TST Add test with reduced tolerance

sklearn/utils/extmath.py

@@ -853,12 +853,21 @@ def _deterministic_vector_sign_flip(u):
     return u
 
 
-def stable_cumsum(arr):
+def stable_cumsum(arr, rtol=1e-05, atol=1e-08):
     """Use high precision for cumsum and check that final value matches sum
+
+    Parameters
+    ----------
+    arr : array-like
+        To be cumulatively summed as flat
+    rtol : float
+        Relative tolerance, see ``np.allclose``
+    atol : float
+        Absolute tolerance, see ``np.allclose``
     """
     out = np.cumsum(arr, dtype=np.float64)
     expected = np.sum(arr, dtype=np.float64)
-    if not np.allclose(out[-1], expected):
+    if not np.allclose(out[-1], expected, rtol=rtol, atol=atol):
         raise RuntimeError('cumsum was found to be unstable: '
                            'its last element does not correspond to sum')
     return out

sklearn/utils/tests/test_extmath.py

@@ -17,6 +17,7 @@
 from sklearn.utils.testing import assert_false
 from sklearn.utils.testing import assert_greater
 from sklearn.utils.testing import assert_raises
+from sklearn.utils.testing import assert_raise_message
 from sklearn.utils.testing import skip_if_32bit
 
 from sklearn.utils.extmath import density
@@ -32,6 +33,7 @@
 from sklearn.utils.extmath import _incremental_mean_and_var
 from sklearn.utils.extmath import _deterministic_vector_sign_flip
 from sklearn.utils.extmath import softmax
+from sklearn.utils.extmath import stable_cumsum
 from sklearn.datasets.samples_generator import make_low_rank_matrix
 
 
@@ -643,3 +645,12 @@ def test_softmax():
     exp_X = np.exp(X)
     sum_exp_X = np.sum(exp_X, axis=1).reshape((-1, 1))
     assert_array_almost_equal(softmax(X), exp_X / sum_exp_X)
+
+
+def test_stable_cumsum():
+    assert_array_equal(stable_cumsum([1, 2, 3]), np.cumsum([1, 2, 3]))
+    r = np.random.RandomState(0).rand(100000)
+    assert_raise_message(RuntimeError,
+                         'cumsum was found to be unstable: its last element '
+                         'does not correspond to sum',
+                         stable_cumsum, r, rtol=0, atol=0)