def test_agg_func_get_set(self, model, agg_func):
if agg_func == "custom":
agg_func = custom_test_func
p = AggregatedIndexParameter(model, [], agg_func=agg_func)
assert p.agg_func == agg_func
p.agg_func = "product"
assert p.agg_func == "product"
def test_agg_anyall(self, simple_linear_model):
"""Test the "any" and "all" aggregation functions"""
model = simple_linear_model
model.timestepper.delta = 1
model.timestepper.start = "2017-01-01"
model.timestepper.end = "2017-01-03"
scenarioA = Scenario(model, "Scenario A", size=2)
scenarioB = Scenario(model, "Scenario B", size=5)
num_comb = len(model.scenarios.get_combinations())
parameters = {
0: DummyIndexParameter(model, 0, name="p0"),
1: DummyIndexParameter(model, 1, name="p1"),
2: DummyIndexParameter(model, 2, name="p2"),
}
data = [(0, 0), (1, 0), (0, 1), (1, 1), (1, 1, 1), (0, 2)]
data_parameters = [[parameters[i] for i in d] for d in data]
expected = [(np.any(d), np.all(d)) for d in data]
for n, params in enumerate(data_parameters):
for m, agg_func in enumerate(["any", "all"]):
p = AggregatedIndexParameter(model, params, agg_func=agg_func)
e = np.ones([len(model.timestepper), num_comb
]) * expected[n][m]
r = AssertionRecorder(model,
p,
expected_data=e,
name="assertion {}-{}".format(
n, agg_func))
model.run()
def test_aggregated_index_parameter(model):
"""Basic tests of AggregatedIndexParameter"""
parameters = []
parameters.append(DummyIndexParameter(2))
parameters.append(DummyIndexParameter(3))
timestep = scenario_index = None # lazy
agg_index = AggregatedIndexParameter(parameters, "sum")
assert (agg_index.index(timestep, scenario_index) == 5)
agg_index = AggregatedIndexParameter(parameters, "max")
assert (agg_index.index(timestep, scenario_index) == 3)
agg_index = AggregatedIndexParameter(parameters, "min")
assert (agg_index.index(timestep, scenario_index) == 2)
def test_aggregated_index_parameter_anyall(model):
"""Test `any` and `all` predicates"""
timestep = scenario_index = None # lazy
data = [(0, 0), (1, 0), (0, 1), (1, 1), (1, 1, 1)]
expected = [(False, False), (True, False), (True, False), (True, True),
(True, True)]
for item, (expected_any, expected_all) in zip(data, expected):
parameters = [DummyIndexParameter(i) for i in item]
agg_index_any = AggregatedIndexParameter(parameters, "any")
agg_index_all = AggregatedIndexParameter(parameters, "all")
assert (agg_index_any.index(timestep,
scenario_index) == int(expected_any))
assert (agg_index_all.index(timestep,
scenario_index) == int(expected_all))
def test_agg(self, simple_linear_model, agg_func):
model = simple_linear_model
model.timestepper.delta = 1
model.timestepper.start = "2017-01-01"
model.timestepper.end = "2017-01-03"
scenarioA = Scenario(model, "Scenario A", size=2)
scenarioB = Scenario(model, "Scenario B", size=5)
p1 = DummyIndexParameter(model, 2)
p2 = DummyIndexParameter(model, 3)
p = AggregatedIndexParameter(model, [p1, p2], agg_func=agg_func)
func = TestAggregatedIndexParameter.funcs[agg_func]
@assert_rec(model, p)
def expected_func(timestep, scenario_index):
x = p1.get_index(scenario_index)
y = p2.get_index(scenario_index)
return func(np.array([x, y], np.int32))
model.run()