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Storing data for "for loop"

Asked by Khang Nguyen on 21 May 2019
Latest activity Commented on by Star Strider
on 21 May 2019
Hi everyone,
for my L0 = [1 2 3 4 5], L10 = [2 3 4 5 6] L20 = [0 9 2 3 4] .... L200 = [2 3 4 5 6] (Up to 20 L values, just type random L for asking)
and x = [0:1:4]
I want to perform a polyfit function for 6th polynomial order for each L, with same x, but i do not want to each time type "polyfit(x,L0,6)" and then "polyfit(x,L20,6)
My question is : How can I make a for loop for this
I have tried L = [L0 L10 L20 ... L200],
but this way, it will store all values in one vector.
Please help ASAP !!
Thanks in advance

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3 Answers

Answer by Star Strider
on 21 May 2019
 Accepted Answer

Try something like this:
L0 = [1 2 3 4 5];
L10 = [2 3 4 5 6];
L20 = [0 9 2 3 4];
L = [L0; L10; L20];
x = 0:4;
n = size(L,2)-2;
for k = 1:size(L,1)
p(k,:) = polyfit(x,L(k,:),n);
end
This creates a matrix of row vectors in ‘L’. Note that I set ‘n’ to be 2 less than the vector lengths. A 6-order polynomial might be appropriate for your actual data, although it will crash here. (Please re-consider fitting a 6-order polynomial anyway.)

  2 Comments

Thanks you so much. It works :)).
As always, my pleasure!

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Answer by Josh
on 21 May 2019

You can store your L variables either as rows in a matrix:
% Create L matrix with a different L value in each row (I only put in three rows for simplicity)
L = [1, 2, 3, 4, 5; 2, 3, 4, 5, 6; 0, 9, 2, 3, 4];
% Create x value
x = 0:4;
% Create a result matrix; this will store the output of polyfit as separate rows:
order = 6;
results = zeros(size(L, 1), order + 1);
% Calculate the results
for i = 1 : size(L, 1)
results(i, :) = polyfit(x, L(i, :), order);
end
% The syntax L(i, :) returns the entire ith row of the matrix

  1 Comment

I have tried your code, and it's only assign the value of the last L to the result matrices

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Answer by Geoff Hayes
on 21 May 2019

Khang - don't create variables just for the sake of having variables. If all of your L arrays are of the same dimension, then just store them in a (for example) 20x5 matrix where each row corresponds to one of your (no longer needed) L variables. You would then iterate over each row and call polyfit on that row. For example,
for k=1:size(myData,1)
[p,S,mu] = polyfit(x,myData(k,:),6);
% store the results in an appropriately sized output matrix
end
where myData is your 20x5 array. If not all L arrays are of the same dimension, then just store all in a cell array.

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