This commit removes remaining deprecated bias and ddof arguments from

Abhi210 · Abhi210 · commit 6b395001dd10 · 2025-10-17T13:45:33.000+05:30
`numpy.ma.extras` and updates the related tests.

In addition:
- Removed redundant declarations of `bias` and `ddof` in `extras.py`
  (deprecated since NumPy 2.0)
- Removed associated tests from `test_extras.py` and `test_regression.py`
- Amended `numpy/lib/_function_base_impl.py` to fully remove these arguments
  from function signatures and ensure consistency with documentation
- Documented the above changes in the release notes

All tests and Ruff checks pass locally.
diff --git a/doc/release/upcoming_changes/29997.expired.rst b/doc/release/upcoming_changes/29997.expired.rst
@@ -1,12 +1,11 @@
-Removal of deprecated `trapz` function, `disp` method, and `bias`/`ddof` args in `corrcoef`
+Removal of deprecated `trapz` function, `disp` function, and `bias`/`ddof` args in `corrcoef`
 -------------------------------------------------------------------------------------------
 
 The following long-deprecated APIs have been removed:
 
 * ``numpy.trapz`` — deprecated since NumPy 2.0 (2023-08-18). Use ``numpy.trapezoid`` or
   ``scipy.integrate`` functions instead.
-* ``disp`` method — deprecated in earlier releases and no longer functional. Use your own printing function instead.
+* ``disp`` function — deprecated from 2.0 release and no longer functional. Use your own printing function instead.
 * ``bias`` and ``ddof`` arguments in ``numpy.corrcoef`` — these had no effect since NumPy 1.10.
 
-Associated tests and type stubs have been updated or removed accordingly.
 
diff --git a/numpy/lib/_function_base_impl.py b/numpy/lib/_function_base_impl.py
@@ -2869,13 +2869,13 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
     return c.squeeze()
 
 
-def _corrcoef_dispatcher(x, y=None, rowvar=None, bias=None, ddof=None, *,
+def _corrcoef_dispatcher(x, y=None, rowvar=None,*,
                          dtype=None):
     return (x, y)
 
 
 @array_function_dispatch(_corrcoef_dispatcher)
-def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue, *,
+def corrcoef(x, y=None, rowvar=True, *,
              dtype=None):
     """
     Return Pearson product-moment correlation coefficients.
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
@@ -1729,8 +1729,8 @@ def cov(x, y=None, rowvar=True, bias=False, allow_masked=True, ddof=None):
     return result
 
 
-def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, allow_masked=True,
-             ddof=np._NoValue):
+def corrcoef(x, y=None, rowvar=True, allow_masked=True,
+             ):
     """
     Return Pearson product-moment correlation coefficients.
 
@@ -1751,6 +1751,11 @@ def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, allow_masked=True,
         variable, with observations in the columns. Otherwise, the relationship
         is transposed: each column represents a variable, while the rows
         contain observations.
+    allow_masked : bool, optional
+        If True, masked values are propagated pair-wise: if a value is masked
+        in `x`, the corresponding value is masked in `y`.
+        If False, raises an exception.  Because `bias` is deprecated, this
+        argument needs to be treated as keyword only to avoid a warning.
 
     See Also
     --------
diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py
@@ -1406,80 +1406,30 @@ def _create_data(self):
         data2 = array(np.random.rand(12))
         return data, data2
 
-    def test_ddof(self):
-        # ddof raises DeprecationWarning
-        x, y = self._create_data()
-        expected = np.corrcoef(x)
-        expected2 = np.corrcoef(x, y)
-        with pytest.warns(DeprecationWarning):
-            corrcoef(x, ddof=-1)
-
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-
-            # ddof has no or negligible effect on the function
-            assert_almost_equal(np.corrcoef(x, ddof=0), corrcoef(x, ddof=0))
-            assert_almost_equal(corrcoef(x, ddof=-1), expected)
-            assert_almost_equal(corrcoef(x, y, ddof=-1), expected2)
-            assert_almost_equal(corrcoef(x, ddof=3), expected)
-            assert_almost_equal(corrcoef(x, y, ddof=3), expected2)
-
-    def test_bias(self):
-        x, y = self._create_data()
-        expected = np.corrcoef(x)
-        # bias raises DeprecationWarning
-        with pytest.warns(DeprecationWarning):
-            corrcoef(x, y, True, False)
-        with pytest.warns(DeprecationWarning):
-            corrcoef(x, y, True, True)
-        with pytest.warns(DeprecationWarning):
-            corrcoef(x, y, bias=False)
 
