function [fitresult, gof] = OneForThreev2(bg,guess,filename)   %input a guess for the spatial frequency of the pattern in 1/pixel and a file name

close all;

 %STC1 = videoinput('winvideo');                           Two adaptors are
 %available, choose the one that is applicable based on the matlab version;
 %for 2014b, use stimaqadaptor, winvideo for 2013
 STC1 = videoinput('stimaqadaptor');

img = getsnapshot(STC1);                             %gets the image from camera
Mean = mean(img(:))
Min = min(img(:))
%img = img(:,:)-min(min(img));
img = img(:,:)-bg;                                    %dark current subtraction
%img2 = uint8(zeros(1200,1600));                     %this func. gives a
                                                     %perfect pattern for analysis.  
%for i=1:1600
%    img2(:,i) = 255*((sin(i*pi/100))^2);
%end
%for i=1:1200
%    img(i,:) = img(i,:)*(sin(i*pi/100))^2;
%end

%max(img2(:));
Max = max(img(:))
Mean = mean(img(:))        %max and mean pixel brightness values
Min = min(img(:))

imgscb = img;
%for i=200:398                  %Use this func. if you want a scalebar on
                                  %saved image (50um with standard lens)
%    imgscb(980:1000,i) = 255;
%end

scrsz = get(0,'ScreenSize');
figure(1), imshow(img);             %Gives a figure of the image with scalebar
hold on;
plot([200;398],[1000;1000], '-k', 'LineWidth', 3, 'Color', 'w');
hold off;
text(300,1050, '50µm', 'HorizontalAlignment','center','Color','w','FontWeight','bold','FontSize',16)
set(1, 'Position', [1 scrsz(4)*2/5 scrsz(3)/2 scrsz(4)/2]);
imggaus = uint8(zeros(1200,1600));

for i = 1:1600
    imggaus(:,i) = img(:,i)*exp(-((i-800)^2)/(2*380^2));%Gaussian windowing
end
%figure(4), imshow(imggaus)

ftrans = fftshift(fft2(imggaus));           %Takes FFT of the image and converts it to be viewable
Submatrix = ftrans(401:800,601:1000);   %the region of interest
doughnut = Submatrix;                   %Doughnut functions allow the image levels to be set
doughnut(195:205,195:205) = 0;          %to allow the regions around the central peaks to be seen
top = max(abs(doughnut(:)));
doughnut(125:275,125:275) = 0;
top2 = max(abs(doughnut(:)));

ftdisp = mat2gray(abs(Submatrix), [100 top2*1.5]);  %sets the image brightness scale
figure(2), imshow(ftdisp)                           %Displays the FFT

Filter1 = fspecial('gaussian', 9, 1.5);               %Gaussian blurr filter
%Temp = imfilter(ftdisp, Filter1);
%d =  uint16( ftdisp.*2^16./(max(ftdisp(:))));
d = uint32(1000000*(abs(Submatrix)/top));           %Defines new FFT in unit 16 forma. ***CARE HERE*** for levels
edg = 20;                                           %Number of edge pixels to be avoided in peak finding
max(max(d))
d = conv2(single(d),Filter1,'same') ;               %Blurrs the image to prevent peak finding noise
sim = size(d);
[y,x] = find(d(edg:sim(1)-edg,edg:sim(2)-edg));     %Forms an array of all coordinates to search
Point = zeros([100, 3]);                            %Array to recieve peak values and locations
Point(1,1:2) = 201;                                 %picks out the DC peak

j = 2;                                              %2 because DC peak is already found
x = x+edg-1;                                        %avoiding edges
y = y+edg-1;

for i = 1:length(x)                                 %Time to find peaks, obsolete methods commented
    if abs(x(i)-200) <= 5 && abs(y(i)-200) <= 5 
        continue;                                   %Avoiding DC again
    elseif d(y(i),x(i)) == max(max(d(y(i)-3:y(i)-1,x(i)-3:x(i)+3))) || d(y(i),x(i)) == max(d(y(i),x(i)-3:x(i)-1)) %Avoiding finding double peaks
        continue;
    elseif (d(y(i),x(i))>=21000) && (d(y(i),x(i))) == max(max(d(y(i)-7:y(i)+7,x(i)-7:x(i)+7))) %Peak definition ***IMPORTANT***
        Point(j,1:3) = [x(i),y(i),0];
        j=j+1;
    end
end

for i = 1:100                               %Finding the intensity of the peaks starts here
    if Point(i,1) == 0                      %This bit stops this section when no more points are recorded
        Waypoint = Point(1:i-1,:);          %New array to keep it tidy
        break;
    end
    Intensity = 0;
    Peak = max(max(abs(ftrans(Point(i,2)+395:Point(i,2)+405,Point(i,1)+595:Point(i,1)+605))));%Searches for peak within 10 square pixels
    for l = 1:10
        for m = 1:10
            if abs(ftrans(Point(i,2)+395+m,Point(i,1)+595+l)) > Peak*(1/(2.718)^2)         %Definition of pixel to be included in intensity calc
            Intensity = Intensity+(abs(ftrans(Point(i,2)+395+m,Point(i,1)+595+l)))^2;
            end
        end
    end
    Point(i,3) = Intensity/(10^15);
    if i == 100
        Waypoint = Point(1:i-1,:);
    end
end
%Waypoint

