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

Andrew Straw strawman@astraw....
Sun Feb 22 17:52:48 CST 2009


Darren,

What's the difference between asanyarray(y) and array(y, copy=False, 
subok=True)? I thought asanyarray would also do what you want.

-Andrew

Darren Dale wrote:
> On Sun, Feb 22, 2009 at 3:22 PM, Darren Dale <dsdale24@gmail.com 
> <mailto:dsdale24@gmail.com>> wrote:
>
>     On Sun, Feb 22, 2009 at 3:17 PM, Darren Dale <dsdale24@gmail.com
>     <mailto:dsdale24@gmail.com>> wrote:
>
>         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'
>
>
>     Actually, my svn checkout was not up to date. With this patch
>     applied, I get 1 known failure and 11 skips.
>
>
> I just double checked and I think I get the same results running the 
> svn 6456 test suite with and without this patch applied. I tried 
> posting an enhancement request at the trac website, but I cant file 
> the ticket because I get "500 Internal Server Error", so I'm posting 
> it here.
> ------------------------------------------------------------------------
>
> _______________________________________________
> Numpy-discussion mailing list
> Numpy-discussion@scipy.org
> http://projects.scipy.org/mailman/listinfo/numpy-discussion



More information about the Numpy-discussion mailing list