Lines Matching refs:self
119 def __init__(self, x=None):
125 self.seed(x)
126 self.gauss_next = None
128 def seed(self, a=None, version=2):
164 self.gauss_next = None
166 def getstate(self):
168 return self.VERSION, super().getstate(), self.gauss_next
170 def setstate(self, state):
174 version, internalstate, self.gauss_next = state
177 version, internalstate, self.gauss_next = state
190 (version, self.VERSION))
203 def __getstate__(self): # for pickle
204 return self.getstate()
206 def __setstate__(self, state): # for pickle
207 self.setstate(state)
209 def __reduce__(self):
210 return self.__class__, (), self.getstate()
235 def _randbelow_with_getrandbits(self, n):
238 getrandbits = self.getrandbits
245 def _randbelow_without_getrandbits(self, n, maxsize=1<<BPF):
251 random = self.random
277 def randbytes(self, n):
279 return self.getrandbits(n * 8).to_bytes(n, 'little')
284 def randrange(self, start, stop=None, step=_ONE):
312 return self._randbelow(istart)
344 return istart + self._randbelow(width)
356 return istart + istep * self._randbelow(n)
358 def randint(self, a, b):
362 return self.randrange(a, b+1)
367 def choice(self, seq):
374 return seq[self._randbelow(len(seq))]
376 def shuffle(self, x):
379 randbelow = self._randbelow
385 def sample(self, population, k, *, counts=None):
451 selections = self.sample(range(total), k=k)
454 randbelow = self._randbelow
480 def choices(self, population, weights=None, *, cum_weights=None, k=1):
487 random = self.random
520 def uniform(self, a, b):
522 return a + (b - a) * self.random()
524 def triangular(self, low=0.0, high=1.0, mode=None):
533 u = self.random()
544 def normalvariate(self, mu=0.0, sigma=1.0):
555 random = self.random
565 def gauss(self, mu=0.0, sigma=1.0):
592 random = self.random
593 z = self.gauss_next
594 self.gauss_next = None
599 self.gauss_next = _sin(x2pi) * g2rad
603 def lognormvariate(self, mu, sigma):
611 return _exp(self.normalvariate(mu, sigma))
613 def expovariate(self, lambd):
628 return -_log(1.0 - self.random()) / lambd
630 def vonmisesvariate(self, mu, kappa):
646 random = self.random
672 def gammavariate(self, alpha, beta):
691 random = self.random
737 def betavariate(self, alpha, beta):
748 ## def betavariate(self, alpha, beta):
751 ## y = self.expovariate(alpha)
752 ## z = self.expovariate(1.0/beta)
759 y = self.gammavariate(alpha, 1.0)
761 return y / (y + self.gammavariate(beta, 1.0))
764 def paretovariate(self, alpha):
768 u = 1.0 - self.random()
771 def weibullvariate(self, alpha, beta):
779 u = 1.0 - self.random()
796 def random(self):
800 def getrandbits(self, k):
808 def randbytes(self, n):
814 def seed(self, *args, **kwds):
818 def _notimplemented(self, *args, **kwds):