[Numpy-discussion] It's so *quiet* I'm testing numpy-discussion

Sebastian Haase haase at msg.ucsf.edu
Wed Feb 16 13:45:15 CST 2005


On Wednesday 16 February 2005 12:42 pm, Travis Oliphant wrote:
> I'm busy finishing Numeric3.  It has made quite a bit of progress.  It
> can be checked out of CVS and played with.   Implementing the
> multidimensional indexing magic of numarray is taking a bit of time,
> though.  I'd like to support mixed integer indexing, boolean indexing,
> and slicing too.    Any help on this would be greatly appreciated.
>
> I'm very confident that record arrays are going to work.   The new
> numeric object has a getfield method that lets you interpret subitem
> slices as a new type of array.  The new void * type arrays let the array
> be a collection of anything.  Constructing the fanciness of numarray
> record arrays will just be a matter of an appropriate Python container
> class or subclass.  I think all the requirements to do this are already
> done in Numeric3.
>
Hi Travis,
I'm a committed numarray user since numarray 0.3.6 (I was told not to look 
into Numeric, because it did not have UInt16 which I needed)
Now, What you say about record arrays makes it sound like you are trying to 
"catch up" on numarray by providing these same features in Numeric.
Will you also look into memmap ?  For us this turned into one of the most 
amazing features of numarray: that we can access 500MB files instantaneously.
How about the speed advantage that numarray was having over Numeric for large 
arrays ?

I just wanted to show my interest in this discussion and thank everbody 
(numarray, scipy, Numeric, ...) for the great tools !

Sebastian Haase





> I've added a possible UPDATEIFCOPY flag to the requirements argument in
> PyArray_FromAny that will tell an array to copy back to the original
> upon deletion if this flag is set.
>
> Typecodes are handled by a TypecodeConverter function that takes quite a
> few different types of arguments including an arbitrary Python object
> with a type_num and itemsize attribute.  This allows a lot of
> flexibility in how types are specified.
>
> Multi-byte character and unicode arrays already seem to work reasonably
> well.  There is a lot more testing that needs to be done, of course.
>
> I would also love feedback and/or help on the PEP that I've started.  It
> is online at numeric.scipy.org but that copy may be a few days behind
> the CVS version at sourceforge.
>
> -Travis




More information about the Numpy-discussion mailing list