def test_launch(self):
"""
Check that all required keys are present in output from BrainViewer launch.
"""
time_series = self.datatypeFactory.create_timeseries(self.connectivity)
covariance = self.datatypeFactory.create_covariance(time_series)
viewer = CovarianceVisualizer()
result = viewer.launch(covariance)
expected_keys = ['matrix_strides', 'matrix_shape', 'matrix_data', 'mainContent', 'isAdapter']
for key in expected_keys:
self.assertTrue(key in result)
def test_launch(self):
"""
Check that all required keys are present in output from BrainViewer launch.
"""
time_series = self.datatypeFactory.create_timeseries(self.connectivity)
covariance = self.datatypeFactory.create_covariance(time_series)
viewer = CovarianceVisualizer()
result = viewer.launch(covariance)
expected_keys = ['matrix_shape', 'matrix_data', 'mainContent', 'isAdapter']
for key in expected_keys:
assert (key in result)
def test_launch(self, time_series_factory, covariance_factory):
"""
Check that all required keys are present in output from BrainViewer launch.
"""
covariance = covariance_factory()
viewer = CovarianceVisualizer()
result = viewer.launch(covariance)
expected_keys = [
'matrix_shape', 'matrix_data', 'mainContent', 'isAdapter'
]
for key in expected_keys:
assert (key in result)
def test_launch(self, covariance_factory):
"""
Check that all required keys are present in output from CovarianceVisualizer launch.
"""
covariance_index = covariance_factory()
viewer = CovarianceVisualizer()
view_model = viewer.get_view_model_class()()
view_model.datatype = UUID(covariance_index.gid)
result = viewer.launch(view_model)
expected_keys = [
'matrix_shape', 'matrix_data', 'mainContent', 'isAdapter'
]
for key in expected_keys:
assert (key in result)