dictances 1.5.2

Distances and divergences between distributions implemented in python.

Distances and divergences between distributions implemented in python.

How do I install this package?

As usual, just download it using pip:

pip install dictances

Tests Coverage

Since some software handling coverages sometime get slightly different results, here’s three of them:

Available metrics

A number of distances and divergences are available:

Distances	Methods
Bhattacharyya distance	bhattacharyya
Bhattacharyya coefficient	bhattacharyya_coefficient
Canberra distance	canberra
Chebyshev distance	chebyshev
Chi Square distance	chi_square
Cosine Distance	cosine
Euclidean distance	euclidean
Hamming distance	hamming
Jensen-Shannon divergence	jensen_shannon
Kullback-Leibler divergence	kullback_leibler
Mean absolute error	mae
Taxicab geometry	manhattan, cityblock, total_variation
Minkowski distance	minkowsky
Mean squared error	mse
Pearson’s distance	pearson
Squared deviations from the mean	squared_variation

Usage example

from dictances import cosine

cosine(my_first_dictionary, my_second_dictionary)

Handling nested dictionaries

If you need to compute the distance between two nested dictionaries you can use deflate_dict as follows:

from dictances import cosine
from deflate_dict import deflate

my_first_dictionary = {
    "a": 8,
    "b": {
        "c": 3,
        "d": 6
    }
}

my_second_dictionary = {
    "b": {
        "c": 8,
        "d": 1
    },
    "y": 3,

}

cosine(deflate(my_first_dictionary), deflate(my_second_dictionary))