--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/+utils/@math/cdfplot.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,161 @@
+% CDFPLOT makes cumulative distribution plot
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% 
+% h = cdfplot(y1,[],ops) Plot an empirical cumulative distribution function
+% against a theoretical cdf.
+% 
+% h = cdfplot(y1,y2,ops) Plot two empirical cumulative distribution
+% functions. Cdf for y1 is compared against cdf for y2 with confidence
+% bounds.
+% 
+% ops is a cell aray of options
+%   - 'ProbDist' -> theoretical distribution. Available distributions are:
+%     - 'Fdist' -> F cumulative distribution function. In this case the
+%     parameter 'params' should be a vector with distribution degrees of
+%     freedoms [dof1 dof2]
+%     - 'Normdist' -> Normal cumulative distribution function. In this case
+%     the parameter 'params' should be a vector with distribution mean and
+%     standard deviation [mu sigma]
+%     - 'Chi2dist' -> Chi square cumulative distribution function. In this
+%     case the parameter 'params' should be a number indicating
+%     distribution degrees of freedom
+%     - 'GammaDist' -> Gamma distribution. 'params' should contain the
+%     shape and scale parameters
+%   - 'ShapeParam' -> In the case of comparison of a data series with a
+%   theoretical distribution and the data series is composed of correlated
+%   elements. K can be adjusted with a shape parameter in order to recover
+%   test fairness. In such a case the test is performed for K* = Phi *K.
+%   Phi is the corresponding Shape parameter. The shape parameter depends
+%   on the correlations and on the significance value. It does not depend
+%   on data length. 
+%   - 'params' -> Probability distribution parameters
+%   - 'conflevel' -> requiered confidence for confidence bounds evaluation.
+%   Default 0.95 (95%)
+%   - 'FontSize' -> Font size for axis. Default 22
+%   - 'LineWidth' -> line width. Default 2
+%   - 'axis' -> set axis properties of the plot. refer to help axis for
+%   further details
+% 
+% Luigi Ferraioli 10-02-2011
+% 
+% % $Id: cdfplot.m,v 1.8 2011/07/08 09:45:48 luigi Exp $
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+function h = cdfplot(y1,y2,ops)
+  
+  %%% check and set imput options
+  % Default input struct
+  defaultparams = struct(...
+    'ProbDist','Fdist',...
+    'ShapeParam',1,...
+    'params',[1 1],...
+    'conflevel',0.95,...
+    'FontSize',22,...
+    'LineWidth',2,...
+    'axis',[]);
+  
+  names = {'ProbDist','ShapeParam','params','conflevel','FontSize','LineWidth','axis'};
+  
+  % collecting input and default params
+  if nargin == 3
+    if ~isempty(ops)
+      for jj=1:length(names)
+        if isfield(ops, names(jj))
+          defaultparams.(names{1,jj}) = ops.(names{1,jj});
+        end
+      end
+    end
+  end
+  
+  pdist = defaultparams.ProbDist; % check theoretical distribution
+  shp = defaultparams.ShapeParam;
+  dof = defaultparams.params; % distribution parameters
+  conf = defaultparams.conflevel; % confidence level for confidence bounds calculation
+  if conf>1
+    conf = conf/100;
+  end
+  fontsize = defaultparams.FontSize;
+  lwidth = defaultparams.LineWidth;
+  axvect = defaultparams.axis;
+
+  
+  %%% check data input
+  if isempty(y2) % do theoretical comparison
+    % get empirical distribution for input data
+    [eCD,ex]=utils.math.ecdf(y1);
+    % switch between input theoretical distributions
+    switch lower(pdist)
+      case 'fdist'
+        CD = utils.math.Fcdf(ex,dof(1),dof(2));
+      case 'normdist'
+        CD = utils.math.Normcdf(ex,dof(1),dof(2));
+      case 'chi2dist'
+        CD = utils.math.Chi2cdf(ex,dof(1));
+      case 'gammadist'
+        CD = gammainc(ex./dof(2),dof(1));
+    end
+    % get confidence levels with Kolmogorow - Smirnov test
+    alp = (1-conf)/2;
+    cVal = utils.math.SKcriticalvalues(numel(ex)*shp,[],alp);
+    % get confidence levels
+    CDu = CD+cVal;
+    CDl = CD-cVal;
+    
+    figure;
+    h = stairs(ex,[eCD CD CDu CDl]);
+    grid on
+    xlabel('x','FontSize',fontsize);
+    ylabel('F(x)','FontSize',fontsize);
+    set(h(3:4), 'Color','b', 'LineStyle',':','LineWidth',lwidth);
+    set(h(1), 'Color','r', 'LineStyle','-','LineWidth',lwidth);
+    set(h(2), 'Color','k', 'LineStyle','--','LineWidth',lwidth);
+    legend([h(1),h(2),h(3)],{'eCDF','CDF','Conf. Bounds'});
+    if ~isempty(axvect)
+      axis(axvect);
+    else
+      % get limit for quantiles corresponding to 0 and 0.99 prob
+      xlw = interp1(eCD,ex,0.001,'linear');
+      if isnan(xlw)
+        xlw = min(ex);
+      end
+      xup = interp1(eCD,ex,0.999,'linear');
+      axis([xlw xup 0 1]);
+    end
+    
+  else % do empirical comparison
+    % get empirical distribution for input data
+    [eCD1,ex1]=utils.math.ecdf(y1);
+    [eCD2,ex2]=utils.math.ecdf(y2);
+    
+    % get confidence levels with Kolmogorow - Smirnov test
+    alp = (1-conf)/2;
+    cVal = utils.math.SKcriticalvalues(numel(ex1),numel(ex2),alp);
+    % get confidence levels
+    CDu = eCD2+cVal;
+    CDl = eCD2-cVal;
+    
+    figure;
+    h1 = stairs(ex1,eCD1);
+    grid on
+    hold on
+    h2 = stairs(ex2,[eCD2 CDu CDl]);
+    xlabel('x','FontSize',fontsize);
+    ylabel('F(x)','FontSize',fontsize);
+    set(h2(2:3), 'Color','b', 'LineStyle',':','LineWidth',lwidth);
+    set(h1(1), 'Color','r', 'LineStyle','-','LineWidth',lwidth);
+    set(h2(1), 'Color','k', 'LineStyle','--','LineWidth',lwidth);
+    legend([h1(1),h2(1),h2(2)],{'eCDF1','eCDF2','Conf. Bounds'});
+    if ~isempty(axvect)
+      axis(axvect);
+    else
+      % get limit for quantiles corresponding to 0 and 0.99 prob
+      xlw = interp1(eCD2,ex2,0.001,'linear');
+      if isnan(xlw)
+        xlw = min(ex2);
+      end
+      xup = interp1(eCD2,ex2,0.999,'linear');
+      axis([xlw xup 0 1]);
+    end
+    h = [h1; h2];
+  end
+  
+end
\ No newline at end of file