Notice you are not only working with 1D arrays:
In [6]: a.ndim
Out[6]: 1
In [7]: b.ndim
Out[7]: 2
So, b
is a 2D array.
You also see this in the output of b.shape
: (1,3) indicates two dimensions as (3,) is one dimension.
The behaviour of np.dot
is different for 1D and 2D arrays (from the docs):
For 2-D arrays it is equivalent to matrix multiplication, and for 1-D
arrays to inner product of vectors
That is the reason you get different results, because you are mixing 1D and 2D arrays. Since b
is a 2D array, np.dot(b, b)
tries a matrix multiplication on two 1x3 matrices, which fails.
With 1D arrays, np.dot does a inner product of the vectors:
In [44]: a = np.array([1,2,3])
In [45]: b = np.array([1,2,3])
In [46]: np.dot(a, b)
Out[46]: 14
In [47]: np.inner(a, b)
Out[47]: 14
With 2D arrays, it is a matrix multiplication (so 1x3 x 3x1 = 1x1, or 3x1 x 1x3 = 3x3):
In [49]: a = a.reshape(1,3)
In [50]: b = b.reshape(3,1)
In [51]: a
Out[51]: array([[1, 2, 3]])
In [52]: b
Out[52]:
array([[1],
[2],
[3]])
In [53]: np.dot(a,b)
Out[53]: array([[14]])
In [54]: np.dot(b,a)
Out[54]:
array([[1, 2, 3],
[2, 4, 6],
[3, 6, 9]])
In [55]: np.dot(a,a)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-55-32e36f9db916> in <module>()
----> 1 np.dot(a,a)
ValueError: objects are not aligned