add end to end tests

Author: mastoffel

tests/test_end_to_end.py

@@ -0,0 +1,59 @@
+import numpy as np
+import pytest
+from sklearn.model_selection import KFold
+
+from autoemulate.compare import AutoEmulate
+
+
+@pytest.fixture()
+def kfold():
+    return KFold(n_splits=2)
+
+
+@pytest.fixture()
+def Xy_single():
+    X = np.random.rand(15, 2)
+    y = np.random.rand(15)
+    return X, y
+
+
+@pytest.fixture()
+def Xy_multi():
+    X = np.random.rand(10, 2)
+    y = np.random.rand(10, 2)
+    return X, y
+
+
+@pytest.mark.parametrize("Xy", ["Xy_single", "Xy_multi"])
+def test_run(Xy, request):
+    X, y = request.getfixturevalue(Xy)
+    em = AutoEmulate()
+    em.setup(X, y, print_setup=False)
+    em.compare()
+    assert em.best_model is not None
+    assert em.cv_results is not None
+
+
+def test_run_param_search(Xy_single, kfold):
+    X, y = Xy_single
+    em = AutoEmulate()
+    em.setup(
+        X,
+        y,
+        print_setup=False,
+        param_search=True,
+        param_search_iters=2,
+        cross_validator=kfold,
+    )
+    em.compare()
+    assert em.best_model is not None
+    assert em.cv_results is not None
+
+
+def test_run_parallel(Xy_single, kfold):
+    X, y = Xy_single
+    em = AutoEmulate()
+    em.setup(X, y, print_setup=False, cross_validator=kfold, n_jobs=2)
+    em.compare()
+    assert em.best_model is not None
+    assert em.cv_results is not None