async def on_message(self, message):
if self.filter_optout(message.author):
print("ignoring user {}".format(message.author.id))
return
#BREAKOUT ROOMS, ill move this somewhere else eventually
if message.content.startswith('!breakout'):
if message.author.id not in GODS:
await message.channel.send("f**k you")
args = message.content.split()
#default number of groups is 3
try:
groups = int(args[1])
except IndexError:
groups = 3
try:
#get all members in same vc as me
victims = message.author.voice.channel.members
except AttributeError: #if in not in a VC dont do anything
return
#shuffle victims to make sure its more random
random.shuffle(victims)
#list of all voice channels
channels = message.guild.voice_channels
#remove channels that arent in the specified category
channels = [x for x in channels if x.category_id == CATEGORY]
#random indexes corresponding to all_channels
rooms = random.sample(range(0, len(channels) ), groups)
i = 0
for v in victims:
index = i % groups
print ("moving %s to %s" % (v, index))
await v.edit(voice_channel=channels[rooms[index]])
i = i+1
if message.author.id == self.user.id: # dont trigger on own messages
return
if message.author.bot == True:
return
try:
if message.content.split()[0] in self.COMMANDS :
output = generate_output(message, self.conn)
await message.channel.send(embed=output)
except IndexError:
return
def copy_output():
# generate output
with open(os.path.join(APP_PATH, "CMakeLists.txt"), 'r') as readfile:
lines = readfile.readlines()
for line in lines:
if line.startswith("project"):
project_name = line.replace(')', '(').split('(')[1]
use_custom_partition_table = False
with open(os.path.join(APP_PATH, "sdkconfig"), 'r') as readfile:
lines = readfile.readlines()
for line in lines:
if line.startswith("CONFIG_PARTITION_TABLE_CUSTOM=y"):
use_custom_partition_table = True
elif line.startswith("CONFIG_PARTITION_TABLE_CUSTOM_FILENAME="):
custom_partition_name = line.replace('"', '=').split('=')[2]
elif line.startswith("CONFIG_PARTITION_TABLE_FILENAME="):
partition_name = line.replace('"', '=').split('=')[2]
if use_custom_partition_table:
partition_name = custom_partition_name
output_list = [
os.path.join(APP_PATH, "build", "ota_data_initial.bin"),
os.path.join(APP_PATH, "build", "bootloader", "bootloader.bin"),
os.path.join(APP_PATH, "build", project_name + ".bin"),
os.path.join(APP_PATH, "build", "partition_table",
"partition-table.bin"),
]
qrgen_image = get_qrgen_image()
if qrgen_image:
output_list.append(os.path.join(qrgen_image))
debug_list = [
os.path.join(APP_PATH, "build", project_name + ".elf"),
os.path.join(APP_PATH, "build", project_name + ".map"),
os.path.join(APP_PATH, "build", "bootloader", "bootloader.elf"),
os.path.join(APP_PATH, "build", "bootloader", "bootloader.map"),
os.path.join(APP_PATH, "sdkconfig"),
]
sys.path.append(COMMON_TOOLS_PATH)
from generate_output import generate_output
generate_output(os.environ["STDK_REF_PATH"], BSP_NAME, APP_NAME,
output_list, debug_list)
def processDirectory(datasize, dirName):
fileQueue, fileCount = getFileList(dirName)
fileOutQueue = mp.Queue()
statListInQueue = mp.Queue()
statListOutQueue = mp.Queue()
heapInQueue = mp.Queue()
statListCount = 0
statFinalList = []
#Some counts
if(fileCount < 8):
fileWorkerThreadCount = fileCount
else:
fileWorkerThreadCount = 8
if(fileCount/4 < 4):
statWorkerThreadCount = fileCount/4 + 1
else:
statWorkerThreadCount = 4
#keep track of processes
fileworkerList = []
statworkerList = []
#statList
statList = []
for i in range(0, fileWorkerThreadCount):
