Function searchsorted

dask/array/routines.py:813–850

(a, v, side="left", sorter=None)

@derived_from(np)
def searchsorted(a, v, side="left", sorter=None):
    if a.ndim != 1:
        raise ValueError("Input array a must be one dimensional")

    if sorter is not None:
        raise NotImplementedError(
            "da.searchsorted with a sorter argument is not supported"
        )

    # call np.searchsorted for each pair of blocks in a and v
    meta = np.searchsorted(a._meta, v._meta)
    out = blockwise(
        _searchsorted_block,
        list(range(v.ndim + 1)),
        a,
        [0],
        v,
        list(range(1, v.ndim + 1)),
        side,
        None,
        meta=meta,
        adjust_chunks={0: 1},  # one row for each block in a
    )

    # add offsets to take account of the position of each block within the array a
    a_chunk_sizes = array_safe((0, *a.chunks[0]), like=meta_from_array(a))
    a_chunk_offsets = np.cumsum(a_chunk_sizes)[:-1]
    a_chunk_offsets = a_chunk_offsets[(Ellipsis,) + v.ndim * (np.newaxis,)]
    a_offsets = asarray(a_chunk_offsets, chunks=1)
    out = where(out < 0, out, out + a_offsets)

    # combine the results from each block (of a)
    out = out.max(axis=0)

    # fix up any -1 values
    out[out == -1] = 0

    return out


def _linspace(bins_range):