I have two matrices in Matlab A and B respectively of dimension MxN and GxN.
M can be greater or smaller than G.
A and B do not contain identical rows.
I want to construct a matrix C of dimension Hx(N+2) in the following way
C=[];
for i=1:size(A,1)
%if A(i,1:end-1) coincides with a row in B(:,1:end-1) (it can coincide with only one row at most)
%then C=[C;A(i,1:end) B(j,end)]; %where j is the index of the identical row in B
%otherwise impose C=[C;A(i,1:end) 0]
end
for i=1:size(B,1)
%if B(i,1:end-1) does not coincide with any row in A(:,1:end-1)
%then impose C=[C; B(i,1:end-1) 0 B(i,end)];
end
For example:
A=[1 2 3 4 5 100; 6 7 8 9 10 101; 11 12 13 14 15 102];
B=[6 7 8 9 10 103; 15 16 17 18 19 104]
C=[1 2 3 4 5 100 0; 6 7 8 9 10 101 103; 11 12 13 14 16 102 0; 15 16 17 18 19 0 104]
As M and G can be very high, I am looking for the fastest way to perform this.
You can use ismember + indexing to do your task:
[idx1,idx2] = ismember(A(:,1:end-1), B(:,1:end-1), 'rows');
idx3 = ~ismember(B(:,1:end-1), A(:,1:end-1), 'rows');
C(idx1,:) = [A(idx1,:) B(idx2(idx1),end)];
C(~idx1,:) = [A(~idx1,:) zeros(sum(~idx1),1)];
C=[C;B(idx3,1:end-1) zeros(sum(idx3),1) B(idx3,end)];
You could also use intersect with a bit of preallocation to speed up the assignment (if M or G gets really large).
A=[1 2 3 4 5 100; 6 7 8 9 10 101; 11 12 13 14 15 102];
B=[6 7 8 9 10 103; 15 16 17 18 19 104];
C=[1 2 3 4 5 100 0; 6 7 8 9 10 101 103; 11 12 13 14 16 102 0; 15 16 17 18 19 0 104];
[M,N] = size(A);
G = size(B,1);
[tmp, idxA, idxB] = intersect(A(:,1:end-1),B(:,1:end-1),'rows')
idxBnotA = setdiff([1:G],idxB);
H = M + G - length(idxA);
C1 = zeros(H,N+1);
C1(1:M,1:N) = A;
C1(idxA,end) = B(idxB,end);
C1(M+1:end,1:end-2) = B(idxBnotA,1:end-1);
C1(M+1:end,end) = B(idxBnotA,end)
Related
The input is an N-by-1 matrix. I need to reshape it to L-by-M matrix. The following is an example.
Input:
b =
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Set length = 18, Output:
X =
1 2 3
2 3 4
3 4 5
4 5 6
5 6 7
6 7 8
7 8 9
8 9 10
9 10 11
10 11 12
11 12 13
12 13 14
13 14 15
14 15 16
15 16 17
16 17 18
17 18 19
18 19 20
Because I have a very big matrix, using a loop to reshape is very inefficient. How can I improve the reshape speed?
Your example output matrix X is the perfect matrix to index a vector of length N to get what you want. It's also very easy to create using bsxfun:
N = 20;
b = rand(N,1);
M = 3; %// number of columns
L = N-M; %// Note that N-M is an upper limit for L!
idx = bsxfun(#plus, (0:L)', 1:M)
X = b(idx)
That's exactly what im2col (from the Image Processing Toolbox) does:
b = (1:20).'; %'// example data
L = 18; % // desired length of sliding blocks
x = im2col(b, [L 1]); % // result
I'd use horzcat. For example:
function X = reshaper(b,len)
diff = length(b) - len + 1;
X = b(1:len);
for i=2:diff
X = horzcat(X,b(i:len+(i-1)));
end
You could probably remove the for loop with some further thought.
I have a matrix
A= [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16; 17 18 19 20]
I want to do some calculation on this matrix. But actually I do not need all the rows. So I have to discard some of the rows from the above matrix before doing a calculation. After discarding 3 rows, we will have a new matrix.
B= [1 2 3 4; 9 10 11 12; 17 18 19 20];
Now I have to use B to make some other calculations. So how can I discard some of the unwanted rows from a matrix in matlab? Any suggestion will be helpful. Thanks.
Try this: (Use when no. of rows to keep is lesser)
%// Input A
A = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16; 17 18 19 20];
%// Rows (1-3,5) you wanted to keep
B = A([1:3, 5],:)
Output:
B =
1 2 3 4
5 6 7 8
9 10 11 12
17 18 19 20
Alternative: (Use when no. of rows to discard is lesser)
%// rows 2 and 3 discarded
A([2,3],:) = [];
Output:
>> A
A =
1 2 3 4
13 14 15 16
17 18 19 20
Note: Here (in the alternate method), the output replaces the original A. So you need to back up A if you need it afterwards. You could do this before discarding operation to backup Input matrix
%// Input A is backed up in B
B = A;
You can select the indices of the rows you want to keep:
A([1,3,5],:)
ans =
1 2 3 4
9 10 11 12
17 18 19 20
I want to write a Matlab script.
