar_Night_Snow', 'Night_Snow']:
pass
if perform['Water Vapor Cloud Test'] is True:
for scene_name in ['Polar_Night_Ocean']:
pass
if perform['11um BT Variability Test'] is True:
for scene_name in ['Polar_Night_Ocean']:
pass
if perform['11-4um BTD Oceanic Stratus'] is True:
# 11-4um BT Difference for oceanic stratus (low emissivity water cloud) Test
for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
'Ocean_Day', 'Ocean_Night', 'Polar_Day_Land', 'Polar_Day_Coast',
'Polar_Day_Desert', 'Polar_Day_Desert_Coast', 'Polar_Day_Snow', 'Polar_Night_Snow',
'Polar_Ocean_Day', 'Polar_Ocean_Night', 'Day_Snow', 'Night_Snow']:
SceneType = CloudTests(viirs_data, scene_name, thresholds)
cmin_G2 = SceneType.single_threshold_test('11-4um_BTD_Oceanic_Stratus_Test', 'M15-M13', cmin_G2)
# --------------------- #
# ### Group 3 tests ### #
# --------------------- #
if perform['NIR Reflectance Test'] is True:
for scene_name in ['Ocean_Day', 'Polar_Ocean_Day']:
pass
if perform['Vis/NIR Ratio Test'] is True:
for scene_name in ['Ocean_Day', 'Polar_Ocean_Day']:
pass
if perform['1.6um or 2.1um NIR Reflectance Test'] is True:
for scene_name in ['Ocean_Day', 'Polar_Ocean_Day']:
pass
if perform['Visible Reflectance Test'] is True:
for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
'Polar_Day_Land', 'Polar_Day_Coast', 'Polar_Day_Desert', 'Polar_Day_Desert_Coast']:
pass
if perform['GEMI Test'] is True:
for scene_name in ['Land_Day_Desert', 'Polar_Day_Desert']:
pass
# --------------------- #
# ### Group 4 tests ### #
# --------------------- #
if perform['1.38um High Cloud Test'] is True:
for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
'Ocean_Day', 'Polar_Day_Land', 'Polar_Day_Coast', 'Polar_Day_Desert',
'Polar_Day_Desert_Coast', 'Polar_OCean_Day', 'Day_Snow']:
pass
# --------------------- #
# ### Group 5 tests ### #
# --------------------- #
if perform['4-12um BTD Thin Cirrus Test'] is True:
for scene_name in ['Land_Night', 'Polar_Night_Land', 'Polar_Night_Snow', 'Night_Snow']:
pass
return cmin_G2
'''
Land_Day = CloudTests(viirs_data, 'Land_Day', thresholds)
Land_Night = CloudTests(viirs_data, 'Land_Night', thresholds)
Land_Day_Coast = CloudTests(viirs_data, 'Land_Day_Coast', thresholds)
Land_Day_Desert = CloudTests(viirs_data, 'Land_Day_Desert', thresholds)
Land_Day_Desert_Coast = CloudTests(viirs_data, 'Land_Day_Desert_Coast', thresholds)
Ocean_Day = CloudTests(viirs_data, 'Ocean_Day', thresholds)
Ocean_Night = CloudTests(viirs_data, 'Ocean_Night', thresholds)
Polar_Day_Land = CloudTests(viirs_data, 'Polar_Day_Land', thresholds)
Polar_Night_Land = CloudTests(viirs_data, 'Polar_Night_Land', thresholds)
Polar_Day_Coast = CloudTests(viirs_data, 'Polar_Day_Coast', thresholds)
Polar_Day_Desert = CloudTests(viirs_data, 'Polar_Day_Desert', thresholds)
Polar_Day_Desert_Coast = CloudTests(viirs_data, 'Polar_Day_Desert_Coast', thresholds)
Polar_Day_Snow = CloudTests(viirs_data, 'Polar_Day_Snow', thresholds)
Polar_Night_Snow = CloudTests(viirs_data, 'Polar_Night_Snow', thresholds)
Polar_Ocean_Day = CloudTests(viirs_data, 'Polar_Ocean_Day', thresholds)
Polar_Ocean_Night = CloudTests(viirs_data, 'Polar_Ocean_Night', thresholds)
Day_Snow = CloudTests(viirs_data, 'Day_Snow', thresholds)
Night_Snow = CloudTests(viirs_data, 'Night_Snow', thresholds)
Antarctic_Day = CloudTests(viirs_data, 'Antarctic_Day', thresholds)
# 11um BT Test
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
cmin_G1 = Ocean_Day.single_threshold_test('11um_Test', 'M15', cmin_G1)
cmin_G1 = Polar_Ocean_Day.single_threshold_test('11um_Test', 'M15', cmin_G1)
cmin_G1 = Polar_Ocean_Night.single_threshold_test('11um_Test', 'M15', cmin_G1)
