function out=legTrackerScoreMovie(mov,scoreJK,scoreBD,scoreKNN,KNNdata,colors)
%Generates a movie with recorded video of a fly on the ball, manual
%behavior scores, the KNN classifier scores, and visualizations of the data
%vectors used to generate the classification. Used to make Movie S1.
%Modified to make Movie S2 by commenting out the portions for displaying
%the manual scores
%Usage:
%out=legTrackerScoreMovie(mov,scoreJK,scoreBD,scoreKNN,KNNdata,colors)
%mov = imported .avi move to be decorated
%scoreJK = JK's manual scores
%scoreBD = BD's manual scores
%scoreKNN = scores generated by the KNN classifier
%KNNdata = Nx45 array where N=number of frames, and 45 corresponds to the
%          raw data and higher order feature vectors.
%colors = illustration colors in variable in legTrackerAnnotateColors.mat

% movie dimensions
H=360;
W=690;

%list of behavioral labels
labels=cell(12,1);
labels{1}='nothing';
labels{2}='postural adjust.';
labels{3}='fwd/bkwd running';
labels{4}='turning in place';
labels{5}='crabwalking';
labels{6}='complex motion';
labels{7}='L1 grooming';
labels{8}='head grooming';
labels{9}='L2-L3 grooming';
labels{10}='abdomen grooming';
labels{11}='L3 grooming';
labels{12}='other';

%start building image data
image(zeros(H,W,3)+1)
hold on;

%composition parameters
legScale=3;
xOff=10;
derivScale=5;
stdScale=5;
velScale=1;
aceScale=1;

% for 4000 frames
for i=1:4000
    
    %status indicator
    disp(i)
    
    %clear current figure
    clf;
    
    %start building image data
    image(zeros(H,W,3)+1);
    set(gca, 'visible', 'off')
    hold on;
    
    %add movie frame
    imTemp=read(mov,263+i);
    image(30,30,imTemp(1:200,36:end-20,:));
    
    %add gray box labels
    N=20;
    plot([32+N/2 292-N/2], [270 270], 'Color', [.84 .84 .84], 'LineWidth', N);
    text(45,270,'video for manual scoring', 'FontSize', 15, 'FontWeight', 'bold');
    plot([339+N/2 430-N/2], [263 263], 'Color', [.84 .84 .84], 'LineWidth', N-2);
    text(347,262,'raw data', 'FontSize', 15);
    plot([445+N/2 655-N/2], [263 263], 'Color', [.84 .84 .84], 'LineWidth', N-2);
    text(459,262,'higher order features', 'FontSize', 15);
    plot([340+N/2 654-N/2], [295 295], 'Color', [.84 .84 .84], 'LineWidth', N);
    text(389,295,'data for KNN classifier', 'FontSize', 15, 'FontWeight', 'bold');
    
    %add manual scores - Comment these 4 lines out to make a movie without
    %manual scores
    text(36,300,'score(jk): ', 'FontSize', 15, 'FontWeight', 'bold');
    text(130,300,labels{scoreJK(i)+1} , 'FontSize', 15, 'FontWeight', 'bold', 'Color', colors(scoreJK(i)+1,:) );
    text(26,325,'score(bd): ', 'FontSize', 15, 'FontWeight', 'bold');
    text(130,325,labels{scoreBD(i)+1} , 'FontSize', 15, 'FontWeight', 'bold', 'Color', colors(scoreBD(i)+1,:) );
    
    %add classifier scores
    text(344,327,'score(KNN): ', 'FontSize', 15, 'FontWeight', 'bold');
    text(466,327,labels{scoreKNN(i)+1} , 'FontSize', 15, 'FontWeight', 'bold', 'Color', colors(scoreKNN(i)+1,:) );
    
    %add leg position label and indicator
    text(xOff+335,120,'leg positions ', 'FontSize', 12, 'FontWeight', 'bold');
    scatter(xOff+365+KNNdata(i,9)*legScale,85+KNNdata(i,3)*legScale,'b.');
    scatter(xOff+390+KNNdata(i,12)*legScale,85+KNNdata(i,6)*legScale, 'b.');
    scatter(xOff+355+KNNdata(i,11)*legScale,65+KNNdata(i,5)*legScale,'b.');
    scatter(xOff+400+KNNdata(i,8)*legScale,65+KNNdata(i,2)*legScale, 'b.');
    scatter(xOff+365+KNNdata(i,7)*legScale,45+KNNdata(i,1)*legScale,'b.');
    scatter(xOff+390+KNNdata(i,10)*legScale,45+KNNdata(i,4)*legScale, 'b.');
    
