plot_data.m~

来自「一个用EM算法的源程序」· M~ 代码 · 共 112 行

% plot_data(data, sampleLabels)
%
% The main function for plotting data generated by the GPCA algorithm.
%
% Can handle two or three dimensional data.
%
% Can also display a set of normal vectors on the same graph.  Not all
% normal vectors need to be computed; the number to be displayed must be
% specified.  Normal vectors will be rendered in order they are passed.
%
function pl = plot_data(data, sampleLabels)

% Hold while drawing a bunch of elements to the current figure.
originalHoldState = ishold;
hold on;

if ~exist('sampleLabels','var'),
    sampleLabels = ones(1,size(data,2));
end

groupCount = max(sampleLabels);
sampleCount = size(data,2);

markers = '.ox+*svp^h<>'; markerCount = length(markers); markerIndex = 1;
colors = 'rbkmgcy'; colorCount = length(colors); colorIndex = 1;

if size(data,1) == 2
    % Plot outliers
    groupDataIndices = samplelabels==0
    if ~isempty(groupDataIndices)
        
    end
    
    for groupIndex = 1:groupCount,
        groupDataIndices = sampleLabels == groupIndex;
        
        pl = plot(data(1, groupDataIndices),data(2,groupDataIndices), [markers(markerIndex) colors(colorIndex)]);
        %       set(pl,'MarkerSize', 5);
        % Set the plot to the default 2D view.
        view(2);
        
        
        % Advance to the next color, and marker if all of the colors have
        % been used.
        colorIndex = colorIndex+1; 
        if (colorIndex > colorCount),
            colorIndex = 1; 
            markerIndex + 1;
            if (markerIndex > markerCount),
                markerIndex = 1;
            end;
        end;
    end
    
    xlabel('axis 1')
    ylabel('axis 2')
    
elseif size(data,1) == 3
    % Plot outliers
    groupDataIndices = samplelabels==0
    if ~isempty(groupDataIndices)
    end
    
    for groupIndex = 1:groupCount,
        groupDataIndices = sampleLabels == groupIndex;
        
        pl = plot3(data(1, groupDataIndices),data(2,groupDataIndices),data(3,groupDataIndices), [markers(markerIndex) colors(colorIndex)]);
        
        set(pl,'MarkerSize', 10);
        % Set the plot to the default 3D view.
        view(3);
        % Set the camera projection type.
        %    camproj('perspective');
        camproj('orthographic');
        
        % Advance to the next color, and marker if all of the colors have
        % been used.
        colorIndex = colorIndex+1; 
        if (colorIndex > colorCount),
            colorIndex = 1; 
            markerIndex + 1;
            if (markerIndex > markerCount),
                markerIndex = 1;
            end;
        end;
    end    
    
    xlabel('axis 1')
    ylabel('axis 2')
    zlabel('axis 3')
    
else 
    warning('Sorry, data must be of dimension 2 or 3 to be displayed by plot_data.m')
    return
end

% Restore original hold state
if ~originalHoldState,
    hold off;
end

% Resize the figure window so that it is more readily visible.
set(0,'Units','pixels');
temp = (get(0,'ScreenSize'));
screenColumns = temp(3);
screenRows = temp(4);
figureFillRatio = [.8 .5]; % Fraction of the columns and rows to fill up.
screenCenter = floor([screenColumns/2 screenRows/2]);
cornerOffset = floor([screenColumns*figureFillRatio(1)/2 screenColumns*figureFillRatio(2)/2]);
set(gcf,'Position',[screenCenter - cornerOffset, 2*cornerOffset]);
%set(gcf,'MenuBar','none')