Getting Started with haze

Introduction

haze provides fast smoothing of per-vertex data on triangular meshes, along with utility functions for mesh manipulation and data interpolation. The smoothing is implemented in C++ and supports parallel processing for multiple overlays.

Smoothing Per-Vertex Data

The main workhorse is pervertexdata.smoothnn(), which performs nearest-neighbor smoothing using the \(k\)-ring neighborhood of each vertex.

library("haze")

# Load a FreeSurfer mesh and per-vertex data
mesh <- freesurferformats::read.fs.surface(
  system.file("extdata", "fsaverage_mesh_lh_white", package = "haze", mustWork = TRUE))
thickness <- freesurferformats::read.fs.morph(
  system.file("extdata", "fsaverage_lh_thickness", package = "haze", mustWork = TRUE))

# Smooth: k=2 neighborhood, 300 iterations
smoothed <- pervertexdata.smoothnn(mesh, thickness, num_iter = 300L, k = 2L)

Re-Using the Mesh Neighborhood

When smoothing many datasets on the same mesh, pre-compute the adjacency list once with mesh.adj() and then use pervertexdata.smoothnn.adj():

mesh_adj <- mesh.adj(mesh, k = 1L)

This adjacency can be reused:

data1 <- rnorm(length(mesh_adj), mean = 1.0, sd = 0.1)
data2 <- rnorm(length(mesh_adj), mean = 5.0, sd = 0.1)

smoothed1 <- pervertexdata.smoothnn.adj(mesh_adj, data1, num_iter = 15L)
smoothed2 <- pervertexdata.smoothnn.adj(mesh_adj, data2, num_iter = 15L)

Multiple overlays (as a matrix, one per row) are automatically smoothed in parallel:

pvd <- rbind(data1, data2)
options("mc.cores" = 2L)
smoothed_pvd <- pervertexdata.smoothnn.adj(mesh_adj, pvd, num_iter = 15L)
#> Handling 2 vertex overlays with 163842 values each in parallel on 2 CPU cores. (Use 'options("mc.cores"=N)' to request N cores).

Creating Sub-Meshes

Use submesh.vertex() to extract a patch of a mesh defined by vertex indices:

# Extract a sub-mesh of the first 1000 vertices
small_mesh <- submesh.vertex(mesh, old_vertex_indices_to_use = 1:1000)

Working with k-d Trees

find_nv_kdtree() finds the nearest mesh vertex for given query coordinates:

query_points <- matrix(c(0, 0, 0, 10, 10, 10), ncol = 3, byrow = TRUE)
nearest_vertex_idx <- find_nv_kdtree(query_points, mesh)

nn_interpolate_kdtree() assigns per-vertex data to query points via nearest-neighbor lookup, while linear_interpolate_kdtree() performs linear interpolation — useful for mapping morphometry data between subjects with aligned spherical meshes.

Mesh Conversion Utilities

Convert between FreeSurfer surfaces and rgl tmesh3d objects using the internal utilities haze:::fs.surface.to.tmesh3d() and haze:::tmesh3d.to.fs.surface():

tmesh <- haze:::fs.surface.to.tmesh3d(mesh)
fs_surface <- haze:::tmesh3d.to.fs.surface(tmesh)