class ChTest(unittest.TestCase):
def setUp(self):
rects = [(2, 12), (12, 2), (4, 17), (17, 4), (5, 14), (14, 5), (7, 25), (25, 7), (22, 14), (14, 22), (12, 29), (29, 12), (18, 24), (24, 18), (22, 20), (20, 22), (26, 18), (18, 26), (18, 27), (27, 18)]
self.g = Guillotine((60, 60), rects)
self.cut = (0, 0, 17, 4, 1, (17, 0, 17, 4, 1, (34, 0, 17, 4, 1, None, None), None), (0, 4, 12, 29, 1, (12, 4, 12, 2, 1, None, (12, 6, 18, 24, 1, (30, 6, 12, 2, 1, (42, 6, 12, 2, 1, None, None), (30, 8, 12, 2, 1, None, (30, 10, 25, 7, 1, None, (30, 17, 14, 5, 1, (44, 17, 12, 2, 1, None, None), None)))), None)), (0, 33, 22, 20, 1, (22, 33, 12, 2, 1, (34, 33, 12, 2, 1, None, None), (22, 35, 5, 14, 1, (27, 35, 5, 14, 1, (32, 35, 2, 12, 1, (34, 35, 2, 12, 1, (36, 35, 2, 12, 1, (38, 35, 2, 12, 1, (40, 35, 2, 12, 1, (42, 35, 2, 12, 1, (44, 35, 2, 12, 1, (46, 35, 2, 12, 1, (48, 35, 12, 2, 1, None, None), None), None), None), None), None), None), None), None), None), (22, 49, 17, 4, 1, None, None))), None)))
self.pieces = [(17, 4), (17, 4), (17, 4), (12, 29), (12, 2), (18, 24), (12, 2), (12, 2), (12, 2), (25, 7), (14, 5), (12, 2), (22, 20), (12, 2), (12, 2), (5, 14), (5, 14), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (12, 2), (17, 4)]
self.sorted_pieces = sorted(self.pieces, key=cmp_to_key(self.__cmp))
def test_lower_y(self):
pieces = sorted(self.g.pieces(self.cut), key=cmp_to_key(self.__cmp))
self.assertEqual(len(self.sorted_pieces), len(pieces))
self.assertEqual(self.sorted_pieces, pieces)
def test_cut(self):
pieces = self.g.pieces(self.cut)
self.assertEqual(self.cut, self.g.cut(pieces))
def __cmp(self, a, b):
if a[0] == b[0]:
return a[1] - b[1]
else:
return a[0] - b[0]
def loading_structural(self, structpath=None):
"""
Loading structural data.
"""
# load structural volume
print "Loading structural information file"
self.structpath = structpath
self.img = nib.load(self.structpath)
data = self.img.get_data()
self.affine = self.img.get_affine()
self.dims = data.shape[:3]
# verifying if structural is color_fa created by TrackVis :: Diffusion Toolkit
if data.dtype == [('R', '|u1'), ('G', '|u1'), ('B', '|u1')]:
data1 = data.view((np.uint8, len(data.dtype.names)))
data = data1
del data1
# Create the Guillotine object
data = (np.interp(data, [data.min(), data.max()], [0, 255]))
self.guil = Guillotine('Volume Slicer', data, np.copy(self.affine))
self.scene.add_actor(self.guil)
from simulated_anealing_cut2d import SimulatedAnnealing
from plotter import Painter
from guillotine_draw import PainterGui
cut_file_path = 'cut.png'
plot_file_path = 'plot.png'
W, H, n, a, b, c, d, e = [int(s) for s in input().split(" ")]
rects = []
for i in range(0, int(n)):
w, h, a, b, c = [int(s) for s in input().split(" ")]
rects.append((w, h))
g = Guillotine((W, H), rects)
p = Painter()
s = SimulatedAnnealing(W, H, rects)
initial = s.initial_solution()
costs, temperatures, solution, stats = SimulatedAnnealing.execute(s, initial)
#stats: (self.__waste(solution), len(self.rects), WxH, self.__cost(start), average, self.__cost(solution))
cut = g.cut(solution)
gui = PainterGui(W, H)
gui.drawGuillotine(cut)
gui.save(cut_file_path)
gui.end()
p.draw(costs, temperatures, plot_file_path)
def setUp(self):
rects = [(2, 12), (12, 2), (4, 17), (17, 4), (5, 14), (14, 5), (7, 25), (25, 7), (22, 14), (14, 22), (12, 29), (29, 12), (18, 24), (24, 18), (22, 20), (20, 22), (26, 18), (18, 26), (18, 27), (27, 18)]
self.g = Guillotine((60, 60), rects)
