code: def mutate_random_individual(population, toolbox):
      """Picks a random individual from the population, and performs mutation on a copy of it.
  
      Parameters
      ----------
      population: array of individuals
  
      Returns
      ----------
      individual: individual
          An individual which is a mutated copy of one of the individuals in population,
          the returned individual does not have fitness.values
      """
      idx = np.random.randint(0, len(population))
      ind = population[idx]
      (ind,) = toolbox.mutate(ind)
      del ind.fitness.values
      return ind
  
file_path: tpot/tpot/gp_deap.py
imports: import numpy
  from deap import tools, gp
  from inspect import isclass
  from .operator_utils import set_sample_weight
  from sklearn.utils import indexable
  from sklearn.metrics import check_scoring
  from sklearn.model_selection._validation import _fit_and_score
  from sklearn.base import clone
  from collections import defaultdict
  import warnings
  from stopit import threading_timeoutable, TimeoutException
label_desc: Use image node_id 2 for calling a global function with example usage: mutate_random_individual(population, toolbox) and returns: ind