Function histogram

dask/array/routines.py:863–1069

Blocked variant of :func:`numpy.histogram`. Parameters ---------- a : dask.array.Array Input data; the histogram is computed over the flattened array. If the ``weights`` argument is used, the chunks of ``a`` are accessed to check chunking compatibility betwe

(a, bins=None, range=None, normed=False, weights=None, density=None)

def histogram(a, bins=None, range=None, normed=False, weights=None, density=None):
    """
    Blocked variant of :func:`numpy.histogram`.

    Parameters
    ----------
    a : dask.array.Array
        Input data; the histogram is computed over the flattened
        array. If the ``weights`` argument is used, the chunks of
        ``a`` are accessed to check chunking compatibility between
        ``a`` and ``weights``. If ``weights`` is ``None``, a
        :py:class:`dask.dataframe.Series` object can be passed as
        input data.
    bins : int or sequence of scalars, optional
        Either an iterable specifying the ``bins`` or the number of ``bins``
        and a ``range`` argument is required as computing ``min`` and ``max``
        over blocked arrays is an expensive operation that must be performed
        explicitly.
        If `bins` is an int, it defines the number of equal-width
        bins in the given range (10, by default). If `bins` is a
        sequence, it defines a monotonically increasing array of bin edges,
        including the rightmost edge, allowing for non-uniform bin widths.
    range : (float, float), optional
        The lower and upper range of the bins.  If not provided, range
        is simply ``(a.min(), a.max())``.  Values outside the range are
        ignored. The first element of the range must be less than or
        equal to the second. `range` affects the automatic bin
        computation as well. While bin width is computed to be optimal
        based on the actual data within `range`, the bin count will fill
        the entire range including portions containing no data.
    normed : bool, optional
        This is equivalent to the ``density`` argument, but produces incorrect
        results for unequal bin widths. It should not be used.
    weights : dask.array.Array, optional
        A dask.array.Array of weights, of the same block structure as ``a``.  Each value in
        ``a`` only contributes its associated weight towards the bin count
        (instead of 1). If ``density`` is True, the weights are
        normalized, so that the integral of the density over the range
        remains 1.
    density : bool, optional
        If ``False``, the result will contain the number of samples in
        each bin. If ``True``, the result is the value of the
        probability *density* function at the bin, normalized such that
        the *integral* over the range is 1. Note that the sum of the
        histogram values will not be equal to 1 unless bins of unity
        width are chosen; it is not a probability *mass* function.
        Overrides the ``normed`` keyword if given.
        If ``density`` is True, ``bins`` cannot be a single-number delayed
        value. It must be a concrete number, or a (possibly-delayed)
        array/sequence of the bin edges.

    Returns
    -------
    hist : dask Array
        The values of the histogram. See `density` and `weights` for a
        description of the possible semantics.
    bin_edges : dask Array of dtype float
        Return the bin edges ``(length(hist)+1)``.