Similarity Network Fusion (SNF) integrates multiple views (similarity matrices) to construct an overall status matrix. This function is adopted from the SNFtool (https://github.com/maxconway/SNFtool/) and has been enhanced for unsupervised analysis of spatial ecosystem. The new function supports sparse matrix and missing data in the input matrices.
Arguments
- Wall
List of similarity matrices. Each element of the list is a square, symmetric matrix that shows affinities of the data points from a certain view.
- K
Number of neighbors in K-nearest neighbors part of the algorithm.
- t
Number of iterations for the diffusion process.
- minibatch
Integer specifying the number of columns to process in each minibatch. Default is 5000. This option splits the matrix into smaller chunks (minibatch), thus reducing memory usage.
- ncores
Integer specifying the number of CPU cores to use for parallel processing.
- verbose
Boolean specifying whether to show the progress messages.