Merge branch 'master' of https://github.com/pymc-devs/pymc3

RELEASE-NOTES.md

@@ -23,6 +23,8 @@
 - Dropped the outdated 'nuts' initialization method for `pm.sample` (see [#3863](https://github.com/pymc-devs/pymc3/pull/3863)).
 - Moved argument division out of `NegativeBinomial` `random` method. Fixes [#3864](https://github.com/pymc-devs/pymc3/issues/3864) in the style of [#3509](https://github.com/pymc-devs/pymc3/pull/3509).
 - The Dirichlet distribution now raises a ValueError when it's initialized with <= 0 values (see [#3853](https://github.com/pymc-devs/pymc3/pull/3853)).
+- End of sampling report now uses `arviz.InferenceData` internally and avoids storing
+  pointwise log likelihood (see [#3883](https://github.com/pymc-devs/pymc3/pull/3883))
 
 ## PyMC3 3.8 (November 29 2019)
 

pymc3/backends/report.py

@@ -87,7 +87,7 @@ class SamplerReport:
     def t_sampling(self) -> typing.Optional[float]:
         """
         Number of seconds that the sampling procedure took.
-        
+
         (Includes parallelization overhead.)
         """
         return self._t_sampling
@@ -108,6 +108,7 @@ class SamplerReport:
             return
 
         from pymc3 import rhat, ess
+        from arviz import from_pymc3
 
         valid_name = [rv.name for rv in model.free_RVs + model.deterministics]
         varnames = []
@@ -119,8 +120,9 @@ class SamplerReport:
             if rv_name in trace.varnames:
                 varnames.append(rv_name)
 
-        self._ess = ess = ess(trace, var_names=varnames)
-        self._rhat = rhat = rhat(trace, var_names=varnames)
+        idata = from_pymc3(trace, log_likelihood=False)
+        self._ess = ess = ess(idata, var_names=varnames)
+        self._rhat = rhat = rhat(idata, var_names=varnames)
 
         warnings = []
         rhat_max = max(val.max() for val in rhat.values())

pymc3/distributions/timeseries.py

@@ -12,6 +12,8 @@
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
 
+import warnings
+
 from scipy import stats
 import theano.tensor as tt
 from theano import scan

requirements.txt

-arviz>=0.4.1
+arviz>=0.7.0
 theano>=1.0.4
 numpy>=1.13.0
 scipy>=0.18.1
@@ -7,4 +7,4 @@ patsy>=0.5.1
 fastprogress>=0.2.0
 h5py>=2.7.0
 typing-extensions>=3.7.4
-contextvars; python_version < '3.7' 
+contextvars; python_version < '3.7'