# CO2 High Clouds Test
# NOTE: VIIRS doesn't have the MODIS equivalent of B35 so this test is not performed
cmin_G1 = Land_Day.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Night.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Coast.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Desert.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Desert_Coast.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Ocean_Day.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Ocean_Night.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Day_Snow.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Night_Snow.single_threshold_test('CO2_High_Clouds_Test', 'bad_data', cmin_G1)
# Water Vapor High Clouds Test
# NOTE: VIIRS doesn't have the MODIS equivalent of B27 so this test is not performed
cmin_G1 = Land_Day.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Night.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Coast.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Desert.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Land_Day_Desert_Coast.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Ocean_Day.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Ocean_Night.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Day_Land.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Night_Land.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Day_Coast.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Day_Desert.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Day_Desert_Coast.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Day_Snow.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Night_Snow.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Ocean_Day.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Polar_Ocean_Night.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Day_Snow.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Night_Snow.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
cmin_G1 = Antarctic_Day.single_threshold_test('Water_Vapor_High_Clouds_Test', 'bad_data', cmin_G1)
# Surface Temperature Test
# ## NOTE: This requires some calculations for the thresholds.
# Moreover this test is using the 11um - 12um difference instead of a single channel
# Also, look at the test carefully for these two cases. Polar_Night_Land uses some hardcoded coeffs
# (i.e. *_df1 and *_df2) that might be worth moving in the thresholds file for consistency
cmin_G1 = Land_Night.single_threshold_test('Surface_Temperature_Test', 'M15-M16', cmin_G1)
cmin_G1 = Polar_Night_Land.single_threshold_test('Surface_Temperature_Test', 'M15-M16', cmin_G1)
# SST Test
# ## NOTE: This requires some calculations for the thresholds.
# Moreover this test is using the 11um - 12um difference instead of a single channel
cmin_G1 = Ocean_Day.single_threshold_test('SST_Test', 'M15-M16', cmin_G1)
cmin_G1 = Polar_Ocean_Day.single_threshold_test('SST_Test', 'M15-M16', cmin_G1)
cmin_G1 = Polar_Ocean_Night.single_threshold_test('SST_Test', 'M15-M16', cmin_G1)
# the following test uses a different set of coefficients compared to the others above
cmin_G1 = Ocean_Night.single_threshold_test('SST_Test', 'M15-M16', cmin_G1)
# 11-8.6um BT Difference Test
cmin_G2 = Ocean_Day.single_threshold_test('11-8.6um_Test', 'M15-M14', cmin_G2)
cmin_G2 = Ocean_Night.single_threshold_test('11-8.6um_Test', 'M15-M14', cmin_G2)
cmin_G2 = Polar_Ocean_Day.single_threshold_test('11-8.6um_Test', 'M15-M14', cmin_G2)
cmin_G2 = Polar_Ocean_Night.single_threshold_test('11-8.6um_Test', 'M15-M14', cmin_G2)
# 11-12um BT Difference
cmin_G1 = Ocean_Day.single_threshold_test('11-12BT_diff',
viirs_data.M15.values-viirs_data.M16.values,
cmin_G1)
Ocean_Night = CloudTests(viirs_data, 'Ocean_Night', thresholds)
cmin_G1 = Ocean_Night.single_threshold_test('11um_test', viirs_data.M15.values, cmin_G1)
cmin_G1 = Ocean_Night.single_threshold_test('11-12um_diff',
viirs_data.M15.values-viirs_data.M16.values,
cmin_G1)
Paolo Veglio
committed
