Provide concatenate along other axes

[RReverser]

While README mentions that it's possible to achieve concatenation along various axes by using transposition, it's pretty hard to wrap my head around how to do that on multi-dimensional arrays. It would be a lot easier if such concatenation was part of the user-facing API, like it is in numpy.

Example code that I'm trying to convert right now:

        image = np.concatenate((image, image[(h - dh) :, :, :]), axis = 0)
        image = np.concatenate((image, image[:, (w - dw) :, :]), axis = 1)
        
        image = np.concatenate((image, image[(h - offset) :, :, :]), axis = 0)
        image = np.concatenate((image[: offset, :, :], image), axis = 0)
        image = np.concatenate((image, image[:, (w - offset) :, :]), axis = 1)
        image = np.concatenate((image[:, : offset, :], image), axis = 1)

Even if I manage to rewrite it using transpositions, I feel it won't be very readable / maintainable going forward.

[RReverser]

This is what I came up with for now as a helper that seems to work:

function concatenateAlong(axis, ...arrays) {
  let lastAxis = arrays[0].shape.length - 1;
  let axes = arrays[0].shape.map((_, i) => {
    // swap the required axis with the last one
    switch (i) {
      case lastAxis:
        return axis;
      case axis:
        return lastAxis;
      default:
        return i;
    }
  });
  arrays = arrays.map(a => a.transpose(...axes));
  let result = numjs.concatenate(...arrays);
  return result.transpose(...axes);
}

Does it look reasonable? Is it perhaps worth adding it to the library?