Floating point errors can kill you!

Humor
1
9 Likes
2

Root cause: accumulation of floating point rounding error combined with a tolerance on the equality check
Lesson: use exact equality checks with floating point numbers

3

Oh please don’t. This will bite you far more often than the example in the video. You’ll be totally scratching your head wondering why

x = 0.1
y = 0.2
z = 0.3
if (x + y == z) print *, "Success!"

doesn’t seem to work.

1 Like
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0.1 is not 0.1,
but 0.125 is 0.125. :robot:

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If you watch the video, the real problem seems to be a form of race condition. There are two flags, one that is set with a tolerance and one that is not.

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Oh the finitely countable joys of floating point numbers!

3 Likes
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Note that I posted that on April 1st (at least in my timezone). :laughing:

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8

phew :sweat_smile: I didn’t read it till after, so wasn’t sure.

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Yes writing sophisticated code like this

real(REAL64) :: a
real               :: b
If ((a-b) == 0.0) then
  a = 1.0
  b = 2
End If

is best left to us experienced programmers :smile:

Surprisingly, I still see nonsense like this in codes written in the last few years by people who should know better.

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Isn’t this a result of the fact tha 0.125 can be exactly represented in binary but 0.1 don’t?

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Yes :

  • 0.125 = 1/8 = 0b0.001
  • 0.1 = 1/10 = 0b0.0001100110011001101…

A number with a finite number of digits in a base can have an infinite number of digits in another base.

But if there is a finite number of digits in binary, there should always be a finite number in decimal, as it is a sum of 1/2^n. But in other bases?

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Dont know the answer, but I think with larger bases there are more number that can be represented exactly.

13

It sounds reasonable.

14

I guess it’s a matter of prime factors in the base. Base two has only one prime factor and therefore can only exactly represent numbers which can be represented as the sum \sum_{k=m}^{n} a_k2^k.
Base ten has two prime factors: 2 and 5. Therefore, every number, that can be represented exactly with a finite amount of digits with base two, can be represented exactly with base 10, but not the other way around.

1 Like
15

Makes a lot of sense