c = np.ones((9, viirs_data['M01'].shape[0], viirs_data['M01'].shape[1]))
cmin1, c[0, :, :], bit1 = odt.simple_test(viirs_data.M15.values, thresholds['Daytime_Ocean']['bt11'], cmin1)
cmin1, c[1, :, :], bit2 = odt.sst_test(viirs_data.M15.values, viirs_data.M16.values,
viirs_data.sensor_zenith.values, viirs_data.geos_sfct.values,
thresholds['Daytime_Ocean']['sst'], cmin1)
cmin2, c[2, :, :], bit3 = odt.simple_test(viirs_data.M14.values-viirs_data.M15.values,
thresholds['Daytime_Ocean']['diff_11_86um'], cmin2)
cmin2, c[3, :, :], bit4 = odt.test_11_12_diff(viirs_data, thresholds['Daytime_Ocean']['diff11_12um'], cmin2)
cmin2, c[4, :, :] = odt.test_11_4_diff(viirs_data.M15.values, viirs_data.M12.values,
thresholds['Daytime_Ocean']['test11_4lo'], scene_flags, cmin2)
cmin3, c[5, :, :] = odt.nir_refl_test(viirs_data.M07.values, thresholds['Daytime_Ocean'],
thresholds['Sun_Glint'], viirs_data, cmin3)
cmin3, c[6, :, :] = odt.vis_nir_ratio_test(viirs_data.M05.values, viirs_data.M07.values,
thresholds, scene_flags, cmin3)
cmin3, c[7, :, :] = odt.nir_refl_test(viirs_data.M10.values, thresholds['Daytime_Ocean'],
thresholds['Sun_Glint'], viirs_data, cmin3)
#
# confidence[0, :, :] = tests.test_11um(viirs_data.M15.values, thresholds['Daytime_Ocean'])
# confidence[1, :, :] = tests.test_11_4diff(viirs_data.M15.values, viirs_data.M13.values,
# thresholds['Daytime_Ocean'], viirs_data,
# thresholds['Sun_Glint']['bounds'][3])
#
# confidence[2, :, :] = tests.nir_refl_test(viirs_data.M07.values, thresholds['Daytime_Ocean'],
# thresholds['Sun_Glint'], viirs_data)
#
# # Note that here I'm using M05/M07 but the corresponding hi-res channels are I1/I2
# # IMPORTANT: conf_test_dble() needs to be verified. I don't think it's working as intended at the moment
# confidence[3, :, :] = tests.vis_nir_ratio_test(viirs_data.M05.values, viirs_data.M07.values,
# thresholds['Daytime_Ocean'], thresholds['Sun_Glint'])
#
# # This test needs to be verified, for the granule I'm running everything is zero
# confidence[4, :, :] = tests.test_11um_var(viirs_data.M15.values, thresholds['Nighttime_Ocean'],
# thresholds['Daytime_Ocean_Spatial_Variability'])
Paolo Veglio
committed
total_bit = bit1 + bit2 + bit4
temp_confidence = cmin1 * cmin2 * cmin3 * cmin4
confidence = cmin1 * cmin2 * cmin3 * cmin4
Paolo Veglio
committed
# idx = np.nonzero((scene_flags['water'] == 1) & (scene_flags['ice'] == 0) & (scene_flags['uniform'] == 1) &
# (confidence <= 0.99) & (confidence >= 0.05))
# confidence[idx] = restoral.spatial(viirs_data, thresholds['Sun_Glint'], scene_flags, confidence)[idx]
Paolo Veglio
committed
idx = np.nonzero((scene_flags['water'] == 1) & (scene_flags['sunglint'] == 1) &
(scene_flags['uniform'] == 1) & (confidence <= 0.95))
confidence[idx] = restoral.sunglint(viirs_data, thresholds['Sun_Glint'], total_bit, temp_confidence)[idx]
temp = np.zeros((viirs_data.M01.shape[0], viirs_data.M01.shape[1]))
temp[idx] = 1
c[8, :, :] = temp
np.savez('test_confidence', confidence=confidence, conf_test=c,
lat=viirs_data.latitude.values, lon=viirs_data.longitude.values)
return confidence
'''
def test_main():
rad1 = [[255, 260, 265, 248, 223],
[278, 285, 270, 268, 256],
[275, 273, 266, 254, 259]]
rad2 = [[270, 273, 271, 268, 265],
[277, 286, 275, 277, 269],
[280, 281, 272, 270, 267]]
thresh_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'
with open(thresh_file) as f:
text = f.read()
rad1 = np.array(rad1)
rad2 = np.array(rad2)
confidence = np.zeros((2, rad1.shape[0], rad1.shape[1]))
thresholds = yml.safe_load(text)
confidence[0, :, :] = tests.test_11um(rad1, thresholds['Daytime_Ocean'])
confidence[1, :, :] = tests.test_11_4diff(rad1, rad2, thresholds['Daytime_Ocean'])
print(f'Confidence[0,:,:]: \n {confidence[0, :, :]}')
print(f'Confidence[1,:,:]: \n {confidence[1, :, :]}')
return confidence
if __name__ == "__main__":