NestedSampling.py 文件源码

def increment(self,logL,nlive=None):
    """
    Increment the state of the evidence integrator
    Simply uses rectangle rule for initial estimate
    """
    if(logL<=self.logLs[-1]):
      print('WARNING: NS integrator received non-monotonic logL. {0:.3f} -> {1:.3f}'.format(self.logLs[-1],logL))
    if nlive is None:
      nlive = self.nlive
    oldZ = self.logZ
    logt=-1.0/nlive
    Wt = self.logw + logL + logsubexp(0,logt)
    self.logZ = logaddexp(self.logZ,Wt)
    # Update information estimate
    if np.isfinite(oldZ) and np.isfinite(self.logZ):
      self.info = exp(Wt - self.logZ)*logL + exp(oldZ - self.logZ)*(self.info + oldZ) - self.logZ

    # Update history
    self.logw += logt
    self.iteration += 1
    self.logLs.append(logL)
    self.log_vols.append(self.logw)