1.265 * 10000 = 126499.99999999999? [duplicate] - javascript

This question already has answers here:
Why does floating-point arithmetic not give exact results when adding decimal fractions?
(31 answers)
Closed 6 years ago.
When I multiply 1.265 by 10000 , I get 126499.99999999999 when using Javascript.
Why is this so?

Floating point numbers can't handle decimals correctly in all cases. Check out
http://en.wikipedia.org/wiki/Floating-point_number#Accuracy_problems
http://www.mredkj.com/javascript/nfbasic2.html

You should be aware that all information in computers is in binary and the expansions of fractions in different bases vary.
For instance 1/3 in base 10= .33333333333333333333333333, while 1/3 in base 3 is equal to .1 and in base 2 is equal to .0101010101010101.
In case you don't have a complete understanding of how different bases work, here's an example:
The base 4 number 301.12. would be equal to 3 * 4^2 + 0 * 4^1 + 1 * 4^0 + 1 * 4^-1 + 2 *4^-2= 3 * 4^2 +1+ 1 * 4^-1 + 2 * 4^-2=49.375 in base 10.
Now the problems with accuracy in floating point comes from a limited number of bits in the significand. Floating point numbers have 3 parts to them, a sign bit, exponent and mantissa, most likely javascript uses 32 or 64 bit IEEE 754 floating point standard. For simpler calculations we'll use 32 bit, so 1.265 in floating point would be
Sign bit of 0 (0 for positive , 1 for negative) exponent of 0 (which with a 127 offset would be, ie exponent+offset, so 127 in unsigned binary) 01111111 (then finally we have the signifcand of 1.265, ieee floating point standard makes use of a hidden 1 representation so our binary represetnation of 1.265 is 1.01000011110101110000101, ignoring the 1:) 01000011110101110000101.
So our final IEEE 754 single (32-bit) representation of 1.625 is:
Sign Bit(+) Exponent (0) Mantissa (1.625)
0 01111111 01000011110101110000101
Now 1000 would be:
Sign Bit (+) Exponent(9) Mantissa(1000)
0 10001000 11110100000000000000000
Now we have to multiply these two numbers. Floating point multiplication consists of re-adding the hidden 1 to both mantissas, multiplying the two mantissa, subtracting the offset from the two exponents and then adding th two exponents together. After this the mantissa has to be normalized again.
First 1.01000011110101110000101*1.11110100000000000000000=10.0111100001111111111111111000100000000000000000
(this multiplication is a pain)
Now obviously we have an exponent of 9 + an exponent of 0 so we keep 10001000 as our exponent, and our sign bit remains, so all that is left is normalization.
We need our mantissa to be of the form 1.000000, so we have to shift it right once which also means we have to increment our exponent bringing us up to 10001001, now that our mantissa is normalized to 1.00111100001111111111111111000100000000000000000. It must be truncated to 23 bits so we are left with 1.00111100001111111111111 (not including the 1, because it will be hidden in our final representation) so our final answer that we are left with is
Sign Bit (+) Exponent(10) Mantissa
0 10001001 00111100001111111111111
Finally if we conver this answer back to decimal we get (+) 2^10 * (1+ 2^-3 + 2^-4 +2^-5+2^-6+2^-11+2^-12+2^-13+2^-14+2^-15+2^-16+2^-17+2^-18+2^-19+2^-20+2^-21+2^-22+2^-23)=1264.99987792
While I did simplify the problem multiplying 1000 by 1.265 instead of 10000 and using single floating point, instead of double, the concept stays the same. You use lose accuracy because the floating point representation only has so many bits in the mantissa with which to represent any given number.
Hope this helps.

It's a result of floating point representation error. Not all numbers that have finite decimal representation have a finite binary floating point representation.

Have a read of this article. Essentially, computers and floating-point numbers do not go together perfectly!

On the other hand, 126500 IS equal to 126499.99999999.... :)
Just like 1 is equal to 0.99999999....
Because 1 = 3 * 1/3 = 3 * 0.333333... = 0.99999999....

Purely due to the inaccuracies of floating point representation.
You could try using Math.round:
var x = Math.round(1.265 * 10000);

These small errors are usually caused by the precision of the floating points as used by the language. See this wikipedia page for more information about the accuracy problems of floating points.

