I have two matrices X (122 x 125973) and Y (1 x 125973). I want to split in the same way X and Y into smaller matrices and vectors of 122 x 1024 (column division) in Matlab.
I have tried several methods (mat2cell, loops, etc), but I think I am missing the syntax. Any help ?
Note: 125973 can't be divided by 1024, so the last matrix (and vector) will the have the size of (122 x 21) (and (1 x 21) respectively). Thank you for your help!
Since your sub-matrices do not have equal size, you cannot put them in a 3D array (without NaN or zero padding). So you can use a cell. To do this with mat2cell you have to specify how many rows of the original matrix should be put in each individual entry of the cell:
X = rand(122,125973);
Y = rand(1,125973);
% your number of rows per 'block'
n = 1024;
% the number of cols per cell entry:
colDist = [repelem(n, floor(size(X,2)/n)) rem(size(X,2),n)];
Xcell = mat2cell(X, size(X,1), colDist);
Ycell = mat2cell(Y, size(Y,1), colDist);
Here repelem(n, floor(size(X,2)/n)) repeats n for the number of times n fits in the number of columns of X. Then I append the remainder for the number of columns at the end (rem(size(X,2),n)) of this division to this row vector colDist.
When calling mat2cell (mat2cell(X, rowDist, colDist)) the second argument rowDist should then contain the number of rows per cell entry, which for each cell entry will be equal to the number of rows in X or Y.
Alternatively, you can use a loop to divide the matrix and vector in sub-matrices and put them in the appropriate cell.
Xcell = cell(ceil(size(X,2)/n),1);
Ycell = cell(ceil(size(X,2)/n),1);
% put in the blocks of n rows
for k = 1:floor(size(X,2)/n)
indices = n*(k-1)+1:n*k;
Xcell{k} = X(:,indices);
Ycell{k} = Y(:,indices);
end
% and the remainder:
Xcell{end} = X(:, indices(end)+1:end);
Ycell{end} = Y(:, indices(end)+1:end);
Related
Thank you for any help in advance. I have a large matrix: 1,000,000 rows and 10 columns. I would like to sum each row and create a new matrix with only the rows that sum to integers. I've tried this so far and manipulated it in many ways, but I'm stuck. How can I do this?
for k = 1:1000000
x = sum(A(k,:)) %A is my large matrix
if x-round(x,0)==0
y = [y;x]% y is my new matrix
end
end
Rather than using a for loop and continuously expanding y which is going to be extremely slow for large x arrays, you can use the second input of sum to compute the sum for each row, and then you can determine which rows sum to an integer by comparing the rounded and original versions using a very small epsilon (the proper way to compare floating-point numbers).
% Sum each row and divide by 3
row_sums = sum(x, 2) / 3;
% Determine which of the row-wise sums are integers
sum_is_integer = abs(round(row_sums) - row_sums) < eps;
% If you want the sums that were integers
y = row_sums(sum_is_integer);
% If you want a sub-matrix containing only the rows where the sums were an integer
z = x(sum_is_integer, :);
I have a 512x512 image , which i made 4x4 block for entire image, then i want access the (3rd row , 3rd element) of the all indivial 4x4 matrices and add it to the index values, which i obtained. Please help me on below code.
[row col] = size(a);
m = zeros(row,col);
count = [(row-4)*(col-4)]/4;
outMat = zeros(4,4,count);
l = 0;
for i=2:4:row-4
for j=2:4:col-4
l = l + 1;
outMat(:,:,l) = double(a(i-1:i+2,j-1:j+2));% for each matrix i have to find(3rd row,3rd element of each matrix.
end;
end;
Adding the (3rd row,3rd element):
m(i,j) = sum(sum(a .* w)); %index value of each 4x4 matrix % w = 4x4 matrix.
LUT = m(i,j)+ outMat(3,3);%(3rd row,3rd element each matrix should be added to all m(i,j) values. In which i fail to add all(3rd row,3rd element) of all 4x4 matrices.
I am going to reword your question so that it's easier to understand, as well as allowing it to be easy for me to write an answer.
From your comments in Kostya's post, you have two images img1 and img2 where they are decomposed into 4 x 4 blocks. outMat would be a 3D matrix where each slice contains a 4 x 4 block extracted from img1. From this, you have a matrix m that stores a weighted sum of 4 x 4 blocks stored outMat.
Next, you'll have another matrix, let's call this outMat2, which also is a 3D matrix where each slice is a 4 x 4 block extracted from img2. From this 3D matrix, you wish to extract the third row and third column of each block, add this to the corresponding position of m and store the output into a variable called LUT.
