numeric_approximator = ImplicitEulerPython(root_finder=root_finder)
ur = UnsaturatedReservoir(parameters={
'Smax': 50.0,
'Ce': 1.0,
'm': 0.01,
'beta': 2.0
},
states={'S0': 25.0},
approximation=numeric_approximator,
id='UR')
fr = PowerReservoir(parameters={
'k': 0.1,
'alpha': 1.0
},
states={'S0': 10.0},
approximation=numeric_approximator,
id='FR')
model = Unit(layers=[[ur], [fr]], id='M4')
from superflexpy.implementation.models.m4_sf_2011 import model
model.set_input([P, E])
model.set_timestep(1.0)
model.reset_states()
output = model.get_output()
from .my_new_model import model
}
PARAMETERS_WEIERBACH_M02 = {
'm02_FR_k': 0.002139433659078,
'm02_FR_alpha': 2.16587447669636,
'm02_UR_Ce': 0.763629137970332,
'm02_UR_Smax': 115.798257318686,
'm02_UR_beta': 10.0,
}
root_finder = PegasusPython(iter_max=1000)
num_app = ImplicitEulerPython(root_finder=root_finder)
unsaturated_reservoir = UnsaturatedReservoir(
parameters={'Smax': 200.0, 'Ce': 1.0, 'm': 0.01, 'beta': 0.02},
states={'S0': 100.0},
approximation=num_app,
id='UR'
)
fast_reservoir = PowerReservoir(
parameters={'k': 0.1, 'alpha': 1.0},
states={'S0': 2.0},
approximation=num_app,
id='FR'
)
m02 = Unit(
layers=[[unsaturated_reservoir], [fast_reservoir]],
id='m02'
)
reservoir_1 = PowerReservoir(parameters={
'k': 0.1,
'alpha': 2.0
},
states={'S0': 10.0},
approximation=num_app,
id='FR1')
reservoir_2 = PowerReservoir(parameters={
'k': 0.5,
'alpha': 1.0
},
states={'S0': 10.0},
approximation=num_app,
id='FR2')
hyd_mod = Unit(layers=[[reservoir_1], [reservoir_2]], id='model')
class spotpy_model(object):
def __init__(self, model, inputs, dt, observations, parameters,
parameter_names, output_index):
self._model = model
self._model.set_input(inputs)
self._model.set_timestep(dt)
self._parameters = parameters
self._parameter_names = parameter_names
self._observarions = observations
self._output_index = output_index
def _init_model(self, solver):
if solver == 'numba':
solver = PegasusNumba()
num_app = ImplicitEulerNumba(root_finder=solver)
elif solver == 'python':
solver = PegasusPython()
num_app = ImplicitEulerPython(root_finder=solver)
# Define HRU 1 (40%)
fr = PowerReservoir(parameters={
'k': 0.01,
'alpha': 2.5
},
states={'S0': 0.0},
approximation=num_app,
id='FR')
h1 = Unit(layers=[[fr]], id='H1')
# Define HRU 2 (60%)
fr = PowerReservoir(parameters={
'k': 0.01,
'alpha': 2.5
},
states={'S0': 0.0},
approximation=num_app,
id='FR')
sr = PowerReservoir(parameters={
'k': 1e-4,
'alpha': 1.0
},
states={'S0': 0.0},
approximation=num_app,
id='SR')
ur = UnsaturatedReservoir(parameters={
'Smax': 50.0,
'Ce': 1.5,
'm': 0.01,
'beta': 1.5,
},
states={
'S0': 0.2 * 50.0,
'PET': None
},
approximation=num_app,
id='UR')
s = Splitter(weight=[[0.3], [0.7]], direction=[[0], [0]], id='S')
j = Junction(direction=[[0, 0]], id='J')
h2 = Unit(layers=[[ur], [s], [fr, sr], [j]], id='H2')
# Define the catchment
cat1 = Node(units=[h1, h2], weights=[0.25, 0.75], area=10.0, id='Cat1')
cat2 = Node(units=[h1, h2], weights=[0.4, 0.6], area=20.0, id='Cat2')
cat3 = Node(units=[h1, h2], weights=[0.8, 0.2], area=30.0, id='Cat3')
# Define the network
net = Network(nodes=[cat1, cat2, cat3],
