def run_game():
#initialize game and create a dispaly object
pygame.init()
setting = Setting()
globalvar.init(setting)
pygame.display.set_caption("BB king")
globalvar.set_player(character.start_game(1, globalvar.screen))
# game loop
while True:
# supervise keyboard and mouse item
# change stat of objects
check_event()
update_screen(setting)
#httpd.shutdown()
def SvcStop(self):
global httpd
self.logger.info("service is stop....")
self.ReportServiceStatus(win32service.SERVICE_STOP_PENDING)
win32event.SetEvent(self.hWaitStop)
self.run = False
WebAPI.recordLog("Service stop ...")
#停止http服务
httpd.shutdown()
if __name__=='__main__':
gl.init()
gl.setvalue('version', 'v0.17')
## port = 9999
## httpd = make_server("0.0.0.0",port,WebAPI.application)
## print ("Health serving http on port {0}...".format(str(port)))
## httpd.serve_forever()
port = 9999
httpd = make_server("0.0.0.0",port,WebAPI.application)
if len(sys.argv) == 1:
try:
evtsrc_dll = os.path.abspath(servicemanager.__file__)
servicemanager.PrepareToHostSingle(PythonService)
servicemanager.Initialize('PythonService', evtsrc_dll)
servicemanager.StartServiceCtrlDispatcher()
import character import globalvar import Setting setting = Setting.Setting() globalvar.init(setting) character.start_game(1, globalvar.screen) player = globalvar.player() print(len(player)) character.add_character() player = globalvar.player() print(len(player))
def __init__(self, flow_size_list, MAX_EPISODES):
super().__init__()
gl.init()
self.flow_size_list = flow_size_list
self.MAX_EPISODES = MAX_EPISODES
# if the model is 'GCN' or 'GAT', undo this comment
# output = model(features, adj)
loss_test = F.nll_loss(output[idx_test], labels[idx_test])
acc_test = accuracy(output[idx_test], labels[idx_test])
# save GNN model
if train_flag:
torch.save(model, "./loads/GNN_model")
print("Test set results:",
"loss= {:.4f}".format(loss_test.item()),
"accuracy= {:.4f}".format(acc_test.item()))
if __name__ == "__main__":
gol.init()
gol.set_value('aggr_units_num', 4)
# Training settings
parser = argparse.ArgumentParser()
parser.add_argument('--no-cuda', action='store_true', default=False, help='Disables CUDA training.')
parser.add_argument('--trainmode', action='store_true', default=False, help='Enable training.')
parser.add_argument('--seqgenflag', action='store_true', default=False, help='Enable generating compute sequence.')
parser.add_argument('--fastmode', action='store_true', default=False, help='Validate during training pass.')
parser.add_argument('--dataset', type=str, default='citeseer', help='Select a dataset.')
parser.add_argument('--model', type=str, default='GCN', help='Select GNN model.')
# general paras
parser.add_argument('--seed', type=int, default=42, help='Random seed.')
parser.add_argument('--epochs', type=int, default=5, help='Number of epochs to train.')
parser.add_argument('--lr', type=float, default=0.1, help='Initial learning rate.')
parser.add_argument('--weight_decay', type=float, default=5e-4, help='Weight decay (L2 loss on parameters).')
parser.add_argument('--hidden', type=int, default=16, help='Number of hidden units.')
datas = msg.replace('$', '').replace('#', '').split(';')
if len(datas) >= 10:
yaw = float(datas[3])
speed = float(datas[7])
elif msg.startswith('&') and msg.endswith('#'):
datas = msg.replace('&', '').replace('#', '').split(';')
gz = float(datas[0])
except KeyboardInterrupt:
break
except Exception:
continue
ser.close()
if __name__ == '__main__':
g.init()
# 开启串口接收线程
thread.start_new_thread(serial_recv_thread, ())
# 开启RTK线程
thread.start_new_thread(ntrip.fun, ())
# 等待定位成功
while g.getValue('lat') == None or g.getValue('lat') == 0:
time.sleep(1)
pass
logging.info('已定位')
# 获取导航点
getPoints('gps.csv')
if len(sidePoints) > 1:
logging.info('已加载导航点，共有%d个点' % len(sidePoints))
index = 0
pos = Point(g.getValue('lat'), g.getValue('lng'))