demofindpeaksliders.m

Basic function to locate and measure the positive peaks in a noisy data sets. Detects peaks by loo

% 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 ([e-mail]). Version 1.6 October 26, 2006
warning off MATLAB:polyfit:RepeatedPointsOrRescale
format compact
close
clear
global x
global y
global SlopeThreshold 
global AmpThreshold  
global SmoothWidth
global FitWidth
global PeakNumber 
global P
figure(1);clf

% Simulate data set
increment=5;
x=[1:increment:4000];
% 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
Noise=.01;
% A = matrix containing one of the unit-amplidude peak in each of its srow
A = zeros(length(pos),length(x));
for k=1:length(pos)
  if amp(k)>0, A(k,:)=gaussian(x,pos(k),wid(k)); end; % Or you can use any other peak function
end
z=amp*A;  % Multiplies each row by the corresponding amplitude and adds them up
y=z+Noise.*randn(size(z));
y=y+lorentzian(x,0,4000); % Adds background signal

% Call the interactive findpeaks script
FindPeakSliders;

%Print out peak table in Matlab Command window
P