def test_to_dataframe(self, mocked_platypus):
result1 = mock.Mock()
result1.variables = [0, 0]
result1.objectives = [1, 1]
result2 = mock.Mock()
result2.variables = [1, 1]
result2.objectives = [0, 0]
data = [result1, result2]
mocked_platypus.unique.return_value = data
optimizer = mock.Mock()
optimizer.results = data
dvnames = ['a', 'b']
outcome_names = ['x', 'y']
df = to_dataframe(optimizer, dvnames, outcome_names)
self.assertListEqual(list(df.columns.values), ['a', 'b', 'x', 'y'])
for i, entry in enumerate(data):
self.assertListEqual(list((df.loc[i, dvnames].values)),
entry.variables)
self.assertListEqual(list((df.loc[i, outcome_names].values)),
entry.objectives)
def test_to_dataframe(self, mocked_platypus):
problem = mock.Mock()
type = mocked_platypus.Real # @ReservedAssignment
type.decode.return_value = 0
problem.types = [type, type]
result1 = mock.Mock()
result1.variables = [0,0]
result1.objectives = [1,1]
result1.problem = problem
result2 = mock.Mock()
result2.variables = [0,0]
result2.objectives = [0,0]
result2.problem = problem
data = [result1, result2]
mocked_platypus.unique.return_value = data
optimizer = mock.Mock()
optimizer.results = data
dvnames = ['a', 'b']
outcome_names = ['x', 'y']
df = to_dataframe(optimizer, dvnames, outcome_names)
self.assertListEqual(list(df.columns.values),['a', 'b', 'x', 'y'] )
for i, entry in enumerate(data):
self.assertListEqual(list((df.loc[i, dvnames].values)),
entry.variables)
self.assertListEqual(list((df.loc[i, outcome_names].values)),
entry.objectives)
def test_to_dataframe(self, mocked_platypus):
problem = mock.Mock()
type = mocked_platypus.Real # @ReservedAssignment
type.decode.return_value = 0
problem.types = [type, type]
result1 = mock.Mock()
result1.variables = [0, 0]
result1.objectives = [1, 1]
result1.problem = problem
result2 = mock.Mock()
result2.variables = [0, 0]
result2.objectives = [0, 0]
result2.problem = problem
data = [result1, result2]
mocked_platypus.unique.return_value = data
optimizer = mock.Mock()
optimizer.results = data
dvnames = ['a', 'b']
outcome_names = ['x', 'y']
df = to_dataframe(optimizer, dvnames, outcome_names)
self.assertListEqual(list(df.columns.values), ['a', 'b', 'x', 'y'])
for i, entry in enumerate(data):
self.assertListEqual(list((df.loc[i, dvnames].values)),
entry.variables)
self.assertListEqual(list((df.loc[i, outcome_names].values)),
entry.objectives)
def test_to_dataframe(self, mocked_platypus):
result1 = mock.Mock()
result1.variables = [0,0]
result1.objectives = [1,1]
result2 = mock.Mock()
result2.variables = [1,1]
result2.objectives = [0,0]
data = [result1, result2]
mocked_platypus.unique.return_value = data
optimizer = mock.Mock()
optimizer.results = data
dvnames = ['a', 'b']
outcome_names = ['x', 'y']
df = to_dataframe(optimizer, dvnames, outcome_names)
self.assertListEqual(list(df.columns.values),['a', 'b', 'x', 'y'] )
for i, entry in enumerate(data):
self.assertListEqual(list((df.loc[i, dvnames].values)),
entry.variables)
self.assertListEqual(list((df.loc[i, outcome_names].values)),
entry.objectives)
def __call__(self, optimizer):
self.index += 1
archive = to_dataframe(optimizer, self.decision_varnames,
self.outcome_varnames)
if self.dataframe_processor is not None:
archive = self.dataframe_processor(archive)
self.figure.data[0].cells.values = [
archive[c] for c in archive.columns
]