def change_weights(self, mutate):
for weight in self.weights:
shape = weight.shape
for r in range(shape[0]):
for c in range(shape[1]):
prob = randfloat(0, 1)
change = 0
if prob+mutation_rate >= 1:
change = randfloat(-mutate, mutate)
weight[r][c] += change
def update(self):
delta: vec2 = (self.target_pos - self.pos).normalized()
self.direction = delta.normalized()
self.update_animation()
if (self.target_pos - self.pos).__len__() <= self.finish_dist():
self.target_pos = self.pos
self.is_move_finished = True
else:
self.pos += delta * self.move_speed * GAME_DELTATIME * GAME_TIME_SCALE
if not self.is_move_finished:
return
if self.is_gathering:
if self.gather_obj is None:
self.wander_at(self.pos)
self.update()
return
if abs(self.pos -
self.gather_obj.pos).__len__() < self.finish_dist():
if self.gather_obj.empty():
self.wander_at(self.pos +
vec2(randfloat(0.5, 1), randfloat(0.5, 1)) *
50)
self.update()
return
self.inner_counter += 1
if (GAME_DELTATIME * self.inner_counter) >= (
self.gather_period / GAME_TIME_SCALE):
self.inner_counter = 0
self.inventory.append(
self.gather_obj.take(self.inventory_capacity))
self.target_pos = self.camp_obj.pos
elif abs(self.pos -
self.camp_obj.pos).__len__() < self.finish_dist():
self.target_pos = self.gather_obj.pos
for el in self.inventory:
self.camp_obj.res_amounts[el[0]] += el[1]
self.inventory.clear()
return
if self.is_wandering:
self.inner_counter += 1
self.is_moving = False
if (GAME_DELTATIME * self.inner_counter) >= (randfloat(0.5, 1.5) /
GAME_TIME_SCALE):
self.inner_counter = 0
self.target_pos = (
self.wandering_pos +
vec2(randfloat(-0.5, 0.5), randfloat(-0.5, 0.5)) *
self.wandering_radius)
self.is_moving = True
self.is_move_finished = False
def UpdateNetwork(self):
TweakLowerBound = -1
TweakUpperBound = 1
for i in self.InputLayer:
i.Threshold += Decimal(randfloat(TweakLowerBound, TweakUpperBound))
for i in self.InputToHidden1Links:
i.Multiplier += Decimal(randfloat(TweakLowerBound,
TweakUpperBound))
for i in self.HiddenLayer1:
i.Threshold += Decimal(randfloat(TweakLowerBound, TweakUpperBound))
for i in self.Hidden1ToHidden2Links:
i.Multiplier += Decimal(randfloat(TweakLowerBound,
TweakUpperBound))
for i in self.HiddenLayer2:
i.Threshold += Decimal(randfloat(TweakLowerBound, TweakUpperBound))
for i in self.Hidden2ToHidden3Links:
i.Multiplier += Decimal(randfloat(TweakLowerBound,
TweakUpperBound))
for i in self.HiddenLayer3:
i.Threshold += Decimal(randfloat(TweakLowerBound, TweakUpperBound))
for i in self.Hidden3ToOutputLinks:
i.Multiplier += Decimal(randfloat(TweakLowerBound,
TweakUpperBound))
for i in self.OutputLayer:
i.Threshold += Decimal(randfloat(TweakLowerBound, TweakUpperBound))
def generate_weights(mother_w, father_w, shape):
child_w = []
for i in range(len(mother_w)):
mf = randint(0, 1)
mutation = randfloat(0, 1)
change = 0
if mutation_rate + mutation >= 1:
change = randfloat(-1, 1)
if mf == 0:
child_w.append(mother_w[i] + change)
else:
child_w.append(father_w[i] + change)
return np.asarray(child_w).reshape(shape)
def rouletteWheelSelect(population, SCORES, scorefunc, scoreparams, N):
""" Select N unique individuals from the population based on roulette wheel selection.
