Model and experiment fitting.

Sebastian Żurek sebzur at pin.if.uz.zgora.pl
Sun Oct 22 05:39:24 CDT 2006


Nadav Horesh napisał(a):
> 1. If at least one of your data sets to be interpulated is on a grid, 
> you can use numpy.ndimage.map function for fast interpolation for 2d (in fact for any dimensional) dataset.

I've already used a splines to interpolate a missing simulated points. 
That procedure works  great and is very fast. But I'll check the 
numpy.ndimage - I haven't used it, yet.


> 2. Isn't there an analytic expression to average the expectration values of SH over all possible orientations 
>  between B and the crystal axis? My experience shows that some analytic work can save 99% of simulation time.

Well, the simulations are already very fast. The time consumption is 
approximately ~0.3s for a single powder spectrum (2.8GHz Pentium D). The 
calculations are held by an external, very fine EPR spectra simulation 
tool. The author must have incorporated into it a lot of 
rationalizations, but this is a binary tool (unfortunately) and I do not 
know, what exactly sits inside of it... All I know, is that the 
orientations are represented by a grid (with an increment step tunable 
by a user). From library documentation: "After having computed the 
spectrum for a number of orientations specified, the simulation function 
interpolates these spectra for additional orientations before summing up 
all spectra." The interpolation is accomplish with a splines.




Thank you for your comment,

best regards

Sebastian


-------------------------------------------------------------------------
Using Tomcat but need to do more? Need to support web services, security?
Get stuff done quickly with pre-integrated technology to make your job easier
Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo
http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642
_______________________________________________
Numpy-discussion mailing list
Numpy-discussion at lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/numpy-discussion


More information about the Numpy-discussion mailing list