def setUp(self): self.results_context = ResultsContext() self.result_table_names = ["Name1", "Name2"] workspace = WorkspaceFactory.create("Workspace2D", NVectors=3, YLength=5, XLength=5) add_ws_to_ads("Name1", workspace) add_ws_to_ads("Name2", workspace)
class ResultsContextTest(unittest.TestCase): @classmethod def setUpClass(cls): FrameworkManager.Instance() def setUp(self): self.results_context = ResultsContext() self.result_table_names = ["Name1", "Name2"] workspace = WorkspaceFactory.create("Workspace2D", NVectors=3, YLength=5, XLength=5) add_ws_to_ads("Name1", workspace) add_ws_to_ads("Name2", workspace) def test_that_the_context_has_been_instantiated_with_empty_data(self): self.assertEqual(self.results_context.result_table_names, []) def test_that_the_result_table_names_can_be_set_in_the_context(self): self.results_context.result_table_names = self.result_table_names self.assertEqual(self.results_context.result_table_names, self.result_table_names) def test_that_add_result_table_will_add_a_table_name(self): self.results_context.add_result_table(self.result_table_names[0]) self.assertEqual(self.results_context.result_table_names, [self.result_table_names[0]]) self.results_context.add_result_table(self.result_table_names[1]) self.assertEqual(self.results_context.result_table_names, self.result_table_names) def test_that_add_result_table_will_not_add_a_duplicate_table_name(self): self.results_context.add_result_table(self.result_table_names[0]) self.assertEqual(self.results_context.result_table_names, [self.result_table_names[0]]) self.results_context.add_result_table(self.result_table_names[0]) self.assertEqual(self.results_context.result_table_names, [self.result_table_names[0]])
def create_test_model(input_workspaces, function_name, parameters, output_workspace_names=None, logs=None, global_parameters=None): """ Create a list of fits with time series logs on the workspaces :param input_workspaces: See create_test_fits :param function_name: See create_test_fits :param parameters: See create_test_fits :param logs: A list of (name, (values...), (name, (values...))) :param global_parameters: An optional list of tied parameters :return: A list of Fits with workspaces/logs attached """ fits = create_test_fits(input_workspaces, function_name, parameters, output_workspace_names, global_parameters) logs = logs if logs is not None else [] for fit, workspace_name in zip(fits, input_workspaces): add_logs(workspace_name, logs) fitting_context = TFAsymmetryFittingContext() for fit in fits: fitting_context.add_fit(fit) return fitting_context, ResultsTabModel(fitting_context, ResultsContext())
def setup_context(freq=False): loaded_data = MuonLoadData() loaded_data.get_main_field_direction = mock.MagicMock(return_value='transverse') data_context = MuonDataContext(load_data=loaded_data) gui_context = MuonGuiContext() group_context = MuonGroupPairContext(data_context.check_group_contains_valid_detectors) corrections_context = CorrectionsContext(loaded_data) phase_table_context = PhaseTableContext() freq_context = FrequencyContext() plot_panes_context = PlotPanesContext() if freq: return FrequencyDomainAnalysisContext(muon_data_context=data_context, muon_group_context=group_context, muon_gui_context=gui_context, muon_phase_context=phase_table_context, corrections_context=corrections_context, fitting_context=BasicFittingContext(allow_double_pulse_fitting=True), frequency_context=freq_context, plot_panes_context=plot_panes_context) else: return DataAnalysisContext(muon_data_context=data_context, muon_group_context=group_context, muon_gui_context=gui_context, corrections_context=corrections_context, muon_phase_context=phase_table_context, fitting_context=TFAsymmetryFittingContext(allow_double_pulse_fitting=True), results_context=ResultsContext(), model_fitting_context=ModelFittingContext(), plot_panes_context=plot_panes_context)
