[Numpy-discussion] small suggestion for numpy.testing utils

[Darren Dale]

Hello,

I am using numpy's assert_array_equal and assert_array_almost_equal to unit
test my physical quantities package. I made a single minor change to
assert_array_compare that I think might make these functions more useful to
ndarray subclasses, and thought maybe they could be useful to numpy itself.
I tried applying this diff to numpy and running the test suite, and instead
of 9 known failures I got 1 known failure, 11 skips, 2 errors and 2
failures. Perhaps it is possible that by not forcing the input arrays to be
ndarray instances, some additional numpy features are exposed.

Thanks,
Darren

$ svn diff
Index: numpy/testing/utils.py
===================================================================
--- numpy/testing/utils.py      (revision 6370)
+++ numpy/testing/utils.py      (working copy)
@@ -240,9 +240,9 @@

 def assert_array_compare(comparison, x, y, err_msg='', verbose=True,
                          header=''):
-    from numpy.core import asarray, isnan, any
-    x = asarray(x)
-    y = asarray(y)
+    from numpy.core import array, isnan, any
+    x = array(x, copy=False, subok=True)
+    y = array(y, copy=False, subok=True)

     def isnumber(x):
         return x.dtype.char in '?bhilqpBHILQPfdgFDG'
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