dates = list(
set([f.split("_")[4][0:8] for f in glob.glob1(process_path, "*.nc")]))
if not os.path.exists(os.path.join(r"outputs")):
os.mkdir(os.path.join(r"outputs"))
hour_ = "1200"
visual = False
export = True
for date_ in dates:
files = [
os.path.join(process_path, row)
for row in glob.glob1(process_path, "W_XX*" + date_ + hour_ + "*.nc")
]
print(date_, files)
scn = Scene(reader="seviri_l1b_nc", filenames=files)
pprint.pprint(scn.available_composite_names())
scn.load(['natural_color', 'snow'], calibrations=['radiance'])
if visual:
scn.show("natural_color")
scn.show("snow")
scn.show("natural_enh")
if not os.path.exists(os.path.join(r"outputs", date_)):
os.mkdir(os.path.join(r"outputs", date_))
if export:
out = scn.save_datasets(
filename='{name}_{start_time:%Y%m%d_%H%M%S}.png',
base_dir=os.path.join(r"outputs", date_))
# compute_writer_results(out)
end = datetime.datetime.now()
print("Duration is : ", str(end - start))
if len(sys.argv) < 2:
print("Usage: " + sys.argv[0] + " MAIA_file ")
sys.exit()
fnmaia = sys.argv[1]
maia_scene = Scene(reader='maia', filenames=[fnmaia])
print(maia_scene.available_dataset_ids())
maia_scene.load(["CloudType", "ct", "cma", "cma_conf",
'opaq_cloud', "CloudTopPres",
"CloudTopTemp", "Alt_surface"])
# CloudType is a bit field containing the actual "ct" with values
# from 0 to 20 which can be interpreted according to the cpool colormap
# "ct" can be display in black and white:
maia_scene.show("ct")
# but it is better to palettize the image:
# step 1: creation of the palette
mycolors = []
for i in range(21):
mycolors.append(hex_to_rgb(cpool[i]))
arr = np.array(mycolors)
np.save("/tmp/binary_maia_ct_colormap.npy", arr)
# step2: creation of the composite
compositor = BWCompositor("test", standard_name="maia_ct")
composite = compositor((maia_scene["ct"],))
kwargs = {"palettes": [
{"filename": "/tmp/binary_maia_ct_colormap.npy",
"min_value": 0, "max_value": 20}]}
print("Usage: " + sys.argv[0] + " MAIA_file ")
sys.exit()
fnmaia = sys.argv[1]
maia_scene = Scene(reader='maia', filenames=[fnmaia])
print(maia_scene.available_dataset_ids())
maia_scene.load([
"CloudType", "ct", "cma", "cma_conf", 'opaq_cloud', "CloudTopPres",
"CloudTopTemp", "Alt_surface"
])
# CloudType is a bit field containing the actual "ct" with values
# from 0 to 20 which can be interpreted according to the cpool colormap
# "ct" can be display in black and white:
maia_scene.show("ct")
# but it is better to palettize the image:
# step 1: creation of the palette
mycolors = []
for i in range(21):
mycolors.append(hex_to_rgb(cpool[i]))
arr = np.array(mycolors)
np.save("/tmp/binary_maia_ct_colormap.npy", arr)
# step2: creation of the composite
compositor = BWCompositor("test", standard_name="maia_ct")
composite = compositor((maia_scene["ct"], ))
kwargs = {
"palettes": [{
"filename": "/tmp/binary_maia_ct_colormap.npy",
