On Sun, Feb 22, 2009 at 3:17 PM, Darren Dale <dsdal...@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.
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