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",