colour.algebra.euclidean_distance#

colour.algebra.euclidean_distance(a: ArrayLike, b: ArrayLike) → NDArrayFloat[source]#

Return the Euclidean distance between point array \(a\) and point array \(b\).

For a two-dimensional space, the metric is as follows:

\(E_D = [(x_a - x_b)^2 + (y_a - y_b)^2]^{1/2}\)

Parameters:

a (ArrayLike) – Point array \(a\).
b (ArrayLike) – Point array \(b\).

Returns:

Euclidean distance.

Return type:

np.float or numpy.ndarray

Examples

>>> a = np.array([100.00000000, 21.57210357, 272.22819350])
>>> b = np.array([100.00000000, 426.67945353, 72.39590835])
>>> euclidean_distance(a, b)  
451.7133019...