feature\1522:

Create random red agent behaviour.

tests/test_red_random_agent_behaviour.py

@@ -0,0 +1,74 @@
+from datetime import time, datetime
+
+from primaite.environment.primaite_env import Primaite
+from tests import TEST_CONFIG_ROOT
+from tests.conftest import _get_temp_session_path
+
+
+def run_generic(env, config_values):
+    """Run against a generic agent."""
+    # Reset the environment at the start of the episode
+    env.reset()
+    for episode in range(0, config_values.num_episodes):
+        for step in range(0, config_values.num_steps):
+            # Send the observation space to the agent to get an action
+            # TEMP - random action for now
+            # action = env.blue_agent_action(obs)
+            # action = env.action_space.sample()
+            action = 0
+
+            # Run the simulation step on the live environment
+            obs, reward, done, info = env.step(action)
+
+            # Break if done is True
+            if done:
+                break
+
+            # Introduce a delay between steps
+            time.sleep(config_values.time_delay / 1000)
+
+        # Reset the environment at the end of the episode
+        env.reset()
+
+    env.close()
+
+
+def test_random_red_agent_behaviour():
+    """
+    Test that hardware state is penalised at each step.
+
+    When the initial state is OFF compared to reference state which is ON.
+    """
+    list_of_node_instructions = []
+    for i in range(2):
+
+        """Takes a config path and returns the created instance of Primaite."""
+        session_timestamp: datetime = datetime.now()
+        session_path = _get_temp_session_path(session_timestamp)
+
+        timestamp_str = session_timestamp.strftime("%Y-%m-%d_%H-%M-%S")
+        env = Primaite(
+            training_config_path=TEST_CONFIG_ROOT / "one_node_states_on_off_main_config.yaml",
+            lay_down_config_path=TEST_CONFIG_ROOT / "one_node_states_on_off_lay_down_config.yaml",
+            transaction_list=[],
+            session_path=session_path,
+            timestamp_str=timestamp_str,
+        )
+        training_config = env.training_config
+        training_config.num_steps = env.episode_steps
+
+        # TOOD: This needs t be refactored to happen outside. Should be part of
+        # a main Session class.
+        if training_config.agent_identifier == "GENERIC":
+            run_generic(env, training_config)
+        all_red_actions = env.red_node_pol
+        list_of_node_instructions.append(all_red_actions)
+
+    # assert not (list_of_node_instructions[0].__eq__(list_of_node_instructions[1]))
+    print(list_of_node_instructions[0]["1"].get_start_step())
+    print(list_of_node_instructions[0]["1"].get_end_step())
+    print(list_of_node_instructions[0]["1"].get_target_node_id())
+    print(list_of_node_instructions[1]["1"].get_start_step())
+    print(list_of_node_instructions[1]["1"].get_end_step())
+    print(list_of_node_instructions[1]["1"].get_target_node_id())
+    assert list_of_node_instructions[0].__ne__(list_of_node_instructions[1])