Organize old files

workflow/.old/apps/matlab/ezview/TempBU/histfitJR.m

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+function h = histfitJR(data,nbins,dist)
+%HISTFIT Histogram with superimposed fitted normal density.
+%   HISTFIT(DATA,NBINS) plots a histogram of the values in the vector DATA,
+%   along with a normal density function with parameters estimated from the
+%   data.  NBINS is the number of bars in the histogram. With one input
+%   argument, NBINS is set to the square root of the number of elements in
+%   DATA. 
+%
+%   HISTFIT(DATA,NBINS,DIST) plots a histogram with a density from the DIST
+%   distribution.  DIST can take the following values:
+%
+%         'beta'                             Beta
+%         'birnbaumsaunders'                 Birnbaum-Saunders
+%         'exponential'                      Exponential
+%         'extreme value' or 'ev'            Extreme value
+%         'gamma'                            Gamma
+%         'generalized extreme value' 'gev'  Generalized extreme value
+%         'generalized pareto' or 'gp'       Generalized Pareto (threshold 0)
+%         'inverse gaussian'                 Inverse Gaussian
+%         'logistic'                         Logistic
+%         'loglogistic'                      Log logistic
+%         'lognormal'                        Lognormal
+%         'negative binomial' or 'nbin'      Negative binomial
+%         'nakagami'                         Nakagami
+%         'normal'                           Normal
+%         'poisson'                          Poisson
+%         'rayleigh'                         Rayleigh
+%         'rician'                           Rician
+%         'tlocationscale'                   t location-scale
+%         'weibull' or 'wbl'                 Weibull
+%
+%   H = HISTFIT(...) returns a vector of handles to the plotted lines.
+%   H(1) is a handle to the histogram, H(2) is a handle to the density curve.
+
+%   Copyright 1993-2008 The MathWorks, Inc. 
+%   $Revision: 1.1.8.2.2.1 $  $Date: 2010/12/13 15:00:40 $
+
+if ~isvector(data)
+   error(message('stats:histfit:VectorRequired'));
+end
+
+data = data(:);
+data(isnan(data)) = [];
+n = numel(data);
+
+if nargin<2 || isempty(nbins)
+    nbins = ceil(sqrt(n));
+elseif ~isscalar(nbins) || ~isnumeric(nbins) || ~isfinite(nbins) ...
+                        || nbins~=round(nbins)
+    error(message('stats:histfit:BadNumBins'))
+end
+
+% Do histogram calculations
+[bincounts,bincenters]=hist(data,nbins);
+
+% Fit distribution to data
+if nargin<3 || isempty(dist)
+    dist = 'normal';
+end
+try
+    pd = fitdist(data,dist);
+catch myException
+    if isequal(myException.identifier,'stats:ProbDistUnivParam:fit:NRequired')
+        % Binomial is not allowed because we have no N parameter
+        error(message('stats:histfit:BadDistribution'))
+    else
+        % Pass along another other errors
+        throw(myException)
+    end
+end
+
+% Find range for plotting
+q = icdf(pd,[0.0013499 0.99865]); % three-sigma range for normal distribution
+x = linspace(q(1),q(2));
+if ~pd.Support.iscontinuous
+    % For discrete distribution use only integers
+    x = round(x);
+    x(diff(x)==0) = [];
+end
+% Plot the histogram with no gap between bars.
+%if min(data)==0, neglim=-50; else neglim= min(data); end
+%hh = bar(bincenters,bincounts,[neglim,max(data)],'hist');
+hh = bar(bincenters,bincounts,[min(data),max(data)],'hist');
+
+% Normalize the density to match the total area of the histogram
+xd = get(hh,'Xdata');             % Gets the x-data of the bins.
+if min(xd(:))==0, neglim = -50; else neglim= min(xd(:)); end
+%rangex = max(xd(:)) - min(xd(:)); % Finds the range of this data.
+rangex = max(xd(:)) - (neglim); % Finds the range of this data.
+
+binwidth = rangex/nbins;          % Finds the width of each bin.
+area = n * binwidth;
+y = area * pdf(pd,x);
+
+% Overlay the density
+np = get(gca,'NextPlot');    
+set(gca,'NextPlot','add')    
+hh1 = plot(x,y,'r-','LineWidth',2);
+set(hh1,'visible','off')
+
+if nargout == 1
+  h = [hh; hh1];
+end
+
+set(gca,'NextPlot',np)