class_docstr: Handles parameter management for estimators composed of named estimators.
  
  Partly adapted from sklearn utils.metaestimator.py.
docstr: Return names for the estimators, optionally made unique.
  
  Parameters
  ----------
  estimators : list of estimators, or list of (str, estimator tuples)
  make_unique : bool, optional, default=False
      whether names should be made unique in the return
  
  Returns
  -------
  names : list of str, unique entries, of equal length as estimators
      names for estimators in estimators
      if make_unique=True, made unique using _make_strings_unique
docstr_tok: ["Return","names","for","the","estimators",",","optionally","made","unique",".","Parameters","--","--","--","--","--","estimators",":","list","of","estimators",",","or","list","of","(","str",",","estimator","tuples",")","make_unique",":","bool",",","optional",",","default=False","whether","names","should","be","made","unique","in","the","return","Returns","--","--","--","-","names",":","list","of","str",",","unique","entries",",","of","equal","length","as","estimators","names","for","estimators","in","estimators","if","make_unique=True",",","made","unique","using","_make_strings_unique"]
code: def _get_estimator_names(self, estimators, make_unique=False):
      """Return names for the estimators, optionally made unique.
  
      Parameters
      ----------
      estimators : list of estimators, or list of (str, estimator tuples)
      make_unique : bool, optional, default=False
          whether names should be made unique in the return
  
      Returns
      -------
      names : list of str, unique entries, of equal length as estimators
          names for estimators in estimators
          if make_unique=True, made unique using _make_strings_unique
      """
      names = [self._coerce_estimator_tuple(x)[0] for x in estimators]
      if make_unique:
          names = self._make_strings_unique(names)
      return names
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 14 for calling the _HeterogenousMetaEstimator obj's underlying member method code with example usage: obj._get_estimator_names(estimators, make_unique) and returns: names