Metadata-Version: 2.1
Name: causalspyne
Version: 0.1.3
Summary: hierarchical data generation for causal discovery and abstraction
Author: Xudong Sun, Alex Markham
Requires-Python: >=3.9,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Dist: matplotlib (>=3.9.0,<4.0.0)
Requires-Dist: networkx (>=3.2.1,<4.0.0)
Requires-Dist: numpy (>=2.0.0,<3.0.0)
Requires-Dist: pandas (>=2.2.2,<3.0.0)
Requires-Dist: scipy (>=1.7.0,<2.0.0)
Description-Content-Type: text/markdown

# ProblemSetApproximateCausalDiscovery

```
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)
```

