Coverage for cosmoHammer/modules/PseudoCmbModule.py : 100%

from __future__ import print_function, division, absolute_import, unicode_literals 

import numpy as np 

from cosmoHammer import getLogger 

#the real means.. 

WMAP7_MEANS = [70.704, 0.02256, 0.1115, 2.18474E-09, 0.9688, 0.08920] 

# ...and non-trivial covariance matrix. 

_cov = np.array([[6.11E+00, 0, 0, 0, 0, 0], 

[7.19E-04, 3.26E-07, 0, 0, 0, 0], 

[-1.19E-02, -3.37E-07, 3.14E-05, 0, 0, 0], 

[-3.56E-11, 1.43E-14, 1.76E-13, 5.96E-21, 0, 0], 

[2.01E-02, 6.37E-06, -2.13E-05, 3.66E-13, 1.90E-04, 0], 

[1.10E-02, 2.36E-06, -1.92E-05, 8.70E-13, 7.32E-05, 2.23E-04]]) 

_cov += _cov.T - np.diag(_cov.diagonal()) 

# Invert the covariance matrix 

WMAP7_ICOV = np.linalg.inv(_cov) 

class PseudoCmbModule(object): 

""" 

Chain for computing the likelihood of a multivariante gaussian distribution 

""" 

def __init__(self, icov=WMAP7_ICOV, mu=WMAP7_MEANS, min_sz=0, max_sz=2): 

self.icov = icov 

self.mu = mu 

self.a = min_sz 

self.b = max_sz 

def computeLikelihood(self, ctx): 

x = ctx.getParams() 

diff = x[:6]-self.mu 

lnprob = -np.dot(diff,np.dot(self.icov,diff))/2.0 

lnprob -= np.log(self.b-self.a) 

return lnprob 

def setup(self): 

getLogger().info("Pseudo cmb setup")