def calculate_and_solve(framework):
### calculate each position array###
v_poss = f.list_verticle_framework(framework)
h_poss = f.list_horizontal_framework(framework)
b_poss = f.list_box_framework(framework)
framework_with_positional_element = f.generate_positional_array(framework)
### solve ####
status, remain_possible = f.solve(framework_with_positional_element,
framework, 1, v_poss, h_poss, b_poss)
return [framework, status, remain_possible]
def main():
with open('input.txt') as file_object:
contents = file_object.read().splitlines()
start = time.time()
result = functions.solve(contents)
print("Part 1 solution (area of overlapping claims): " + str(result) +
" found in " + str(time.time() - start))
start = time.time()
result = functions.solve_part2(contents)
print("Part 2 solution (single non-overlapping claim): " +
str(result) + " found in " + str(time.time() - start))
if __name__ == '__main__':
# starting parallel workers
multiprocessing.set_start_method('spawn', True)
workers = Pool(functions.num_workers)
# training phase (Tensorflow graph activation, performing CMA-ES optimisation)
with functions.sess.as_default():
functions.sess.run(tf.compat.v1.global_variables_initializer())
saver = tf.compat.v1.train.Saver()
cma = CMAES(functions.NPARAMS,
sigma_init=functions.sigma,
weight_decay=0,
popsize=functions.NPOPULATION)
cma_history = functions.solve(cma, workers)
# loading learned gait after training
with open(functions.save_dir, 'rb') as f:
bestparams = pickle.load(f)
with open(functions.max_fit_dir, 'rb') as f:
history = pickle.load(f)
# testing learned gait
functions.env[0].reset()
time.sleep(2)
fitness = functions.fitness_func(bestparams, True)
# showing reward/time graph
plt.plot(history)
plt.show()
import functions as f
from pathlib import Path
import cv2
img_path = Path.cwd().joinpath('data').joinpath('diplom_data').joinpath(
'raw').joinpath('008.jpg')
img = cv2.imread(str(img_path))
f.solve(img)
sudoku = [
[0, 9, 0, 3, 6, 0, 1, 0, 4],
[0, 7, 5, 0, 0, 2, 3, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 7],
[0, 0, 3, 4, 8, 0, 0, 0, 0],
[0, 4, 0, 0, 0, 0, 0, 7, 0],
[0, 0, 0, 0, 2, 5, 4, 0, 0],
[8, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 8, 0, 0, 6, 3, 0],
[6, 0, 4, 0, 3, 1, 0, 2, 0],
]
def print_sudoku(grid):
for i in range(len(grid)):
if i % 3 == 0 and i != 0:
print("- - - - - - - - - - - - - ")
for j in range(len(grid[0])):
if j % 3 == 0 and j != 0:
print(" | ", end=" ")
if j == 8:
print(grid[i][j])
else:
print(grid[i][j], end=" ")
print_sudoku(sudoku)
solve(sudoku)
print("________________________")
print_sudoku(sudoku)
libraries_num = content[0][1]
days = content[0][2]
scores_of_books = content[1]
libraries = []
# print (scores_of_books)
for x in range(1, len(content) / 2):
# books = {}
# for b in content[x * 2 + 1]:
# books[b] = book(b,scores_of_books[b])
books = []
for b in content[x * 2 + 1]:
books.append(book(b, scores_of_books[b]))
books.sort(key=lambda x: x.score, reverse=True)
libraries.append(
lib(x - 1, content[x * 2][0], content[x * 2][1], content[x * 2][2],
books))
print("done reading file")
ret = solve(days, libraries)
ret = [' '.join(map(str, x)) for x in ret]
with open("output/" + filename + ".out", "w") as f:
for item in ret:
print >> f, item
print("all done.")
# print (ret)