NumPy NumPy参考

• 数组对象
•    N维数组（ndarray）
•       numpy.ndarray
•             numpy.ndarray.all
•             numpy.ndarray.any
•             numpy.ndarray.argmax
•             numpy.ndarray.argmin
•             numpy.ndarray.argpartition
•             numpy.ndarray.argsort
•             numpy.ndarray.astype
•             numpy.ndarray.byteswap
•             numpy.ndarray.choose
•             numpy.ndarray.clip
•             numpy.ndarray.compress
•             numpy.ndarray.conj
•             numpy.ndarray.conjugate
•             numpy.ndarray.copy
•             numpy.ndarray.cumprod
•             numpy.ndarray.cumsum
•             numpy.ndarray.diagonal
•             numpy.ndarray.dot
•             numpy.ndarray.dump
•             numpy.ndarray.dumps
•             numpy.ndarray.fill
•       numpy.ndarray.flatten
•       numpy.ndarray.sort
•       numpy.ndarray.tofile
•       numpy.ndarray.tolist
•       numpy.ndarray.T
•       numpy.ndarray.flat
•       numpy.ndarray.__lt__
•       numpy.ndarray.__le__
•       numpy.ndarray.__gt__
•       numpy.ndarray.__ge__
•       numpy.ndarray.__eq__
•       numpy.ndarray.__ne__
•       numpy.ndarray.__bool__
•       numpy.ndarray.__neg__
•       numpy.ndarray.__pos__
•       numpy.ndarray.__abs__
•       numpy.ndarray.__invert__
•       numpy.ndarray.__add__
•       numpy.ndarray.__sub__
•       numpy.ndarray.__mul__
•       numpy.ndarray.__truediv__
•       numpy.ndarray.__floordiv__
•       numpy.ndarray.__mod__
•       numpy.ndarray.__divmod__
•       numpy.ndarray.__pow__
•       numpy.ndarray.__lshift__
•       numpy.ndarray.__rshift__
•       numpy.ndarray.__and__
•       numpy.ndarray.__or__
•       numpy.ndarray.__xor__
•       numpy.ndarray.__iadd__
•       numpy.ndarray.__isub__
•       numpy.ndarray.__imul__
•       numpy.ndarray.__itruediv__
•       numpy.ndarray.__ifloordiv__
•       numpy.ndarray.__imod__
•       numpy.ndarray.__ipow__
•       numpy.ndarray.__ilshift__
•       numpy.ndarray.__irshift__
•       numpy.ndarray.__iand__
•       numpy.ndarray.__ior__
•       numpy.ndarray.__ixor__
•       numpy.ndarray .__ matmul__
•       numpy.ndarray .__ copy__
•       numpy.ndarray .__ deepcopy__
•       numpy.ndarray .__ reduce__
•       numpy.ndarray .__ setstate__
•       numpy.ndarray .__ new__
•       numpy.ndarray .__ array__
•       numpy.ndarray .__ array_wrap__
•       numpy.ndarray .__ len__
•       numpy.ndarray .__ getitem__
•       numpy.ndarray .__ setitem__
•       numpy.ndarray .__包含__
•       numpy.ndarray .__ int__
•       numpy.ndarray .__ float__
•       numpy.ndarray .__ complex__
•       numpy.ndarray .__ str__
•       numpy.ndarray .__ repr__
•    标量
•    数据类型对象（dtype）
•    索引编制
•    遍历数组
•    标准数组子类
•    Masked arrays
•    Masked array operations
•    阵列介面
•    日期时间和时间增量
• 常数
• 通用功能（ufunc）
• 例行程序
• Packaging (numpy.distutils)
• NumPy Distutils - Users Guide
• NumPy C-API
• NumPy内部
• NumPy和SWIG

方法

ndarray.all（axis = None，out = None，keepdims = False ）¶

如果所有元素的评估结果为True，则返回True。

请参阅numpy.all完整的文档。

也可以看看

numpy.all

等效功能