numpy.dot(a, b, out=None)
Dot product of two arrays. Specifically,
a
and b
are 1D arrays, it is inner product of vectors (without complex conjugation). a
and b
are 2D arrays, it is matrix multiplication, but using matmul
or a @ b
is preferred. a
or b
is 0D (scalar), it is equivalent to multiply
and using numpy.multiply(a, b)
or a * b
is preferred. a
is an ND array and b
is a 1D array, it is a sum product over the last axis of a
and b
. If a
is an ND array and b
is an MD array (where M>=2
), it is a sum product over the last axis of a
and the secondtolast axis of b
:
dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])
Parameters: 


Returns: 

Raises: 

See also
>>> np.dot(3, 4) 12
Neither argument is complexconjugated:
>>> np.dot([2j, 3j], [2j, 3j]) (13+0j)
For 2D arrays it is the matrix product:
>>> a = [[1, 0], [0, 1]] >>> b = [[4, 1], [2, 2]] >>> np.dot(a, b) array([[4, 1], [2, 2]])
>>> a = np.arange(3*4*5*6).reshape((3,4,5,6)) >>> b = np.arange(3*4*5*6)[::1].reshape((5,4,6,3)) >>> np.dot(a, b)[2,3,2,1,2,2] 499128 >>> sum(a[2,3,2,:] * b[1,2,:,2]) 499128
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Licensed under the 3clause BSD License.
https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.dot.html