Function running_median

more_itertools/recipes.py:1384–1418

Cumulative median of values seen so far or values in a sliding window. Set *maxlen* to a positive integer to specify the maximum size of the sliding window. The default of *None* is equivalent to an unbounded window. For example: >>> list(running_median([5.0, 9.0, 4.0, 12

(iterable, *, maxlen=None)

def running_median(iterable, *, maxlen=None):
    """Cumulative median of values seen so far or values in a sliding window.

    Set *maxlen* to a positive integer to specify the maximum size
    of the sliding window.  The default of *None* is equivalent to
    an unbounded window.

    For example:

        >>> list(running_median([5.0, 9.0, 4.0, 12.0, 8.0, 9.0]))
        [5.0, 7.0, 5.0, 7.0, 8.0, 8.5]
        >>> list(running_median([5.0, 9.0, 4.0, 12.0, 8.0, 9.0], maxlen=3))
        [5.0, 7.0, 5.0, 9.0, 8.0, 9.0]

    Supports numeric types such as int, float, Decimal, and Fraction,
    but not complex numbers which are unorderable.

    On version Python 3.13 and prior, max-heaps are simulated with
    negative values. The negation causes Decimal inputs to apply context
    rounding, making the results slightly different than that obtained
    by statistics.median().
    """

    iterator = iter(iterable)

    if maxlen is not None:
        maxlen = _index(maxlen)
        if maxlen <= 0:
            raise ValueError('Window size should be positive')
        return _running_median_windowed(iterator, maxlen)

    if not _max_heap_available:
        return _running_median_minheap_only(iterator)  # pragma: no cover

    return _running_median_minheap_and_maxheap(iterator)  # pragma: no cover


def _windowed_running_mean(iterator, n):