code: def main():
      numpy.random.seed()
  
      # The CMA-ES One Plus Lambda algorithm takes a initialized parent as argument
      parent = creator.Individual(
          (numpy.random.rand() * 5) - 1 for _ in range(N)
      )
      parent.fitness.values = toolbox.evaluate(parent)
  
      strategy = cma.StrategyOnePlusLambda(
          parent, sigma=5.0, lambda_=10
      )
      toolbox.register(
          "generate", strategy.generate, ind_init=creator.Individual
      )
      toolbox.register("update", strategy.update)
  
      hof = tools.HallOfFame(1)
      stats = tools.Statistics(lambda ind: ind.fitness.values)
      stats.register("avg", numpy.mean)
      stats.register("std", numpy.std)
      stats.register("min", numpy.min)
      stats.register("max", numpy.max)
  
      algorithms.eaGenerateUpdate(
          toolbox, ngen=200, halloffame=hof, stats=stats
      )
  
file_path: deap/examples/es/cma_1+l_minfct.py
imports: import numpy
  from deap import algorithms
  from deap import base
  from deap import benchmarks
  from deap import cma
  from deap import creator
  from deap import tools
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types