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density

Gaussian kernel density estimation over packed batches.

Functions:

gaussian_kernel_density [source] 

gaussian_kernel_density(
    x: Tensor, batch: Tensor, bandwidth: float
) -> Tensor

Computes the Gaussian Kernel Density (KDE) for a given tensor.

Parameters:

  • x (Tensor) –

    The input tensor of shape \((N, C)\).

  • batch (Tensor) –

    The batch tensor of shape \((N,)\).

  • bandwidth (float) –

    The bandwidth of the Gaussian kernel.

Returns:

  • Tensor –

    The Gaussian Kernel Density of shape \((N,)\).

Example 
import torch
from torch_pointcloud.ops.density import gaussian_kernel_density

pos = torch.randn(100, 3)
batch = torch.zeros(100, dtype=torch.long)
bandwidth = 0.1

density = gaussian_kernel_density(pos, batch, bandwidth)
print(density.shape)
# torch.Size([100])