Conversion of a decimal to double number in C# results in a difference
Interesting - although I generally don't trust normal ways of writing out floating point values when you're interested in the exact results.
Here's a slightly simpler demonstration, using DoubleConverter.cs which I've used a few times before.
using System;
class Test
{
static void Main()
{
decimal dcm1 = 8224055000.0000000000m;
decimal dcm2 = 8224055000m;
double dbl1 = (double) dcm1;
double dbl2 = (double) dcm2;
Console.WriteLine(DoubleConverter.ToExactString(dbl1));
Console.WriteLine(DoubleConverter.ToExactString(dbl2));
}
}
Results:
8224055000.00000095367431640625
8224055000
Now the question is why the original value (8224055000.0000000000) which is an integer - and exactly representable as a double - ends up with extra data in. I strongly suspect it's due to quirks in the algorithm used to convert from decimal to double, but it's unfortunate.
It also violates section 6.2.1 of the C# spec:
For a conversion from decimal to float or double, the decimal value is rounded to the nearest double or float value. While this conversion may lose precision, it never causes an exception to be thrown.
The "nearest double value" is clearly just 8224055000... so this is a bug IMO. It's not one I'd expect to get fixed any time soon though. (It gives the same results in .NET 4.0b1 by the way.)
To avoid the bug, you probably want to normalize the decimal value first, effectively "removing" the extra 0s after the decimal point. This is somewhat tricky as it involves 96-bit integer arithmetic - the .NET 4.0 BigInteger class may well make it easier, but that may not be an option for you.
The answer lies in the fact that decimal attempts to preserve the number of significant digits. Thus, 8224055000.0000000000m has 20 significant digits and is stored as 82240550000000000000E-10, while 8224055000m has only 10 and is stored as 8224055000E+0. double's mantissa is (logically) 53 bits, i.e. at most 16 decimal digits. This is exactly the precision you get when you convert to double, and indeed the stray 1 in your example is in the 16th decimal place. The conversion isn't 1-to-1 because double uses base 2.
Here are the binary representations of your numbers:
dcm:
00000000000010100000000000000000 00000000000000000000000000000100
01110101010100010010000001111110 11110010110000000110000000000000
dbl:
0.10000011111.1110101000110001000111101101100000000000000000000001
dcm2:
00000000000000000000000000000000 00000000000000000000000000000000
00000000000000000000000000000001 11101010001100010001111011011000
dbl2 (8224055000.0):
0.10000011111.1110101000110001000111101101100000000000000000000000
For double, I used dots to delimit sign, exponent and mantissa fields; for decimal, see MSDN on decimal.GetBits, but essentially the last 96 bits are the mantissa. Note how the mantissa bits of dcm2 and the most significant bits of dbl2 coincide exactly (don't forget about the implicit 1 bit in double's mantissa), and in fact these bits represent 8224055000. The mantissa bits of dbl are the same as in dcm2 and dbl2 but for the nasty 1 in the least significant bit. The exponent of dcm is 10, and the mantissa is 82240550000000000000.
Update II: It is actually very easy to lop off trailing zeros.
// There are 28 trailing zeros in this constant —
// no decimal can have more than 28 trailing zeros
const decimal PreciseOne = 1.000000000000000000000000000000000000000000000000m ;
// decimal.ToString() faithfully prints trailing zeroes
Assert ((8224055000.000000000m).ToString () == "8224055000.000000000") ;
// Let System.Decimal.Divide() do all the work
Assert ((8224055000.000000000m / PreciseOne).ToString () == "8224055000") ;
Assert ((8224055000.000010000m / PreciseOne).ToString () == "8224055000.00001") ;
The article What Every Computer Scientist Should Know About Floating-Point Arithmetic would be an excellent place to start.
The short answer is that floating-point binary arithmetic is necessarily an approximation, and it's not always the approximation you would guess. This is because CPUs do arithmetic in base 2, while humans (usually) do arithmetic in base 10. There are a wide variety of unexpected effects that stem from this.
To see this problem more plainly illustrated try this in LinqPad (or replace all the .Dump()'s and change to Console.WriteLine()s if you fancy).
It seems logically incorrect to me that the precision of the decimal could result in 3 different doubles. Kudos to @AntonTykhyy for the /PreciseOne idea:
((double)200M).ToString("R").Dump(); // 200
((double)200.0M).ToString("R").Dump(); // 200
((double)200.00M).ToString("R").Dump(); // 200
((double)200.000M).ToString("R").Dump(); // 200
((double)200.0000M).ToString("R").Dump(); // 200
((double)200.00000M).ToString("R").Dump(); // 200
((double)200.000000M).ToString("R").Dump(); // 200
((double)200.0000000M).ToString("R").Dump(); // 200
((double)200.00000000M).ToString("R").Dump(); // 200
((double)200.000000000M).ToString("R").Dump(); // 200
((double)200.0000000000M).ToString("R").Dump(); // 200
((double)200.00000000000M).ToString("R").Dump(); // 200
((double)200.000000000000M).ToString("R").Dump(); // 200
((double)200.0000000000000M).ToString("R").Dump(); // 200
((double)200.00000000000000M).ToString("R").Dump(); // 200
((double)200.000000000000000M).ToString("R").Dump(); // 200
((double)200.0000000000000000M).ToString("R").Dump(); // 200
((double)200.00000000000000000M).ToString("R").Dump(); // 200
((double)200.000000000000000000M).ToString("R").Dump(); // 200
((double)200.0000000000000000000M).ToString("R").Dump(); // 200
((double)200.00000000000000000000M).ToString("R").Dump(); // 200
((double)200.000000000000000000000M).ToString("R").Dump(); // 199.99999999999997
((double)200.0000000000000000000000M).ToString("R").Dump(); // 200
((double)200.00000000000000000000000M).ToString("R").Dump(); // 200.00000000000003
((double)200.000000000000000000000000M).ToString("R").Dump(); // 200
((double)200.0000000000000000000000000M).ToString("R").Dump(); // 199.99999999999997
((double)200.00000000000000000000000000M).ToString("R").Dump(); // 199.99999999999997
"\nFixed\n".Dump();
const decimal PreciseOne = 1.000000000000000000000000000000000000000000000000M;
((double)(200M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.000000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.0000000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
((double)(200.00000000000000000000000000M/PreciseOne)).ToString("R").Dump(); // 200
This is an old problem, and has been the subject of many similar questions on StackOverflow.
The simplistic explanation is that decimal numbers can't be exactly represented in binary
This link is an article which might explain the problem.