DEBUG test_compute_bias_numerical_feature

src/model_diagnostics/calibration/tests/test_identification.py

@@ -234,6 +234,9 @@ def test_compute_bias_numerical_feature():
     # With polars==0.19.19, to_numpy() returns polars.series._numpy.SeriesView instead
     # of numpy array. Therefore, we add the np.asarray().
     bias = np.asarray((df.get_column("y_pred") - df.get_column("y_obs")).to_numpy())
+    assert n_steps == 10
+    assert np.sqrt(n_steps) == pytest.approx(3.1622776601683795)
+    assert np.std(bias[: n_steps], ddof=1) == pytest.approx(0.030276503540974924)
     df_expected = pl.DataFrame(
         {
             "feature": 0.045 + 0.1 * np.arange(10),