[Numpy-discussion] bug triggered by array.astype()

[Travis Oliphant]

Gerard Vermeulen wrote:

>On Sun, 29 Jan 2006 01:50:57 -0700
>Travis Oliphant <oliphant.travis at ieee.org> wrote:
>
>[ .. ]
>
>  
>
>>In SVN, now a Overflow error is raised instead in this example because 
>>negative long integer objects are trying to be converted to unsigned 
>>integers (this is a Python error being raised).  We could check for this 
>>and instead do what the c-compiler would do in converting from signed to 
>>unsigned objects. 
>>
>>Is that preferrable?
>>
>>    
>>
>
>Well, the current SVN does now almost what Numeric does:
>
>  
>
>>>>from Numeric import *
>>>>v = arange(0, 10, 1, Float32)
>>>>c = (255<<24)*cos(v)+ (255<<16)*cos(v+2*pi/3) + (255<<8)*cos(v+4*pi/3) + 255
>>>>c.astype(UInt32)
>>>>        
>>>>
>Traceback (most recent call last):
>  File "<stdin>", line 1, in ?
>OverflowError: long int too large to convert to int
>  
>
>
>However, numarray does:
>
>  
>
>>>>from numarray import *
>>>>v = arange(0, 10, 1, Float32)
>>>>c = (255<<24)*cos(v)+ (255<<16)*cos(v+2*pi/3) + (255<<8)*cos(v+4*pi/3) + 255
>>>>c.astype(UInt32)
>>>>        
>>>>
>array([4269801984, 2294853120, 2504994432,   65861376, 1514949120,
>       1225005568, 4103764992, 3209541888, 3659448448,  398681088], type=UInt32)
>  
>
>
>This is more user friendly, but may cost more CPU cycles.
>  
>

The issue here is really that in Numeric (and numpy)  c is an object 
array while in numarray c is a float array.  Because Numeric and numpy 
support object arrays, long integers have been converted to objects. 

I think what should be changed is that long integers should only be 
converted to objects if they are bigger than the maximum integer-type on 
the platform.   That is what numarray allows and makes sense. 

In other words, the root of this difference is what array(255<<24) 
returns.  In Numeric and numpy it returns an object array.  In numarray 
it returns a UInt64 array.

-Travis