Here's a way to overcome your problem, although arguably not very pretty:
var correct = parseFloat((1.265*10000).toFixed(3));
// Here's a breakdown of the line of code:
var result = (1.265*10000);
var rounded = result.toFixed(3); // Gives a string representation with three decimals
var correct = parseFloat(rounded); // Convert string into a float
// (doesn't show decimals)

If you need a solution, stop using floats or doubles and start using BigDecimal.
Check the BigDecimal implementation stz-ida.de/html/oss/js_bigdecimal.html.en

Even additions on the MS JScript engine :
WScript.Echo(1083.6-1023.6) give 59.9999999

Related

Adding integer numbers javascript, double float [duplicate]

This question already has answers here:
Floating point representations seem to do integer arithmetic correctly - why?
(8 answers)
Closed 5 years ago.
So I have read this answer here:
Is floating point math broken?
That because every number in JS is double float 0.1+0.2 for example will NOT equal to 0.3.
But I don't understand why it never happens with integers? Why then 1+2 always equals 3 etc. It would seem that integers like 1 or 2 similarly to 0.1 and 0.2 don't have perfect representation in the binary64 so their math should also sometimes break but that never happens.
Why is that?
but I don't understand why it never happens with integers?
It does, the integer just has to be really big before they hit the limits of the IEEE-754 format:
var a = 9007199254740992;
console.log(a); // 9007199254740992
var b = a + 1;
console.log(b); // still 9007199254740992
console.log(a == b); // true
Floating point formats, such as IEEE-754 are essentially an expression that describes the value as the following:
value := sign * mantissa * 2 ^ exponent
The mantissa is an integer of various sizes. For four byte floating point, the mantissa is 24 bits and, for eight byte floating point, the mantissa is 48 bits. If the exponent is 0, the value of the expression is determined only by the sign and the mantissa. This is, in fact, how integers are represented by JavaScript.
What seems to take most people by surprise is due to the base 2 exponent instead of base 10. We accept, that, in base 10, the result of 1/3 or 2/3 cannot be exactly represented without an infinite number of digits or the acceptance of round-off error. Similarly, there are fractions in base 2 that have similar issues. Unfortunately for our base 10 mindset, these fractions most often involve negative powers of 10.

JavaScript number automatically "rounded" [duplicate]

See this code:
var jsonString = '{"id":714341252076979033,"type":"FUZZY"}';
var jsonParsed = JSON.parse(jsonString);
console.log(jsonString, jsonParsed);
When I see my console in Firefox 3.5, the value of jsonParsed is the number rounded:
Object id=714341252076979100 type=FUZZY
Tried different values, the same outcome (number rounded).
I also don't get its rounding rules. 714341252076979136 is rounded to 714341252076979200, whereas 714341252076979135 is rounded to 714341252076979100.
Why is this happening?
You're overflowing the capacity of JavaScript's number type, see §8.5 of the spec for details. Those IDs will need to be strings.
IEEE-754 double-precision floating point (the kind of number JavaScript uses) can't precisely represent all numbers (of course). Famously, 0.1 + 0.2 == 0.3 is false. That can affect whole numbers just like it affects fractional numbers; it starts once you get above 9,007,199,254,740,991 (Number.MAX_SAFE_INTEGER).
Beyond Number.MAX_SAFE_INTEGER + 1 (9007199254740992), the IEEE-754 floating-point format can no longer represent every consecutive integer. 9007199254740991 + 1 is 9007199254740992, but 9007199254740992 + 1 is also 9007199254740992 because 9007199254740993 cannot be represented in the format. The next that can be is 9007199254740994. Then 9007199254740995 can't be, but 9007199254740996 can.
The reason is we've run out of bits, so we no longer have a 1s bit; the lowest-order bit now represents multiples of 2. Eventually, if we keep going, we lose that bit and only work in multiples of 4. And so on.
Your values are well above that threshold, and so they get rounded to the nearest representable value.
As of ES2020, you can use BigInt for integers that are arbitrarily large, but there is no JSON representation for them. You could use strings and a reviver function:
const jsonString = '{"id":"714341252076979033","type":"FUZZY"}';
// Note it's a string −−−−^−−−−−−−−−−−−−−−−−−^
const obj = JSON.parse(jsonString, (key, value) => {
if (key === "id" && typeof value === "string" && value.match(/^\d+$/)) {
return BigInt(value);
}
return value;
});
console.log(obj);
(Look in the real console, the snippets console doesn't understand BigInt.)
If you're curious about the bits, here's what happens: An IEEE-754 binary double-precision floating-point number has a sign bit, 11 bits of exponent (which defines the overall scale of the number, as a power of 2 [because this is a binary format]), and 52 bits of significand (but the format is so clever it gets 53 bits of precision out of those 52 bits). How the exponent is used is complicated (described here), but in very vague terms, if we add one to the exponent, the value of the significand is doubled, since the exponent is used for powers of 2 (again, caveat there, it's not direct, there's cleverness in there).
So let's look at the value 9007199254740991 (aka, Number.MAX_SAFE_INTEGER):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110011 1111111111111111111111111111111111111111111111111111
= 9007199254740991 (Number.MAX_SAFE_INTEGER)
That exponent value, 10000110011, means that every time we add one to the significand, the number represented goes up by 1 (the whole number 1, we lost the ability to represent fractional numbers much earlier).
But now that significand is full. To go past that number, we have to increase the exponent, which means that if we add one to the significand, the value of the number represented goes up by 2, not 1 (because the exponent is applied to 2, the base of this binary floating point number):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000000
= 9007199254740992 (Number.MAX_SAFE_INTEGER + 1)
Well, that's okay, because 9007199254740991 + 1 is 9007199254740992 anyway. But! We can't represent 9007199254740993. We've run out of bits. If we add just 1 to the significand, it adds 2 to the value:
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000001
= 9007199254740994 (Number.MAX_SAFE_INTEGER + 3)
The format just cannot represent odd numbers anymore as we increase the value, the exponent is too big.
Eventually, we run out of significand bits again and have to increase the exponent, so we end up only being able to represent multiples of 4. Then multiples of 8. Then multiples of 16. And so on.
What you're seeing here is actually the effect of two roundings. Numbers in ECMAScript are internally represented double-precision floating-point. When id is set to 714341252076979033 (0x9e9d9958274c359 in hex), it actually is assigned the nearest representable double-precision value, which is 714341252076979072 (0x9e9d9958274c380). When you print out the value, it is being rounded to 15 significant decimal digits, which gives 14341252076979100.
It is not caused by this json parser. Just try to enter 714341252076979033 to fbug's console. You'll see the same 714341252076979100.
See this blog post for details:
http://www.exploringbinary.com/print-precision-of-floating-point-integers-varies-too
JavaScript uses double precision floating point values, ie a total precision of 53 bits, but you need
ceil(lb 714341252076979033) = 60
bits to exactly represent the value.
The nearest exactly representable number is 714341252076979072 (write the original number in binary, replace the last 7 digits with 0 and round up because the highest replaced digit was 1).
You'll get 714341252076979100 instead of this number because ToString() as described by ECMA-262, §9.8.1 works with powers of ten and in 53 bit precision all these numbers are equal.
The problem is that your number requires a greater precision than JavaScript has.
Can you send the number as a string? Separated in two parts?
JavaScript can only handle exact whole numbers up to about 9000 million million (that's 9 with 15 zeros). Higher than that and you get garbage. Work around this by using strings to hold the numbers. If you need to do math with these numbers, write your own functions or see if you can find a library for them: I suggest the former as I don't like the libraries I've seen. To get you started, see two of my functions at another answer.

