function sig = Guass_Fit(sig) %return sigma
% Emit_Calc.m
% read one image from files
% fits a gaussian funtion on the projection, get the rms values.
% then pass them to fit parabola
%
% Dec-2010
% Sadiq Setiniyaz

% now we do the action......................................
disp('Read image ...')
% get image
for scan=1:6
    switch scan
        case 1
            addpath(genpath('C:\work\Get_Emittance\Scan1\'));
        case 2
            addpath(genpath('C:\work\Get_Emittance\Scan2\'));
        case 3
            addpath(genpath('C:\work\Get_Emittance\Scan3\'));
        case 4
            addpath(genpath('C:\work\Get_Emittance\Scan4\'));
        case 5
            addpath(genpath('C:\work\Get_Emittance\Scan5\'));
        case 6
            addpath(genpath('C:\work\Get_Emittance\Scan6\'));
    end
    for ii = 1:41;
        imNo = ii;
        switch ii
            case 1
                im = imread('1.png'); % reading 1.png
                tifname='1';
            case 2
                im = imread('2.png'); % reading 1.png
                tifname='2';
            case 3
                im = imread('3.png');
                tifname='3';
            case 4
                im = imread('4.png');
                tifname='4';
            case 5
                im = imread('5.png');
                tifname='5';
            case 6
                im = imread('6.png');
                tifname='6';
            case 7
                im = imread('7.png');
                tifname='7';
            case 8
                im = imread('8.png');
                tifname='8';
            case 9
                im = imread('9.png');
                tifname='9';
            case 10
                im = imread('10.png');
                tifname='10';
            case 11
                im = imread('11.png');
                tifname='11';
            case 12
                im = imread('12.png'); % reading 1.png
                tifname='12';
            case 13
                im = imread('13.png');
                tifname='13';
            case 14
                im = imread('14.png');
                tifname='14';
            case 15
                im = imread('15.png');
                tifname='15';
            case 16
                im = imread('16.png');
                tifname='16';
            case 17
                im = imread('17.png');
                tifname='17';
            case 18
                im = imread('18.png');
                tifname='18';
            case 19
                im = imread('19.png');
                tifname='19';
            case 20
                im = imread('20.png');
                tifname='20';
            case 21
                im = imread('21.png');
                tifname='21';
            case 22
                im = imread('22.png'); % reading 1.png
                tifname='22';
            case 23
                im = imread('23.png');
                tifname='23';
            case 24
                im = imread('24.png');
                tifname='24';
            case 25
                im = imread('25.png');
                tifname='25';
            case 26
                im = imread('26.png');
                tifname='26';
            case 27
                im = imread('27.png');
                tifname='27';
            case 28
                im = imread('28.png');
                tifname='28';
            case 29
                im = imread('29.png');
                tifname='29';
            case 30
                im = imread('30.png');
                tifname='30';
            case 31
                im = imread('31.png');
                tifname='31';
            case 32
                im = imread('32.png'); % reading 1.png
                tifname='32';
            case 33
                im = imread('33.png');
                tifname='33';
            case 34
                im = imread('34.png');
                tifname='34';
            case 35
                im = imread('35.png');
                tifname='35';
            case 36
                im = imread('36.png');
                tifname='36';
            case 37
                im = imread('37.png');
                tifname='37';
            case 38
                im = imread('38.png');
                tifname='38';
            case 39
                im = imread('39.png');
                tifname='39';
            case 40
                im = imread('40.png');
                tifname='40';
            case 41
                im = imread('41.png');
                tifname='41';
        end

        if isempty(im)
            warndlg('Could not grab the image. Check the image server.')
            return
        end
        imd = double(im(:,:,1));

        imd=255*imd; % rescale

        %imt=imd'; % transpose to orient it correctly
        imt=imd;
        % determine image size in pixels
        dim=size(imt);
        %dim=size(imd);
        dim_x = dim(1);
        dim_y = dim(2);

        %pic = imt - imbgt;
        pic = imt;

        %enter calibration here:
        calibration_y=0.000169*0.54344345; %m/px
        calibration_x=0.000169*0.54344345; %m/px

        xunit='m';
        yunit='m';

        % create scaling vectors
        x=[0:0.00001:calibration_x*dim_x];%how to do the binning
        y=[0:0.00001:calibration_y*dim_y];%how to do the binning

        % profiles
        profx = sum(pic,1);%how to make projection
        profy = sum(pic,2)';%how to make projection

        xbins=size(profx);
        ybins=size(profy);
        x=(1:1:xbins(2));
        y=(1:1:ybins(2));

        % gauss fit with narrowed range
        xl = 1;
        xr = 656;
        yl = 1;
        yr = 506;

        gau_x = gaussfit(x(xl:xr),profx(xl:xr));%gaussion fitting in x
        gau_y = gaussfit(y(yl:yr),profy(yl:yr));%gaussion fitting in y

        % unpack fit parameters
        % include calibration pix-> mm
        gaux_sigma = gau_x(1)*calibration_x;%How to get rms of the gaussion fit.
        gaux_amplitude = gau_x(2);
        gaux_center    = gau_x(3)*calibration_x;
        %
        gauy_sigma = gau_y(1)*calibration_y;%How to get rms of the gaussion fit.
        gauy_amplitude = gau_y(2);
        gauy_center    = gau_y(3)*calibration_y;

        sigx(scan,ii)=gaux_sigma;
        sigy(scan,ii)=gauy_sigma;
        sig_index(scan,ii) = ii; %store scan number
        

        thisfilename=tifname;
        % write summary
        % string = [thisfilename,' ',...
        %    num2str(gaux_sigma,'%12.4f'),' ', ...
        %    num2str(gaux_amplitude,'%12.4f'),' ', ...
        %    num2str(gaux_center,'%12.4f'),' ', ...
        %    num2str(gauy_sigma,'%12.4f'),' ', ...
        %    num2str(gauy_amplitude,'%12.4f'),' ', ...
        %    num2str(gauy_center,'%12.4f'),' ', ...
        %    ];
        % disp(string);
        
        %Plot_Beam_Spot(x,y,pic);
        %Plot_Gauss_Fit(x,y,profx,profy,gau_x,gau_y,gaux_sigma,gauy_sigma,xunit,yunit,gaux_center,gauy_center,thisfilename);      
    
    end
end
        % check rms x, y, and indexes.
        %sigx
        %sigy 
        %sig_index 
        
        % plot beam spots and Gaussian fits 
      
        
        for ii = 1:41
        mean_sigx(ii) = mean(sigx(:,ii));
        mean_sigy(ii) = mean(sigy(:,ii));
        er_sigx(ii) = std(sigx(:,ii));
        er_sigy(ii) = std(sigy(:,ii));
        end
        
        %mean_sigx
        %er_sigx
        %mean_sigy
        %er_sigy
        
       Emit_Parabola_Fit_kl_XProjection(mean_sigx,er_sigx);
       Emit_Parabola_Fit_kl_YProjection(mean_sigy,er_sigy);        
      
return