Fitting data from file

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Piotr
Piotr on 27 Sep 2022
Commented: Rik on 30 Sep 2022
Hello,
I am trying to fit data from a file. For that I have created data with simply a sine wave function. Here is my code:
load test_fit
Error using load
Unable to find file or directory 'test_fit.txt'.
x = test_fit(:,1);
y = test_fit(:,2);
fo=fit(y,x,'a*sin(b*x+c)+d');
plot(fo,y,x)
But the results I got are clearly not good:
I'm just wondering if I should specify somwhere the number of itterations or the fitting constrains?
Thank you in advance for any help or comments!

Accepted Answer

Rik
Rik on 27 Sep 2022
Edited: Rik on 27 Sep 2022
You can specify those parameters, but what is much more effective is providing good initial guesses (and not mixing up x and y):
test_fit=load(websave('test_fit.txt','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1137860/test_fit.txt'));
x = test_fit(:,1);
y = test_fit(:,2);
plot(x,y,'*')
fo=fit(x,y,'a*sin(b*x+c)+d','StartPoint',[1 4 0 2])
fo =
General model: fo(x) = a*sin(b*x+c)+d Coefficients (with 95% confidence bounds): a = 1 (1, 1) b = 4 (4, 4) c = 0.3927 (0.3927, 0.3927) d = 2 (2, 2)
hold on,plot(fo)
  10 Comments
Rik
Rik on 30 Sep 2022
If you look at the code below, you see that c starts with a NaN. So we should remove it.
I = imread(websave('testf5.png','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1139785/testf5.png'));
x = [size(I,2)/2 size(I,2)/2];
y = [0 size(I,1)];
c = improfile(I,x,y);
c = c(:,1,1); % select red chanel
x_adapted = linspace(y(1),y(2),numel(c));
x_adapted = x_adapted.'; % transpose 1x1491 to 1491x1
subplot(2,1,1)
imshow(I)
hold on
plot(x,y,'-o')
hold off
subplot(2,1,2)
plot(x_adapted,c)
ft = fittype('m*sin(n*x+o)+p');
options=fitoptions(ft);
options.StartPoint = [125 100 0 125];
options.Weights = [1,1];
find(isnan(x_adapted)),find(isnan(c))
ans = 0×1 empty double column vector
ans = 1
Here is the problem, so we'll have to remove that point.
L = isnan(x_adapted) | isnan(c); % the first part is just good habit
x_adapted(L) = [];
c(L) = [];
% Now we can safely to the fit:
fo=fit(x_adapted,c,ft,StartPoint=[125 100 0 125])
fo =
General model: fo(x) = m*sin(n*x+o)+p Coefficients (with 95% confidence bounds): m = 0.15 (-6.376, 6.676) n = 100 (99.9, 100.1) o = -0.001634 (-87.15, 87.15) p = 129.3 (124.6, 133.9)
figure,plot(fo)
So the fit is not great, you will have to adjust the start point.
Rik
Rik on 30 Sep 2022
If my answer helped you, please consider marking it as accepted answer.

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