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 = FittingContext()
for fit in fits:
fitting_context.add_fit(fit)
return fitting_context, ResultsTabModel(fitting_context)
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)
phase_table_context = PhaseTableContext()
fitting_context = FittingContext()
freq_context = FrequencyContext()
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,
fitting_context=fitting_context,
frequency_context=freq_context)
else:
return DataAnalysisContext(muon_data_context=data_context,
muon_group_context=group_context,
muon_gui_context=gui_context,
muon_phase_context=phase_table_context,
fitting_context=fitting_context)
def test_context_constructor_accepts_fit_list(self):
fit_list = [
FitInformation(mock.MagicMock(), 'MuonGuassOsc', mock.MagicMock(),
mock.MagicMock())
]
context = FittingContext(fit_list)
self.assertEqual(fit_list, context.fit_list)
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.phase_table_context = PhaseTableContext()
parent_object.fitting_context = FittingContext()
parent_object.context = MuonContext(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,
fitting_context=parent_object.fitting_context)
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, [])
model = ResultsTabModel(FittingContext(fits_func1 + fits_func2))
model.on_new_fit_performed()
self.assertEqual(model.selected_fit_function(), 'func2')
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, [])
model = ResultsTabModel(FittingContext(fits_func1 + fits_func2))
selected_results = [('ws1', 0), ('ws2', 1)]
self.assertRaises(RuntimeError, 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'])
model = ResultsTabModel(FittingContext(fits_func1 + fits_globals))
selected_results = [('ws1', 0), ('ws2', 1)]
self.assertRaises(RuntimeError, model.create_results_table, [],
selected_results)
def setup_context():
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)
phase_table_context = PhaseTableContext()
fitting_context = FittingContext()
return MuonContext(muon_data_context=data_context,
muon_group_context=group_context,
muon_gui_context=gui_context,
muon_phase_context=phase_table_context,
fitting_context=fitting_context)
def test_create_results_table_with_logs_missing_from_some_workspaces_raises(
self):
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=('ws1', ))
add_logs(fits_logs1[0].input_workspaces[0], logs[:2])
fits_logs2 = create_test_fits(('ws2', ), 'func1', parameters, output_workspace_names=('ws2', ))
add_logs(fits_logs2[0].input_workspaces[0], logs[2:])
model = ResultsTabModel(FittingContext(fits_logs1 + fits_logs2))
selected_results = [('ws1', 0), ('ws2', 1)]
selected_logs = ['log1', 'log3']
self.assertRaises(RuntimeError, model.create_results_table,
selected_logs, selected_results)
class FittingContextTest(GuiTest):
def setUp(self):
self.fitting_context = FittingContext()
def test_context_constructor_accepts_fit_list(self):
fit_list = [
FitInformation(mock.MagicMock(), 'MuonGuassOsc', mock.MagicMock(),
mock.MagicMock())
]
context = FittingContext(fit_list)
self.assertEqual(fit_list, context.fit_list)
def test_len_gives_length_of_fit_list(self):
self.assertEqual(0, len(self.fitting_context))
self.fitting_context.add_fit(
FitInformation(mock.MagicMock(), 'MuonGuassOsc', mock.MagicMock(),
mock.MagicMock()))
self.assertEqual(1, len(self.fitting_context))
def test_items_can_be_added_to_fitting_context(self):
fit_information_object = FitInformation(mock.MagicMock(),
'MuonGuassOsc',
mock.MagicMock(),
mock.MagicMock())
self.fitting_context.add_fit(fit_information_object)
self.assertEqual(fit_information_object,
self.fitting_context.fit_list[0])
def test_fitfunctions_gives_list_of_unique_function_names(self):
test_fit_function = 'MuonGuassOsc'
self.fitting_context.add_fit_from_values(mock.MagicMock(),
test_fit_function,
mock.MagicMock(),
mock.MagicMock(), [])
self.fitting_context.add_fit_from_values(mock.MagicMock(),
test_fit_function,
mock.MagicMock(),
mock.MagicMock(), [])
fit_functions = self.fitting_context.fit_function_names()
self.assertEqual(len(fit_functions), 1)
self.assertEqual(test_fit_function, fit_functions[0])
def test_can_add_fits_without_first_creating_fit_information_objects(self):
parameter_workspace = mock.MagicMock()
input_workspace = mock.MagicMock()
output_workspace_names = mock.MagicMock()
fit_function_name = 'MuonGuassOsc'
fit_information_object = FitInformation(parameter_workspace,
fit_function_name,
input_workspace,
output_workspace_names)
self.fitting_context.add_fit_from_values(parameter_workspace,
fit_function_name,
input_workspace,
output_workspace_names)
self.assertEqual(fit_information_object,
self.fitting_context.fit_list[0])
def test_can_add_fits_with_global_parameters_without_creating_fit_information(
self):
parameter_workspace = mock.MagicMock()
input_workspace = mock.MagicMock()
fit_function_name = 'MuonGuassOsc'
global_params = ['A']
fit_information_object = FitInformation(parameter_workspace,
fit_function_name,
input_workspace, global_params)
self.fitting_context.add_fit_from_values(parameter_workspace,
fit_function_name,
input_workspace,
global_params)
self.assertEqual(fit_information_object,
self.fitting_context.fit_list[0])
def test_parameters_are_readonly(self):
test_parameters = OrderedDict([('Height', (10., 0.4)),
('A0', (1, 0.01)),
('Cost function', (0.1, 0.))])
