def avoid_obstacle(self, obstacle_center, obstacle_outside):
"""
Function to avoid obstacles
need to take into account whether agents inside/outside the obstacle
moves the agent away from the boarder by distance equivalent to its size
:param obstacle_center: tuple (int,int), the center coordinates of the obstacle
:param obstacle_outside: boolean, defines whether the agents are inside or outside of the obstacle
"""
x, y = self.mask.get_size() #get the size of the boid
x_ob, y_ob = obstacle_center
if obstacle_outside: #agents outside the obstacle
if self.pos[0] >= x_ob:
self.pos[0] += x
else:
self.pos[0] -= x
if self.pos[1] >= y_ob:
self.pos[1] += y
else:
self.pos[1] -= y
else: #agents inside the obstacle:
if self.pos[0] <= x_ob:
self.pos[0] += x
else:
self.pos[0] -= x
if self.pos[1] <= y_ob:
self.pos[1] += y
else:
self.pos[1] -= y
#adjust the velocity by rotating it around
self.v = (helperfunctions.rotate(helperfunctions.normalize(self.v)) *
helperfunctions.norm(self.v))
def find_neighbor_separation(self,boid,neighbors): #show what works better
separate = np.zeros(2)
for idx in neighbors:
neighbor_pos = list(self.agents)[idx].pos
difference = boid.pos - neighbor_pos #compute the distance vector (v_x, v_y)
difference /= helperfunctions.norm(difference) #normalize to unit vector with respect to its maginiture
separate += difference #add the influences of all neighbors up
return separate/len(neighbors)
def avoid_obstacle(self):
"""
Function to avoid obstacles
need to take into account whether agents inside/outside the obstacle
moves the agent away from the boarder by distance equivalent to its size
"""
#adjust the velocity by rotating it around
self.v = (helperfunctions.rotate(helperfunctions.normalize(self.v)) *
helperfunctions.norm(self.v))
self.pos += self.v * 1.5