Say I have a matrix
A = zeros(5, 5);
Instead of looping with a for loop, I wish to batch-modify some of the elements. For example, I wish to change elements marked by pts_to_modify to 1, where
pts_to_modify=[[2 3]; [3 2]];
So I wish A to become
0 0 0 0 0
0 0 1 0 0
0 1 0 0 0
0 0 0 0 0
However, when I do
A(pts_to_modify(:, 1), pts_to_modify(:, 2)) = 1,
I get
A =
0 0 0 0 0
0 1 1 0 0
0 1 1 0 0
0 0 0 0 0
0 0 0 0 0
How can I do it correctly?
You can use sub2ind:
>> ind = sub2ind(size(A), pts_to_modify(1,:), pts_to_modify(2,:))
ind =
12 8
>> A(ind) = 1
A =
0 0 0 0 0
0 0 1 0 0
0 1 0 0 0
0 0 0 0 0
0 0 0 0 0
sub2ind
linear indexing
Related
I want to get rid of leading zeros in each row of a matrix, but limit it to eliminating one zero at a time.
This is my current solution, but is there a simpler way of doing it?
a = [ 0 0 0 0 0 0 0 0 0 0
0 0 5 2 3 4 0 0 0 0
0 0 0 1 2 3 4 0 0 0
0 0 1 2 3 0 0 0 0 0
0 0 0 0 1 0 0 0 0 0
1 0 0 0 0 0 0 0 0 0 ]
b=zeros(size(a));
for j=1:size(a,2)
for i=1:size(a,1)
temp=find(a(i,:),1,'first');
candelete=min(2,temp);
b(i,1:end-candelete+1)=a(i,candelete:end);
end
a=b
end
EDIT:
I'm want to print every iteration, so that the first output will only have the first leading zero removed:
0 0 0 0 0 0 0 0 0 0
0 5 2 3 4 0 0 0 0 0
0 0 1 2 3 4 0 0 0 0
0 1 2 3 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0 0
1 0 0 0 0 0 0 0 0 0
the second will have 2 zeros removed, and so on...
EDIT: Now that the question was clarified, here's a better answer using circshift:
index = (a(:, 1) == 0) & any(a, 2);
while any(index)
a(index, :) = circshift(a(index, :), -1, 2);
disp(a);
index = (a(:, 1) == 0) & index;
end
I want to create a matrix of size m-by-n where all elements in a column are 0 except one element which is 1. That one element must be at a random position.
eg.
[0 1 0 0 0
0 0 1 0 0
1 0 0 1 0
0 0 0 0 0
0 0 0 0 1]
To add some variety, here's another approach:
m = 4;
n = 5;
[~, result] = sort(rand(m,n));
result = double(result==1);
This gives, for example,
result =
0 0 0 0 1
0 1 0 0 0
1 0 0 1 0
0 0 1 0 0
You can also use rand and max to do the job:
m=4;
n=5;
R=rand(m,n);
result = bsxfun(#eq, R, max(R,[],1))
On my machine it gave:
1 1 0 0 0
0 0 0 0 0
0 0 1 0 1
0 0 0 1 0
How it works: Generating a random matrix, R, and then setting to 1 the entry corresponding to the maximal element at each column. No need for sorting.
Regarding the original answer of Divakar, since it uses randperm it is restricted to square matrix only, and it will only produce random permutation matrices.
