Point Sampling

sample_AABB(box, n_pts, mode='uniform', return_point_cloud=False)

Sample a point cloud uniformly at random inside an axis-aligned bounding box. Works by sampling the unit cube and applying an affine transformation.

Parameters:

Name	Type	Description	Default
box	AABB	the domain of sampling	required
n_pts	int	number of points to sample. If mode is 'grid', the function may return a slightly smaller number of points (nearest perfect n-th root).	required
mode	str	sampling mode. 'uniform' or 'grid'. Uniform takes points at random, while 'grid' generates a grid of regularly spaced points.	'uniform'
return_point_cloud	bool	whether to compile the points in a PointCloud object or return the raw numpy array. Is ignored if the bounding box has dimension >3. Defaults to False.	False

Raises:

Type	Description
Exception	fails if the bounding box is empty.
ValueError	fails if the dimension of the box is > 3 and return_point_cloud is set to True, so that no PointCloud object with dim > 3 is created.

Returns:

Type	Description
	PointCloud | np.ndarray: a sampled point cloud of n_pts points

sample_ball(center, radius, n_pts, return_point_cloud=False)

Samples points uniformly inside a 3D ball.

Parameters:

Name	Type	Description	Default
center	Vec	center of the ball	required
radius	float	radius of the ball	required
n_pts	int	number of points to sample	required
return_point_cloud	bool	whether to compile the points in a PointCloud object or return the raw numpy array. Defaults to False.	False

Returns:

Type	Description
	PointCloud | np.ndarray: a sampled point cloud of n_pts points

sample_polyline(mesh, n_pts, return_point_cloud=False)

Sample a point cloud uniformly at random from a polyline

Parameters:

Name	Type	Description	Default
mesh	PolyLine	the input polyline	required
n_pts	int	number of points to sample	required
return_point_cloud	bool	whether to compile the points in a PointCloud object or return the raw numpy array. Defaults to False.	False

Returns:

Type	Description
	PointCloud | np.ndarray: a sampled point cloud of n_pts points

sample_sphere(center, radius, n_pts, return_point_cloud=False)

Samples points uniformly on the surface of a 3D sphere

Parameters:

Name	Type	Description	Default
center	Vec	center of the sphere	required
radius	float	radius of the spheres	required
n_pts	int	number of points to sample	required
return_point_cloud	bool	whether to compile the points in a PointCloud object or return the raw numpy array. Defaults to False.	False

Returns:

Type	Description
	PointCloud | np.ndarray: a sampled point cloud of n_pts points

sample_surface(mesh, n_pts, return_point_cloud=False, return_normals=False)

Sample a point cloud uniformly at random from a surface mesh

Parameters:

Name	Type	Description	Default
mesh	SurfaceMesh	input mesh	required
n_pts	int	number of points to sample	required
return_point_cloud	bool	whether to compile the points in a PointCloud object or return the raw numpy array. Defaults to False.	False
return_normals	bool	wether to assign the normal of the faces to sampled points. Only has effect if return_point_cloud is set to True. Defaults to False.	False

Returns:

Type	Description
	PointCloud | np.ndarray: a sampled point cloud of n_pts points
	np.ndarray : the associated normals (if sample_normals was set to True)