Distances and divergences between discrete distributions described as dictionaries implemented in Python.
These are meant as fast solutions to compute distances and divergences between discrete distributions, especially when the two distributions contain a significant amount of events with nil probability which are not described in the dictionaries.
Find the complete list just below.
As usual, just download it using pip:
pip install dictancesA 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 |
Suppose you have a point described by my_first_dictionary and another one described by my_second_dictionary:
from dictances import cosine
my_first_dictionary = {
"a": 56,
"b": 34,
"c": 89
}
my_second_dictionary = {
"a": 21,
"d": 51,
"e": 74
}
cosine(my_first_dictionary, my_second_dictionary)
#>>> 0.8847005261889619Suppose you have a point described by my_first_dictionary and another one described by my_second_dictionary:
from dictances import bhattacharyya, bhattacharyya_coefficient
a = {
"event_1": 0.4,
"event_2": 0.1,
"event_3": 0.2,
"event_4": 0.3,
}
b = {
"event_1": 0.1,
"event_2": 0.2,
"event_5": 0.2,
"event_9": 0.5,
}
bhattacharyya_coefficient(a, b)
#>>> 0.3414213562373095
bhattacharyya(a, b)
#>>> 1.07463791569453If 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))This software is distributed under the MIT License. See the LICENSE file for more information.
If you want to contribute to the project and make it better, your help is very welcome. If you find a bug, please raise an issue with all the minimal code necessary to reproduce it. If you have a feature request, please open an adequately detailed issue to discuss it before starting to work on it in a pull request.