History example with dot layout

pydot_history.py

#    This file is part of DEAP.
#
#    DEAP is free software: you can redistribute it and/or modify
#    it under the terms of the GNU Lesser General Public License as
#    published by the Free Software Foundation, either version 3 of
#    the License, or (at your option) any later version.
#
#    DEAP is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
#    GNU Lesser General Public License for more details.
#
#    You should have received a copy of the GNU Lesser General Public
#    License along with DEAP. If not, see <http://www.gnu.org/licenses/>.

import random

from deap import algorithms
from deap import base
from deap import creator
from deap import tools

import numpy

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", list, fitness=creator.FitnessMax)

toolbox = base.Toolbox()

# Attribute generator
toolbox.register("attr_bool", random.randint, 0, 1)

# Structure initializers
toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_bool, 100)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)

def evalOneMax(individual):
    return sum(individual),

toolbox.register("evaluate", evalOneMax)
toolbox.register("mate", tools.cxTwoPoints)
toolbox.register("mutate", tools.mutFlipBit, indpb=0.05)
toolbox.register("select", tools.selTournament, tournsize=3)

history = tools.History()
toolbox.decorate("mate", history.decorator)
toolbox.decorate("mutate", history.decorator)

def main():
    random.seed(64)
    
    pop = toolbox.population(n=20)
    hof = tools.HallOfFame(1)
    history.update(pop)
    
    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.eaSimple(pop, toolbox, cxpb=0.5, mutpb=0.2, ngen=5, stats=stats,
                        halloffame=hof, verbose=True)
    
    import matplotlib.pyplot as plt
    import networkx

    graph = networkx.DiGraph(history.genealogy_tree)
    graph = graph.reverse()     # Make the grah top-down
    colors = [toolbox.evaluate(history.genealogy_history[i])[0] for i in graph]
    positions = networkx.graphviz_layout(graph, prog="dot")
    
    networkx.draw(graph, positions, node_color=colors)
    plt.show()
    
    return pop, stats, hof

if __name__ == "__main__":
    main()

Is there any reason why the graph initialised using:
graph = networkx.DiGraph(history.genealogy_tree)
could be of different length than the genealogy_tree?
len(history.genealogy_tree) != len(graph)