def get_tau_cov(mu, tau=None, cov=None):
 if (tau is None):
  if (cov is None):
   cov = np.eye(len(mu))
   tau = np.eye(len(mu))
  else:
   tau = tt.nlinalg.matrix_inverse(cov)
 elif (cov is not None):
  raise ValueError("Can't pass both tau and sd")
 else:
  cov = tt.nlinalg.matrix_inverse(tau)
 return (tau, cov)

def get_tau_cov ( mu , tau = None , cov = None ) : if ( tau is None ) : if ( cov is None ) : cov = np . eye ( len ( mu ) ) tau = np . eye ( len ( mu ) ) else : tau = tt . nlinalg . matrix_inverse ( cov ) elif ( cov is not None ) : raise ValueError ( "Can't pass both tau and sd" ) else : cov = tt . nlinalg . matrix_inverse ( tau ) return ( tau , cov )
find precision and standard deviation .