Re: [Numpy-discussion] Attempting to sub-class NumArray

[Colin J. W. <cj...@sy...>]

Todd Miller wrote:

>On Sat, 2003-09-06 at 11:25, Colin J. Williams wrote:
>  
>
>>Todd Miller wrote:
>>
>>    
>>
>>>I think the problem you are having is caused by the assumption that
>>>instance initialization is equivalent to an unordered assignment of all
>>>instance attributes.  That's not true because the private attributes are
>>>interrelated;  assigning "shape" affects "_shape" and "_strides",
>>>_itemsize must be known before _strides can be computed from shape, and
>>>so on. 
>>>
>>>      
>>>
>>It would be helpful if you could let us know what assignment ordering 
>>would be appropriate, or, if there were information about the 
>>interactions, perhaps we could work these things out for ourselves.
>>    
>>
>
>In truth,  I don't think the order is the issue, so let's drop that. 
>All I can say is that somehow special.__init__() is creating
>inconsistent _shape and _strides.  I also noticed it creating and
>assigning bound methods, which you probably don't want to do.
>
Yes, I had spotted that and limited the updating to the variables.  This 
seemed to work, but your suggestion below is the neater way to go.

>>As we've discussed before, there is little information available on 
>>private objects and their roles.  Even to have the source code of some 
>>of the C code might be useful.  I wasn't able to spot the relevant C 
>>code among the CVS directories.
>>    
>>
>
>The source code is all there.
>
>Look in Include/numarray/numarray.h, Src/_ndarraymodule.c, and
>Src/_numarraymodule.c, and maybe Src/libnumarraymodule.c.
>
Thanks, I'll poke around there.

>
>  
>
>>However, the assumption would appear to apply to the crude 
>>initialization of 'special'.  The problem which is being reported seems 
>>to be connected with the function setshape in generic.py.  This is far 
>>from the unordered assignment, although I recognize that ther might be 
>>some connection.
>>    
>>
>
>I'm not sure where and how, but I think the problem is in your dir()
>loop.   So, instead, try this:
>
>self.__setstate__(arr.__getstate__())
>
This seems to be a better approach than mine.

>
>That ensures that you're only copying the data attributes and appears to
>work.
>
Thanks, over that hurdle and on to the next

Colin W.

