[Numpy-discussion] ANN: NumPy 1.5.0 beta 2

Charles R Harris charlesr.harris@gmail....
Wed Aug 18 07:50:10 CDT 2010


On Wed, Aug 18, 2010 at 12:18 AM, Christoph Gohlke <cgohlke@uci.edu> wrote:

>
>
> On 8/17/2010 9:56 PM, Charles R Harris wrote:
> >
> >
> > On Tue, Aug 17, 2010 at 9:11 PM, Christoph Gohlke <cgohlke@uci.edu
> > <mailto:cgohlke@uci.edu>> wrote:
> >
> >
> >
> >     On 8/17/2010 1:02 PM, Charles R Harris wrote:
> >     >
> >     >
> >     >  On Tue, Aug 17, 2010 at 1:38 PM, Christoph Gohlke <
> cgohlke@uci.edu
> >     <mailto:cgohlke@uci.edu>
> >     >  <mailto:cgohlke@uci.edu <mailto:cgohlke@uci.edu>>> wrote:
> >     >
> >     >
> >     >
> >     >      On 8/17/2010 8:23 AM, Ralf Gommers wrote:
> >     >
> >     >          I am pleased to announce the availability of the second
> >     beta of
> >     >          NumPy
> >     >          1.5.0. This will be the first NumPy release to include
> >     support for
> >     >          Python 3, as well as for Python 2.7.
> >     >
> >     >          Please try this beta and report any problems on the NumPy
> >     >          mailing list.
> >     >          Especially with Python 3 testing will be very useful. On
> Linux
> >     >          and OS X
> >     >          building from source should be straightforward, for
> >     Windows a binary
> >     >          installer is provided. There is one important known issue
> >     on Windows
> >     >          left, in fromfile and tofile (ticket 1583).
> >     >
> >     >          Binaries, sources and release notes can be found at
> >     >  https://sourceforge.net/projects/numpy/files/
> >     >  <https://sourceforge.net/projects/numpy/files/>
> >     >
> >     >          Enjoy,
> >     >          Ralf
> >     >
> >     >
> >     >      NumPy 1.5.0 beta 2 built with msvc9/mkl for Python 2.7 and 3.1
> (32
> >     >      and 64 bit) still reports many (> 200) warnings and three
> >     known test
> >     >      failures/errors. Nothing serious, but it would be nice to
> clean up
> >     >      before the final release.
> >     >
> >     >      The warnings are of the type "Warning: invalid value
> >     encountered in"
> >     >      for the functions reduce, fmax, fmin, logaddexp, maximum,
> greater,
> >     >      less_equal, greater_equal, absolute, and others. I do not see
> >     any of
> >     >      these warnings in the msvc9 builds of numpy 1.4.1.
> >     >
> >     >
> >     >  The warnings were accidentally turned off for earlier versions of
> >     Numpy.
> >     >  I expect these warnings are related to nans and probably due to
> >     problems
> >     >  with isnan or some such. Can you take a closer look? The fmax
> function
> >     >  should be easy to check out.
> >     >
> >     >  <sniip>
> >     >
> >     >  Chuck
> >     >
> >
> >
> >     Thanks for the hint. Warnings are issued in the test_umath test_*nan*
> >     functions. The problem can be condensed to this statement:
> >
> >     > >> numpy.array([numpy.nan]) > 0
> >     Warning: invalid value encountered in greater
> >     array([False], dtype=bool)
> >
> >
> >     When using msvc, ordered comparisons involving NaN raise an exception
> >     [1], i.e. set the 'invalid' x87 status bit, which leads to the
> warning
> >     being printed. I don't know if this violates IEEE 754 or C99
> standards
> >     but it does not happen with the gcc builds. Maybe
> >     seterr(invalid='ignore') could be added to the test_*nan* functions?
> >
> >     [1]
> http://msdn.microsoft.com/en-us/library/e7s85ffb%28v=VS.90%29.aspx
> >
> >
> > OK, this does seem to be the standard. For instance
> >
> > The isless macro determines whether its first argument is less than its
> > second
> > argument. The value of isless(x, y) is always equal to (x) < (y);
> however,
> > unlike (x) < (y), isless(x, y) does not raise the ‘‘invalid’’
> floating-point
> > exception when x and y are unordered.
> >
> > There are other macros for the rest of the comparisons. Can you check if
> > MSVC has these macros available?
> >
>
> MSVC doesn't have these macros. It should not be too difficult to define
> them according to
>
> http://code.google.com/p/v8/source/browse/branches/bleeding_edge/src/platform-win32.cc
>
> int isless(double x, double y) {
>   return isnan(x) || isnan(y) ? 0 : x < y;
> }
>
>
> int isgreater(double x, double y) {
>   return isnan(x) || isnan(y) ? 0 : x > y;
> }
>
>
Looks like we should just rewrite the ufuncs. Having these checks will slow
things down a bit but it is probably the easiest way to make things portable
without doing a lot of complicated work to determine what the platform does.
However, this means that numpy won't ever set exceptions when nans are
encountered and this is a design decision we should make up front.

Chuck
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