def helpm(output_dir):
manager = HelpManager(workdir=output_dir,
path_to_grid=INPUT_FILES['grid'],
path_to_precip=INPUT_FILES['precip'],
path_to_airtemp=INPUT_FILES['airtemp'],
path_to_solrad=INPUT_FILES['solrad'])
return manager
def test_read_weather_incomplete(testvar, workdir):
"""
Test that the HelpManager throws an error if the weather are not complete
for one or more years in the dataset.
"""
kwargs = {
'workdir': workdir,
'path_to_grid': osp.join(DATAFOLDER, 'input_grid.csv')
}
for var in ['precip', 'airtemp', 'solrad']:
if var == testvar:
filename = f'{var}_input_data_incomplete.csv'
else:
filename = f'{var}_input_data_2001-2002.csv'
kwargs[f'path_to_{var}'] = osp.join(DATAFOLDER, filename)
with pytest.raises(ValueError):
HelpManager(**kwargs)
def test_read_weather_dates_nomatch(testvar, workdir):
"""
Test that the HelpManager throws an error if the len of the weather
data do not match.
"""
kwargs = {
'workdir': workdir,
'path_to_grid': osp.join(DATAFOLDER, 'input_grid.csv')
}
for var in VARNAMES:
if var == testvar:
kwargs[f'path_to_{var}'] = osp.join(
DATAFOLDER, f'{var}_input_data_2002-2003.csv')
else:
kwargs[f'path_to_{var}'] = osp.join(
DATAFOLDER, f'{var}_input_data_2001-2002.csv')
with pytest.raises(ValueError):
HelpManager(**kwargs)
def test_read_input(workdir):
"""
Test that the input files are read as expected by the HelpManager.
"""
helpm = HelpManager(
workdir,
path_to_grid=osp.join(DATAFOLDER, 'input_grid.csv'),
path_to_precip=osp.join(DATAFOLDER, 'precip_input_data_2001-2002.csv'),
path_to_airtemp=osp.join(DATAFOLDER,
'airtemp_input_data_2001-2002.csv'),
path_to_solrad=osp.join(DATAFOLDER, 'solrad_input_data_2001-2002.csv'))
assert len(helpm.airtemp_data) == 365 * 2
assert list(helpm.airtemp_data.index.year.unique()) == [2001, 2002]
assert list(helpm.airtemp_data.columns.get_level_values('lat_dd')) == [
46.1, 45.9, 45.8, 45.9, 46, 46.1
]
assert list(helpm.airtemp_data.columns.get_level_values('lon_dd')) == [
-74, -74.4, -74.1, -74, -74.1, -74.1
]
assert len(helpm.precip_data) == 365 * 2
assert list(helpm.precip_data.index.year.unique()) == [2001, 2002]
assert list(helpm.precip_data.columns.get_level_values('lat_dd')) == [
46.1, 45.9, 45.8
]
assert list(helpm.precip_data.columns.get_level_values('lon_dd')) == [
-74, -74.4, -74.1
]
assert len(helpm.solrad_data) == 365 * 2
assert list(helpm.solrad_data.index.year.unique()) == [2001, 2002]
assert list(
helpm.solrad_data.columns.get_level_values('lat_dd')) == [45.47]
assert list(
helpm.solrad_data.columns.get_level_values('lon_dd')) == [-73.74]
helpm.build_help_input_files()
output = helpm.calc_help_cells(help_output_hdf5, cellnames, tfsoil=-3)
return output
if __name__ == '__main__':
# For an explanation of why (on Windows) the if __name__ == '__main__'
# part is necessary, please see :
# https://docs.python.org/3.6/library/
# multiprocessing.html#programming-guidelines
# Instantiate the HelpManager and calculate the monthrly water budget
# for the 2000-2010 period.
workdir = "C:/Users/User/pyhelp/example"
helpm = HelpManager(workdir, year_range=(2000, 2010))
output = run_help(helpm)
# Export and save the data to an ESRI shapefile.
help_output_shp = osp.join(workdir, 'help_example.shp')
output.save_to_shp(help_output_shp)
# Plot some results.
output.plot_area_monthly_avg()
output.plot_area_yearly_avg()
output.plot_area_yearly_series()
# Calculate the yearly water budget for surface water cells.
evp_surf = 650
surf_output_hdf5 = osp.join(workdir, 'surf_example.out')
output_surf = helpm.calc_surf_water_cells(evp_surf, surf_output_hdf5)
import pyhelp.bilan as HelpBilan
if __name__ == '__main__':
# For an explanation of why (on Windows) the if __name__ == '__main__'
# part is necessary, please see :
# https://docs.python.org/3.6/library/
# multiprocessing.html#programming-guidelines
# Define the working directory.
workdir = "D:/Projets/pyhelp/example/"
# Instantiate the HelpManager and provide the paths to the grid and
# weather input data files so that they are loaded automatically.
helpm = HelpManager(workdir,
path_to_grid=workdir + 'input_grid.csv',
path_to_precip=workdir + 'precip_input_data.csv',
path_to_airtemp=workdir + 'airtemp_input_data.csv',
path_to_solrad=workdir + 'solrad_input_data.csv')
# Note that you can access the grid input data through
# the 'grid' attribute of the HelpManager.
# Note that you can access the weather input data through the
# 'precip_data', 'airtemp_data', and 'solrad_data' attributes
# of the HelpManager.
# =========================================================================
# Run HELP simulation for all the cells in cellnames.
# =========================================================================
# We want to run HELP only for the cells that are located within
# rname = "LAUALL_inputHELP_0416t3_0.15edepth" rname = "BTALL_inputHELP_0416base_0.35edepth" figname_sufix = rname riv = 2 rootdir = "C:\\Users\\User\\pyhelp\\RADEAU2\\calage_inputHELP_0416" workdir = osp.join(rootdir, rname) os.chdir(workdir) path_help_output = osp.join(workdir, "help_%s.out" % rname) path_surf_output = osp.join(workdir, "surface_%s.out" % rname) # %% Load the HELP grid path_togrid = osp.join(rootdir, 'inputHELP_0416t3.csv') helpm = HelpManager(workdir, year_range=(1965, 2014)) grid = helpm.load_grid(path_togrid) # %% Compute yearly values # Compute monthly values for cells that were run in HELP. help_output = h5py.File(path_help_output, mode='r+') cellnames = list(help_output.keys()) years = help_output[cellnames[0]]['years'].value # urbancells = grid['maille'][grid['Urbain'] == 1][grid['run'] == 1][grid['BT'] == 1].tolist() # # ruralcells = grid['maille'][grid['Urbain'] == 0][grid['BT'] == 1] # urbancells = grid['maille'][grid['Urbain'] == 1][grid['Contexte'] == 0][grid['BT'] == 1].tolist() Np = len(cellnames)
def helpm(example_folder):
manager = HelpManager(example_folder, year_range=(2000, 2010))
return manager