def analyze_directional_state_models(models, states, rewards, params):
current_models, current_states, current_rewards = \
filter_models_with_rewards_by_state(models, states, rewards,
lambda state: state.startswith("Directional") and
not state.startswith("DirectionalDistance"))
plot_model_analysis(current_models, current_rewards, "directional_state",
params)
def analyze_aggregated_models(filenames, models, params):
order = list(np.argsort(filenames))
filenames = [filenames[i] for i in order]
models = [models[i] for i in order]
states = []
for filename in filenames:
states.append(filename.split("_")[0])
plot_model_analysis(models, states, "all", params)
def analyze_board_state_models(models, states, rewards, params):
current_models, current_states, current_rewards = \
filter_models_with_rewards_by_state(models, states, rewards,
lambda state: state.startswith("Board"))
plot_model_analysis(current_models, current_rewards, "board_state", params)
def analyze_state_with_score_without_dim_models(models, states, params): current_models, current_states = \ filter_models_by_state(models, states, lambda state: "Score" in state and "Dimension" not in state) plot_model_analysis(current_models, current_states, "score", params)
def analyze_state_with_score_models(models, states, params): current_models, current_states = \ filter_models_by_state(models, states, lambda state: "Score" in state) plot_model_analysis(current_models, current_states, "score_dim", params)
def analyze_snake_food_state_models(models, states, params):
current_models, current_states = \
filter_models_by_state(models, states,
lambda state: state.startswith("SnakeFood"))
plot_model_analysis(current_models, current_states, "snake_food_state", params)