排序

返回输入数组 `x` 的排序副本。

参数

名称	类型	描述	默认值
x	SparseArray	输入数组。应具有实数值数据类型。	必需
axis	int	排序的轴。如果设置为 `-1`，函数必须沿最后一个轴排序。默认值：`-1`。	-1
descending	bool_	排序顺序。如果为 `True`，数组必须按降序（按值）排序。如果为 `False`，数组必须按升序（按值）排序。默认值：`False`。	False
stable	bool_	排序是否稳定。目前仅支持 `False`。	False

返回值

名称	类型	描述
out	COO	已排序的数组。

引发

类型	描述
ValueError	如果输入数组不是 COO 格式或无法转换为 COO 格式。

示例

>>> import sparse
>>> x = sparse.COO.from_numpy([1, 0, 2, 0, 2, -3])
>>> sparse.sort(x).todense()
array([-3,  0,  0,  1,  2,  2])
>>> sparse.sort(x, descending=True).todense()
array([ 2,  2,  1,  0,  0, -3])

源代码位于 sparse/numba_backend/_coo/common.py

def sort(x, /, *, axis=-1, descending=False, stable=False):
    """
    Returns a sorted copy of an input array ``x``.

    Parameters
    ----------
    x : SparseArray
        Input array. Should have a real-valued data type.
    axis : int
        Axis along which to sort. If set to ``-1``, the function must sort along
        the last axis. Default: ``-1``.
    descending : bool
        Sort order. If ``True``, the array must be sorted in descending order (by value).
        If ``False``, the array must be sorted in ascending order (by value).
        Default: ``False``.
    stable : bool
        Whether the sort is stable. Only ``False`` is supported currently.

    Returns
    -------
    out : COO
        A sorted array.

    Raises
    ------
    ValueError
        If the input array isn't and can't be converted to COO format.

    Examples
    --------
    >>> import sparse
    >>> x = sparse.COO.from_numpy([1, 0, 2, 0, 2, -3])
    >>> sparse.sort(x).todense()
    array([-3,  0,  0,  1,  2,  2])
    >>> sparse.sort(x, descending=True).todense()
    array([ 2,  2,  1,  0,  0, -3])

    """
    from .._common import moveaxis
    from .core import COO

    x = _validate_coo_input(x)

    if stable:
        raise ValueError("`stable=True` isn't currently supported.")

    original_ndim = x.ndim
    if x.ndim == 1:
        x = x[None, :]
        axis = -1

    x = moveaxis(x, source=axis, destination=-1)
    x_shape = x.shape
    x = x.reshape((-1, x_shape[-1]))

    new_coords, new_data = _sort_coo(x.coords, x.data, x.fill_value, sort_axis_len=x_shape[-1], descending=descending)

    x = COO(new_coords, new_data, x.shape, has_duplicates=False, sorted=True, fill_value=x.fill_value)

    x = x.reshape(x_shape[:-1] + (x_shape[-1],))
    x = moveaxis(x, source=-1, destination=axis)
    if original_ndim == x.ndim:
        return x
    x = x.squeeze()
    if x.shape == ():
        return x[None]
    return x