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)
