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Finished, working on biodiversity
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@solomondg
solomondg committed Nov 6, 2015
1 parent cbe27ac commit 0eb0b1b
Showing 1 changed file with 97 additions and 69 deletions.
166 changes: 97 additions & 69 deletions main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,9 +31,9 @@
# pass


mutation_rate = 100 # (out of 100)
mutation_rate = 3 # (out of 100)

population_size = 32
population_size = 256


def chromosonegen():
Expand Down Expand Up @@ -62,29 +62,32 @@ def __init__(self, input_chromosone=5):
self.chromosone = input_chromosone


def point_swap(input_chromosone, outside_chromosone):
def point_swap(chrom1, chrom2):
"""Swaps genes between two points in an input and output chromosone"""
swap_pos = random.randrange(1, 5, 1) # Randomly picks pos to swap at
return input_chromosone[:swap_pos] + outside_chromosone[swap_pos:] # swaps
swap_pos = random.randint(0, 6) # Randomly picks pos to swap at
return chrom1[swap_pos:] + chrom2[:swap_pos]


def fragment_return(chromosone, startpos, endpos):
return chromosone[startpos:endpos]


def evaluator(to_eval):
x = to_eval.chromosone
# print (to_eval.chromosone)
angle_set = [find_angle(x[5], x[0], x[1]), # Run the find angle function
find_angle(x[0], x[1], x[2]), # with all the vertcies
find_angle(x[1], x[2], x[3]),
find_angle(x[2], x[3], x[4]),
find_angle(x[3], x[4], x[5]),
find_angle(x[4], x[5], x[0])]
total_error = 0
for y in angle_set:
total_error += math.fabs(60-y) # Calculate total error with abs(60-y)
return total_error
x = to_eval.chromosone # print (to_eval.chromosone)
try:
angle_set = [find_angle(x[5], x[0], x[1]), # Run the find anglefunction
find_angle(x[0], x[1], x[2]), # with all the vertcies
find_angle(x[1], x[2], x[3]),
find_angle(x[2], x[3], x[4]),
find_angle(x[3], x[4], x[5]),
find_angle(x[4], x[5], x[0])]
total_error = 0
for y in angle_set:
total_error += math.fabs(60-y) # Calculate totalerror withabs(60-y)
# print (total_error)
return total_error
except ZeroDivisionError:
return 360


def find_angle(vertA, vertB, vertC):
Expand Down Expand Up @@ -156,6 +159,8 @@ def fitness_select(fitness_dict):
lastobj = z[(adjusted_fitness_list[x]-360) * -1] # Lastobj
x += 1
winner = lastobj # Step 6
if evaluator(winner) == 360:
winner = fitness_select(fitness_dict)
return winner


Expand All @@ -169,9 +174,21 @@ def roulette_generate(fitness_dict, genmethod):
return fitness_select(fitness_dict).chromosone
elif genmethod == 1:
# print (fitness_select(fitness_dict))
return point_swap(
fitness_select(fitness_dict).chromosone,
fitness_select(fitness_dict).chromosone)
x = fitness_select(fitness_dict).chromosone
y = fitness_select(fitness_dict).chromosone
while checker(x, y):
y = fitness_select(fitness_dict).chromosone
x = fitness_select(fitness_dict).chromosone
return point_swap(x, y)


def checker(a, b):
returns = False
while n in a:
for m in b:
if n == m:
returns = True
return returns


def initiate_population():
Expand All @@ -188,62 +205,67 @@ def generate_generation(population_list):
for x in range(0, len(population_list)):
population_list[x].chromosone = \
roulette_generate(make_fitness_dict(population_list), 1)
# print ("generated generation " + str(x))
return population_list


def mutation_chance(mutation_rate):
x = random.randint(0, 100)
if x == (round((100.0/mutation_rate)/2)):
if x < mutation_rate:
return True
else:
return False


