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Module « scipy.stats.mstats »

Fonction zmap - module scipy.stats.mstats

Signature de la fonction zmap

def zmap(scores, compare, axis=0, ddof=0, nan_policy='propagate') 

Description

help(scipy.stats.mstats.zmap)

Calculate the relative z-scores.

Return an array of z-scores, i.e., scores that are standardized to
zero mean and unit variance, where mean and variance are calculated
from the comparison array.

Parameters
----------
scores : array_like
    The input for which z-scores are calculated.
compare : array_like
    The input from which the mean and standard deviation of the
    normalization are taken; assumed to have the same dimension as
    `scores`.
axis : int or None, optional
    Axis over which mean and variance of `compare` are calculated.
    Default is 0. If None, compute over the whole array `scores`.
ddof : int, optional
    Degrees of freedom correction in the calculation of the
    standard deviation. Default is 0.
nan_policy : {'propagate', 'raise', 'omit'}, optional
    Defines how to handle the occurrence of nans in `compare`.
    'propagate' returns nan, 'raise' raises an exception, 'omit'
    performs the calculations ignoring nan values. Default is
    'propagate'. Note that when the value is 'omit', nans in `scores`
    also propagate to the output, but they do not affect the z-scores
    computed for the non-nan values.

Returns
-------
zscore : array_like
    Z-scores, in the same shape as `scores`.

Notes
-----
This function preserves ndarray subclasses, and works also with
matrices and masked arrays (it uses `asanyarray` instead of
`asarray` for parameters).

Examples
--------
>>> from scipy.stats import zmap
>>> a = [0.5, 2.0, 2.5, 3]
>>> b = [0, 1, 2, 3, 4]
>>> zmap(a, b)
array([-1.06066017,  0.        ,  0.35355339,  0.70710678])

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