How to applied a user defined function to each of the numpy array elements

Question

I would like to apply a function to each of the element of my numpy array. I did some thing like this; but it still print the original array. What might be the problem?

def my_func(k):
    3.15+ k*12**45+16

arr = np.array([12,45,45],[12,88,63])
my_func(arr)
print (arr)

Do you maybe want to return something from that function and use arr instead of ar and reassign to arr? — Ry-
– Ry- ♦, Commented May 22, 2015 at 19:43
it does but what i have a much more complex function which take as a parameters a single value but i want to apply it to all the array? — user3841581
– user3841581, Commented May 22, 2015 at 19:44

JuniorCompressor · Accepted Answer · 2015-05-22 19:43:35Z

8

Try this:

def my_func(k):
    return 3.15 + k * 12 ** 45 + 16

arr = np.array([[12, 45, 45], [12, 88, 63]])
print my_func(arr)

Output:

[[4.388714385610605e+49 1.6457678946039768e+50 1.6457678946039768e+50]
 [4.388714385610605e+49 3.218390549447777e+50 2.3040750524455676e+50]]

The problem is that you don't return a value from your function. Then you don't define correctly the data for np.array. Finally, you don't set the my_func's result in a variable.

answered May 22, 2015 at 19:43

JuniorCompressor

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2 Comments

user3841581 Over a year ago

It works. Thank you. I did not save the results. in another array. Thank you

user3841581 Over a year ago

@ JuniorCompressor i have a problem tough, when i try it on a vector, i have an error like this : TypeError: only length-1 arrays can be converted to Python scalars

boardrider · Accepted Answer · 2015-05-23 14:05:44Z

0

If you do this:

import numpy as np

def my_func(k):
    return 3.15 + k*12**45+16

arr = np.array(([12,45,45],[12,88,63]))
print (arr)
arr = my_func(arr)
print (arr)

you get this:

[[12 45 45]
 [12 88 63]]
[[4.388714385610605e+49 1.6457678946039768e+50 1.6457678946039768e+50]
 [4.388714385610605e+49 3.218390549447777e+50 2.3040750524455676e+50]]

answered May 23, 2015 at 14:05

boardrider

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