This function computes a bilateral smoothing of the input data, which combines spatial and feature information to provide a smoothed representation of the data.
Usage
bilateral_smoother(
coord_mat,
feature_mat,
nnk = 27,
s_sigma = 2.5,
f_sigma = 0.7,
stochastic = FALSE
)Arguments
- coord_mat
A matrix with the spatial coordinates of the data points, where each row represents a point and each column represents a coordinate dimension.
- feature_mat
A matrix with the feature vectors of the data points, where each row represents a point and each column represents a feature dimension.
- nnk
The number of nearest neighbors to consider for smoothing (default: 27). Must be >= 4.
- s_sigma
The spatial bandwidth in standard deviations (default: 2.5).
- f_sigma
The normalized feature bandwidth in standard deviations (default: 0.7).
- stochastic
A logical value indicating whether to make the resulting adjacency matrix doubly stochastic (default: FALSE).
Examples
set.seed(123)
coord_mat <- as.matrix(expand.grid(1:10, 1:10))
feature_mat <- matrix(rnorm(100*10), 100, 10)
S <- bilateral_smoother(coord_mat, feature_mat, nnk=8)