void Explode()
{
Driver best_time_obj = GameObject.Find("Floor").GetComponent <Driver>();
TyroData data = GetComponent <TyroData>();
float average_score = total_score / total_times_scored;
if (average_score < data.current_tdata.best_score)//(data.current_tdata.best_time - (data.current_tdata.best_time * .3f) < Time.time - start_time)
{
//Debug.Log("New Best Time! \nOld Time: " + data.current_tdata.best_time + " - New Time: " + (Time.time - start_time));
Debug.Log("######### New best score: " + average_score + " - Old: " + data.current_tdata.best_score);
data.current_tdata.best_time = (Time.time - start_time);
data.current_tdata.best_score = average_score;
// Destroy the visualization for that car so they don't stack
data.Save();
}
else
{
Debug.Log("Score: " + average_score);
//current_tdata.current_tdata.best_time = (current_tdata.current_tdata.best_time * 10 + Time.time - start_time) / 11 ;
}
foreach (GameObject data_point in GameObject.FindGameObjectsWithTag("Datapoint"))
{
Destroy(data_point);
}
Destroy(this.gameObject);
}
// Use this for initialization
void Start()
{
learner = new OrdinaryLeastSquares()
{
UseIntercept = true
};
data = GetComponent <TyroData>();
car = GetComponent <CarMovement>();
// Now, we can use the learner to finally estimate our model:
if (Time.time > 10)
{
data.Mutate();
}
regression = learner.Learn(data.current_tdata.input.ToArray(), data.current_tdata.output.ToArray());
}
// Use this for initialization
void Start()
{
action = "Nothing";
data = GetComponent <TyroData>();
}