files_nwc = find_files_and_readers(sensor='seviri',
start_time=start_time,
end_time=end_time,
base_dir=base_dir,
reader='nwcsaf-geo')
#print (files_nwc)
#files = dict(files_sat.items() + files_nwc.items())
files = dict(list(files_nwc.items()))
global_scene = Scene(filenames=files)
global_scene.available_dataset_names()
#!!# print(global_scene['overview']) ### this one does only work in the develop version
print("")
print("available_composite_names")
print(global_scene.available_composite_names())
if make_images:
# this will load RGBs ready to plot
global_scene.load(nwcsaf.product[p_])
#global_scene.load([ 'cloud_top_height', 'cloud_top_pressure', 'cloud_top_temperature'])
#global_scene.load(['cloudtype'])
print("global_scene.keys()", global_scene.keys())
#[DatasetID(name='cloud_top_height', wavelength=None, resolution=None, polarization=None, calibration=None, level=None, modifiers=None)]
# 'cloud_top_height' is loaded in RGB mode already
#print(global_scene['cloud_top_height'].data.shape)
#print(global_scene['cloud_top_height'].data.compute())
#print(global_scene['cloud_top_height'].values)
#### https://satpy.readthedocs.io/en/latest/quickstart.html
testfile = "MSG3-SEVI-MSG15-0100-NA-20170326102740.340000000Z-20170326102757-1213498.nat"
data_dir = "/data/COALITION2/database/meteosat/radiance_nat/native_test/"
filenames = [data_dir + testfile]
global_scene = Scene(sensor="seviri",
reader="native_msg",
filenames=[data_dir + testfile])
print(global_scene.available_dataset_names())
#['HRV', 'IR_016', 'IR_039', 'IR_087', 'IR_097', 'IR_108', 'IR_120', 'IR_134', 'VIS006', 'VIS008', 'WV_062', 'WV_073']
#global_scene.load([0.6, 0.8, 10.8])
#global_scene.load(["VIS006", "VIS008", "IR_108"])
available_composite_names = global_scene.available_composite_names()
print(available_composite_names)
available_composite_names = [
'airmass', 'ash', 'cloudtop', 'convection', 'day_microphysics',
'day_microphysics_winter', 'dust', 'fog', 'green_snow', 'ir108_3d',
'ir_cloud_day', 'ir_overview', 'natural', 'natural_color',
'natural_color_sun', 'natural_sun', 'night_fog', 'night_microphysics',
'overview', 'overview_sun', 'snow'
]
global_scene.load(available_composite_names)
local_scene = global_scene.resample(area)
for composite in available_composite_names:
print("================================")
print(composite)
data_dir = Path('/home/mklee/git/py_skripte/data')
output_dir = exercise / 'results'
# using the utils function mkdir to create folders, if they doesn`t already exist
mkdir(data_dir)
mkdir(output_dir)
# -----------------------------------------------------------------------
# 1. Read the Scene that you downloaded from the data directory using SatPy. [2P]
files = find_files_and_readers(base_dir = data_dir,reader="seviri_l1b_nc")
scn = Scene(filenames=files)
# 2. Load the composites "natural_color" and "convection" [2P]
# list all composite names
scn.available_composite_names()
# load natural_color and convection
scn.load(["natural_color"])
scn.load(["convection"])
# 3. Resample the fulldisk to the Dem. Rep. Kongo and its neighbours [4P]
# by defining your own area in Lambert Azimuthal Equal Area.
# Use the following settings:
# - lat and lon of origin: -3/23
# - width and height of the resulting domain: 500px
# - projection x/y coordinates of lower left: -15E5
# - projection x/y coordinates of upper right: 15E5
from pyresample.geometry import AreaDefinition
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))
