def impl_text(setup):
parameter_text = '\n'.join(
f':{p.name}: [{p.minbound:0.4g}..{p.maxbound:0.4g}] {p.description}'
for p in setup.parameters
)
cmf_text = cmf.describe(setup.project)
return dedent(f'''
Implementierung des Konzepts
-------------------------------
Modell-Parameter
.................
{parameter_text}
Die Modell-Klasse
.................
.. autoclass:: {setup.__module__}.{setup.__class__.__name__}
:members:
Das CMF-Projekt
...................
{cmf_text}
''')
def __init__(self, days=None):
self.driver_data = _load_data('cmf_data/driver_data_site24.csv')
self.evaluation_data = np.loadtxt('cmf_data/soilmoisture_site24.csv',
delimiter=',',
comments='#',
usecols=[1, 2, 3])
self.datastart = self.driver_data.time[0]
# Set the end point for the model runtime, either by parameter days or
# run to the end of available driver data
if days is None:
self.dataend = self.driver_data.time[-1]
else:
self.dataend = self.datastart + timedelta(days=days)
# The depth below ground in m where the evaluation data belongs to
self.eval_depth = [0.1, 0.25, 0.4]
# Make the model
self.model = _CmfProject(self.make_parameters())
# Load meteo data
self.model.load_meteo(driver_data=self.driver_data)
self.__doc__ += '\n\n' + cmf.describe(self.model.project)
def test_describe(self):
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, True)
p.meteo_stations.add_station('Giessen', (0, 0, 0))
c.add_layer(1.0)
text = cmf.describe(p).split('\n')
self.assertGreaterEqual(len(text), 25)
def test_describe(self):
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, True)
p.meteo_stations.add_station('Giessen', (0, 0, 0))
c.add_layer(1.0)
text = cmf.describe(p).split('\n')
print('cmf.describe(project) returns {} lines'.format(len(text)))
self.assertGreaterEqual(len(text), 5)
def descr(model):
"""
Prints out a description of your model
Usage: cmflumped descr <model.py>
<model.py>: The Python file containing the model
"""
import cmf
m = _get_model_class(model)()
print(cmf.describe(m.project))
def test_inlet():
folder_path = r'C:\Users\Christian\Dropbox\Arbejde\DTU BYG\Livestock\livestock\livestock\test\test_data\cmf_boundary_conditions\outlet'
helper.unpack(folder_path)
model = hy.CMFModel(folder_path)
p = model.run_model()
print(cmf.describe(p))
plot_outlet(folder_path)
def make_boundaries(self):
"""
Creates the boundary conditions like outlet and rain
:return:
"""
p = self.project
c = p[0]
outlet = p.NewOutlet('GW', c.x, c.y, c.z - c.soildepth)
cmf.FreeDrainagePercolation(c.layers[-1], outlet)
rainfall = cmf.timeseries.from_sequence(self.starttime, cmf.day,
[25, 0, 0, 0, 0, 0, 0] * 200)
p.rainfall_stations.add('Heavy rain once a week', rainfall, (0, 0, 0))
print(cmf.describe(p.rainfall_stations))
p.use_nearest_rainfall()
return outlet
runs = 2
# File names of the forcing data
fnQ = "Q_Kammerzell_1979_1999.txt"
fnT = "T_kammerzell_1979_1999_max_min_avg.txt"
fnP = "P_Krigavg_kammerzell_1979_1999.txt"
# import algorithm
from spotpy.algorithms import mc as Sampler
# Find out if the model should run parallel (for supercomputer)
parallel = 'mpi' if 'OMPI_COMM_WORLD_SIZE' in os.environ else 'seq'
# Create the model
model = ComplexLumped(datetime.datetime(begin, 1, 1),
datetime.datetime(end, 12, 31))
print(cmf.describe(model.project))
# If there is an command line argument, take its value for the amount of
# runs
if len(sys.argv) > 1:
runs = int(sys.argv[1])
# run the model
if runs:
sampler = Sampler(model,
parallel=parallel,
dbname="complex_lumped",
dbformat="csv",
save_sim=True)
sampler.sample(runs) #, subsets = 30)
def summerize(self):
for ts_name in 'P ETpot T Q'.split():
ts = getattr(self, ts_name)
print(ts_name, cmf.describe(ts).replace('\n', ''))
def describe(self):
return cmf.describe(self.project)