On Wed, Jul 7, 2010 at 10:13 PM, Christoph Gohlke <[email protected]> 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
>
>
Just for laughs, what happens if you reverse the order of the arguments?
Type promotion in numpy is not always symmetric.
<snip>
Chuck
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