Manipulate elements in a matrix based on a mathematical condition using logical indexing
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I am having trouble figuring out how to manipulate and reduce a matrix based on a mathematical condition.
Let's say I have a 26x500 matrix named A. After a certain number of columns, a lot of the values in A can be considered redundant, as the value for each row in that column becomes very similar, if not identical, to the value in the first row of that column. Therefore, I would like to implement a conditional statement that basically says if the difference between the value in the last row and the first row is <0.01, to replace all the rows in that column to the value in the first row. Something like this:
A = zeros(26,500); % zeros() just used for illustration
condition = ( A(26,:) - A(1,:) ) < 0.01;
A(:,condition) = A(1,:);
However, the problem that I am running into is when manipulating the original matrix with the condition, the first x amount of columns gets removed due to the false return from the logical array created by the condition and the last statement does not run. I know that when manipulating an array on conditions a statement in the form of
A(A<5) = 23;
A(A>10) = 0;
A(isnan(A)) = 0;
% etc.
However I cannot see how I can implement this form due to the mathematical expression indicating the condition. I also understand that I could create a new matrix from the result of the condition, or use a for loop to iterate through each row and replace the values manually based on what the condition found, but I was more interested in using the logical indexing approach to manipulate the original matrix to be used in later applications.
Can someone shed some light on possible methods and solutions?
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Voss
le 18 Fév 2024
Sounds like what you're going for is:
condition = abs( A(end,:) - A(1,:) ) < 0.01;
A(:,condition) = A(ones(end,1),condition);
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VBBV
le 18 Fév 2024
A = rand(26,500) % zeros() just used for illustration
condition = ( A(26,:) - A(1,:) ) < 0.01;
A(:,condition) = A(1);
A
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