I'm storing a number as a double. It works well with small numbers but if the double is 1000000 and I try to add 10 to it, it doesn't work but I can add 100 to it. If the double is 100000 and I try to add 1 to it, it doesn't work but I can add 10 to it.
Is this a problem with using a double? What format should I be using for up to a 9 digit number?
Edit: I'm doing calculations on the number and putting it in a 0.00 decimal format. It works on small numbers but not on big. It might have something to do with the other calculations. Just seeing if maybe double was the problem.
I run into problems when I take 1000001 / 100 and put in 0.00 decimal format. But 1000100 / 100 put into a 0.00 dec format works.
Not sure what you mean by "it doesn't work", considering that it should:
System.out.println(1000000d + 10d); // 1000010.0
Cases where it wouldn't work are where there is a value that is more than about 15 digits from the most significant digit of the largest double involved:
System.out.println(Math.pow(10, 18) + 10d - Math.pow(10, 18)); // 0.0
System.out.println(Math.pow(10, 17) + 10d - Math.pow(10, 17)); // 16.0
System.out.println(Math.pow(10, 16) + 10d - Math.pow(10, 16)); // 10.0
An int is absolutely large enough to store a 9-digit number, since the maximum value stored by a (signed) integer is 2^31 - 1 = 2,147,483,647 which has 10 digits.
If you need a larger range, use a long.
Java Tutorial: Primitive Data Types
Yes, this is how floating point works in general. (Although, as others pointed out, this should be well within the actual capabilities of double.) It loses more and more precision as the number is getting bigger. And even with small numbers, it isn't guaranteed to be precise. For small integers it is, as a general rule, but in practice, relying on the precision of floating point is a bad idea.
For integers, long should be good enough, 263-1 is the biggest number you can store in it.
Otherwise BigDecimal is the answer. Not very convenient, but it is precise.
Judging by the update to your question, you want to store prices or something similar. In that case, you can either use a library dedicated to currency arithmetic (as there are often weird rules of rounding involved for example), or store pennies/cents in a long.
A double is actually able to hold that result. The most likely thing is probably that you're inspecting/printing out the number in such a way that appears like the number isn't different (could you post your test code?).
As a general rule of thumb, doubles give you ~16 digits of precision, and floats give you ~8 digits of precision.
What kind of 9-digit number do you need to keep? A double should have enough precision track 9 significant digits as would an int, but you need to know which type of number you need before you choose a type. If you need real values (i.e., they have digits to the right of the decimal), then choose double. If they are integers, choose int.
I don't think your exact problem is very clear. Are you using integer arithmetic? In which case you should expect an integer division to round down the answer.
int i = 1000001 / 100;
System.out.println(i);
double d = (double) 1000001 / 100;
System.out.println(d);
prints as expected
10000
10000.01
However, since you have't given a clear example of what does work and what you expect to happen, we are just guessing what your problem might be.
Nevertheless, there is something wrong. It should be possible to (ab)use a double (which is in 64bit IEEE format in Java) as an 48-bit-or so integer. 48 bt should be enough to store 9 decimal digits.
Related
This question already has answers here:
Java float 123.129456 to 123.12 without rounding
(5 answers)
How to round a number to n decimal places in Java
(39 answers)
Closed 5 years ago.
Can I reduce the precision of a float number?
In all the searching I've been doing I saw only how to reduce the precision for printing the number. I do not need to print it.
I want, for example, to convert 13.2836 to 13.28. Without even rounding it.
Is it possible?
The suggested answer from the system is not what I am looking for. It also deals with printing the value and I want to have a float.
There isn't really a way to do it, with good reason. While john16384's answer alludes to this, his answer doesn't make the problem clear... so probably you'll try it, it won't do what you want, and perhaps you still won't know why...
The problem is that while we think in decimal and expect that the decimal point is controlled by a power-of-10 exponent, typical floating point implementations (including Java float) use a power-of-2 exponent. Why does it matter?
You know that to represent 1/3 in decimal you'd say 0.3(repeating) - so if you have a limited number of decimal digits, you can't really represent 1/3. When the exponent is 2 instead of 10, you can't really represent 1/5 either, or a lot of other numbers that you could represent exactly in decimal.
As it happens .28 is one of those numbers. So you could multiply by 100, pass the result to floor, and divide by 100, but when this gets converted back to a float, the resulting value will be a little different from .28 and so, if you then check its value, you'll still see more than 2 decimal places.
The solution would be to use something like BigDecimal that can exactly represent decimal values of a given precision.
The standard warnings about doing precision arithmetic with floats applies, but you can do this:
float f = 13.2836;
f = Math.floor(f * 100) / 100;
if you need to save memory in some part of your calculation, And your numbers are smaller than 2^15/100 (range short), you can do the following.
