numpy.dot(vector_a, vector_b, out = None) returns the dot product of vectors a and b. It can handle 2D arrays but considering them as matrix and will perform matrix multiplication. For N dimensions it is a sum product over the last axis of a and the second-to-last of b :
dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])
- vector_a : [array_like] if a is complex its complex conjugate is used for the calculation of the dot product.
- vector_b : [array_like] if b is complex its complex conjugate is used for the calculation of the dot product.
- out : [array, optional] output argument must be C-contiguous, and its dtype must be the dtype that would be returned for dot(a,b).
Dot Product of vectors a and b. if vector_a and vector_b are 1D, then scalar is returned
Code 1 –
Dot Product of scalar values : 20 Dot Product : (-7+22j)
How Code1 works ?
vector_a = 2 + 3j
vector_b = 4 + 5j
now dot product
= 2(4 + 5j) + 3j(4 – 5j)
= 8 + 10j + 12j – 15
= -7 + 22j
Code 2 –
Dot Product : [[22 12] [40 32]] Dot Product : [[22 32] [15 32]]
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