def init_connection(self):
"""Initialize variables that are local to a connection, (needed if the client automatically reconnect)"""
self.ready_lock.acquire(
False) # reacquire the ready-lock in case of reconnection
self.connected = PYMUMBLE_CONN_STATE_NOT_CONNECTED
self.control_socket = None
self.media_socket = None # Not implemented - for UDP media
self.bandwidth = PYMUMBLE_BANDWIDTH # reset the outgoing bandwidth to it's default before connectiong
self.server_max_bandwidth = None
self.udp_active = False
self.users = users.Users(
self, self.callbacks
) # contain the server's connected users informations
self.channels = channels.Channels(
self, self.callbacks) # contain the server's channels informations
self.blobs = blobs.Blobs(self) # manage the blob objects
self.sound_output = soundoutput.SoundOutput(
self, PYMUMBLE_AUDIO_PER_PACKET,
self.bandwidth) # manage the outgoing sounds
self.commands = commands.Commands(
) # manage commands sent between the main and the mumble threads
self.receive_buffer = "" # initialize the control connection input buffer
def run_game():
pygame.init()
ai_settings = Settings()
#创建屏幕
screen = pygame.display.set_mode(
(ai_settings.screen_width, ai_settings.screen_height))
pygame.display.set_caption("Supreme Commander Kim VS Trump")
#创建一艘飞船
player = Player(screen)
#创建n个blob
my_blobs = blobs.Blobs()
my_blobs.generate_blob(ai_settings, screen, player,
ai_settings.blob_num_init)
while True:
#对各个事件做出反应
gf.check_events(player, my_blobs, ai_settings)
#更新屏幕
if player.life_value > 0:
gf.update_screen(ai_settings, screen, player, my_blobs)
else:
screen.fill([0, 0, 0])
pygame.display.flip()
# Format data and merge on shapefile IDs
ordered_blocks = pd.DataFrame(
df.loc[:, ['geoid10', 'tract_bloc', 'Pop', 'order']])
ordered_blocks.sort(['order'])
crime_hour_tables = []
for i in range(24):
hourlyTable = pd.merge(crime_hour[i],
ordered_blocks,
how='right',
left_on='geoid10',
right_on='geoid10',
sort=False).fillna(0).sort(['order'])
hourlyTable = hourlyTable.drop(['order', 'hour'], 1)
crime_hour_tables.append(hourlyTable)
i = 0
print i
class bd:
data = crime_hour_tables[i]
w = w
shp_link = shp_link
id = 'geoid10'
level = 'block'
d = bd()
b = blobs.Blobs(d, 'Pop', 1000, plot=False, iterations=1)
b.generate_shapefile(filename='blob_hour_test_0_1000.shp')
### script to test blobs ### contributors: [email protected] ### 6/18/15 import blobs # tract level d = blobs.Blobs_Data('Chicago Census.csv', 'tract', 'tracts/CensusTractsTIGER2010.shp', 'tractce10', [ 'crimes_2001_to_present', '311_service_requests_vacant_and_abandoned_building', '311_service_requests_rodent_baiting' ]) b = blobs.Blobs(d, 'pop', 10000) # block level d = blobs.Blobs_Data('Chicago Census.csv', 'block', 'blocks/CensusBlockTIGER2010.shp', 'geoid10', [ 'crimes_2001_to_present', '311_service_requests_vacant_and_abandoned_building', '311_service_requests_rodent_baiting' ]) b = blobs.Blobs(d, 'pop', 10000) cl = blobs.Cluster_blobs(b, blobs_per_cluster=10) # the following will let you get started immediately on pre-downloaded data import numpy as np import pandas as pd import pysal as ps shp_link = 'tracts/CensusTractsTIGER2010.shp' dbf = ps.open('tracts/CensusTractsTIGER2010.dbf')