fit_params = create_test_fit_parameters(test_parameters)
fit_info = FitInformation(fit_params._parameter_workspace,
mock.MagicMock(), mock.MagicMock(),
mock.MagicMock())
self.assertRaises(AttributeError, setattr, fit_info, "parameters",
fit_params)
def test_log_names_returns_logs_from_all_fits_by_default(self):
time_series_logs = (('ts_1', (1., )), ('ts_2', (3., )), ('ts_3', [2.]),
('ts_4', [3.]))
fake1 = create_test_workspace(ws_name='fake1',
time_series_logs=time_series_logs[:2])
fake2 = create_test_workspace(ws_name='fake2',
time_series_logs=time_series_logs[2:])
self.fitting_context.add_fit(
FitInformation(mock.MagicMock(), 'func1', fake1.name(),
fake1.name()))
self.fitting_context.add_fit(
FitInformation(mock.MagicMock(), 'func1', fake2.name(),
fake2.name()))
log_names = self.fitting_context.log_names()
self.assertEqual(len(time_series_logs), len(log_names))
for name, _ in time_series_logs:
self.assertTrue(name in log_names,
msg="{} not found in log list".format(name))
def test_log_names_respects_filter(self):
time_series_logs = (('ts_1', (1., )), ('ts_2', (3., )), ('ts_3', [2.]),
('ts_4', [3.]))
fake1 = create_test_workspace(ws_name='fake1',
time_series_logs=time_series_logs[:2])
fake2 = create_test_workspace(ws_name='fake2',
time_series_logs=time_series_logs[2:])
self.fitting_context.add_fit(
FitInformation(mock.MagicMock(), 'func1', fake1.name(),
fake1.name()))
self.fitting_context.add_fit(
FitInformation(mock.MagicMock(), 'func1', fake2.name(),
fake2.name()))
required_logs = ('ts_2', 'ts_4')
log_names = self.fitting_context.log_names(
filter_fn=lambda log: log.name in required_logs)
self.assertEqual(len(required_logs), len(log_names))
for name in required_logs:
self.assertTrue(name in log_names,
msg="{} not found in log list".format(name))
def __init__(self, parent=None):
super(MuonAnalysisGui, self).__init__(parent)
self.setAttribute(QtCore.Qt.WA_DeleteOnClose)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
self.setObjectName("MuonAnalysis2")
self.current_tab = ''
try:
check_facility()
except AttributeError as error:
self.warning_popup(error.args[0])
# initialise the data storing classes of the interface
self.loaded_data = MuonLoadData()
self.data_context = MuonDataContext('Muon Data', self.loaded_data)
self.gui_context = MuonGuiContext()
self.group_pair_context = MuonGroupPairContext(
self.data_context.check_group_contains_valid_detectors)
self.phase_context = PhaseTableContext()
self.fitting_context = FittingContext()
self.context = DataAnalysisContext(
muon_data_context=self.data_context,
muon_gui_context=self.gui_context,
muon_group_context=self.group_pair_context,
fitting_context=self.fitting_context,
muon_phase_context=self.phase_context)
# create the Dockable plot widget
self.fitting_tab = FittingTabWidget(self.context, self)
self.plot_widget = PlotWidget(
self.context,
self.fitting_tab.fitting_tab_presenter.get_selected_fit_workspaces,
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)
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)
# set up other widgets
self.load_widget = LoadWidget(self.loaded_data, self.context, self)
self.home_tab = HomeTabWidget(self.context, self)
self.grouping_tab_widget = GroupingTabWidget(self.context)
self.phase_tab = PhaseTabWidget(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.setup_tabs()
self.help_widget = HelpWidget("Muon Analysis 2")
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)
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_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_on_recalulation_finished_notifier()
self.context.data_context.message_notifier.add_subscriber(
self.grouping_tab_widget.group_tab_presenter.message_observer)
self.setup_disable_notifier()
self.setup_enable_notifier()
def __init__(self, parent=None):
super(MuonAnalysisGui, self).__init__(parent)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
try:
check_facility()
except AttributeError as error:
self.warning_popup(error.args[0])
# initialise the data storing classes of the interface
self.loaded_data = MuonLoadData()
self.data_context = MuonDataContext('Muon Data', self.loaded_data)
self.gui_context = MuonGuiContext()
self.group_pair_context = MuonGroupPairContext(
self.data_context.check_group_contains_valid_detectors)
self.phase_context = PhaseTableContext()
self.fitting_context = FittingContext()
self.context = MuonContext(muon_data_context=self.data_context,
muon_gui_context=self.gui_context,
muon_group_context=self.group_pair_context,
muon_phase_context=self.phase_context,
fitting_context=self.fitting_context,
workspace_suffix=' MA')
# create the dockable widget
self.dockable_plot_widget = PlottingWidget(self.context)
self.dockable_plot_widget_window = PlottingDockWidget(
parent=self, plotting_widget=self.dockable_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)
# set up other widgets
self.load_widget = LoadWidget(self.loaded_data, self.context, self)
self.home_tab = HomeTabWidget(self.context, self)
self.grouping_tab_widget = GroupingTabWidget(self.context)
self.phase_tab = PhaseTabWidget(self.context, 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.setup_tabs()
self.help_widget = HelpWidget("Muon Analysis 2")
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)
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_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_on_recalulation_finished_notifier()
self.context.data_context.message_notifier.add_subscriber(
self.grouping_tab_widget.group_tab_presenter.message_observer)
def __init__(self, parent=None):
super(FrequencyAnalysisGui, self).__init__(parent)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
try:
check_facility()
except AttributeError as error:
self.warning_popup(error.args[0])
# 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.group_pair_context = MuonGroupPairContext(
self.data_context.check_group_contains_valid_detectors)
self.phase_context = PhaseTableContext()
self.fitting_context = FittingContext()
self.frequency_context = FrequencyContext()
self.context = MuonContext(muon_data_context=self.data_context,
muon_gui_context=self.gui_context,
muon_group_context=self.group_pair_context,
muon_phase_context=self.phase_context,
fitting_context=self.fitting_context,
workspace_suffix=' FD',
frequency_context=self.frequency_context)
# create the dockable widget
self.plot_widget = PlotWidget(self.context)
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.