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            # bias has no or negligible effect on the function
-            assert_almost_equal(corrcoef(x, bias=1), expected)
 
     def test_1d_without_missing(self):
         # Test cov on 1D variable w/o missing values
         x = self._create_data()[0]
         assert_almost_equal(np.corrcoef(x), corrcoef(x))
         assert_almost_equal(np.corrcoef(x, rowvar=False),
                             corrcoef(x, rowvar=False))
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True),
-                                corrcoef(x, rowvar=False, bias=True))
 
     def test_2d_without_missing(self):
         # Test corrcoef on 1 2D variable w/o missing values
         x = self._create_data()[0].reshape(3, 4)
         assert_almost_equal(np.corrcoef(x), corrcoef(x))
         assert_almost_equal(np.corrcoef(x, rowvar=False),
                             corrcoef(x, rowvar=False))
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            assert_almost_equal(np.corrcoef(x, rowvar=False, bias=True),
-                                corrcoef(x, rowvar=False, bias=True))
 
     def test_1d_with_missing(self):
         # Test corrcoef 1 1D variable w/missing values
         x = self._create_data()[0]
         x[-1] = masked
         x -= x.mean()
         nx = x.compressed()
-        assert_almost_equal(np.corrcoef(nx), corrcoef(x))
         assert_almost_equal(np.corrcoef(nx, rowvar=False),
                             corrcoef(x, rowvar=False))
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            assert_almost_equal(np.corrcoef(nx, rowvar=False, bias=True),
-                                corrcoef(x, rowvar=False, bias=True))
         try:
             corrcoef(x, allow_masked=False)
         except ValueError:
@@ -1489,14 +1439,6 @@ def test_1d_with_missing(self):
         assert_almost_equal(np.corrcoef(nx, nx[::-1]), corrcoef(x, x[::-1]))
         assert_almost_equal(np.corrcoef(nx, nx[::-1], rowvar=False),
                             corrcoef(x, x[::-1], rowvar=False))
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            # ddof and bias have no or negligible effect on the function
-            assert_almost_equal(np.corrcoef(nx, nx[::-1]),
-                                corrcoef(x, x[::-1], bias=1))
-            assert_almost_equal(np.corrcoef(nx, nx[::-1]),
-                                corrcoef(x, x[::-1], ddof=2))
 
     def test_2d_with_missing(self):
         # Test corrcoef on 2D variable w/ missing value
@@ -1507,16 +1449,6 @@ def test_2d_with_missing(self):
         test = corrcoef(x)
         control = np.corrcoef(x)
         assert_almost_equal(test[:-1, :-1], control[:-1, :-1])
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            # ddof and bias have no or negligible effect on the function
-            assert_almost_equal(corrcoef(x, ddof=-2)[:-1, :-1],
-                                control[:-1, :-1])
-            assert_almost_equal(corrcoef(x, ddof=3)[:-1, :-1],
-                                control[:-1, :-1])
-            assert_almost_equal(corrcoef(x, bias=1)[:-1, :-1],
-                                control[:-1, :-1])
 
 
 class TestPolynomial:
diff --git a/numpy/ma/tests/test_regression.py b/numpy/ma/tests/test_regression.py
@@ -59,18 +59,6 @@ def test_var_sets_maskedarray_scalar(self):
         a.var(out=mout)
         assert_(mout._data == 0)
 
-    def test_ddof_corrcoef(self):
-        # See gh-3336
-        x = np.ma.masked_equal([1, 2, 3, 4, 5], 4)
-        y = np.array([2, 2.5, 3.1, 3, 5])
-        # this test can be removed after deprecation.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                'ignore', "bias and ddof have no effect", DeprecationWarning)
-            r0 = np.ma.corrcoef(x, y, ddof=0)
-            r1 = np.ma.corrcoef(x, y, ddof=1)
-            # ddof should not have an effect (it gets cancelled out)
-            assert_allclose(r0.data, r1.data)
 
     def test_mask_not_backmangled(self):
         # See gh-10314.  Test case taken from gh-3140.
