From 481a231dd2ef31d5f1581e26320cf387edeed343 Mon Sep 17 00:00:00 2001 From: Chris Fonnesbeck Date: Tue, 29 Nov 2016 19:08:13 -0600 Subject: [PATCH] Removed redundant size argument from sample_ppc --- pymc3/sampling.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/pymc3/sampling.py b/pymc3/sampling.py index 8937fc35b..7b0b91c7a 100644 --- a/pymc3/sampling.py +++ b/pymc3/sampling.py @@ -343,7 +343,7 @@ def _soft_update(a, b): a.update({k: v for k, v in b.items() if k not in a}) -def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_seed=None, progressbar=True): +def sample_ppc(trace, samples=None, model=None, vars=None, random_seed=None, progressbar=True): """Generate posterior predictive samples from a model given a trace. Parameters @@ -358,9 +358,6 @@ def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_see vars : iterable Variables for which to compute the posterior predictive samples. Defaults to `model.observed_RVs`. - size : int - The number of random draws from the distribution specified by the - parameters in each sample of the trace. Returns ------- @@ -387,8 +384,7 @@ def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_see for idx in indices: param = trace[idx] for var in vars: - ppc[var.name].append(var.distribution.random(point=param, - size=size)) + ppc[var.name].append(var.distribution.random(point=param)) return {k: np.asarray(v) for k, v in ppc.items()}