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Ho to find the interception

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Navaneeth Tejasvi Mysore Nagendra
Navaneeth Tejasvi Mysore Nagendra el 23 de Jun. de 2022
Comentada: Star Strider el 23 de Jun. de 2022
I have a fitted Guassian plot to which I have plotted yline. Now I am interested to extrac two x- interception points through which my line is passing. I am not able to find any easy way to do it. so any help is appreciable.
code:
clc;close all;clear;
resultsdir = 'results';
Row = dir('cross_section_*.mat');
%Coefficients (with 95% confidence bounds):
a1 = 394.5 ;
b1 = 985.1 ;
c1 = 114.8 ;
a2 = 511.4 ;
b2 = 878.5 ;
c2 = 231.2 ;
a3 = -529.8 ;
b3 = 989.8 ;
c3 = 133.6 ;
xData = zeros(1,1640);
yData = zeros(1,1640);
color = ['r','g','b']
for X = 1:9
Filename = Row(X).name;
dest = fullfile(resultsdir, Filename);
Filedata(X) = load(Filename);
figure()
plot(Filedata(X).x)
[xData, yData] = prepareCurveData( [], Filedata(X).x);
ft = fittype( 'gauss3' );
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.Display = 'Off';
opts.Lower = [-Inf -Inf 0 -Inf -Inf 0 -Inf -Inf 0];
opts.StartPoint = [446.913 842 37.5821195501848 401.619376603545 761 47.8742720232778 393.885950193204 926 55.7197242033307];
[fitresult, gof] = fit( xData, yData, ft, opts );
figure()
h = plot( fitresult,'k', xData, yData);
set(h,'LineWidth', 2)
title(sprintf('Name:%s , R-Square = %0.4f',Filename,gof.rsquare))
legend( h, 'Experiment', 'fit ', 'Location', 'NorthEast', 'Interpreter', 'none' );
% Label axes
ylabel('Intensity values')
xlabel( 'Along X of the CMOS', 'Interpreter', 'none' );
grid on
f = fitresult.a1*exp(-((xData-fitresult.b1)/fitresult.c1).^2) + fitresult.a2*exp(-((xData-fitresult.b2)/fitresult.c2).^2) + fitresult.a3*exp(-((xData-fitresult.b3)/fitresult.c3).^2);
Max(X) = max(f)
exp_perc(X) = Max(X)/exp(2);
yline(exp_perc(X))
% Max(X) = max(fitresult.val)
% f = a1*exp(-((Filedata(X)-b1)/c1).^2) + a2*exp(-((Filedata(X)-b2)/c2).^2) + a3*exp(-((Filedata(X)-b3)/c3).^2);
end
plot:

Respuesta aceptada

Star Strider
Star Strider el 23 de Jun. de 2022
If you simply want to do it yourself, try something like this —
xData = 1:150;
yData = 50*exp(-(xData-75).^2 * 0.01) + randn(1,150);
ft = fittype( 'gauss3' );
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
[fitresult, gof] = fit( xData(:), yData(:), ft, opts );
h = plot( fitresult,'k', xData, yData);
ylineval = 10; % This Needs To Be Stated Separately From The 'yline' Call
yline(ylineval, 'DisplayName','yline');
hold on
xfit = h(2).XData; % Get Fitted Curve Data
yfit = h(2).YData; % Get Fitted Curve Data
ixv = find(diff(sign(yfit-ylineval))); % Calculate The Approximate Intersection Indicess
for k = 1:numel(ixv)
idxrng = max(1,ixv(k)-1) : min(numel(xfit),ixv(k)+1);
xv(k) = interp1(yfit(idxrng), xfit(idxrng), ylineval); % Interpolate 'Exact' Values
yv(k) = interp1(xfit(idxrng), yfit(idxrng), xv(k));
end
% xv
% yv
plot(xv, yv, 'sr','MarkerSize',10, 'DisplayName','Intersections')
text(10,40,sprintf('Intersections:\nX = %.3f\nX = %.3f',xv))
hold off
.
  2 comentarios
Navaneeth Tejasvi Mysore Nagendra
Navaneeth Tejasvi Mysore Nagendra el 23 de Jun. de 2022
Thank you, this is extremely helpful
Star Strider
Star Strider el 23 de Jun. de 2022
As always, my pleasure!

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Más respuestas (1)

KSSV
KSSV el 23 de Jun. de 2022
  1 comentario
Navaneeth Tejasvi Mysore Nagendra
Navaneeth Tejasvi Mysore Nagendra el 23 de Jun. de 2022
Thank you for the suggestion, I will take a look

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