transpose

Builtin index · Core maths

result = transpose(A)

Input: A · Output: result

What it is

Matrix/vector transpose: swaps rows and columns. A is a Vec (treated as a single row or column) or Mat/CMat; an r×c input returns a c×r output of the same element type.

Overloads

One call shape — this function is not overloaded.

Code	Input	Output	Description
`result = transpose(A)`	`A` Mat, vector, Vec, or CMatnot documented yet	`result` Mat, CMat, or Vec	Returns a `Mat`, or a `CMat` for a complex input — including for a `Vec` argument, which comes back as an `n×1` column `Mat` rather than a `Vec`.

Examples

From the documentation, and run by the build -- the output and the figure below are what the engine actually produced. Simplest first.

A = [1, 2, 3; 4, 5, 6]
x = 5
print("val={val(x)}")
print(transpose(A))
print("mirror={mirror([1, 2, 3])}")

output

val=5
[1, 4; 2, 5; 3, 6]
mirror=[3, 2, 1]

from core-math

How it works

d(transpose(x))/dx: transpose is a linear permutation of elements, so its own vjp is just transposing the upstream adjoint back — reuses the free transpose_value helper every OTHER vjp rule already calls for local derivatives (here it's the WHOLE rule, not just a local factor).

From the note above this builtin in the interpreter, where the reasoning was written down as it was built.