If there are not at least N individuals in the population, ValueError is raised """
if len(population) < N: raise ValueError("Cannot Select %d individuals from a population of %d" %(N, len(population)))
# print 'getting wheel' ##
wheel = getRouletteWheel(population, SCORES, scorefunc, scoreparams)
# print 'got wheel' ##
answer = []
selection = set([])
while N:
# print 'while', N ##
try:
# print 'trying' ##
r = randfloat(-1,0)
slot = (s for s in wheel if s[1]<=r<=s[0]).next()
answer.append(wheel[slot])
selection.add(slot)
N -= 1
except:
# print 'excepting' ##
print r
for slot in wheel: print slot
raise
crash()
return answer
def randHsv():
return [
randint(0, 360),
randint(40, 80),
randint(20, 80),
randfloat(0, 0.5)
]
def do_work(counter, lock, queue, df):
name = multiprocessing.current_process().name
new_data = [] # this will store processed data
made_by = []
timestamp = []
for data in df["data"]: # not discussing df.applymap() here
new_data.append(data ** 3) # we're transforming our input data
made_by.append(name)
timestamp.append(time.ctime())
# counter update
with lock:
counter.value += 1
time.sleep(randfloat(0.1, 1))
print("worker:", name, "reports: WORK DONE")
new_df = pd.DataFrame({"old_data" : df["data"],
"new_data" : new_data,
"made_by" : made_by,
"timestamp" : timestamp
}
)
queue.put(new_df)
def random_symbol(weights): ceil = reduce(lambda x, y: x + y, [x[1] for x in weights]); while True: thresh = randfloat(0, ceil); print "thresh = %s"%thresh; s = reduce(lambda x, y: (x[1] + y[1]) if isinstance(x, int) and x < ceil else x, weights); yield s
def generate_obstacle(self):
random_pos = int(randfloat(self.size / 2 + Constants.circCenter_x - Constants.circRadius,
Constants.screen_width -
(self.size / 2 + Constants.circCenter_x - Constants.circRadius)))
star = Star(Vector2(random_pos, -self.size), self.size,
Material(Color.yellow))
self.game_object_list.append(star)
def selectBestActionProb(actionVector, probChoosingRandom):
prob = random.randfloat(0, 1)
if prob > probChoosingRandom:
randAction = random.randint(0, len(actionVector) - 1)
return randAction
else:
return actionVector.index(max(actionVector))
def sample_one(items):
roll = randfloat()
curr = 0.0
for (item, prob) in items:
#print roll, curr, '\t', prob
curr += prob
if roll <= curr: return item
return item
def mutate(p, mutprob): answer = [] for g in p: if randfloat(0,1) <= mutprob: answer.append((int(g) +1) %2) else: answer.append(g) return ''.join(str(i) for i in answer)
def generate_obstacle(self):
random_pos = int(randfloat(self.radius + Constants.circCenter_x - Constants.circRadius,
Constants.screen_width -
(self.radius + Constants.circCenter_x - Constants.circRadius)))
circle = InvencibleCircle(Vector2(random_pos, -2 * self.radius), self.radius,
Material(Color.purple))
self.game_object_list.append(circle)
def crossover(p1, p2, crossprob): G = len(p1) crosspoint = randint(0,G-1) if randfloat(0,1) <= crossprob: c1 = p1[:crosspoint] + p2[crosspoint:] c2 = p2[:crosspoint] + p1[crosspoint:] return c1, c2 else: return p1, p2
def test_bo_observation_added():
observations = list()
for index, param_config in enumerate(BO.searchspace):
observation = randfloat(0.1, 10)
observations.append(observation)
BO.update_after_evaluation(observation, index, param_config)
assert BO.is_valid(observation)
assert len(observations) == index + 1
assert len(BO.unvisited_cache) == len(BO.searchspace) - index - 1
assert BO.current_optimum == min(observations)
def expectedgood(self, output, place, abit=False):
"""
output = np.copy(output[0])
expected = [0]*len(output)
output = output.tolist()
expected[output.index(max(output))] = 1
"""
place = place - 1
expected = np.copy(output[0])
expected = expected.tolist()
if abit:
expected[place] += randfloat(0.1, 0.2)
else:
expected[place] += randfloat(0.01, 0.1)
#for i in range(len(expected)):
# if i != place:
# expected[i] = 0
#"""
return [expected]
def symbol_gnrt(weights): ceil = reduce(lambda x, y: x + y, [x[1] for x in weights]); while True: thresh = randfloat(0, ceil); #print "tttthresh = %s"%thresh; x = 0; for t in weights: x += t[1]; if (x > thresh): yield t[0] break;
def should_step_get_rejected(self, standardError):
"""
Given a standard error, return whether to keep or reject new
standard error according to the constraint reject probability function.
