[SciPy-User] Mapping objects to numpy array

[josef.pktd at gmail.com]

On Wed, Aug 5, 2009 at 9:27 AM, Chris Colbert<sccolbert at gmail.com> wrote:
> its for the same reason you cant do this:
>
> In [1]: a = 1
>
> In [2]: b = a
>
> In [3]: a
> Out[3]: 1
>
> In [4]: b
> Out[4]: 1
>
> In [5]: a = 2
>
> In [6]: a
> Out[6]: 2
>
> In [7]: b
> Out[7]: 1
>
>
> but you CAN do this:
>
> In [8]: a = [1, 2]
>
> In [9]: b = a
>
> In [10]: a
> Out[10]: [1, 2]
>
> In [11]: b
> Out[11]: [1, 2]
>
> In [12]: a[0] = 0
>
> In [13]: a
> Out[13]: [0, 2]
>
> In [14]: b
> Out[14]: [0, 2]
>
>
> floats and ints are immutables in python.
> you'll need a mutable container to store the values how you are wanting.
>
> That said, you still cant map to them with a numpy array like you want (AFAIK)
>
> You may want to look into subclassing ndarray or reformulating your
> problem so you dont need this requirement.
>
>
> On Wed, Aug 5, 2009 at 9:05 AM, Emmanuelle
> Gouillart<emmanuelle.gouillart at normalesup.org> wrote:
>>        Hi Jack,
>>
>>        I don't think you can do it this way. The reason is that p1.x and
>> p1.v can be anywhere in the memory, maybe at very different places. So
>> np.array makes a *copy* when you pass ( p1.x, p1.v) as arguments. I tried
>> setting copy=False as a keyword argument of np.array but it doesn't
>> change the result; apparently a copy has to be made. Why don't you define
>> an array inside the class Particle, instead of different attributes?
>>
>>        Cheers,
>>
>>        Emmanuelle
>>
>> On Wed, Aug 05, 2009 at 02:44:18PM +0200, Jack Liddle wrote:
>>> Hi
>>
>>> I'm trying to map some objects to a numpy array, so I can solve some
>>> ode's with them and then work on the results with my objects.
>>
>>> Here's some code.
>>
>>> from numpy import array
>>
>>> class Particle(object):
>>>    def __init__(self,x,v):
>>>       self.x = x
>>>       self.v = v
>>
>>> p1 = Particle(1,0)
>>> a  = array(( p1.x, p1.v))
>>> a[0] = 5
>>> print p1.x
>>
>>> This prints 1 instead of 5.  How do I make the array 'a' share the
>>> same memory as the p1 attributes?
>>
>>> Any ideas, hope this makes sense
>>
>>> Thanks
>>
>>> Jack Liddle
>>> _______________________________________________
>>> SciPy-User mailing list
>>> SciPy-User at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/scipy-user
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>>
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>

I was trying to do it from scratch, but I got confused about class variables.
Can class variables only be accessed through the class self.__class__
? I seem to get rusty in my python knowledge.

the following seems to do what Emmanuelle proposed, but there might be
better examples already in the mailing lists.

Josef


class Particle(object):
  a  = np.empty((3,2))
  def __init__(self,k,x,v):
     self.k = k
     #why do I need self.__class__ for class variable
     self.__class__.a[k,0] = x
     self.__class__.a[k,1] = v

  def _getx(self):
      return self.__class__.a[self.k,0]
  def _setx(self, value):
      self.__class__.a[self.k,0] = value

  x = property(_getx, _setx)


aa  = Particle.a
print aa
p1 = Particle(0, 1, 2)
print p1
p2 = Particle(1, 2, 3)
p3 = Particle(2, 3, 4)
print aa
aa[:,:] = 1
print aa
print p2._getx(), p2.x
aa[0,0] = 5
print p1.x
p2.x = 10
print aa
print Particle.a
print vars(p2)