Compute the pairwise euclidean distances between the rows of two matrices.

dist.xyz(a, b = NULL, all.pairs=TRUE, ncore=1, nseg.scale=1)

Arguments

a

a ‘xyz’ object, numeric data matrix, or vector.

b

an optional second ‘xyz’ object, data matrix, or vector.

all.pairs

logical, if TRUE all pairwise distances between the rows of ‘a’ and all rows of ‘b’ are computed, if FALSE only the distances between coresponding rows of ‘a’ and ‘b’ are computed.

ncore

number of CPU cores used to do the calculation. ncore>1 requires package ‘parallel’ installed.

nseg.scale

split input data into specified number of segments prior to running multiple core calculation. See fit.xyz.

Details

This function returns a matrix of euclidean distances between each row of ‘a’ and all rows of ‘b’. Input vectors are coerced to three dimensional matrices (representing the Cartesian coordinates x, y and z) prior to distance computation. If ‘b’ is not provided then the pairwise distances between all rows of ‘a’ are computed.

Value

Returns a matrix of pairwise euclidean distances between each row of ‘a’ and all rows of ‘b’.

References

Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.

Author

Barry Grant

Note

This function will choke if ‘b’ has too many rows.

See also

Examples

dist.xyz( c(1,1,1, 3,3,3), c(3,3,3, 2,2,2, 1,1,1))
#> [,1] [,2] [,3] #> [1,] 3.464102 1.732051 0.000000 #> [2,] 0.000000 1.732051 3.464102
dist.xyz( c(1,1,1, 3,3,3), c(3,3,3, 2,2,2, 1,1,1), all.pairs=FALSE)
#> [1] 3.464102 1.732051 NA