Part of this taken from this post https://stackoverflow.com/a/25201407/7256243.
float number = 1.2345667f;
number= (short)(100*number);
number=(float)(number/100);
You only need to rememeber that the short's are 100 times larger.
Most answers went straight to how do represent floats more accurately, which is strange because you're asking:
Can I reduce the precision of a float number
Which is the exact opposite. So I'll try to answer this.
However there are several way to "reduce precision":
Reduce precision to gain performance
Reduce memory footprint
Round / floor arbitrarily
Make the number more "fuzzy"
Reduce the number of digits after the coma
I'll tackle those separately.
Reduce precision to gain performance
Just to get it out of the way: simply because you're dropping precision off of your calculations on a float, doesn't mean it'll be any faster. Quite the contrary. This answer by #john16384:
f = Math.floor(f * 100) / 100;
Only adds up computation time. If you know the number of significant digits from the result is low, don't bother removing them, just carry that information with the number:
public class Number WithSignificantDigits {
private float value;
private int significantdigits;
(implement basic operations here, but don't floor/round anywhere)
}
If you're doing this because you're worried about performance: stop it now, just use the full precision. If not, read on.
Reduce memory footprint
To actually store a number with less precision, you need to move away from float.
One such representation is using an int with a fixed point convention (i.e. the last 2 digits are past the coma).
If you're trying to save on storage space, do this. If not, read on.
Round / floor arbitrarily
To keep using float, but drop its precision, several options exist:
#john16384 proposed:
`f = Math.floor(f * 100) / 100;`
Or even
f = ((int) (f*100)) / 100.;
If the answer is this, your question is a duplicate. If not, read on.
Make the number more "fuzzy"
Since you just want to lose precision, but haven't stated how much, you could do with bitwise shifts:
float v = 0;
int bits = Float.floatToIntBits(v);
bits = bits >> 7; // Precision lost here
float truncated = Float.intBitsToFloat(bits);
Use 7 bitshifts to reduce precision to nearest 1/128th (close enough to 1/100)
Use 10 bitshifts to reduce precision to nearest 1/1024th (close enough to 1/1000)
I haven't tested performance of those, but If your read this, you did not care.
If you want to lose precision, and you don't care about formatting (numbers may stil have a large number of digits after the coma, like 0,9765625 instead of 1), do this. If you care about formatting and want a limited number of digits after the coma, read on.
Reduce the number of digits after the coma
For this you can:
Follow #Mark Adelsberger's suggestion of BigDecimals, or
Store as a String (yuk)
Because floats or doubles won't let you do this in most cases.
I understand that due to the nature of a float/double one should not use them for precision important calculations. However, i'm a little confused on their limitations due to mixed answers on similar questions, whether or not floats and doubles will always be inaccurate regardless of significant digits or are only inaccurate up to the 16th digit.
I've ran a few examples in Java,
System.out.println(Double.parseDouble("999999.9999999999");
// this outputs correctly w/ 16 digits
System.out.println(Double.parseDouble("9.99999999999999");
// This also outputs correctly w/ 15 digits
System.out.println(Double.parseDouble("9.999999999999999");
// But this doesn't output correctly w/ 16 digits. Outputs 9.999999999999998
I can't find the link to another answer that stated that values like 1.98 and 2.02 would round down to 2.0 and therefore create inaccuracies but testing shows that the values are printed correctly. So my first question is whether or not floating/double values will always be inaccurate or is there a lower limit where you can be assured of precision.
My second question is in regards to using BigDecimal. I know that I should be using BigDecimal for precision important calculations. Therefore I should be using BigDecimal's methods for arithmetic and comparing. However, BigDecimal also includes a doubleValue() method which will convert the BigDecimal to a double. Would it be safe for me to do a comparison between double values that I know for sure have less than 16 digits? There will be no arithmetic done on them at all so the inherent values should not have changed.
For example, is it safe for me to do the following?
BigDecimal myDecimal = new BigDecimal("123.456");
BigDecimal myDecimal2 = new BigDecimal("234.567");
if (myDecimal.doubleValue() < myDecimal2.doubleValue()) System.out.println("myDecimal is smaller than myDecimal2");
Edit: After reading some of the responses to my own answer i've realized my understanding was incorrect and have deleted it. Here are some snippets from it that might help in the future.
