dynutils (version 1.0.4)

calculate_distance: 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

# NOT RUN {
## 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")
# }

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