[SciPy-User] Projecting volumes down to 2D

Chris Weisiger cweisiger@msg.ucsf....
Fri Sep 2 10:15:01 CDT 2011

On Thu, Sep 1, 2011 at 2:37 PM, Christoph Gohlke <cgohlke@uci.edu> wrote:
> On 9/1/2011 2:24 PM, Chris Weisiger wrote:
>> Just to followup, the maximum size of a 3D texture on this laptop is
>> only 128 pixels in any direction, so I'd have to do some nasty
>> stitching together of texture blocks to use OpenGL to solve this
>> problem. Nice idea, though. Of course, practically every computer here
>> is more powerful than my laptop, but they don't always have unusually
>> strong graphics cards, and I'd rather not restrict what computers my
>> code can run on.
> Fair enough. Just wondering how your underpowered laptop can run well
> processing multiple gigabyte volumes with ndimage.map_coordinates :)

Video memory is separate from RAM, and RAM can page out to disk if it
has to. So the heavy lifting may be slower on this laptop than it is
on the heavier machines, but it does work. But the original point of
the thread was that I wasn't processing multiple-gigabyte volumes on
this laptop, for the most part -- once the original volume was loaded
into memory, every other process was working only with 2D slices,
which are much faster.

A related question: is there some function in Scipy that will, given
an arbitrary ray, return either the values in a data volume that the
ray passes through, or get the largest volume, etc.? Turns out I now
have two projects that could use that ability.


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