:Parameters:
#. standardError (number): Standard error to compare with the
Constraint standard error.
:Return:
#. result (boolean): True to reject step, False to accept.
"""
previousRatio = 1 - (self.standardError / self.__maximumStandardError)
currentRatio = 1 - (standardError / self.__maximumStandardError)
if currentRatio >= self.__thresholdRatio: # must be accepted
return False
elif previousRatio >= self.__thresholdRatio: # it must be rejected
return randfloat() < self.rejectProbability
elif standardError <= self.standardError: # must be accepted
return False
else: # must be rejected
return randfloat() < self.rejectProbability
def trokut(i):
t.pu()
## randomizirano generiranje tocaka
a = random(-400, 400), random(-400, 400)
b = random(-400, 400), random(-400, 400)
c = random(-400, 400), random(-400, 400)
## nasumicno generiranje boje
clr = randfloat(), randfloat(), randfloat()
t.color(clr)
t.width(5)
## provjera je li pravi trokut i crtanje ako je
if pravi(a, b, c):
lista.append(i)
n += 1
t.goto(a)
t.pd()
t.goto(b)
t.goto(c)
t.goto(a)
def should_step_get_rejected(self, standardError):
"""
Given a standardError, return whether to keep or reject new standardError according to the constraint rejectProbability.
:Parameters:
#. standardError (number): The standardError to compare with the Constraint standardError
:Return:
#. result (boolean): True to reject step, False to accept
"""
if self.standardError is None:
raise Exception(LOGGER.error("must compute data first"))
if standardError<=self.standardError:
return False
return randfloat() < self.__rejectProbability
def drawOneCircle(x, y, radius, h, s, v, opacity):
randOpacity = round(randfloat(0.3, opacity), 3)
randOpacity2 = round(randfloat(0.1, (opacity * 0.5)), 3)
env = Environment(autoescape=False)
if (radius < 3):
tpl = env.from_string("""
<circle
r="{{ radius }}%" cx="{{ x }}%" cy="{{ y }}%"
fill="hsla({{ h }}, {{ s }}%, 90%, {{ randOpacity }})"
>
</circle>
<circle
r="{{ radius }}%" cx="{{ x }}%" cy="{{ y }}%"
fill="none"
stroke="white"
stroke-opacity="{{ randOpacity2 }}"
>
</circle>
""")
else:
tpl = env.from_string("""
<circle
r="{{ radius }}%" cx="{{ x }}%" cy="{{ y }}%"
fill="hsla({{ h }}, {{ s }}%, 90%, {{ randOpacity2 }})"
filter="url(#blur)"
>
</circle>
""")
return tpl.render(x=x,
y=y,
radius=radius,
h=h,
s=s,
v=v,
randOpacity=randOpacity,
randOpacity2=randOpacity2)
def generate_obstacle(self):
random_pos = int(randfloat(self.size / 2 + Constants.circCenter_x - Constants.circRadius,
Constants.screen_width -
(self.size / 2 + Constants.circCenter_x - Constants.circRadius)))
rect = Rectangle(Vector2(random_pos, -self.size),
Vector2(self.size, self.size),
Material((255, 255, 255)))
rect.animation = ObstaclePulsingAnimation(rect)
rect.animator = Animator(rect, [rect.animation])
rect.animator.play()
direction = randint(0, 1)
if direction == 0:
direction = -1
rect.vel = direction # Checks if going left or right. Can be 1 for right or -1 for left
self.game_object_list.append(rect)
def expectedgood(self, output, val=0.1):
"""
output = np.copy(output[0])
expected = [0]*len(output)
output = output.tolist()
expected[output.index(max(output))] = 1
"""
expected = np.copy(output[0])
expected = expected.tolist()
place = expected.index(max(expected))
expected[place] += randfloat(0.1, 0.2)
#for i in range(len(expected)):
# if i != place:
# expected[i] = 0
#"""
return [expected]
def expected(self, output):
#"""
expected = np.copy(output[0])
expected = expected.tolist()
place = expected.index(max(expected))
expected[place] = 0
for i in range(len(expected)):
if i != place:
expected[i] += randfloat(0.01, 0.1)
"""
output = np.copy(output[0])
expected = [1] * len(output)
output = output.tolist()
expected[output.index(max(output))] = 0
"""
return [expected]
async def scrutinize_messages(self, message):
channel = message.channel
user = message.author
if hasattr(user, 'bot') and user.bot is True:
return
if channel.id not in self.flippedTables:
self.flippedTables[channel.id] = {}
#┬─┬ ┬┬ ┻┻ ┻━┻ ┬───┬ ┻━┻ will leave 3 tables left flipped
#count flipped tables
for m in re.finditer('┻━*┻|┬─*┬', message.content):
t = m.group()
if '┻' in t and not (message.author.id == self.bot.user.id
and self.settings["BOT_EXEMPT"]):
if t in self.flippedTables[channel.id]:
self.flippedTables[channel.id][t] += 1
else:
self.flippedTables[channel.id][t] = 1
if not self.settings["ALL_TABLES"]:
break
else:
f = t.replace('┬', '┻').replace('─', '━')
if f in self.flippedTables[channel.id]:
if self.flippedTables[channel.id][f] <= 0:
del self.flippedTables[channel.id][f]
else:
self.flippedTables[channel.id][f] -= 1
#wait random time. some tables may be unflipped by now.
