resample fails on axis >1

[Jacob-Stevens-Haas]

resampy version: 0.2.1
Python: 3.7.3
numpy version: 1.16.2
Windows 10

resampy.resample returns array of zeros of appropriate size when axis parameter is greater than 1 (tested for axis=2 and axis=3). See minimal working example below:

>>> rand_arr = np.random.rand(3,4,5,100)
>>> resampled_arr = resampy.resample(rand_arr, 100, 24, axis=3)
>>> resampled_t_arr = resampy.resample(np.transpose(rand_arr), 100, 24, axis=0)
>>> print(resampled_arr.sum())
0.0
>>> print(resampled_t_arr.sum())
718.0698928346849

Believe it's due to the lines:

    x_2d = x.swapaxes(0, axis).reshape((x.shape[axis], -1))
    y_2d = y.swapaxes(0, axis).reshape((y.shape[axis], -1))
    resample_f(x_2d, y_2d, sample_ratio, interp_win, interp_delta, precision)

I can look into submitting a PR if it's simple and desirable?

[bmcfee]

Thanks for noting this. I'll try to make some time to look into it later in the week, but for now I'll confirm that i see the same behavior as your example.

You're almost certainly correct that this is due to the reshaping hackery we do to keep the resampling output arrays memory-contiguous and easy to compute. I don't see an obvious reason why this shouldn't work though.

[bmcfee]

Finally circling back on this - it's amazing how many issues / PRs were abandoned in early 2020.

I'm still not sure why this is happening, and suspect it may be a strange interaction with numba. FWIW we use similar shape manipulation logic in librosa (without numba) all the time and have no problems like this.

[bmcfee]

Ok, I've tracked this one down, but I'm not sure how to resolve it.

Based on the notes in the reshape documentation, it turns out that y_2d is indeed invoking a copy when the input array is of dimension 3 or greater. When this happens, the resample_f function is writing into a copy of the output buffer, rather than a view of the output buffer.

This 2d-reshape business was all to get around limitations of numba array indexing. However, I just tried it out and it seems that this is no longer necessary. I'll have to work out exactly what version of numba made this possible, but I think we should be able to sort this out and simplify things a bit.

[Jacob-Stevens-Haas]

Thanks! I had ended up forgetting about this too, but it's cool to see things come full circle!

[bmcfee]

Fix should go out in the 0.3 release, hopefully some time next week.