Using this snippet:
public static void main(String[] args){
int i = XXX;
System.out.println( (int) ( (float) i ) );
}
If int i = 1234; then the output is 1234
If int i = Integer.MAX_VALUE; then the output is equal to Integer.MAX_VALUE
However, if int i = 1234567990;, then the output is 1234567936, which is not equal to i.
And if int i = 1235567990;, then the output is 1235568000, which is also not equal to i.
How does this casting conversion math work?
This is entirely normal for floating point maths. Both int and float are 32-bit values. float only has about 7 significant digits of precision, because it uses some of the bits for scale. As you get to large values, "adjacent" float values (i.e. going from one precisely-representable value to the next one up) are more than 1 apart - so any integer between those two adjacent values can't be represented precisely as a float.
Another way of looking at this is a version of the pigeonhole principle:
Both float and int have 2^32 possible bit patterns
There's a valid mapping from every int to a float value
Every bit pattern is a valid int, so there are 2^32 possible integer values
float also contains the value 1.5 (and many other non-integers, but we only need one of them to prove the point)
Therefore at least two int values must map to the same float, which means the mapping cannot be reversible in every case
Note that if you use double, you're fine - every int can be cast to double and then cast back to int, and you'll get the original value. However, using double and long (instead of int) you get the same problem, for the same reason, but using 64 bits instead of 32.
How does this casting conversion math work?
Casting an int to a float works the same way any float operation works: Do the math (which in this case is nothing - just take the int as is), then convert it to the 'nearest representable float' - that float which is closer to the result of the calculation than any other.
Why is it 'lossy'? See the other answer.
What's the math behind which floats are representable? Wikipedia's page on IEEE754 floating point representation explains that.
public class doublePrecision {
public static void main(String[] args) {
double total = 0;
total += 5.6;
total += 5.8;
System.out.println(total);
}
}
The above code prints:
11.399999999999
How would I get this to just print (or be able to use it as) 11.4?
As others have mentioned, you'll probably want to use the BigDecimal class, if you want to have an exact representation of 11.4.
Now, a little explanation into why this is happening:
The float and double primitive types in Java are floating point numbers, where the number is stored as a binary representation of a fraction and a exponent.
More specifically, a double-precision floating point value such as the double type is a 64-bit value, where:
1 bit denotes the sign (positive or negative).
11 bits for the exponent.
52 bits for the significant digits (the fractional part as a binary).
These parts are combined to produce a double representation of a value.
(Source: Wikipedia: Double precision)
For a detailed description of how floating point values are handled in Java, see the Section 4.2.3: Floating-Point Types, Formats, and Values of the Java Language Specification.
The byte, char, int, long types are fixed-point numbers, which are exact representions of numbers. Unlike fixed point numbers, floating point numbers will some times (safe to assume "most of the time") not be able to return an exact representation of a number. This is the reason why you end up with 11.399999999999 as the result of 5.6 + 5.8.
When requiring a value that is exact, such as 1.5 or 150.1005, you'll want to use one of the fixed-point types, which will be able to represent the number exactly.
As has been mentioned several times already, Java has a BigDecimal class which will handle very large numbers and very small numbers.
From the Java API Reference for the BigDecimal class:
Immutable,
arbitrary-precision signed decimal
numbers. A BigDecimal consists of an
arbitrary precision integer unscaled
value and a 32-bit integer scale. If
zero or positive, the scale is the
number of digits to the right of the
decimal point. If negative, the
unscaled value of the number is
multiplied by ten to the power of the
negation of the scale. The value of
the number represented by the
BigDecimal is therefore (unscaledValue
× 10^-scale).
There has been many questions on Stack Overflow relating to the matter of floating point numbers and its precision. Here is a list of related questions that may be of interest:
Why do I see a double variable initialized to some value like 21.4 as 21.399999618530273?
How to print really big numbers in C++
How is floating point stored? When does it matter?
Use Float or Decimal for Accounting Application Dollar Amount?
If you really want to get down to the nitty gritty details of floating point numbers, take a look at What Every Computer Scientist Should Know About Floating-Point Arithmetic.
When you input a double number, for example, 33.33333333333333, the value you get is actually the closest representable double-precision value, which is exactly:
33.3333333333333285963817615993320941925048828125
Dividing that by 100 gives:
0.333333333333333285963817615993320941925048828125
which also isn't representable as a double-precision number, so again it is rounded to the nearest representable value, which is exactly:
0.3333333333333332593184650249895639717578887939453125
When you print this value out, it gets rounded yet again to 17 decimal digits, giving:
0.33333333333333326
If you just want to process values as fractions, you can create a Fraction class which holds a numerator and denominator field.
Write methods for add, subtract, multiply and divide as well as a toDouble method. This way you can avoid floats during calculations.
