[Numpy-discussion] subclassing ndaray

[Stefan van der Walt]

I see the same strange result.  Here is a minimal code example to
demonstrate:

import numpy as N

class Bar(N.ndarray):
    v = 0.
    
    def __new__(cls, *args, **kwargs):
	print "running new"
	return super(Bar, cls).__new__(cls, *args)

    def __init__(self, *args, **kwargs):
	print "running init"
	self[:] = 0
	self.v = 3

In [88]: b = Bar(3)
running new
running init

In [89]: b
Out[89]: Bar([0, 0, 0])

In [90]: b.v
Out[90]: 3

In [91]: c = b+1

In [92]: c.v
Out[92]: 0.0

However, if I do b[:] = 1, everything works fine.

Stéfan

On Fri, Feb 24, 2006 at 10:56:02AM -0500, Colin J. Williams wrote:
> I have a subclass Bar, a 1-dim array which has some methods and some 
> attributes.  One of the attributes is a view of the Bar to permit 
> different shaping.
> 
> Suppose that 'a' is an instance of 'Bar', which has a method 'show' and 
> a view attribute 'v'. 
> 
> a ^ 15 returns a Bar instance, with its methods but without the attributes.
> 
> I am attempt to change this, Bar has a method __xor__, see below:
> 
>      def __xor__(self, other):
>        ''' Exclusive or: __xor__(x, y) => x ^ y . '''
>        z=
>    1                                                                    
>    <<  this loops to the recursion limit
>        result= ArrayType.__xor__(self, other)
>        n= self.n
>        result.n= n
>        result.rowSize= self.rowSize
>        result.show= self.show
>        result.v= _n.reshape(result.view(), (n*n, n*n))
>        return result
> 
> Could anyone suggest a workaround please?
> 
> Colin W.