# colour.utilities.metric_mse¶

colour.utilities.metric_mse(a, b, axis=None)[source]

Computes the mean squared error (MSE) or mean squared deviation (MSD) between given array_like $$a$$ and $$b$$ variables.

Parameters
• a (array_like) – $$a$$ variable.

• b (array_like) – $$b$$ variable.

• axis (None or int or tuple of ints, optional) – Axis or axes along which the means are computed. The default is to compute the mean of the flattened array. If this is a tuple of ints, a mean is performed over multiple axes, instead of a single axis or all the axes as before.

Returns

Mean squared error (MSE).

Return type

float

References

[Wikipedia03d]

Examples

>>> a = np.array([0.48222001, 0.31654775, 0.22070353])
>>> b = a * 0.9
>>> metric_mse(a, b)
0.0012714...