topology={
'Cat1': 'Cat3',
'Cat2': 'Cat3',
'Cat3': None,
})
net.set_timestep(1.0)
self._cat1 = cat1
self._cat2 = cat2
self._cat3 = cat3
self._model = net
'alpha': 1.0
},
states={'S0': 0.0},
approximation=approximator,
id='slow')
lower_transparent = Transparent(id='lower-transparent')
lower_junction = Junction(direction=[[0, 0]], id='lower-junction')
consolidated = Unit(layers=[
[upper_splitter],
[snow, upper_transparent],
[upper_junction],
[unsaturated],
[lower_splitter],
[slow, lag_fun],
[lower_transparent, fast],
[lower_junction],
],
id='consolidated')
unconsolidated = Unit(layers=[
[upper_splitter],
[snow, upper_transparent],
[upper_junction],
[unsaturated],
[lower_splitter],
[slow, lag_fun],
[lower_transparent, fast],
[lower_junction],
'm01_FR_alpha': 4.34329024018006,
'm01_FR_Ce': 0.77318384036332,
}
root_finder = PegasusPython(iter_max=1000)
num_app = ImplicitEulerPython(root_finder=root_finder)
fast_reservoir = PowerReservoirET(
parameters={'k': 0.1, 'alpha': 1.0, 'Ce': 1.0, 'm': 0.5},
states={'S0': 20.0},
approximation=num_app,
id='FR'
)
m01 = Unit(
layers=[[fast_reservoir]],
id='m01'
)
# if __name__ == '__main__':
# import pandas as pd
# data = pd.read_csv('data/Maimai.csv')
# data.set_index(pd.to_datetime((data.year*10000+data.month*100+data.day).apply(str),format='%Y%m%d'), inplace=True)
# data.drop(columns=['year', 'month', 'day'], inplace=True)
# m01.set_parameters(PARAMETERS_MAIMAI)
# START_SIMULATE = 50
# START_VISUALIZE = 50 # Relative to START_SIMULATE
# END_SIMULATE = 830 # Absolute
# P = data['P(mm/d)'].values[START_SIMULATE:END_SIMULATE]
# E = data['E(mm/d)'].values[START_SIMULATE:END_SIMULATE]
# Q_obs = data['Q_obs(mm/d)'].values[START_SIMULATE:END_SIMULATE]
states={'lag': None},
id='uh1')
unit_hydrograph_2 = UnitHydrograph2(parameters={'lag-time': 2*x4},
states={'lag': None},
id='uh2')
routing_store = RoutingStore(parameters={'x2': x2, 'x3': x3,
'gamma': 5.0, 'omega': 3.5},
states={'S0': 10.0},
approximation=numerical_approximation,
id='rs')
transparent = Transparent(id='tr')
junction = Junction(direction=[[0, None], # First output
[1, None], # Second output
[None, 0]], # Third output
id='jun')
flux_aggregator = FluxAggregator(id='fa')
model = Unit(layers=[[interception_filter],
[production_store],
[splitter],
[unit_hydrograph_1, unit_hydrograph_2],
[routing_store, transparent],
[junction],
[flux_aggregator]],
id='model')
approximation=numerical_approximation,
id='cr1')
channel_routing_2 = LinearReservoir(parameters={'k': 0.1},
states={'S0': 10.0},
approximation=numerical_approximation,
id='cr2')
channel_routing_3 = LinearReservoir(parameters={'k': 0.1},
states={'S0': 10.0},
approximation=numerical_approximation,
id='cr3')
lower_zone = LinearReservoir(parameters={'k': 0.1},
states={'S0': 10.0},
approximation=numerical_approximation,
id='lz')
transparent_1 = Transparent(id='tr1')
transparent_2 = Transparent(id='tr2')
junction = Junction(
direction=[[0, 0]], # First output
id='jun')
model = Unit(layers=[[upper_zone], [splitter], [channel_routing_1, lower_zone],
[channel_routing_2, transparent_1],
[channel_routing_3, transparent_2], [junction]],
id='model')