> > > def __new__(info_arr_cls,arr,info={}):
> > > info_arr_cls.info = info
> > > return N.array(arr).view(info_arr_cls)
>
> One has to be careful of this approach. It ads *the same* information
> to all arrays, i.e.
Indeed. That's basically why you have to edit your __array_finalize__ .
class InfoArray(N.ndarray):
def __new__(info_arr_cls,arr,info={}):
info_arr_cls._info = info
return N.array(arr).view(info_arr_cls)
def __array_finalize__(self, obj):
if hasattr(obj,'info'):
self.info = obj.info
else:
self.info = self._info
return
OK, so you end up w/ two attributes 'info' and '_info', the latter having the
info you want, the latter playing a temporary placeholder. That looks a bit
overkill, but that works pretty nice.
a = InfoArray(N.array([1,2,3]),{1:1})
b = InfoArray(N.array([1,2,3]),{1:2})
assert a.info=={1:1}
assert b.info=={1:2}
assert (a+1).info==a.info
assert (b-2).info==b.info
------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642
_______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion