Issue computing ApEn with scikit-learn version 1.3.1

[danibene]

Describe the bug Tried to run hrv() after upgrading from scikit-learn 1.3.0 to 1.3.1 and got the following error:

out["ApEn"], _ = entropy_approximate(rri, delay=1, dimension=2, tolerance=tolerance)
/neurokit2/complexity/entropy_approximate.py", line 100, in entropy_approximate
    out, _ = _entropy_apen(signal, delay, dimension, info["Tolerance"], **kwargs)
/neurokit2/complexity/optim_complexity_tolerance.py", line 363, in _entropy_apen
    phi, info = _phi(
/neurokit2/complexity/utils.py", line 29, in _phi
    embedded1, count1, kdtree1 = _get_count(
/neurokit2/complexity/utils.py", line 115, in _get_count
    valid_metrics = sklearn.neighbors.KDTree.valid_metrics() + ["range"]
TypeError: 'list' object is not callable

Downgrading to scikit-learn 1.3.0 fixed it.

System Specifications I am using neurokit2 0.2.6, pandas 1.5.3, scipy 1.11.2, and numpy 1.24.3

[DominiqueMakowski]

Yes, I just realized it's what messing up with the CIs, let me give it a fix

[danibene]

Seems like it's related to this: https://github.com/scikit-learn/scikit-learn/pull/26754

[danibene]

Yes, I just realized it's what messing up with the CIs, let me give it a fix

Thank you!

[DominiqueMakowski]

Weird the tests still fail as if they weren't running with the update I made

[DominiqueMakowski]

I think I'll merge that branch soon anyway, and then we'll see from dev

[stale[bot]]

Is this still relevant? If so, what is blocking it? Is there anything you can do to help move it forward?

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