def decode_geometry_msg(request_geometries):
product_boxes = []
for sp in request_geometries:
product_boxes.append(
Cuboid(Point(sp.dimensions))
)
return product_boxes
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
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, container_spec: Cuboid):
self.container_spec = container_spec
self.container_upper_right = Point(
self.container_spec.dimensions.coords)