def main():
#define two players, chose gameType as the following: 1-implementation 1 (theoretical) ; 2 - implementation 2(practically form 1); 3 - implementation 3(practically form 2) - recommended
player1 = Player(10001, 25, 2, 1700.00, 1, game_Type=3)
player2 = Player(10001, 16, 17, 2500.00, 2, game_Type=3)
#set links between players. (They have to communicate one with each other)
player1.setNeighborPlayer(player2)
player2.setNeighborPlayer(player1)
#update gains
#player1.measureGains()
#player2.measureGains()
player1.setDirectGain(GainCalculations.getAverageGain(player1.coordinator_id, player1.tx_node.node_id, player1.rx_node.node_id, year=2013, month=8, day=23))
player1.setCrossGain(GainCalculations.getAverageGain(player1.coordinator_id, player2.tx_node.node_id, player1.rx_node.node_id, year=2013, month=8, day=23))
player2.setDirectGain(GainCalculations.getAverageGain(player2.coordinator_id, player2.tx_node.node_id, player2.rx_node.node_id, year=2013, month=8, day=23))
player2.setCrossGain(GainCalculations.getAverageGain(player2.coordinator_id, player1.tx_node.node_id, player2.rx_node.node_id, year=2013, month=8, day=23))
#if you want to see some info about players
player1.printPlayerInfo()
player2.printPlayerInfo()
#check convergence. See if the topology suits the game conditions
if not checkConvergence(player1.direct_gain, player2.cross_gain, player1.cross_gain, player2.direct_gain):
return
livePlot = gameLivePlot(player1, player2)
#start live plotting
livePlot.startPloting()
#start Power Allocation threads
player1.startGame()
player2.startGame()
time.sleep(3)
#trigger an event by changing the power of one player
player1.unbalance()
#wait for the threads to finish
while player1.powerAllocation.isAlive() or player2.powerAllocation.isAlive() or livePlot.is_alive():
time.sleep(3)
#if you want to plot the results
iterations.plotIterations(player1.player_number, player1.tx_node.node_id, player1.rx_node.node_id, player2.player_number, player2.tx_node.node_id, player2.rx_node.node_id, int(player1.cost), int(player2.cost), TruncatedValues=False, saveImage=True)
choice = raw_input("Do you want to start PlayerApp threads(sends packets continuously) - yes/no:")
if choice.lower() == "yes":
player1.playerApp.start()
player2.playerApp.start()
def bestResponseAsAFunctionOfRx():
player = Player(10001, 25, 2, 1000.00, 1)
#get gain measurements until 23 august
player.setDirectGain(GainCalculations.getAverageGain(player.coordinator_id, player.tx_node.node_id, player.rx_node.node_id, year=2013, month=8, day=23))
#find max Prx_dBm in which Bi > -55 dBm
Prx_dBm = -100
while True:
tmp_bi = getBi(player.cost, math.pow(10.00, Prx_dBm/10.00)*0.001, 10.00*math.log10(player.direct_gain))
if tmp_bi is None or tmp_bi<-55:
Prx_dBm-=0.001
break
Prx_dBm+=0.0001
#now plot results
plot.ioff()
plot.clf()
plot.grid()
plot.title("B%d=f(I+N)" %(player.player_number))
plot.xlabel("I+N [dBm]")
plot.ylabel("B%d [dBm]" %(player.player_number))
Prx_crt = Prx_dBm
Prx_inf = Prx_dBm-20
Prx_step = 0.001
Bi = []
Prx = []
while Prx_crt>=Prx_inf:
best_response = getBi(player.cost, math.pow(10.00, Prx_crt/10.00)*0.001, 10.00*math.log10(player.direct_gain))
Bi.append(best_response)
Prx.append(Prx_crt)
Prx_crt-=Prx_step
plot.plot(Prx, Bi, label = "h%d%d=%.1f dBm" %(player.player_number,player.player_number,10.00*math.log10(player.direct_gain)), linewidth = 2)
plot.axis([min(Prx)-1, max(Prx)+1, min(Bi)-1, max(Bi)+1])
leg = plot.legend(loc = 'upper right', fontsize = 18)
leg.get_frame().set_alpha(0.6)
plot.show()
