def printEquationPopulation(population, generation):
size = len(population)
equation_dict = {}
#print (colored("Size of population: %d", 'blue') %(len(population)))
for tree in population:
path = []
recombination.loadPaths(tree.root, path)
equation = fitness.createEquation(path)
error = fitness.fitnessValue(tree)
if equation not in set(equation_dict.keys()):
equation_dict[equation] = {}
equation_dict[equation][error] = 1
else:
equation_dict[equation][error] += 1
#Output Generation Number
first_part = colored("\nGENERATION: %d ", 'magenta') % (generation)
boundary = "=" * 100
second_part = colored(boundary, 'magenta')
print first_part + second_part
#Sort based on value of dictionary
sorted_equation = sorted(equation_dict.iteritems(), key=lambda x: x[1])
for i, equation_and_error in enumerate(sorted_equation):
for j in range(0, equation_and_error[1].values()[0]):
equation = (colored("%s", 'green') % (equation_and_error[0]))
error = (colored("Fitness: %s", 'blue') %
(equation_and_error[1].keys()[0]))
print equation + " === " + error
population_fitness = map(lambda x: x.fitness, population)
mean_fitness = sum(population_fitness) / float(size)
best_fitness = min(population_fitness)
output_mean_fitness = colored("Mean Fitness: %f",
'yellow') % (mean_fitness)
output_best_fitness = colored("Best Fitness: %f", 'red') % (best_fitness)
mean_best.write(str(mean_fitness) + " " + str(best_fitness) +
"\n") #Write to file
print output_mean_fitness + "\n" + output_best_fitness
def printEquationPopulation(population, generation):
size = len(population)
equation_dict = {}
#print (colored("Size of population: %d", 'blue') %(len(population)))
for tree in population:
path = []
recombination.loadPaths(tree.root, path)
equation = fitness.createEquation(path)
error = fitness.fitnessValue(tree)
if equation not in set(equation_dict.keys()):
equation_dict[equation] = {}
equation_dict[equation][error] = 1
else:
equation_dict[equation][error] += 1
#Output Generation Number
first_part = colored("\nGENERATION: %d ", 'magenta') %(generation)
boundary = "=" * 100
second_part = colored(boundary, 'magenta')
print first_part + second_part
#Sort based on value of dictionary
sorted_equation = sorted(equation_dict.iteritems(), key=lambda x: x[1])
for i, equation_and_error in enumerate(sorted_equation):
for j in range(0, equation_and_error[1].values()[0]):
equation = (colored("%s", 'green') %(equation_and_error[0]))
error = (colored("Fitness: %s", 'blue') %(equation_and_error[1].keys()[0]))
print equation + " === " + error
population_fitness = map(lambda x: x.fitness, population)
mean_fitness = sum(population_fitness)/float(size)
best_fitness = min(population_fitness)
output_mean_fitness = colored("Mean Fitness: %f", 'yellow') %(mean_fitness)
output_best_fitness = colored("Best Fitness: %f", 'red') %(best_fitness)
mean_best.write(str(mean_fitness) + " " + str(best_fitness) + "\n") #Write to file
print output_mean_fitness + "\n" + output_best_fitness
def printEquation(tree):
path = []
recombination.loadPaths(tree.root, path)
equation = fitness.createEquation(path)
print equation
def printEquation(tree): path = [] recombination.loadPaths(tree.root, path) equation = fitness.createEquation(path) print equation
