On Wed, Jan 03, 2007 at 04:29:10AM -0600, eric jones wrote:
> I am playing around with sub-classing the new-fangled float64 objects
> and friends. I really like the new ndarray subclassing features
> (__array_finalize__, etc.), and was exploring whether or not the scalars
> worked the same way. I've stubbed my toe right out of the blocks
> though. I can sub-class from standard python floats just fine, but when
> I try to do the same from float64, I get a traceback. (examples below)
> Anyone have ideas on how to do this correctly?
>
> from numpy import float64
>
> class MyFloat2(float64):
>
> def __new__(cls, data, my_attr=None):
> obj = float64.__new__(cls, data)
> obj.my_attr = my_attr
> return obj
>
> a = MyFloat2(1.2,my_attr="hello")
> print a, a.my_attr
>
>
> output:
> Traceback (most recent call last):
> File "C:\wrk\eric\trunk\src\lib\geo\examples\scalar_subtype.py",
> line 33, in ?
> a = MyFloat2(1.2,my_attr="hello")
> File "C:\wrk\eric\trunk\src\lib\geo\examples\scalar_subtype.py",
> line 30, in __new__
> obj.my_attr = my_attr
> AttributeError: 'numpy.float64' object has no attribute 'my_attr'
With classes defined in C I've often noticed that you can't add
attributes, i.e.
f = N.float64(1.2)
f.x = 1
breaks with
AttributeError: 'numpy.float64' object has no attribute 'x'
The way to fix this for arrays is to first view the array as the new
subclass, i.e.
x = N.array([1])
class Ary(N.ndarray):
pass
x = x.view(Ary)
x.y = 1
However, with floats I noticed that the following fails:
import numpy as N
f = N.float64(1.2)
class Floaty(N.float64):
pass
f.view(Floaty)
with
TypeError: data type cannot be determined from type object
Maybe this is part of the problem?
Regards
Stéfan
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