def test_multiple_runs(self):
w = self.widgetClass
previewer = WidgetPreview(w)
previewer.run(42, no_exit=True)
w.int1(43)
previewer.send_signals([(44, 1), (45, 2)])
previewer.run(46, no_exit=True)
w.int1.assert_has_calls(
[call(42), call(43), call(44, 1), call(45, 2), call(46)])
def test_multiple_runs(self):
w = self.widgetClass
previewer = WidgetPreview(w)
previewer.run(42, no_exit=True)
w.int1(43)
previewer.send_signals([(44, 1), (45, 2)])
previewer.run(46, no_exit=True)
w.int1.assert_has_calls(
[call(42), call(43),
call(44, 1),
call(45, 2),
call(46)])
def test_widget_is_shown_and_ran(self):
w = self.widgetClass
app.exec_.reset_mock()
previewer = WidgetPreview(w)
previewer.run()
w.show.assert_called()
w.show.reset_mock()
app.exec_.assert_called()
app.exec_.reset_mock()
w.saveSettings.assert_called()
w.saveSettings.reset_mock()
sys.exit.assert_called()
sys.exit.reset_mock()
self.assertIsNone(previewer.widget)
previewer.run(no_exit=True)
w.show.assert_called()
w.show.reset_mock()
app.exec_.assert_called()
app.exec_.reset_mock()
w.saveSettings.assert_not_called()
sys.exit.assert_not_called()
self.assertIsNotNone(previewer.widget)
widget = previewer.widget
previewer.run(no_exec=True, no_exit=True)
w.show.assert_not_called()
app.exec_.assert_not_called()
w.saveSettings.assert_not_called()
sys.exit.assert_not_called()
self.assertIs(widget, previewer.widget)
previewer.run(no_exec=True)
w.show.assert_not_called()
app.exec_.assert_not_called()
w.saveSettings.assert_called()
sys.exit.assert_called()
self.assertIsNone(previewer.widget)
def test_widget_is_shown_and_ran(self):
w = self.widgetClass
app.exec_.reset_mock()
previewer = WidgetPreview(w)
previewer.run()
w.show.assert_called()
w.show.reset_mock()
app.exec_.assert_called()
app.exec_.reset_mock()
w.saveSettings.assert_called()
w.saveSettings.reset_mock()
sys.exit.assert_called()
sys.exit.reset_mock()
self.assertIsNone(previewer.widget)
previewer.run(no_exit=True)
w.show.assert_called()
w.show.reset_mock()
app.exec_.assert_called()
app.exec_.reset_mock()
w.saveSettings.assert_not_called()
sys.exit.assert_not_called()
self.assertIsNotNone(previewer.widget)
widget = previewer.widget
previewer.run(no_exec=True, no_exit=True)
w.show.assert_not_called()
app.exec_.assert_not_called()
w.saveSettings.assert_not_called()
sys.exit.assert_not_called()
self.assertIs(widget, previewer.widget)
previewer.run(no_exec=True)
w.show.assert_not_called()
app.exec_.assert_not_called()
w.saveSettings.assert_called()
sys.exit.assert_called()
self.assertIsNone(previewer.widget)
headerState = headerState[0]
if isinstance(headerState, bytes):
hview = QHeaderView(Qt.Horizontal)
hview.restoreState(headerState)
column, order = hview.sortIndicatorSection() - 1, hview.sortIndicatorOrder()
settings["sorting"] = (column, order)
@classmethod
def migrate_context(cls, context, version):
if version is None or version < 2:
# Old selection was saved as sorted indices. New selection is original indices.
# Since we can't devise the latter without first computing the ranks,
# just reset the selection to avoid confusion.
context.values['selected_rows'] = []
if __name__ == "__main__": # pragma: no cover
from Orange.classification import RandomForestLearner
previewer = WidgetPreview(OWRank)
previewer.run(Table("heart_disease.tab"), no_exit=True)
previewer.send_signals(
set_learner=(RandomForestLearner(), (3, 'Learner', None)))
previewer.run()
"""
WidgetPreview(OWRank).run(
set_learner=(RandomForestLearner(), (3, 'Learner', None)),
set_data=Table("heart_disease.tab"))
"""
if self.use_min_count:
filters.append(
FilterProxyModel.Filter(Header.count, Qt.DisplayRole,
lambda value: value >= self.min_count))
return filters
def filter_view(self):
filter_proxy: FilterProxyModel = self.filter_proxy_model
model: QStandardItemModel = filter_proxy.sourceModel()
if isinstance(model, QStandardItemModel):
# apply filtering rules
filter_proxy.set_filters(self.create_filters())
if model.rowCount() and not filter_proxy.rowCount():
self.Warning.all_sets_filtered()
else:
self.Warning.clear()
def sizeHint(self):
return QSize(800, 600)
if __name__ == "__main__":
from Orange.widgets.utils.widgetpreview import WidgetPreview
widget = WidgetPreview(OWGeneSets)
widget.run()
if isinstance(headerState, bytes):
hview = QHeaderView(Qt.Horizontal)
hview.restoreState(headerState)
column, order = hview.sortIndicatorSection() - 1, hview.sortIndicatorOrder()
settings["sorting"] = (column, order)
@classmethod
def migrate_context(cls, context, version):
if version is None or version < 2:
# Old selection was saved as sorted indices. New selection is original indices.
# Since we can't devise the latter without first computing the ranks,
# just reset the selection to avoid confusion.
context.values['selected_rows'] = []
if __name__ == "__main__": # pragma: no cover
from Orange.classification import RandomForestLearner
previewer = WidgetPreview(OWRank)
previewer.run(Table("heart_disease.tab"), no_exit=True)
previewer.send_signals(
set_learner=(RandomForestLearner(), (3, 'Learner', None)))
previewer.run()
# pylint: disable=pointless-string-statement
"""
WidgetPreview(OWRank).run(
set_learner=(RandomForestLearner(), (3, 'Learner', None)),
set_data=Table("heart_disease.tab"))
"""
self.model.index(0, 0),
self.model.index(n_selected - 1, column_count - 1))
else:
selection = QItemSelection()
if self.selected_attrs is not None:
attr_indices = [
self.covariates_from_worker_result.index(var.name)
for var in self.selected_attrs
]
for row in self.model.mapFromSourceRows(attr_indices):
selection.append(
QItemSelectionRange(
self.model.index(row, 0),
self.model.index(row, column_count - 1)))
selection_model.select(selection, QItemSelectionModel.ClearAndSelect)
def on_select(self):
selected_rows = self.table_view.selectionModel().selectedRows(0)
row_indices = [i.row() for i in selected_rows]
attr_indices = self.model.mapToSourceRows(row_indices)
self.selected_attrs = [
self.model._headers[Qt.Vertical][row] for row in attr_indices
]
self.commit()
if __name__ == '__main__':
previewer = WidgetPreview(OWRankSurvivalFeatures)
previewer.run(Table('iris.tab'))
