Multidimensional Matrices
OML supports multidimensional matrices.
This is an extension of the 2D matrices (see Collections), where data can be added and extracted across multiple dimensions.
b = ones(2); ==> b is a 2x2 matrix
b(:,:,3) = [5,6;7,8] ==> b is now a 2x2x3 matrix as follows:
slice(:, :, 1) =
[Matrix] 2 x 2
1 1
1 1
slice(:, :, 2) =
[Matrix] 2 x 2
0 0
0 0
slice(:, :, 3) =
[Matrix] 2 x 2
5 6
7 8
All rules that apply to accessing elements of a 2D matrix also apply to multidimensional matrices.
m3m = ones(2,2);
m3m(:,:,2) = [5,6;7,8];
m3m(:)
m3m(:,:,:)
m3m(1)
m3m(:,1,:)
m3m(1,:,2)
ans = [Matrix] 8 x 1
1
1
1
1
5
7
6
8
ans =
slice(:, :, 1) =
[Matrix] 2 x 2
1 1
1 1
slice(:, :, 2) =
[Matrix] 2 x 2
5 6
7 8
ans = 1
ans =
slice(:, :, 1) =
[Matrix] 2 x 1
1
1
slice(:, :, 2) =
[Matrix] 2 x 1
5
7
ans = [Matrix] 1 x 2
5 6
m(2,:,:) = [1,2;3,4]
The left-hand side
is expecting to assign data in dimensions 2 and 3, but the right-hand side has data in
dimensions 1 and 2. Strictly, this might be regarded as an error. However, it is useful to
allow an implicit assignment of the two right-hand side dimensions to the two colon
dimensions on the left to produce the following
result:m =
slice(:, :, 1) =
[Matrix] 2 x 2
0 0
1 3
slice(:, :, 2) =
[Matrix] 2 x 2
0 0
2 4
By
allowing both m(:,:,2)
and m(2,:,:)
on the left-hand side,
you can interpret the dimensions of m
as either (row, col, page) or (page,
row, col). This kind of flexibility applies to all numbers of dimensions and colons.m3m(2,2,2) = 1
m3m =
slice(:, :, 1) =
[Matrix] 2 x 2
0 0
0 0
slice(:, :, 2) =
[Matrix] 2 x 2
0 0
0 1
m(2,:,:) = [1,2;3,4];
b = m(:,1,:) ==> here b is a 2x1x2 matrix
b = squeeze(b) ==> here b is now a 2x2 matrix
b = ones(2,2)
b(:,:,2) = [5,6;7,8]; ==> here b is a 2x2x2 matrix
b(:,:,2) = []; ==> here b is now a 2x2 matrix