await asyncio.sleep(randfloat(0, 1.5))
tables = ""
deleteTables = []
#unflip tables in self.flippedTables[channel.id]
for t, n in self.flippedTables[channel.id].items():
unflipped = t.replace('┻', '┬').replace('━',
'─') + " ノ( ゜-゜ノ)" + "\n"
for i in range(0, n):
tables += unflipped
#in case being processed in parallel
self.flippedTables[channel.id][t] -= 1
deleteTables.append(t)
for t in deleteTables:
del self.flippedTables[channel.id][t]
if tables != "":
await self.bot.send_message(channel, tables)
def _gen_graph(username: str) -> nx.DiGraph:
log = logging.getLogger('_gen_graph')
# TODO
text = f'partial key #4:'
node_indices = tuple(range(0, len(text)))
node_data = ((idx, {'key': text[idx]}) for idx in node_indices)
edge_data = ((source, target, randfloat())
for source, target in itertools.zip_longest(
node_indices[1:], node_indices[:-1]))
graph = _create_graph(node_data, edge_data)
seed: int = sum(map(ord, username))
log.debug(f'seed for username {username} is {seed}')
graph = _obfuscate_graph(graph, seed)
return graph
async def scrutinize_messages(self, message):
channel = message.channel
user = message.author
if hasattr(user, 'bot') and user.bot is True:
return
if channel.id not in self.flippedTables:
self.flippedTables[channel.id] = {}
#┬─┬ ┬┬ ┻┻ ┻━┻ ┬───┬ ┻━┻ will leave 3 tables left flipped
#count flipped tables
for m in re.finditer('┻━*┻|┬─*┬', message.content):
t = m.group()
if '┻' in t and not (message.author.id == self.bot.user.id and self.settings["BOT_EXEMPT"]):
if t in self.flippedTables[channel.id]:
self.flippedTables[channel.id][t] += 1
else:
self.flippedTables[channel.id][t] = 1
if not self.settings["ALL_TABLES"]:
break
else:
f = t.replace('┬','┻').replace('─','━')
if f in self.flippedTables[channel.id]:
if self.flippedTables[channel.id][f] <= 0:
del self.flippedTables[channel.id][f]
else:
self.flippedTables[channel.id][f] -= 1
#wait random time. some tables may be unflipped by now.
await asyncio.sleep(randfloat(0,1.5))
tables = ""
deleteTables = []
#unflip tables in self.flippedTables[channel.id]
for t, n in self.flippedTables[channel.id].items():
unflipped = t.replace('┻','┬').replace('━','─') + " ノ( ゜-゜ノ)" + "\n"
for i in range(0,n):
tables += unflipped
#in case being processed in parallel
self.flippedTables[channel.id][t] -= 1
deleteTables.append(t)
for t in deleteTables:
del self.flippedTables[channel.id][t]
if tables != "":
await self.bot.send_message(channel, tables)
def Répondre2(Entrée, Phrases):
Dico = {}
l = len(Phrases)
for i in range(l):
Dico[str(Rsb(Phrases[i], Entrée))] = i
Progression(i, 0, l)
Ressemblances = list(Dico)
Ressemblances.sort()
Ressemblances.reverse()
Proba = []
for i in range(len(Liste)):
Proba.append(Ressemblances[i] / 2**i)
r = random.randfloat(0, len(sum(Proba)))
i = 0
n = 0
while i < r:
i += Proba[n]
n += 1
Sortie = Phrases[Dico[Ressemblances[i]] + 1]
return Sortie
def create_float(self):
return randfloat() * randint(1, 100)
import random
hidden_number = random.randfloat(0, 1)
user_guess = 0
while not user_guess == hidden_number:
user_guess = int(input("Guess a number:"))
if user_guess > hidden_number:
print("Too high!")
