def test_river_discharge_em(): input_file_name = 'descarga_fluvial.csv' input_path = os.path.join(tests.full_data_path, 'locations', 'em', 'river_flow') output_csv_file_name = 'mondego_estuary_river_discharge.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'mondego_estuary_river_discharge.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'SNIRH', 'id': 'AC_Ponte_Mocate_APC_Azude_Ponte_Coimbra', 'latitude': 40.216, 'longitude': -8.440 } # Adapt driver modf_river_disch = snirh.river_discharge(input_file_name, metadata, input_path) # Plot results fig = plt.figure() ax = fig.gca() ax.plot(modf_river_disch) plt.show() # Save results at output tests.save_to_csv(modf_river_disch, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_river_disch.to_file(output_modf)
def test_sea_level_pressure_pg(): # Read the first file (era interim until 1979) input_file_name = 'data.nc' input_path = os.path.join(tests.full_data_path, 'locations', 'pg', 'sea_level_pressure', 'ERA_granada') metadata = {'source': 'ERA(ECMWF)'} modf_slp_era_interim = era.sea_level_pressure(input_file_name, metadata, input_path) # Read the second file (era 40 from 1979) input_path = os.path.join(tests.full_data_path, 'locations', 'pg', 'sea_level_pressure', 'ERA40_granada') metadata = {'source': 'ERA(ECMWF)'} modf_slp_era_40 = era.sea_level_pressure(input_file_name, metadata, input_path) # Combination of both files modf_slp = modf_slp_era_interim.combine_first(modf_slp_era_40) # Plot results plt.figure() plt.plot(modf_slp_era_interim, 'g^') plt.plot(modf_slp_era_40, 'bs') plt.plot(modf_slp, 'r--') plt.legend(['Msl era interim', 'Msl era40', 'Msl combined']) plt.show() # Save results at output output_csv_file_name = 'granada_beach_sea_level_pressure.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'granada_beach_sea_level_pressure.modf' output_modf_path = os.path.join('output', 'modf') tests.save_to_csv(modf_slp, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_slp.to_file(output_modf)
def test_river_discharge_eg(): input_file_name = 'caudal_desembalsado' dams = ['270_BORNOS', '273_GUADALCACIN'] input_path = os.path.join(tests.full_data_path, 'locations', 'eg', 'river_flow', 'rediam') output_csv_file_name = 'guadalete_estuary_river_discharge.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'guadalete_estuary_river_discharge.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'rediam', 'id': '270_BORNOS_273_GUADALCACIN', 'latitude': 36.693, 'longitude': -5.858 } # Adapt driver modf_river_disch_rediam = rediam.river_discharge(input_file_name, metadata, dams, input_path) # Read the data from de saih from 1972 input_file_name = 'river_flow.txt' input_path = os.path.join(tests.full_data_path, 'locations', 'eg', 'river_flow', 'saih') modf_river_disch_saih = saih.river_discharge(input_file_name, metadata, input_path) # Combine modf_river_disch = modf_river_disch_saih.combine_first( modf_river_disch_rediam) # Plot results fig = plt.figure() ax = fig.gca() ax.plot(modf_river_disch_saih) plt.hold ax.plot(modf_river_disch_rediam, '.k', markersize=2) ax.plot(modf_river_disch, 'r') plt.show() # Save results tests.save_to_csv(modf_river_disch, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_river_disch.to_file(output_modf)
def test_tidal_model_driver_jl(): input_file_name = 'time_series.out' input_path = os.path.join(tests.full_data_path, 'locations', 'jl', 'astronomical_tide') output_csv_file_name = 'juan_lacaze_astronomical_tide.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'juan_lacaze_astronomical_tide.modf' output_modf_path = os.path.join('output', 'modf') metadata = {'source': 'tidal_model_driver', 'latitude': -34.49, 'longitude': -57.38, 'depth': 'deep_water'} # Adapt driver modf_astron_tide = tidal_model_driver.astronomical_tide(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_astron_tide, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_astron_tide.to_file(output_modf)
