Numpy: Applying a formula with elements of each row of an array

Question

I have a multidimensional numpy array called k . Each row represents variables and i have the formula

How can I have a numpy array where every row (depending of the number of columns, this is just an example) has been processed by this formula?

My desired output is something like this:

or

[[12][12][4]]

Answer 1

You could use apply_along_axis.

import numpy as np

k = [[4, 2, 6], [5, 2, 9], [10, 3, 7]]

k = np.array(k)

def function(m):

  x = m[0]
  y = m[1]
  z = m[2]

  return ((4*z)/(x-y))

result = np.apply_along_axis(function, 1, k)

print(result)

Answer 2

Since these are numpy arrays, you can use array operations to solve all of these together without needing loops:

import numpy as np

k = [[4, 2, 6], [5, 2, 9], [10, 3, 7]]
k = np.array(k)

t = k.transpose()
x, y, z = t
print((4*z)/(x-y))

Output:

[12. 12.  4.]

Putting that in a function:

def function(m):
    x, y, z = m.transpose()
    return (4*z)/(x-y)

And if you want it as 3 single-item arrays in an array, put this reshape as the last part of the function:

a = (4*z)/(x-y)
print(a.reshape(3, 1))

Output:

[[12.]
 [12.]
 [ 4.]]

Answer 3

you can try this:

import numpy as np

# [(x1, y1, z1), (x2, y2, z2) ...)]
k = [[4, 2, 6], [5, 2, 9], [10, 3, 7]]

k = np.asarray(k)

x = k[:, 0]
y = k[:, 1]
z = k[:, 2]

out = np.divide(4*z, x-y)
# out = (4*z) / (x-y)
print(out)