API¶

Import skdim as:

import skdim

ID estimators¶

`id.CorrInt`([k1, k2, DM])	Intrinsic dimension estimation using the Correlation Dimension.
`id.DANCo`([k, D, calibration_data, ver, …])	Intrinsic dimension estimation using the Dimensionality from Angle and Norm Concentration algorithm.
`id.ESS`([ver, d, random_state])	Intrinsic dimension estimation using the Expected Simplex Skewness algorithm.
`id.FisherS`([conditional_number, …])	Intrinsic dimension estimation using the Fisher Separability algorithm.
`id.KNN`([k, ps, M, gamma])	Intrinsic dimension estimation using the kNN algorithm.
`id.lPCA`([ver, alphaRatio, alphaFO, …])	Intrinsic dimension estimation using the PCA algorithm.
`id.MADA`([DM])	Intrinsic dimension estimation using the Manifold-Adaptive Dimension Estimation algorithm.
`id.MiND_ML`([k, D, ver])	Intrinsic dimension estimation using the MiND_MLk and MiND_MLi algorithms.
`id.MLE`([dnoise, sigma, n, …])	Intrinsic dimension estimation using the Maximum Likelihood algorithm.
`id.MOM`	Intrinsic dimension estimation using the Method Of Moments algorithm.
`id.TLE`([epsilon])	Intrinsic dimension estimation using the Tight Local intrinsic dimensionality Estimator algorithm.
`id.TwoNN`(discard_fraction, dist)	Intrinsic dimension estimation using the TwoNN algorithm.

`datasets.hyperSphere`(n, d[, random_state])	Generates a sample from a uniform distribution on the hypersphere
`datasets.hyperBall`(n, d[, radius, center, …])	Generates a sample from a uniform distribution on the hyperball
`datasets.hyperTwinPeaks`(n[, d, height, …])	Generates a sample from a plane with protruding peaks.
`datasets.lineDiskBall`(n[, random_state])	Generates a sample from a uniform distribution on a line, an oblong disk and an oblong ball Translated from ldbl function in Hideitsu Hino’s package
`datasets.swissRoll3Sph`(n_swiss, n_sphere[, …])	Generates a sample from a uniform distribution on a Swiss roll-surface, possibly together with a sample from a uniform distribution on a 3-sphere inside the Swiss roll.
`datasets.BenchmarkManifolds`(random_state, …)	Generates a commonly used benchmark set of synthetic manifolds with known intrinsic dimension described by Hein et al.