所有

测试沿指定轴的所有输入数组元素是否评估为 True。

参数

名称	类型	描述	默认值
x		输入数组。	必需
轴		要执行逻辑 AND 归约的轴或多个轴。默认情况下，对整个数组执行逻辑 AND 归约。如果是一个整数元组，则在多个轴上执行逻辑 AND 归约。有效的 axis 是在 [-N, N) 区间上的整数，其中 N 是 x 的秩（维度数）。如果 axis 指定为负整数，函数通过从最后一个维度（其中 -1 指的是最后一个维度）向后计数来确定要执行归约的轴。如果提供了无效的 axis，函数将引发异常。默认值：None。	None
keepdims		如果为 True，则归约的轴（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，则归约的轴（维度）不包含在结果中。默认值：False。	False

返回值

名称	类型	描述
out	数组	如果对整个数组执行了逻辑 AND 归约，则返回的数组是包含测试结果的零维数组；否则，返回的数组是包含测试结果的非零维数组。返回的数组数据类型为 bool。

特殊情况

• 正无穷、负无穷和 NaN 评估为 True。

• 如果 x 具有复浮点数据类型，则具有非零分量（实部或虚部）的元素评估为 True。

• 如果 x 是空数组，或者用于评估元素的轴（维度）大小为零，则测试结果为 True。

示例

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

源代码位于 sparse/numba_backend/_common.py

def all(x, /, *, axis=None, keepdims=False):
    """
    Tests whether all input array elements evaluate to ``True`` along a specified axis.

    Parameters
    ----------
    x: array
        input array.
    axis: Optional[Union[int, Tuple[int, ...]]]
        axis or axes along which to perform a logical AND reduction. By default, a logical AND
        reduction is performed over the entire array.
        If a tuple of integers, logical AND reductions are performed over multiple axes.
        A valid ``axis`` is an integer on the interval ``[-N, N)``, where ``N`` is the rank
        (number of dimensions) of ``x``. If an ``axis`` is specified as a negative integer,
        the function determines the axis along which to perform a reduction by counting backward
        from the last dimension (where ``-1`` refers to the last dimension). If provided an invalid
        ``axis``, the function raiseS an exception. Default: ``None``.
    keepdims: bool
        If ``True``, the reduced axes (dimensions) are included in the result as singleton dimensions,
        and, accordingly, the result is compatible with the input array.
        Otherwise, if ``False``, the reduced axes (dimensions) are not included in the result.
        Default: ``False``.

    Returns
    -------
    out: array
        if a logical AND reduction was performed over the entire array, the returned array is a
        zero-dimensional array containing the test result; otherwise, the returned array is a
        non-zero-dimensional array containing the test results.
        The returned array has a data type of ``bool``.

    Special Cases
    -------------

       - Positive infinity, negative infinity, and NaN  evaluate to ``True``.

       - If ``x`` has a complex floating-point data type, elements having a non-zero component
        (real or imaginary) evaluate to ``True``.

       - If ``x`` is an empty array or the size of the axis (dimension) along which to evaluate elements
         is zero, the test result is ``True``.

    Examples
    --------
    >>> a = sparse.COO.from_numpy(np.array([[0, 1], [2, 0]]))
    >>> o = sparse.all(a, axis=1)
    >>> o.todense()  # doctest: +NORMALIZE_WHITESPACE
    array([False, False])
    """
    return x.all(axis=axis, keepdims=keepdims)