feat: add power_config capabilities

cluster_experiments/experiment_analysis.py

@@ -1263,11 +1263,16 @@ def __init__(
             hypothesis=hypothesis,
         )
         self.scale_col = scale_col
+        self.cluster_cols = cluster_cols or []
 
         if covariates is not None:
             warnings.warn(
                 "Covariates are not supported in the Delta Method approximation for the time being. They will be ignored."
             )
+        if cluster_cols is None:
+            raise ValueError(
+                "cluster_cols must be provided for the Delta Method analysis"
+            )
 
     def _aggregate_to_cluster(self, df: pd.DataFrame) -> pd.DataFrame:
         """
@@ -1366,6 +1371,18 @@ def analysis_standard_error(self, df: pd.DataFrame) -> float:
         _mean_diff, standard_error = self._get_mean_standard_error(df)
         return standard_error
 
+    @classmethod
+    def from_config(cls, config):
+        """Creates a DeltaMethodAnalysis object from a PowerConfig object"""
+        return cls(
+            cluster_cols=config.cluster_cols,
+            target_col=config.target_col,
+            scale_col=config.scale_col,
+            treatment_col=config.treatment_col,
+            treatment=config.treatment,
+            hypothesis=config.hypothesis,
+        )
+
     def __warn_small_group_size(self):
         warnings.warn(
             "Delta Method approximation may not be accurate for small group sizes"

cluster_experiments/power_config.py

@@ -39,6 +39,10 @@ class MissingArgumentError(ValueError):
     pass
 
 
+class UnexpectedArgumentError(ValueError):
+    pass
+
+
 @dataclass(eq=True)
 class PowerConfig:
     """
@@ -106,6 +110,7 @@ class PowerConfig:
 
     # optional mappings
     cupac_model: str = ""
+    scale_col: Optional[str] = None
 
     # Shared
     target_col: str = "target"
@@ -197,6 +202,10 @@ def __post_init__(self):
         if "segmented" in self.perturbator:
             self._raise_error_if_missing("segment_cols", "perturbator")
 
+        if "delta" not in self.analysis:
+            if self.scale_col is not None:
+                self._raise_error_if_missing("scale_col", "analysis")
+
     def _are_different(self, arg1, arg2) -> bool:
         return arg1 != arg2
 
@@ -215,6 +224,13 @@ def _raise_error_if_missing(self, attr, other_attr):
                 f"{other_attr} = {getattr(self, other_attr)}."
             )
 
+    def _raise_error_if_present(self, attr, other_attr):
+        if getattr(self, attr) is None:
+            raise UnexpectedArgumentError(
+                f"{attr} is not expected when using "
+                f"{other_attr} = {getattr(self, other_attr)}."
+            )
+
 
 perturbator_mapping = {
     "binary": BinaryPerturbator,