EDIT: Quick implementation,
public class Fraction {
private int numerator;
private int denominator;
public Fraction(int n, int d){
numerator = n;
denominator = d;
}
public double toDouble(){
return ((double)numerator)/((double)denominator);
}
public static Fraction add(Fraction a, Fraction b){
if(a.denominator != b.denominator){
double aTop = b.denominator * a.numerator;
double bTop = a.denominator * b.numerator;
return new Fraction(aTop + bTop, a.denominator * b.denominator);
}
else{
return new Fraction(a.numerator + b.numerator, a.denominator);
}
}
public static Fraction divide(Fraction a, Fraction b){
return new Fraction(a.numerator * b.denominator, a.denominator * b.numerator);
}
public static Fraction multiply(Fraction a, Fraction b){
return new Fraction(a.numerator * b.numerator, a.denominator * b.denominator);
}
public static Fraction subtract(Fraction a, Fraction b){
if(a.denominator != b.denominator){
double aTop = b.denominator * a.numerator;
double bTop = a.denominator * b.numerator;
return new Fraction(aTop-bTop, a.denominator*b.denominator);
}
else{
return new Fraction(a.numerator - b.numerator, a.denominator);
}
}
}
Observe that you'd have the same problem if you used limited-precision decimal arithmetic, and wanted to deal with 1/3: 0.333333333 * 3 is 0.999999999, not 1.00000000.
Unfortunately, 5.6, 5.8 and 11.4 just aren't round numbers in binary, because they involve fifths. So the float representation of them isn't exact, just as 0.3333 isn't exactly 1/3.
If all the numbers you use are non-recurring decimals, and you want exact results, use BigDecimal. Or as others have said, if your values are like money in the sense that they're all a multiple of 0.01, or 0.001, or something, then multiply everything by a fixed power of 10 and use int or long (addition and subtraction are trivial: watch out for multiplication).
However, if you are happy with binary for the calculation, but you just want to print things out in a slightly friendlier format, try java.util.Formatter or String.format. In the format string specify a precision less than the full precision of a double. To 10 significant figures, say, 11.399999999999 is 11.4, so the result will be almost as accurate and more human-readable in cases where the binary result is very close to a value requiring only a few decimal places.
The precision to specify depends a bit on how much maths you've done with your numbers - in general the more you do, the more error will accumulate, but some algorithms accumulate it much faster than others (they're called "unstable" as opposed to "stable" with respect to rounding errors). If all you're doing is adding a few values, then I'd guess that dropping just one decimal place of precision will sort things out. Experiment.
You may want to look into using java's java.math.BigDecimal class if you really need precision math. Here is a good article from Oracle/Sun on the case for BigDecimal. While you can never represent 1/3 as someone mentioned, you can have the power to decide exactly how precise you want the result to be. setScale() is your friend.. :)
Ok, because I have way too much time on my hands at the moment here is a code example that relates to your question:
import java.math.BigDecimal;
/**
* Created by a wonderful programmer known as:
* Vincent Stoessel
* xaymaca#gmail.com
* on Mar 17, 2010 at 11:05:16 PM
*/
public class BigUp {
public static void main(String[] args) {
BigDecimal first, second, result ;
first = new BigDecimal("33.33333333333333") ;
second = new BigDecimal("100") ;
result = first.divide(second);
System.out.println("result is " + result);
//will print : result is 0.3333333333333333
}
}
and to plug my new favorite language, Groovy, here is a neater example of the same thing:
import java.math.BigDecimal
def first = new BigDecimal("33.33333333333333")
def second = new BigDecimal("100")
println "result is " + first/second // will print: result is 0.33333333333333
Pretty sure you could've made that into a three line example. :)
If you want exact precision, use BigDecimal. Otherwise, you can use ints multiplied by 10 ^ whatever precision you want.
As others have noted, not all decimal values can be represented as binary since decimal is based on powers of 10 and binary is based on powers of two.
If precision matters, use BigDecimal, but if you just want friendly output:
System.out.printf("%.2f\n", total);
Will give you:
11.40
You're running up against the precision limitation of type double.
Java.Math has some arbitrary-precision arithmetic facilities.
You can't, because 7.3 doesn't have a finite representation in binary. The closest you can get is 2054767329987789/2**48 = 7.3+1/1407374883553280.
Take a look at http://docs.python.org/tutorial/floatingpoint.html for a further explanation. (It's on the Python website, but Java and C++ have the same "problem".)
The solution depends on what exactly your problem is:
If it's that you just don't like seeing all those noise digits, then fix your string formatting. Don't display more than 15 significant digits (or 7 for float).
If it's that the inexactness of your numbers is breaking things like "if" statements, then you should write if (abs(x - 7.3) < TOLERANCE) instead of if (x == 7.3).
If you're working with money, then what you probably really want is decimal fixed point. Store an integer number of cents or whatever the smallest unit of your currency is.
