How to fit curve using for loop?

조회 수: 19(최근 30일)
Ass
Ass 2021년 10월 4일
댓글: Mathieu NOE 2021년 10월 25일
I have a 15 number of signals with data point 64 in each. I want to use loop to fit all the signals with fittype 'gauss2' and plot all the curves with thier fitting. I have written like this but it is showing eroor. Kindly suggest me to resolve this. Thank you.
figure;
for i1=1:64
for j1=1:15
recon1_f(j1)=fit(t(i1),recon_amp2_1(:,j1),'gauss2');
h2{i}=plot(recon1_f(j1),t,recon_amp2_1(:,j1));
ylim([0 0.05]);
end
end
  댓글 수: 1
Mathieu NOE
Mathieu NOE 2021년 10월 4일
hi
maybe you should share some data so we can test the code
tx

댓글을 달려면 로그인하십시오.

채택된 답변

Mathieu NOE
Mathieu NOE 2021년 10월 4일
hello again
in the mean time I created this example (only 5 loops) on dummy data
you can easily expand and adapt it to your own needs
NB you only need one for loop and not two as in your code
hope it helps
clearvars
clc
% dummy data
x1 = [0:1:20];
y1 = [0,0.004,0.008,0.024,0.054,0.112,0.33,0.508,0.712,0.926,1,0.874,0.602,0.404,0.252,0.146,0.074,0.036,0.018,0.004,0];
for ci = 1:5
% modify x and y range (dummy data generation)
x = x1*ci;
y = y1*ci^2 + 0.1*rand(size(y1));
% curve fit using fminsearch
f = @(a,b,c,x) a.*exp(-(x-b).^2 / c.^2);
obj_fun = @(params) norm(f(params(1), params(2), params(3),x)-y);
sol = fminsearch(obj_fun, [max(y),max(x)/2,max(x)/6]);
a_sol = sol(1);
b_sol = sol(2);
c_sol = sol(3);
xx = linspace(min(x),max(x),300);
y_fit = f(a_sol, b_sol,c_sol, xx);
yy = interp1(x,y, xx);
Rsquared = my_Rsquared_coeff(yy,y_fit); % correlation coefficient
figure(ci)
plot(xx, y_fit, '-',x,y, 'r .', 'MarkerSize', 40)
title(['Gaussian Fit / R² = ' num2str(Rsquared) ], 'FontSize', 15)
ylabel('Intensity (arb. unit)', 'FontSize', 14)
xlabel('x(nm)', 'FontSize', 14)
eqn = " y = "+a_sol+ " * exp(-(x - " +b_sol+")² / (" +c_sol+ ")²";
legend(eqn)
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Rsquared = my_Rsquared_coeff(data,data_fit)
% R2 correlation coefficient computation
% The total sum of squares
sum_of_squares = sum((data-mean(data)).^2);
% The sum of squares of residuals, also called the residual sum of squares:
sum_of_squares_of_residuals = sum((data-data_fit).^2);
% definition of the coefficient of correlation is
Rsquared = 1 - sum_of_squares_of_residuals/sum_of_squares;
end
  댓글 수: 20
Mathieu NOE
Mathieu NOE 2021년 10월 25일
hello
seems to me the index i1 is not usedin the line
c(i,:,i2)=(data(p(i),:));
so It should be
c(i,i1,i2)=(data(p(i),:));

댓글을 달려면 로그인하십시오.

추가 답변(0개)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by