Thank you Cristophe for your comments and your link for the
Savitzky-Golay smoothing ,
Here is a simple code using lsq-splin() on your example data I played
with. Nothing spectacular - just followed the Scilab Help, but I hope
someone will find it useful.
Regards,
Radovan
//
Hello,
> De la part de Samuel Enibe
> Envoyé : samedi 22 mars 2014 19:01
>
> May I know the best way to determine dy/dx for the data set.
The best way is the way that gives you accurate results in the minimal time.
If you have an analytical model, the best is to fit it and then derive the
funct
Thank you very much, Omorjan.
It worked very well.
God bless you.
Enibe
-Original Message-
From: Radovan Omorjan
Sent: 2014/03/22, 20:46
To: "International users mailing list for Scilab."
Subject: Re: [Scilab-users] Numerical Diffe
Hello,
You can try spline interpolation and numerical derivatives on that spline
//function for spline interpolation of x-y data
deff ('[yk] = fspline(xx,x,y)', ...
'yk=interp(xx, x, y, splin(x,y))');
//
//Use the spline for finding derivatives
//
a=10 //give the point
numdiff(fspline,a
I would like to use the functions *derivative* or *numdiff* to numerically
differentiate a tabulated data such as
x = [0 2 5 20 40 60 80]';//time in minutes
y = [0.0956820 0.0480457 0.0277857 0.0036214 0.0002543 0.0002543
0.0001265]';//values of y
May I know the best way to determine dy/dx for th
