# ============================================================================= 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):