def test_calc_help_cells(helpm, output_file):
"""Test that the HelpManager is able to run water budget calculation."""
cellnames = helpm.cellnames[:100]
helpm.calc_help_cells(output_file, cellnames, tfsoil=-3)
assert osp.exists(output_file)
inputdir = osp.join(helpm.inputdir, 'd10d11_input_files')
assert len(os.listdir(inputdir)) == 98 * 2
inputdir = osp.join(helpm.inputdir, 'D4_input_files')
assert len(os.listdir(inputdir)) == 2
inputdir = osp.join(helpm.inputdir, 'D7_input_files')
assert len(os.listdir(inputdir)) == 2
inputdir = osp.join(helpm.inputdir, 'D13_input_files')
assert len(os.listdir(inputdir)) == 1
# Assert that the results are as expected.
output = HelpOutput(output_file)
area_yrly_avg = output.calc_area_yearly_avg()
expected_results = {
'precip': 11614.46,
'perco': 2767.51,
'evapo': 6034.42,
'rechg': 1432.13,
'runoff': 2334.89,
'subrun1': 509.02,
'subrun2': 1243.24
}
for key in list(expected_results.keys()):
assert abs(np.sum(area_yrly_avg[key]) - expected_results[key]) < 1, key
def test_plot_area_monthly_avg(output_dir, output_file, fig_title):
"""
Test that the water budget plots are created and saved as expected.
"""
output = HelpOutput(output_file)
figfilename = osp.join(output_dir, 'area_monthly_avg.pdf')
fig = output.plot_area_monthly_avg(figfilename,
year_from=2003,
year_to=2009,
fig_title=fig_title)
assert fig is not None
assert osp.exists(figfilename)
children = fig.axes[0].get_children()
assert (children[0].get_ydata().sum() -
1086.8448950125246) < 0.01 # precip
assert (children[1].get_ydata().sum() - 136.12068516893297) < 0.01 # rechg
assert (children[2].get_ydata().sum() - 226.9635476845988) < 0.01 # runoff
assert (children[3].get_ydata().sum() - 550.11140519815) < 0.01 # evapo
assert (children[4].get_ydata().sum() -
47.97935577404126) < 0.01 # subrun1
assert (children[5].get_ydata().sum() -
121.66539490800443) < 0.01 # subrun2
if fig_title is None:
assert fig._suptitle is None
else:
assert fig._suptitle.get_text() == fig_title
def test_plot_area_yearly_avg(output_dir, output_file, fig_title):
"""
Test that plotting the yearly averages is working expected.
"""
output = HelpOutput(output_file)
figfilename = osp.join(output_dir, 'area_yearly_avg.pdf')
fig = output.plot_area_yearly_avg(figfilename,
year_from=2003,
year_to=2009,
fig_title=fig_title)
assert fig is not None
assert osp.exists(figfilename)
children = fig.axes[0].get_children()
assert (children[0].get_height() - 1086.8448950125246) < 0.01 # precip
assert children[1].get_text() == '1087\nmm/an'
assert (children[2].get_height() - 136.12068516893297) < 0.01 # rechg
assert children[3].get_text() == '136\nmm/an'
assert (children[4].get_height() - 226.9635476845988) < 0.01 # runoff
assert children[5].get_text() == '227\nmm/an'
assert (children[6].get_height() - 550.11140519815) < 0.01 # evapo
assert children[7].get_text() == '550\nmm/an'
assert (children[8].get_height() - 47.97935577404126) < 0.01 # subrun1
assert children[9].get_text() == '48\nmm/an'
assert (children[10].get_height() - 121.66539490800443) < 0.01 # subrun2
assert children[11].get_text() == '122\nmm/an'
if fig_title is None:
assert fig._suptitle is None
else:
assert fig._suptitle.get_text() == fig_title
def test_calc_cells_yearly_avg(output_file):
"""
Test that the method to calculate cells yearly average values is
working as expected.
"""
output = HelpOutput(output_file)
# Test calc_cells_yearly_avg without providing any value for the
# year_from and year_to argument.
yearly_avg = output.calc_cells_yearly_avg()
expected_results = {
'precip': 1055.8597373343132,
'perco': 251.5843470406275,
'evapo': 548.5954285729573,
'rechg': 130.18263914385366,
'runoff': 212.26214164981408,
'subrun1': 46.26946108344004,
'subrun2': 113.02721698440918
}
for varname in list(expected_results.keys()):
result = np.sum(yearly_avg[varname]) / len(yearly_avg[varname])
