I have a question regarding Matlab Plotting.
After interpolating I get matrix of 101*101 order which I have plot with scalar value Distance.
101*101 is a scatter plot.
I have attached the script and .mat file with this email.
How is it possible to get a single line which will fit this scatter plot.
I have tried with a polyval function but its not working for many columns.
Can any one please help me in this matter. I will wait for your reply.
Regards
Zuhaib
scatter( repmat( Distance, [size(Displacement,2) 1] ), Displacement(:), '.r' )
lsline
%or
plot(Distance,Displacement,'.r');
stats = regstats( Displacement(:), repmat(Distance, [size(Displacement,2) 1]) );
refline( stats.beta(2), stats.beta(1) )
Hi,
I tried to deal with your problem. Maybe you be able to understand the modified code. If you have a question, just let me know or you can refer to the MATLAB help.
Good luck.
Dear Sir Stephen Politzer Ahles
Here I am getting only a single line. Is it possible I can fit a curve line in this scatter plot?
As you can see in the picture.
I have 101 *102 in which first column represents x axis and other 101 columns as y axis scatter data points.
Waiting for your reply.
Your question did not specify that you wanted a curved line, so I didn't make one. If you look at either my code or Se-Hyeon's, though, it is very easy to adapt it to make a curved line. Notice that both Se-Hyeon's example and mine involve regressing Displacement on Distance and then using the regression coefficients to plot a line; the reason the line is straight is because both of us only included those two variables and did not include polynomial terms. So all you need to do is add polynomial terms to the regression to make a curved regression line instead of a straight one. Here's some code that will do it, but I suggest you also work through this on your own to make sure you understand how it works.
figure
plot(Distance,Displacement,'.r');
% create a matrix for regression: X1 is Displacement, X2 is Displacement^2,
% X3 is Displacement^4
X = repmat(Distance, [size(Displacement,2) 3]);
X(:,2) = X(:,2).^2;
X(:,3) = X(:,3).^3;
% regression with quadratic and cubic terms
stats = regstats( Displacement(:), X );
% Plot the regression line
x = (min(Distance)-10):.1:(max(Distance)+10);
hold on; plot( x, stats.beta(1) + x.*stats.beta(2) + (x.^2).*stats.beta(3) + (x.^3).*stats.beta(4), 'k-' )
set(gca, 'XLim', [min(Distance) max(Distance)] )
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