R: Calculate (column-wise) distances/similarity between two...

calculate_distance {dynutils} | R Documentation

## Calculate (column-wise) distances/similarity between two matrices

### Description

These matrices can be dense or sparse.

### Usage

    calculate_distance(x, y = NULL, method = c("pearson", "spearman",
      "cosine", "euclidean", "manhattan"), margin = 1)

    list_distance_methods()

    calculate_similarity(x, y = NULL, margin = 1, method = c("spearman",
      "pearson", "cosine"))

    list_similarity_methods()

### Arguments

`x` | A numeric matrix, dense or sparse.
`y` | (Optional) a numeric matrix, dense or sparse, with `nrow(x) == nrow(y)`.
`method` | Which distance method to use. Options are: `"cosine"`, `"pearson"`, `"spearman"`, `"euclidean"`, and `"manhattan"`.
`margin` | Which margin to use for the pairwise comparison. 1 => rowwise, 2 => columnwise.

### Examples

    ## Generate two matrices with 50 and 100 samples
    library(Matrix)
    x <- Matrix::rsparsematrix(50, 1000, .01)
    y <- Matrix::rsparsematrix(100, 1000, .01)

    dist_euclidean <- calculate_distance(x, y, method = "euclidean")
    dist_manhattan <- calculate_distance(x, y, method = "manhattan")
    dist_spearman <- calculate_distance(x, y, method = "spearman")
    dist_pearson <- calculate_distance(x, y, method = "pearson")
    dist_angular <- calculate_distance(x, y, method = "cosine")

[Package dynutils version 1.0.4 Index]