PERF: Avoid using `@recursive`.

None of the functions decorated with `@recursive` actually need to close
over internal variables, so they can be lifted to become toplevel
recursive functions which avoid the need for an `@recursive` decorator.
(No change was made to the logic of any of the functions.)

As it turns out, the `@recursive` decorator adds a lot of overhead:
`python runtests.py --bench bench_io` reports a ~15-20% perf gain(!)
for `loadtxt` from this PR.  (`_recursive_mask_or` seems less likely to
matter performance-wise, but I also lifted it out for good measure...
and just deleted the decorator's implementation.)

1 files changed, 10 insertions, 12 deletions

diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 431114fe0..d2150919f 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -39,7 +39,6 @@ from numpy.compat import (
     )
 from numpy import expand_dims
 from numpy.core.numeric import normalize_axis_tuple
-from numpy.core._internal import recursive
 
 
 __all__ = [
@@ -1685,6 +1684,16 @@ def make_mask_none(newshape, dtype=None):
     return result
 
 
+def _recursive_mask_or(m1, m2, newmask):
+    names = m1.dtype.names
+    for name in names:
+        current1 = m1[name]
+        if current1.dtype.names is not None:
+            _recursive_mask_or(current1, m2[name], newmask[name])
+        else:
+            umath.logical_or(current1, m2[name], newmask[name])
+
+
 def mask_or(m1, m2, copy=False, shrink=True):
     """
     Combine two masks with the ``logical_or`` operator.
@@ -1722,17 +1731,6 @@ def mask_or(m1, m2, copy=False, shrink=True):
 
     """
 
-    @recursive
-    def _recursive_mask_or(self, m1, m2, newmask):
-        names = m1.dtype.names
-        for name in names:
-            current1 = m1[name]
-            if current1.dtype.names is not None:
-                self(current1, m2[name], newmask[name])
-            else:
-                umath.logical_or(current1, m2[name], newmask[name])
-        return
-
     if (m1 is nomask) or (m1 is False):
         dtype = getattr(m2, 'dtype', MaskType)
         return make_mask(m2, copy=copy, shrink=shrink, dtype=dtype)