>
>Todd
>
>  
>
>>Colin W.
>>
>>    
>>
>>>On Fri, 2003-09-05 at 20:32, Colin J. Williams wrote:
>>> 
>>>
>>>      
>>>
>>>>Todd,
>>>>
>>>>Thanks again for your prompt response.
>>>>Todd Miller wrote:
>>>>   
>>>>
>>>>        
>>>>
>>>>>Hi Colin,
>>>>>
>>>>>I haven't looked at this in detail,  but special.__init__() is making me
>>>>>queasy.  
>>>>>     
>>>>>
>>>>>          
>>>>>
>>>>We don't call __init__ directly, but only when we construct the
>>>>instance, a,  of the class special.
>>>>   
>>>>
>>>>        
>>>>
>>>>>Why doesn't it call NumArray.__init__()?
>>>>>     
>>>>>
>>>>>          
>>>>>
>>>>Because we have data to install in the newly created a.  We go off to
>>>>the factory function, numarray.array, to create the array, which we
>>>>then specialize.
>>>>
>>>>I don't see how NumArray.__init__ would help.  This cumbersome
>>>>procedure seems to work OK in most respects, but fails to display
>>>>properly.
>>>>
>>>>I don't follow the code sufficiently well to be sure, but my hunch is
>>>>that the problem lies with setShape.  It fails to update _strides.
>>>>
>>>>Colin W.
>>>>   
>>>>
>>>>        
>>>>
>>>>>Todd
>>>>>
>>>>>On Fri, 2003-09-05 at 15:03, Colin J. Williams wrote:
>>>>> 
>>>>>     
>>>>>
>>>>>          
>>>>>
>>>>>>When ravel() is used on an instance of NumArray, the _strides attribute 
>>>>>>is recalculated correctly.
>>>>>>When ravel() is used on an instance of special, a sub-class of NumArray, 
>>>>>>the _strides attribute keeps its old value.  This appears to cause the 
>>>>>>display problem which is reported.
>>>>>>
>>>>>>The essentials of the code used are below.
>>>>>>
>>>>>>To investigate this problem, two print statements were added to the 
>>>>>>method setshape in generic.py:
>>>>>>
>>>>>>           if newnelements == nelements:
>>>>>>               self._shape = tuple(shape)
>>>>>>               print 'In setShape self._shape:', self._shape
>>>>>>               self._strides = self._stridesFromShape()
>>>>>>               print 'In setShape self._strides:', self._strides
>>>>>>           else:
>>>>>>               raise ValueError("New shape is not consistent with the
>>>>>>   old shape")
>>>>>>
>>>>>>It seems that only the first of these print statements is executed with 
>>>>>>special, but both are executed with NumArray.  In the second case, the 
>>>>>>output is not in the expected sequence.
>>>>>>
>>>>>>I would appreciate any suggestion as to a workaround.
>>>>>>
>>>>>>Colin W,
>>>>>>
>>>>>>Grief when attempting to sub-class NumArray
>>>>>>
>>>>>>Code used:
>>>>>>
>>>>>># Try to sub-class
>>>>>>class special(N.NumArray):
>>>>>> def __init__(self, data= None, shape= None, eType= None):
>>>>>>##                         eType= _nt.Any or AnyType not acceptable %%
>>>>>>   arr= N.array(sequence= data, shape= shape, type= eType)
>>>>>>   for attr in dir(arr):
>>>>>>##      This is a longwinded way of setting up special
>>>>>>##      There must be a better way                     %%
>>>>>>##      Perhaps we should use generic._view
>>>>>>##      It's not documented                 TRY IT LATER
>>>>>>##      There is no need to transfer methods!
>>>>>>     if attr[0] == '_' and attr[1] != '_':
>>>>>>       print attr
>>>>>>       exec 'self.' + attr + '= ' 'arr.' + attr
>>>>>>       exec 'print self.' + attr
>>>>>>   pass
>>>>>>
>>>>>>a= special(data= [1, 2, 3, 4], shape= (2, 2))
>>>>>>a= N.array([1, 2, 3, 4], shape= (2, 2))
>>>>>>print 'In ts a._strides:', a._strides
>>>>>>b= _gen.ravel(a)
>>>>>>print 'In ts b._strides:', b._strides       #  <<< Unchanged with 
>>>>>>special, OK with NumArray
>>>>>>print 'b:', b
>>>>>>
>>>>>>
>>>>>>
>>>>>>USING THE SUBCLASS special
>>>>>>            
>>>>>>
>>>>>>>C:\Progra~1\Python23\pythonw -u ts.py
>>>>>>>              
>>>>>>>
>>>>>>In ts a._strides: (8, 4)
>>>>>>In setShape self._shape: (4,)
>>>>>>In ts b._strides: (8, 4)
>>>>>>b: In setShape self._shape: (4,)
>>>>>>Traceback (most recent call last):
>>>>>> File "ts.py", line 37, in ?
>>>>>>   print 'b:', b
>>>>>> File 
>>>>>>"C:\PROGRA~1\Python23\lib\site-packages\numarray\numarraycore.py", line 
>>>>>>618, in __str__
>>>>>>   MAX_LINE_WIDTH, PRECISION, SUPPRESS_SMALL, ' ', "")
>>>>>> File "C:\PROGRA~1\Python23\lib\site-packages\numarray\arrayprint.py", 
>>>>>>line 176, in array2string
>>>>>>   separator, prefix)
>>>>>> File "C:\PROGRA~1\Python23\lib\site-packages\numarray\arrayprint.py", 
>>>>>>line 138, in _array2string
>>>>>>   max_str_len = max(len(str(max_reduce(data))),
>>>>>>libnumarray.error: maximum_Int32_reduce: access beyond buffer. offset=27 
>>>>>>buffersize=16
>>>>>>            
>>>>>>
>>>>>>>Exit code: 1
>>>>>>>              
>>>>>>>
>>>>>>__________________________________________________________
>>>>>>
>>>>>># USING NumArray
>>>>>>
>>>>>>In setShape self._shape: (2, 2)
>>>>>>In ts a._strides: (8, 4)
>>>>>>In setShape self._shape: (4,)
>>>>>>In ts b._strides: (4,)
>>>>>>b: In setShape self._shape: (4,)
>>>>>>[1 2 3 4]
>>>>>>            
>>>>>>
>>>>>>>Exit code: 0
>>>>>>>              
>>>>>>>
>>>>>>
>>>>>>
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>>>>>>   
>>>>>>       
>>>>>>
>>>>>>            
>>>>>>