DC = max(Waypoint(1,3))            %define DC peak value and find fringe pattern peak value

Scan=0;
for i=2:length(Waypoint)
    if Waypoint(i,3) >= Scan && ((Waypoint(i,1)-201)^2+(Waypoint(i,2)-201)^2) <= 1225
        %OR Waypoint(i,3) >= Scan && Waypoint(i,2) >= 195 && Waypoint(i,2) <= 205 && Waypoint(i,1) >= 
        Scan = 4*Waypoint(i,3);
    end
end
Scan/4
%if max(Waypoint(1:ceil((length(Waypoint(:,3))/2)-1),3)) >= max(Waypoint(ceil((length(Waypoint(:,3))/2)):length(Waypoint),3))%If the max val in first half(excluding middle) is greater
%    PAT = 4*max(Waypoint(ceil(length(Waypoint(:,3))/2):length(Waypoint),3));%Take it
%else
%    PAT = 4*max(Waypoint(1:ceil((length(Waypoint(:,3))/2)-1),3));%if it wasnt greater, take the max of the second half
%end
Fou = Scan/DC                       %Normalised value is calculated

for i=120:200
   ftdisp(375:380,i) = 255;         %Scale bars in 20 / 100 um^-1
end
for j=200:260
    ftdisp(j,20:25) = 255;
end

text(760,800, '20 (100µm)-1', 'HorizontalAlignment','center','Color','w','FontWeight','bold','FontSize',12)
set(2, 'Position',[scrsz(3)/2 scrsz(4)*2/5 scrsz(3)/2 scrsz(4)/2]);

hold on
plot(Waypoint(:,1),Waypoint(:,2),'*r');     %display peaks
hold off

line = zeros(1,length(img(1,:)));           %Binning fit method begins here
for i=1:length(img(1,:))
line(i) = sum(img(:,i))/(length(img(:,1))); %line is a vector containing the average of each row of pixels
end
[xData, yData] = prepareCurveData( [], line );%prepare the data for the fit
ft = fittype( 'a0+a1*sin(x*b1+c1)^2' );
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.Display = 'Off';
opts.Lower = [0 5 0 0];
opts.StartPoint = [30 200 guess 10];
[fitresult, gof] = fit( xData, yData, ft, opts );%do tha fit

Vis = fitresult.a1/(fitresult.a0+fitresult.a1)%calculation of visibility from fit coefficients

figure(3),
set(3, 'Position', [1 10 scrsz(3)/2 scrsz(4)/2], 'Name', 'Sine Squared Fit');%display the fit
axes1 = axes('Parent',3,'GridLineStyle','none','FontSize',14);
xlim(axes1,[0 1600]);
box(axes1,'on');
grid(axes1,'off');
hold(axes1,'on');
h = plot( fitresult, xData, yData, '--*b');
ylim(axes1,[0 65]);
legend( h, 'Original Data', 'a0+a1*sin^2(x*b1+c1)', 'Location', 'NorthEast' );
ylabel( 'Avg. Intensity' );
grid on

if exist('filename', 'var') == 1
Names = 'Visibility   %f\r\nFourier   %f\r\na0   %f\r\na1   %f\r\nb1   %f\r\nc1   %f\r\n';%the rest simply saves the data how I like
Peaks = 'Peak x coord   y coord   Intensity\r\n';
for i=1:length(Waypoint)
    Peaks = strcat(Peaks, '%f   %f   %f\r\n');
end
Data = [Vis, Fou, fitresult.a0, fitresult.a1, fitresult.b1, fitresult.c1];
%Coords = Coords.';Transposes Coords

Wpt = Waypoint.';

FID = fopen(strcat('C:\Matlab\Data\050117\data_', filename, '.txt'), 'w');
fprintf(FID, Names, Data);
fprintf(FID, Peaks, Wpt);
fclose(FID);

imwrite(img,strcat('C:\Matlab\Data\archive\050117\Origin_', filename,'.jpg'),'jpg')
save(strcat('C:\Matlab\Data\archive\050117\BaseFT_', filename,'.txt'),'ftrans','-ascii')
imwrite(imgscb,strcat('C:\Matlab\Data\050117\Img_', filename,'.jpg'),'jpg')
imwrite(ftdisp,strcat('C:\Matlab\Data\050117\FT_', filename,'.jpg'),'jpg')
print('-f3',strcat('C:\Matlab\Data\050117\Fit_', filename),'-djpeg','-r0')
else
end