In matlab, I have a matrix and index vector v (in real problem, v vector is very long)
A = [1,2,3;4,5,6;7,8,9]; % 3-by-3 matrix
v = [1,2,3,2,3,3,1]
How can I generate a matrix like
[A(1,:);A(2,:);A(3,:);A(2,:);A(3,:);A(3,:);A(1,:)]
without using loop or write out everything explicitly?
You can use vectors to index, A([1,1,1]) would give you three times the first element.
A(v,:)
Related
I have a m * n * k Matrix called M which I want to index to get the mean of some Data.
I have a logical m * n matrix called EZG and want to apply this on every of the k-th dimension from 1:(end-1) (call this vector V).
Any chance to write it without a loop like this:
M=rand(3,3,3)
EZG=logical([1,1,1;0,1,0;0,0,1])
V=1:size(M,3)-1
mean(mean(M(EZG,V)1),2)
Result should be a onedimensional vector of the length of V.
Thank you
I think this is what you want:
M=rand(3,3,3);
EZG=logical([1,1,1;0,1,0;0,0,1]);
% repeat EZG K-1 times, and add zeros to the Kth slice
V=cat(3,repmat(EZG,1,1,size(M,3)-1),false(size(M,1),size(M,2)));
% logical index and mean
m=mean(M(V));
I'm trying to compute a vector A for which the ith element is the sum of the first i elements of a different vector B (this vector is given).
I couldn't work out how to do this and the internet wasn't much help either.
I am very new to matlab so an easy solution would be preferred :)
Use MATLAB's cumsum function.
code example:
%generates random vector b
b = rand(5,1);
%calculates accomulative sum
a = cumsum(b);
Result:
b = [0.4319 0.9616 0.5671 0.8731 0.5730]
a = [0.4319 1.3935 1.9606 2.8338 3.4068]
I have an njxnj matrix made up of nxn matrices. I want to extract the diagonal j blocks of nxn matrices. i.e. I want to extract the diagonal (for n = 2, j = 4):
What would be the most efficient way of doing this?
To index the elements you can use blkdiag to create a corresponding mask.
%your parameters
n=2
j=4
%some example matrix
M=magic(n*j);
%create the input for blkdiag, j matrices of size n
h=repmat({true(n)},j,1)
%use blkdiag to select the elements
M(logical(blkdiag(h{:})))
For large j, this answer of #Daniel becomes slow. I would instead recommend using linear indices of block diagonal.
n=2;
j=4;
%some example matrix
M=magic(n*j);
linIndices = (0:n*((n*j)+1):n*((n*j)+1)*(j-1))+reshape((1:n)'+n*j*(0:n-1),[],1);
newM = reshape(M(linIndices),n,n,[]);
I have a vector created from linspace between specific numbers and have dimensions of 1*150. Now i want to multiply each element of the above created vector with another vector whose dimension is 1*25. The detail of my code is given below
c_p = linspace(1,.3*pi,150);
c = c_p';
C = zeros([150,25]);
for i= 1:1:size(C,1)
wp= c(i);
for n= 1:25
c_wp(n) = cos(n*wp);
end
C(i,25)= c_wp;
end
The vector is actually a multiple of cosine of length 25 and here wp is the elements of first vector of dimension 1*150. SO by the logic, I must have an output of 150*25 but instead giving me "subscripted assignment dimension mismatch". Any help would be appreciated, as i am new to matlab.
To multiply each element of a row vector a with each element of another row vector b, we can use linear algebra. We transpose a to make it a column vector and then use matrix multiplication:
a.' * b
That way you don't even need a for loop.
Suppose I have a 9x9 matrix A that that consists of integers. I have another matrix IDX that's 2500x4 and consists of the same integers in A. I want to find the indices of all the values in IDX in the matrix A.
Here's what I have:
for ii=1:length(IDX)
Mat_idx=ismember(A,IDX(ii,:));
[StatIdxX StatIdxY] = find(Mat_idx);
end
Now for each ii the StatIdxX and StatIdxY are the row and col indices of IDX in the matrix A. This is slow, and the culprit is ismember
Any thoughts on speeding this up?
Thanks.
first flatten A with A=A(:), that will make a single linear index instead of row,col.
Then just use logical indexing. For example:
B=zeros(size(IDX));
for n=1:numel(A)
B(IDX==A(n))=n;
end