Divide each row by a vector element with floating value precision

Question

Suppose i have

a = np.arange(9).reshape((3,3))

and i want to divide each row with a vector

n = np.array([1.1,2.2,3.3])

I tried the proposed solution in this question but the fractional value is not taken into account.

@Divakar pls answer the question so I can give you credits thanks — Jasper Bernales, Apr 08 '16 at 14:16
You would learn more if you try to answer your own question. So, please do so, if you could. Feel free to use the comment and online docs on how to use it. — Divakar, Apr 08 '16 at 14:17
When I executed `a / n` on my interpreter (anaconda 2.7) I think I got your desired result. When you say "the fractional value is not taken into account", do you mean you're getting results from integer division? — Matt Messersmith, Apr 08 '16 at 14:28
An other workaround is to generate a float array with arange(9.0) . — B. M., Apr 08 '16 at 14:46

score 0 · Accepted Answer · answered Apr 08 '16 at 17:23

I understand your question differently from the comments above:

import numpy as np 
a = np.arange(12).reshape((4,3))
print a

n = np.array([[1.1,2.2,3.3]])
print n

print a/n

Output:

[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]]
[[ 1.1  2.2  3.3]]
[[ 0.          0.45454545  0.60606061]
 [ 2.72727273  1.81818182  1.51515152]
 [ 5.45454545  3.18181818  2.42424242]
 [ 8.18181818  4.54545455  3.33333333]]

I also changed from a symmetric matrix (3x3) to (3x4) to point out that row vs columns matter. Also the divisor is a column vector now (double brackets).

Divide each row by a vector element with floating value precision

1 Answers1