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_that_when_new_fit_is_performed_function_name_is_set_to_lastest_fit_name( 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() fits = fits_func1 + fits_func2 for fit in fits: fitting_context.add_fit(fit) model = ResultsTabModel(fitting_context, ResultsContext()) model.on_new_fit_performed() self.assertEqual(model.selected_fit_function(), 'func2')
def setup_context_for_tests(parent_object): parent_object.loaded_data = MuonLoadData() parent_object.loaded_data.get_main_field_direction = mock.MagicMock(return_value='transverse') parent_object.data_context = MuonDataContext(load_data=parent_object.loaded_data) parent_object.gui_context = MuonGuiContext() parent_object.group_context = MuonGroupPairContext(parent_object.data_context.check_group_contains_valid_detectors) parent_object.corrections_context = CorrectionsContext(parent_object.loaded_data) parent_object.phase_table_context = PhaseTableContext() parent_object.fitting_context = TFAsymmetryFittingContext(allow_double_pulse_fitting=True) parent_object.results_context = ResultsContext() parent_object.plot_panes_context = PlotPanesContext() parent_object.model_fitting_context = ModelFittingContext() parent_object.context = DataAnalysisContext(muon_data_context=parent_object.data_context, muon_group_context=parent_object.group_context, muon_gui_context=parent_object.gui_context, muon_phase_context=parent_object.phase_table_context, corrections_context=parent_object.corrections_context, fitting_context=parent_object.fitting_context, results_context=parent_object.results_context, model_fitting_context=parent_object.model_fitting_context, plot_panes_context=parent_object.plot_panes_context)
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)
def __init__(self, parent=None, window_flags=None): super(FrequencyAnalysisGui, self).__init__(parent) if window_flags: self.setWindowFlags(window_flags) self.setAttribute(QtCore.Qt.WA_DeleteOnClose) self.setFocusPolicy(QtCore.Qt.StrongFocus) try: check_facility() except AttributeError as error: self.warning_popup(error.args[0]) # load the feature flags feature_dict = load_features() # initialise the data storing classes of the interface self.loaded_data = MuonLoadData() self.data_context = MuonDataContext('Frequency Domain Data', self.loaded_data) self.gui_context = MuonGuiContext() self.plot_panes_context = PlotPanesContext() self.group_pair_context = MuonGroupPairContext( self.data_context.check_group_contains_valid_detectors) self.corrections_context = CorrectionsContext(self.loaded_data) self.phase_context = PhaseTableContext() self.fitting_context = BasicFittingContext( allow_double_pulse_fitting=True) self.results_context = ResultsContext() self.model_fitting_context = ModelFittingContext( allow_double_pulse_fitting=False) self.frequency_context = FrequencyContext() self.context = FrequencyDomainAnalysisContext( muon_data_context=self.data_context, muon_gui_context=self.gui_context, muon_group_context=self.group_pair_context, corrections_context=self.corrections_context, muon_phase_context=self.phase_context, plot_panes_context=self.plot_panes_context, fitting_context=self.fitting_context, results_context=self.results_context, model_fitting_context=self.model_fitting_context, frequency_context=self.frequency_context) # create the dockable widget self.plot_widget = FrequencyAnalysisPlotWidget(self.context, parent=self) self.dockable_plot_widget_window = PlottingDockWidget( parent=self, plotting_widget=self.plot_widget.view) self.dockable_plot_widget_window.setMinimumWidth(575) # Add dock widget to main Muon analysis window self.addDockWidget(QtCore.Qt.RightDockWidgetArea, self.dockable_plot_widget_window) # Need this line to stop the bug where the dock window snaps back to its original size after resizing. # 0 argument is arbitrary and has no effect on fit widget size # This is a qt bug reported at (https://bugreports.qt.io/browse/QTBUG-65592) if QT_VERSION >= LooseVersion("5.6"): self.resizeDocks({self.dockable_plot_widget_window}, {1}, QtCore.Qt.Horizontal) # construct all the widgets. self.load_widget = LoadWidget(self.loaded_data, self.context, self) self.grouping_tab_widget = GroupingTabWidget(self.context, parent) self.corrections_tab = CorrectionsTabWidget(self.context, self) self.home_tab = HomeTabWidget(self.context, self) self.phase_tab = PhaseTabWidget(self.context, self) self.transform = TransformWidget(self.context, FFTWidget, MaxEntWidget, parent=self) self.fitting_tab = FittingTabWidget(self.context, self) self.seq_fitting_tab = SeqFittingTabWidget( self.context, self.fitting_tab.fitting_tab_model, self) self.results_tab = ResultsTabWidget(self.context.fitting_context, self.context, self) self.add_model_analysis = AddModelAnalysis(self, feature_dict) self.add_raw_plots = AddRawPlots(self, feature_dict) self.add_fitting = AddFitting(self, feature_dict) setup_group_ws = AddGroupingWorkspaces(self, feature_dict) self.setup_tabs() self.plot_widget.insert_plot_panes() self.help_widget = HelpWidget(self.context.window_title) central_widget = QtWidgets.QWidget() vertical_layout = QtWidgets.QVBoxLayout() vertical_layout.addWidget(self.load_widget.load_widget_view) vertical_layout.addWidget(self.tabs) vertical_layout.addWidget(self.help_widget.view) central_widget.setLayout(vertical_layout) central_widget.setSizePolicy( QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Maximum)) self.disable_notifier = GenericObservable() self.disable_observer = GenericObserver( self.disable_notifier.notify_subscribers) self.enable_notifier = GenericObservable() self.enable_observer = GenericObserver( self.enable_notifier.notify_subscribers) self.setup_disable_notifier() self.setup_enable_notifier() self.setCentralWidget(central_widget) self.setWindowTitle(self.context.window_title) self.setup_load_observers() self.setup_gui_variable_observers() self.setup_grouping_changed_observers() self.setup_corrections_changed_observers() self.setup_instrument_changed_notifier() self.setup_group_calculation_enable_notifier() self.setup_group_calculation_disabler_notifier() self.setup_on_load_enabler() self.setup_on_load_disabler() self.setup_phase_quad_changed_notifier() self.setup_phase_table_changed_notifier() self.setup_fitting_notifier() self.setup_counts_calculation_finished_notifier() self.setup_asymmetry_pair_and_diff_calculations_finished_notifier() self.setup_transform() self.context.data_context.message_notifier.add_subscriber( self.grouping_tab_widget.group_tab_presenter.message_observer) self.add_model_analysis.add_observers_to_feature(self) self.add_model_analysis.set_feature_observables(self) self.add_raw_plots.add_observers_to_feature(self) setup_group_ws.add_observers_to_feature(self)
def test_model_returns_no_log_selection_if_no_fits_present(self): model = ResultsTabModel(TFAsymmetryFittingContext(), ResultsContext()) self.assertEqual(0, len(model.log_selection({})))
def test_updating_model_selected_fit_function(self): model = ResultsTabModel(TFAsymmetryFittingContext(), ResultsContext()) new_selection = 'func2' model.set_selected_fit_function(new_selection) self.assertEqual(model.selected_fit_function(), new_selection)
def test_default_model_has_no_selected_function_without_fits(self): model = ResultsTabModel(TFAsymmetryFittingContext(), ResultsContext()) self.assertTrue(model.selected_fit_function() is None)
def test_updating_model_results_table_name(self): table_name = 'table_name' model = ResultsTabModel(TFAsymmetryFittingContext(), ResultsContext()) model.set_results_table_name(table_name) self.assertEqual(model.results_table_name(), table_name)
def test_default_model_has_results_table_name(self): model = ResultsTabModel(TFAsymmetryFittingContext(), ResultsContext()) self.assertEqual(model.results_table_name(), DEFAULT_TABLE_NAME)