mad_std¶
-
astropy.stats.
mad_std
(data, axis=None)[source] [edit on github]¶ Calculate a robust standard deviation using the median absolute deviation (MAD).
The standard deviation estimator is given by:
\sigma \approx \frac{\textrm{MAD}}{\Phi^{-1}(3/4)} \approx 1.4826 \ \textrm{MAD}
where \Phi^{-1}(P) is the normal inverse cumulative distribution function evaluated at probability P = 3/4.
Parameters: data : array-like
Data array or object that can be converted to an array.
axis : int, optional
Axis along which the robust standard deviations are computed. The default (
None
) is to compute the robust standard deviation of the flattened array.Returns: mad_std : float or
ndarray
The robust standard deviation of the input data. If
axis
isNone
then a scalar will be returned, otherwise andarray
will be returned.Examples
>>> import numpy as np >>> from astropy.stats import mad_std >>> rand = np.random.RandomState(12345) >>> madstd = mad_std(rand.normal(5, 2, (100, 100))) >>> print(madstd) 2.0232764659422626