Module « scipy.stats »

Fonction scoreatpercentile - module scipy.stats

Signature de la fonction scoreatpercentile

def scoreatpercentile(a, per, limit=(), interpolation_method='fraction', axis=None) 

Description

scoreatpercentile.__doc__

Calculate the score at a given percentile of the input sequence.

    For example, the score at `per=50` is the median. If the desired quantile
    lies between two data points, we interpolate between them, according to
    the value of `interpolation`. If the parameter `limit` is provided, it
    should be a tuple (lower, upper) of two values.

    Parameters
    ----------
    a : array_like
        A 1-D array of values from which to extract score.
    per : array_like
        Percentile(s) at which to extract score.  Values should be in range
        [0,100].
    limit : tuple, optional
        Tuple of two scalars, the lower and upper limits within which to
        compute the percentile. Values of `a` outside
        this (closed) interval will be ignored.
    interpolation_method : {'fraction', 'lower', 'higher'}, optional
        Specifies the interpolation method to use,
        when the desired quantile lies between two data points `i` and `j`
        The following options are available (default is 'fraction'):

          * 'fraction': ``i + (j - i) * fraction`` where ``fraction`` is the
            fractional part of the index surrounded by ``i`` and ``j``
          * 'lower': ``i``
          * 'higher': ``j``

    axis : int, optional
        Axis along which the percentiles are computed. Default is None. If
        None, compute over the whole array `a`.

    Returns
    -------
    score : float or ndarray
        Score at percentile(s).

    See Also
    --------
    percentileofscore, numpy.percentile

    Notes
    -----
    This function will become obsolete in the future.
    For NumPy 1.9 and higher, `numpy.percentile` provides all the functionality
    that `scoreatpercentile` provides.  And it's significantly faster.
    Therefore it's recommended to use `numpy.percentile` for users that have
    numpy >= 1.9.

    Examples
    --------
    >>> from scipy import stats
    >>> a = np.arange(100)
    >>> stats.scoreatpercentile(a, 50)
    49.5