|
From: | Oscar Bayona Candel |
Subject: | RE: Interpolation time response |
Date: | Mon, 13 Jul 2009 23:26:17 +0200 |
Thanks a lot for all. > Date: Mon, 13 Jul 2009 13:43:05 -0400 > From: address@hidden > To: address@hidden; address@hidden > Subject: Re: Interpolation time response > > > You are recalculating spline 10000+ times, getting the same result laboriously every time. > Use spline to calculate the individual datapoints, as explained in 'help spline' > > a =[ 1 1 > 30 2 > 60 8 > 90 10 > 7300 27 > 7665 30 > 8030 31 > 8395 32 > 8760 37 > 9125 38 > 9490 44 > 9855 46 > 10220 48 > 10585 50 > 10950 53 ]; > y=spline(a(:,1),a(:,2),1:10950); > plot(a(:,1),a(:,2),"+-",1:10950,y) > > As you can see, spline does some surprising things with sparse datasets; I would > recommend the interpolation routines (interp1 for instance): > > plot(a(:,1),a(:,2),"+-",1:10950,interp1(a(:,1),a(:,2),1:10950,"pchip")) > > Try different interpolation algorithms, 'nearest' 'linear' 'cubic' 'spline' Charlas más divertidas con el nuevo Windows Live Messenger |
[Prev in Thread] | Current Thread | [Next in Thread] |