def addBoid(self, x, y):
self.n += 1
vx, vy = uniform(-1, 1), uniform(-1, 1)
#s = self.dist(0, 0, vx, vy)
#if s>MAX_SPEED or s<MIN_SPEED:
# vx, vy = self.unit(vx, vy)
# vx *= MAX_SPEED
# vy *= MAX_SPEED
self.boids.append(boid.Boid(x, y, vx, vy))
def __init__(self, size):
self.bocal = 800
self.size = size
self.boids = [boid.Boid(self.bocal) for i in range(0, self.size)]
self.root = tkinter.Tk()
self.canvas = tkinter.Canvas(self.root,
width=self.bocal,
height=self.bocal,
background='white')
self.canvas.pack()
def __init__(self):
self.gfx = gfx.Gfx()
object_collection.ObjectCollection.all_boids = []
for i in range(100):
object_collection.ObjectCollection.all_boids.append(boid.Boid())
object_collection.ObjectCollection.all_predators = []
for i in range(0):
object_collection.ObjectCollection.all_predators.append(
predator.Predator())
self.run()
def initVars(self, startPoint, endPoint, flockSize, **kwargs):
"""
Parses the file to get the obstacle list. Creates a PRM generator to
create a global map of the environment. Gets the list of intermediate
goals. Also, creates the list of boids used in the simulation
@param startPoint The starting point for the boids
@param endPoint The ending point for the boids
@param flockSize The size of the flock (number of boids)
@param filename The name of the file that contains the environment map
"""
## List of obstacles
# parse static obstalces
self.obstacleList = mp.mparse(kwargs.get("map_file", "maps/m1.map"))
# parse dynamic obstalces
dynamic_obstacles_fp = kwargs.get("dynamic_obstacles", None)
self.parseDynamicObstacles(dynamic_obstacles_fp)
# auto geneate dynamic obstacles
self.auto_gen_obst = kwargs.get("auto_gen_obst", False)
self.auto_gen_number = kwargs.get("auto_gen_number", 0)
if self.auto_gen_obst:
self.autoGenerateDynamicObstacles(startPoint, endPoint)
## Starting point
self.startPoint = startPoint
## Ending point
self.endPoint = endPoint
## Object containing variables and mehtods for the global planner
self.prmGen = PRMGenerator(startPoint, endPoint, self.obstacleList,
Configuration.xSize, Configuration.ySize,
Configuration.numSamplePoints,
Configuration.screen)
## List of intermediate goals derived by the global planner
self.goalList = self.prmGen.generate(Configuration.goalRadius)
## List of boids in the flock
self.boidList = [
boid.Boid(startPoint, endPoint, Configuration.boidSpeed,
Configuration.xSize, Configuration.ySize,
Configuration.numNeighbours, boid.guassianFunc,
self.obstacleList, self.goalList, self.prmGen,
Configuration.screen, Configuration.colorList[i],
Configuration.boid_radius,
self.determinePositionInConfig(i, flockSize, startPoint))
for i in range(flockSize)
]
def make_babies(self, location):
for _ in range(
random.randint(Settings.minimum_number_of_babies,
Settings.maximum_number_of_babies)):
baby_location = pygame.Vector2(
location.y + random.randint(-Settings.maximum_baby_distance,
Settings.maximum_baby_distance),
location.x + random.randint(-Settings.maximum_baby_distance,
Settings.maximum_baby_distance),
)
self.boids.append(
boid.Boid(self,
location=baby_location,
velocity=pygame.Vector2(0, -3),
age=0))
def main():
world_turtle = turtle.Turtle()
screen = world_turtle.getscreen()
screen.setworldcoordinates(0, 0, WIDTH - 1, HEIGHT - 1)
screen.tracer(NUM_BIRDS)
world_turtle.hideturtle()
sky = w.World(WIDTH, HEIGHT) # create the world
for index in range(NUM_BIRDS): # create the boids in myworld=sky
bird = b.Boid(sky)
for step in range(ITERATIONS): # run the simulation
sky.step_all()
screen.update()
screen.exitonclick()
def startsim(self):
'''
makes objects for the given amount
as stated in the PARAMETERS file
'''
for i in range(BOIDNUMBERS):
bird = boid.Boid(BOIDSIZE, BOIDMAXSPEED)
boid.Boid.boidlist.append(bird)
for i in range(HOIKNUMBERS):
eagle = boid.Hoik(HOIKSIZE, HOIKMAXSPEED)
boid.Hoik.hoiklist.append(eagle)
for i in range(OBJECTNUMBERS):
object = boid.Hindrance()
boid.Hindrance.hindrancelist.append(object)
X_GOAL = 1100
Y_GOAL = 100
#weights for further calibration
WEIGHT_OPTIMAL = 0.8 #temporary, most likely 1 minus the other two weights
WEIGHT_OBSTACLE = 0.1 #this will use the inverse
WEIGHT_BOID = 0.1
#the boids will only take the effort to avoid the boid nearest to it
#coords and dimensions for rectangular obstacle
OB_X = 450
OB_Y = 450
OB_WIDTH = 300
OB_HEIGHT = 300
burd = boid.Boid(X_START, Y_START, X_GOAL, Y_GOAL)
navigateBoid(burd)
#define window height and width
gameWindow = pyglet.window.Window(width=WIDTH, height=HEIGHT)
#this can easily not be a global dude fix it
boidStillFlying = True
#pyglet.resource.path = ['/Users/kai/Documents/SNNProject']
#pyglet.resource.reindex()
#boid_image = ("boid.png")
boidSprite = pyglet.sprite.Sprite(
img=pyglet.image.load('/Users/kai/Documents/SNNProject/src/boid.png'),
for i in range(SCREEN_WIDTH // partitionSizeX):
partitions.append([])
for j in range(SCREEN_HEIGHT // partitionSizeY):
partitions[i].append([])
while run:
delta = clock.tick(30)
boidSpawnTimer -= delta / 1000
if len(boids) < max_boids and boidSpawnTimer <= 0:
boids.append(
boid.Boid(SCREEN_WIDTH // 2, SCREEN_HEIGHT // 2,
random.random() * 2 - 1,
random.random() * 2 - 1, SCREEN_WIDTH, SCREEN_HEIGHT,
(random.randrange(1, 255), random.randrange(
1, 255), random.randrange(1, 255))))
boidSpawnTimer = boidSpawnTimerResetValue
print(len(boids))
for event in pygame.event.get():
if event.type == pygame.QUIT:
run = False
draw()
update()
#print(1000 / delta)
#Groups to hold all sprites
boidGroup = pygame.sprite.Group()
"""
============================= Game Loop ================================
"""
while not quit:
clock.tick(30)
# All events (mouse and keyboard)
for event in pygame.event.get():
if event.type == pygame.QUIT:
quit = True
if event.type == pygame.MOUSEBUTTONDOWN:
boidGroup.add(boid.Boid("boid.png", pygame.mouse.get_pos()[0], pygame.mouse.get_pos()[1]))
#Clear the screen
screen.fill((255,255,255))
#update sprites
for eachBoid in range(len(boidGroup.sprites())):
list = boidGroup.sprites()
list.pop(eachBoid)
boidGroup.sprites()[eachBoid].update(screen, list)
#Draw sprites
boidGroup.draw(screen)
#Display the next screen
pygame.display.flip()