46 lines
1.8 KiB
Python
46 lines
1.8 KiB
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
|
|
|
|
def update_border(voxel_values, idx=None):
|
|
|
|
voxel_values = voxel_values > 0
|
|
|
|
if idx is None:
|
|
x_m1 = voxel_values[1:, :, :]
|
|
x_m1 = np.concatenate((x_m1, np.zeros((1, x_m1.shape[1], x_m1.shape[2]))), axis=0)
|
|
|
|
x_p1 = voxel_values[:-1, :, :]
|
|
x_p1 = np.concatenate((np.zeros((1, x_p1.shape[1], x_p1.shape[2])), x_p1), axis=0)
|
|
|
|
y_m1 = voxel_values[:, 1:, :]
|
|
y_m1 = np.concatenate((y_m1, np.zeros((y_m1.shape[0], 1, y_m1.shape[2]))), axis=1)
|
|
|
|
y_p1 = voxel_values[:, :-1, :]
|
|
y_p1 = np.concatenate((np.zeros((y_p1.shape[0], 1, y_p1.shape[2])), y_p1), axis=1)
|
|
|
|
z_m1 = voxel_values[:, :, 1:]
|
|
z_m1 = np.concatenate((z_m1, np.zeros((z_m1.shape[0], z_m1.shape[1], 1))), axis=2)
|
|
|
|
z_p1 = voxel_values[:, :, :-1]
|
|
z_p1 = np.concatenate((np.zeros((z_p1.shape[0], z_p1.shape[1], 1)), z_p1), axis=2)
|
|
|
|
return np.logical_or.reduce((voxel_values != x_m1, voxel_values != x_p1,
|
|
voxel_values != y_m1, voxel_values != y_p1,
|
|
voxel_values != z_m1, voxel_values != z_p1))
|
|
|
|
# TODO: update only concidered voxels (idx)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
voxel_values = np.array([[[np.sqrt(x**2 + y**2 + z**2) < 20 for z in np.arange(-10, 10, 1.0)] for y in np.arange(-10, 10, 1.0)] for x in np.arange(-10, 10, 1.0)])
|
|
|
|
border = update_border(voxel_values)
|
|
|
|
# Plot voxel grid that are the border
|
|
fig = plt.figure()
|
|
ax = fig.add_subplot(111, projection='3d')
|
|
ax.scatter(np.where(voxel_values)[0], np.where(voxel_values)[1], np.where(voxel_values)[2], c='r', marker='o')
|
|
ax.scatter(np.where(border)[0], np.where(border)[1], np.where(border)[2], c='b', marker='o', s=1)
|
|
plt.show()
|