Add a `projectReducedDims` function about scater HOT 5 CLOSED

Seems like a bad idea but also something people would certainly use. I like the weighted average idea, something like

projectReducedDim <- function(old.points, new.points, old.embedding, k = 2) {
    res <- queryKNN(X = old.points, query = new.points, k = k)
    weight <- 1 / res$distance
    weight <- weight / rowSums(weight)
    new.embedding <- sapply(1:ncol(old.embedding), function(i) {
        rowMeans(
            sapply(1:ncol(res$index), function(j) {
                old.embedding[res$index[, j], i] * weight[, j]
            })
        )
    })
    new.embedding
}

I realise there's surely a more elegant way to do the nested loops.

I could also wrap the snifter stuff into scater without a terrible amount of effort.

from scater.

Check out https://github.com/LTLA/batchelor/blob/master/R/utils_tricube.R for a tricube-weighted average based on the nearest neighbors. Watch out for problems with distances of zero if you're going to use inverse weights.

from scater.

Ooh, perfect. Might just ::: that unless that's deeply frowned on

from scater.

Probably best to just copy it over, avoid an explicit dependency on batchelor. It's not too large and it should be easy to drag across the few unit tests just in case.

from scater.

Resolved by commit(s) above but feel free to submit feedback/gripes here

from scater.