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Module « scipy.stats »

Fonction trim_mean - module scipy.stats

Signature de la fonction trim_mean

def trim_mean(a, proportiontocut, axis=0) 

Description

help(scipy.stats.trim_mean)

Return mean of array after trimming a specified fraction of extreme values

Removes the specified proportion of elements from *each* end of the
sorted array, then computes the mean of the remaining elements.

Parameters
----------
a : array_like
    Input array.
proportiontocut : float
    Fraction of the most positive and most negative elements to remove.
    When the specified proportion does not result in an integer number of
    elements, the number of elements to trim is rounded down.
axis : int or None, default: 0
    Axis along which the trimmed means are computed.
    If None, compute over the raveled array.

Returns
-------
trim_mean : ndarray
    Mean of trimmed array.

See Also
--------
trimboth : Remove a proportion of elements from each end of an array.
tmean : Compute the mean after trimming values outside specified limits.

Notes
-----
For 1-D array `a`, `trim_mean` is approximately equivalent to the following
calculation::

    import numpy as np
    a = np.sort(a)
    m = int(proportiontocut * len(a))
    np.mean(a[m: len(a) - m])

Examples
--------
>>> import numpy as np
>>> from scipy import stats
>>> x = [1, 2, 3, 5]
>>> stats.trim_mean(x, 0.25)
2.5

When the specified proportion does not result in an integer number of
elements, the number of elements to trim is rounded down.

>>> stats.trim_mean(x, 0.24999) == np.mean(x)
True

Use `axis` to specify the axis along which the calculation is performed.

>>> x2 = [[1, 2, 3, 5],
...       [10, 20, 30, 50]]
>>> stats.trim_mean(x2, 0.25)
array([ 5.5, 11. , 16.5, 27.5])
>>> stats.trim_mean(x2, 0.25, axis=1)
array([ 2.5, 25. ])

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