estimate_cutoff#
- datafold.pcfold.estimate_cutoff(pcm, n_subsample=1000, k=10, random_state=None, distance_matrix=None)[source]#
Estimates a good choice of cut-off for a Gaussian radial basis kernel, given a certain tolerance below which the kernel values are considered zero.
- Parameters:
pcm – point cloud to compute pair-wise kernel matrix with
n_subsample (
int
) – Maximum subsample used for the estimation. Ignored ifdistance_matrix is not None
.k (
int
) – Compute the k-th nearest neighbor distance to estimate the cut-off distance.random_state (
Optional
[int
]) – setsnp.random.default_rng(random_state)
distance_matrix – pre-computed distance matrix instead of using the internal cdist method
- Return type: