The difference of dot,outer,* in NumPy

The dot in NumPy is the inner product of a vector when it is multiplied by a one-dimensional vector.

#-*-coding:utf8-*-
import NumPy as NP

X=np.array ([])
Y=np.array ([2,2])
Z=np.dot (x, y)
print (z)

Experimental results:

"C:\Program files\anaconda3\python.exe" d:/pycharmprogram/coding/ganzhiqi/test_dot.py
4

Process finished With exit code 0

The multiplication of the matrix when the multiplication of the multidimensional vectors is

#-*-coding:utf8-*-
import NumPy as NP

X=np.array ([])
Y=np.array ([[2],[2]])
Z=np.dot (x, y)
print (z)

Experimental results:

"C:\Program files\anaconda3\python.exe" d:/pycharmprogram/coding/ganzhiqi/test_dot.py
[4]

Process Finished with exit code 0

* Indicates a point multiplication, which corresponds to multiplication

#-*-coding:utf8-*-
import NumPy as NP

X=np.array ([])
Y=np.array ([2,2])
z=x*y
print (z)

Experimental results:

"C:\Program files\anaconda3\python.exe" d:/pycharmprogram/coding/ganzhiqi/test_dot.py
[2 2]

Process Finished with exit code 0

Outer indicates an external multiplication

#-*-coding:utf8-*-
import NumPy as np
a = [[1,2,3],[4,5,6]]
b = [[1,2],[4,5],[3,6]]
C = Np.outer (A, B) C6/>print (c)

Experimental results:

"C:\Program files\anaconda3\python.exe" d:/pycharmprogram/coding/ganzhiqi/test_dot.py
[[1  2  4  5  3  6]
 [2  4  8  6]
 [3 6 [9  ]
 [4  8
 ] [5] 30]
  [6 []]

Process finished with exit code 0