# 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}, {40},
QtCore.Qt.Horizontal)
# construct all the widgets.
self.load_widget = LoadWidget(self.loaded_data, self.context, self)
self.grouping_tab_widget = GroupingTabWidget(self.context)
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.results_tab = ResultsTabWidget(self.context.fitting_context,
self.context, self)
self.setup_tabs()
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)
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_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_on_recalculation_finished_notifier()
self.transform.set_up_calculation_observers(
self.fitting_tab.fitting_tab_presenter.enable_tab_observer,
self.fitting_tab.fitting_tab_presenter.disable_tab_observer)
self.transform.new_data_observer(
self.fitting_tab.fitting_tab_presenter.input_workspace_observer)
self.transform.new_data_observer(
self.plot_widget.presenter.input_workspace_observer)
self.context.data_context.message_notifier.add_subscriber(
self.grouping_tab_widget.group_tab_presenter.message_observer)
def test_default_model_has_no_selected_function_without_fits(self):
model = ResultsTabModel(FittingContext())
self.assertTrue(model.selected_fit_function() is None)
def test_updating_model_results_table_name(self):
table_name = 'table_name'
model = ResultsTabModel(FittingContext())
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(FittingContext())
self.assertEqual(model.results_table_name(), DEFAULT_TABLE_NAME)
def __init__(self, parent=None):
super(FrequencyAnalysisGui, self).__init__(parent)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
try:
check_facility()
except AttributeError as error:
self.warning_popup(error.args[0])
# 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.group_pair_context = MuonGroupPairContext(
self.data_context.check_group_contains_valid_detectors)
self.phase_context = PhaseTableContext()
self.fitting_context = FittingContext()
self.context = MuonContext(muon_data_context=self.data_context,
muon_gui_context=self.gui_context,
muon_group_context=self.group_pair_context,
muon_phase_context=self.phase_context,
workspace_suffix=' FD',
fitting_context=self.fitting_context)
# construct all the widgets.
self.load_widget = LoadWidget(self.loaded_data, self.context, self)
self.grouping_tab_widget = GroupingTabWidget(self.context)
self.home_tab = HomeTabWidget(self.context, self)
self.phase_tab = PhaseTabWidget(self.context, self)
self.transform = TransformWidget(self.context,
FFTWidget,
MaxEntWidget,
parent=self)
self.setup_tabs()
self.help_widget = HelpWidget("Frequency Domain Analysis")
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)
self.setCentralWidget(central_widget)
self.setWindowTitle("Frequency Domain Analysis")
self.setup_load_observers()
self.setup_gui_variable_observers()
self.setup_alpha_recalculated_observers()
self.setup_grouping_changed_observers()
self.setup_instrument_changed_notifier()
self.setup_group_calculation_enable_notifer()
self.setup_group_calculation_disabler_notifer()
self.setup_on_load_enabler()
self.setup_on_load_disabler()
self.setup_phase_quad_changed_notifer()
self.setup_phase_table_changed_notifier()
self.setup_on_recalulation_finished_notifer()
self.context.data_context.message_notifier.add_subscriber(
self.grouping_tab_widget.group_tab_presenter.message_observer)
def setUp(self):
self.fitting_context = FittingContext()
def test_updating_model_selected_fit_function(self):
model = ResultsTabModel(FittingContext())
new_selection = 'func2'
model.set_selected_fit_function(new_selection)
self.assertEqual(model.selected_fit_function(), new_selection)
def test_model_returns_no_log_selection_if_no_fits_present(self):
model = ResultsTabModel(FittingContext())
self.assertEqual(0, len(model.log_selection({})))