"A double cannot hold 0.1 precisely. The closest representable value to 0.1 is 0.1000000000000000055511151231257827021181583404541015625. Java Double.toString only prints enough digits to uniquely identify the double, not the exact value." - Patricia Shanahan
Sources:
https://stackoverflow.com/a/5749978 - States that a double can hold up to 15 digits
I suggest you read this page:
https://en.wikipedia.org/wiki/Double-precision_floating-point_format
Once you've read and understood it, and perhaps converted several examples to their binary representations in the 64 bit floating point format, then you'll have a much better idea of what significant digits a Double can hold.
As a side note, (perhaps trivial) a nice and reliable way to store a known precision of value is to simply multiply it by the relevant factor and store as some integral type, which are completely precise.
For example:
double costInPounds = <something>; //e.g. 3.587
int costInPence = (int)(costInPounds * 100 + 0.5); //359
Plainly some precision can be lost, but if a required/desired precision is known, this can save a lot of bother with floating point values, and once this has been done, no precision can be lost by further manipulations.
The + 0.5 is to ensure that rounding works as expected. (int) takes the 'floor' of the provided double value, so adding 0.5 makes it round up and down as expected.
I am trying to affect the translation of a 3D model using some UI buttons to shift the position by 0.1 or -0.1.
My model position is a three dimensional float so simply adding 0.1f to one of the values causes obvious rounding errors. While I can use something like BigDecimal to retain precision, I still have to convert it from a float and back to a float at the end and it always results in silly numbers that are making my UI look like a mess.
I could just pretty the displayed values but the rounding errors will only get worse with more editing and they make my save files rather hard to read.
So how do I actually avoid these errors when I need to use a float?
The Kahan summation and pairwise summation algorithms help to reduce floating point errors. Here's some Java code for the Kahan algorithm.
I would use a Rational class. There are many out there - this one looks like it should work.
One significant cost will be when the Rational is rendered into a float and one when the denominator is reduced to the gcd. The one I posted keeps the numerator and denominator in fully reduced state at all times which should be quite efficient if you are always adding or subtracting 1/10.
This implementation holds the values normalised (i.e. with consistent sign) but unreduced.
You should choose your implementation to best fit your usage.
A simple solution is to either use fixed precision. i.e. an integer 10x or 100x what you want.
float f = 10;
f += 0.1f;
becomes
int i = 100;
i += 1; // use an many times as you like
// use i / 10.0 as required.
I wouldn't use float in any case as you get more rounding errors than double for next to no benefit (unless you have millions of float values) double gives you 8 more digits of precision and with sensible rounding would won't see those errors.
If you stick with floats:
The easiest way to avoid the error is using floats which are exact, but
near the desired value which is
round(2^n * value) * 1/2^n.
n is the number of bits, value the number to use (in your case 0.1)
In your case with increasing precision:
n = 4 => 0.125
n = 8 (byte) => 0.9765625
n = 16 (short)=> 0.100006103516....
The long number chains are artefacts of the binary conversion,
the real number has much less bits.
As the floats are exact, addition and subtraction will
not introduce offset errors, but will always be
predictable as long as the number of bits is
not longer than the float value holds.
If you fear that your display will be compromised by
using this solution (because they are odd floats), use
and store only integers (step increase -1/1).
The final value which is internally set is
x = value * step.
As the step increases or decreases by an amount of 1,
precision will be retained.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Retain precision with Doubles in java
Alright so I've got the following chunk of code:
int rotation = e.getWheelRotation();
if(rotation < 0)
zoom(zoom + rotation * -.05);
else if(zoom - .05 > 0)
zoom(zoom - rotation * .05);
System.out.println(zoom);
Now, the zoom variable is of type double, initially set to 1. So, I would expect the results to be like 1 - .05 = .95; .95 - .05 = .9; .9 - .05 = .85; etc. This appears to be not the case though when I print the result as you can see below:
0.95
0.8999999999999999
0.8499999999999999
0.7999999999999998
0.7499999999999998
0.6999999999999997
Hopefully someone is able to clearly explain. I searched the internet and I read it has something to do with some limitations when we're storing floats in binary but I still don't quite understand. A solution to my problem is not shockingly important but I would like to understand this kind of behavior.
Java uses IEEE-754 floating point numbers. They're not perfectly precise. The famous example is:
System.out.println(0.1d + 0.2d);
...which outputs 0.30000000000000004.
What you're seeing is just a symptom of that imprecision. You can improve the precision by using double rather than float.
If you're dealing with financial calculations, you might prefer BigDecimal to float or double.
float and double have limited precision because its fractional part is represented as a series of powers of 2 e.g. 1/2 + 1/4 + 1/8 ... If you have an number like 1/10 it has to be approximated.
For this reason, whenever you deal with floating point you must use reasonable rounding or you can see small errors.
e.g.
