Merge pull request #323 from ariddell/feature/release-2.15

Updates before PyStan 2.15

Author: ariddell

pystan/model.py

@@ -245,10 +245,10 @@ def __init__(self, file=None, charset='utf-8', model_name="anon_model",
             lib_dir,
             pystan_dir,
             os.path.join(pystan_dir, "stan", "src"),
-            os.path.join(pystan_dir, "stan", "lib", "stan_math"),
-            os.path.join(pystan_dir, "stan", "lib", "stan_math", "lib", "eigen_3.2.9"),
-            os.path.join(pystan_dir, "stan", "lib", "stan_math", "lib", "boost_1.62.0"),
-            os.path.join(pystan_dir, "stan", "lib", "stan_math", "lib", "cvodes_2.9.0", "include"),
+            os.path.join(pystan_dir, "stan", "lib", "stan_math_2.15.0"),
+            os.path.join(pystan_dir, "stan", "lib", "stan_math_2.15.0", "lib", "eigen_3.2.9"),
+            os.path.join(pystan_dir, "stan", "lib", "stan_math_2.15.0", "lib", "boost_1.62.0"),
+            os.path.join(pystan_dir, "stan", "lib", "stan_math_2.15.0", "lib", "cvodes_2.9.0", "include"),
             np.get_include(),
         ]
 

pystan/stan

@@ -4,19 +4,20 @@
 import pystan.chains
 import pystan._chains
 
-# NOTE: This test is fragile because there is no guarantee that samples are
-# consistent between Stan releases (even with fixed random seeds).  Consider
-# this a smoke test.
+# NOTE: This test is fragile because the default sampling algorithm used by Stan
+# may change in significant ways.
+
 
 class TestESS(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
         model_code = 'parameters {real y;} model {y ~ normal(0,1);}'
-        model = pystan.StanModel(model_code=model_code, model_name="normal2")
-        cls.fit = model.sampling(iter=4000, chains=2, seed=5)
+        model = pystan.StanModel(model_code=model_code)
+        cls.fits = [model.sampling(iter=4000, chains=2, seed=i) for i in range(10)]
 
     def test_ess(self):
-        sim = self.fit.sim
-        ess = pystan.chains.ess(sim, sim['fnames_oi'].index('y'))
-        self.assertGreater(ess, 2000)
+        sims = [fit.sim for fit in self.fits]
+        esses = [pystan.chains.ess(sim, sim['fnames_oi'].index('y')) for sim in sims]
+        # in Stan 2.15 the default acceptance rate was changed, ess dropped
+        self.assertGreater(sum(esses) / len(esses), 1200)

pystan/tests/test_ess.py

@@ -16,7 +16,7 @@ def test_init_zero_exception_inf_grad(self):
             real x;
         }
         model {
-            lp__ <- 1 / log(x);
+            target += 1 / log(x);
         }
         """
         sm = StanModel(model_code=code)

pystan/tests/test_rstan_stanfit.py

@@ -99,10 +99,10 @@ def find_version(*parts):
 from distutils.extension import Extension
 
 stan_include_dirs = ['pystan/stan/src',
-                     'pystan/stan/lib/stan_math/',
-                     'pystan/stan/lib/stan_math/lib/eigen_3.2.9',
-                     'pystan/stan/lib/stan_math/lib/boost_1.62.0',
-                     'pystan/stan/lib/stan_math/lib/cvodes_2.9.0/include']
+                     'pystan/stan/lib/stan_math_2.15.0/',
+                     'pystan/stan/lib/stan_math_2.15.0/lib/eigen_3.2.9',
+                     'pystan/stan/lib/stan_math_2.15.0/lib/boost_1.62.0',
+                     'pystan/stan/lib/stan_math_2.15.0/lib/cvodes_2.9.0/include']
 stan_macros = [
     ('BOOST_RESULT_OF_USE_TR1', None),
     ('BOOST_NO_DECLTYPE', None),