JavaScript Highest Representable Number

This question asks about the highest number in JavaScript without losing precision. Here, I ask about the highest representable number in JavaScript. Some answers to the other question reference the answer to this question, but they do not answer that question, so I hope I am safe asking here.
I tried to find the answer, but I got lost halfway through. The highest number representable in JavaScript seems to be somewhere between 2^1023 and 2^1024. I went further (in the iojs REPL) with
var highest = Math.pow(2, 1023);
for(let i = 1022; i > someNumber; i--) {
highest += Math.pow(2, someNumber);
}
The highest number here seems to be when someNumber is between 969 and 970. This means it is between (2^1023 + 2^1022 + ... + 2^970) and (2^1023 + 2^1022 + ... + 2^969). I'm not sure how to go further without running out of memory and/or waiting years for a loop or function to finish.
What is the highest number representable in JavaScript? Does JavaScript store all digits of this number, or just some, because whenever I see numbers of 10^21 or higher they are represented in scientific notation? Why can JavaScript represent these extremely high numbers, especially if it can "remember" all the digits? Isn't JavaScript a base 64 language?
Finally, why is this the highest representable number? I am asking because it is not an integer exponent of 2. Is it because it is a floating point number? If we took the highest floating point number, would that be related to some exponent of 2?
ECMAScript uses IEEE 754 floating points to represent all numbers (integers and floating points) in memory. It uses double precision (64 bit), so the largest possible number would be the following (in binary):
(-1)^0 * (1.1111111111111111111111111111111111111111111111111111)_2 * 2^1023
^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^
sign bit 52 binary digits exponent
That is 1.9999999999999997779553950749686919152736663818359375 * 2^1023, which is exactly equal to 179769313486231570814527423734518473246981451219193357160576872808257310254570927992989173324623785766498017753719800531497718555288192667185248845624861831489179706103179456665410545164365169396987674822445002542175370097858557402467390846365155202987281348776667818932226328810501776426180817703854493120592.218308495538871112145305600. That number is also available in JavaScript as Number.MAX_VALUE.
JavaScript uses IEE 754 double-precision floating point numbers, aka the binary64. This format has 1 sign bit, 11 bits of exponent, and 52 bits of mantissa.
The highest possible number is that which is encoded using the highest possible exponents and mantissa, with a 0 sign bit. Except that the exponent value of 7ff (base 16) is used to encode Infinity and NaNs. The largest number is therefore encoded as 7fef ffff ffff ffff, and its value is (1 + (1 − 2^(−52))) × 2^1023.
Refer to the linked article for further details about the formula.

Javascript number conversion [duplicate]

