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Commit 3ce76d86 authored by Paolo Veglio's avatar Paolo Veglio
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.gitlab-ci.yml
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......@@ -10,7 +10,6 @@ ci:
services:
- docker:19.03.1-dind
script:
- docker --version
- docker login --username $CI_REGISTRY_USER --password $CI_REGISTRY_PASSWORD $CI_REGISTRY
- cd ci
- docker build --tag $CI_REGISTRY_IMAGE .
......
mvcm/__init__.py
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"""Set up version."""
__version__ = "0.2.3"
__version__ = "0.2.4"
mvcm/main.py
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− 90
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......@@ -12,6 +12,7 @@ import time
import numpy as np
import xarray as xr
from netCDF4 import Dataset
from pkg_resources import get_distribution # type: ignore
from rich.logging import RichHandler
......@@ -217,7 +218,11 @@ def main(
return
logger.info(f"All bands found in file {file_names['IMG02']}. The code will run.")
# logger.info(f"Reading VNP02: {file_names['MOD02']}")
with Dataset(file_names["MOD03"]) as f:
# time_coverage_start = f.getncattr("time_coverage_start")
# time_coverage_end = f.getncattr("time_coverage_end")
# orbit_number = f.getncattr("OrbitNumber")
attrs = {attr: f.getncattr(attr) for attr in f.ncattrs()}
viirs_data = rd.get_data(satellite, sensor, file_names, hires=use_hires)
......@@ -483,33 +488,8 @@ def main(
# cmin,
# bits['r06'])[idx]
# cmin_3d[i, :, :] = cmin
# i += 1
# cmin_final = np.min(cmin_3d, axis=0)
# bit['15'] = np.max(temp_bit, axis=0)
cmin_final = cmin
"""
idx = np.nonzero((scene_flags['day'] == 1) & (scene_flags['water'] == 1) &
(scene_flags['ice'] == 0))
cmin[idx] = restore.shallow_water(sh_water_bits, cmin)[idx]
idx = np.nonzero((scene_flags['day'] == 1) & (scene_flags['land'] == 1) &
(scene_flags['snow'] == 0) & (scene_flags['ice'] == 0) &
(cmin <= 0.95))
cmin[idx] = restore.land(land_bits, cmin)[idx]
idx = np.nonzero((scene_flags['day'] == 1) & (scene_flags['land'] == 1) &
(scene_flags['snow'] == 0) & (scene_flags['ice'] == 0) &
(scene_flags['coast'] == 1))
cmin[idx] = restore.coast(coast_bits, cmin)[idx]
idx = np.nonzero((scene_flags['night'] == 1) & (scene_flags['land'] == 1) &
(scene_flags['snow'] == 0) & (scene_flags['ice'] == 0) &
(cmin <= 0.95))
cmin[idx] = restore.land_night(land_night_bits, cmin)[idx]
"""
# bits translation MVCM-python -> MVCM-C
# 01 13 test_11um
# 02 27 surface_temperature_test
......@@ -523,29 +503,6 @@ def main(
# 15 16 test_1_38um_high_clouds
# 16 17 thin_cirrus_4_12um_BTD_test
# if scene_name in ['Ocean_Day']:
# # total_bit = np.full(viirs_data.M01.shape, 4)
# total_bit = bit1 + bit2 + bit4 + bit11
# sunglint_angle = thresholds['Sun_Glint']['bounds'][3]
# scene_flags = scn.find_scene(viirs_data, sunglint_angle)
#
# # idx = np.nonzero((scene_flags['water'] == 1) &
# (scene_flags['ice'] == 0) &
# # (scene_flags['uniform'] == 1) &
# (cmin <= 0.99) & (cmin >= 0.05))
# # cmin[idx] = restoral.spatial(viirs_data, thresholds['Sun_Glint'],
# scene_flags, cmin)[idx]
#
# idx = np.nonzero((scene_flags['water'] == 1) &
# (scene_flags['sunglint'] == 1) &
# (scene_flags['uniform'] == 1) & (cmin <= 0.95))
# cmin[idx] = restoral.sunglint(viirs_data, thresholds['Sun_Glint'],
# total_bit, cmin)[idx]
#
# # MVCM = tst.ComputeTests(viirs_data, scene_name, thresholds)
# # cmin = MVCM.clear_sky_restoral(cmin)
#
# # return cmin
csc = cmin_final
cloud_mask = np.zeros(csc.shape)
cloud_mask[csc > 0.99] = 3
......@@ -560,6 +517,7 @@ def main(
"longitude": {"dims": ("x", "y"), "data": viirs_data.longitude.values},
"confidence": {"dims": ("x", "y"), "data": cmin_final},
"cloud_mask": {"dims": ("x", "y"), "data": cloud_mask},
"sensor_zenith": {"dims": ("x", "y"), "data": viirs_data.sensor_zenith.values},
}
d_debug = {
"ndvi": {"dims": ("x", "y"), "data": viirs_data.ndvi.values},
......@@ -632,54 +590,17 @@ def main(
ds_out = xr.Dataset.from_dict(out_dict)
comp = dict(zlib=True, complevel=5)
comp = {"zlib": True, "complevel": 5}
if type(ds_out) is xr.Dataset:
for var in ds_out:
ds_out[var].encoding.update(comp)
if type(ds_out) is xr.DataArray:
ds_out.encoding.update(comp)
# if use_hires is False:
# ds_out.to_netcdf('test_w_restorals.nc')
# else:
# ds_out.to_netcdf('test_hires.nc')
ds_out.to_netcdf(out_file)
"""
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)
for attr in attrs:
ds_out.attrs[attr] = attrs[attr]
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
"""
ds_out.to_netcdf(out_file)
if __name__ == "__main__":
......
mvcm/preprocess_thresholds.py
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......@@ -16,7 +16,7 @@ _DTR = np.pi / 180
logger = logging.getLogger(__name__)
def prepare_11_12um_thresholds(thresholds: Dict, dim1: int) -> Dict:
def prepare_11_12um_thresholds(thresholds: dict, dim1: int) -> dict:
"""Prepare 11-12um test thresholds."""
coeff_values = np.empty((dim1, 2))
coeff_values[:, 0] = np.full(dim1, thresholds["coeffs"][0])
......@@ -108,9 +108,11 @@ def thresholds_11_12um(
elif scene in ["Day_Snow"]:
hicut = locut - (thr_dict["cmult"] * locut)
else:
raise ValueError("Scene name not valid")
err_msg = "Scene name not valid"
raise ValueError(err_msg)
else:
raise ValueError("Scene name not valid")
err_msg = "Scene name not valid"
raise ValueError(err_msg)
thr_out = np.dstack((locut, midpt, hicut, np.ones(locut.shape), np.ones(locut.shape)))
return np.squeeze(thr_out.T)
......
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