DADApy: Distance-based Analysis of DAta-manifolds in Python

Abstract

DADApy is a python software package for analysing and characterising high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering and for comparing different distance metrics. We review the main functionalities of the package and exemplify its usage in toy cases and in a real-world application. DADApy is freely available under the open-source Apache 2.0 license.

9 pages, 6 figures. Patterns (2022)

References in corpus (4)

• PLUMED: a portable plugin for free-energy calculations with molecular dynamics
• Exploring the robust extrapolation of high-dimensional machine learning potentials
• Intrinsic dimension estimation for discrete metrics
• Distributional Results for Model-Based Intrinsic Dimension Estimators

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• Density Estimation via Binless Multidimensional Integration
• Family-Vicsek universality of the binary intrinsic dimension of nonequilibrium data
• MDIntrinsicDimension: Dimensionality-Based Analysis of Collective Motions in Macromolecules from Molecular Dynamics Trajectories