elif user_guess < hidden_number:
print("Too low!")
else:
print("Thats right!")
def random(cls):
return Color(randfloat(), randfloat(), randfloat(), 1.0)
def add_device(self, device):
"""
Add a device to the managed list and announce it. Multiple hierarchies are not
supported and must be handled separately.
:param device: UPnP host device
:return: (bool) True if added successfully
:since: v0.2.00
"""
if (self.log_handler is not None): self.log_handler.debug("#echo(__FILEPATH__)# -{0!r}.add_device()- (#echo(__LINE__)#)", self, context = "pas_upnp")
_return = True
if (isinstance(device, Device) and device.is_managed()):
with self.lock:
device_identifier = Device.get_identifier(device.get_usn(), self.bootid, self.configid)
if (device_identifier is not None and device_identifier['usn'] not in self.usns):
if (self.log_handler is not None): self.log_handler.info("pas.upnp.ControlPoint adds UPnP device USN '{0}'", device_identifier['usn'], context = "pas_upnp")
if (device_identifier['device'] not in self.rootdevices): self.rootdevices.append(device_identifier['device'])
device_identifier['url_desc'] = device.get_desc_url()
self.managed_devices[device_identifier['uuid']] = device
self.usns[device_identifier['usn']] = device_identifier
self._remove_task(device_identifier['usn'], "deliver_event")
if (self.configid < 16777216): self.configid += 1
else: self.configid = 0
wait_seconds = randfloat(0.2, 0.4)
event = ControlPointEvent(ControlPointEvent.TYPE_DEVICE_ALIVE, control_point = self)
event.set_usn(device_identifier['usn'])
event.set_location(device_identifier['url_desc'])
event.schedule(wait_seconds)
Hook.call("dNG.pas.upnp.ControlPoint.onHostDeviceAdded", identifier = device_identifier)
embedded_device_uuids = device.get_embedded_device_uuids()
for uuid in embedded_device_uuids:
embedded_device = device.get_embedded_device(uuid)
embedded_device_identifier = Device.get_identifier(embedded_device.get_usn(), self.bootid, self.configid)
if (self.log_handler is not None): self.log_handler.info("pas.upnp.ControlPoint adds UPnP device USN '{0}'", embedded_device_identifier['usn'], context = "pas_upnp")
embedded_device_identifier['url_desc'] = embedded_device.get_desc_url()
self.managed_devices[embedded_device_identifier['uuid']] = embedded_device
self.usns[embedded_device_identifier['usn']] = embedded_device_identifier
wait_seconds = randfloat(0.4, 0.6)
event = ControlPointEvent(ControlPointEvent.TYPE_DEVICE_ALIVE, control_point = self)
event.set_usn(embedded_device_identifier['usn'])
event.set_location(embedded_device_identifier['url_desc'])
event.schedule(wait_seconds)
Hook.call("dNG.pas.upnp.ControlPoint.onHostDeviceAdded", identifier = embedded_device_identifier)
#
if (self.gena is None):
self.gena = Gena.get_instance()
self.gena.start()
#
else: _return = False
#
else: _return = False
return _return
def randomNormalizedPrice():
price = 0
while price < 0.0101 or price > 0.9899:
price = randfloat()
return price
def handle_request(source_data, source_wait_timeout, search_target, additional_data = None):
"""
Searches for hosted devices matching the given UPnP search target.
