[SciPy-dev] Some suggestions for scipy_core
Francesc Altet
faltet at carabos.com
Tue Jan 3 13:07:36 EST 2006
Hi,
Attached is a patch (against SVN 1764) that implements a new typeNA
dictionary that provides mappings between numarray<-->scipy_core
datatypes. This solves a couple of issues:
- Logically separates the datatypes in typeDict (where it remains just
the scipy_core types) from the datatypes present in numarray, that are
in the new typeNA. This also relieves doing ugly mappings in current
typeDict, like 'Complex32'-->complex64_arrtype and
'Complex64'-->complex128_arrtype.
- Now, there is a direct way to get the numarray type coming from a
scipy_core type. For example:
In [27]: q=scicore.array([1],dtype='Q')
In [28]: scicore.typeNA[q.dtypechar]
Out[28]: 'UInt64'
In [29]: scicore.typeNA[q.dtype]
Out[29]: 'UInt64'
that was not possible before.
OTOH, I'd have preferred to follow the numarray convention (except
perhaps for complex types were the full bit-wide would have been more
consistent) for the long string representation of scipy_core types.
For example, we could have:
In [30]: q.dtypedescr.dtypestr
Out[30]: 'UInt64'
which I find clearer than the current:
In [30]: q.dtypedescr.dtypestr
Out[30]: '<u8'
of course, we would have lost the information of the byteorder, but
this is always accessible in:
In [31]: q.dtypedescr.byteorder
Out[31]: '='
Anyway, I guess that Travis has announced the new type naming schema
long time ago and I lost the opportunity to chime in by then, so never
mind.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
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