max

计算输入数组 x 的最大值。

参数

名称	类型	描述	默认值
x		实值数据类型的输入数组。	必需
axis		计算最大值的轴。默认情况下，最大值在整个数组上计算。如果是一个整数元组，则在多个轴上计算最大值。默认值：None。	无
keepdims		如果为 True，则将约简的轴（维度）作为单例维度包含在结果中。因此，结果与输入数组兼容。否则，如果为 False，则约简的轴（维度）不得包含在结果中。默认值：False。	False

返回值

名称	类型	描述
out	数组	如果最大值是在整个数组上计算的，则为一个包含最大值的零维数组。否则，为一个包含最大值的非零维数组。返回的数组具有与 x 相同的数据类型。

特殊情况

对于浮点操作数，如果 x_i 为 NaN，则最大值为 NaN（即，NaN 值会传播）。

示例

>>> a = sparse.COO.from_numpy(np.array([[0, 1], [2, 0]]))
>>> o = sparse.max(a, axis=1)
>>> o.todense()
array([1, 2])

源代码位于 sparse/numba_backend/_common.py

def max(x, /, *, axis=None, keepdims=False):
    """
    Calculates the maximum value of the input array ``x``.

    Parameters
    ----------
    x: array
        input array of a real-valued data type.
    axis: Optional[Union[int, Tuple[int, ...]]]
        axis or axes along which maximum values are computed.
        By default, the maximum value are computed over the entire array.
        If a tuple of integers, maximum values are computed over multiple axes. Default: ``None``.
    keepdims: bool
        If ``True``, the reduced axes (dimensions) are included in the result as singleton dimensions.
        Accordingly, the result is compatible with the input array.
        Otherwise, if ``False``, the reduced axes (dimensions) must not be included in the result. Default: ``False``.

    Returns
    -------
    out: array
        if the maximum value was computed over the entire array, a zero-dimensional array containing the maximum value.
        Otherwise, a non-zero-dimensional array containing the maximum values.
        The returned array has the same data type as ``x``.

    Special Cases
    -------------
    For floating-point operands, if ``x_i`` is ``NaN``, the maximum value is ``NaN`` (i.e., ``NaN`` values propagate).

    Examples
    --------
    >>> a = sparse.COO.from_numpy(np.array([[0, 1], [2, 0]]))
    >>> o = sparse.max(a, axis=1)
    >>> o.todense()
    array([1, 2])
    """
    return x.max(axis=axis, keepdims=keepdims)