ET_PDToolkit/PDToolkit/@PDTrial/plot.m

function[obj]= plot(varargin)
cla;
hold on;

obj = varargin{1};
settings = struct('BaselineCorrection', 0,...
                  'FilterSize', 100, ...
                  'BlinkExtension', [10 10],...
                  'MaximumBlinkSize', 150,...
                  'QualityThreshold',50);

if nargin > 1
    settings = varargin{2};
end

%% get plotting options
options = get(gcf, 'UserData');
    
if ~isfield(options,'raw')
    options.raw = 0;
    options.logtransformed = 1;
    options.interpolated = 1;
    options.filtered = 1;
    options.blinks = 1;
    options.markers = 1;
    options.labels   = 1;
    options.baseline = 0;
    options.baseline_corrected = 0;
    options.deconvolution = 0;
    
    options.drawing = options;
    options.drawing.raw = {'-', [1 0 0], 3};
    options.drawing.logtransformed = {'-', [0 0 0.5], 3};
    options.drawing.interpolated= {'-', [0.5 0 0], 3};
    options.drawing.filtered= {'-', [0 0.5 0], 3};
    options.drawing.markers= {'-.', [0.5 0 0], 3};
    options.drawing.baseline= {'--', [0 0 1], 3};
    options.drawing.baseline_corrected= {'--', [0 0 0], 3};
    
end

if (options.baseline_corrected)
    field = 'baseline_corrected';
    options.baseline = 0;
else    
   field = 'uncorrected';
            
end


miny = 1e6; maxy = 0;

signals = fieldnames(options);
for i = 1:length(signals)
    if (strcmp(signals{i}, 'drawing') || ...
        strcmp(signals{i}, 'markers') || ...
        strcmp(signals{i}, 'labels')  || ...
        strcmp(signals{i}, 'blinks')  || ...
        strcmp(signals{i}, 'deconvolution')  || ...
        strcmp(signals{i}, 'baseline_corrected'))
                continue;   
    end
        
    if getfield(options, signals{i}) %% plotting is enabled
        
        signal = getfield(getfield(obj.data, field), signals{i});
        y = [min(signal) max(signal) ];
        len = min(length(obj.time),  length(signal));
        
        drawing = getfield(options.drawing, signals{i});
        ls = drawing{1}; color = drawing{2}; lw = drawing{3};
        
        if (strcmp(signals{i}, 'filtered'))
            signal(1:settings.FilterSize) = NaN;
            signal(len - settings.FilterSize:len) = NaN;
        end
        
        miny = min(min(signal),miny);
        maxy = max(max(signal),maxy);

        
        plot(obj.time(1:len), signal(1:len), 'LineWidth', lw, 'Color', color, 'LineStyle', ls);
     
    end
end



if miny > maxy
    tmp = maxy;
    maxy = miny
    miny = tmp;
end


if (options.baseline)
    len = length(obj.data.uncorrected.interpolated);
    baseline_signal = repmat(obj.baseline, 1,len);
    ls = options.drawing.baseline{1}; 
    color = options.drawing.baseline{2}; 
    lw = options.drawing.baseline{3};
    
    len = min(length(obj.time),len);
    plot(obj.time(1:len), baseline_signal, 'Color', color, 'LineWidth', lw, 'LineStyle', ls);
    
    %% real baseline signal plotted
    baseline_ind = intersect(find(obj.time > obj.baseline_onset), ...
                                find(obj.time <= obj.baseline_offset));
    b_time  = obj.time(baseline_ind);
    b_value = obj.data.uncorrected.interpolated(baseline_ind);
    
    plot(b_time, b_value, 'Color', color, 'LineWidth', lw, 'LineStyle', ls);
    
end

if options.blinks

    nans = find(isnan(obj.data.uncorrected.raw));
    dnans = diff(nans);

    i=1;
    
    if (~isempty(nans))    
        x1=obj.time(nans(i));
    end
    %end

    xlist=[];
    while i < length(nans)
        if dnans(i) ~=1
            x2 = obj.time(nans(i));
            xlist = [xlist; x1 x2];
            x1 = obj.time(nans(i+1));
        end
        i=i+1;
    end
 
    for t = 1:size(xlist,1);
      x = [xlist(t,1) xlist(t,1) xlist(t,2) xlist(t,2)];
      y = [miny maxy maxy miny];
      fa=fill(x,y,[1 0 0]);
     set(fa, 'EdgeAlpha', .5, 'EdgeColor',[1 0 0]);
     alpha(fa, 0.5);
    end
    
    plot([obj.time(obj.settings.FilterSize) obj.time(obj.settings.FilterSize)], [miny maxy], 'r-');
    plot([obj.time(end-obj.settings.FilterSize) obj.time(end-obj.settings.FilterSize)], [miny maxy], 'r-');
end
 
if ~isempty(miny)
     ylim([miny*.9 maxy*1.1]); %% fix y limits
end

% %% add 50% grey squares on top of the filter startup effects
% ends = get(gca,'XLim');
% 
% box1 = [ends(1) obj.time(obj.settings.FilterSize) obj.time(obj.settings.FilterSize) ends(1)];
% box2 = [ends(2) obj.time(end-obj.settings.FilterSize) obj.time(end-obj.settings.FilterSize) ends(2)];
% boxy = [miny*.95 miny*.95 maxy*1.1 maxy*1.1];
% %h(1) = fill(box1, boxy,[.5 0 0]);
% %h(2) = fill(box2, boxy,[.5 0 0]);
% %alpha(h, .2);
% 
if options.markers
    markers = {'trial_start', 'trial_end', 'baseline_onset', 'baseline_offset','stimulus_onset', 'stimulus_offset'};    
    marker_colors = {[0 0 0], [0 0 0], [0 0 1], [0 0 1], [1 0.5 0], [1 0.5 0]};
    
    for m = 1:length(markers)
        if ~isempty(obj.(markers{m})) 
            obj.(markers{m})
            
            plot([obj.(markers{m})(1) obj.(markers{m})(1)], [miny maxy], 'Color', marker_colors{m}, 'LineWidth', 2);
        end
    end
end

if options.labels
    
    for l = 1:length(obj.labels)   
        if ~(isfield(obj.labels(l), 'color') && length(obj.labels(l))==3)
            obj.labels(l).color = [ .5 .5 .5];
        end
        plot([obj.labels(l).time obj.labels(l).time], [miny maxy], 'Color', obj.labels(l).color, 'LineWidth', 2);
        
    end
end


if options.deconvolution

    if isfield(obj.deconvolution, 'params')
        params   = obj.deconvolution.params;
        modelfit = obj.prf_convolve(obj.stick_model(params(2:end)),params(1));

        plot(obj.deconvolution.time,modelfit, 'k:');
    
    end
end

    
%qt = text((obj.trial_end - (obj.trial_end - obj.trial_start)/4),...
%           miny + ((maxy - miny) /5), sprintf('Quality: %2.2f%%', obj.quality));
qt = title(sprintf('Quality: %2.2f%%', obj.quality));
set(qt, 'FontName', 'Verdana');
set(qt, 'FontWeight', 'bold');
set(qt, 'FontSize', 10);