clc;
clear;
close all;


img = imread('stplot.tif');
doflip = true;
step = 32;
wndsz = 64;
fps = 800;

if doflip
    img = fliplr(img);
    imwrite(img, '_img.tif');
else
    imwrite(img, '_img.tif');
end
clear doflip;
a = 1 : step : size(img,1);
b = wndsz : step : size(img,1);
a = a(1:length(b));


TrImg = uint8(zeros(size(img)));
invalid = [];
for i = 1 : 1 : length(a)
    % enhance trace
    st = img(a(i):b(i),:);
    m = mean(st,2);
    m = [find(m==0); find(m==255)];
    if ~isempty(m)
        invalid = [invalid, a(i):b(i)];
        continue;
    end
    [ste, ang] = TraceEnhance(st);
    
    % find hough peaks
    th = graythresh(ste);
    bw = imbinarize(ste, th);
    [H,T,R] = hough(bw, 'Theta',[-89:-1]);
    P  = houghpeaks(H, wndsz);
    
    % remove false hough peaks (wrong angle)
    th = 3;
    y = P(:,1);
    x = P(:,2);
    k = abs(ang+T(x));
    k = find(k>th);
    P(k,:) = [];
    y = P(:,1);
    x = P(:,2);
    
    % remove false hough peaks (out of 2x SD )
    rx = [mean(x)-2*std(x), mean(x)+2*std(x)];
    k = [find(x<rx(1)); find(x>rx(2))];
    k = sort(unique(k));
    P(k,:) = [];
    
    % fit hough peaks, linear fitting
    [xData, yData] = prepareCurveData( P(:,1), P(:,2) );
    [fitresult, gof] = fit( xData, yData, fittype( 'poly1' ) );
    y = 1 : size(H,1);
    x = round(fitresult.p1.*y + fitresult.p2);
    z = zeros(1,length(y));
    for j = 1 : length(z)
        if(x(j)>89)
            continue;
        end
        z(j) = H(y(j),x(j));
    end
    
    % find hough peaks on the fitted line
    th = 3;
    z(z<th) = 0;
    z = (z-min(z)) / (max(z)-min(z));
    [ypeak, xpeak] = findpeaks(z);
    [~, xvally] = findpeaks(1-z);
    yvally = z(xvally);
    k = find(yvally~=0);
    n = [];
    if ~isempty(k)
        k = xvally(k);
        n = nan(1, length(k));
        for j = 1 : length(k)
            [~, s] = sort(abs(xpeak-k(j)));
            s = s(1:2);
            s = xpeak(s);
            if z(s(1)) > z(s(2))
                n(j) = s(2);
            elseif z(s(1)) < z(s(2))
                n(j) = s(1);
            else
                n(j) = s(2);
            end
            n(j) = find(xpeak==n(j));
        end
    end
    xpeak(n) = [];
    
    % find hough lines
    y = y(xpeak);
    x = x(xpeak);
    P = [y',x'];
    lines = houghlines(bw,T,R,P, 'FillGap',wndsz, 'MinLength',5);
    p1 = zeros(length(lines), 2);
    p2 = zeros(length(lines), 2);
    for j = 1 : length(lines)
        p1(j,:) = lines(j).point1;
        p2(j,:) = lines(j).point2;
    end
    
    % extend hough lines to image size
    p = cell(1,2);
    p{1} = zeros(size(p1));
    p{2} = zeros(size(p2));
    k = zeros(1, size(p1,1));
    d = zeros(1, size(p1,1));
    for j = 1 : size(p1,1)
        y = [p1(j,2), p2(j,2)];
        x = [p1(j,1), p2(j,1)];
        [xData, yData] = prepareCurveData( x, y );
        [fitresult, gof] = fit( xData, yData, fittype( 'poly1' ) );
        x = [1 size(ste,2)];
        y = round(fitresult(x));
        p{1}(j,1) = x(1);
        p{1}(j,2) = y(1);
        p{2}(j,1) = x(2);
        p{2}(j,2) = y(2);
        k(j) = fitresult.p1;
        d(j) = fitresult.p2;
    end
    xi = 1;
    yi = 2;
    
    % remove false hough lines
    [~,n] = sort(p{1}(:,yi));
    p{1} = p{1}(n,:);
    p{2} = p{2}(n,:);
    k = k(n);
    d = d(n);
    n = [];
    m = mean(k);
    for j = 1 : size(p{1},1)-1
        if ( ( p{2}(j,yi)>=p{2}(j+1,yi) ) && ( p{2}(j+1,yi)<=size(ste,1) ) )
            if abs(k(j)-m) >= abs(k(j+1)-m)
                n = [n, j];
            else
                n = [n, j+1];
            end
        end
    end
    p{1}(n,:) = [];
    p{2}(n,:) = [];
    k(n) = [];
    d(n) = [];
    