def test_tidal_model_driver_eg(): input_file_name = 'time_series.out' input_path = os.path.join(tests.full_data_path, 'locations', 'eg', 'astronomical_tide') output_csv_file_name = 'guadalete_estuary_astronomical_tide.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'guadalete_estuary_astronomical_tide.modf' output_modf_path = os.path.join('output', 'modf') metadata = {'source': 'tidal_model_driver', 'latitude': 36.45, 'longitude': -6.55, 'depth': 'deep_water'} # Adapt driver modf_astron_tide = tidal_model_driver.astronomical_tide(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_astron_tide, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_astron_tide.to_file(output_modf)
def test_wind_cc_i(): input_file_name = 'Pto_5.txt' input_path = os.path.join(tests.full_data_path, 'locations', 'cc', 'waves_wind', 'Ptos') output_csv_file_name = 'cancun_wind_I.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'cancun_wind_I.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'wave_watch_III', 'id': 'Pto_5', 'depth': 'deep_water' } # Adapt driver modf_wind = ww3.wind(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_wind, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wind.to_file(output_modf)
def test_wave_pg(): input_file_name = 'SIMAR_2041080' input_path = os.path.join(tests.full_data_path, 'locations', 'pg', 'waves_wind') output_csv_file_name = 'granada_beach_wave.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'granada_beach_wave.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'SIMAR', 'id': 2041080, 'latitude': 36.667, 'longitude': -3.583, 'depth': 'deep_water' } # Adapt driver modf_wave = simar.wave(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_wave, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wave.to_file(output_modf)
def test_wind_eg(): input_file_name = 'SIMAR_1052046' input_path = os.path.join(tests.full_data_path, 'locations', 'eg', 'waves_wind') output_csv_file_name = 'guadalete_estuary_wind.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'guadalete_estuary_wind.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'SIMAR', 'id': 1052046, 'latitude': 36.5, 'longitude': -7.00, 'depth': 'deep_water' } # Adapt driver modf_wind = simar.wind(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_wind, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wind.to_file(output_modf)
def test_wind_em_ii(): input_file_name = 'SIMAR_1042062' input_path = os.path.join(tests.full_data_path, 'locations', 'em', 'waves_wind') output_csv_file_name = 'mondego_estuary_wind_II.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'mondego_estuary_wind_II.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'SIMAR', 'id': 1042062, 'latitude': 40.000, 'longitude': -9.500, 'depth': 'deep_water' } # Adapt driver modf_wind = simar.wind(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_wind, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wind.to_file(output_modf)
def test_wave_vp(): input_file_name = 'Nodo 8 (-33,-73) - Valparaiso.txt' input_path = os.path.join(tests.full_data_path, 'locations', 'vp', 'waves_wind') output_csv_file_name = 'gran_valparaiso_wave.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'gran_valparaiso_wave.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'Atlas_Chile', 'id': 'Nodo_8', 'latitude': -33.00, 'longitude': -73.00, 'depth': 'Deep water' } # Adapt driver modf_wave = atlas_oleaje_chile.wave(input_file_name, metadata, input_path) # Save results at output tests.save_to_csv(modf_wave, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wave.to_file(output_modf)
def test_wave_jl(): input_file_name = 'Oleaje.mat' input_path = os.path.join(tests.full_data_path, 'locations', 'jl', 'waves_wind') output_csv_file_name = 'juan_lacaze_wave.csv' output_csv_path = os.path.join('output', 'csv') output_modf_file_name = 'juan_lacaze_wave.modf' output_modf_path = os.path.join('output', 'modf') metadata = { 'source': 'Unknown', 'latitude': -34.47, 'longitude': -57.45, 'depth': 5.5 } # Adapt driver modf_wave = uruguay_matlab_file.wave(input_file_name, 'JL1cor', 0, metadata, input_path) # Save results at output tests.save_to_csv(modf_wave, output_csv_file_name, output_csv_path) output_modf = os.path.join(output_modf_path, output_modf_file_name) modf_wave.to_file(output_modf)