% A self-contained interactive demonstration of FindPeakSliders
% applied to noisy synthetic data set consisting of a random number
% of narrow peaks. Use the sliders to explore the effect of the
% variables SlopeThreshold (SlopeT), AmplitudeThreshold (AmpT),
% SmoothWidth (Smooth), and FitWidth (Fit). Peak number and the
% estimated position, height, and width of each peak is returned in
% the matrix P. The 4 parameters are:
% SlopeThreshold - Slope of the smoothed third-derivative that is taken
% to indicate a peak. Larger values will neglect small features.
% AmpThreshold - Any peaks with height less than AmpThreshold are ignored.
% SmoothWidth - Width of smooth functions applied to data before slope is
% measured. Larger values will neglect small features. A reasonable value is
% about equal to 1/2 the width of the peaks.
% FitWidth - The number of points around the "top part" of the (unsmoothed)
% peak that are taken to determine the peak height, positions, and width.
% A reasonable value is about equal to 1/2 the width of the peaks.
% Tom O'Haver (email@example.com). Version 1.6 October 26, 2006
warning off MATLAB:polyfit:RepeatedPointsOrRescale
% Simulate data set
% For each simulated peak, enter the amplitude, position, and width below
amp=randn(1,39); % Amplitudes of the peaks
pos=[200:100:4000]; % Positions of the peaks
wid=60.*ones(size(pos)); % Widths of the peaks
% A = matrix containing one of the unit-amplidude peak in each of its srow
A = zeros(length(pos),length(x));
if amp(k)>0, A(k,:)=gaussian(x,pos(k),wid(k)); end; % Or you can use any other peak function
z=amp*A; % Multiplies each row by the corresponding amplitude and adds them up
y=y+lorentzian(x,0,4000); % Adds background signal
% Call the interactive findpeaks script
%Print out peak table in Matlab Command window