def __init__(self, name , mu, p, k, a, b):
rv_continuous.__init__(self, name)
self.mu = mu
self.k = k
self.p = p
self.a = a
self.b = b
def __init__(self, p, sigma1, mu1, sigma2, mu2):
rv_continuous.__init__(self)
self.p = p
self.sigma2 = sigma2
self.sigma2 = sigma2
self.sigma1 = sigma1
self.mu1 = mu1
def __init__(self, name, mu, p, k, a, b):
rv_continuous.__init__(self, name)
self.mu = mu
self.k = k
self.p = p
self.a = a
self.b = b
def __init__(self, p, sigma1, mu1, a, b):
rv_continuous.__init__(self)
self.p = p
self.a = a
self.b = b
self.sigma1 = sigma1
self.mu1 = mu1
def __init__(self, p, sigma1, mu1, a, b):
rv_continuous.__init__(self)
self.p = p
self.a = a
self.b = b
self.sigma1 = sigma1
self.mu1 = mu1
def __init__(self, p, sigma1, mu1, sigma2, mu2):
rv_continuous.__init__(self)
self.p = p
self.sigma2 = sigma2
self.sigma2 = sigma2
self.sigma1 = sigma1
self.mu1 = mu1
def __init__(self, filename, **args):
rv_continuous.__init__(self, **args)
df = pd.pandas.read_csv(filename)
self.table = df.values
self.counter = 0
self.gist = np.linspace(0, 1, self.table.shape[1] + 1)
self.max_time = self.table.shape[0]
def __init__(self, m):
self.shapes = ''
for i in range(m):
self.shapes += 'k%d,l%d' % (i,i)
self.shapes += ',scale'
rv_continuous.__init__(self, a=-np.inf, b=np.inf, shapes=self.shapes)
self.numargs = 2*m
def __init__(self,name, lambda1, lambda2, p, a,b):
rv_continuous.__init__(self, name)
self.lambda1 = lambda1
self.lambda2 = lambda2
self.p = p
self.a = a
self.b = b
def __init__(self, name, lambda1, lambda2, p, a, b):
rv_continuous.__init__(self, name)
self.lambda1 = lambda1
self.lambda2 = lambda2
self.p = p
self.a = a
self.b = b
def __init__(self,
abulge,
rcut,
momtype=1,
a=None,
b=None,
xtol=1e-14,
badvalue=None,
name=None,
longname=None,
shapes=None,
extradoc=None,
seed=None):
rv_continuous.__init__(self, momtype, a, b, xtol, badvalue, name,
longname, shapes, extradoc, seed)
self.abulge = abulge
self.rcut = rcut
def __init__(self,
a_plum,
Mcluster,
momtype=1,
a=0,
b=None,
xtol=1e-14,
badvalue=None,
name=None,
longname=None,
shapes=None,
extradoc=None,
seed=None):
rv_continuous.__init__(self, momtype, a, b, xtol, badvalue, name,
longname, shapes, extradoc, seed)
self.a_plum = a_plum
self.Mcluster = Mcluster
def __init__(self, low=0, high=1):
rv_continuous.__init__(self,
a=np.exp(low),
b=np.exp(high))
self._low = low
self._high = high
def __init__(self, name, lambda1, lambda2, p):
rv_continuous.__init__(self, name)
self.lambda1 = lambda1
self.lambda2 = lambda2
self.p = p
def __init__(self,k, mu):
rv_continuous.__init__(self, "erlang")
self.mu = mu
self.k = k
def __init__(self,alpha, mu):
rv_continuous.__init__(self, "gamma")
self.alpha = alpha
self.mu = mu
def __init__(self,a, mu,k ):
rv_continuous.__init__(self, "gamma")
self.a = a
self.mu = mu
self.k = k
def __init__(self, a, mu, k):
rv_continuous.__init__(self, "gamma")
self.a = a
self.mu = mu
self.k = k
def __init__(self, mass): rv_continuous.__init__(self) self.mass = mass
def __init__(self, k, mu):
rv_continuous.__init__(self, "erlang")
self.mu = mu
self.k = k
def __init__(self, name, mu, p, k):
rv_continuous.__init__(self, name)
self.mu = mu
self.k = k
self.p = p
def __init__(self,name, lambda1, lambda2, p):
rv_continuous.__init__(self, name)
self.lambda1 = lambda1
self.lambda2 = lambda2
self.p = p
def __init__(self):
rv_continuous.__init__(self, a=-np.inf, b=np.inf)
def __init__(self, name , mu, p, k):
rv_continuous.__init__(self, name)
self.mu = mu
self.k = k
self.p = p
def __init__(self, mu, sigma):
self.mu_ = mu
self.s_ = sigma
self.norm_ = scipy.stats.norm
rv_continuous.__init__(self, a=0.0, name='loguniform', shapes='s')
def __init__(self, discrete_d, continuous_cases, **kwargs):
rv_continuous.__init__(self, **kwargs)
assert isinstance(discrete_d, rv_sample)
self.discrete_d = discrete_d
self.continuous_cases = continuous_cases
def __init__(self, mu, sigma):
self.mu_ = mu
self.s_ = sigma
self.norm_ = scipy.stats.norm
rv_continuous.__init__(self, a=0.0, name='loguniform', shapes='s')
def __init__(self, alpha, mu):
rv_continuous.__init__(self, "gamma")
self.alpha = alpha
self.mu = mu
def __init__(self, discrete_d, smooth_scale=0.01, **kwargs):
rv_continuous.__init__(self, **kwargs)
assert isinstance(discrete_d, rv_sample)
self.discrete_d = discrete_d
self.smooth_scale = smooth_scale
def __init__(self, low=0, high=1):
rv_continuous.__init__(self, a=np.exp(low), b=np.exp(high))
self._low = low
self._high = high
def __init__(self, mu, a, b, resolution):
rv_continuous.__init__(self, a=a, b=b)
self.cumulativeMu = np.cumsum(mu)
self.res = resolution
