User Guide

• 1. Causal Graphs in PyWhy
  • 1.1. Which graph class should I use?
  • 1.2. pywhy_graphs.classes: Causal graph types
  • 1.3. pywhy_graphs.classes.timeseries: Causal graph types for time-series (alpha)
• 2. Functional Causal Graphical Models
  • 2.1. Representing a node’s functional relationships
  • 2.2. Specific Functional Graphs
  • 2.3. Linear
  • 2.4. Linear
  • 2.5. Linear functional graphs
  • 2.6. Multidomain
  • 2.7. Linear functional selection diagrams
• 3. Causal Graph Algorithms in PyWhy
  • 3.1. Core Algorithms
  • 3.2. Algorithms for Markov Equivalence Classes
  • 3.3. Algorithms for Time-Series Graphs
  • 3.4. Algorithms for handling acyclicity
• 4. Semi-directed (possibly-directed) Paths
  • 4.1. pywhy_graphs.algorithms.semi_directed_paths.all_semi_directed_paths
  • 4.2. pywhy_graphs.algorithms.semi_directed_paths.is_semi_directed_path
• 5. Simulation module
  • 5.1. pywhy_graphs.simulate: Causal graphical model simulations
• 6. Importing causal graphs to PyWhy-Graphs, or exporting PyWhy-Graphs to another package
  • 6.1. Causal-Learn
  • 6.2. Numpy (graphviz and dagitty)
  • 6.3. PCAlg from R (Experimental)
  • 6.4. Tetrad from Java
• 7. Glossary of Common Terms and API Elements
  • 7.1. General Concepts