Examples of Deap History applied to onemax and Symbreg examples. See: https://deap.readthedocs.io/en/master/api/tools.html#deap.tools.History

history_pop_eample_onemax_base.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/>.


# From https://github.com/DEAP/deap/blob/master/examples/ga/onemax_short.py

import array
import random

import numpy

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

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", array.array, typecode='b', 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.cxTwoPoint)
toolbox.register("mutate", tools.mutFlipBit, indpb=0.05)
toolbox.register("select", tools.selTournament, tournsize=3)

# Based on https://deap.readthedocs.io/en/master/api/tools.html#deap.tools.History
##################################################
history = tools.History()
# Decorate the variation operators
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)
    
    pop, log = algorithms.eaSimple(pop, toolbox, cxpb=0.5, mutpb=0.2, ngen=6, 
                                   stats=stats, halloffame=hof, verbose=True)


    ##################################################
    #Useful, source for history so you can manipulate it
    # https://github.com/DEAP/deap/blob/master/deap/tools/support.py#L21
    #print (history.genealogy_history)
    ##################################################

    # Producing a weird chart...very odd...maybe my networkx is messed up?
    ##################################################
    import matplotlib.pyplot as plt
    import networkx

    plt.figure(figsize=(10,10))
    graph = networkx.DiGraph(history.genealogy_tree)
    graph = graph.reverse()     # Make the graph top-down
    colors = [toolbox.evaluate(history.genealogy_history[i])[0] for i in graph]
    networkx.draw(graph, node_color=colors)
    plt.show()
    ##################################################
    
    return pop, log, hof

if __name__ == "__main__":
    main()

history_pop_example_symbreg_base.py

#    This file is part of EAP.
#
#    EAP 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.
#
#    EAP 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 EAP. If not, see <http://www.gnu.org/licenses/>.

# from https://github.com/DEAP/deap/blob/master/examples/gp/symbreg.py

import operator
import math
import random

import numpy

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

# Define new functions
def protectedDiv(left, right):
    try:
        return left / right
    except ZeroDivisionError:
        return 1

pset = gp.PrimitiveSet("MAIN", 1)
pset.addPrimitive(operator.add, 2)
pset.addPrimitive(operator.sub, 2)
pset.addPrimitive(operator.mul, 2)
pset.addPrimitive(protectedDiv, 2)
pset.addPrimitive(operator.neg, 1)
pset.addPrimitive(math.cos, 1)
pset.addPrimitive(math.sin, 1)
pset.addEphemeralConstant("rand101", lambda: random.randint(-1,1))
pset.renameArguments(ARG0='x')

creator.create("FitnessMin", base.Fitness, weights=(-1.0,))
creator.create("Individual", gp.PrimitiveTree, fitness=creator.FitnessMin)

toolbox = base.Toolbox()
toolbox.register("expr", gp.genHalfAndHalf, pset=pset, min_=1, max_=2)
toolbox.register("individual", tools.initIterate, creator.Individual, toolbox.expr)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
toolbox.register("compile", gp.compile, pset=pset)

def evalSymbReg(individual, points):
    # Transform the tree expression in a callable function
    func = toolbox.compile(expr=individual)
    # Evaluate the mean squared error between the expression
    # and the real function : x**4 + x**3 + x**2 + x
    sqerrors = ((func(x) - x**4 - x**3 - x**2 - x)**2 for x in points)
    return math.fsum(sqerrors) / len(points),

toolbox.register("evaluate", evalSymbReg, points=[x/10. for x in range(-10,10)])
toolbox.register("select", tools.selTournament, tournsize=3)
toolbox.register("mate", gp.cxOnePoint)
toolbox.register("expr_mut", gp.genFull, min_=0, max_=2)
toolbox.register("mutate", gp.mutUniform, expr=toolbox.expr_mut, pset=pset)

toolbox.decorate("mate", gp.staticLimit(key=operator.attrgetter("height"), max_value=17))
toolbox.decorate("mutate", gp.staticLimit(key=operator.attrgetter("height"), max_value=17))




# Based on https://deap.readthedocs.io/en/master/api/tools.html#deap.tools.History
##################################################
history = tools.History()
# Decorate the variation operators
toolbox.decorate("mate", history.decorator)
toolbox.decorate("mutate", history.decorator)
##################################################

def main():
    random.seed(318)

    pop = toolbox.population(n=20)
    hof = tools.HallOfFame(1)

    ##################################################
    history.update(pop)
    ##################################################
    
    stats_fit = tools.Statistics(lambda ind: ind.fitness.values)
    stats_size = tools.Statistics(len)
    mstats = tools.MultiStatistics(fitness=stats_fit, size=stats_size)
    mstats.register("avg", numpy.mean)
    mstats.register("std", numpy.std)
    mstats.register("min", numpy.min)
    mstats.register("max", numpy.max)

    pop, log = algorithms.eaSimple(pop, toolbox, 0.5, 0.1, 6, stats=mstats,
                                   halloffame=hof, verbose=True)


    ##################################################
    #Useful, source for history so you can manipulate it
    # https://github.com/DEAP/deap/blob/master/deap/tools/support.py#L21
    #print (history.genealogy_history)
    ##################################################

    ##################################################
    import matplotlib.pyplot as plt
    import networkx

    plt.figure(figsize=(10,10))
    graph = networkx.DiGraph(history.genealogy_tree)
    graph = graph.reverse()     # Make the graph top-down
    colors = [toolbox.evaluate(history.genealogy_history[i])[0] for i in graph]
    networkx.draw(graph, node_color=colors)
    plt.show()
    ##################################################

    # print log
    return pop, log, hof

if __name__ == "__main__":
    main()