fileworker = mp.Process(target = processFile, args = ("fileworker" + str(i), fileQueue, fileOutQueue, ))
fileworker.start()
fileworkerList.append(fileworker)
for i in range(0, statWorkerThreadCount):
statworker = mp.Process(target = processBulkStats, args = ("statListWorker" + str(i), statListInQueue, statListOutQueue, ))
statworker.start()
statworkerList.append(statworker)
#Deal with heaplaw
heapworker = mp.Process(target = processHeapLaw, args = ("heapworker", heapInQueue, fileCount, datasize, ))
heapworker.start()
for i in range(0, fileCount):
try:
queueElement = fileOutQueue.get(True, 240)
statList.append(queueElement)
heapL = heapLaw()
heapL.bookWordSet = queueElement.bookWordSet
heapL.wordCount = queueElement.wordCount
heapInQueue.put(heapL)
if(len(statList) == 20 or i == fileCount-1):
statListInQueue.put(statList)
print "element going into statlistinqueue {} {}".format(i, fileCount)
touch(statList)
statListCount += 1
del statList[:]
gc.collect()
except:
print traceback.format_exc()
break
cleanUpProcesses(fileworkerList)
print "statListcount {}".format(statListCount)
#Do a final sweep and add all the stats to be processed to the list
for i in range(0, statListCount):
try:
statFinalList.append(statListOutQueue.get(True, 240))
print "received statlists {}".format(i)
if(i % 100 == 0):
gc.collect()
except:
print traceback.format_exc()
break
cleanUpProcesses(statworkerList)
print "FINAL STATS COMPILATION"
finalstats = processFinalStats(statFinalList)
#printStats(finalstats)
computeExtraStats(datasize, finalstats)
generate_output(datasize, finalstats)
heapworker.terminate()
def main():
global number_of_population
number_of_population = 150
print('initializing population...')
population = Population(number_of_population)
population.sort(key=Chromosome.compute_fitness_value)
first_pen = population[0].penalty
generation_number = 1000
iteration = 0
best_fit = math.inf
best_cnt = 0
cnt_limit = 100
while True:
p_r = 0.05
p_c = 0.75
number_of_population = len(population)
iteration += 1
best_cnt += 1
population.sort(key=Chromosome.compute_fitness_value)
print(iteration, population[0].num_of_hard_conflicts,
population[0].num_of_soft_conflicts,
population[0].compute_fitness_value(), population[0].penalty,
len(population))
if population[0].num_of_hard_conflicts != 0 or population[
0].penalty != first_pen:
if best_fit > population[0].compute_fitness_value():
best_fit = population[0].compute_fitness_value()
best_cnt = 0
# cnt_limit += 5
elif best_cnt == cnt_limit:
# i = 0
# while population[0][i] == -1 or i >= population[0].size // 2:
# i += 1
# population[0][i] = population[0][i + population[0].size // 2 if i < population[0].size / 2 else
# i - population[0].size // 2] = -1
# for p in population:
# p[i] = p[i + p.size // 2] = -1
# population[-1] = Chromosome(True)
# population.fit()
# population.sort(key=Chromosome.compute_fitness_value)
best_cnt = 0
cnt_limit = 100
p_r = 0.3
if population.is_mundane() or iteration == generation_number:
if population[0].num_of_hard_conflicts == 0 or population[
0].penalty == first_pen:
break
else:
# i = 0
# while population[0][i] == -1 and i < population[0].size // 2:
# i += 1
# for p in population:
# p[i] = p[i + p.size // 2] = -1
# iteration = 0
generation_number += 200
p_r = 0.3
if generation_number >= 2000:
break
children = crossover(population, p_c)
mutation(children, p_r)
children.fit()
population = children
# for i in population[0].conflicting_genes:
# population[0][i] = -1
# population.fit()
# print(population[0].num_of_hard_conflicts, population[0].num_of_soft_conflicts, population[0].penalty)
generate_output(population[0])