So np.asarray converts the input (x) to a numpy array, which has loads of utility functions.

On line 2, x is converted to an array.

On line 3, N is assigned as the length of the array along the x axis.

On line 4 and 5, they're checking if the length is a power of two. Another way of doing it is this:

GML:

```
if (((N - 1) & N) != 0) {
throw "Must be a power of 2"; // Before GMS2.3, this would be `show_error("Must be a power of 2", true)`
}
```

On line 7, n is assigned as an array range. This is the 1-dimensional array containing [0, 1, 2, ... N_min - 1].

On line 8, k is assigned as a 2-dimensional array. In y index 0, it has a duplicate of n. However, its length along the y axis is 1. In GML, this can be achieved this way:

GML:

```
k = [n];
/*
Before GMS2.3, this would be:
k = 0;
k[0] = n;
*/
```

On line 9, it's just a lot of different math. First, each element of k is squared. Then, it's multiplied by -2i * pi / N_min (a complex number). Then, the exponential function is applied to each element of k. Finally, the result is assigned to M. Since the input for the exponential function is complex, you'll have to write your own complex exponential function.

On line 10, it's performing matrix multiplication between the Nx1 matrix M and the Nx1 matrix that is the transposition of x. This will output a NxN matrix.

Actually, all the code is readily understandable if you look at the numpy documentation.