code: def _regressor_names(con_name, hrf_model, fir_delays=None):
      """Return a list of regressor names, \
      computed from con-name and hrf type \
      when this information is explicitly given.
  
      If hrf_model is a custom function or a list of custom functions,
      return their names.
  
      Parameters
      ----------
      con_name : string
          identifier of the condition
      %(hrf_model)s
      fir_delays : 1D array_like, optional
          Delays (in scans) used in case of an FIR model
  
      Returns
      -------
      names : list of strings,
          regressor names
  
      """
      # Default value
      names = [con_name]
  
      # Handle strings
      if hrf_model in ["glover", "spm"]:
          names = [con_name]
      elif hrf_model in ["glover + derivative", "spm + derivative"]:
          names = [con_name, f"{con_name}_derivative"]
      elif hrf_model in [
          "spm + derivative + dispersion",
          "glover + derivative + dispersion",
      ]:
          names = [
              con_name,
              f"{con_name}_derivative",
              f"{con_name}_dispersion",
          ]
      elif hrf_model == "fir":
          names = [f"{con_name}_delay_{int(i)}" for i in fir_delays]
      elif callable(hrf_model):
          names = [f"{con_name}_{hrf_model.__name__}"]
      elif isinstance(hrf_model, Iterable) and all(
          callable(_) for _ in hrf_model
      ):
          names = [
              f"{con_name}_{model.__name__}" for model in hrf_model
          ]
      elif isinstance(hrf_model, Iterable) and not isinstance(
          hrf_model, str
      ):
          names = [f"{con_name}_{i}" for i in range(len(hrf_model))]
  
      # Check that all names within the list are different
      if len(np.unique(names)) != len(names):
          raise ValueError(
              f"Computed regressor names are not unique: {names}"
          )
  
      return names
  
imports: import warnings
  from collections.abc import Iterable
  import numpy
  from scipy.stats import gamma
  from nilearn._utils import fill_doc
label_desc: Use image node_id 16 for calling a global function with example usage: _regressor_names(con_name, hrf_model, fir_delays) and returns: names