def main():
'''
i: Iterating variable
nt: Maximum timesteps
'''
print("Reading parameters and variables")
init.init()
print("Initialization finished. Start calculation.")
#print(var.h[:,:,0])
for i in range(1, param.nt):
print("Integrating for timesstep t = " + str(i) + " of " +
str(param.nt - 1))
swe_rk4.__init__()
swe_rk4.swe_rk4(i)
dio.output_netcdf()
print("Simulation all completed. Enjoy your work!")
def basic():
#INITIALIZATION
#schedules initialization
S = ini.init()
#map initialization
mapp = {}
for user_id in S:
mapp[user_id] = []
#loop to create an event and do feedback
# pprint(S)
events = ev.generateEvents(S,mapp)
# S_copy = S.copy()
S_copy = ev.placeEvents(copy.deepcopy(S), events, mapp)
pprint(S)
# pprint(S_copy)
pprint(events)
ap.assignment(S,events)
import initialization as ini
import exchs_data
import matching
import json
import random
from pprint import pprint
botconf = json.load(open('bot_config.json'))
pairs = botconf['symbols']
limit = botconf['limit']
conffile = botconf['config_file']
exchsfile = botconf['exchs_credentials']
exchs, minvolumes = ini.init(pairs, conffile, exchsfile)
while True:
balances = ini.get_balances(pairs, conffile)
order_books = exchs_data.get_order_books(pairs, limit, conffile)
for key in balances.keys():
for kkey in balances[key].keys():
balances[key][kkey] = random.randint(0, 10000)
pprint(balances)
our_orders = matching.get_arb_opp(order_books, balances)
pprint(our_orders)
break
def main(argv):
try:
opts, args = getopt.getopt(argv, "his:lr:g:t",
["init", "store=", "list"])
except getopt.GetoptError:
logger.error(getopt.GetoptError)
print("Must be in the following format")
print(
"Options are [-i or --init to initialize and create backup folder]"
)
print(
" [-s or --store <directory_path> to create a backup of directory in backup folder]"
)
print(
" [-r or --restore <destination_directory> to restore entire backup into destination]"
)
print(
" [-l or --list to list all files currently in backup folder]"
)
print(
" [-g or --get <'filename'> restores individual file to current directory]"
)
print(" [-t Tests for errors in the archive]")
sys.exit()
for opt, arg in opts:
if opt == "-h":
print(
"Options are [-i or --init to initialize and create backup folder]"
)
print(
" [-s or --store <directory_path> to create a backup of directory in backup folder]"
)
print(
" [-r or --restore <destination_directory> to restore entire backup into destination]"
)
print(
" [-l or --list to list all files currently in backup folder]"
)
print(
" [-g or -get <'filename'> restores individual file to current directory]"
)
print(" [-t or Tests for errors in the archive]")
sys.exit()
elif opt in ("-i", "--init"):
initialization.init(myArchive, logger)
elif opt in ("-l", "--list"):
list_all_items()
elif opt in ("-r", "--restore"):
restore_files(arg)
elif opt in ("-s", "--store"):
print("Store")
stored_directory = arg
update_index()
store.store_backup(stored_directory)
elif opt in "-t":
test()
elif opt in ("-g" or "--get"):
if not type(arg) is str:
print("-g or --get <'filename'> (filename must be in quotes)")
sys.exit()
get_file(arg)
else:
logger.error("Command not found, type -h for help")
def test(RTS_enable, suspend_enable, reserved_data_size, d_max):
PRAWs_duration = 5.3 * 1000
BI = 500 * 1000
#STA_number=20
CWmin = 16
CWmax = 16 * (2**6) # 1024
#packet_arrival_rate=1.0/150000 #in us
end_time = 10**7 * 2
data_size = reserved_data_size #in bytes, this parameter is also need to be changed in packets.py
STA_list = []
radius = 1000
amount = 500 # the total number of stations, it is used to read the corresponding files
# d_max=1900
for times in range(20):
print("system end time=" + str(end_time))
############## initialization ###########
timer = system_timer.SystemTimer(end_time)
# file=open("./results/d_max="+str(d_max)+"_amount="+str(amount)+"/CWmax="+str(CWmax)+\
# "_suspend="+str(suspend_enable)+"_round="+str(times)+"_new.txt","w")
folder_name = "./results/d_max=" + str(d_max) + "_amount=" + str(
amount)
if not os.path.isdir(folder_name):
os.makedirs(folder_name)
file = open(
folder_name + "/data_size=" + str(data_size) + "_round=" +
str(times) + ".txt", "w")
# file=open("./results/CWmax/CWmax="+str(CWmax)+\
# "_suspend="+str(suspend_enable)+"_round="+str(times)+".txt","w")
# file=open("./results/d_max="+str(d_max)+"_amount="+str(amount)+"/CWmax=unlimited"+"_suspend="+str(suspend_enable)+"_round="+str(times)+".txt","w")
statistics_collection.collector.set_output_file(file)
system_channel = channel.channel()
system_AP, STA_list = initialization.init(amount,
d_max,
timer,
RTS_enable,
suspend_enable,
CWmax,
system_channel,
data_size=data_size)
system_AP.block_list = initialization.AID_assignment(STA_list)
system_channel.register_devices(STA_list + [system_AP])
system_AP.channel = system_channel
system_AP.max_data_size = reserved_data_size
statistics_collection.collector.end_time = end_time
############# excute the simualtion ####################
while timer.events: #simulation starts
current_events = timer.get_next_events()
for each_event in current_events:
if each_event.type != "backoff":
print("The event type is " + each_event.type + " at " +
str(timer.current_time))
if each_event.time > timer.end_time: # end the pragram
break
each_event.execute(STA_list + [system_AP], timer,
system_channel) #### !!!!!
