def test_create_results_table_raises_error_if_number_params_different(
self):
parameters = OrderedDict([('Height', (100, 0.1)),
('Cost function value', (1.5, 0))])
fits_func1 = create_test_fits(('ws1',), 'func1', parameters)
parameters = OrderedDict([('Height', (100, 0.1)), ('A0', (1, 0.001)),
('Cost function value', (1.5, 0))])
fits_func2 = create_test_fits(('ws2',), 'func2', parameters)
fitting_context = TFAsymmetryFittingContext()
fitting_context.fit_list = fits_func1 + fits_func2
model = ResultsTabModel(fitting_context, ResultsContext())
selected_results = [('ws1', 0), ('ws2', 1)]
self.assertRaises(IndexError, model.create_results_table, [],
selected_results)
def test_create_results_table_with_mixed_global_non_global_raises_error(
self):
parameters = OrderedDict([('f0.Height', (100, 0.1)),
('f1.Height', (90, 0.001)),
('Cost function value', (1.5, 0))])
fits_func1 = create_test_fits(('ws1',), 'func1', parameters)
fits_globals = create_test_fits(('ws2',),
'func1',
parameters,
global_parameters=['Height'])
fitting_context = TFAsymmetryFittingContext()
fitting_context.fit_list = fits_func1 + fits_globals
model = ResultsTabModel(fitting_context, ResultsContext())
selected_results = [('ws1', 0), ('ws2', 1)]
self.assertRaises(IndexError, model.create_results_table, [],
selected_results)
def test_create_results_table_with_logs_missing_from_some_workspaces_raises(self):
workspace = WorkspaceFactory.create("Workspace2D", NVectors=3, YLength=5, XLength=5)
parameters = OrderedDict([('f0.Height', (100, 0.1))])
logs = [('log1', (1., 2.)), ('log2', (3., 4.)), ('log3', (4., 5.)),
('log4', (5., 6.))]
fits_logs1 = create_test_fits(('ws1',), 'func1', parameters,
output_workspace_names=[StaticWorkspaceWrapper('test-ws1-ws', workspace)])
add_logs(fits_logs1[0].input_workspaces[0], logs[:2])
fits_logs2 = create_test_fits(('ws2',), 'func1', parameters,
output_workspace_names=[StaticWorkspaceWrapper('test-ws2-ws', workspace)])
add_logs(fits_logs2[0].input_workspaces[0], logs[2:])
fitting_context = TFAsymmetryFittingContext()
fitting_context.fit_list = fits_logs1 + fits_logs2
model = ResultsTabModel(fitting_context, ResultsContext())
selected_results = [('ws1', 0), ('ws2', 1)]
selected_logs = ['log1', 'log3']
self.assertRaises(IndexError, model.create_results_table,
selected_logs, selected_results)