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EfficientKeyboard.py
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EfficientKeyboard.py
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from Algorithms.Genetic import *
from copy import deepcopy
import string
import random
class Problem(object):
def __init__(self, common_chars, common_char_pairs):
self.common_chars = common_chars
self.common_char_pairs = common_char_pairs
def initial_state(self):
keyboard = []
alphabet = list(string.ascii_lowercase)
for i in range(0, 3):
temp = []
for j in range(0, 10):
if i == 0:
temp.append(alphabet.pop(alphabet.index(random.choice(alphabet))))
else:
if j == 0 or j == 9:
temp.append('-')
else:
temp.append(alphabet.pop(alphabet.index(random.choice(alphabet))))
keyboard.append(deepcopy(temp))
return keyboard
def heuristic(self, keyboard):
left_single_char = 0
right_single_char = 0
left_pair_char = 0
right_pair_char = 0
single_score = 0
pair_score = 0
for i in range(0, 3):
for j in range(0, 10):
for key in common_chars:
if keyboard[i][j] == key and j < 5:
left_single_char = left_single_char + 1
elif keyboard[i][j] == key:
right_single_char = right_single_char + 1
for key in common_char_pairs:
key = list(key)
if keyboard[i][j] == key[0]:
if i > 0 and keyboard[i - 1][j] == key[1] and j < 5:
left_pair_char = left_pair_char + 1
elif i > 0 and keyboard[i - 1][j] == key[1] and j > 5:
right_pair_char = right_pair_char + 1
if i < 2 and keyboard[i + 1][j] == key[1] and j < 5:
left_pair_char = left_pair_char + 1
elif i < 2 and keyboard[i + 1][j] == key[1] and j > 5:
right_pair_char = right_pair_char + 1
if j > 0 and keyboard[i][j - 1] == key[1] and j < 5:
left_pair_char = left_pair_char + 1
elif j < 9 and keyboard[i][j - 1] == key[1] and j > 5:
right_pair_char = right_pair_char + 1
single_score = single_score + 9 - abs(right_single_char - left_single_char)
pair_score = pair_score + 8 - abs(right_single_char - left_single_char)
return single_score + pair_score
def crossover(self, population1, population2):
linear_population1 = []
linear_population2 = []
for i in range(0, len(population1)):
for j in range(0, len(population1[1])):
if population1[i][j] != '-':
linear_population1.append(population1[i][j])
linear_population2.append(population2[i][j])
new_population1 = deepcopy(linear_population1)
new_population2 = deepcopy(linear_population2)
new_population1[4:23], new_population2[4:23] = linear_population2[4:23], linear_population1[4:23]
temp_list1 = []
for i in range(0, 26):
i = (i + 4) % 26
if new_population1[i] not in temp_list1:
temp_list1.append(new_population1[i])
else:
for j in range(0, 26):
j = (j + 23) % 26
if new_population2[j] not in new_population1:
new_population1[i] = new_population2[j]
temp_list1.append(new_population1[i])
temp_list2 = []
for i in range(0, 26):
i = (i + 4) % 26
if new_population2[i] not in temp_list2:
temp_list2.append(new_population2[i])
else:
for j in range(0, 26):
j = (j + 23) % 26
if new_population1[j] not in new_population2:
new_population2[i] = new_population1[j]
temp_list2.append(new_population2[i])
new_population1_correct_format = deepcopy(population1)
new_population2_correct_format = deepcopy(population2)
row = 0
col = 0
for i in range(0, 26):
if i < 10:
new_population1_correct_format[row][col] = new_population1[i]
new_population2_correct_format[row][col] = new_population2[i]
else:
if col == 0:
row = row + 1
new_population1_correct_format[row][col] = '-'
new_population2_correct_format[row][col] = '-'
else:
new_population1_correct_format[row][col] = new_population1[i]
new_population2_correct_format[row][col] = new_population2[i]
col = (col + 1) % 10
return [new_population1_correct_format, new_population2_correct_format]
def mutation(self, keyboard):
not_dash = False
while not not_dash:
i1 = keyboard.index(random.choice(keyboard))
j1 = keyboard[i1].index(random.choice(keyboard[i1]))
i2 = keyboard.index(random.choice(keyboard))
j2 = keyboard[i2].index(random.choice(keyboard[i2]))
if keyboard[i1][j1] != '-' and keyboard[i2][j2] != '-':
keyboard[i1][j1], keyboard[i2][j2] = keyboard[i2][j2], keyboard[i1][j1]
not_dash = True
return keyboard
def is_goal(self, keyboard):
return self.heuristic(keyboard) == 15
common_chars = ['a', 'i', 'n', 'o', 's', 'h', 'r']
common_char_pairs = ['th', 'er', 'on', 'an', 're', 'he', 'in', 'ed']
p = Problem(common_chars, common_char_pairs)
g = Genetic(p, 10)