# =============================================================================
print('Raeding rea6 data')
in_df_rea6 = pd.read_csv(path_to_rea6_files, sep=';', index_col=0, engine='c')
# in_df_rea6 = pd.read_csv(path_to_rea6_daily, sep=';',
# index_col=0, engine='c')
in_df_rea6.index = pd.to_datetime(in_df_rea6.index, format='%Y-%m-%d %H:%M:%S')
in_df_rea6 = in_df_rea6.round(2)
# =============================================================================
#
# =============================================================================
dwd_hdf5_hannover = HDF5(infile=path_dwd_data_hannover)
dwd_ids_hannover = dwd_hdf5_hannover.get_all_names()
dwd_hdf5_de = HDF5(infile=path_dwd_data_de)
dwd_ids_de = dwd_hdf5_de.get_all_names()
dwd_coords_utm32 = pd.DataFrame(
index=dwd_ids_de,
data=dwd_hdf5_de.get_coordinates(dwd_ids_de)['easting'],
columns=['X'])
dwd_coords_utm32['Y'] = dwd_hdf5_de.get_coordinates(dwd_ids_de)['northing']
print('Reading dwd data')
#dwd_pcp.dropna(how='all').head()
modulepath = r'/home/abbas/Documents/Resample-ReprojectCosmoRea2-6-master'
sys.path.append(modulepath)
from read_hdf5 import HDF5
path_dwd = r"/home/abbas/Documents/REA2/DWD_1min_metadata_wgs84.csv"
path_dwd_data = r"/home/abbas/Documents/REA2/dwd_comb_5min_data_agg_5min_2020_flagged_Hannover.h5"
path_to_all_rea6_files = r'/run/media/abbas/EL Hachem 2019/REA6/TOT_PRECIP'
os.chdir(path_to_all_rea6_files)
all_grib_files = glob.glob('*.grb')
list_years = np.arange(1995, 2020, 1)
dwd_hdf5 = HDF5(infile=path_dwd_data)
dwd_ids = dwd_hdf5.get_all_names()
dwd_coords_utm32 = pd.DataFrame(index=dwd_ids,
data=dwd_hdf5.get_coordinates(dwd_ids)['lon'],
columns=['lon'])
dwd_coords_utm32['lat'] = dwd_hdf5.get_coordinates(dwd_ids)['lat']
def find_nearest(array, value):
''' given a value, find nearest one to it in original data array'''
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return array[idx]
out_dir = (r"/run/media/abbas/EL Hachem 2019/REA_Pcp/analysis/070621")
path_rea2_data = (
r"/run/media/abbas/EL Hachem 2019/REA_Pcp/comb_years/rea2_2007_2013.csv")
path_rea2_data = (
"/run/media/abbas/EL Hachem 2019/REA6/Extracted_Hannover/comb_years/rea6_1995_2019.csv"
)
path_to_all_rea2_files = r'/home/abbas/Documents/REA2/REA_Pcp'
list_years = np.arange(2000, 2019, 1)
percentile_level = 0.99
test_for_extremes = True
dwd_hdf5 = HDF5(infile=path_dwd_data)
dwd_ids = dwd_hdf5.get_all_names()
dwd_coords_utm32 = pd.DataFrame(
index=dwd_ids,
data=dwd_hdf5.get_coordinates(dwd_ids)['easting'],
columns=['X'])
dwd_coords_utm32['Y'] = dwd_hdf5.get_coordinates(dwd_ids)['northing']
dwd_hdf5_hourly = HDF5(infile=path_dwd_data_hourly)
os.chdir(path_to_all_rea2_files)
all_grib_files = glob.glob('*.csv')
def calculate_angle_between_two_positions(x0, y0, x_vals, y_vals):
