`matrix`

and `MSnSet`

instances.
`signature(object = "matrix", k = "numeric", dist = "character", ...)`

- Calculates indices and distances to the
`k`

(default is 3) nearest neighbours of each feature (row) in the input matrix`object`

. The distance`dist`

can be either of`"euclidean"`

or`"mahalanobis"`

. Additional parameters can be passed to the internal function`FNN::get.knn`

. Output is a matrix with`2 * k`

columns and`nrow(object)`

rows. `signature(object = "MSnSet", k = "numeric", dist = "character", ...)`

- As above, but for an
`MSnSet`

input. The indices and distances to the`k`

nearest neighbours are added to the object's feature metadata. `signature(object = "matrix", query = "matrix", k = "numeric", ...)`

- If two
`matrix`

instances are provided as input, the`k`

(default is 3) indices and distances of the nearest neighbours of`query`

in`object`

are returned as a matrix of dimensions`2 * k`

by`nrow(query)`

. Additional parameters are passed to`FNN::get.knnx`

. Only euclidean distance is available.

library("pRolocdata") data(dunkley2006) ## Using a matrix as input m <- exprs(dunkley2006) m[1:4, 1:3] head(nndist(m, k = 5)) tail(nndist(m[1:100, ], k = 2, dist = "mahalanobis")) ## Same as above for MSnSet d <- nndist(dunkley2006, k = 5) head(fData(d)) d <- nndist(dunkley2006[1:100, ], k = 2, dist = "mahalanobis") tail(fData(d)) ## Using a query nndist(m[1:100, ], m[101:110, ], k = 2)