assert abs(result - expected_results[varname]) < 1, varname
# Test calc_cells_yearly_avg with non null year_from and year_to argument.
yearly_avg = output.calc_cells_yearly_avg(year_from=2003, year_to=2009)
expected_results = {
'precip': 1086.8448950125246,
'perco': 259.85654385728577,
'evapo': 550.11140519815,
'rechg': 136.12068516893297,
'runoff': 226.9635476845988,
'subrun1': 47.97935577404126,
'subrun2': 121.66539490800443
}
for varname in list(expected_results.keys()):
result = np.sum(yearly_avg[varname]) / len(yearly_avg[varname])
assert abs(result - expected_results[varname]) < 1, varname
# Test calc_cells_yearly_avg with year_from == year_to.
yearly_avg = output.calc_cells_yearly_avg(year_from=2003, year_to=2003)
expected_results = {
'precip': 1144.4142919267927,
'perco': 324.15252048559057,
'evapo': 492.4243657442988,
'rechg': 148.72946963740077,
'runoff': 164.32582637467374,
'subrun1': 56.33706154407843,
'subrun2': 140.96849990912418
}
for varname in list(expected_results.keys()):
result = np.sum(yearly_avg[varname]) / len(yearly_avg[varname])
assert abs(result - expected_results[varname]) < 1, varname
def test_validate_results(output_file):
"""Test that the water budget results are as expected. """
output = HelpOutput(output_file)
area_yrly_avg = output.calc_area_yearly_avg()
expected_results = {'precip': 11614.46,
'perco': 2767.51,
'evapo': 6034.42,
'rechg': 1432.13,
'runoff': 2334.89,
'subrun1': 509.02,
'subrun2': 1243.24}
for key in list(expected_results.keys()):
assert abs(np.sum(area_yrly_avg[key]) - expected_results[key]) < 1, key
def test_save_output_to_csv(output_dir, output_file):
"""
Test that saving yearly results to csv is working as expected.
"""
output = HelpOutput(output_file)
# Save yearly results to csv.
csvfilename = osp.join(output_dir, 'test_help_yearly_results.csv')
assert not osp.exists(csvfilename)
output.save_to_csv(csvfilename)
assert osp.exists(csvfilename)
# Assert that the content of the csv is as expected.
df = pd.read_csv(csvfilename, dtype={'cid': 'str'})
df = df.set_index('cid', drop=True)
assert list(df.columns) == ['lat_dd', 'lon_dd'] + VARNAMES
assert df.index.name == 'cid'
assert len(df) == 98
assert df.index[0] == output.data['cid'][0]
assert df.iloc[0]['lat_dd'] == output.data['lat_dd'][0]
assert df.iloc[0]['lon_dd'] == output.data['lon_dd'][0]
expected_results = {
'precip': 1055.86,
'perco': 251.59,
'evapo': 548.58,
'rechg': 130.19,
'runoff': 212.26,
'subrun1': 46.27,
'subrun2': 113.02
}
for key in list(expected_results.keys()):
result = df[key].sum() / len(df)
expected_result = expected_results[key]
assert abs(result - expected_result) < 1, key
def test_plot_area_yearly_series(output_dir, output_file, fig_title):
"""
Test that plotting the yearly values is working expected.
"""
output = HelpOutput(output_file)
figfilename = osp.join(output_dir, 'area_yearly_series.pdf')
fig = output.plot_area_yearly_series(figfilename,
year_from=2003,
year_to=2009,
fig_title=fig_title)
assert fig is not None
assert osp.exists(figfilename)
expected_xdata = [2003, 2004, 2005, 2006, 2007, 2008, 2009]
children = fig.axes[0].get_children()
for i in range(12):
assert list(children[i].get_xdata()) == expected_xdata
assert (children[0].get_ydata().mean() -
1086.8448950125246) < 0.01 # precip
assert (children[2].get_ydata().mean() -
136.12068516893297) < 0.01 # rechg
assert (children[4].get_ydata().mean() -
226.9635476845988) < 0.01 # runoff
assert (children[6].get_ydata().mean() - 550.11140519815) < 0.01 # evapo
assert (children[8].get_ydata().mean() -
47.97935577404126) < 0.01 # subrun1
assert (children[10].get_ydata().mean() -
121.66539490800443) < 0.01 # subrun2
if fig_title is None:
assert fig._suptitle is None
else:
assert fig._suptitle.get_text() == fig_title
def test_plot_water_budget(output_file, example_folder):
"""
Test that the water budget plots are created and saved as expected.
Regression test for Issue #29.
