/usr/share/freemat/toolbox/fitting/gausfit.m is in freemat-data 4.0-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | % GAUSFIT GAUSFIT Gaussian Curve Fit
%
% Usage
%
% The gausfit routine has the following syntax
%
% [mu,sigma,dc,gain,yhat] = gausfit(t,y,w,mug,sigmag,dcg,gaing).
%
% where the required inputs are
% - t - the values of the independant variable (e.g., time samples)
%
% - y - the values of the dependant variable (e.g., f(t))
%
% The following inputs are all optional, and default values are
% available for each of them.
% - w - the weights to use in the fitting (set to ones if omitted)
%
% - mug - initial estimate of the mean
%
% - sigmag - initial estimate of the sigma (standard deviation)
%
% - dcg - initial estimate of the DC value
%
% - gaing - initial estimate of the gain
%
% The fit is of the form yhat=gain*exp((t-mu).^2/(2*sigma^2))+dc.
% The outputs are
% - mu - the mean of the fit
%
% - sigma - the sigma of the fit
%
% - dc - the dc term of the fit
%
% - gain - the gain of the gaussian fit
%
% - yhat - the output samples (the Gaussian fits)
%
% Because the fit is nonlinear, a good initial guess is critical to
% convergence of the solution. Thus, you can supply initial guesses
% for each of the parameters using the mug, sigmag, dcg,
% gaing arguments. Any arguments not supplied are estimated using
% a simple algorithm. In particular, the DC value is estimated by
% taking the minimum value from the vector y. The gain is
% estimated from the range of y. The mean and standard deviation
% are estimated using the first and second order moments of y.
% This function uses fitfun.
% Copyright (c) 2002-2006 Samit Basu
% Licensed under the GPL
function [mu,sigma,dc,gain,yhat] = gausfit(t,y,w,mug,sigmag,dcg,gaing)
if (~isset('w'))
w = y*0+1;
end
if (~isset('dcg'))
dcg = min(y(:));
end
ycor = y - dcg;
if (~isset('gaing'))
gaing = max(ycor);
end
ycor = ycor/gaing;
if (~isset('mug'))
mug = sum(ycor.*t)/sum(ycor);
end
if (~isset('sigmag'))
sigmag = sqrt(abs(sum((ycor).*(t-mug).^2)/sum(ycor)));
end
[xopt,err] = fitfun('gfitfun',[mug,sigmag,dcg,gaing],y,w,eps,t);
mu = xopt(1);
sigma = xopt(2);
dc = xopt(3);
gain = xopt(4);
yhat = gfitfun(xopt,t);
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