Printing numpy array in python

Question

Here's a simple code in python.

end = np.zeros((11,2))
alpha=0
while(alpha<=1):
    end[int(10*alpha)] = alpha
    print(end[int(10*alpha)])
    alpha+=0.1
print('')
print(end)

and output:

[ 0.  0.]
[ 0.1  0.1]
[ 0.2  0.2]
[ 0.3  0.3]
[ 0.4  0.4]
[ 0.5  0.5]
[ 0.6  0.6]
[ 0.7  0.7]
[ 0.8  0.8]
[ 0.9  0.9]
[ 1.  1.]

[[ 0.   0. ]
 [ 0.1  0.1]
 [ 0.2  0.2]
 [ 0.3  0.3]
 [ 0.4  0.4]
 [ 0.5  0.5]
 [ 0.6  0.6]
 [ 0.8  0.8]
 [ 0.   0. ]
 [ 1.   1. ]
 [ 0.   0. ]]

It is easy to notice that 0.7 is missing and after 0.8 goes 0 instead of 0.9 etc... Why are these outputs differ?

Denziloe · Accepted Answer · 2017-03-17 12:54:19Z

1

It's because of floating point errors. Run this:

import numpy as np

end = np.zeros((11, 2))
alpha=0
while(alpha<=1):
    print("alpha is ", alpha)
    end[int(10*alpha)] = alpha
    print(end[int(10*alpha)])
    alpha+=0.1
print('')
print(end)

and you will see that alpha is, successively:

alpha is  0
alpha is  0.1
alpha is  0.2
alpha is  0.30000000000000004
alpha is  0.4
alpha is  0.5
alpha is  0.6
alpha is  0.7
alpha is  0.7999999999999999
alpha is  0.8999999999999999
alpha is  0.9999999999999999

Basically floating point numbers like 0.1 are stored inexactly on your computer. If you add 0.1 together say 8 times, you won't necessarily get 0.8 -- the small errors can accumulate and give you a different number, in this case 0.7999999999999999. Numpy arrays must take integers as indexes however, so it uses the int function to force this to round down to the nearest integer -- 7 -- which causes that row to be overwritten.

To solve this, you must rewrite your code so that you only ever use integers to index into an array. One slightly crude way would be to round the float to the nearest integer using the round function. But really you should rewrite your code so that it iterates over integers and coverts them into floats, rather than iterating over floats and converting them into integers.

You can read more about floating point numbers here:

https://docs.python.org/3/tutorial/floatingpoint.html

edited Mar 17, 2017 at 12:54

answered Mar 17, 2017 at 12:49

Denziloe

8,3323 gold badges31 silver badges40 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

user2261062 Over a year ago

Yes, you can try int(10*(0.1+0.1+0.1+0.1+0.1+0.1+0.1+0.1)) and it will give 7 instead of 8. Use round() instead of int() to solve the problem.

Denziloe Over a year ago

Thanks, I have incorporated that into my answer.

user2261062 · Accepted Answer · 2017-03-17 12:55:14Z

1

As @Denziloe pointed, this is due to floating point errors.

If you look at the definition of int():

If x is floating point, the conversion truncates towards zero

To solve your problem use round() instead of int()

answered Mar 17, 2017 at 12:55

user2261062

Collectives™ on Stack Overflow

Printing numpy array in python

2 Answers 2

2 Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

2 Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related