Samplers

Samplers use PyntCloud information to generate a sample of points. These points might or might not have been present in the original point cloud.

For example, RandomPoints generates a sample by randomly selecting points from the original point cloud. In this case all sample’s points were present in the original point cloud.

On the other hand, VoxelgridCentroids generates a sample by computing the centroid of each group of points inside of each occupied VoxelGrid’s cell. In this case any of the sample’s points were present in the original point cloud.

All samplers take a point cloud as input and return a pandas DataFrame.

This pandas DataFrame can be used to generate a new PyntCloud.

All samplers are accessible trough:

PyntCloud.get_sample()

We group the available samplers based on what information is used for their computation.

Require points

“points_random_sampling”

Require mesh

pointcloud.mesh must exists.

“mesh_random_sampling”

Require VoxelGrid

Required args:

voxelgrid: VoxelGrid.id

voxelgrid = pointcloud.add_structure("voxelgrid", ...)

“voxelgrid_centers”

“voxelgrid_centroids”

“voxelgrid_nearest”