ENH: Implement initial kwarg for ufunc.add.reduce

1 files changed, 13 insertions, 8 deletions

diff --git a/numpy/core/_methods.py b/numpy/core/_methods.py
index 0f928676b..33f6d01a8 100644
--- a/numpy/core/_methods.py
+++ b/numpy/core/_methods.py
@@ -11,6 +11,7 @@ from numpy.core import multiarray as mu
 from numpy.core import umath as um
 from numpy.core.numeric import asanyarray
 from numpy.core import numerictypes as nt
+from numpy._globals import _NoValue
 
 # save those O(100) nanoseconds!
 umr_maximum = um.maximum.reduce
@@ -22,17 +23,21 @@ umr_all = um.logical_and.reduce
 
 # avoid keyword arguments to speed up parsing, saves about 15%-20% for very
 # small reductions
-def _amax(a, axis=None, out=None, keepdims=False):
-    return umr_maximum(a, axis, None, out, keepdims)
+def _amax(a, axis=None, out=None, keepdims=False,
+          initial=_NoValue):
+    return umr_maximum(a, axis, None, out, keepdims, initial)
 
-def _amin(a, axis=None, out=None, keepdims=False):
-    return umr_minimum(a, axis, None, out, keepdims)
+def _amin(a, axis=None, out=None, keepdims=False,
+          initial=_NoValue):
+    return umr_minimum(a, axis, None, out, keepdims, initial)
 
-def _sum(a, axis=None, dtype=None, out=None, keepdims=False):
-    return umr_sum(a, axis, dtype, out, keepdims)
+def _sum(a, axis=None, dtype=None, out=None, keepdims=False,
+         initial=_NoValue):
+    return umr_sum(a, axis, dtype, out, keepdims, initial)
 
-def _prod(a, axis=None, dtype=None, out=None, keepdims=False):
-    return umr_prod(a, axis, dtype, out, keepdims)
+def _prod(a, axis=None, dtype=None, out=None, keepdims=False,
+          initial=_NoValue):
+    return umr_prod(a, axis, dtype, out, keepdims, initial)
 
 def _any(a, axis=None, dtype=None, out=None, keepdims=False):
     return umr_any(a, axis, dtype, out, keepdims)