points, normals = load_svg(svg_path, point_count)
initial_resolution = 32
iterations = [500, 250, 100, 20, 20]
if show_point_cloud:
plot_points_norms(points, normals)
reconstruct_2d(points, normals, initial_resolution, iterations, save_gif)
@cli.command()
@click.argument("point_cloud_path", type=click.Path(exists=True), required=True)
@click.option('--output', 'output_name', type=click.Path(), default='volume.npz')
@click.option('--save-gif', default=None, type=click.Path())
def surface_reconstruction_3d(point_cloud_path, output_name, save_gif):
"""
Perform Poisson Surface Reconstruction of the provided 3D oriented point cloud
"""
from common.io import load_point_cloud
from geometry.poisson_reconstruction import reconstruct_3d
points, normals = load_point_cloud(point_cloud_path)
iterations = [500, 250, 100, 20, 20]
reconstruct_3d(points, normals, output_name, 32, iterations, save_gif)
if __name__ == '__main__':
icecream.install()
icecream.ic.configureOutput(includeContext=True)
cli()
from pathlib import Path
from icecream import install
install()
class AdventOfCode:
part_one_test_solution = None
part_two_test_solution = None
@property
def test_input(self):
return self.load_file('input.test.txt')
@property
def input(self):
return self.load_file('input.txt')
def load_file(self, file_path):
with Path(file_path).open() as f:
lines = list(map(lambda l: l.strip(), f.readlines()))
input_ = self.preprocess_input(lines)
if type(input_) is not tuple:
return input_,
return input_
def preprocess_input(self, lines):
if all(line.isnumeric() for line in lines):
lines = list(map(int, lines))
if len(lines) == 0:
return lines[0]
def testInstall(self):
icecream.install()
with disableColoring(), captureStandardStreams() as (out, err):
runMe()
assert parseOutputIntoPairs(out, err, 1)[0][0] == ('x', '3')
icecream.uninstall() # Clean up builtins.
