diff --git a/main.py b/main.py
index 10b5f1f34571df28759321e47ff3dab12ce0a523..eba3e025a5cdce92818443e2d972c2d2330c70c9 100644
--- a/main.py
+++ b/main.py
@@ -37,15 +37,55 @@ _eco_file = 'goge1_2_img.v1'
# #################################################################### #
-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'
+def main(*,
+ data_path: str = _datapath,
+ mod02: str = _fname_mod02,
+ mod03: str = _fname_mod03,
+ img02: str = _fname_img02,
+ img03: str = _fname_img03,
+ threshold_file: str = _threshold_file,
+ geos_atm_1: str = _geos_atm_1,
+ geos_atm_2: str = _geos_atm_2,
+ geos_land: str = _geos_land,
+ geos_ocean: str = _geos_ocean,
+ geos_constants: str = _geos_constants,
+ ndvi_file: str = _ndvi_file,
+ sst_file: str = _sst_file) -> None:
+ """Main function for the MVCM.
+
+ Parameters
+ ----------
+ data_path: str
+ path where the data is stored
+ mod02: str
+ VIIRS MOD02 file name
+ mod03: str
+ VIIRS MOD03 file name
+ img02: str
+ VIIRS IMG02 file name
+ img03: str
+ VIIRS IMG03 file name
+ threshold_file: str
+ thresholds file name
+ geos_atm_1: str
+ file name of first GEOS5 file for atmospheric parameters
+ goes_atm_2: str
+ file name of second GEOS5 file for atmospheric parameters
+ geos_land: str
+ file name of GEOS5 land parameters
+ geos_ocean: str
+ file name of GEOS5 ocean parameters
+ geos_constants: str
+ file name of GEOS5 constants
+ ndvi_file: str
+ NDVI file name
+ sst_file:
+ Sea surface temperature file name
+
+ Returns
+ -------
+ None
+ """
file_names = {'MOD02': f'{mod02}',
'MOD03': f'{mod03}',
@@ -69,36 +109,21 @@ def main(*, data_path=_datapath, mod02=_fname_mod02, mod03=_fname_mod03,
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'])
-
+ # Initialize the confidence arrays for the various test groups
cmin_G1 = np.ones(viirs_data.M01.shape)
cmin_G2 = np.ones(viirs_data.M01.shape)
cmin_G3 = np.ones(viirs_data.M01.shape)
cmin_G4 = np.ones(viirs_data.M01.shape)
cmin_G5 = 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)
-# }
-# 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,
+
+ perform = {'11um BT Test': True,
'CO2 High Clouds Test': False,
'Water Vapor High Clouds Test': False,
- 'Surface Temperature Test': True,
+ 'Surface Temperature Test': False,
'SST Test': False,
'8.6-11um BT Difference Test': False,
'11-12um BTD Thin Cirrus Test': False,
diff --git a/read_data.py b/read_data.py
index 2d940407f431ff9665ef8c829603eacc71aa5c00..166f1bd0127c6e7db1c173798fd8868186c7f03d 100644
--- a/read_data.py
+++ b/read_data.py
@@ -4,11 +4,15 @@ import numpy as np
import ancillary_data as anc
import scene as scn
+from typing import Dict
+
_DTR = np.pi/180.
