In linear algebra, the transpose of a matrix A is another matrix AT (also written A′, Atr,tA or At) created by any one of the following equivalent actions:
- reflect A over its main diagonal (which runs from top-left to bottom-right) to obtain AT
- write the rows of A as the columns of AT
- write the columns of A as the rows of AT
Formally, the ith row, jth column element of AT is the jth row, ith column element of A:
[AT]i j = [A]j i
If A is an m × n matrix then AT is an n × m matrix.
You have been given a matrix as a 2D list with integers. Your task is to return a transposed matrix based on input.
Input: A matrix as a list of lists with integers.
Output: The transposed matrix as a list/tuple of lists/tuples with integers.
transposeMatrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) ==...
The most obvious use for this idea is in mathematical software, but the concept can be applied in the area of vector graphics. On a computer, one can often avoid explicitly transposing a matrix in memory by simply accessing the same data in a different order.
0 < len() < 10
all(0 < len(row) < 10 for row in )