normalize multi dimensional numpy array-CodePudding

I have the following numpy array :

A = np.array([[1,2,3,4,5],
             [15,25,35,45,55]])

I would like to create a new array with the same shape by dividing each dimension by the last element of the dimension

The output desired would be :

B = np.array([[0.2,0.4,0.6,0.8,1],
              [0.27272727,0.45454545,0.63636364,0.81818182,1]])

Any idea ?

CodePudding user response：

You mean this?

B = np.array([[A[i][j]/A[i][len(A[i])-1] for j in range(0,len(A[i]))] for i in range(0,len(A))])

CodePudding user response：

You can achieve this using:

[list(map(lambda i: i / a[-1], a)) for a in A]

Result:

[[0.2, 0.4, 0.6, 0.8, 1.0], [0.2727272727272727, 0.45454545454545453, 0.6363636363636364, 0.8181818181818182, 1.0]]