def test_selected_backend(self, mocked_backends: mock.Mock):
b1, b2 = mock.Mock(), mock.Mock()
b1.display_name = "B1"
b2.display_name = "B2"
mocked_backends.return_value = [b1, b2]
widget = self.create_widget(OWSql)
self.assertEqual(widget.backendcombo.currentText(), "B1")
simulate.combobox_activate_index(widget.backendcombo, 1)
self.assertEqual(widget.backendcombo.currentText(), "B2")
settings = widget.settingsHandler.pack_data(widget)
widget = self.create_widget(OWSql, stored_settings=settings)
self.assertEqual(widget.backendcombo.currentText(), "B2")
settings = widget.settingsHandler.pack_data(widget)
settings["selected_backend"] = "B3"
widget = self.create_widget(OWSql, stored_settings=settings)
self.assertEqual(widget.backendcombo.currentText(), "B1")
mocked_backends.return_value = []
settings = widget.settingsHandler.pack_data(widget)
widget = self.create_widget(OWSql, stored_settings=settings)
self.assertEqual(widget.backendcombo.currentText(), "")
def test_nans(self):
"""Widget does not crash with nans"""
self.send_signal(self.widget.Inputs.data, self.heart_disease)
self.assertIsNotNone(self.get_output(self.widget.Outputs.inliers))
simulate.combobox_activate_index(self.widget.method_combo,
self.widget.Covariance)
self.assertIsNotNone(self.get_output(self.widget.Outputs.inliers))
self.assertFalse(self.widget.Error.singular_cov.is_shown())
def test_datasets(self):
self.widget.controls.show_strip_plot.setChecked(True)
self.widget.controls.show_rug_plot.setChecked(True)
for ds in datasets.datasets():
self.send_signal(self.widget.Inputs.data, ds)
for i in range(3):
cb = self.widget.controls.scale_index
simulate.combobox_activate_index(cb, i)
def test_methods(self):
self.send_signal(self.widget.Inputs.data, self.data)
method_cb = self.widget.controls.method_index
for i, (cls, _, _) in enumerate(LearnerItemModel.LEARNERS):
if cls is None:
continue
simulate.combobox_activate_index(method_cb, i)
self.widget.apply_button.button.click()
self.assertIsInstance(self.widget.learner, cls)
def test_scoring_method_control(self):
self._restore_annotation_functions()
self.send_signal(self.widget.Inputs.genes, self.genes)
self.send_signal(self.widget.Inputs.data, self.data)
self.wait_until_stop_blocking(wait=TIMEOUT)
output1 = self.get_output(self.widget.Outputs.annotated_data)
cbox = self.widget.controls.scoring_method
simulate.combobox_activate_index(cbox, 2)
self.widget.run_button.click()
self.wait_until_stop_blocking(wait=TIMEOUT)
output2 = self.get_output(self.widget.Outputs.annotated_data)
np.testing.assert_array_equal(output1.X, output2.X)
np.testing.assert_array_equal(output1.Y, output2.Y)
self._patch_annotation_functions()
def test_color_by_cluster(self):
self._restore_annotation_functions()
self.send_signal(self.widget.Inputs.genes, self.genes)
self.send_signal(self.widget.Inputs.data, self.data)
self.wait_until_stop_blocking(wait=TIMEOUT)
self.assertTrue(self.widget.controls.attr_color.isEnabled())
simulate.combobox_activate_index(self.widget.controls.attr_color, 0)
is_grey = [brush.color().name() == "#808080" for brush in self.widget.graph.scatterplot_item.data['brush']]
self.assertTrue(all(is_grey))
self.widget.controls.color_by_cluster.click()
self.assertFalse(self.widget.controls.attr_color.isEnabled())
is_not_grey = [brush.color().name() != "#808080" for brush in self.widget.graph.scatterplot_item.data['brush']]
self.assertTrue(any(is_not_grey))
self._patch_annotation_functions()
def test_statistical_test_control(self):
self._restore_annotation_functions()
self.send_signal(self.widget.Inputs.genes, self.genes)
self.send_signal(self.widget.Inputs.data, self.data)
self.wait_until_finished(timeout=TIMEOUT)
output1 = self.get_output(self.widget.Outputs.annotated_data)
cbox = self.widget.controls.statistical_test
simulate.combobox_activate_index(cbox, 1)
self.widget.run_button.click()
self.wait_until_finished(timeout=TIMEOUT)
output2 = self.get_output(self.widget.Outputs.annotated_data)
np.testing.assert_array_equal(output1.X, output2.X)
np.testing.assert_array_equal(output1.Y, output2.Y)
self.assertFalse((output1.metas == output2.metas).all())
self._patch_annotation_functions()
def test_xgb_params(self):
simulate.combobox_activate_index(self.widget.controls.method_index, 1)
editor = self.widget.editor
controls = editor.controls
reg_slider = controls.lambda_index
self.parameters = [
ParameterMapping("n_estimators", controls.n_estimators, [500, 10]),
ParameterMapping("learning_rate", controls.learning_rate),
ParameterMapping("max_depth", controls.max_depth),
ParameterMapping("reg_lambda",
reg_slider,
values=[editor.LAMBDAS[0], editor.LAMBDAS[-1]],
getter=lambda: editor.LAMBDAS[reg_slider.value()],
setter=lambda val: reg_slider.setValue(
editor.LAMBDAS.index(val))),
]
self.test_parameters()
def test_output_empirical_covariance(self):
simulate.combobox_activate_index(self.widget.method_combo,
self.widget.Covariance)
self.send_signal(self.widget.Inputs.data, self.iris)
inliers = self.get_output(self.widget.Outputs.inliers)
outliers = self.get_output(self.widget.Outputs.outliers)
data = self.get_output(self.widget.Outputs.data)
self.assertEqual(len(inliers), 135)
self.assertEqual(len(outliers), 15)
self.assertEqual(len(data), 150)
self.assertEqual(len(inliers.domain.attributes), 4)
self.assertEqual(len(outliers.domain.attributes), 4)
self.assertEqual(len(data.domain.attributes), 4)
self.assertEqual(len(inliers.domain.class_vars), 1)
self.assertEqual(len(outliers.domain.class_vars), 1)
self.assertEqual(len(data.domain.class_vars), 1)
self.assertEqual(len(inliers.domain.metas), 0)
self.assertEqual(len(outliers.domain.metas), 0)
self.assertEqual(len(data.domain.metas), 2)
self.assertEqual([m.name for m in data.domain.metas],
["Outlier", "Mahalanobis"])
def test_axis_controls(self):
self.send_signal(self.widget.Inputs.corpus, self.corpus)
simulate.combobox_activate_index(self.widget.controls.attr_y, 0)
self.assertTrue(self.widget.Warning.same_axis_features.is_shown())
self.send_signal(self.widget.Inputs.corpus, None)
self.assertFalse(self.widget.Warning.same_axis_features.is_shown())
