Hi All,
So I have a need to use longdouble numpy scalars in an application, and
I need to be able to reliably set long-double precision values in them.
Currently I don't see an easy way to do that. For example:
In [19]: numpy.longdouble("1.12345678901234567890")
Out[19]: 1.1234567890123456912
Note the loss of those last couple digits.
In [20]: numpy.float("1.12345678901234567890")
Out[20]: 1.1234567890123457
In [21]: numpy.longdouble("1.12345678901234567890") -
numpy.float("1.12345678901234567890")
Out[21]: 0.0
And so internally they are identical.
In this case, the string appears to be converted to a C double (i.e.
numpy float) before being assigned to the numpy scalar. And therefore
it loses precision.
Is there a good way of setting longdouble values? Is this a numpy bug?
I was considering using a tiny cython wrapper of strtold() to do a
conversion from a string to a long double, but it seems like this is
basically what should be happening internally in numpy in the above example!
Thanks,
Scott
--
Scott M. Ransom Address: NRAO
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email: [email protected] Charlottesville, VA 22903 USA
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