def randomSnack(rows, items):
positions = item.body
while True:
x = random.randomrange(rows)
y = random.randomrange(rows)
if len(list(filter(lambda z: z.pos == (x, y), positions))) > 0:
continue
else:
break
return (x, y)
def update_waiting_time(self, state):
rand = random.randomrange(0, 100)
print(rand)
if state == LKW_state_enum.LOADING:
if rand < 10:
return 16.0
elif rand < 30:
return 10.0
elif rand > 30:
return 12.0
elif state == LKW_state_enum.WEIGHTING:
if rand < 20:
return 24.0
elif rand < 35:
return 18.0
elif rand > 35:
return 16.0
elif state == LKW_state_enum.EMPTYING:
if rand < 10:
return 120
elif rand < 15:
return 80
elif rand > 15:
return 60
else:
return 0
def random_item(n):
a = len(n)
for i in n:
i = random.randomrange(n[0], n[a - 1])
b.append(i)
return b
def find_sriov_nic(self, select_policy='first'):
"""
Find pci NICs which support SR-IOV and return a NIC name
according to select policy ('auto', 'first')
:param select_policy: the policy to select, 'auto', 'first'
"""
sr_iov_devs = []
pci_id = None
pci_devs = self.find_pci_devices('Ethernet Controller')
for dev in pci_devs:
if self.is_pci_support_sriov(dev):
sr_iov_devs.append(dev)
if select_policy == 'first':
pci_id = sr_iov_devs[0]
elif select_policy == 'auto':
pci_id = sr_iov_devs[random.randomrange(len(sr_iov_devs))]
else:
LOG.error("Invalid select policy")
if pci_id is not None:
all_nics = self.get_all_physical_nics()
for nic in all_nics:
output = self.run_command('ethtool -i %s' % nic).stdout
if pci_id in output:
LOG.info("Found device: %s => %s" % (pci_id, nic))
return (pci_id, nic)
LOG.error("Failed to find SR-IOV nic")
def play_with_model(model):
scores = []
choices = []
print("Playing wtih Trained Model.....")
for each_game in range(10):
score = 0
game_memory = []
prev_obs = []
env.reset()
for _ in range(goal_steps):
env.render()
if len(prev_obs) == 0:
action = random.randomrange(0, 2)
else:
#this clever call finds the index of the max argument
#since predict will return something like [][0.23.., 0.76..]]
#it will return 0 if the first is bigger, 1 if the second
# which is the same as 'left' or 'right' in the action space
action = np.argmax(model.predict([prev_obs])[0])
choices.append(action)
new_observation, reward, done, info = env.step(action)
prev_obs = new_observation
game_memory.append([new_observation, action])
score += reward
if done: break
scores.append(score)
print('Average Score', sum(scores) / len(scores))
print('Choice 1: {}, Choice 0: {}'.format(
choices.count(1) / len(choices),
choices.count(0) / len(choices)))
def process(oid, tag, value, **context):
if not context['nextFlag'] and not context['exactMatch']:
return context['origOid'], context['errorStatus'] # serve exact OIDs
if context['setFlag']:
return context['origOid'], context['errorStatus'] # read-only mode
if oid not in settingsCache:
settingsCache[oid] = dict([ x.split('=') for x in value.split(',') ])
if 'function' in settingsCache[oid]:
f = getattr(math, settingsCache[oid]['function'])
else:
f = lambda x: x
v = f((time.time() - booted) * float(settingsCache[oid].get('rate', 1))) * float(settingsCache[oid].get('scale', 1)) + float(settingsCache[oid].get('offset', 0))
d = int(settingsCache[oid].get('deviation', 0))
if d:
v += random.randomrange(-d, d)
if v < int(settingsCache[oid].get('min', 0)):
v = int(settingsCache[oid].get('min', 0))
elif v > int(settingsCache[oid].get('max', 0xffffffff)):
v = int(settingsCache[oid].get('max', 0xffffffff))
return oid, v
def DieOutcomes():
global playagain
rolls = random.randrange(
0, 6) #this generates a random number between 1 and 6
if rolls == 1:
print('Oh no, you rolled a 1, that isnt good.')
print('')
print('You wake up once again in a horrid and dark place.')
print(
'You spend your few remaining days clawing around in the dark, eventually starving to death.'
)
playAgain()
elif rolls == 2:
print('Ah yes, you rolled a 2.')
print(
'I grant you the sword, Excalibur, to make you undefeateable in combat.'
)
print('')
win2()
elif rolls == 3:
print(
'A 3, allow me to turn back the passage of time. Of course, you won\'t be allowed to remember this. Bye!'
)
print('')
playagain = 'y'
start()
elif rolls == 4:
print('A 4, now, let me explain.')
print('')
four()
elif rolls == 5:
print('')
print(
'A 5, you have won the lottery. As promised, I grant you infinite wealth.'
)
win3()
elif rolls == 6:
print('')
print(
'No, no no, that is not supposed to happen. What makes you think you can roll a 6?'
)
print('You know what that means, do you not?')
print(
'But I have decided I can make an exception, so roll again, quickly, before he notices'
)
print('')
rolls == random.randomrange(0, 6)
def sendState(num=1):
# Default number of copies to send is 1
for i in range(num):
# If RAND_MOD == 1, always send
if RAND_MOD == 1:
sendUDP(str(STATE))
elif RAND_TYPE == True:
# Drop 1 of n packets
if random.randrange(RAND_MOD) != 0:
sendUDP(str(STATE))
else:
# Send 1 of n packets
if random.randomrange(RAND_MOD) == 0:
sendUDP(str(STATE))
return
import random as m from m import randomrange print(m.randomrange(1,10))
def img_from_link(url):
name = random.randomrange(1, 1001)
full_name = "img/" + str(name) + ".jpg"
urllib.request.urlretrieve(url, full_name)
def randomize(l):
for i in range(len(l)//2):
j = random.randomrange(0, len(l), 1)
k = random.randomrange(0, len(l), 1)
(l[j], l[k]) = (l[k], l[j])
def most_common(L):
# get an iterable of (item, iterable) pairs
SL = sorted((x, i) for i, x in enumerate(L))
# print 'SL:', SL
groups = itertools.groupby(SL, key=operator.itemgetter(0))
# auxiliary function to get "quality" for an item
def _auxfun(g):
item, iterable = g
count = 0
min_index = len(L)
for _, where in iterable:
count += 1
min_index = min(min_index, where)
# print 'item %r, count %r, minind %r' % (item, count, min_index)
return count, -min_index
# pick the highest-count/earliest item
return max(groups, key=_auxfun)[0]
def getRandom():
Randoms = list()
Randoms.append(random.randrange(2, 15))
return Randoms
RandomList = list()
for i in range(8):
RandomList.append(getRandom())
indexnum = random.randomrange(0,8)
print RandomList[indexnum]
import random random.randomrange(1, 10)
def loadCsv(filename):
lines=csv.reader(open(filename,"r"))
dataset=list(lines)
for i in range(len(dataset)):
dataset[i]=[float(x) for x in dataset[i]]
return dataset
def splitDataset(dataset,splitRatio):
trainSize=int(len(dataset)*splitRatio)
trainSet=[]
copy=list(dataset)
while len(trainSet)<trainSize:
index=random.randomrange(len(copy))
trainSet.append(copy.pop(index))
return[trainSet,copy]
def separateByClass(dataset):
separated={}
for i in range(len(dataset)):
vector=dataset[i]
if(vector[-1]not in separated):
separated[vector[-1]]=[]
separated[vector[-1]].append(vector)
return separated
for x in [2,4,6,8,10]:
print(x)
num_list = [[1,2,3],[13,45,63,54], [500,700,500,498]]
for x in range(0,3):
for y in range(0,3):
print(num_list[x][y])
# A bit about while loop
# They are going to be use when you don't have any idea ahead of time how many times you are going to loop.
# This will generate a random number from 0-99
random_number = random.randomrange(0,100)
# What this is doing here is it has a condition to loop through until it hits 15. It's going to continure producing random number until It get's to 15 and as soon as it hits that it'll jump out of the loop.
while(random_number != 15):
print(random_number)
random_number = random.randomrange(0,100)
i = 0;
while( i <= 22):
if(i%2 == 0):
print(i)
elif (i == 9):
break
else:
i += 1 # i = i + 1