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import numpy as N
class VarianceFunction:
"""
Variance function that relates the variance of a random variable
to its mean. Defaults to 1.
"""
def __call__(self, mu):
return N.ones(mu.shape, N.float64)
constant = VarianceFunction()
class Power:
"""
Variance function:
V(mu) = fabs(mu)**power
"""
def __init__(self, power=1.):
self.power = power
def __call__(self, mu):
return N.power(N.fabs(mu), self.power)
class Binomial:
"""
Binomial variance function
p = mu / n; V(mu) = p * (1 - p) * n
"""
tol = 1.0e-10
def __init__(self, n=1):
self.n = n
def clean(self, p):
return N.clip(p, Binomial.tol, 1 - Binomial.tol)
def __call__(self, mu):
p = self.clean(mu / self.n)
return p * (1 - p) * self.n
mu = Power()
mu_squared = Power(power=2)
mu_cubed = Power(power=3)
binary = Binomial()
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