def interaction(z):
robot_j = robots[pairwise_list[z][0][0]-1]
rho_j= pairwise_list[z][0][1] #pair number
robot_k= robots[pairwise_list[z][1][0]-1]
rho_kk = pairwise_list[z][1][1]
xj,yj=update_pairwisedistance(robot_j,rho_j,robot_k,rho_kk,times,mu,win,robots)
robot_j.move(xj,yj)
def robot_movement(robots, particles, robot_id, times, mu, win):
lock.acquire()
pairwise_list = random.sample(particles, 1)
robot_j = robots[particles[robot_id - 1][0] - 1]
rho_j = particles[robot_id - 1][1]
robot_k = robots[pairwise_list[0][0] - 1]
rho_k = pairwise_list[0][1]
xj, yj = update_pairwisedistance(robot_j, rho_j, robot_k, rho_k, times, mu,
win, robots)
lock.release()
robot_j.move(xj, yj)
for i in range(1, N + 1, 1):
particles.append([i, rho_k[i - 1]])
#pairwise_list= list(combinations(particles,2))
pairwise_list = random.sample(particles, 2)
#mt_shuffle()
step = 0
while (1): #replace with energy function
pairwise_list = random.sample(particles, 2)
robot_j = robots[pairwise_list[0][0] - 1]
rho_j = pairwise_list[0][1]
robot_k = robots[pairwise_list[1][0] - 1]
rho_kk = pairwise_list[1][1]
xj, yj, xk, yk, x_newj, y_newj, x_newk, y_newk = update_pairwisedistance(
robot_j, rho_j, robot_k, rho_kk, times, mu, win)
robot_j.move(xj, yj)
#robot_k.move(xk,yk)
#for z in range(len(pairwise_list)):
# pairwise_list = random.sample(particles, 2)
# robot_j = robots[pairwise_list[0][0]-1]
# rho_j= pairwise_list[0][1]
# robot_k= robots[pairwise_list[1][0]-1]
# rho_kk = pairwise_list[1][1]
# print(robots[pairwise_list[z][0][0]-1])
# print(robots[pairwise_list[z][1][0]-1])
# xj,yj,xk,yk,x_newj,y_newj,x_newk,y_newk=update_pairwisedistance(robot_j,rho_j,robot_k,rho_kk,times,mu,win)
#time.sleep(100)
#robots[pairwise_list[z][0][0]-1].move(xj + win.getWidth()/2,(win.getHeight()/2) - yj) # move bot to new position
#robots[pairwise_list[z][1][0]-1].move(xk + win.getWidth()/2,(win.getHeight()/2) - yk)
# robot_j.move(xj,yj) # move bot to new position
Uma_knot=0
while(((np.abs(du))>epsilon) and ((np.abs(dUma))>epsilon)):
objective_func = AverageMeter()
averageobjective_func= AverageMeter()
#previous Uma
interaction=1
while(interaction!=combination):
print("Interaction : %d Step: %d",interaction,step)
pairwise_list = random.sample(particles, 2)
robot_j = robots[pairwise_list[0][0]-1]
rho_j= pairwise_list[0][1]
robot_k= robots[pairwise_list[1][0]-1]
rho_kk = pairwise_list[1][1]
xj,yj=update_pairwisedistance(robot_j,rho_j,robot_k,rho_kk,times,mu,win,robots)
robot_j.move(xj,yj)
interaction = interaction+1
# print("du/dt",du)
if step==0:
total_relativedist=total_relativedistance(robots,win,N)
averageinterparticledist= (1/combination)*total_relativedist
U_knot= averageinterparticledist- rho_kmean
U=U_knot
du=U
#xk,yk,x_newj,y_newj,x_newk,y_newk
Uma.append(U) #average list
Uma_knot=np.mean(Uma)
if step>0:
total_relativedist=total_relativedistance(robots,win,N)
