I discovered on my x86 VM (32 bit) that the following program:
#include <stdio.h> void foo (long double x) { int y = x; printf("(int)%Lf = %d\n", x, y); } int main () { foo(.9999999999999999999728949456878623891498136799780L); foo(.999999999999999999972894945687862389149813679978L); return 0; }
Produces the following output:
(int)1.000000 = 1 (int)1.000000 = 0
Ideone also produces this behavior.
What is the compiler doing to allow this to happen?
I found this constant as I was tracking down why the following program didn't produce 0
as I expected (using 19 9
s produced the 0
I expected):
int main () { long double x = .99999999999999999999L; /* 20 9's */ int y = x; printf("%d\n", y); return 0; }
As I tried to compute the value at which the result switches from expected to unexpected, I arrived at the constant this question is about.
Floating-point decimal values generally do not have an exact binary representation. This is a side effect of how the CPU represents floating point data. For this reason, you may experience some loss of precision, and some floating-point operations may produce unexpected results.
The floating-point calculations are inaccurate because mainly the rationals are approximating that cannot be represented finitely in base 2 and in general they are approximating numbers which may not be representable in finitely many digits in any base.
It's a problem caused when the internal representation of floating-point numbers, which uses a fixed number of binary digits to represent a decimal number. It is difficult to represent some decimal number in binary, so in many cases, it leads to small roundoff errors.
It's broken in the exact same way the decimal (base-10) notation you learned in grade school and use every day is broken, just for base-2. To understand, think about representing 1/3 as a decimal value. It's impossible to do exactly!
Your problem is that long double
on your platform has insufficient precision to store the exact value 0.99999999999999999999. This means that the value of that must be converted to a representable value (this conversion happens during translation of your program, not at runtime).
This conversion can generate either the nearest representable value, or the next greater or smaller representable value. The choice is implementation-defined, so your implementation should document which it is using. It seems that your implementation uses x87-style 80bit long double
, and is rounding to the nearest value, resulting in a value of 1.0 stored in x
.
With the assumed format for long double
(with 64 mantissa bits), the highest representable number less than 1.0 is, in hexadecimal:
0x0.ffffffffffffffff
The number exactly halfway between this value and the next higher representable number (1.0) is:
0x0.ffffffffffffffff8
Your very long constant 0.9999999999999999999728949456878623891498136799780 is equal to:
0x0.ffffffffffffffff7fffffffffffffffffffffffa1eb2f0b64cf31c113a8ec...
which should obviously be rounded down if rounding to nearest, but you appear to have reached some limit of the floating point representation your compiler is using, or a rounding bug.
Compiler uses binary numbers. Most compilers do the same thing.
According to wolframalpha, binary representation of
0.99999999999999999999
looks like this:
0.11111111111111111111111111111111111111111111111111111111111111111101000011000110101111011110011011011011011110111011100101000101010111011100001011010001001110001101011001010000110000101001111011111001111110000101010111111110100110000010001001101011001101010110110010010101101111101001110001100111101100000000100110110001100110000011000100100011000011110100001000000100001000101000111011010111111101011010010000010110011111110100100110001011001110100011100001111101011110101001000000111110010000101101001001010110010011001110111111100111101111100000111010001101101011000100110001010010001000100010110000101110100101010101001010100010001001100111111111001001101100000000010010001011110100101011101001001101001111001001000101011101001100111101110111111001101110100111000001111101101101101101110100100111101000000000111101101101001000111101100010101110011101110001110010110110111101000011110110100011000110101100011111111110111000010010001111000000000101100101000100101110100001001101000010110101000100011100000110010001110101...
That's 932 bits, and that STILL isn't enough to precisely represent your number (see dots at the end).
Which means that as long as your underlying platform uses base of 2 to store numbers, you will not be able to store exactly 0.99999999999999999999
.
Because number cannot be stored precisely, it'll be rounded up or down. With 20 9s it ends up being rounded up, and with 19 9s it ends up being rounded down.
To avoid this problem, instead of doubles you'll need to use some kind of 3rd party mathematics/bignum library that stores numbers internally using decimal base (i.e. two decimal digits per byte or something) or uses fractions (ratios) instead of floating point numbers. That would solve your problem.
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