Hi, I want to fit my data with an exponential curve. I use fit and fittype=exp. So far no problem. But now I only want to use the first 600 data points and the last 200 datapoints (every trace has 15000 datapoints) and make an exponential fit over the whole trace only using this datapoints.
Can anybody help me which methods to use?
Thanks for your efforts!
I will assume that you have the 15,000 data samples stored in the MATLAB Workspace as a 15,000 x 1 column vector called dataset.x.
%% Create time domain:
N = size(dataset.x,1); Fs = 125; dt = 1/Fs;
dataset.t = dt*(0:N-1)';
%% Create subset:
p = 600; q = 200; subset.x = [ dataset.x(1:p) ; dataset.x(end-q+1:end) ]; subset.t = [ dataset.t(1:p) ; dataset.t(end-q+1:end) ];
%% Exponential fit:
fitType = 'exp1'; myFit = fit(subset.t,subset.x,fitType);
If "x" is your explanatory variable, then it should be as simple as using x([1:600,end-199:end]), do similar for your response variable,and run fit() just as you did with "no problem" before. Or is it more complicated than that?
But I also want the "timepoints" between this two "epochs" to be fitted. So that an exponential function goes from timepoint 0 to timepoint 15000 only using the first values and the last values.
Thanks for your answer!
I want to give another explanation because I think it is a bit confusing: I have a data trace containing of 15.000 timepoints (every 0.008 s one frame -->125 Hz). At the beginning and the end of the trace there are no "events" so only baseline with noise. I want to fit the whole trace with an exponential function only using the first n data points and the last m datapoints. So that the points between do not play any role but the exponential function should consider the gap between because there I also need the baseline!