:param source_data: UPnP client address data
:param source_wait_timeout: UPnP MX value
:param search_target: UPnP search target
:param additional_data: Additional data received
:since: v0.2.00
"""
condition = None
condition_identifier = None
if (search_target == "ssdp:all" or search_target == "upnp:rootdevice" or search_target.startswith("uuid:")): condition = search_target
elif (search_target.startswith("urn:")):
condition = search_target
condition_identifier = Device.get_identifier("uuid:00000000-0000-0000-0000-000000000000::{0}".format(search_target), None, None)
elif (len(search_target) > 41):
condition = search_target
condition_identifier = Device.get_identifier(search_target, None, None)
#
results = [ ]
if (condition is not None):
control_point = ControlPoint.get_instance()
if (condition_identifier is None
and condition == "upnp:rootdevice"
): results += SsdpSearch._get_rootdevice_results(condition)
else:
managed_devices = control_point.get_managed_devices()
for uuid in managed_devices:
device = managed_devices[uuid]
results += SsdpSearch._handle_device_search(condition,
condition_identifier,
uuid,
device
)
if (condition == "ssdp:all"
or (condition_identifier is not None and condition_identifier['class'] == "service")
):
services = device.get_service_ids()
for service_id in services:
service = device.get_service(service_id)
results += SsdpSearch._handle_service_search(condition,
condition_identifier,
service,
device
)
#
#
embedded_devices = device.get_embedded_device_uuids()
for embedded_uuid in embedded_devices:
embedded_device = device.get_embedded_device(embedded_uuid)
results += SsdpSearch._handle_device_search(condition,
condition_identifier,
embedded_uuid,
embedded_device
)
if (condition_identifier is not None and condition_identifier['class'] == "service"):
services = embedded_device.get_service_ids()
for service_id in services:
service = embedded_device.get_service(service_id)
results += SsdpSearch._handle_service_search(condition,
condition_identifier,
service,
embedded_device
)
#
#
#
#
#
if (len(results) > 0):
if (additional_data is not None):
if ('USER-AGENT' in additional_data):
client_settings = ClientSettings(additional_data['USER-AGENT'])
source_wait_timeout = client_settings.get("ssdp_upnp_search_wait_timeout", source_wait_timeout)
elif (source_wait_timeout < 4):
# Expect broken clients if no user-agent is given and MX is too small
source_wait_timeout = 0
#
if (source_wait_timeout > 0):
wait_seconds = randfloat(0,
(source_wait_timeout if (source_wait_timeout < 10) else 10) / len(results)
)
else: wait_seconds = 0
for result in results:
event = ControlPointEvent(ControlPointEvent.TYPE_SEARCH_RESULT, control_point = control_point)
event.set_usn(result['usn'])
event.set_location(result['location'])
event.set_search_target(result['search_target'])
event.set_response_target(("[{0}]".format(source_data[0]) if (":" in source_data[0]) else source_data[0]),
source_data[1]
)
event.schedule(wait_seconds)
def punish(self, output, pos):
expected = output[:]
expected[pos - 1] = 0
for i in range(len(expected)):
if i != pos - 1:
expected[i] += randfloat(0.01, 0.1)
def random_value(self) -> float:
"""Generate a random value within the range allowed by this quantity."""
return self.minimum + random.randfloat(0, self.variance)
def swing_max(self):
return self.self_control + randfloat(-self.unpredictability,
self.unpredictability)
resPlace = 0
clock = pygame.time.Clock()
while not m_quit:
for ev in pygame.event.get():
if ev.type == pygame.QUIT:
m_quit = True
break
if ev.type == pygame.MOUSEBUTTONDOWN:
if ev.button == pygame.BUTTON_RIGHT:
res = get_resource_copy(resPlace)
res.pos = vec2(pygame.mouse.get_pos()[0],
pygame.mouse.get_pos()[1])
if resPlace == 1 or resPlace == 0:
res.fill(50, refresh_time=60 + 120 * randfloat(0, 1))
else:
res.fill(100)
mainCamp.register_resource(res)
elif ev.button == pygame.BUTTON_WHEELUP:
if resPlace < (GAME_RESOURCES.__len__() - 1):
resPlace += 1
elif ev.button == pygame.BUTTON_WHEELDOWN:
if resPlace >= 1:
resPlace -= 1
elif ev.type == pygame.KEYDOWN:
if ev.key == pygame.K_ESCAPE:
m_quit = True
break
if ev.key == pygame.K_SPACE:
GAME_TIME_SCALE = 5.0