    % generate trace image
    tr = uint8(zeros(size(ste)));
    for j = 1 : size(p{1},1)
        % x -> y
        x = 1 : size(ste,2);
        y = k(j) .* x + d(j);
        y = round(y);
        n = [find(y<1), find(y>size(ste,1))];
        y(n) = [];
        x(n) = [];
        x1 = x;
        y1 = y;
        for t = 1 : length(x1)
            tr(y1(t),x1(t)) = 255;
        end
        % y -> x
        y = 1 : size(ste,1);
        x = (y - d(j)) ./ k(j);
        x = round(x);
        n = [find(x<1), find(x>size(ste,2))];
        y(n) = [];
        x(n) = [];
        x2 = x;
        y2 = y;
        for t = 1 : length(x2)
            tr(y2(t),x2(t)) = 255;
        end
    end
    TrImg(a(i)+wndsz/4 : b(i)-wndsz/4, :) = tr(wndsz/4+1 : wndsz-wndsz/4, :);
end
imwrite(TrImg, '_tr.tif');
valid = [a(1)+wndsz/4, b(i)-wndsz/4];
invalid = unique(invalid);
save('info.mat', 'step', 'wndsz', 'fps', 'valid', 'invalid')


clear all;
tr = imread('_tr.tif');
load('info.mat');
timeseq = 0 : 1/fps : (size(tr,1)-1)/fps;

cellnum = nan(1, size(tr,1));
for i = valid(1) : valid(2)
    if isempty(find(invalid==i))
        p = [0, tr(i,:), 0];
        p = single(p);
        [~, n] = findpeaks(p);
        cellnum(i) = length(n);
    end
end
cellnum(invalid) = nan;
cnt = cellnum(valid(1):valid(2));
c = cnt(~isnan(cnt));
m = mean(c);
s = std(c);

r = round([m-2*s, m+2*s]);
n2 = [find(cnt<r(1)), find(cnt>r(2))];
n2 = sort(n2);
n2 = unique(n2);
r = round([m-s, m+s]);
n1 = [find(cnt<r(1)), find(cnt>r(2))];
n1 = sort(n1);
n = find(ismember(n1,n2));
n1(n) = [];

n = [];
if n1(1)+1 ~= n1(2)
    n = [n, n1(1)];
end
for i = 2 : length(n1)-1
    if ( (n1(i)-1 ~= n1(i-1)) && (n1(i)+1 ~= n1(i+1)) )
        n = [n, n1(i)];
    end
end
if n1(end)-1 ~= n1(end-1)
    n = [n, n1(end)];
end

n = [n, n2];
n = unique(n);
n = sort(n);
if n(end) == length(cnt)
    cnt(end) = cnt(end-1);
    n(end) = [];
end
if n(1) == 1
    cnt(1) = cnt(2);
    n(1) = [];
end

x = 0 : length(cnt)-1;
y = cnt;
x([n, find(isnan(cnt))]) = [];
y([n, find(isnan(cnt))]) = [];
[xData, yData] = prepareCurveData( x, y );
ft = 'linearinterp';
[fitresult, gof] = fit( xData, yData, ft );
x = 0 : length(cnt)-1;
y = fitresult(x);
y = round(y');
cnt(n) = y(n);

cellnum(valid(1):valid(2)) = cnt;
cellnum(invalid) = nan;
cnt([n, find(isnan(cnt))]) = [];
m = mean(cnt);
s = std(cnt);
CellNum = [timeseq; cellnum];
save CellNum CellNum;

n = cellnum;
n(isnan(n)) = [];
m = [];
for i = min(n) : max(n)
    m = [m, length(find(n==i))];
end
m = m./(sum(m));
bar([min(n):max(n)], m);
xlabel('Lineal density');
ylabel('Frequency');








function [StEn, Ang] = TraceEnhance(st)

g = single(st);
gt = mean(g,2);
gd = mean(g,1);
gm = mean(g(:));
gi = gt*gd/gm;
r = g./gi;
r = r - mean(r(:));

Theta = [1 : 0.1 : 89];
[phi,~] = radon(r, Theta);
sn = rms(phi,1) / rms(phi(:));
[~,ta] = max(sn);
Ang = Theta(ta);

m = mean(st);
st = double(st);
for i = 1 : size(st,1)
    st(i,:) = st(i,:)./m;
end

wavelength = 7;
orientation = [Ang];
sfb = 1.75;
sar = 0.25;
g = gabor(wavelength,orientation, 'SpatialFrequencyBandwidth',sfb, 'SpatialAspectRatio',sar);
m = imgaborfilt(st,g);
r = m.*m;

% g = single(r);
% gt = mean(g,2);
% gd = mean(g,1);
% gm = mean(g(:));
% gi = gt*gd/gm;
% r = g./gi;
% r = r - mean(r(:));

r = (255 * (r - min(r(:))) / (max(r(:)) - min(r(:))));
se = strel('disk', 1, 4);
r = imerode(r, se);

sigmas = [0.25 : 0.25 : 1];
spacing = [2;2];
tau = 1;
brightondark = true;
r = vesselness2D(r, sigmas, spacing, tau, brightondark);

StEn = (r - min(r(:))) / (max(r(:)) - min(r(:)));

clear st g gt gd gm gi r Theta phi sn ta m wavelength orientation se sfb sar sigmas spacing tau brightondark i;

end