DEBUG print

sklearn/isotonic.py

@@ -154,10 +154,18 @@ def isotonic_regression(
     """
     y = check_array(y, ensure_2d=False, input_name="y", dtype=[np.float64, np.float32])
     if sp_base_version >= parse_version("1.12.0"):
+        do_print = y.shape == (7,) and np.allclose(
+            y, np.array([10, 9, 10, 7, 6, 6.1, 5])
+        )
+        if do_print:
+            print("DEBUG INFO:")
+            print(f"increasing={increasing} sw={sample_weight}\ny={y}")
         res = optimize.isotonic_regression(
             y=y, weights=sample_weight, increasing=increasing
         )
         y = np.asarray(res.x, dtype=y.dtype)
+        if do_print:
+            print(f"After isotonic_regression:\ny={y}")
     else:
         # TODO: remove this branch when Scipy 1.12 is the minimum supported version
         # Also remove _inplace_contiguous_isotonic_regression.

sklearn/tests/test_isotonic.py

@@ -227,7 +227,13 @@ def test_isotonic_regression_with_ties_in_differently_sized_groups():
 
 def test_isotonic_regression_reversed():
     y = np.array([10, 9, 10, 7, 6, 6.1, 5])
+    y_result = np.array([10, 9.5, 9.5, 7, 6.05, 6.05, 5])
+
+    y_iso = isotonic_regression(y, increasing=False)
+    assert_allclose(y_iso, y_result)
+
     y_ = IsotonicRegression(increasing=False).fit_transform(np.arange(len(y)), y)
+    assert_allclose(y_, y_result)
     assert_array_equal(np.ones(y_[:-1].shape), ((y_[:-1] - y_[1:]) >= 0))