add python test for sampling from GaussianConditional with a PRNG

python/gtsam/tests/test_GaussianBayesNet.py

@@ -23,11 +23,12 @@ _x_ = 11
 _y_ = 22
 _z_ = 33
 
+I_1x1 = np.eye(1, dtype=float)
+
 
 def smallBayesNet():
     """Create a small Bayes Net for testing"""
     bayesNet = GaussianBayesNet()
-    I_1x1 = np.eye(1, dtype=float)
     bayesNet.push_back(GaussianConditional(_x_, [9.0], I_1x1, _y_, I_1x1))
     bayesNet.push_back(GaussianConditional(_y_, [5.0], I_1x1))
     return bayesNet
@@ -51,8 +52,9 @@ class TestGaussianBayesNet(GtsamTestCase):
         values.insert(_x_, np.array([9.0]))
         values.insert(_y_, np.array([5.0]))
         for i in [0, 1]:
-            self.assertAlmostEqual(bayesNet.at(i).logProbability(values),
-                                   np.log(bayesNet.at(i).evaluate(values)))
+            self.assertAlmostEqual(
+                bayesNet.at(i).logProbability(values),
+                np.log(bayesNet.at(i).evaluate(values)))
         self.assertAlmostEqual(bayesNet.logProbability(values),
                                np.log(bayesNet.evaluate(values)))
 
@@ -66,6 +68,16 @@ class TestGaussianBayesNet(GtsamTestCase):
         mean = bayesNet.optimize()
         self.gtsamAssertEquals(sample, mean, tol=3.0)
 
+        # Sample with rng
+        rng = gtsam.MT19937(42)
+        conditional = GaussianConditional(_x_, [9.0], I_1x1)
+        # Sample multiple times and average to gey mean
+        val = 0
+        niters = 10000
+        for _ in range(niters):
+            val += conditional.sample(rng).at(_x_).item()
+        self.assertAlmostEqual(val / niters, 9.0, 2)
+
 
 if __name__ == "__main__":
     unittest.main()