gedagui.m

常用ROBUST STATISTICAL

        % First reset the stuff to black and the same size as others.
        % Then also put the tag on there.
        for i = 1:length(dims)
            for j = i:length(dims)
                set(H(i,j),'markersize',3,'marker','o','linestyle','none',...
                    'markerfacecolor','w','color','k',...
                    'tag','black')
                set(H(j,i),'markersize',3,'marker','o','linestyle','none',...
                    'markerfacecolor','w','color','k',...
                    'tag','black')
            end
        end
        pp = length(dims);
        % just need the axes for highlighting. Do not add this to the brushing one.
        ind = sub2ind(size(ax),1:pp,1:pp);
        ax = ax(:);
        ax(ind) = [];
        % Save handles to highlighted axes in here.
        ud.highlight = [ud.highlight,ax'];
        
        set(0,'userdata',ud)

    case 2
        % Color by groups - must be loaded by the user. Not from
        % clustering.
        if isempty(ud.classlab)
            errordlg('You must load some group labels.')
            close(hf)
            return
        end
        % No variable labels with this one - histograms on diagonal.
        gplotmatrix(data(:,dims),[],ud.classlab,[],[],[],'no');
    case 3
        % Color by clusters. 
        if isempty(ud.kmeansids) & isempty(ud.agcids) & isempty(ud.mbcids)
            % haven't clustered anything yet.
            errordlg('You must create some clusters first.')
            close(hf)
            return
        end
        menustrg = [];
        cidstr = [];
        if ~isempty(ud.kmeansids)
            menustrg = [menustrg, {'k-Means Clusters'}];
            cidstr = [cidstr, {'ud.kmeansids'}];
        end
        if ~isempty(ud.agcids)
            menustrg = [menustrg, {'Agglomerative Clustering'}];
            cidstr = [cidstr, {'ud.agcids'}];
        end
        if ~isempty(ud.mbcids)
            menustrg = [menustrg, {'Model-Based Clustering'}];
            cidstr = [cidstr, {'ud.mbcids'}];
        end
        if length(cidstr) == 1
            % no need for a listbox. Just plot.
            eval(['gplotmatrix(data(:,dims),data(:,dims), ' cidstr{1} ' );'])
        else
            [sel,ok] = listdlg('PromptString','Select a type of clustering:',...
                'SelectionMode','single',...
                'ListString',menustrg);
            if ok == 1
                % person selected something.
                eval(['gplotmatrix(data(:,dims),data(:,dims), ' cidstr{sel} ' );'])
            end
            
        end
end


%%%%%%%%%%%%%%%%%%%%%%%%%
function brushlink
% This function will not do any color stuff, so no need to worry about
% color, brushing or linking.
% NOTE that this plot will NOT be closed with the GUI like the others.

tg = findobj('tag','gedagui');
H = get(tg,'userdata');
ud = get(0,'userdata');
if isempty(ud.X)
    errordlg('You must load some data first.')
    return
end
% Get the dataset to be used.
tmp = get(H.data,'string');
dataset = tmp{get(H.data,'value')};
switch dataset
    case 'X'
        % use the original data ud.X
        data = ud.X;
        xstr = 'X';
    case 'PCA'
        % use PCA field. this is the projection matrix so data =
        % ud.X*ud.pca(:,1:d). 
        data = ud.X*ud.pca;
        xstr = 'PCA';

    case 'LLE'
        data = ud.LLE;
        xstr = 'LLE';
    case 'HLLE'
        data = ud.hLLE;
        xstr = 'HLLE';
    case 'ISOMAP'
        % Check to see what is saved there. Might be the whole thing or
        % might be just what the user outputs. Depends on whether the other
        % gui is open or not.
        % if iscell - then get the right number of dimensions wanted - like
        % pca. else it is double - correct array to just use.
        [n,p] = size(ud.X);
        if ~iscell(ud.isomap)
            data = ud.isomap;
        else
            data = ud.isomap{end}';
        end
        xstr = 'ISOMAP';
                
    case 'MDS'
        % Added 11-12-05 - Process the MDS data.
        data = ud.mds;
        xstr = 'MDS';
        
    case 'CMDS'
        % Added 11-12-05 - Process the CMDS data.
        data = ud.cmds;
        xstr = 'CMDS';
        
    case 'PPEDA'
        % Added 11-12-05 - Process the PPEDA data.
        Z = sphere(ud.X);
        data = Z*ud.ppeda;
        xstr = 'PPEDA';
       

end
[n,p] = size(data);
% Get the information for plotting: Dimensions to use.
tmp = get(H.dimbrush,'string');
if strcmp(lower(tmp),'all')
    % user wants all dimensions to display.
    dims = 1:p;
else
    eval(['dims = [' tmp '];']);
    dims = round(dims);
end
if any(dims < 1) | any(dims > p)
    errordlg(['Dimensions must be between 1 and ' int2str(p)])
    return
end
if length(unique(dims)) < length(dims)
    errordlg('Dimensions must be different.')
    return
end

% Set up the string array for plotting purposes.
if strcmp(dataset,'X')
    % Then we are plotting the regular data set. Just use the regular
    % labels.
    labstrg = ud.varlab(dims);
else
    % we are plotting something else - PCA, etc.
    for ii = 1:length(dims)
        labstrg{ii} = [xstr ' ' int2str(dims(ii))];
    end
end

% This function will create its own figure. Do not mess with the function -
% too many things can get messed up!!!!!
brushscatter(data(:,dims),labstrg);

