Function digitize

numpy/lib/_function_base_impl.py:5667–5775

Return the indices of the bins to which each value in input array belongs. ========= ============= ============================ `right` order of bins returned index `i` satisfies ========= ============= ============================ ``False`` increasing ``bins[i-1]

(x, bins, right=False)

@array_function_dispatch(_digitize_dispatcher)
def digitize(x, bins, right=False):
    """
    Return the indices of the bins to which each value in input array belongs.

    =========  =============  ============================
    `right`    order of bins  returned index `i` satisfies
    =========  =============  ============================
    ``False``  increasing     ``bins[i-1] <= x < bins[i]``
    ``True``   increasing     ``bins[i-1] < x <= bins[i]``
    ``False``  decreasing     ``bins[i-1] > x >= bins[i]``
    ``True``   decreasing     ``bins[i-1] >= x > bins[i]``
    =========  =============  ============================

    If values in `x` are beyond the bounds of `bins`, 0 or ``len(bins)`` is
    returned as appropriate.

    Parameters
    ----------
    x : array_like
        Input array to be binned. Prior to NumPy 1.10.0, this array had to
        be 1-dimensional, but can now have any shape.
    bins : array_like
        Array of bins. It has to be 1-dimensional and monotonic.
    right : bool, optional
        Indicating whether the intervals include the right or the left bin
        edge. Default behavior is (right==False) indicating that the interval
        does not include the right edge. The left bin end is open in this
        case, i.e., bins[i-1] <= x < bins[i] is the default behavior for
        monotonically increasing bins.

    Returns
    -------
    indices : ndarray of ints
        Output array of indices, of same shape as `x`.

    Raises
    ------
    ValueError
        If `bins` is not monotonic.
    TypeError
        If the type of the input is complex.

    See Also
    --------
    bincount, histogram, unique, searchsorted

    Notes
    -----
    If values in `x` are such that they fall outside the bin range,
    attempting to index `bins` with the indices that `digitize` returns
    will result in an IndexError.

    .. versionadded:: 1.10.0

    `numpy.digitize` is  implemented in terms of `numpy.searchsorted`.
    This means that a binary search is used to bin the values, which scales
    much better for larger number of bins than the previous linear search.
    It also removes the requirement for the input array to be 1-dimensional.