Modify .rst docs for density estimation to match tutorials

docs/algorithms/density.rst

@@ -43,12 +43,24 @@ Detailed example notebook: :doc:`../tutorials/7_train_density`
     env = util.make_vec_env("Pendulum-v1", rng=rng, n_envs=2)
     rollouts = serialize.load("../tests/testdata/expert_models/pendulum_0/rollouts/final.npz")
 
-    imitation_trainer = PPO(ActorCriticPolicy, env)
+    imitation_trainer = PPO(
+        ActorCriticPolicy,
+        env,
+        learning_rate=3e-4,
+        gamma=0.95,
+        ent_coef=1e-4,
+        n_steps=2048
+    )
     density_trainer = db.DensityAlgorithm(
         venv=env,
+        rng=rng,
         demonstrations=rollouts,
         rl_algo=imitation_trainer,
-        rng=rng,
+        density_type=db.DensityType.STATE_ACTION_DENSITY,
+        is_stationary=True,
+        kernel="gaussian",
+        kernel_bandwidth=0.4,
+        standardise_inputs=True,
     )
     density_trainer.train()
 
@@ -63,7 +75,7 @@ Detailed example notebook: :doc:`../tutorials/7_train_density`
     print("Stats before training:")
     print_stats(density_trainer, 1)
 
-    density_trainer.train_policy(100)
+    density_trainer.train_policy(100)  # Train for 1_000_000 steps to approach the expert.
 
     print("Stats after training:")
     print_stats(density_trainer, 1)