if each_event.type != "backoff":
counter = []
for each in STA_list: # how many STAs stay awake
if each.status != "Sleep":
counter.append(each.AID)
print("There are " + str(counter.__len__()) +
" STAs stays awake at " + str(timer.current_time))
counter = []
backoff_timer = []
for each in STA_list:
if not (each.backoff_status == "Off" or not each.queue
or each.status != "Listen"):
counter.append(each.AID)
backoff_timer.append(each.backoff_timer)
print("There are " + str(counter.__len__()) +
" STAs are competing for the channel at " +
str(timer.current_time))
print("The backoff timers are " + str(backoff_timer) +
"\n ")
if statistics_collection.collector.number_of_packet == statistics_collection.collector.successful_transmissions.__len__(
): # stop the simulation
if not [
x
for x in timer.events if x.type == "Polling round end"
]:
statistics_collection.collector.end_time = timer.current_time
timer.events = []
# for each in STA_list:
# if each.has_pending_packet():
# statistics_collection.collector.register_backoff_times(each.number_of_attempts,each.number_of_backoffs)
if system_channel.packet_list: # renew the channel busy time
statistics_collection.collector.channel_busy_time += timer.end_time - statistics_collection.collector.last_time_idle
statistics_collection.collector.print_statistics_of_delays()
statistics_collection.collector.print_polling_info()
statistics_collection.collector.print_other_statistics(
end_time, data_size)
statistics_collection.collector.clear()
os.system('cls' if os.name == 'nt' else 'clear')
file.close()
""" import initialization import evaluation import survivor_selection import parent_selection import recombination import constraints from visulization import Visulization import matplotlib.pyplot as plt import time import os import random # Call the initialization script to collect configuration data from csv files and build the # population for generation 0 init_items = initialization.init(constraints.pop_size) pop = init_items[0] courses = init_items[1] rooms = init_items[2] profs = init_items[3] times = init_items[4] best_fitness = 0 generation = constraints.numgenmax viable_gen = -1 record_fitness = 0 fit_log = [] # Visualization setup plt.show() axes = plt.gca()
def test(d_max, threshold, detection_time):
end_time = 10**7
packet_size = 100
STA_list = []
amount = 500
CWmax = 1024
for times in range(10):
sys.stdout = open("log_file_Thr=" + str(threshold) + ".txt", 'w')
timer = system_timer.SystemTimer(end_time)
folder_name = "./Parameter_test/Thr=" + str(threshold) + "_T=" + str(
detection_time / 10**3)
if not os.path.isdir(folder_name):
os.makedirs(folder_name)
file = open(
folder_name + "/d_max=" + str(d_max) + "_round=" + str(times) +
".txt", 'w')
statistics_collection.collector.set_output_file(file)
system_channel = channel.channel()
AP, STA_list = initialization.init(amount, d_max, timer, False, False,
CWmax, system_channel, threshold,
detection_time)
AP.block_list = initialization.AID_assignment(STA_list)
system_channel.register_devices(STA_list + [AP])
AP.channel = system_channel
AP.max_data_size = packet_size
statistics_collection.collector.end_time = end_time
################# start the simulation ##################
while timer.events:
current_events = timer.get_next_events()
for each_event in current_events:
if each_event.type != "backoff":
print("The event type is " + each_event.type + " at " +
str(timer.current_time))
if each_event.time > timer.end_time:
break
each_event.execute(STA_list + [AP], timer, system_channel)
if each_event.type != "backoff":
counter = []
for each in STA_list: # how many STAs stay awake
if each.status != "Sleep":
counter.append(each.AID)
print("There are " + str(counter.__len__()) +
" STAs stays awake at " + str(timer.current_time))
counter = []
backoff_timer = []
for each in STA_list:
if not (each.backoff_status == "Off" or not each.queue
or each.status != "Listen"):
counter.append(each.AID)
backoff_timer.append(each.backoff_timer)
print("There are " + str(counter.__len__()) +
" STAs are competing for the channel at " +
str(timer.current_time) + "\n")
# print("The backoff timers are "+str(backoff_timer)+"\n ")
if (statistics_collection.collector.number_of_packet ==
statistics_collection.collector.successful_transmissions.
