def test_control_curve_interpolated(model):
m = model
m.scenarios.setup()
si = ScenarioIndex(0, np.array([0], dtype=np.int32))
s = Storage(m, 'Storage', max_volume=100.0)
cc = ConstantParameter(0.8)
values = [20.0, 5.0, 0.0]
s.cost = ControlCurveInterpolatedParameter(s, cc, values)
s.setup(m)
for v in (0.0, 10.0, 50.0, 80.0, 90.0, 100.0):
s.initial_volume = v
s.reset()
assert_allclose(s.get_cost(m.timestepper.current, si), np.interp(v/100.0, [0.0, 0.8, 1.0], values[::-1]))
# special case when control curve is 100%
cc.update(np.array([1.0,]))
s.initial_volume == 100.0
s.reset()
assert_allclose(s.get_cost(m.timestepper.current, si), values[1])
# special case when control curve is 0%
cc.update(np.array([0.0,]))
s.initial_volume == 0.0
s.reset()
assert_allclose(s.get_cost(m.timestepper.current, si), values[0])
def test_with_values(self, model):
"""Test with `values` keyword argument"""
m = model
s = Storage(m, 'Storage', max_volume=100.0)
# Return 10.0 when above 0.0 when below
s.cost = ControlCurveParameter(s, [0.8, 0.6], [1.0, 0.7, 0.4])
self._assert_results(m, s)
def test_with_parameters(self, model):
""" Test with `parameters` keyword argument. """
m = model
s = Storage(m, 'Storage', max_volume=100.0)
# Two different control curves
cc = [ConstantParameter(0.8), ConstantParameter(0.6)]
# Three different parameters to return
params = [
ConstantParameter(1.0), ConstantParameter(0.7), ConstantParameter(0.4)
]
s.cost = ControlCurveParameter(s, cc, parameters=params)
self._assert_results(m, s)