[R] Interesting quirk with fractions and rounding

JRG loesljrg at accucom.net
Fri Apr 21 14:48:15 CEST 2017

A good part of the problem in the specific case you initially presented
is that some non-integer numbers have an exact representation in the
binary floating point arithmetic being used.  Basically, if the
fractional part is of the form 1/2^k for some integer k > 0, there is an
exact representation in the binary floating point scheme.

> options(digits=20)

> (100*23)/40
[1] 57.5

> 100*(23/40)
[1] 57.499999999999992895

So the two operations give a slightly different result because the
fractional part of the division of 100*23 by 40 is 0.5.  So the first
operations gives, exactly, 57.5 while the second operation does not
because 23/40 has no exact representation.

But, change the example's divisor from 40 to 30 [the fractional part
from 1/2 to 2/3]:

> (100*23)/30
[1] 76.666666666666671404

> 100*(23/30)
[1] 76.666666666666671404

Now the two operations give the same answer to the full precision
available.  So, it isn't "generally true true in R that (100*x)/y is
more accurate than 100*(x/y), if x > y."

The key (in your example) is a property of the way that floating point
arithmetic is implemented.


On 04/21/2017 08:19 AM, Paul Johnson wrote:
> We all agree it is a problem with digital computing, not unique to R. I
> don't think that is the right place to stop.
> What to do? The round example arose in a real funded project where 2 R
> programs differed in results and cause was  that one person got 57 and
> another got 58. The explanation was found, but its less clear how to
> prevent similar in future. Guidelines, anyone?
> So far, these are my guidelines.
> 1. Insert L on numbers to signal that you really mean INTEGER. In R,
> forgetting the L in a single number will usually promote whole calculation
> to floats.
> 2. S3 variables are called 'numeric' if they are integer or double storage.
> So avoid "is.numeric" and prefer "is.double".
> 3. == is a total fail on floats
> 4. Run print with digits=20 so we can see the less rounded number. Perhaps
> start sessions with "options(digits=20)"
> 5. all.equal does what it promises, but one must be cautious.
> Are there math habits we should follow?
> For example, Is it generally true in R that (100*x)/y is more accurate than
> 100*(x/y), if x > y?   (If that is generally true, couldn't the R
> interpreter do it for the user?)
> I've seen this problem before. In later editions of the game theory program
> Gambit, extraordinary effort was taken to keep values symbolically as
> integers as long as possible. Avoid division until the last steps. Same in
> Swarm simulations. Gary Polhill wrote an essay about the Ghost in the
> Machine along those lines, showing accidents from trusting floats.
> I wonder now if all uses of > or < with numeric variables are suspect.
> Oh well. If everybody posts their advice, I will write a summary.
> Paul Johnson
> University of Kansas
> On Apr 21, 2017 12:02 AM, "PIKAL Petr" <petr.pikal at precheza.cz> wrote:
>> Hi
>> The problem is that people using Excel or probably other such spreadsheets
>> do not encounter this behaviour as Excel silently rounds all your
>> calculations and makes approximate comparison without telling it does so.
>> Therefore most people usually do not have any knowledge of floating point
>> numbers representation.
>>  Cheers
>> Petr
>> -----Original Message-----
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Paul
>> Johnson
>> Sent: Thursday, April 20, 2017 11:56 PM
>> To: R-help <r-help at r-project.org>
>> Subject: [R] Interesting quirk with fractions and rounding
>> Hello, R friends
>> My student unearthed this quirk that might interest you.
>> I wondered if this might be a bug in the R interpreter. If not a bug, it
>> certainly stands as a good example of the dangers of floating point numbers
>> in computing.
>> What do you think?
>>> 100*(23/40)
>> [1] 57.5
>>> (100*23)/40
>> [1] 57.5
>>> round(100*(23/40))
>> [1] 57
>>> round((100*23)/40)
>> [1] 58
>> The result in the 2 rounds should be the same, I think.  Clearly some
>> digital number devil is at work. I *guess* that when you put in whole
>> numbers and group them like this (100*23), the interpreter does integer
>> math, but if you group (23/40), you force a fractional division and a
>> floating point number. The results from the first 2 calculations are not
>> actually 57.5, they just appear that way.
>> Before you close the books, look at this:
>>> aa <- 100*(23/40)
>>> bb <- (100*23)/40
>>> all.equal(aa,bb)
>> [1] TRUE
>>> round(aa)
>> [1] 57
>>> round(bb)
>> [1] 58
>> I'm putting this one in my collection of "difficult to understand"
>> numerical calculations.
>> If you have seen this before, I'm sorry to waste your time.
>> pj
>> --
>> Paul E. Johnson   http://pj.freefaculty.org
>> Director, Center for Research Methods and Data Analysis
>> http://crmda.ku.edu
>> To write to me directly, please address me at pauljohn at ku.edu.
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