class_docstr: Creates a suitable auxiliary distribution from samples of likelihood values
  
  The distribution is the CDF of a beta distribution, with
  0 -> logLmin
  1 -> 90% quantile of logLs
  0.5 -> 10% quantile of logLs
  
  .modify_Lgrad() returns the conversion from logL, grad to the
  equivalents on the auxiliary distribution.
  
  .__call__(x) returns logL, grad on the auxiliary distribution.
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code: def generate_momentum(self):
      return generate_momentum_flattened(self.d, self.massmatrix)
      return generate_momentum_normal(self.d, self.massmatrix)
      return generate_momentum(
          self.d, self.massmatrix, self.alpha, self.beta
      )
  
imports: import numpy
  import matplotlib.pyplot
  import scipy.special
  import scipy.stats
label_desc: Use image node_id 4 for calling the FlattenedProblem obj's underlying member method code with example usage: obj.generate_momentum() and returns: generate_momentum_flattened, generate_momentum_normal, generate_momentum