Compute distance to archetypes

arch_dist() calculates Euclidean distance from every point to every archetype give matrices that contain this data.

arch_dist(data, archetypes, dist_metric = "euclidean")

Arguments

data	matrix of dim(variables/dimentions, examples)
archetypes	matrix of dim(variables/dimentions, archetypes)
dist_metric	distance metric, currently only "euclidean" implemented

Value

matrix of distances to archetypes of dim(examples, archetypes)

See also

fit_pch, generate_arc, generate_data

Examples

# Triangle with sides of 3,4,5 units length
arch_dist(matrix(c(0,0),1,2), matrix(c(3,4),1,2))
#>      archetype_1 archetype_2
#> [1,]           3           4
#> [2,]           3           4
# Random data that fits into the triangle
set.seed(4355)
archetypes = generate_arc(arc_coord = list(c(5, 0), c(-10, 15), c(-30, -20)),
                          mean = 0, sd = 1, N_dim = 2)
#> Error in generate_arc(arc_coord = list(c(5, 0), c(-10, 15), c(-30, -20)),     mean = 0, sd = 1, N_dim = 2): unused argument (N_dim = 2)
data = generate_data(archetypes, N_examples = 1e4, jiiter = 0.04, size = 0.9)
#> Error in ncol(archetypes): object 'archetypes' not found
# Find Euclidean distance between data points and archetypes
distance = arch_dist(data, archetypes)
#> Error in ncol(archetypes): object 'archetypes' not found
# Find Euclidean distance between archetypes
arc_distance = arch_dist(archetypes, archetypes)
#> Error in ncol(archetypes): object 'archetypes' not found