def test_Pipegraph__filter_nodes_predict(self):
alternative_connections = {'Regressor': dict(X='X', y='y')}
pgraph = PipeGraph(steps=self.steps,
fit_connections=self.connections,
predict_connections=alternative_connections)
pgraph.fit(self.X, self.y)
predict_nodes = list(pgraph._filter_predict_nodes())
self.assertEqual(predict_nodes, ['Regressor'])
def test_Pipegraph__predict_connections(self):
pgraph = PipeGraph(self.steps, self.connections)
pgraph.fit(self.X, self.y)
predict_nodes_list = list(pgraph._filter_predict_nodes())
self.assertEqual(
sorted(predict_nodes_list),
sorted([
'Concatenate_Xy',
'Gaussian_Mixture',
'Dbscan',
'Combine_Clustering',
'Regressor',
]))
def test_Pipegraph__some_predict_connections(self):
some_connections = {
'Concatenate_Xy': dict(df1='X', df2='y'),
'Gaussian_Mixture': dict(X=('Concatenate_Xy', 'predict')),
'Dbscan': dict(X=('Concatenate_Xy', 'predict')),
}
pgraph = PipeGraph(steps=self.steps,
fit_connections=self.connections,
predict_connections=some_connections)
pgraph.fit(self.X, self.y)
predict_nodes_list = list(pgraph._filter_predict_nodes())
self.assertEqual(
sorted(predict_nodes_list),
sorted([
'Concatenate_Xy',
'Gaussian_Mixture',
'Dbscan',
]))
