[Numpy-discussion] TypeError when using double , longdouble in numpy.dot

[Christoph Gohlke]

On 7/7/2010 9:43 PM, Charles R Harris wrote:
>
>
> On Wed, Jul 7, 2010 at 10:13 PM, Christoph Gohlke <cgohlke at uci.edu
> <mailto:cgohlke at uci.edu>> wrote:
>
>     Dear NumPy developers,
>
>     I am trying to solve some scipy.sparse TypeError failures reported in
>     [1] and reduced them to the following example:
>
>
>     > >> import numpy
>     > >> a = numpy.array([[1]])
>
>     > >> numpy.dot(a.astype('single'), a.astype('longdouble'))
>     array([[1.0]], dtype=float64)
>
>     > >> numpy.dot(a.astype('double'), a.astype('longdouble'))
>     Traceback (most recent call last):
>        File "<stdin>", line 1, in <module>
>     TypeError: array cannot be safely cast to required type
>
>
>     Is this exception expected?
>
>
> I think not. On some platforms longdouble is the same as double, on
> others it is extended precision or quad precision. On your platform this
> looks like a bug, on my platform it would be correct except there is a
> fallback version of dot that works with extended precision. Is there a
> mix of compilers here, or is it msvc all the way down.

Yes, msvc9 all the way down. It fails no matter whether I build with 
setup.py or setupscons.py. Using mingw build gives the expected results.


>
> In [5]: a = array([[1]])
>
> In [6]: dot(a.astype('single'), a.astype('longdouble'))
> Out[6]: array([[1.0]], dtype=float128)
>
>
>     Also I noticed this:
>
>     > >> numpy.array([1]).astype('longdouble').dtype.num
>     13
>     > >> numpy.array([1.0]).astype('longdouble').dtype.num
>     12
>
>
> Yeah, that is probably correct in a strange sort of way since the two
> types are identical under the hood. On ubuntu I get
>
> In [1]: array([1]).astype('longdouble').dtype.num
> Out[1]: 13
>
> In [2]: array([1.]).astype('longdouble').dtype.num
> Out[2]: 13
>
> Type numbers aren't a good way to determine precision in a platform
> independent way.


I should have mentioned that the following example works for me:

>>> a = numpy.array([[1.0]])
>>> numpy.dot(a.astype('double'), a.astype('longdouble'))
array([[ 1.]])


--
Christoph