Skip to content

Fix group selection in sample_posterior_predictive when predictions=True is passed in kwargs #426

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 8 commits into
base: main
Choose a base branch
from
Open

Fix group selection in sample_posterior_predictive when predictions=True is passed in kwargs #426

Changes from 6 commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
34839ad
Fix group selection for posterior predictive samples when predictions…
butterman0 Feb 17, 2025
7cdd900
refactor: make predictions argument explicit
butterman0 Feb 18, 2025
a0501fe
refactor: change default predictions to True
butterman0 Feb 18, 2025
079e131
doc: update docstrings
butterman0 Feb 18, 2025
fb6b1e9
docs: update
butterman0 Mar 6, 2025
ce1b2d5
refactor: pass predictions by keyword
butterman0 Mar 6, 2025
4ea5fbc
test: added test for predictions grouping
butterman0 Apr 9, 2025
7f84f03
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Apr 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 16 additions & 5 deletions pymc_extras/model_builder.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -530,6 +530,7 @@ def predict(
self,
X_pred: np.ndarray | pd.DataFrame | pd.Series,
extend_idata: bool = True,
predictions: bool = True,
**kwargs,
) -> np.ndarray:
"""
Expand All @@ -542,6 +543,9 @@ def predict(
The input data used for prediction.
extend_idata : Boolean determining whether the predictions should be added to inference data object.
Defaults to True.
predictions : bool
Whether to use the predictions group for posterior predictive sampling.
Defaults to True.
**kwargs: Additional arguments to pass to pymc.sample_posterior_predictive

Returns
Expand All @@ -559,7 +563,7 @@ def predict(
"""

posterior_predictive_samples = self.sample_posterior_predictive(
X_pred, extend_idata, combined=False, **kwargs
X_pred, extend_idata, combined=False, predictions=predictions, **kwargs
)

if self.output_var not in posterior_predictive_samples:
Expand Down Expand Up @@ -624,7 +628,7 @@ def sample_prior_predictive(

return prior_predictive_samples

def sample_posterior_predictive(self, X_pred, extend_idata, combined, **kwargs):
def sample_posterior_predictive(self, X_pred, extend_idata, combined, predictions = True, **kwargs):
"""
Sample from the model's posterior predictive distribution.

Expand All @@ -634,6 +638,8 @@ def sample_posterior_predictive(self, X_pred, extend_idata, combined, **kwargs):
The input data used for prediction using prior distribution..
extend_idata : Boolean determining whether the predictions should be added to inference data object.
Defaults to False.
predictions : Boolean determing whether to use the predictions group for posterior predictive sampling.
Defaults to True.
combined: Combine chain and draw dims into sample. Won't work if a dim named sample already exists.
Defaults to True.
**kwargs: Additional arguments to pass to pymc.sample_posterior_predictive
Expand All @@ -646,12 +652,14 @@ def sample_posterior_predictive(self, X_pred, extend_idata, combined, **kwargs):
self._data_setter(X_pred)

with self.model: # sample with new input data
post_pred = pm.sample_posterior_predictive(self.idata, **kwargs)
post_pred = pm.sample_posterior_predictive(self.idata, predictions=predictions, **kwargs)
if extend_idata:
self.idata.extend(post_pred, join="right")

group_name = "predictions" if predictions else "posterior_predictive"

posterior_predictive_samples = az.extract(
post_pred, "posterior_predictive", combined=combined
post_pred, group_name, combined=combined
)

return posterior_predictive_samples
Expand Down Expand Up @@ -700,6 +708,7 @@ def predict_posterior(
X_pred: np.ndarray | pd.DataFrame | pd.Series,
extend_idata: bool = True,
combined: bool = True,
predictions: bool = True,
**kwargs,
) -> xr.DataArray:
"""
Expand All @@ -713,6 +722,8 @@ def predict_posterior(
Defaults to True.
combined: Combine chain and draw dims into sample. Won't work if a dim named sample already exists.
Defaults to True.
predictions : Boolean determing whether to use the predictions group for posterior predictive sampling.
Defaults to True.
**kwargs: Additional arguments to pass to pymc.sample_posterior_predictive

Returns
Expand All @@ -723,7 +734,7 @@ def predict_posterior(

X_pred = self._validate_data(X_pred)
posterior_predictive_samples = self.sample_posterior_predictive(
X_pred, extend_idata, combined, **kwargs
X_pred, extend_idata, combined, predictions=predictions, **kwargs
)

if self.output_var not in posterior_predictive_samples:
Expand Down