[Numpy-discussion] Optimize speed of for loop using numpy

Trond Kristiansen trond@unc....
Mon Feb 25 20:32:54 CST 2008

Hi again. 

I have attached the function that the FOR loop is part of as a python file.
What I am trying to do is to create a set of functions that will read the
output files (NetCDF) from running the ROMS model (ocean model). The output
file is organized in xi (x-direction), eta (y-direction), and s
(z-direction) where the s-values are vertical layers and not depth. This
particular function (z_slice) will find the closest upper and lower s-layer
for a given depth in meters (e.g. -100). Then values from the two selcted
layers will be interpolated to create a new layer at the selected depth
(-100). The problem is that the s-layers follow the bathymetry and a
particular s-layer will therefore sometimes be above and sometimes below the
selected depth that we want to interpolate to. That's why I need a quick
script that searches all of the layers and find the upper and lower layers
for a given depth value (which is negative). The z_r is a 3D array
(s,eta,xi) that is created using the netcdf module.

The main goal of these set of functions is to move away from using matlab,
but also to speed things up. The sliced data array will be plotted using GMT
or pyNGL.

Thanks for helping me. Cheers, Trond

On 2/25/08 9:15 PM, "Robert Kern" <robert.kern@gmail.com> wrote:

> On Mon, Feb 25, 2008 at 8:08 PM, Trond Kristiansen <trond@unc.edu> wrote:
>>  Hi all.
>>  This is my first email to the discussion group. I have spent two days trying
>>  to get a particular loop to speed up, and the best result I got was this:
> Can you try to repost this in such a way that the indentation is
> preserved? Feel free to attach it as a text file. Also, can you
> describe at a higher level what it is you are trying to accomplish and
> what the arrays mean?

-------------- next part --------------
A non-text attachment was scrubbed...
Name: z_slice.py
Type: application/octet-stream
Size: 1708 bytes
Desc: not available
Url : http://projects.scipy.org/pipermail/numpy-discussion/attachments/20080225/1db44f6b/attachment.obj 

More information about the Numpy-discussion mailing list