def test_to_robust_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [
RealParameter('a', 0, 1),
RealParameter('b', 0, 1)
]
mocked_model.uncertainties = [
RealParameter('c', 0, 1),
RealParameter('d', 0, 1)
]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
scenarios = 5
robustness_functions = [
ScalarOutcome('mean x', variable_name='x', function=mock.Mock()),
ScalarOutcome('mean y', variable_name='y', function=mock.Mock())
]
problem = to_robust_problem(mocked_model, scenarios,
robustness_functions)
self.assertEqual('robust', problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertEqual(['a', 'b'], problem.parameter_names)
self.assertEqual(['mean x', 'mean y'], problem.outcome_names)
def test_to_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [RealParameter('a', 0, 1),
RealParameter('b', 0, 1)]
mocked_model.uncertainties = [RealParameter('c', 0, 1),
RealParameter('d', 0, 1)]
mocked_model.outcomes = [ScalarOutcome('x', kind=1),
ScalarOutcome('y', kind=1)]
searchover = 'levers'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertIn(entry, list(mocked_model.levers))
for entry in problem.outcome_names:
self.assertIn(entry, mocked_model.outcomes.keys())
searchover = 'uncertainties'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.uncertainties.keys())
self.assertIn(entry, list(mocked_model.uncertainties))
for entry in problem.outcome_names:
self.assertIn(entry, mocked_model.outcomes.keys())
def test_to_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [
RealParameter('a', 0, 1),
RealParameter('b', 0, 1)
]
mocked_model.uncertainties = [
RealParameter('c', 0, 1),
RealParameter('d', 0, 1)
]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
mocked_model.constraints = []
searchover = 'levers'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertIn(entry, list(mocked_model.levers))
for entry in problem.outcome_names:
self.assertIn(entry.name, mocked_model.outcomes.keys())
searchover = 'uncertainties'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.uncertainties.keys())
self.assertIn(entry, list(mocked_model.uncertainties))
for entry in problem.outcome_names:
self.assertIn(entry.name, mocked_model.outcomes.keys())
def test_to_robust_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [RealParameter('a', 0, 1),
RealParameter('b', 0, 1)]
mocked_model.uncertainties = [RealParameter('c', 0, 1),
RealParameter('d', 0, 1)]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
scenarios = 5
robustness_functions = [ScalarOutcome('mean x', variable_name='x',
function=mock.Mock()),
ScalarOutcome('mean y', variable_name='y',
function=mock.Mock())]
problem = to_robust_problem(mocked_model, scenarios,
robustness_functions)
self.assertEqual('robust', problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertEqual(['mean x', 'mean y'], problem.outcome_names)
