Dividing all elements in a multidimensional array by an array of numbers Numpy Python-CodePudding

I have a python question:

If I have a multidimensional array lets say shape (3,4) and a 1D array with 3 values that for example look like this:

profile = np.array([[1,2,3,5],[3,6,2,5],[2,8,3,5]]) 

radius = np.array([4,8,3])

I am looking for a way to divide all values from the first/second element of my multidimensional array by the corresponding first/second number of the 1D array. So as an output I would basically something like:

profile_new = np.array[[1,2,3,5]/4], [[3,6,2,5]/8], [[2,8,3,5]/3]

I tried:

for i,j in zip(radius_prof, r_500):
    radius = i/j

But this yields an array only consisting of 4 elements, but I want again a multidimensional array with shape (3,4).

I hope my question is understandable, this is my first post here and I could not find any similar question.

Thanks in advance!

CodePudding user response：

You need to append results to a list in for:

import numpy as np

profile = np.array([[1,2,3,5],[3,6,2,5],[2,8,3,5]])
radius = np.array([4,8,3])


result = []
for i,j in zip(profile, radius):
    result.append(i/j)

result

By list comprehension :

result = [x/y for x,y in zip(profile,radius) ]

A better way :

result = np.divide(profile.T, radius).T

Output:

[array([0.25, 0.5 , 0.75, 1.25]),
 array([0.375, 0.75 , 0.25 , 0.625]),
 array([0.66666667, 2.66666667, 1.        , 1.66666667])]

CodePudding user response：

What about using simple division and broadcasting?

profile = np.array([[1,2,3,5],[3,6,2,5],[2,8,3,5]])
radius = np.array([4,8,3])
print(profile / radius[:, None])
# [[0.25       0.5        0.75       1.25      ]
#  [0.375      0.75       0.25       0.625     ]
#  [0.66666667 2.66666667 1.         1.66666667]]