Added n-ary vector summation

appengine/findit/libs/math/vectors.py

Index: appengine/findit/libs/math/vectors.py
diff --git a/appengine/findit/libs/math/vectors.py b/appengine/findit/libs/math/vectors.py
new file mode 100644
index 0000000000000000000000000000000000000000..62dfe92034b5a47a956eb9200bf51d748464a3b2
--- /dev/null
+++ b/appengine/findit/libs/math/vectors.py
@@ -0,0 +1,41 @@
+# Copyright 2016 The Chromium Authors. All rights reserved.
+# Use of this source code is governed by a BSD-style license that can be
+# found in the LICENSE file.
+
+import math
+import numpy as np
+
+def vsum(xs, shape=None):
+  """Accurate summation of a list of vectors.
+
+  This function is like ``math.fsum`` except operating over collections
+  of vectors rather than collections of scalars.
+
+  Args:
+    xs (list of np.ndarray of float): The vectors to add up.
+    shape (tuple of int): the shape of the vectors. Optional.
+
+  Returns:
+    Returns an ``np.ndarray`` if all is well, otherwise returns
+    ``None``. The situations where all is not well (and so we return
+    ``None``) are: (1) ``xs`` is empty and ``shape`` is not provided;
+    (2) a ``shape`` is provided but does not match the actual shape of
+    the vectors; (3) not all the vectors in the list have the same shape.
+  """
+  if shape is None:
+    if not xs:
+      return None
+
+    shape = xs[0].shape
+
+  # TODO(wrengr): reimplement this in C, inling CPython's implementation

[Martin Barbella, 2016/12/02 19:52:37]

FWIW, I don't think that this is a worthwhile goal. It would be too significant
a maintenance burden for the win it provides.

[Sharu Jiang, 2016/12/02 22:17:51]

+1

+  # of Shewchuk's algorithm, so that we can compute the final vector in
+  # in a single pass over the list of vectors, rather than doing this hack.
+  # <http://svn.python.org/view/python/trunk/Modules/mathmodule.c?view=markup>
+  total = np.zeros(shape)
+  it = np.nditer(total, flags=['multi_index'], op_flags=['writeonly'])
+  while not it.finished:
+    it[0] = math.fsum(x[it.multi_index] for x in xs)
+    it.iternext()
+
+  return total