Equality test and accuracy of machine [duplicate] - c

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Floating point inaccuracy examples
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C++ floating point precision [duplicate]
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I found this code snippet on Page 174, A Book on C -Al Kelley, Ira Pohl .
int main()
{
int cnt=0; double sum=0.0,x;
for( x=0.0 ;x!= 9.9 ;x+=0.1)
{
sum=sum +x;
printf("cnt = %5d\n",cnt++);
}
return 0;
}
and it became a infinite loop as the book said it would. It didnt mention the precise reason except saying that it had to do with the accuracy of the machine.
I modified the code to check if
x=9.9
would ever become true, i.e. x was attaining 9.9 by adding the following lines
diff=x-9.9;
printf("cnt =10%d \a x =%10.10lf dif=%10.10lf \n",++cnt,x,diff);
and i got the following lines among the output
cnt =1098 x =9.7000000000 dif=-0.2000000000
cnt =1099 x =9.8000000000 dif=-0.1000000000
cnt =10100 x =9.9000000000 dif=-0.0000000000
cnt =10101 x =10.0000000000 dif=0.1000000000
cnt =10102 x =10.1000000000 dif=0.2000000000
if x is attaining the value 9.9 exactly , why is it still a infinite loop?

Answer 1

You are simply printing the number with too poor accuracy to notice that it isn't exact. Try something like this:
#include <stdio.h>
int main()
{
double d = 9.9;
if(d == 9.9)
{
printf("Equal!");
}
else
{
printf("Not equal! %.20f", d);
}
}
Output on my machine:
Not equal! 9.90000000000000035527
The book is likely trying to teach you to never use == or != operators to compare floating point variables. Also for the same reason, never use floats as loop iterators.

Answer 2

The problem is that most floating point implementation are based on IEEE 754. See http://en.wikipedia.org/wiki/IEEE_floating_point
The problem with this is, that numbers are builded with base 2 (binary formats).
The number 9.9 can never be build with base 2 excatly.
The "Numerical Computation Guide" by David Goldberg gves an exact statement about it:
Several different representations of real numbers have been proposed,
but by far the most widely used is the floating-point representation.
Floating-point representations have a base b (which is always assumed to
be even) and a precision p. If b = 10 and p = 3, then the number 0.1 is
represented as 1.00 × 10^-1. If b = 2 and p = 24, then the decimal
number 0.1 cannot be represented exactly, but is approximately
1.10011001100110011001101 × 2^-4.

Answer 3

You can safely assume two floating point numbers are never equal 'exactly' (unless one is a copy of the other).

Answer 4

Computer works on binary and floating point, in other words in base 2. Just like base 10, base 2 have numbers that it cannot build. For example, try to write the fraction 10/3 in base 10. You'll end up with infinite 3s. and in Binary, you cannot even write 0.1 (decimal) in binary, you'll also get a recurring pattern 0.0001100110011... (binary).
This video will do better to explain http://www.youtube.com/watch?v=PZRI1IfStY0