"""
output = HelpOutput(output_file)
figfilename = osp.join(example_folder, 'area_monthly_avg.pdf')
output.plot_area_monthly_avg(figfilename)
assert osp.exists(figfilename)
figfilename = osp.join(example_folder, 'area_yearly_avg.pdf')
output.plot_area_yearly_avg(figfilename)
assert osp.exists(figfilename)
figfilename = osp.join(example_folder, 'area_yearly_series.pdf')
output.plot_area_yearly_series(figfilename)
assert osp.exists(figfilename)
Created on Tue Apr 26 09:21:49 2022
@author: Jean-Sébastien Gosselin
"""
from pyhelp.output import HelpOutput
import matplotlib.pyplot as plt
plt.close('all')
dirname = "D:/Projets/pyhelp/example/"
# On charge en mémoire les résultats PyHELP d'une simulation antérieure
# dont nous avions sauvegarder les résultats sur le disque.
# À noter que cela revient au même que d'utiliser l'output de la commande
# "output_help = helpm.calc_help_cells()" directement.
output_help = HelpOutput(dirname + "help_example.out")
# On peut ensuite exporter, dans un fichier CSV, les moyennes annuelles du
# bilan hydrologique.
# On peut également spécifier (disponible dans pyhelp 0.3) les années pour
# lesquelles ont souhaite calculer les moyennes annuelles du bilan. Par
# exemple, pour calculer les moyennes entre 2003 et 2009 inclusivement, on
# écrirait :
output_help.save_to_csv(dirname + "help_example_yearly_2003-2009.csv",
year_from=2003,
year_to=2007)
# On peut également produires des graphiques des moyennes annuelles et
# ensuelles du bilan hydrologique de même que les valeurs annuelles du
# bilan hydrologique à l'aide des 3 fonctions ci-dessous. Ici encore,
def calc_help_cells(self,
path_to_hdf5=None,
cellnames=None,
tfsoil=0,
sf_edepth: float = 1,
sf_ulai: float = 1,
sf_cn: float = 1,
build_help_input_files: bool = True) -> HelpOutput:
"""
Calcul the water budget for all eligible cells with HELP.
Run HELP to compute the monthly water budget for the cells listed in
"cellnames". If a file name is provided in _path_outfile_, the results
are also saved to disk in a HDF5 file.
Parameters
----------
path_to_hdf5: str, optional
File path where to save the results to disk in a HDF5 file.
tfsoil: float, optional
The average air temperature, in Celcius degrees,
below which the soil is assumed to be freezing. The default is 0.
sf_edepth : float, optional
Global scale factor for the Evaporative Zone Depth (applied to
the whole grid). The default is 1.
sf_ulai : float, optional
Global scale factor for the Maximum Leaf Area Index (applied to
the whole grid). The default is 1.
sf_cn : float, optional
Global scale factor for the Curve Number (applied to
the whole grid). The default is 1.
build_help_input_files: bool
A flag to indicate whether to generate the basic HELP input
files before running the simulation.
"""
if build_help_input_files:
self.build_help_input_files(cellnames, sf_edepth, sf_ulai, sf_cn)
# Convert from Celcius to Farenheight
tfsoil = (tfsoil * 1.8) + 32
tempdir = osp.join(self.inputdir, ".temp")
if not osp.exists(tempdir):
os.makedirs(tempdir)
run_cellnames = self.get_run_cellnames(cellnames)
cellparams = {}
skipped_cells = []
for cellname in run_cellnames:
fpath_d4 = self.connect_tables['D4'][cellname]
fpath_d7 = self.connect_tables['D7'][cellname]
fpath_d13 = self.connect_tables['D13'][cellname]
fpath_d10 = self.connect_tables['D10'][cellname]
fpath_d11 = self.connect_tables['D11'][cellname]
fpath_out = osp.abspath(osp.join(tempdir, str(cellname) + '.OUT'))
if fpath_d10 is None or fpath_d11 is None:
skipped_cells.append(cellname)
continue
daily_out = 0
monthly_out = 1
yearly_out = 0
summary_out = 0
unit_system = 2 # IP if 1 else SI
year_start = self.precip_data.index.year.min()
year_end = self.precip_data.index.year.max()
simu_nyear = year_end - year_start + 1
cellparams[cellname] = (fpath_d4, fpath_d7, fpath_d13, fpath_d11,
fpath_d10, fpath_out, daily_out,
monthly_out, yearly_out, summary_out,
unit_system, simu_nyear, tfsoil)
skipped_cells = list(set(skipped_cells))
if skipped_cells:
print('-' * 25)
msg = "Warning: calcul for "
msg += "cell " if len(skipped_cells) == 1 else "cells "
msg += ", ".join(skipped_cells)
msg += " will be skipped due to problems with the input data."
print(msg)
print('-' * 25)
output_data = run_help_allcells(cellparams)
output_data = self._post_process_output(output_data)
help_output = HelpOutput(output_data)
if path_to_hdf5:
help_output.save_to_hdf5(path_to_hdf5)
return help_output