import ruamel_yaml as yml
import numpy as np
# import xarray as xr
from glob import glob
import read_data as rd
import scene as scn
# import tests
import ocean_day_tests as odt
import restoral
# #################################################################### #
# TEST CASE
# data:
_datapath = '/ships19/hercules/pveglio/mvcm_viirs_hires'
_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]
_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]
# thresholds:
_threshold_file = '/home/pveglio/mvcm_leo/thresholds/new_thresholds.mvcm.snpp.v1.0.0.yaml'
# 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'
_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'
mod_bands = ['M01', 'M02', 'M03', 'M04', 'M06', 'M08', 'M09', 'M11', 'M13', 'M14', 'M15', 'M16']
# #################################################################### #
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'
ancillary_file_names = {'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'
}
viirs_data = rd.read_data('viirs', f'{mod02}', f'{mod03}')
viirs_hires = rd.read_data('viirs', f'{img02}', f'{img03}')
for bnd in mod_bands:
viirs_hires[bnd] = (['number_of_lines', 'number_of_pixels'], viirs_data[bnd].values.repeat(2, 0).repeat(2, 1))
viirs_hires = viirs_hires.rename({'I01': 'M05', 'I02': 'M07', 'I03': 'M10', 'I04': 'M12'})
print('VIIRS data read')
viirs_hires = rd.read_ancillary_data(ancillary_file_names, viirs_hires, resolution=2)
print('ancillary data read')
viirs_data = viirs_hires
with open(threshold_file) as f:
text = f.read()
thresholds = yml.safe_load(text)
sunglint_angle = thresholds['Sun_Glint']['bounds'][3]
scene_flags = scn.find_scene(viirs_data, sunglint_angle)
cmin1 = np.ones(viirs_data.M01.shape)
cmin2 = np.ones(viirs_data.M01.shape)
cmin3 = np.ones(viirs_data.M01.shape)
cmin4 = np.ones(viirs_data.M01.shape)
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)
# For this test I changed the sst to [7.000, 6.500, 6.000, 1.0, 1.0]
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.I05.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)
total_bit = bit1 + bit2 + bit4
temp_confidence = cmin1 * cmin2 * cmin3 * cmin4
confidence = cmin1 * cmin2 * cmin3 * cmin4
# 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]
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
if __name__ == "__main__":
main()