Distances

All the functions here are functions to find the distance between two pieces of data based on contingency table.

	Row 2
Row 1		1	0
	1	a	b
	0	c	d

Each function has the same parameters and return values:

Parameters

aint

Count of same 1 numbers.

bint

The sum of 1 in row 1 and 0 in row 2.

cint

Sum 1 in row 2 and 0 in row 1.

dint

Count of same 0 numbers.

nint

Sum of all the numbers.

Returns

float

The similarity value between two pieces of data.

besimilarity.distance.bray_curtis(a, b, c, d, n)

Bray-Curtis distance from contingency table.

besimilarity.distance.canberra(a, b, c, d, n)

Canberra distance from contingency table.

besimilarity.distance.chord(a, b, c, d, n)

Chord distance from contingency table.

besimilarity.distance.cityblock(a, b, c, d, n)

Cityblock distance from contingency table.

besimilarity.distance.euclidean(a, b, c, d, n)

Euclidean distance from contingency table.

besimilarity.distance.get_all_functions_name()

Get all the functions in the module.

Returns

List of functions object.

Return type

list

besimilarity.distance.get_function(name)

Get function by name.

Parameters

name (str) – Name of the function.

Returns

Function object.

Return type

function

besimilarity.distance.hamming(a, b, c, d, n)

Hamming coefficient from contingency table.

besimilarity.distance.hellinger(a, b, c, d, n)

Hellinger distance from contingency table.

besimilarity.distance.lance_williams(a, b, c, d, n)

Lance Williams distance from contingency table.

besimilarity.distance.manhattan(a, b, c, d, n)

Manhattan distance from contingency table.

besimilarity.distance.mean_manhattan(a, b, c, d, n)

Mean Manhattan distance from contingency table.

besimilarity.distance.minkowski(a, b, c, d, n)

Minkowski distance from contingency table

besimilarity.distance.pattern_difference(a, b, c, d, n)

Pattern difference from contingency table.

besimilarity.distance.shape_difference(a, b, c, d, n)

Shape difference from contingency table.

besimilarity.distance.size_difference(a, b, c, d, n)

Size difference from contingency table.

besimilarity.distance.squared_euclidean(a, b, c, d, n)

Squared Euclidean distance from contingency table.

besimilarity.distance.vari(a, b, c, d, n)

Vari distance from contingency table.

besimilarity.distance.yuleq(a, b, c, d, n)

Yule-Q distance from contingency table.