code: def range_search_reference(self, index, parameters, range_metric):
      logger.info("range_search_reference: begin")
      if isinstance(range_metric, list):
          assert len(range_metric) > 0
          m_radius = (
              max(rm[-2] for rm in range_metric)
              if self.distance_metric_type == faiss.METRIC_L2
              else min(rm[-2] for rm in range_metric)
          )
      else:
          m_radius = range_metric
  
      lims, D, I, R, P, _ = self.range_search(
          False,
          index,
          parameters,
          radius=m_radius,
      )
      flat = index.factory == "Flat"
      (
          gt_radius,
          range_search_metric_function,
          coefficients,
          coefficients_training_data,
      ) = get_range_search_metric_function(
          range_metric,
          D if not flat else None,
          R if not flat else None,
      )
      logger.info("range_search_reference: end")
      return (
          gt_radius,
          range_search_metric_function,
          coefficients,
          coefficients_training_data,
      )
  
imports: import logging
  from copy import copy
  from dataclasses import dataclass
  from operator import itemgetter
  from statistics import median, mean
  from typing import Any, Dict, List, Optional
  from .utils import dict_merge
  from .index import Index, IndexFromCodec, IndexFromFactory
  from .descriptors import DatasetDescriptor, IndexDescriptor
  import faiss
  import numpy
  from scipy.optimize import curve_fit
label_desc: Use image node_id 4 for calling the Benchmark obj's underlying member method code with example usage: obj.range_search_reference(index, parameters, range_metric) and returns: gt_radius,  range_search_metric_function,  coefficients,  coefficients_training_data