System.out.printf("%.2f%n", zoom);
To minimise round errors, you could count the number of rotations instead and divide this int value by 20.0. You won't see a rounding error this way, and it will be faster, with less magic numbers.
float and double have precision issues. I would recommend you take a look at the BigDecimal Class. That should take care of precision issues.
Since decimal numbers (and integer numbers as well) can have an infinite number of possible values, they are impossible to map precisely to bits using a standard format. Computers circumvent this problem by limiting the range the numbers can assume.
For example, an int in java can represent nothing larger then Integer.MAX_VALUE or 2^31 - 1.
For decimal numbers, there is also a problem with the numbers after the comma, which also might be infinite. This is solved by not allowing all decimal values, but limiting to a (smartly chosen) number of possibilities, based on powers of 2. This happens automatically but is often nothing to worry about, you can interpret your result of 0.899999 as 0.9. In case you do need explicit precision, you will have to resort to other data types, which might have other limitations.
I'm wondering what the best way to fix precision errors is in Java. As you can see in the following example, there are precision errors:
class FloatTest
{
public static void main(String[] args)
{
Float number1 = 1.89f;
for(int i = 11; i < 800; i*=2)
{
System.out.println("loop value: " + i);
System.out.println(i*number1);
System.out.println("");
}
}
}
The result displayed is:
loop value: 11
20.789999
loop value: 22
41.579998
loop value: 44
83.159996
loop value: 88
166.31999
loop value: 176
332.63998
loop value: 352
665.27997
loop value: 704
1330.5599
Also, if someone can explain why it only does it starting at 11 and doubling the value every time. I think all other values (or many of them at least) displayed the correct result.
Problems like this have caused me headache in the past and I usually use number formatters or put them into a String.
Edit: As people have mentioned, I could use a double, but after trying it, it seems that 1.89 as a double times 792 still outputs an error (the output is 1496.8799999999999).
I guess I'll try the other solutions such as BigDecimal
If you really care about precision, you should use BigDecimal
https://docs.oracle.com/javase/8/docs/api/java/math/BigDecimal.html
https://docs.oracle.com/en/java/javase/11/docs/api/java.base/java/math/BigDecimal.html
The problem is not with Java but with the good standard float's (http://en.wikipedia.org/wiki/IEEE_floating-point_standard).
You can either:
use Double and have a bit more precision (but not perfect of course, it also has limited precision)
use a arbitrary-precision-library
use numerically stable algorithms and truncate/round digits of which you are not sure they are correct (you can calculate numeric precision of operations)
When you print the result of a double operation you need to use appropriate rounding.
System.out.printf("%.2f%n", 1.89 * 792);
prints
1496.88
If you want to round the result to a precision, you can use rounding.
double d = 1.89 * 792;
d = Math.round(d * 100) / 100.0;
System.out.println(d);
prints
1496.88
However if you see below, this prints as expected, as there is a small amount of implied rounding.
It worth nothing that (double) 1.89 is not exactly 1.89 It is a close approximation.
new BigDecimal(double) converts the exact value of double without any implied rounding. It can be useful in finding the exact value of a double.
System.out.println(new BigDecimal(1.89));
System.out.println(new BigDecimal(1496.88));
prints
1.8899999999999999023003738329862244427204132080078125
1496.8800000000001091393642127513885498046875
Most of your question has been pretty well covered, though you might still benefit from reading the [floating-point] tag wiki to understand why the other answers work.
However, nobody has addressed "why it only does it starting at 11 and doubling the value every time," so here's the answer to that:
for(int i = 11; i < 800; i*=2)
╚═══╤════╝ ╚╤═╝
│ └───── "double the value every time"
│
└───── "start at 11"
You could use doubles instead of floats
If you really need arbitrary precision, use BigDecimal.
first of Float is the wrapper class for the primitive float
and doubles have more precision
but if you only want to calculate down to the second digit (for monetary purposes for example) use an integer (as if you are using cents as unit) and add some scaling logic when you are multiplying/dividing
or if you need arbitrary precision use BigDecimal
If precision is vital, you should use BigDecimal to make sure that the required precision remains. When you instantiate the calculation, remember to use strings to instantiate the values instead of doubles.
I never had a problem with simple arithmetic precision in either Basic, Visual Basic, FORTRAN, ALGOL or other "primitive" languages. It is beyond comprehension that JAVA can't do simple arithmetic without introducing errors. I need just two digits to the right of the decimal point for doing some accounting. Using Float subtracting 1000 from 1355.65 I get 355.650002! In order to get around this ridiculous error I have implemented a simple solution. I process my input by separating the values on each side of the decimal point as character, convert each to integers, multiply each by 1000 and add the two back together as integers. Ridiculous but there are no errors introduced by the poor JAVA algorithms.