The order of three-dimensional arrays in MATLAB is: row, column, and page. A two-dimensional array only has rows and columns. If two values are assigned between them, there is a dimensionality reduction issue that needs to be noted.
For example, A3 is a three-dimensional array, where A3 (:,:, 1)=[1,2,3; 4,5,6]; A3 (:,:, 2)=[7,8,9; 10,11,12];
So in the assignment of A2=A3 (:,:, 1), the result A2 is a two-dimensional matrix (a two-dimensional array) (a matrix of 2X3).
In the assignment of A2=A3 (1,:,:), the result A2 is a three-dimensional matrix (1X3X2 matrix).
Essentially, they should all be a two-dimensional matrix. Why does A2 become a three-dimensional matrix in the latter assignment, while the former is two-dimensional?
That is to say, the former should also be considered three-dimensional, how can it be reduced to two-dimensional, while the latter cannot be reduced to two-dimensional?
The main reason is that in a three-dimensional matrix, the first dimension represents rows, the second dimension represents columns, and the third dimension represents pages. When the third dimension is 1, it represents only 1 page, naturally reducing to 2D. When the first dimension is 1, it represents only one row, but each page has one, so from the perspective of the room, it is not reduced to two-dimensional.
The order of three-dimensional arrays in MATLAB is: row, column, and page. A two-dimensional array only has rows and columns. If two values are assigned between them, there is a dimensionality reduction issue that needs to be noted.
For example, A3 is a three-dimensional array, where A3 (:,:, 1)=[1,2,3; 4,5,6]; A3 (:,:, 2)=[7,8,9; 10,11,12];
So in the assignment of A2=A3 (:,:, 1), the result A2 is a two-dimensional matrix (a two-dimensional array) (a matrix of 2X3).
In the assignment of A2=A3 (1,:,:), the result A2 is a three-dimensional matrix (1X3X2 matrix).
Essentially, they should all be a two-dimensional matrix. Why does A2 become a three-dimensional matrix in the latter assignment, while the former is two-dimensional?
That is to say, the former should also be considered three-dimensional, how can it be reduced to two-dimensional, while the latter cannot be reduced to two-dimensional?
The main reason is that in a three-dimensional matrix, the first dimension represents rows, the second dimension represents columns, and the third dimension represents pages. When the third dimension is 1, it represents only 1 page, naturally reducing to 2D. When the first dimension is 1, it represents only one row, but each page has one, so from a physical perspective, it is not reduced to two-dimensional.
If a 2D result is required in the end, please use reshape processing.
