#For Sensor and brain testbed expiriments
@use Braitenberg7.
#@use NeuralNetwork3.
@use NetworkServer.

@define PORT_NUM 2323.
@define MASTERHOST "192.168.0.100".
@define POP 4.                            #Maximum population
@define STATIC 20.                         #Maximum number of static blocks.
@define NCOUNT 20.                         #Brain size
@define AT_HOME 1.
@define LOAD 0.
@define SAVE 1.
@define TIME_C 10.

Controller TestBed.

BraitenbergControl2 : TestBed {
	+ variables:
		block(object).
		stimuli(object).
		sensor(object).
		Size(vector).
		temp(object).
		tempShape(object).

	+ to init:
		super init.
		block = new BraitenbergVehicle2.
                Size = (4.0, .75, 3.0).
                tempShape = (new Cube init-with size Size). 
                temp = new Segment.
                temp move to (0,6,0).
                temp set-shape to tempShape of Size.
                block add-body with temp.
                sensor = (block add-sensor at (2.0, .4, 1.65) of-kind 1 with-normal (1, 0, 0)).
                sensor set-start to 1.
                sensor add-kind of 2.
                sensor set-direction to (0, -1, 0).
                Size = (1, 1, 1).
           	tempShape = (new Cube init-with size Size). 
		stimuli = new Segment.
		stimuli move to ( -6,6, -4).
		stimuli set-color-integer to 1.		
                stimuli set-shape to tempShape of Size.
                block init-and-start-brain of NCOUNT.
	+ to iterate:
		block control at-time (self get-time).
                #self display-current-driver.
		super iterate.                

}
Data : Results {
    + variables:        
        fits (list).
    + to add-fitness of fit(double) at-trial t (int) of-run r (int) with-data-string stuff (string):
        tmp(list).
        push fit onto tmp.
        push t onto tmp.
        push r onto tmp.
        push stuff onto tmp.
        push tmp onto fits.
    + to get-total-trials:
        rtn(int).
        tmp(list).
        tmp = fits{|fits| - 1}.
        rtn = tmp{1}.
        return rtn.
    + to get-total-runs:
        rtn(int).
        tmp(list).
        tmp = fits{|fits| - 1}.
        rtn = tmp{2}.
        return rtn.
    + to get-average-fitness over-last trials(int):
        tot(double).
        n(int).
        tmp(list).
        for n = (|fits| - 1), n > (|fits| - trials), n--:{
            tmp = fits{n}.
            tot += tmp{0}.
        }
        return (tot / (trials - 1)).
    + to set-to fitness obj (list):
        fits = obj.       
    + to get-fits:
        return fits.
}