Double check posterior predictions for counterfactual / "test set" data

[drbenvincent]

Check how we call pm.sample_posterior_predictive in ModelBuilder.predict.

https://github.com/pymc-labs/CausalPy/blob/e011c9de204d2b3fbb8d31480faa11d53553956d/causalpy/pymc_models.py#L32-L39

More specifically,

• Do we need to use the kwarg predictions=True?
• And should we store these predictions in idata, rather than a separate inferencedata object post_pred?