% Set some housekeeping things.
hf = findobj('Name','Scatterplot Brushing');
set(hf,'numbertitle','off','name','EDA: Scatterplot Matrix Brushing')
% set(hf,'tag','brush','numbertitle','off','name','EDA: Scatterplot Matrix Brushing')
% Upon figure close, this should delete from the array.
set(hf,'CloseRequestFcn',...
    'tg = findobj(''tag'',''gedagui''); H = get(tg,''userdata''); H.plots(find(H.plots == gcf)) = []; set(tg,''userdata'',H); delete(gcf)')
H.plots = [H.plots, hf];
set(tg,'userdata',H)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%       DO ANDREWS CURVES
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function doandrews

tg = findobj('tag','gedagui');
H = get(tg,'userdata');
ud = get(0,'userdata');
if isempty(ud.X)
    errordlg('You must load some data first.')
    return
end
% Get the dataset to be used.
tmp = get(H.data,'string');
dataset = tmp{get(H.data,'value')};
switch dataset
    case 'X'
        % use the original data ud.X
        data = ud.X;
        xstr = 'X';
    case 'PCA'
        % use PCA field. this is the projection matrix so data =
        % ud.X*ud.pca(:,1:d). 
        data = ud.X*ud.pca;
        xstr = 'PCA';

    case 'LLE'
        data = ud.LLE;
        xstr = 'LLE';
    case 'HLLE'
        data = ud.hLLE;
        xstr = 'HLLE';
    case 'ISOMAP'
        % Check to see what is saved there. Might be the whole thing or
        % might be just what the user outputs. Depends on whether the other
        % gui is open or not.
        % if iscell - then get the right number of dimensions wanted - like
        % pca. else it is double - correct array to just use.
        [n,p] = size(ud.X);
        if ~iscell(ud.isomap)
            data = ud.isomap;
        else
            data = ud.isomap{end}';
        end
        xstr = 'ISOMAP';
        
                
    case 'MDS'
        % Added 11-12-05 - Process the MDS data.
        data = ud.mds;
        xstr = 'MDS';
        
    case 'CMDS'
        % Added 11-12-05 - Process the CMDS data.
        data = ud.cmds;
        xstr = 'CMDS';
        
    case 'PPEDA'
        % Added 11-12-05 - Process the PPEDA data.
        Z = sphere(ud.X);
        data = Z*ud.ppeda;
        xstr = 'PPEDA';
       

end
[n,p] = size(data);
% Get the information for plotting: Dimensions to use.
tmp = get(H.dimandrews,'string');
if strcmp(lower(tmp),'all')
    % user wants all dimensions to display.
    dims = 1:p;
else
    eval(['dims = [' tmp '];']);
    dims = round(dims);
end
if any(dims < 1) | any(dims > p)
    errordlg(['Dimensions must be between 1 and ' int2str(p)])
    return
end
if length(unique(dims)) < length(dims)
    errordlg('Dimensions must be different.')
    return
end
% Get the color by groups flag.
colflag = get(H.popmode,'value');
% OK to plot
hf = figure;
set(hf,'tag','andrews','numbertitle','off','name','EDA: Andrews'' Curves')
set(hf,'backingstore','off','renderer','painters','DoubleBuffer','on')
% Upon figure close, this should delete from the array.
set(hf,'CloseRequestFcn',...
    'gedagui(''update'');tg = findobj(''tag'',''gedagui''); H = get(tg,''userdata''); H.plots(find(H.plots == gcf)) = []; set(tg,''userdata'',H); delete(gcf)')
H.plots = [H.plots, hf];
set(tg,'userdata',H)
figure(hf)
fud = [];
switch colflag
    case 1
        % just do a plain plot
        Hline = andrews(data(:,dims),0);
        % This is a vector of handles - each observation has a handle.
        ud.linkptrap = [ud.linkptrap, hf];
        ud.linkap = [ud.linkap, Hline(:)];
        set(0,'userdata',ud)

    case 2
        % Color by groups - must be loaded by the user. Not from
        % clustering.
        if isempty(ud.classlab)
            errordlg('You must load some group labels.')
            close(hf)
            return
        end
        andrews(data(:,dims),1,ud.classlab);
    case 3
        % Color by clusters. 
        if isempty(ud.kmeansids) & isempty(ud.agcids) & isempty(ud.mbcids)
            % haven't clustered anything yet.
            errordlg('You must create some clusters first.')
            close(hf)
            return
        end
        menustrg = [];
        cidstr = [];
        if ~isempty(ud.kmeansids)
            menustrg = [menustrg, {'k-Means Clusters'}];
            cidstr = [cidstr, {'ud.kmeansids'}];
        end
        if ~isempty(ud.agcids)
            menustrg = [menustrg, {'Agglomerative Clustering'}];
            cidstr = [cidstr, {'ud.agcids'}];
        end
        if ~isempty(ud.mbcids)
            menustrg = [menustrg, {'Model-Based Clustering'}];
            cidstr = [cidstr, {'ud.mbcids'}];
        end
        if length(cidstr) == 1
            % no need for a listbox. Just plot.
            eval(['andrews(data(:,dims),1, ' cidstr{1} ' );'])
        else
            [sel,ok] = listdlg('PromptString','Select a type of clustering:',...
                'SelectionMode','single',...
                'ListString',menustrg);
            if ok == 1
                % person selected something.
                eval(['andrews(data(:,dims),1, ' cidstr{sel} ' );'])
            end
            
        end
end
title(xstr)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
function Hline = andrews(data,colflag,g)
% Hline is a vector of line handles.
% g is a vector of class labels.
[n,p] = size(data);

% THe following gets the axis lines.
% axis off
hax = axes('position',[0.05 0.075 0.9  0.8]);
set(hax,'visible','off')
set(hax,'xlimmode','manual')
set(hax,'xlim',[-pi pi])
axis off