为什么 numpy 不允许数组乘以标量？
Why doesn't numpy allow array multiplication by scalars?
对于 dot 方法，我假设 @ 是 shorthand。是什么促使设计决定阻止形状为 () 的数组乘法？
In [6]: a = np.ones((2,1))
In [7]: a.dot(1)
Out[7]:
array([[ 1.],
[ 1.]])
In [8]: a @ 1
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-8-398cff4c0ec9> in <module>()
----> 1 a @ 1
ValueError: Scalar operands are not allowed, use '*' instead
@ 是 matmul 的中缀运算符，而不是 dot （请注意，这两个函数对于 higher-dimensional 数组（高于 2D）是不等价的）。
文档中没有明确说明拒绝标量作为操作数的原因，但动机似乎可能源于 PEP 0465，它最初提议引入 @ 作为 [ 的中缀运算符=27=] 3.5。来自 'semantics' 部分：
0d (scalar) inputs raise an error. Scalar * matrix multiplication is a mathematically and algorithmically distinct operation from matrix @ matrix multiplication, and is already covered by the elementwise * operator. Allowing scalar @ matrix would thus both require an unnecessary special case, and violate TOOWTDI ["There's Only One Way To Do It"].
对于 dot 方法，我假设 @ 是 shorthand。是什么促使设计决定阻止形状为 () 的数组乘法？
In [6]: a = np.ones((2,1))
In [7]: a.dot(1)
Out[7]:
array([[ 1.],
[ 1.]])
In [8]: a @ 1
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-8-398cff4c0ec9> in <module>()
----> 1 a @ 1
ValueError: Scalar operands are not allowed, use '*' instead
@ 是 matmul 的中缀运算符，而不是 dot （请注意，这两个函数对于 higher-dimensional 数组（高于 2D）是不等价的）。
文档中没有明确说明拒绝标量作为操作数的原因，但动机似乎可能源于 PEP 0465，它最初提议引入 @ 作为 [ 的中缀运算符=27=] 3.5。来自 'semantics' 部分：
0d (scalar) inputs raise an error. Scalar
*matrix multiplication is a mathematically and algorithmically distinct operation from matrix@matrix multiplication, and is already covered by the elementwise*operator. Allowing scalar@matrix would thus both require an unnecessary special case, and violate TOOWTDI ["There's Only One Way To Do It"].