One possible way to correct his solution is to use randi instead of randperm:
result = bsxfun( #eq, (1:m)', randi(m, 1, n ) )
May give this output:
1 0 1 0 0
0 0 0 0 0
0 0 0 0 0
0 1 0 1 1
As for the answer of bla, using accumarry can save the use of zeros and sub2ind:
m=5; n=10;
R=randi(m,n,1);
A = accumarray( {R, (1:n)' }, 1, [m n] )
May give this output:
0 0 0 0 1 0 0 1 0 0
0 1 0 0 0 0 1 0 1 0
1 0 0 1 0 0 0 0 0 1
0 0 0 0 0 1 0 0 0 0
0 0 1 0 0 0 0 0 0 0
Another idea I have is to create the identity matrix of size m x m, then use randi with a range from 1 up to m to create a vector of n elements long. After, you'd use this vector to access the columns of the identity matrix to complete the random matrix you desire:
m = 5; n = 5; %// Given your example
M = eye(m);
out = M(:,randi(m, n, 1));
Here's one possible run of the above code:
out =
1 0 0 0 0
0 0 0 0 0
0 0 0 1 0
0 0 0 0 0
0 1 1 0 1
here's an example using randi:
m=5; n=10;
A=zeros(m,n);
R=randi(m,n,1);
A(sub2ind(size(A),R',1:n))=1
A =
0 0 0 0 0 0 0 1 0 1
0 0 1 0 0 0 0 0 0 0
0 1 0 1 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0 0
1 0 0 0 0 0 1 0 1 0
You can use sparse with randi for a one-liner, like so -
full(sparse(randi(m,1,n),1:n,1,m,n))
Sample run -
>> m = 5; n = 6;
>> full(sparse(randi(m,1,n),1:n,1,m,n))
ans =
0 1 0 0 0 1
0 0 1 1 0 0
0 0 0 0 0 0
1 0 0 0 1 0
0 0 0 0 0 0
I have a matrix looks like:
0 0 0 0 0
1 0 0 0 0
0 2 0 0 0
0 0 2 0 0
0 0 0 1 0
1 0 0 0 1
0 4 0 0 0
0 0 3 0 0
6 0 0 4 0
0 3 0 0 2
0 0 5 0 0
It is 11x5 matrix.
I want to interpolate between the values vertically for each column.
Any help ?
Thanks.
M =[0 0 0 0 0
1 0 0 0 0
0 2 0 0 0
0 0 2 0 0
0 0 0 1 0
1 0 0 0 1
0 4 0 0 0
0 0 3 0 0
6 0 0 4 0
0 3 0 0 2
0 0 5 0 0];
xi = 1:size(M,1)
for colIdx = 1:size(M,2)
col = M(:,colIdx);
x = xi(~~col); %// Note that ~~col is a logical vector of elements that are not equal to zero. i.e. it's the same as col ~= 0
y = col(~~col);
M(:,colIdx) = interp1(x,y,xi);
end
then if you want the outer points to be 0 add this line after the loop:
M(isnan(M)) = 0;
I want to access multiple indices of a matrix as shown below. So what I want is indices (1,3),(2,6),(3,7) to be set to one. However, as you can see the entire column is set to one. I can see what it is doing but is there a way to do what I want it to (in an elegant way - no loops).
a=zeros(3,10)
a(1:3,[3 6 7])=1
a =
0 0 1 0 0 1 1 0 0 0
0 0 1 0 0 1 1 0 0 0
0 0 1 0 0 1 1 0 0 0
I realise that you can do something along the lines of
x_idx=1:3, y_idx=[3 6 7];
idx=x_idx*size(a,2)+y_idx;
a(idx)=1;
but just wondering if there was a better, or proper way of doing this in Matlab
You can use sub2ind, which essentially is doing what you have mentioned in your post, but MATLAB has this built-in:
a = zeros(3,10);
a(sub2ind(size(a), 1:3, [3 6 7])) = 1
a =
0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 0 0
0 0 0 0 0 0 1 0 0 0
Another way would be to create a logical sparse matrix, then use this to index into a:
a = zeros(3,10);
ind = logical(sparse(1:3, [3 6 7], true, size(a,1), size(a,2)));
a(ind) = 1
a =
0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 0 0
0 0 0 0 0 0 1 0 0 0
How to replace elements of a matrix by an another matrix in MATLAB?
Ex: let say if we have a matrix A, where
A=[1 0 0; 0 1 0; 1 0 1]
I want to replace all ones by
J=[1 0 0; 0 1 0; 0 0 1]
and zeros by
K=[0 0 0; 0 0 0; 0 0 0]
So that I can get 9x9 matrix. So how we will code it in MATLAB
Thanks
Sounds like you might want to take a look at the kronecker tensor product. This is not a general case but the idea should work for what you want
>> kron(A==1,J)+kron(A==0,K)
ans =
1 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 0 1 0 0 0
1 0 0 0 0 0 1 0 0
0 1 0 0 0 0 0 1 0
0 0 1 0 0 0 0 0 1
which, for the example case, would simplify to a simpler command:
>> kron(A,J)
ans =
1 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 0 1 0 0 0
1 0 0 0 0 0 1 0 0
0 1 0 0 0 0 0 1 0
0 0 1 0 0 0 0 0 1
You can do:
A2=imresize(A,size(A).*size(J),'nearest');
J2=repmat(J,size(A));
K2=repmat(K,size(A));
A2(A2==1)=J2(A2==1);
A2(A2==0)=K2(A2==0)