# calculate_distance: Calculate (column-wise) distances/similarity between two... In dynutils: Common Functionality for the 'dynverse' Packages

## Description

These matrices can be dense or sparse.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```calculate_distance( x, y = NULL, method = c("pearson", "spearman", "cosine", "euclidean", "chisquared", "hamming", "kullback", "manhattan", "maximum", "canberra", "minkowski"), 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

 ``` 1 2 3 4 5 6 7 8 9 10``` ```## 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") ```

dynutils documentation built on March 22, 2021, 5:06 p.m.