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+ from pathlib import Path
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import matplotlib .pyplot as plt
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import pandas as pd
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import numpy as np
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# }
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# rcParams.update(rc_fonts)
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- ROOT = os .path .realpath (os .path .dirname (__file__ ))
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- OBSERVATIONAL_DATA_PATH = f" { ROOT } / data/ 10k_observational_data.csv"
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+ ROOT = Path ( os .path .realpath (os .path .dirname (__file__ ) ))
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+ OBSERVATIONAL_DATA_PATH = ROOT / " data" / " 10k_observational_data.csv"
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def doubling_beta_CATE_on_csv (
@@ -262,6 +263,7 @@ def setup(observational_data_path):
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)
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# 7. Create a data collector
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+ breakpoint ()
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data_collector = ObservationalDataCollector (scenario , pd .read_csv (observational_data_path ))
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# 8. Obtain the minimal adjustment set for the base test case from the causal DAG
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