def decode_geometry_msg(request_geometries):
product_boxes = []
for sp in request_geometries:
product_boxes.append(
Cuboid(Point(sp.dimensions))
)
return product_boxes
class DFTRCStrategy(PlacementStrategy):
def __init__(self, container_spec: Cuboid):
self.container_spec = container_spec
self.container_upper_right = Point(
self.container_spec.dimensions.coords)
# DFTRC-2 Distance to the Front Top Right Corner
def find_best_placement_space(self, container: Container,
product_box: Cuboid) -> Space:
max_dist = -1.0
best_ems = None
orientations = product_box.get_rotation_permutations()
for ems in container.empty_space_list:
if ems.volume() >= product_box.volume():
max_dist, best_ems = self._find_best_ems_for_orientations(
max_dist, best_ems, ems, orientations)
return best_ems
def _find_best_ems_for_orientations(self, max_dist, best_ems, ems: Space,
orientations: []) -> (float, Space):
fitting_orientations = (o for o in orientations if o.can_fit_in(ems))
for orientation in fitting_orientations:
box_upper_right = Space.from_placement(ems.origin(),
orientation).upper_right
dist = self.container_upper_right.squared_distance_from(
box_upper_right)
if dist > max_dist:
max_dist = dist
best_ems = ems
return max_dist, best_ems
def __calculate_genetic_parameters(parameters: dict, num_items: int):
parameters['population_size'] = parameters['population_factor'] * num_items
parameters['num_elites'] = int(parameters['elites_percentage'] *
parameters['population_size'])
parameters['num_mutants'] = int(parameters['mutants_percentage'] *
parameters['population_size'])
if parameters['delivery_bin_spec'] is None:
parameters['delivery_bin_spec'] = [30, 30, 30]
parameters['delivery_bin_spec'] = Cuboid(
Point(np.array(parameters['delivery_bin_spec'])))
return parameters
def read_csv_data(file="data/product_boxes.csv"):
product_boxes = []
with open(file, 'r') as csvfile:
reader = csv.DictReader(csvfile, delimiter=',')
for row in reader:
count = int(row['count'])
index = 0
while index < count:
product_boxes.append(
Cuboid(
Point.from_scalars(int(row['width']),
int(row['depth']),
int(row['height']))))
index += 1
return product_boxes
def create_vertices(cuboid):
o = Point.new_origin().coords
u = cuboid.dimensions.coords
return create_vertices_from_points(o, u)
float(placement_solution.box_id) /
len(delivery_bins[del_bin]),
float(placement_solution.box_id) /
len(delivery_bins[del_bin]), 1))
plt.show()
def plot_placements(container_bin, placements, plot_spaces=False):
g = plot_container(container_bin)
for i, product_placement in enumerate(placements):
if product_placement:
draw_placement(g, product_placement,
((float(i + 1) / len(placements)), 0, 0, 0))
if plot_spaces:
for empty_space in container_bin.empty_space_list:
if empty_space:
draw_space(g, empty_space, empty_color)
plt.show()
if __name__ == '__main__':
spec = Cuboid(Point.from_scalars(30, 30, 30))
container_ = Container(spec)
g = plot_container(container_)
g.view_init(elev=30., azim=60)
b = Point(np.array([5, 5, 5]))
d = Point(np.array([3, 2, 3]))
s = Space(d, b)
draw_space(g, s, product_color)
plt.show()
def __init__(self, specification: Cuboid):
self.specification = specification
self.used_volume: int = 0
self.empty_space_list = [Space.from_placement(Point.new_origin(), specification)]
def __init__(self, container_spec: Cuboid):
self.container_spec = container_spec
self.container_upper_right = Point(
self.container_spec.dimensions.coords)