WeightedNNBasedLinesetMatching: Compute point & tangent vector similarity score between two linesets

Description

WeightedNNBasedLinesetMatching is a low level function that is called by nblast. Most end users will not usually need to call it directly. It does allow the results of an NBLAST comparison to be inspected in further detail (see examples).

Usage

WeightedNNBasedLinesetMatching(target, query, ...)
# S3 method for dotprops
WeightedNNBasedLinesetMatching(target, query, UseAlpha = FALSE, ...)
# S3 method for neuron
WeightedNNBasedLinesetMatching(
  target,
  query,
  UseAlpha = FALSE,
  OnlyClosestPoints = FALSE,
  ...
)

Value

Value of NNDistFun passed to

WeightedNNBasedLinesetMatching

Arguments

target, query: dotprops or neuron objects to compare (must be of the same class)
...: extra arguments to pass to the distance function.
UseAlpha: Whether to scale dot product of tangent vectors (default=F)
OnlyClosestPoints: Whether to restrict searches to the closest points in the target (default FALSE, only implemented for dotprops).

Details

WeightedNNBasedLinesetMatching will work with 2 objects of class dotprops or neuron. The code to calculate scores directly for neuron objects gives broadly comparable scores to that for dotprops objects, but has been lightly tested. Furthermore only objects in dotprops form were used in the construction of the scoring matrices distributed in this package. It is therefore recommended to convert neuron objects to dotprops objects using the dotprops function.

UseAlpha determines whether the alpha values (eig1-eig2)/sum(eig1:3) are passed on to WeightedNNBasedLinesetMatching. These will be used to scale the dot products of the direction vectors for nearest neighbour pairs.

Examples

Run this code

# Retrieve per segment distances / absolute dot products
segvals=WeightedNNBasedLinesetMatching(kcs20[[1]], kcs20[[2]], NNDistFun=list)
names(segvals)=c("dist", "adotprod")
pairs(segvals)