All you have to do is extract a single vector that slices through all of the slices located at the third row and third column. You would then have to reshape this into a matrix that is the same size as m then add this on top of m and store it into a variable called LUT. Bear in mind that if we reshape this into a matrix, the reshaping will be done in column major format, and so you would stack the values by columns. Because your blocks were created row-wise, what we need to do reshape this matrix so that it has size(m,2) rows and size(m,1) columns then transpose it.
Therefore:
vec = outMat2(3,3,:);
vec = vec(:); %// Make sure it's a 1D vector
m2 = reshape(vec, size(m,2), size(m,1)).';
LUT = m + m2;
LUT will contain a 2D matrix where each element contains the weighted sum of the 4 x 4 blocks from img1 with the corresponding third row, third column of each block in img2.
Next time, please update your question so that you have all of the information. We shouldn't have to dig through your comments to figure out what you want.
I think you can do just
LUT = sum( sum( a(3:4:row,3:4,col) * w(3,3) ) );
I want to concatenate 100 column vectors into one matrix. The code is the following:
for i = 1:100
X = mean(TMP(i).SonarReturnData.BeamsOutput(1:200, 25:35), 2);
end
What I want is to concatenate all 100 column vectors (each 200x1 length vectors) into one matrix (which should become a 200x100 matrix). I tried to use C = cat(2,X(:)), but it didn't work. Does anyone have an idea? Thank you.
Just pre-allocate X with your desired 200x100 size and then index into columns of X appropriately in your loop. I.e.,
X = zeros(200, 100);
for i = 1:100
X(:,i) = mean(TMP(i).SonarReturnData.BeamsOutput(1:200, 25:35), 2);
end
I am trying to find the sum of certain coordinates in a matrix.
I have a N x M matrix. I have a vector which contains 2xM values. Every pair of values in the vector is a coordinate in the matrix. Hence their are M number of coordinates. I want to find the sum of all of the coordinates without using a for loop.
Is there a matrix operation I can use to get this?
Thanks
As I understand it the vector contains the (row,column) coordinates to the matrix elements. You can just transform them into matrix element number indices. This example shows how to do it. I'm assuming that your coordinate vector looks like this:
[n-coordinate1 m-coordinate1 n-coordinate2 m-coordinate2 ...]
n = 5; % number of rows
m = 5; % number of columns
matrix = round(10*rand(n,m)); % An n by m example matrix
% A vector with 2*m elements. Element 1 is the n coordinate,
% Element 2 the m coordinate, and so on. Indexes into the matrix:
vector = ceil(rand(1,2*m)*5);
% turn the (n,m) coordinates into the element number index:
matrixIndices = vector(1:2:end) + (vector(2:2:end)-1)*n);
sumOfMatrixElements = sum(matrix(matrixIndices)); % sums the values of the indexed matrix elements
If you want to find the centroid of your 2xM array coords, then you can simply write
centroid = mean(coords,2)
If you want to find the weighted centroid, where each coordinate pair is weighted by the corresponding entry in the MxN array A, you can use sub2ind like this:
idx = sub2ind(size(A),coords(1,:)',coords(2,:)');
weights = A(idx);
weightedCentroid = sum( bsxfun( #times, coords', weights), 1 ) / sum(weights);
If all you want is the sum of all the entries to which the coordinates point, you can do the above and simply sum the weights:
idx = sub2ind(size(A),coords(1,:)',coords(2,:)');
weights = A(idx);
sumOfValues = sum(weights);
I have a 128 x 100 matrix in matlab, where each column should be treated as a separate element. Lets call this matrix M.
I have another 128 x 2000 matrix(called V) composed of columns from matrix M.
How would I make a histogram that maps the frequency of each column being used in the second matrix?
hist(double(V),double(M)) gives the error:
Error using histc
Edge vector must be monotonically
non-decreasing.
what should I be doing?
Here is an example. We start with data that resembles what you described
%# a matrix of 100 columns
M = rand(128,100);
sz = size(M);
%# a matrix composed of randomly selected columns of M (with replacement)
V = M(:,randi([1 sz(2)],[1 2000]));
Then:
%# map the columns to indices starting at 1
[~,~,idx] = unique([M,V]', 'rows', 'stable');
idx = idx(sz(2)+1:end);
%# count how many times each column occurs
count = histc(idx, 1:sz(2));
%# plot histogram
bar(1:sz(2), count, 'histc')
xlabel('column index'), ylabel('frequency')
set(gca, 'XLim',[1 sz(2)])
[Lia,Locb] = ismember(A,B,'rows') also returns a vector, Locb,
containing the highest index in B for each row in A that is also a row
in B. The output vector, Locb, contains 0 wherever A is not a row of
B.
ismember with the rows argument can identify which row of one matrix the rows of another matrix come from. Since it works on rows, and you are looking for columns, just transpose both matrices.
[~,Locb]=ismember(V',M');
histc(Locb)