On 11/12/06, Erin Sheldon <[EMAIL PROTECTED]> wrote:
> On 11/12/06, Pierre GM <[EMAIL PROTECTED]> wrote:
> >
> > You could try the fromarrays function of numpy.core.records
> >
> > >>> mydescriptor = {'names': (a','b','c','d'), 'formats':('f4', 'f4', 'f4',
> > 'f4')}
> > >>> a = N.core.records.fromarrays(N.transpose(yourlist), dtype=mydescriptor)
> >
> > The 'transpose' function ensures that 'fromarrays' sees 4 arrays (one for
> > each
> > column).
Actually, there is a problem with that approach. It first converts
the entire array to a single type, by default a floating type. For
very large integers this precision is insufficient. For example, I
have the following integer in my arrays:
94137100072000193L
which ends up as
94137100072000192
after going to a float and then back to an integer.
Erin
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