See this code:
var jsonString = '{"id":714341252076979033,"type":"FUZZY"}';
var jsonParsed = JSON.parse(jsonString);
console.log(jsonString, jsonParsed);
When I see my console in Firefox 3.5, the value of jsonParsed is the number rounded:
Object id=714341252076979100 type=FUZZY
Tried different values, the same outcome (number rounded).
I also don't get its rounding rules. 714341252076979136 is rounded to 714341252076979200, whereas 714341252076979135 is rounded to 714341252076979100.
Why is this happening?
You're overflowing the capacity of JavaScript's number type, see §8.5 of the spec for details. Those IDs will need to be strings.
IEEE-754 double-precision floating point (the kind of number JavaScript uses) can't precisely represent all numbers (of course). Famously, 0.1 + 0.2 == 0.3 is false. That can affect whole numbers just like it affects fractional numbers; it starts once you get above 9,007,199,254,740,991 (Number.MAX_SAFE_INTEGER).
Beyond Number.MAX_SAFE_INTEGER + 1 (9007199254740992), the IEEE-754 floating-point format can no longer represent every consecutive integer. 9007199254740991 + 1 is 9007199254740992, but 9007199254740992 + 1 is also 9007199254740992 because 9007199254740993 cannot be represented in the format. The next that can be is 9007199254740994. Then 9007199254740995 can't be, but 9007199254740996 can.
The reason is we've run out of bits, so we no longer have a 1s bit; the lowest-order bit now represents multiples of 2. Eventually, if we keep going, we lose that bit and only work in multiples of 4. And so on.
Your values are well above that threshold, and so they get rounded to the nearest representable value.
As of ES2020, you can use BigInt for integers that are arbitrarily large, but there is no JSON representation for them. You could use strings and a reviver function:
const jsonString = '{"id":"714341252076979033","type":"FUZZY"}';
// Note it's a string −−−−^−−−−−−−−−−−−−−−−−−^
const obj = JSON.parse(jsonString, (key, value) => {
if (key === "id" && typeof value === "string" && value.match(/^\d+$/)) {
return BigInt(value);
}
return value;
});
console.log(obj);
(Look in the real console, the snippets console doesn't understand BigInt.)
If you're curious about the bits, here's what happens: An IEEE-754 binary double-precision floating-point number has a sign bit, 11 bits of exponent (which defines the overall scale of the number, as a power of 2 [because this is a binary format]), and 52 bits of significand (but the format is so clever it gets 53 bits of precision out of those 52 bits). How the exponent is used is complicated (described here), but in very vague terms, if we add one to the exponent, the value of the significand is doubled, since the exponent is used for powers of 2 (again, caveat there, it's not direct, there's cleverness in there).
So let's look at the value 9007199254740991 (aka, Number.MAX_SAFE_INTEGER):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110011 1111111111111111111111111111111111111111111111111111
= 9007199254740991 (Number.MAX_SAFE_INTEGER)
That exponent value, 10000110011, means that every time we add one to the significand, the number represented goes up by 1 (the whole number 1, we lost the ability to represent fractional numbers much earlier).
But now that significand is full. To go past that number, we have to increase the exponent, which means that if we add one to the significand, the value of the number represented goes up by 2, not 1 (because the exponent is applied to 2, the base of this binary floating point number):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000000
= 9007199254740992 (Number.MAX_SAFE_INTEGER + 1)
Well, that's okay, because 9007199254740991 + 1 is 9007199254740992 anyway. But! We can't represent 9007199254740993. We've run out of bits. If we add just 1 to the significand, it adds 2 to the value:
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000001
= 9007199254740994 (Number.MAX_SAFE_INTEGER + 3)
The format just cannot represent odd numbers anymore as we increase the value, the exponent is too big.
Eventually, we run out of significand bits again and have to increase the exponent, so we end up only being able to represent multiples of 4. Then multiples of 8. Then multiples of 16. And so on.
What you're seeing here is actually the effect of two roundings. Numbers in ECMAScript are internally represented double-precision floating-point. When id is set to 714341252076979033 (0x9e9d9958274c359 in hex), it actually is assigned the nearest representable double-precision value, which is 714341252076979072 (0x9e9d9958274c380). When you print out the value, it is being rounded to 15 significant decimal digits, which gives 14341252076979100.
It is not caused by this json parser. Just try to enter 714341252076979033 to fbug's console. You'll see the same 714341252076979100.
See this blog post for details:
http://www.exploringbinary.com/print-precision-of-floating-point-integers-varies-too
JavaScript uses double precision floating point values, ie a total precision of 53 bits, but you need
ceil(lb 714341252076979033) = 60
bits to exactly represent the value.
The nearest exactly representable number is 714341252076979072 (write the original number in binary, replace the last 7 digits with 0 and round up because the highest replaced digit was 1).
You'll get 714341252076979100 instead of this number because ToString() as described by ECMA-262, §9.8.1 works with powers of ten and in 53 bit precision all these numbers are equal.
The problem is that your number requires a greater precision than JavaScript has.
Can you send the number as a string? Separated in two parts?
JavaScript can only handle exact whole numbers up to about 9000 million million (that's 9 with 15 zeros). Higher than that and you get garbage. Work around this by using strings to hold the numbers. If you need to do math with these numbers, write your own functions or see if you can find a library for them: I suggest the former as I don't like the libraries I've seen. To get you started, see two of my functions at another answer.

