[Numpy-discussion] Proposal for new ufunc functionality

Travis Oliphant oliphant@enthought....
Sat Apr 10 12:23:03 CDT 2010


I've been mulling over a couple of ideas for new ufunc methods plus a  
couple of numpy functions that I think will help implement group-by  
operations with NumPy arrays.

I wanted to discuss them on this list before putting forward an actual  
proposal or patch to get input from others.

The group-by operation is very common in relational algebra and NumPy  
arrays (especially structured arrays) can often be seen as a database  
table.    There are common and easy-to implement approaches for select  
and other relational algebra concepts, but group-by basically has to  
be implemented yourself.

Here are my suggested additions to NumPy:

ufunc methods:
	* reduceby (array, by, sorted=1, axis=0)

              array is the array to reduce
	     by is the array to provide the grouping (can be a structured  
array or a list of arrays)

              if sorted is 1, then possibly a faster algorithm can be  
	* reducein (array, indices, axis=0)

               similar to reduce-at, but the indices provide both the  
start and end points (rather than being fence-posts like reduceat).

numpy functions (or methods):

	 * segment(array)

	   (produce an array of integers from an array producing the  
different "regions" of an array:

	    segment([10,20,10,20,30,30,10])  would produce ([0,1,0,1,2,2,0])

	 * edges(array, at=True)
	   produce an index array providing the edges (with either fence-post  
like syntax for reduce-at or both boundaries like reducein.



Thoughts on the general idea?

Travis Oliphant
Enthought Inc.

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