Really dumb question but I’m currently doing MCMC with AIES (or NUTS):

```
mcmc = MCMC(AIES(model),num_warmup=500,num_samples=500,num_chains=20,chain_method='vectorized')
mcmc.run(key(1), model_params=model_params, obs_data=obs_data, obs_sigma=0.1)
```

Then I can use Predictive to get posterior samples of my model parameters but this seems to exclude warmup samples by default :

```
Predictive(model, mcmc.get_samples())(key(1), model_params)["obs"]
```

Is there anyway to get the entire chain INCLUDING the warm-up samples? I want to make a movie showing how initially the draws from the prior don’t match obs_data but then eventually later samples from the chain (which may happen before/after num_warmup draws…) start to match the data. But for this I need samples from the warmup/burn-in stage…