Sample ppc does not shuffle by default

pymc-devs · Sep 26, 2018 · 5574449 · 5574449
1 parent bdd3dc0
commit 5574449
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diff --git a/RELEASE-NOTES.md b/RELEASE-NOTES.md
@@ -6,6 +6,7 @@
 
 - Track the model log-likelihood as a sampler stat for NUTS and HMC samplers
   (accessible as `trace.get_sampler_stats('model_logp')`) (#3134)
+- Behavior of `sample_posterior_predictive` is now to produce posterior predictive samples in order from all values of the `trace`. Previously, by default it would produce 1 chain worth of samples, using a random selection from the `trace` (#3212)
 
 ### Maintenance
 

diff --git a/pymc3/sampling.py b/pymc3/sampling.py
@@ -1098,7 +1098,7 @@ def sample_posterior_predictive(trace, samples=None, model=None, vars=None, size
         nchain = 1
 
     if samples is None:
-        samples = len(trace)
+        samples = sum(len(v) for v in trace._straces.values())
 
     model = modelcontext(model)
 
@@ -1108,7 +1108,7 @@ def sample_posterior_predictive(trace, samples=None, model=None, vars=None, size
     if random_seed is not None:
         np.random.seed(random_seed)
 
-    indices = np.random.randint(0, nchain * len_trace, samples)
+    indices = np.arange(samples)
 
     if progressbar:
         indices = tqdm(indices, total=samples)