def wp_powerlaw_model(self, rsep, r0, gamma):
"""
Power law model for wp(rp) assuming that xi = (r/r0)^-gamma.
"""
if rsep.any < 0.0:
return np.inf
return rsep * (rsep / r0)**(-gamma) * gammafn(0.5) * gammafn(
(gamma - 1.0) / 2.0) / gammafn(gamma / 2.0)
def f(a, b, m):
y = (np.arange(20000.) - 10000)/100
return gammafn(a+0.5) / (sqrt(4*pi*b) * gammafn(a)) * (1 + (y-m)**2/(4*b))**-(a+0.5)
def lik(a, b, m, y):
return gammafn(a+0.5) / (sqrt(4*pi*b) * gammafn(a)) * (1 + (y-m)**2/(4*b))**-(a+0.5)
def p(t):
return 0.25 * gammafn(10) / (gammafn(2) *
gammafn(8)) * (3 * t * (1 - t)**7 + t**7 *
(1 - t))
def lgamma(x):
return gammafn(np.log(x))
