On Tuesday 04 April 2006 08:09, Charles R Harris wrote:
I can't get worked up over this one way or the other: complex128 make sense if I count bits, complex64 makes sense if I note precision; I just have to remember the numpy convention. One could argue that complex64 is the more conventional choice and so has the virtue of least surprise, but I don't think it is terribly difficult to become accustomed to using complex128 in its place. I suppose this is one of those programmer's vs user's point of view thingees. For the guy writing general low level numpy code what matters is the length of the type, how many bytes have to be moved and so on, and from the other point of view what counts is the precision of the arithmetic.
I kind of like your comparison of programmer vs user ;-) And so I was "hoping" that numpy (and scipy !!) is intended for the users - like supposedly IDL and Matlab are... No one likes my "backwards compatibility" argument !? Thanks - Sebastian Haase PS: I understand that voting is only for a last resort - some people, always use na.Complex and na.Float and don't care - BUT I use single precision all the time because my image data is already getting to large. So I have to look at this every day, and as Travis pointed out, now is about the last chance to possibly change complex128 to complex64 ...
Chuck
On 4/4/06, Colin J. Williams
wrote: Sebastian Haase wrote:
Hi, Could we start another poll on this !?
I think I would vote +1 for complex32 & complex64 mostly just because of "that's what I'm used to"
+1 Most people look to the number to give a clue as to the precision of the value.
Colin W.
But I'm curious to hear what others "know to be in use" - e.g. Matlab or IDL !
- Thanks Sebastian Haase
Travis Oliphant wrote:
Sebastian Haase wrote:
Tim Hochberg wrote: <snip>
This would work fine if repr were instead:
dtype([('x', float64), ('z', complex128)])
Anyway, this all seems reasonable to me at first glance. That said, I don't plan to work on this, I've got other fish to fry at the moment.
A new point: Please remind me (and probably others): when did it get decided to introduce 'complex128' to mean numarray's complex64 and the 'complex64' to mean numarray's complex32 ?
It was last February (i.e. 2005) when I first started posting regarding the new NumPy. I claimed it was more consistent to use actual bit-widths. A few people, including Perry, indicated they weren't opposed to the change and so I went ahead with it.
You can read relevant posts by searching on numpy-discussion@lists.sourceforge.net
Discussions are always welcome. I suppose it's not too late to change something like this --- but it's getting there...
-Travis