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_single_cc_load(self, model):
""" Test load from dict with 'control_curve' key
This is different to the above test by using singular 'control_curve' key in the dict
"""
m = model
m.scenarios.setup()
s = Storage(m, 'Storage', max_volume=100.0)
data = {
"type": "controlcurve",
"storage_node": "Storage",
"control_curve": 0.8,
}
s.cost = p = load_parameter(model, data)
assert isinstance(p, ControlCurveParameter)
s.setup(m) # Init memory view on storage (bypasses usual `Model.setup`)
si = ScenarioIndex(0, np.array([0], dtype=np.int32))
s.initial_volume = 90.0
m.reset()
assert_allclose(s.get_cost(m.timestepper.current, si), 0)
s.initial_volume = 70.0
m.reset()
assert_allclose(s.get_cost(m.timestepper.current, si), 1)
