class_docstr: Base class for fitness functions
  
  Each fitness function class has the following:
  - fitness(...) : compute fitness function.
     Arguments accepted by fitness must be among [T_k, N_k, a_k, b_k, c_k]
  - prior(N, Ntot) : compute prior on N given a total number of points Ntot
class_docstr_tok: ["Base","class","for","fitness","functions","Each","fitness","function","class","has","the","following",":","-","fitness","(","...",")",":","compute","fitness","function",".","Arguments","accepted","by","fitness","must","be","among","[","T_k",",","N_k",",","a_k",",","b_k",",","c_k","]","-","prior","(","N",",","Ntot",")",":","compute","prior","on","N","given","a","total","number","of","points","Ntot"]
docstr: Basic prior, parametrized by gamma (eq. 3 in Scargle 2012)
docstr_tok: ["Basic","prior",",","parametrized","by","gamma","(","eq",".","3","in","Scargle","2012",")"]
code: def gamma_prior(self, N, Ntot):
      """Basic prior, parametrized by gamma (eq. 3 in Scargle 2012)"""
      if self.gamma == 1:
          return 0
      else:
          return (
              np.log(1 - self.gamma)
              - np.log(1 - self.gamma ** (Ntot + 1))
              + N * np.log(self.gamma)
          )
  
imports: import numpy
  from astroML.utils import deprecated
  from astroML.utils.exceptions import AstroMLDeprecationWarning
label_desc: Use image node_id 6 for calling the FitnessFunc obj's underlying member method code with example usage: obj.gamma_prior(N, Ntot) and returns: int, unknown