4 Apr
2013
4 Apr
'13
4:07 p.m.
On Apr 4, 2013, at 12:42 PM, James Stroud wrote:
So, even if numpy-to-flex conversion catches wrongly [1] typed arrays, users still need to know which numpy dtypes to use for which flex constructors. Here is what I have determined:
I realized that it is possible that unqualified specifiers like "numpy.float", etc, may have different meanings on different systems. Therefore, I think a better (i.e. more explicit) mapping is flex.bool : numpy.bool8 flex.int : numpy.int32 flex.long : numpy.int64 flex.float : numpy.float32 flex.double : numpy.float64 James