causalspyne 0.1.6

hierarchical data generation for causal discovery and abstraction

CausalSpyne

A Python package for simulating data from confounded causal models.

Quick start

Install with: pip install causalspyne

Generate some data:

from causalspyne import gen_partially_observed


gen_partially_observed(size_micro_node_dag=4,
                       num_macro_nodes=4,
                       degree=2,  # average vertex/node degree
                       list_confounder2hide=[0.5, 0.9], # choie of confounder to hide: percentile or index of all toplogically sorted confounders
                       num_sample=200,
                       output_dir="output",
                       rng=0)

Submodules

git submodule update --init