Separate InterruptedTimeSeries and SyntheticControl classes, update uml

causalpy/__init__.py

@@ -23,11 +23,12 @@
 from .data import load_data
 from .experiments.diff_in_diff import DifferenceInDifferences
 from .experiments.instrumental_variable import InstrumentalVariable
+from .experiments.interrupted_time_series import InterruptedTimeSeries
 from .experiments.inverse_propensity_weighting import InversePropensityWeighting
-from .experiments.prepostfit import InterruptedTimeSeries, SyntheticControl
 from .experiments.prepostnegd import PrePostNEGD
 from .experiments.regression_discontinuity import RegressionDiscontinuity
 from .experiments.regression_kink import RegressionKink
+from .experiments.synthetic_control import SyntheticControl
 
 az.style.use("arviz-darkgrid")
 

causalpy/experiments/base.py

@@ -81,7 +81,7 @@ def _ols_plot(self, *args, **kwargs):
         raise NotImplementedError("_ols_plot method not yet implemented")
 
     def get_plot_data(self, *args, **kwargs) -> pd.DataFrame:
-        """Recover the data of a PrePostFit experiment along with the prediction and causal impact information.
+        """Recover the data of an experiment along with the prediction and causal impact information.
 
         Internally, this function dispatches to either :func:`get_plot_data_bayesian` or :func:`get_plot_data_ols`
         depending on the model type.