TST: add test for transformed data rng consistency

Author: ariddell

pystan/tests/test_generated_quantities_seed.py

@@ -0,0 +1,53 @@
+from collections import OrderedDict
+import gc
+import os
+import tempfile
+import unittest
+
+import numpy as np
+
+import pystan
+from pystan._compat import PY2
+
+
+class TestGeneratedQuantitiesSeed(unittest.TestCase):
+    """Verify that the RNG in the transformed data block uses the overall seed.
+
+    See https://github.com/stan-dev/stan/issues/2241
+
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        model_code = """
+            data {
+              int<lower=0> N;
+            }
+            transformed data {
+              vector[N] y;
+              for (n in 1:N)
+                y[n] = normal_rng(0, 1);
+            }
+            parameters {
+              real mu;
+              real<lower = 0> sigma;
+            }
+            model {
+              y ~ normal(mu, sigma);
+            }
+            generated quantities {
+              real mean_y = mean(y);
+              real sd_y = sd(y);
+            }
+        """
+        cls.model = pystan.StanModel(model_code=model_code, verbose=True)
+
+    def test_generated_quantities_seed(self):
+        fit1 = self.model.sampling(data={'N': 1000}, iter=10, seed=123)
+        extr1 = fit1.extract()
+        fit2 = self.model.sampling(data={'N': 1000}, iter=10, seed=123)
+        extr2 = fit2.extract()
+        self.assertTrue((extr1['mean_y'] == extr2['mean_y']).all())
+        fit3 = self.model.sampling(data={'N': 1000}, iter=10, seed=456)
+        extr3 = fit3.extract()
+        self.assertFalse((extr1['mean_y'] == extr3['mean_y']).all())