seeding and flipping any

Author: williambdean

pymc/tests/distributions/test_timeseries.py

@@ -835,8 +835,11 @@ class TestEulerMaruyama:
     @pytest.mark.parametrize("batched_param", [1, 2])
     @pytest.mark.parametrize("explicit_shape", (True, False))
     def test_batched_size(self, explicit_shape, batched_param):
+        RANDOM_SEED = 42
+        numpy_rng = np.random.default_rng(RANDOM_SEED)
+
         steps, batch_size = 100, 5
-        param_val = np.square(np.random.randn(batch_size))
+        param_val = np.square(numpy_rng.standard_normal(batch_size))
         if explicit_shape:
             kwargs = {"shape": (batch_size, steps)}
         else:
@@ -853,9 +856,9 @@ def sde_fn(x, k, d, s):
                 "y", dt=0.02, sde_fn=sde_fn, sde_pars=sde_pars, init_dist=init_dist, **kwargs
             )
 
-        y_eval = draw(y, draws=2)
+        y_eval = draw(y, draws=2, random_seed=RANDOM_SEED)
         assert y_eval[0].shape == (batch_size, steps)
-        assert not np.any(np.isclose(y_eval[0], y_eval[1]))
+        assert np.any(~np.isclose(y_eval[0], y_eval[1]))
 
         if explicit_shape:
             kwargs["shape"] = steps
@@ -873,7 +876,7 @@ def sde_fn(x, k, d, s):
                     **kwargs,
                 )
 
-        t0_init = t0.initial_point()
+        t0_init = t0.initial_point(seed=RANDOM_SEED)
         t1_init = {f"y_{i}": t0_init["y"][i] for i in range(batch_size)}
         np.testing.assert_allclose(
             t0.compile_logp()(t0_init),