[Numpy-discussion] Problems with Numexpr and discontiguous arrays

Tim Hochberg tim.hochberg at ieee.org
Thu Oct 5 15:13:53 CDT 2006


Travis Oliphant wrote:
> Tim Hochberg wrote:
>
>   
>>>>  
>>>>      
>>>>
>>>>         
>>> That would be easy to do. Right now the opcodes should work correctly 
>>> on data that is spaced in multiples of the itemsize on the last axis. 
>>> Other arrays are copied (no opcode required, it's embedded at the top 
>>> of interp_body lines 64-80). The record array case apparently slips 
>>> through the cracks when we're checking whether an array is suitable to 
>>> be used correctly (interpreter.c 1086-1103). It would certainly not be 
>>> any harder to only allow contiguous arrays than to correctly deal with 
>>> record arrays. Only question I have is whether the extra copy will 
>>> overwhelm the savings of that operating on contiguous data gives.  The 
>>> thing to do is probably try it and see what happens.
>>>    
>>>
>>>       
>> OK, I've checked in a fix for this that makes a copy when the array is 
>> not strided in an even multiple of the itemsize. I first tried copying 
>> for all discontiguous array, but this resulted in a large speed hit for 
>> vanilla strided arrays (a=arange(10)[::2], etc.), so I was more frugal 
>> with my copying. I'm not entirely certain that I caught all of the 
>> problematic cases, so let me know if you run into any more issues like this.
>>
>>  
>>
>>     
> There is an ElementStrides check and similar requirement flag you can 
> use to make sure that you have an array whose strides are multiples of 
> it's itemsize.
>
>   
Thanks Travis, I'll make a note; next time I look at this code I'll see 
if that can be used to simplify the code in question.


-tim





More information about the Numpy-discussion mailing list