A Python package for simulating data from confounded causal models.
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)
git submodule update --init