MAINT: speed up _block by avoiding a recursive closure

1 files changed, 15 insertions, 18 deletions

diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py
index 30919ed7e..52717abda 100644
--- a/numpy/core/shape_base.py
+++ b/numpy/core/shape_base.py
@@ -7,7 +7,6 @@ __all__ = ['atleast_1d', 'atleast_2d', 'atleast_3d', 'block', 'hstack',
 from . import numeric as _nx
 from .numeric import array, asanyarray, newaxis
 from .multiarray import normalize_axis_index
-from ._internal import recursive
 
 def atleast_1d(*arys):
     """
@@ -438,7 +437,13 @@ def _block_check_depths_match(arrays, parent_index=[]):
         return parent_index, _nx.ndim(arrays)
 
 
-def _block(arrays, max_depth, result_ndim):
+def _atleast_nd(a, ndim):
+    # Ensures `a` has at least `ndim` dimensions by prepending
+    # ones to `a.shape` as necessary
+    return array(a, ndmin=ndim, copy=False, subok=True)
+
+
+def _block(arrays, max_depth, result_ndim, depth=0):
     """
     Internal implementation of block. `arrays` is the argument passed to
     block. `max_depth` is the depth of nested lists within `arrays` and
@@ -446,22 +451,14 @@ def _block(arrays, max_depth, result_ndim):
     `arrays` and the depth of the lists in `arrays` (see block docstring
     for details).
     """
-    def atleast_nd(a, ndim):
-        # Ensures `a` has at least `ndim` dimensions by prepending
-        # ones to `a.shape` as necessary
-        return array(a, ndmin=ndim, copy=False, subok=True)
-
-    @recursive
-    def block_recursion(self, arrays, depth=0):
-        if depth < max_depth:
-            arrs = [self(arr, depth+1) for arr in arrays]
-            return _nx.concatenate(arrs, axis=-(max_depth-depth))
-        else:
-            # We've 'bottomed out' - arrays is either a scalar or an array
-            # type(arrays) is not list
-            return atleast_nd(arrays, result_ndim)
-
-    return block_recursion(arrays)
+    if depth < max_depth:
+        arrs = [_block(arr, max_depth, result_ndim, depth+1)
+                for arr in arrays]
+        return _nx.concatenate(arrs, axis=-(max_depth-depth))
+    else:
+        # We've 'bottomed out' - arrays is either a scalar or an array
+        # type(arrays) is not list
+        return _atleast_nd(arrays, result_ndim)
 
 
 def block(arrays):