median_absolute_deviation

astropy.stats.median_absolute_deviation(a, axis=None)[source] [edit on github]

Calculate the median absolute deviation (MAD).

The MAD is defined as median(abs(a - median(a))).

Parameters:

a : array-like

Input array or object that can be converted to an array.

axis : int, optional

Axis along which the MADs are computed. The default (None) is to compute the MAD of the flattened array.

Returns:

mad : float or ndarray

The median absolute deviation of the input array. If axis is None then a scalar will be returned, otherwise a ndarray will be returned.

See also

mad_std

Examples

Generate random variates from a Gaussian distribution and return the median absolute deviation for that distribution:

>>> import numpy as np
>>> from astropy.stats import median_absolute_deviation
>>> rand = np.random.RandomState(12345)
>>> from numpy.random import randn
>>> mad = median_absolute_deviation(rand.randn(1000))
>>> print(mad)    
0.65244241428454486