    %add leg derivative label and indicator
    text(xOff+440,120,'leg derivatives', 'FontSize', 12, 'FontWeight', 'bold');
    arrow([xOff+475 85],[xOff+475 85]-[KNNdata(i,39)*derivScale KNNdata(i,33)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    arrow([xOff+500 85],[xOff+500 85]-[KNNdata(i,42)*derivScale KNNdata(i,36)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    arrow([xOff+465 65],[xOff+465 65]-[KNNdata(i,41)*derivScale KNNdata(i,35)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    arrow([xOff+510 65],[xOff+510 65]-[KNNdata(i,38)*derivScale KNNdata(i,32)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    arrow([xOff+475 45],[xOff+475 45]-[KNNdata(i,37)*derivScale KNNdata(i,31)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    arrow([xOff+500 45],[xOff+500 45]-[KNNdata(i,40)*derivScale KNNdata(i,34)*derivScale],'Width', 1, 'TipAngle', 30, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    
    %add ellipse representation of local x- and y- standard deviations of
    %leg position
    text(xOff+560,120,'std(leg pos)', 'FontSize', 12, 'FontWeight', 'bold');
    ellipse(KNNdata(i,24)*stdScale,KNNdata(i,18)*stdScale,0,587,85,[.5 .5 .5]);
    ellipse(KNNdata(i,27)*stdScale,KNNdata(i,21)*stdScale,0,612,85,[.5 .5 .5]);
    ellipse(KNNdata(i,26)*stdScale,KNNdata(i,20)*stdScale,0,577,65,[.5 .5 .5]);
    ellipse(KNNdata(i,23)*stdScale,KNNdata(i,17)*stdScale,0,622,65,[.5 .5 .5]);
    ellipse(KNNdata(i,22)*stdScale,KNNdata(i,16)*stdScale,0,587,45,[.5 .5 .5]);
    ellipse(KNNdata(i,25)*stdScale,KNNdata(i,19)*stdScale,0,612,45,[.5 .5 .5]);
    
    % add ball 3-axis velocity labels and data values
    text(xOff+335,225,'ball velocity', 'FontSize', 12, 'FontWeight', 'bold');
    plot(xOff+345+[0 0], 178-[0 KNNdata(i,14)*velScale], 'r', 'LineWidth',4)
    text(xOff+335,190,'fwd', 'FontSize', 10, 'FontWeight', 'bold');
    plot(xOff+375+[0 0], 178-[0 KNNdata(i,13)*velScale], 'k', 'LineWidth',4)
    text(xOff+365,190,'turn', 'FontSize', 10, 'FontWeight', 'bold');
    plot(xOff+405+[0 0], 178-[0 KNNdata(i,15)*velScale], 'g', 'LineWidth',4)
    text(xOff+395,190,'crab', 'FontSize', 10, 'FontWeight', 'bold');
    
    % add ball 3-axis acceleration labels and data values
    text(xOff+440,225,'ball accelerat.', 'FontSize', 12, 'FontWeight', 'bold');
    arrow([xOff+457 178], [xOff+457 178-KNNdata(i,44)*aceScale],'Width', 2, 'TipAngle', 45, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'r', 'faceColor', 'r');
    text(xOff+447,190,'fwd', 'FontSize', 10, 'FontWeight', 'bold');
    arrow([xOff+487 178], [xOff+487 178-KNNdata(i,43)*aceScale],'Width', 2, 'TipAngle', 45, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'k', 'faceColor', 'k');
    text(xOff+477,190,'turn', 'FontSize', 10, 'FontWeight', 'bold');
    arrow([xOff+517 178], [xOff+517 178-KNNdata(i,45)*aceScale],'Width', 2, 'TipAngle', 45, 'BaseAngle', 90, 'Length', 3, 'edgeColor', 'g', 'faceColor', 'g');
    text(xOff+507,190,'crab', 'FontSize', 10, 'FontWeight', 'bold');
    
    %add ball 3-axis local standard deviations labels and values
    text(xOff+560,225,'std(ball vel)', 'FontSize', 12, 'FontWeight', 'bold');
    plot(xOff+571+[0 0], 178-[0 KNNdata(i,29)*velScale], 'r', 'LineWidth',4)
    text(xOff+561,190,'fwd', 'FontSize', 10, 'FontWeight', 'bold');
    plot(xOff+601+[0 0], 178-[0 KNNdata(i,28)*velScale], 'k', 'LineWidth',4)
    text(xOff+591,190,'turn', 'FontSize', 10, 'FontWeight', 'bold');
    plot(xOff+631+[0 0], 178-[0 KNNdata(i,30)*velScale], 'g', 'LineWidth',4)
    text(xOff+621,190,'crab', 'FontSize', 10, 'FontWeight', 'bold');
    
    %pause to update screen and buffer
    pause(0.01);
    
    %grab image to movie output.
    movie1(i)=getframe;
    
end


out=movie1;