def random_mutation(individual):
x = random.randint(0, 128)
print (individual)
if x < 8:
individual = bound_mutation(individual)
elif x < 32:
individual = chromosone_regen(individual)
elif x < 64:
individual = chromosone_scramble(individual)
else:
individual = arithmatic_mutation(individual)
# x = random.randint(0, 128)
# print (individual.chromosone)
# chromosone_regen(individual)
individual = chromosone_scramble(individual)
# print (individual.chromosone)
# if x < 8:
# individual = bound_mutation(individual)
# elif x < 32:
# individual = chromosone_regen(individual)
# elif x < 64:
# individual = chromosone_scramble(individual)
# else:
# individual = arithmatic_mutation(individual)
return individual


def bound_mutation(individual):
if random.randint(0, 1) == 0:
# Lower Bound Mutation
y = Vertex(0, 0)
individual.chromosone = [y, y, y, y, y, y]
else:
# upper bound mutation
y = Vertex(10, 10)
individual.chromosone = [y, y, y, y, y, y]
return individual


def arithmatic_mutation(individual):
x = random.randint(1, 4)
z = random.randint(1, 10)
a = random.randint(1, 10)
for y in range(len(individual.chromosone)):
print (individual.chromosone[y])
if x == 1:
individual.chromosone[y].x += z
individual.chromosone[y].y += a
elif x == 2:
individual.chromosone[y].x -= z
individual.chromosone[y].y -= a
elif x == 3:
individual.chromosone[y].x = individual.chromosone[y].x * z
individual.chromosone[y].y = individual.chromosone[y].z * a
elif x == 4:
individual.chromosone[y].x = individual.chromosone[y].x / z
individual.chromosone[y].y = individual.chromosone[y].z / a
return individual
# def bound_mutation(individual):
# if random.randint(0, 1) == 0:
# # Lower Bound Mutation
# y = Vertex(1, 1)
# individual.chromosone = [y, y, y, y, y, y]
# else:
# # upper bound mutation
# y = Vertex(10, 10)
# individual.chromosone = [y, y, y, y, y, y]
# return individual


# def arithmatic_mutation(individual):
# x = random.randint(1, 4)
# z = random.randint(1, 10)
# a = random.randint(1, 10)
# x = 1
# temp = []
# for y in range(len(temp)):
# if x == 1:
# temp[y] = Vertex(individual.chromosone[y].x + z,
# individual.chromosone[y].y + a)
# elif x == 2:
# temp[y].x = individual.chromosone[y].x - z
# temp[y].y = individual.chromosone[y].y - a
# elif x == 3:
# temp[y].x = individual.chromosone[y].x * z
# temp[y].y = individual.chromosone[y].z * a
# elif x == 4:
# temp[y].x = individual.chromosone[y].x / z
# temp[y].y = individual.chromosone[y].z / a
# return temp


def chromosone_regen(individual):
Expand All @@ -252,9 +274,9 @@ def chromosone_regen(individual):


def chromosone_scramble(individual):
for x in range(0, random.randint(0, 100)):
individual.chromosone = \
point_swap(individual.chromosone, individual.chromosone)
# for x in range(random.randint(0, 100)):
individual.chromosone = \
point_swap(individual.chromosone, individual.chromosone)
return individual

popset = initiate_population()
Expand All @@ -268,12 +290,18 @@ def chromosone_scramble(individual):

# print (y.chromosone)
y = 0
for n in range(0, 1024):
for n in range(1024):
x = make_fitness_dict(popset)
popset = generate_generation(popset)
y += 1
print ("Generation " + str(y) + ". Example roulette selection is " +
str(evaluator(fitness_select(x))))
for n in range(0, len(popset)):
if mutation_chance(0.02) == True:
popset[n] = random_mutation(popset[n])
# for n in range(0, len(popset)):
# if mutation_chance(mutation_rate):
# popset[n] = random_mutation(popset[n])
fitlist = []
for z in x:
fitlist.append(x[z])
a = findmax(x, fitlist[0])
print (a.chromosone)

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