The complex numbers are compared first by magnitude, then by phase angle (if there is a tie for the maximum magnitude.) From help max: When X is complex, the maximum is computed using the magnitude MAX(ABS(X)). In the case of equal magnitude elements, then the phase angle MAX(ANGLE(X)) is used. NaN’s are ignored when computing … Read more
To work with elements in a cell array, use curly braces {} to retrieve the data stored at each cell index, as in the following loop: for i = 1:74 str = m{i}; % do something with string end 0 solved How to work with strings in a loop – MatLab [closed]
you can use ordfilt2 . For example, if your “ring” is just defined by: ring= fspecial(‘gaussian’,21,1) ring = ring>eps & ring<1e-9 then: order=sum(ring(:))/2; B = ordfilt2(A,order,ring); replaces each element in A by the order-th element in the sorted set of neighbors specified by the nonzero elements in the ring domain. Here I chose ‘order’ to … Read more
Quick answer (because you finally explained a workable example input=>desired output) before closing the question. x = [1 2 3 ; 4 5 6 ; 7 8 9] ; T = size(x,1) ; N = size(x,2) ; R = [x,x(:,1)] ; % copy the first column in last position (to be able to loop seamlessly) … Read more
There are several ways to do this, but maybe a good way is to store the image (after applying a filter) in the figure’s application data. You can do this with guidata. After each filter you store the image; % — Executes on button press in black. function black_Callback(hObject, eventdata, handles) % hObject handle to … Read more
There are many ways to do this. Most clean way would be setting ROI (Region of Interest) and then applying matrix operations. Something like: subtract(x(Rect(1,0,NumCols-1,NumRows)),x(Rect(0,0,NumCols-1,NumRows),R) singleLineMask = Mat(1,NumCols,CV_8U) for (int i=1;i<NumCols;i++) singleLineMask.at<int>(1,i)=1; repeat(singleLineMask,NumRows,1,MaskImage) d=mean(R,MaskImage) a=(8*mean(abs(R))-d)/7 assuming you create R and compute NumRows,NumCols prior to this operation and allocate MaskImage. 4 solved conversion of matlab code … Read more
Assuming original data is in matrix A: indx=unique(A(:,1)); for ii=1:numel(indx) RowMean(ii,:)=mean(A(1,:)==indx(ii),:); end 2 solved Calculate the mean of set of rows in a matrix [duplicate]
If I understand correctly, you can generate all permutations of column indices with perms, and use the result to index into the matrix: M = magic(3); % // example matrix pp = perms(1:size(M,2)); % // each row is a permutation for p = pp.’ %’// “for” loops over columns, so transpose pp permuted_M = M(:,p); … Read more
How about: N = 100; B = rand(N, N); A = B / norm(B); % substitute norm of your choice 0 solved How to loop vectors when using matlab?
I don’t even know how that code could even run. x is not defined anywhere and you suddenly are starting to use it in your for loop at the beginning. My guess is that you have some code defined somewhere earlier on, those iterations start happening and then once those iterations end, this function runs. … Read more
This solution below should do the trick (at least it does for the simplified version you put above. fi = fopen(‘myFile.txt’,’r’); fileCount = 1; fo = fopen([‘output’,num2str(fileCount),’.txt’],’w’); header = fgets(fi); fprintf(fo,header); tline = header; first = true; mark_index = 8; while ischar(tline) if (~first) values = cell2mat(textscan(tline,’%f ‘)); if values(mark_index) == 1 fclose(fo); fileCount = … Read more
I am not really sure that I got all of your requirements but this might be the script you are searching for: N = 10; % count of numbers p = 0.2; % switching probability a = 5; b = 20; % init empty numbers and get the first random number numbers = zeros(N,1); numbers(1) … Read more
You can pass a vector as the first input to plot and a matrix (with a dimension which matches the size of the first vector) as the second input and it will create a plot for each pairing of the first vector and each row/column of the second input. plot(X, Y, ‘o’) This will automatically … Read more
The MClust package contains the function densityMclust which produces an object that contains parameter estimates for the fitted Gaussian mixture model along with the density itself. From the MClust manual: > densWaiting <- densityMclust(faithful$waiting) > summary(densWaiting, parameters = TRUE) ——————————————————- Density estimation via Gaussian finite mixture modeling ——————————————————- Mclust E (univariate, equal variance) model with … Read more
Ok, I have the solution. I can find the rank through this command: [A_sorted, rank] = sort(A, ‘descend’); for k=1:10 rank = find(A_sorted == A(k)); end solved Find ranking in matrix in descending order [duplicate]