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Table of Contents

  • Installation
  • Implemented Algorithms
  • Typical usage of the package
  • Modules (API reference)
    • The base module
    • The id_estimation module
    • The neigh_graph module
    • The density_estimation module
    • The density_advanced module
    • The diff_imbalance module
    • The causal_graph module
    • The clustering module
    • The id_discrete module
    • The metric_comparisons module
    • The feature_weighting module
    • The data module
    • The utils module
  • Tutorial: Density Based Clustering
  • Tutorial: Information Imbalance
  • Tutorial: Intrinsic dimension
  • Tutorial: Using DADApy to analyse a molecular dynamics trajectory of a small peptide
  • Tutorial: Intrinsic dimension estimation for discrete metrics
  • Tutorial: Differentiable Information Imbalance
  • Tutorial: Differentiable Information Imbalance (JAX implementation)
  • Tutorial: Community causal graph reconstruction
  • Hands-on tutorial at SISSA
  • Citing DADApy
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  • Modules (API reference)
  • View page source

Modules (API reference)

The package contains the following modules:

  • The base module
    • Base
  • The id_estimation module
    • IdEstimation
  • The neigh_graph module
    • NeighGraph
  • The density_estimation module
    • DensityEstimation
  • The density_advanced module
    • DensityAdvanced
  • The diff_imbalance module
    • DiffImbalance
  • The causal_graph module
    • CausalGraph
  • The clustering module
    • Clustering
  • The id_discrete module
    • IdDiscrete
  • The metric_comparisons module
    • MetricComparisons
  • The feature_weighting module
    • FeatureWeighting
  • The data module
    • Data
  • The utils module
    • compute_NN_PBC()
    • compute_all_distances()
    • compute_cross_nn_distances()
    • compute_nn_distances()
    • from_all_distances_to_nndistances()
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