__len__()):
if not [
x
for x in timer.events if x.type == "Polling round end"
]: # stop the simulation
statistics_collection.collector.end_time = timer.current_time
timer.events = []
if system_channel.packet_list: # renew the channel busy time
statistics_collection.collector.channel_busy_time += (
timer.end_time -
statistics_collection.collector.last_time_idle)
statistics_collection.collector.print_statistics_of_delays()
statistics_collection.collector.print_polling_info()
statistics_collection.collector.print_other_statistics(
end_time, packet_size)
statistics_collection.collector.clear()
file.close()
os.system('cls' if os.name == 'nt' else 'clear')
db_name = botconf['database']
except KeyError as e:
Time = datetime.datetime.utcnow()
EventType = "KeyError"
Function = "main"
Explanation = "Some of bot_config.json's required keys are not set"
EventText = e
ExceptionType = type(e)
print("{}|{}|{}|{}|{}|{}|{}".format(Time, EventType, Function, File, Explanation, EventText,
ExceptionType))
exit(1)
else:
print2console('Parsing successful', last=True)
print2console('Initialization')
exchs, minvolumes = ini.init(pairs, conffile, exchsfile, exchanges_names)
requests = ini.get_urls(pairs, conffile, limit)
while len(exchs) <= 1:
time.sleep(60)
exchs, minvolumes = ini.init(pairs, conffile, exchsfile, exchanges_names)
continue
currency_list = set()
for pair in pairs:
for cur in pair.split('_'):
currency_list.add(cur)
print2console('Initialization successful', last=True)
print2console('Connecting to Mongo')
ok_mongo = False
main_command = [
('Play',play,[dungeon[0]]),
('Credits',play,[credits_scene]),
('Quit',game.close,[])
]
main_scene = cocos.scene.Scene()
menu = MainMenu(main_command)
#Title
label = cocos.text.Label(TITLE,position = (400,500), font_name = 'Drakoheart Leiend', font_size = 45, anchor_x = 'center')
main_scene.add(label)
main_scene.add(menu)
#music
bgm = ServerConnection.getMusic('bgm/main_screen.ogg')
bgm_player = pyglet.media.Player()
bgm_player.queue(bgm)
bgm_player.eos_action = bgm_player.EOS_LOOP
bgm_player.play()
cocos.director.director.run(main_scene)
except UDungeonException as ude:
print ude.message
if __name__ == "__main__":
init()
test()
# _*_coding:utf-8 _*_
# author: hsh
# file name: app.py
# data: 2019/8/26 14:46
from initialization import init
if __name__ == '__main__':
init()
em_data = open("em_data", "r")
data = np.loadtxt(em_data)
em_data.close()
print('Data shape:', data.shape)
#2D plot of imported data
x, y = data.T
plt.plot(x, y, 'x')
plt.axis('equal')
plt.show()
print('Data shape:', data.shape)
#Initializtion of parameters for EM algorithm
delta = 4
mu_, sig_, pi_c = ini.init(data, C, delta)
#Convergence condition
conv = 0.000001
#Compute parameters using EM algorithm
log_a, mu_new, sig_new, pic_new = em.gaussian(data, mu_, sig_, pi_c, conv)
#Print results
iterations = np.array(log_a.shape)
print('\n Number of iterations:', iterations[0])
print('\n New Means: \n', mu_new)
print('New covariance matrices: \n', sig_new)
print('New prior probabilities: \n', pic_new)
#Save results
