def test_empty_results(self):
"""Test on empty results."""
res = Results(data=self.iris[:0], store_data=True)
res.row_indices = np.array([], dtype=int)
res.actual = np.array([])
res.predicted = np.array([[]])
res.probabilities = np.zeros((1, 0, 3))
self.send_signal(self.widget.Inputs.evaluation_results, res)
self.widget.select_correct()
self.widget.select_wrong()
def test_empty_results(self):
"""Test on empty results."""
res = Results(data=self.iris[:0], store_data=True)
res.row_indices = np.array([], dtype=int)
res.actual = np.array([])
res.predicted = np.array([[]])
res.probabilities = np.zeros((1, 0, 3))
self.send_signal(self.widget.Inputs.evaluation_results, res)
self.widget.select_correct()
self.widget.select_wrong()
def test_nan_results(self):
"""Test on results with nan values in actual/predicted"""
res = Results(data=self.iris, nmethods=2, store_data=True)
res.row_indices = np.array([0, 50, 100], dtype=int)
res.actual = np.array([0., np.nan, 2.])
res.predicted = np.array([[np.nan, 1, 2], [np.nan, np.nan, np.nan]])
res.probabilities = np.zeros((1, 3, 3))
self.send_signal(self.widget.Inputs.evaluation_results, res)
self.assertTrue(self.widget.Error.invalid_values.is_shown())
self.send_signal(self.widget.Inputs.evaluation_results, None)
self.assertFalse(self.widget.Error.invalid_values.is_shown())
def test_nan_results(self):
"""Test on results with nan values in actual/predicted"""
res = Results(data=self.iris, nmethods=2, store_data=True)
res.row_indices = np.array([0, 50, 100], dtype=int)
res.actual = np.array([0., np.nan, 2.])
res.predicted = np.array([[np.nan, 1, 2],
[np.nan, np.nan, np.nan]])
res.probabilities = np.zeros((1, 3, 3))
self.send_signal(self.widget.Inputs.evaluation_results, res)
self.assertTrue(self.widget.Error.invalid_values.is_shown())
self.send_signal(self.widget.Inputs.evaluation_results, None)
self.assertFalse(self.widget.Error.invalid_values.is_shown())
def get_fold(self, fold):
results = Results()
results.data = self.data
if self.folds is None:
raise ValueError("This 'Results' instance does not have folds.")
if self.models is not None:
results.models = self.models[fold]
results.row_indices = self.row_indices
results.actual = self.actual
results.predicted = self.predicted[:, fold, :]
results.domain = self.domain
return results
