class_docstr: Proxy for ClockedSamplers.
docstr: Initialise sampler.
  
  Parameters
  -----------
  nnewdirections: int
      number of accepted steps until the sample is considered independent.
  sampler: str
      which sampler to use
  nsteps:
      number of steps in sampler
  balance:
      acceptance rate to target
  scale:
      initial proposal scale
  nudge:
      adjustment factor for scale when acceptance rate is too low or high.
      must be >=1.
docstr_tok: ["Initialise","sampler",".","Parameters","--","--","--","--","--","-","nnewdirections",":","int","number","of","accepted","steps","until","the","sample","is","considered","independent",".","sampler",":","str","which","sampler","to","use","nsteps",":","number","of","steps","in","sampler","balance",":","acceptance","rate","to","target","scale",":","initial","proposal","scale","nudge",":","adjustment","factor","for","scale","when","acceptance","rate","is","too","low","or","high",".","must","be",">","=1","."]
code: def __init__(
      self,
      nnewdirections,
      sampler="steps",
      nsteps=0,
      balance=0.9,
      scale=0.1,
      nudge=1.1,
      log=False,
  ):
      """Initialise sampler.
  
      Parameters
      -----------
      nnewdirections: int
          number of accepted steps until the sample is considered independent.
      sampler: str
          which sampler to use
      nsteps:
          number of steps in sampler
      balance:
          acceptance rate to target
      scale:
          initial proposal scale
      nudge:
          adjustment factor for scale when acceptance rate is too low or high.
          must be >=1.
  
      """
      self.nsteps = nsteps
      self.samplername = sampler
      self.sampler = None
  
      self.scale = scale
      self.nudge = nudge
      self.balance = balance
      self.log = log
  
      self.last = None, None
      self.ncalls = 0
      self.nnewdirections = nnewdirections
      self.nreflections = 0
      self.nreverses = 0
      self.nsteps_done = 0
  
      self.naccepts = 0
      self.nrejects = 0
  
      self.logstat = []
      self.logstat_labels = ["accepted", "scale"]
  
imports: import numpy
  import matplotlib.pyplot
  from ultranest.samplingpath import SamplingPath, ContourSamplingPath, extrapolate_ahead
  from ultranest.stepsampler import StepSampler
  from ultranest.stepsampler import generate_region_oriented_direction, generate_region_random_direction, generate_random_direction
  from ultranest.flatnuts import ClockedStepSampler, ClockedBisectSampler, ClockedNUTSSampler
  from ultranest.flatnuts import SingleJumper, DirectJumper, IntervalJumper
label_desc: Use image node_id 1 to create a new OtherSamplerProxy object from inherited base classes: object with example: obj = OtherSamplerProxy(nnewdirections, sampler, nsteps, balance, scale, nudge, log)