self.cut = (0, 0, 17, 4, 1, (17, 0, 17, 4, 1, (34, 0, 17, 4, 1, None, None), None), (0, 4, 12, 29, 1, (12, 4, 12, 2, 1, None, (12, 6, 18, 24, 1, (30, 6, 12, 2, 1, (42, 6, 12, 2, 1, None, None), (30, 8, 12, 2, 1, None, (30, 10, 25, 7, 1, None, (30, 17, 14, 5, 1, (44, 17, 12, 2, 1, None, None), None)))), None)), (0, 33, 22, 20, 1, (22, 33, 12, 2, 1, (34, 33, 12, 2, 1, None, None), (22, 35, 5, 14, 1, (27, 35, 5, 14, 1, (32, 35, 2, 12, 1, (34, 35, 2, 12, 1, (36, 35, 2, 12, 1, (38, 35, 2, 12, 1, (40, 35, 2, 12, 1, (42, 35, 2, 12, 1, (44, 35, 2, 12, 1, (46, 35, 2, 12, 1, (48, 35, 12, 2, 1, None, None), None), None), None), None), None), None), None), None), None), (22, 49, 17, 4, 1, None, None))), None)))
self.pieces = [(17, 4), (17, 4), (17, 4), (12, 29), (12, 2), (18, 24), (12, 2), (12, 2), (12, 2), (25, 7), (14, 5), (12, 2), (22, 20), (12, 2), (12, 2), (5, 14), (5, 14), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (2, 12), (12, 2), (17, 4)]
self.sorted_pieces = sorted(self.pieces, key=cmp_to_key(self.__cmp))
class SimulatedAnnealing:
MAX_INTERATIONS = 400 # iterações
MAX_RANDOMIZE = 1000 # perturbações
MAX_SUCESS = 1000000 # sucessos
ALPHA = 0.8
def __init__(self, w, h, rects):
self.w = w
self.h = h
self.rects = rects
self.guillotine = Guillotine((w, h), rects)
def __cut2d(self, pieces):
return sum([x[0] * x[1] for x in pieces])
def __cost(self, solution):
return self.__cut2d(solution)
def __diff_solution(self, solutionA, solutionB):
return self.__cost(solutionA) - self.__cost(solutionB)
def __randomize(self, solution):
return self.guillotine.change(solution)
def initial_solution(self):
area = 0
pieces = []
while area < self.w * self.h:
p = choice(self.rects)
pieces.append(p)
area += p[0] * p[1]
cut = self.guillotine.cut(pieces)
return self.guillotine.pieces(cut)
def __diff_values(self, solution):
self.start = solution
for i in range(0, 100):
initial_solution = solution
solution = self.initial_solution()
if self.__cost(solution) > self.__cost(self.start):
self.start = solution
diff_s = self.__diff_solution(initial_solution, solution)
if diff_s > 0:
yield diff_s
def __initial_temperature(self, solution):
SECRET = 4.48 # DESCRIBE THIS VARIABLE
diffs = self.__diff_values(solution)
l = list(diffs)
return SECRET * (sum(l) / len(l))
def __waste(self, solution):
total = self.w * self.h
return ((total - self.__cost(solution)) / total) * 100
def execute(self, start):
t0 = time.time()
temperature = self.__initial_temperature(start)
success_iterator = 0
temperatures = []
costs = []
solutions = []
solution = self.start
no_change_counter = 0
for j in range(0, self.MAX_INTERATIONS):
for i in range(0, self.MAX_RANDOMIZE):
new_solution = self.__randomize(solution)
diff_s = self.__diff_solution(new_solution, solution)
try:
if diff_s >= 0 or math.exp(
-diff_s / temperature) > uniform(0, 1):
solution = new_solution
success_iterator = success_iterator + 1
except:
pass
if success_iterator >= self.MAX_SUCESS:
break
solutions.insert(j, self.__cost(solution))
if j > 0 and solutions[j] == solutions[j - 1]:
no_change_counter += 1
else:
no_change_counter = 0
temperatures.append(temperature)
costs.append(self.__cost(solution))
temperature = self.ALPHA * temperature
if success_iterator == 0 or 0.2 * self.MAX_INTERATIONS <= no_change_counter: # stop condition
break
average = sum(solutions) / len(solutions)
return temperatures, costs, solution, (self.__waste(solution),
len(self.rects),
"{0}x{1}".format(
self.w, self.h),
self.__cost(start), average,
self.__cost(solution),
time.time() - t0, "{0}".format(
dict(Counter(solution))))
def __init__(self, w, h, rects):
self.w = w
self.h = h
self.rects = rects
self.guillotine = Guillotine((w, h), rects)