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@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion