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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% QQFPLOT makes quantile-quantile plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: Make quantile-quantile plot and calculate confidence % intervals on the basis of the Kolmogorov-Smirnov test. % % CALL: qqplot(a, pl) % % INPUT: a: are real valued AO % % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'kstest')">Parameters Description</a> % % VERSION: $Id: qqplot.m,v 1.1 2011/07/08 10:28:02 luigi Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = qqplot(varargin) % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end import utils.const.* utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename); % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin,in_names{ii} = inputname(ii);end % Collect all AOs and plists [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names); pl = utils.helper.collect_objects(varargin(:), 'plist', in_names); % combine plists if isempty(pl) model = 'empirical'; else model = lower(find(pl, 'TESTDISTRIBUTION')); if isempty(model) model = 'empirical'; pl.pset('TESTDISTRIBUTION', model); end end pl = parse(pl, getDefaultPlist(model)); % get parameters conf = find(pl, 'CONFLEVEL'); if isa(conf, 'ao') conf = conf.y; end shapeparam = find(pl, 'SHAPEPARAM'); if isa(shapeparam, 'ao') shapeparam = shapeparam.y; end ftsize = find(pl, 'FONTSIZE'); if isa(ftsize, 'ao') ftsize = ftsize.y; end lwidth = find(pl, 'LINEWIDTH'); if isa(lwidth, 'ao') lwidth = lwidth.y; end % switch among test type switch lower(model) case 'normal' mmean = find(pl, 'MEAN'); if isa(mmean, 'ao') mmean = mmean.y; end sstd = find(pl, 'STD'); if isa(sstd, 'ao') sstd = sstd.y; end distparams = [mmean, sstd]; dist = 'normdist'; case 'chi2' ddof = find(pl, 'DOF'); if isa(ddof, 'ao') ddof = ddof.y; end distparams = [ddof]; dist = 'chi2dist'; case 'f' dof1 = find(pl, 'DOF1'); if isa(dof1, 'ao') dof1 = dof1.y; end dof2 = find(pl, 'DOF2'); if isa(dof2, 'ao') dof2 = dof2.y; end distparams = [dof1, dof2]; dist = 'fdist'; case 'gamma' shp = find(pl, 'SHAPE'); if isa(shp, 'ao') shp = shp.y; end scl = find(pl, 'SCALE'); if isa(scl, 'ao') scl = scl.y; end distparams = [shp, scl]; dist = 'gammadist'; otherwise distparams = []; end % run test switch lower(model) case 'empirical' % build parameters struct params = struct(... 'conflevel',conf,... 'FontSize',ftsize,... 'LineWidth',lwidth); y1 = as(1).y; % run over input aos for ii=1:numel(as)-1 y2 = as(ii+1).y; if size(y1,1)~=size(y2,1) % reshape y2 = y2.'; end utils.math.qqplot(y1, y2, params); end otherwise % build parameters struct params = struct(... 'ProbDist',dist,... 'ShapeParam',shapeparam,... 'params',distparams,... 'conflevel',conf,... 'FontSize',ftsize,... 'LineWidth',lwidth); % run over input aos for ii=1:numel(as) utils.math.qqplot(as(ii).y, [], params); end end end %-------------------------------------------------------------------------- % Get Info Object %-------------------------------------------------------------------------- function ii = getInfo(varargin) if nargin == 1 && strcmpi(varargin{1}, 'None') sets = {}; pl = []; elseif nargin == 1 && ~isempty(varargin{1}) && ischar(varargin{1}) sets{1} = varargin{1}; pl = getDefaultPlist(sets{1}); else sets = SETS(); % get plists pl(size(sets)) = plist; for kk = 1:numel(sets) pl(kk) = getDefaultPlist(sets{kk}); end end % Build info object ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: qqplot.m,v 1.1 2011/07/08 10:28:02 luigi Exp $', sets, pl); end %-------------------------------------------------------------------------- % Defintion of Sets %-------------------------------------------------------------------------- function out = SETS() out = {... 'empirical', ... 'normal', ... 'chi2', ... 'f', ... 'gamma' ... }; end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function plout = getDefaultPlist(set) persistent pl; persistent lastset; if ~exist('pl', 'var') || isempty(pl) || ~strcmp(lastset, set) pl = buildplist(set); lastset = set; end plout = pl; end function plo = buildplist(set) plo = plist(); p = param({'TESTDISTRIBUTION', ['test data are compared with the given'... 'test distribution. Available choices are:<ol>'... '<li>EMPIRICAL test the all the input object (starting from the second) against the first object.</li>'... '<li>NORMAL test all the input objects against the Normal distribution</li>'... '<li>CHI2 test all the input objects against the Chi square distribution</li>'... '<li>F test all the input objects against the F distribution</li>'... '<li>GAMMA test all the input objects against the Gamma distribution</li></ol>']}, ... {1, {'EMPIRICAL', 'NORMAL', 'CHI2', 'F', 'GAMMA'}, paramValue.SINGLE}); plo.append(p); p = param({'CONFLEVEL', 'Confidence level for confidence interval calculations.'},... paramValue.DOUBLE_VALUE(0.95)); plo.append(p); p = param({'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 [3]. 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.']}, paramValue.DOUBLE_VALUE(1)); plo.append(p); p = param({'FONTSIZE', 'Font size for axis'}, paramValue.DOUBLE_VALUE(22)); plo.append(p); p = param({'LINEWIDTH', 'Line Width'}, paramValue.DOUBLE_VALUE(2)); plo.append(p); switch lower(set) case 'empirical' % do nothing case 'normal' p = param({'MEAN', ['The mean of the normal distribution']}, paramValue.DOUBLE_VALUE(0)); plo.append(p); p = param({'STD', ['The standard deviation of the normal distribution']}, paramValue.DOUBLE_VALUE(1)); plo.append(p); case 'chi2' p = param({'DOF', ['Degrees of freedom of the chi square distribution']}, paramValue.DOUBLE_VALUE(2)); plo.append(p); case 'f' p = param({'DOF1', ['First degree of freedom of the F distribution']}, paramValue.DOUBLE_VALUE(2)); plo.append(p); p = param({'DOF2', ['Second degree of freedom of the F distribution']}, paramValue.DOUBLE_VALUE(2)); plo.append(p); case 'gamma' p = param({'SHAPE', ['Shape parameter (k) of the Gamma distribution']}, paramValue.DOUBLE_VALUE(2)); plo.append(p); p = param({'SCALE', ['Scale parameter (theta) of the Gamma distribution']}, paramValue.DOUBLE_VALUE(2)); plo.append(p); otherwise end end