% function bwim = hairpin( centers, rotim, xrange, yrange )
function  hairpin(path);
% bwim : 1 = normal tile, 2 = hairpined tile, 0 = background


% method 1: look in region of tile, take mean/median value , cluster 2
% groups

% q1 : is there a better idicator than mean/median?
%   average upper 1/4 of gray values
% q2 : is the time tradeoff worth this better indicator?

% uncomment to test without interfacing to program
% function hairpin
% centers = imread('/home/wrightc/find/test/test/result.091','tiff');
% centers = double(centers);
% rotim = imread('/home/wrightc/find/test/rotim.091','tiff');
% 
% yrange = 9;
% xrange = 5;

load('-mat', path, 'xave','yave','N', 'xmax','ymax', 'x', 'y', 'rotim');

xrange = ceil(xave/3);
yrange = ceil(yave/3);

gray1 = zeros(N,1);
gray2 = zeros(N,1);
gray3 = zeros(N,1);
for n = 1:N
    ylow = y(n)-yrange;
    yhigh = y(n)+yrange;
    xlow = x(n)-xrange;
    xhigh = x(n)+xrange;
    if ( ylow > 0 & xlow > 0 & yhigh < ymax & xhigh < xmax )
    area = rotim( (y(n)-yrange):(y(n)+yrange), (x(n)-xrange):(x(n)+xrange) );

    % mean of top 1/4 brightest values
    temp = sort(area(:), 'descend');
    len = length(temp);
    r =  ceil(len/2);

    gray3(n) = temp(1) - temp( r );
    
    end
end
    h = hist(gray3, 40);
figure (3)
plot(h)

% no seperation
% median 
% median of top 1/4 
% mean of top 1/4

% seperation
% mean
% difference of max and min
% difference in means of top1/2 and bottom 1/2  
% difference of max and median *best*


%%%%%%%%%%%%%%%%%%%% CLUSTERING

[ind1,int1] = kmeans(gray3,2,'replicates',3);

% problem with clustering : gray values are not distinct enough, continuous
% spectrum of gray values makes it hard to cluster
% median clusters sssssssssslightly better, because of indifference to
% extreme values -- more seperable
% other problem: image not sufficiently flattened

if int1(1) > int1(2)
    hair = 1;
    nohair = 2;
else
    hair = 2;
    nohair = 1;
end
% the one with the larger cluster value is the hairpin cluster
hair1 = find( ind1 == hair);
nohair1 = find( ind1 == nohair);

figure(4)
    imagesc(rotim)
    colormap gray
    hold on
    plot(x(hair1),y(hair1), 'r+')
    plot(x(nohair1),y(nohair1), 'b+')

for n = 1:N
    if ind1(n) == hair
        centers(y(n),x(n)) = 2;
    end
end
        
% correcting hairpins
button =1;
while button ~= 2
    [xx,yy,button] = ginput(1);
    n = findclosest( x,y ,xx,yy);
    
    % hairpin
    if button == 1
        ind1(n) = hair;
        plot(x(n),y(n), 'r+')
    % not hairpin
    elseif button == 3
        ind1(n) = nohair;
        plot(x(n),y(n), 'b+')
    end
end
    hold off

    
    hair = (ind1 == hair);
    save( path, 'hair', '-mat','-append');