Large numbers erroneously rounded in JavaScript

See this code:
var jsonString = '{"id":714341252076979033,"type":"FUZZY"}';
var jsonParsed = JSON.parse(jsonString);
console.log(jsonString, jsonParsed);
When I see my console in Firefox 3.5, the value of jsonParsed is the number rounded:
Object id=714341252076979100 type=FUZZY
Tried different values, the same outcome (number rounded).
I also don't get its rounding rules. 714341252076979136 is rounded to 714341252076979200, whereas 714341252076979135 is rounded to 714341252076979100.
Why is this happening?
You're overflowing the capacity of JavaScript's number type, see §8.5 of the spec for details. Those IDs will need to be strings.
IEEE-754 double-precision floating point (the kind of number JavaScript uses) can't precisely represent all numbers (of course). Famously, 0.1 + 0.2 == 0.3 is false. That can affect whole numbers just like it affects fractional numbers; it starts once you get above 9,007,199,254,740,991 (Number.MAX_SAFE_INTEGER).
Beyond Number.MAX_SAFE_INTEGER + 1 (9007199254740992), the IEEE-754 floating-point format can no longer represent every consecutive integer. 9007199254740991 + 1 is 9007199254740992, but 9007199254740992 + 1 is also 9007199254740992 because 9007199254740993 cannot be represented in the format. The next that can be is 9007199254740994. Then 9007199254740995 can't be, but 9007199254740996 can.
The reason is we've run out of bits, so we no longer have a 1s bit; the lowest-order bit now represents multiples of 2. Eventually, if we keep going, we lose that bit and only work in multiples of 4. And so on.
Your values are well above that threshold, and so they get rounded to the nearest representable value.
As of ES2020, you can use BigInt for integers that are arbitrarily large, but there is no JSON representation for them. You could use strings and a reviver function:
const jsonString = '{"id":"714341252076979033","type":"FUZZY"}';
// Note it's a string −−−−^−−−−−−−−−−−−−−−−−−^
const obj = JSON.parse(jsonString, (key, value) => {
if (key === "id" && typeof value === "string" && value.match(/^\d+$/)) {
return BigInt(value);
}
return value;
});
console.log(obj);
(Look in the real console, the snippets console doesn't understand BigInt.)
If you're curious about the bits, here's what happens: An IEEE-754 binary double-precision floating-point number has a sign bit, 11 bits of exponent (which defines the overall scale of the number, as a power of 2 [because this is a binary format]), and 52 bits of significand (but the format is so clever it gets 53 bits of precision out of those 52 bits). How the exponent is used is complicated (described here), but in very vague terms, if we add one to the exponent, the value of the significand is doubled, since the exponent is used for powers of 2 (again, caveat there, it's not direct, there's cleverness in there).
So let's look at the value 9007199254740991 (aka, Number.MAX_SAFE_INTEGER):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110011 1111111111111111111111111111111111111111111111111111
= 9007199254740991 (Number.MAX_SAFE_INTEGER)
That exponent value, 10000110011, means that every time we add one to the significand, the number represented goes up by 1 (the whole number 1, we lost the ability to represent fractional numbers much earlier).
But now that significand is full. To go past that number, we have to increase the exponent, which means that if we add one to the significand, the value of the number represented goes up by 2, not 1 (because the exponent is applied to 2, the base of this binary floating point number):
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000000
= 9007199254740992 (Number.MAX_SAFE_INTEGER + 1)
Well, that's okay, because 9007199254740991 + 1 is 9007199254740992 anyway. But! We can't represent 9007199254740993. We've run out of bits. If we add just 1 to the significand, it adds 2 to the value:
+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− sign bit
/ +−−−−−−−+−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− exponent
/ / | +−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−+− significand
/ / | / |
0 10000110100 0000000000000000000000000000000000000000000000000001
= 9007199254740994 (Number.MAX_SAFE_INTEGER + 3)
The format just cannot represent odd numbers anymore as we increase the value, the exponent is too big.
Eventually, we run out of significand bits again and have to increase the exponent, so we end up only being able to represent multiples of 4. Then multiples of 8. Then multiples of 16. And so on.
What you're seeing here is actually the effect of two roundings. Numbers in ECMAScript are internally represented double-precision floating-point. When id is set to 714341252076979033 (0x9e9d9958274c359 in hex), it actually is assigned the nearest representable double-precision value, which is 714341252076979072 (0x9e9d9958274c380). When you print out the value, it is being rounded to 15 significant decimal digits, which gives 14341252076979100.
It is not caused by this json parser. Just try to enter 714341252076979033 to fbug's console. You'll see the same 714341252076979100.
See this blog post for details:
http://www.exploringbinary.com/print-precision-of-floating-point-integers-varies-too
JavaScript uses double precision floating point values, ie a total precision of 53 bits, but you need
ceil(lb 714341252076979033) = 60
bits to exactly represent the value.
The nearest exactly representable number is 714341252076979072 (write the original number in binary, replace the last 7 digits with 0 and round up because the highest replaced digit was 1).
You'll get 714341252076979100 instead of this number because ToString() as described by ECMA-262, §9.8.1 works with powers of ten and in 53 bit precision all these numbers are equal.
The problem is that your number requires a greater precision than JavaScript has.
Can you send the number as a string? Separated in two parts?
JavaScript can only handle exact whole numbers up to about 9000 million million (that's 9 with 15 zeros). Higher than that and you get garbage. Work around this by using strings to hold the numbers. If you need to do math with these numbers, write your own functions or see if you can find a library for them: I suggest the former as I don't like the libraries I've seen. To get you started, see two of my functions at another answer.

Categories