def set_data(self, data):
self.closeContext()
self.Error.clear()
prev_data, self.data = self.data, data
self.openContext(self.data)
# Make sure to properly enable/disable slider based on `apply_pca` setting
self.controls.pca_components.setEnabled(self.apply_pca)
if prev_data and self.data and ut.array_equal(prev_data.X,
self.data.X):
if self.auto_commit:
self._send_data()
return
# Clear the outputs
self.Outputs.annotated_data.send(None)
if Graph is not None:
self.Outputs.graph.send(None)
# Clear internal state
self.clear()
self._invalidate_pca_projection()
# Make sure the dataset is ok
if self.data is not None and len(self.data.domain.attributes) < 1:
self.Error.empty_dataset()
self.data = None
if self.data is None:
return
# Can't have more PCA components than the number of attributes
n_attrs = len(data.domain.attributes)
self.pca_components_slider.setMaximum(min(_MAX_PCA_COMPONENTS,
n_attrs))
self.pca_components_slider.setValue(
min(_DEFAULT_PCA_COMPONENTS, n_attrs))
# Can't have more k neighbors than there are data points
self.k_neighbors_spin.setMaximum(min(_MAX_K_NEIGBOURS, len(data) - 1))
self.k_neighbors_spin.setValue(min(_DEFAULT_K_NEIGHBORS,
len(data) - 1))
self.info_label.setText("Clustering not yet run.")
self.commit()
def set_data(self, data):
self.closeContext()
self.Error.clear()
prev_data, self.data = self.data, data
self.openContext(self.data)
# Make sure to properly enable/disable slider based on `apply_pca` setting
self.controls.pca_components.setEnabled(self.apply_pca)
if prev_data and self.data and ut.array_equal(prev_data.X, self.data.X):
if self.auto_commit:
self._send_data()
return
# Clear the outputs
self.Outputs.annotated_data.send(None)
if Graph is not None:
self.Outputs.graph.send(None)
# Clear internal state
self.clear()
self._invalidate_pca_projection()
# Make sure the dataset is ok
if self.data is not None and len(self.data.domain.attributes) < 1:
self.Error.empty_dataset()
self.data = None
if self.data is None:
return
# Can't have more PCA components than the number of attributes
n_attrs = len(data.domain.attributes)
self.pca_components_slider.setMaximum(min(_MAX_PCA_COMPONENTS, n_attrs))
self.pca_components_slider.setValue(min(_DEFAULT_PCA_COMPONENTS, n_attrs))
# Can't have more k neighbors than there are data points
self.k_neighbors_spin.setMaximum(min(_MAX_K_NEIGBOURS, len(data) - 1))
self.k_neighbors_spin.setValue(min(_DEFAULT_K_NEIGHBORS, len(data) - 1))
self.info_label.setText("Clustering not yet run.")
self.commit()
def test_with_different_values(self, array):
x = array([0, 1, 0, 0, 2])
y = array([0, 3, 0, 0, 2])
self.assertFalse(array_equal(x, y))
def test_with_different_shapes(self, array):
x = array(np.eye(4))
y = array(np.eye(5))
self.assertFalse(array_equal(x, y))
def test_same_matrices(self, array):
x = array([0, 1, 0, 0, 2])
self.assertTrue(array_equal(x, x))
def test_with_different_values(self, array):
x = array([0, 1, 0, 0, 2])
y = array([0, 3, 0, 0, 2])
self.assertFalse(array_equal(x, y))
def test_with_different_shapes(self, array):
x = array(np.eye(4))
y = array(np.eye(5))
self.assertFalse(array_equal(x, y))
def test_same_matrices(self, array):
x = array([0, 1, 0, 0, 2])
self.assertTrue(array_equal(x, x))