def test_wind_dir_from_components(path_uas_cnrmcm5, path_vas_cnrmcm5, direct_uas_cnrmcm5, direct_vas_cnrmcm5): with nc.Dataset(path_uas_cnrmcm5, 'r') as uas_reader, \ nc.Dataset(path_vas_cnrmcm5, 'r') as vas_reader: wind_dir = NCdata.wind_dir_from_components(uas_reader, vas_reader) wind_dir_truth = tools.degfromnorth(np.asarray(direct_uas_cnrmcm5.variables['uas'][:]), np.asarray(direct_vas_cnrmcm5.variables['vas'][:])) assert wind_dir.var_name == 'wdir' assert wind_dir.var_units == 'degrees clockwise from north' assert_almost_equal(wind_dir.variable, wind_dir_truth) assert wind_dir.model_id == 'CNRM-CM5' assert wind_dir.globalattrs['frequency'] == 'day' assert wind_dir.globalattrs['parent_experiment_rip'] == 'r1i1p1' assert wind_dir.globalattrs['creation_date_uas'] == '2011-05-10T10:54:55Z'
def test_wind_dir_from_comp_model_misaligned_error(path_uas_cmcccm, path_vas_cnrmcm5): with nc.Dataset(path_uas_cmcccm, 'r') as uas_reader, \ nc.Dataset(path_vas_cnrmcm5, 'r') as vas_reader: with pytest.raises(TypeError): NCdata.wind_dir_from_components(uas_reader, vas_reader)
def test_wind_dir_from_comp_coord_misaligned_error(path_uas_cnrmcm5, path_vas_cnrmcm5_modified_lats): with nc.Dataset(path_uas_cnrmcm5, 'r') as uas_reader, \ nc.Dataset(path_vas_cnrmcm5_modified_lats, 'r') as vas_reader: with pytest.raises(TypeError): NCdata.wind_dir_from_components(uas_reader, vas_reader)
def test_wind_dir_from_comp_vas_type_error(path_uas_cmcccm, path_pr_access10): with nc.Dataset(path_uas_cmcccm, 'r') as uas_reader, \ nc.Dataset(path_pr_access10, 'r') as vas_reader: with pytest.raises(TypeError): NCdata.wind_dir_from_components(uas_reader, vas_reader)
def wdir_ncdata_cnrmcm5(path_uas_cnrmcm5, path_vas_cnrmcm5): with nc.Dataset(path_uas_cnrmcm5, 'r') as uas_reader, \ nc.Dataset(path_vas_cnrmcm5, 'r') as vas_reader: return NCdata.wind_dir_from_components(uas_reader, vas_reader)
def wdir_ncdata_access13(path_uas_access13, path_vas_access13): with nc.Dataset(path_uas_access13, 'r') as uas_reader, \ nc.Dataset(path_vas_access13, 'r') as vas_reader: return NCdata.wind_dir_from_components(uas_reader, vas_reader)
uas_test_file_lin = os.path.join( folder, r"ACCESS1-3/uas_day_ACCESS1-3_rcp85_r1i1p1_1year_spatial_clip.nc") vas_test_file_lin = os.path.join( folder, r"ACCESS1-3/vas_day_ACCESS1-3_rcp85_r1i1p1_1year_spatial_clip.nc") # Generate precipitation rate with nc.Dataset(precip_test_file_lin, 'r') as p_flux_reader: print(p_flux_reader.__class__) p_rate = NCdata.pr_rate_from_flux(p_flux_reader) p_rate_path = os.path.join(folder, r"created/pr_from_flux_ACCESS1-3.nc") # p_rate.write(p_rate_path) # Generate wind direction with nc.Dataset(uas_test_file_lin, 'r') as uas_reader, \ nc.Dataset(vas_test_file_lin, 'r') as vas_reader: wdir = NCdata.wind_dir_from_components(uas_reader, vas_reader) wdir_path = os.path.join(folder, r"created/wdir_ACCESS1-3.nc") # wdir.write(wdir_path) # Compute monsoon criteria = criteria_generator(pr_min=5, wd_min=180, wd_max=270) with nc.Dataset(p_rate_path, 'r') as pr_reader, \ nc.Dataset(wdir_path, 'r') as wd_reader: output = MonsoonData.compute(pr_reader, wd_reader, criteria) filepath = '/home/rwegener/repos/wnpmonsoon/tests/data/created/monsoon_index_access13_pr5plus_180270wd_nomask.nc' # output.write(filepath) src = nc.Dataset(filepath, 'r') print(src.variables['monsoon'][:])