Jules - RL 2 Tests

[s2t2]

This commit introduces unit tests for parts of the reinforcement learning code added in PR google#98.

Here's a summary of what I did:

1. I reviewed PR Reinforcement Learning Module, Part 2 google/sbsim#98, analyzing changes related to new RL scripts (eval, gin generation), TD3/DDPG agents, and visualization.
2. I fetched the code from PR Reinforcement Learning Module, Part 2 google/sbsim#98.
3. I attempted to run the RL scripts:
   • generate_gin_config_files.py ran successfully.
   • train.py failed with a TypeError in tf_agents.policies.policy_saver.PolicySaver, which prevented training and a full evaluation of eval.py. This indicates an issue with the TF-Agents setup or its usage in the PR.
4. I created unit tests for:
   • smart_control/reinforcement_learning/scripts/generate_gin_config_files.py: These tests cover reading the base configuration, substituting parameters, and generating output files.
   • smart_control/reinforcement_learning/visualization/trajectory_plotter.py: These tests cover the plotting methods for actions, rewards, and cumulative rewards, including how timestamps and empty data are handled.

The tests for these two modules pass. I didn't pursue further testing of agent-specific code or environment wrappers due to the blocking issue with train.py and the TF-Agents environment.