_RTD = 180./np.pi
-def read_data(sensor: str, l1b_filename: str, geo_filename: str):
+def read_data(sensor: str,
+ l1b_filename: str,
+ geo_filename: str) -> xr.Dataset:
in_data = xr.open_dataset(geo_filename, group='geolocation_data')
@@ -41,12 +45,15 @@ def read_data(sensor: str, l1b_filename: str, geo_filename: str):
return in_data
-def relative_azimuth_angle(sensor_azimuth: float, solar_azimuth: float) -> float:
+def relative_azimuth_angle(sensor_azimuth: np.ndarray,
+ solar_azimuth: np.ndarray) -> np.ndarray:
rel_azimuth = np.abs(180. - np.abs(sensor_azimuth - solar_azimuth))
return rel_azimuth
-def sun_glint_angle(sensor_zenith: float, solar_zenith: float, rel_azimuth: float) -> float:
+def sun_glint_angle(sensor_zenith: np.ndarray,
+ solar_zenith: np.ndarray,
+ rel_azimuth: np.ndarray) -> np.ndarray:
cossna = (np.sin(sensor_zenith*_DTR) * np.sin(solar_zenith*_DTR) * np.cos(rel_azimuth*_DTR) +
np.cos(sensor_zenith*_DTR) * np.cos(solar_zenith*_DTR))
cossna[cossna > 1] = 1
@@ -54,7 +61,9 @@ def sun_glint_angle(sensor_zenith: float, solar_zenith: float, rel_azimuth: floa
return sunglint_angle
-def scattering_angle(solar_zenith, sensor_zenith, relative_azimuth):
+def scattering_angle(solar_zenith: np.ndarray,
+ sensor_zenith: np.ndarray,
+ relative_azimuth: np.ndarray) -> np.ndarray:
cos_scatt_angle = -1. * (np.cos(solar_zenith*_DTR) * np.cos(sensor_zenith*_DTR) -
np.sin(solar_zenith*_DTR) * np.sin(sensor_zenith*_DTR) *
np.cos(relative_azimuth*_DTR))
@@ -66,7 +75,9 @@ def correct_reflectances():
pass
-def read_ancillary_data(file_names: str, viirs_data: float, resolution=1):
+def read_ancillary_data(file_names: str,
+ viirs_data: xr.Dataset,
+ resolution: int = 1) -> xr.Dataset:
# Ancillary files temporarily defined here. Eventually we will find a better way to pass these
start_time = '2022-06-22 14:54:00.000'
@@ -81,7 +92,7 @@ def read_ancillary_data(file_names: str, viirs_data: float, resolution=1):
dim1 = viirs_data.latitude.shape[0]
dim2 = viirs_data.latitude.shape[1]
- print(dim1, dim2)
+
sst = np.empty((dim1*dim2, ), dtype=np.float32)
ndvi = np.empty((dim1*dim2, ), dtype=np.float32)
eco = np.empty((dim1*dim2, ), dtype=np.ubyte)
@@ -97,22 +108,22 @@ def read_ancillary_data(file_names: str, viirs_data: float, resolution=1):
sst = anc.py_get_Reynolds_SST(viirs_data.latitude.values.reshape((dim1*dim2, )),
viirs_data.longitude.values.reshape((dim1*dim2, )),
resolution, anc_dir, sst_file, sst)
- print('sst')
+ print('SST read successfully')
ndvi = anc.py_get_NDVI_background(viirs_data.latitude.values.reshape((dim1*dim2, )),
viirs_data.longitude.values.reshape((dim1*dim2, )),
resolution, anc_dir, ndvi_file, ndvi)
+ print('NDVI read successfully')
- print('ndvi')
eco = anc.py_get_Olson_eco(viirs_data.latitude.values.reshape((dim1*dim2, )),
viirs_data.longitude.values.reshape((dim1*dim2, )),
resolution, anc_dir, eco)
+ print('Olson eco read successfully')
- print('eco')
geos_data = anc.py_get_GEOS(viirs_data.latitude.values.reshape((dim1*dim2, )),
viirs_data.longitude.values.reshape((dim1*dim2, )),
resolution, start_time, anc_dir, geos1, geos2, geos_lnd, geos_ocn, geos_cnst, geos_data)
- print('geos')
+ print('GEOS5 data read successfully')
data = viirs_data
data['sst'] = (('number_of_lines', 'number_of_pixels'), sst.reshape((dim1, dim2)))
@@ -128,7 +139,8 @@ def read_ancillary_data(file_names: str, viirs_data: float, resolution=1):
return data
-def get_data(file_names, sunglint_angle):
+def get_data(file_names: Dict[str, str],
+ sunglint_angle: float) -> xr.Dataset:
mod02 = file_names['MOD02']
mod03 = file_names['MOD03']
@@ -136,7 +148,7 @@ def get_data(file_names, sunglint_angle):
viirs_data = read_data('viirs', f'{mod02}', f'{mod03}')
viirs_data = read_ancillary_data(file_names, viirs_data)
- # Include channel differences and ratios that are used in the tests
+ # Compute channel differences and ratios that are used in the tests
viirs_data['M15-M14'] = (('number_of_lines', 'number_of_pixels'),
viirs_data.M15.values - viirs_data.M14.values)
viirs_data['M15-M16'] = (('number_of_lines', 'number_of_pixels'),