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Project description
causy
Causal discovery made easy.
Dev usage
Setup
We recommend using poetry to manage the dependencies. To install poetry follow the instructions on https://python-poetry.org/docs/#installation.
Install dependencies
poetry install
Execute tests
poetry run python -m unittest discover -s tests
Usage via CLI
Run causy with one of the default algorithms
poetry run causy execute --help
poetry run causy execute tests/fixtures/toy_data_larger.json --algorithm PC
Customize your causy pipeline by ejecting and modifying the pipeline file.
poetry run causy eject PC pc.json
# edit pc.json
poetry run causy execute tests/fixtures/toy_data_larger.json --pipeline pc.json
Usage via Code
Use a default algorithm
from causy.algorithms import PC
from causy.utils import retrieve_edges
model = PC()
model.create_graph_from_data(
[
{"a": 1, "b": 0.3},
{"a": 0.5, "b": 0.2}
]
)
model.create_all_possible_edges()
model.execute_pipeline_steps()
edges = retrieve_edges(model.graph)
for edge in edges:
print(
f"{edge[0].name} -> {edge[1].name}: {model.graph.edges[edge[0]][edge[1]]}"
)
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