BUG: `pm.sample_posterior_predictive` discards new results when `extend_inferencedata=True` and `posterior_predictive` group already exists

Description

import pymc as pm
import numpy as np

y = np.random.normal(loc=1, size=(100,))
with pm.Model() as m:
    mu = pm.Normal('mu')
    y_hat = pm.Normal('y_hat', mu=mu, sigma=1, observed=y)
    idata = pm.sample()
    idata = pm.sample_posterior_predictive(idata, extend_inferencedata=True)

with pm.Model() as m2:
    new_mu = pm.Normal('mu2', sigma=10)
    y_hat = pm.Normal('y_hat', mu=new_mu, sigma=1)
    idata = pm.sample_posterior_predictive(idata, extend_inferencedata=True)

Contributor guide

Tech stack

python

Domain

data

Issue type

bug

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

3

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

half day

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

fresh

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

clear

Prerequisites

Basic knowledge of PyMCInferenceData concepts

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

60

Research direction

Examine the `sample posterior predictive` function in the PyMC source code (likely `pymc/sampling.py`) to understand how it handles the `extend inferencedata=True` and existing `posterior predictive` group. Trace the logic to see why new samples are discarded instead of appended. Check any relevant comments or existing tests for expected behavior.