In my example I have a vector A=[1 3 4 5 7 8 9 10 11 13 14 15 16 17 19 20 21]
Now I want to cut the vector automatically at the points where a number is missing(here the numbers 2, 6, 12, 18 are missing).
As a result I want to have the vectors [1] and [3 4 5] and [7 8 9 10 11] and [13 14 15 16 17] and [19 20 21]. So as you can see the new vectors have different lenghts.
I thought about using a for loop, but I am not sure how to write these new vectors.
Thank you for your help :)
One liner with diff, cumsum & accumarray -
out = accumarray(cumsum([0 ; diff(A(:))~=1])+1,A(:),[],#(x) {x})
Sample run -
>> A
A =
1 3 4 5 7 8 9 10 ...
11 13 14 15 16 17 19 20 21
>> celldisp(out)
out{1} =
1
out{2} =
3
4
5
out{3} =
7
8
9
10
11
out{4} =
13
14
15
16
17
out{5} =
19
20
21
This is one approach:
s = [find(diff(A(:).')>1) numel(A)]; %'// detect where consecutive difference exceeds 1
s = [s(1) diff(s)]; %// sizes of groups
result = mat2cell(A(:).', 1, s); %'// split into cells according to those sizes
In your example, this gives
>> celldisp(result)
result{1} =
1
result{2} =
3 4 5
result{3} =
7 8 9 10 11
result{4} =
13 14 15 16 17
result{5} =
19 20 21
Another approach (computes group sizes differently):
s = diff([0 sum(bsxfun(#lt, A(:), setdiff(1:max(A(:).'), A(:).')), 1) numel(A)]);
result = mat2cell(A(:).', 1, s);
I would like to transform the matrix A into the matrix B without using cells (e.g. mat2cell) in Matlab, where
A=[1 2 3;
4 5 6;
7 8 9;
10 11 12;
13 14 15;
16 17 18;
19 20 21;
22 23 24;
25 26 27];
B=[1 2 3 10 11 12 19 20 21;
4 5 6 13 14 15 22 23 24;
7 8 9 16 17 18 25 26 27];
All you need is some reshape + permute magic -
N = 3; %// Cut after every N rows and this looks like the no. of columns in A
B = reshape(permute(reshape(A,N,size(A,1)/N,[]),[1 3 2]),N,[])
This builds a linear index to rearrange the entries of A and then reshapes into the desired matrix B:
m = 3; %// cut size in rows of A. Assumed to divide size(A,1)
n = size(A,2);
p = size(A,1);
ind = bsxfun(#plus, ...
bsxfun(#plus, (1:m).', (0:n-1)*p), permute((0:p/m-1)*m, [1 3 2]));
B = reshape(A(ind(:)), m, [])
In an algorithm, in each level, I have two corresponding matrices in a way one of them has 4 times more element than the other. like children and parent, but i need to have the corresponding elements. consider the two following indices as an example for a level
1 5 9 13
2 6 10 14 and 1 3
3 7 11 15 2 4
4 8 12 16
so for example, I want to receive the element by the index of 1 from the second matrix when i have each of 1,2,5,6 element indices from the first matrix or 2 when i have 3,4,7,8 or 3 for 9,10,16,14 and so on. how can i do that?
as an another example for another level:
1 9 17 25 33 41 49 57
2 10 18 26 34 42 50 58
3 11 19 27 35 43 51 59 and 1 5 9 13
4 12 20 28 36 44 52 60 2 6 10 14
5 13 21 29 37 45 53 61 3 7 11 15
6 14 22 30 38 46 54 62 4 8 12 16
7 15 23 31 39 47 55 63
8 16 24 32 40 48 56 64
Here is one way of doing that:
% Size of matrix A (8x8)
sizeA = 8;
% Size of matrix B (4x4)
sizeB = 4;
% Index of element on matrix A
idxA = 43;
% That is how you can get the corresponding index on matrix B
[r, c] = ind2sub([sizeA sizeA], idxA);
idxB = sub2ind([sizeB sizeB], ceil(r / 2), ceil(c / 2))
It will give you idxB = 10.
It is possible that reshape could be helpful for you.
Consider
A = [1 5 9 13;
2 6 10 14;
3 7 11 15;
4 8 12 16];
B = reshape(permute(reshape(A, [2 2 2 2]), [2 4 1 3]), [4 4]);
B
1 2 5 6
3 4 7 8
9 10 13 14
11 12 15 16
Now you have a nice mapping of the indices from one level to the next.
B(1,:) corresponds to all the indices that map to element 1 in your second array, etc.
When the matrix gets larger (2n x 2n), the operation becomes
B = reshape(permute(reshape(A, [2 n 2 n]), [2 4 1 3]), [n*n 4]);
If you know the 2D indices for the first matrix, then you just divide each by 2 to get the second pair indices:
r = 3;
c = 2;
% Then A(r,c) corresponds to B(floor(r/2), floor(c/2))
If you DON'T know the indices, but instead have the element value itself, you have to find the 2D index first:
val = 7; % test value
[r c] = find(A==val);
other_val = B(floor(r/2), floor(c/2));