DEP: add deprecation warning for binom_test

scipy/stats/_morestats.py

@@ -22,6 +22,7 @@
 from ._distn_infrastructure import rv_generic
 from ._hypotests import _get_wilcoxon_distr
 from ._axis_nan_policy import _axis_nan_policy_factory
+from .._lib.deprecation import _deprecated
 
 
 __all__ = ['mvsdist',
@@ -2645,16 +2646,20 @@ def levene(*samples, center='median', proportiontocut=0.05):
     return LeveneResult(W, pval)
 
 
+@_deprecated("'binom_test' is deprecated in favour of"
+             " 'binomtest' from version 1.7.0 and will"
+             " be removed in Scipy 1.12.0.")
 def binom_test(x, n=None, p=0.5, alternative='two-sided'):
     """Perform a test that the probability of success is p.
 
-    Note: `binom_test` is deprecated; it is recommended that `binomtest`
-    be used instead.
-
     This is an exact, two-sided test of the null hypothesis
     that the probability of success in a Bernoulli experiment
     is `p`.
 
+    .. deprecated:: 1.10.0
+        'binom_test' is deprecated in favour of 'binomtest' and will
+        be removed in Scipy 1.12.0.
+
     Parameters
     ----------
     x : int or array_like

scipy/stats/tests/test_morestats.py

@@ -728,10 +728,27 @@ def test_1d_input(self):
         assert_raises(ValueError, stats.levene, g1, x)
 
 
-class TestBinomP:
-    """Tests for stats.binom_test."""
+class TestBinomTestP:
+    """
+    Tests for stats.binomtest as a replacement for deprecated stats.binom_test.
+    """
+    @staticmethod
+    def binom_test_func(x, n=None, p=0.5, alternative='two-sided'):
+        # This processing of x and n is copied from from binom_test.
+        x = np.atleast_1d(x).astype(np.int_)
+        if len(x) == 2:
+            n = x[1] + x[0]
+            x = x[0]
+        elif len(x) == 1:
+            x = x[0]
+            if n is None or n < x:
+                raise ValueError("n must be >= x")
+            n = np.int_(n)
+        else:
+            raise ValueError("Incorrect length for x.")
 
-    binom_test_func = staticmethod(stats.binom_test)
+        result = stats.binomtest(x, n, p=p, alternative=alternative)
+        return result.pvalue
 
     def test_data(self):
         pval = self.binom_test_func(100, 250)
@@ -772,29 +789,6 @@ def test_boost_overflow_raises(self):
         assert_raises(OverflowError, self.binom_test_func, 5.0, 6, p=sys.float_info.min)
 
 
-class TestBinomTestP(TestBinomP):
-    """
-    Tests for stats.binomtest as a replacement for stats.binom_test.
-    """
-    @staticmethod
-    def binom_test_func(x, n=None, p=0.5, alternative='two-sided'):
-        # This processing of x and n is copied from from binom_test.
-        x = np.atleast_1d(x).astype(np.int_)
-        if len(x) == 2:
-            n = x[1] + x[0]
-            x = x[0]
-        elif len(x) == 1:
-            x = x[0]
-            if n is None or n < x:
-                raise ValueError("n must be >= x")
-            n = np.int_(n)
-        else:
-            raise ValueError("Incorrect length for x.")
-
-        result = stats.binomtest(x, n, p=p, alternative=alternative)
-        return result.pvalue
-
-
 class TestBinomTest:
     """Tests for stats.binomtest."""
 

scipy/stats/tests/test_stats.py

@@ -5952,6 +5952,22 @@ def test_masked_3d_array(self):
         assert_equal(gstd_actual.mask, mask)
 
 
+@pytest.mark.parametrize('alternative', ['two-sided', 'greater', 'less'])
+def test_binom_test_deprecation(alternative):
+    deprecation_msg = ("'binom_test' is deprecated in favour of"
+                       " 'binomtest' from version 1.7.0 and will"
+                       " be removed in Scipy 1.12.0.")
+    num = 10
+    rng = np.random.default_rng(156114182869662948677852568516310985853)
+    X = rng.integers(10, 100, (num,))
+    N = X + rng.integers(0, 100, (num,))
+    P = rng.uniform(0, 1, (num,))
+    for x, n, p in zip(X, N, P):
+        with pytest.warns(DeprecationWarning, match=deprecation_msg):
+            res = stats.binom_test(x, n, p, alternative=alternative)
+        assert res == stats.binomtest(x, n, p, alternative=alternative).pvalue
+
+
 def test_binomtest():
     # precision tests compared to R for ticket:986
     pp = np.concatenate((np.linspace(0.1, 0.2, 5),
@@ -5968,10 +5984,9 @@ def test_binomtest():
                2.6102587134694721e-006]
 
     for p, res in zip(pp, results):
-        assert_approx_equal(stats.binom_test(x, n, p), res,
+        assert_approx_equal(stats.binomtest(x, n, p).pvalue, res,
                             significant=12, err_msg='fail forp=%f' % p)
-
-    assert_approx_equal(stats.binom_test(50, 100, 0.1),
+    assert_approx_equal(stats.binomtest(50, 100, 0.1).pvalue,
                         5.8320387857343647e-024,
                         significant=12)
 
@@ -5995,16 +6010,15 @@ def test_binomtest2():
          1.000000000, 0.753906250, 0.343750000, 0.109375000, 0.021484375,
          0.001953125]
     ]
-
     for k in range(1, 11):
-        res1 = [stats.binom_test(v, k, 0.5) for v in range(k + 1)]
+        res1 = [stats.binomtest(v, k, 0.5).pvalue for v in range(k + 1)]
         assert_almost_equal(res1, res2[k-1], decimal=10)
 
 
 def test_binomtest3():
     # test added for issue #2384
     # test when x == n*p and neighbors
-    res3 = [stats.binom_test(v, v*k, 1./k)
+    res3 = [stats.binomtest(v, v*k, 1./k).pvalue
             for v in range(1, 11) for k in range(2, 11)]
     assert_equal(res3, np.ones(len(res3), int))
 
@@ -6086,9 +6100,9 @@ def test_binomtest3():
          0.736270323773157, 0.737718376096348
         ])
 
-    res4_p1 = [stats.binom_test(v+1, v*k, 1./k)
+    res4_p1 = [stats.binomtest(v+1, v*k, 1./k).pvalue
                for v in range(1, 11) for k in range(2, 11)]
-    res4_m1 = [stats.binom_test(v-1, v*k, 1./k)
+    res4_m1 = [stats.binomtest(v-1, v*k, 1./k).pvalue
                for v in range(1, 11) for k in range(2, 11)]
 
     assert_almost_equal(res4_p1, binom_testp1, decimal=13)