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

zmap.__doc__

    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])