Rounding Issue With Python

Question

This code

np.uint32( 1.13*100 )

returns 112

It should be 113.

How can I get around the strange rounding issue and make it return 113?

I am on numpy 1.9.1

start with 1.13*100 you'll see it is not 1.12. (there has to be a question here that explains what is wrong with floats, but I can't find it for now) — njzk2
– njzk2, Commented Feb 2, 2015 at 20:22
possible duplicate of Is floating point math broken? There it is. — njzk2
– njzk2, Commented Feb 2, 2015 at 20:23

Alex Riley · Accepted Answer · 2015-02-02 22:19:15Z

4

If you can avoid it, don't cast the result of a floating point multiplication directly to an integer. Casting doesn't round the number to the nearest integer, it merely drops the decimal part of the float.

The problem is that floating point numbers are often only close approximations of real numbers. Arithmetical operations can exacerbate discrepancies. In your example:

>>> 1.13*100
112.99999999999999

The decimal part is dropped upon casting to an integer, leaving 112.

It would be better to round the number to the nearest integer first (e.g. with np.round) and then cast it to an integer type:

>>> np.int32(np.round(1.13*100))
113

edited Feb 2, 2015 at 22:19

answered Feb 2, 2015 at 20:40

Alex Riley

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