[Numpy-discussion] small suggestion for numpy.testing utils
Sun Feb 22 14:17:36 CST 2009
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.
$ svn diff
--- 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,
- 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)
return x.dtype.char in '?bhilqpBHILQPfdgFDG'
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