(VERY UNLIKELY) If you need more than 53 significant bits (15-16 significant digits) of precision, then use a high-precision floating-point type, like BigDecimal.
private void getRound() {
// this is very simple and interesting
double a = 5, b = 3, c;
c = a / b;
System.out.println(" round val is " + c);
// round val is : 1.6666666666666667
// if you want to only two precision point with double we
// can use formate option in String
// which takes 2 parameters one is formte specifier which
// shows dicimal places another double value
String s = String.format("%.2f", c);
double val = Double.parseDouble(s);
System.out.println(" val is :" + val);
// now out put will be : val is :1.67
}
Use java.math.BigDecimal
Doubles are binary fractions internally, so they sometimes cannot represent decimal fractions to the exact decimal.
/*
0.8 1.2
0.7 1.3
0.7000000000000002 2.3
0.7999999999999998 4.2
*/
double adjust = fToInt + 1.0 - orgV;
// The following two lines works for me.
String s = String.format("%.2f", adjust);
double val = Double.parseDouble(s);
System.out.println(val); // output: 0.8, 0.7, 0.7, 0.8
Doubles are approximations of the decimal numbers in your Java source. You're seeing the consequence of the mismatch between the double (which is a binary-coded value) and your source (which is decimal-coded).
Java's producing the closest binary approximation. You can use the java.text.DecimalFormat to display a better-looking decimal value.
Short answer: Always use BigDecimal and make sure you are using the constructor with String argument, not the double one.
Back to your example, the following code will print 11.4, as you wish.
public class doublePrecision {
public static void main(String[] args) {
BigDecimal total = new BigDecimal("0");
total = total.add(new BigDecimal("5.6"));
total = total.add(new BigDecimal("5.8"));
System.out.println(total);
}
}
Multiply everything by 100 and store it in a long as cents.
Computers store numbers in binary and can't actually represent numbers such as 33.333333333 or 100.0 exactly. This is one of the tricky things about using doubles. You will have to just round the answer before showing it to a user. Luckily in most applications, you don't need that many decimal places anyhow.
Floating point numbers differ from real numbers in that for any given floating point number there is a next higher floating point number. Same as integers. There's no integer between 1 and 2.
There's no way to represent 1/3 as a float. There's a float below it and there's a float above it, and there's a certain distance between them. And 1/3 is in that space.
Apfloat for Java claims to work with arbitrary precision floating point numbers, but I've never used it. Probably worth a look.
http://www.apfloat.org/apfloat_java/
A similar question was asked here before
Java floating point high precision library
Use a BigDecimal. It even lets you specify rounding rules (like ROUND_HALF_EVEN, which will minimize statistical error by rounding to the even neighbor if both are the same distance; i.e. both 1.5 and 2.5 round to 2).
Why not use the round() method from Math class?
// The number of 0s determines how many digits you want after the floating point
// (here one digit)
total = (double)Math.round(total * 10) / 10;
System.out.println(total); // prints 11.4
Check out BigDecimal, it handles problems dealing with floating point arithmetic like that.
The new call would look like this:
term[number].coefficient.add(co);
Use setScale() to set the number of decimal place precision to be used.
If you have no choice other than using double values, can use the below code.
public static double sumDouble(double value1, double value2) {
double sum = 0.0;
String value1Str = Double.toString(value1);
int decimalIndex = value1Str.indexOf(".");
int value1Precision = 0;
if (decimalIndex != -1) {
value1Precision = (value1Str.length() - 1) - decimalIndex;
}
String value2Str = Double.toString(value2);
decimalIndex = value2Str.indexOf(".");
int value2Precision = 0;
if (decimalIndex != -1) {
value2Precision = (value2Str.length() - 1) - decimalIndex;
}
int maxPrecision = value1Precision > value2Precision ? value1Precision : value2Precision;
sum = value1 + value2;
String s = String.format("%." + maxPrecision + "f", sum);
sum = Double.parseDouble(s);
return sum;
}
You can Do the Following!
System.out.println(String.format("%.12f", total));
if you change the decimal value here %.12f
So far I understand it as main goal to get correct double from wrong double.
Look for my solution how to get correct value from "approximate" wrong value - if it is real floating point it rounds last digit - counted from all digits - counting before dot and try to keep max possible digits after dot - hope that it is enough precision for most cases:
public static double roundError(double value) {
BigDecimal valueBigDecimal = new BigDecimal(Double.toString(value));
String valueString = valueBigDecimal.toPlainString();
if (!valueString.contains(".")) return value;
String[] valueArray = valueString.split("[.]");
int places = 16;
places -= valueArray[0].length();
if ("56789".contains("" + valueArray[0].charAt(valueArray[0].length() - 1))) places--;
//System.out.println("Rounding " + value + "(" + valueString + ") to " + places + " places");
return valueBigDecimal.setScale(places, RoundingMode.HALF_UP).doubleValue();
}
I know it is long code, sure not best, maybe someone can fix it to be more elegant. Anyway it is working, see examples:
roundError(5.6+5.8) = 11.399999999999999 = 11.4
roundError(0.4-0.3) = 0.10000000000000003 = 0.1
roundError(37235.137567000005) = 37235.137567
roundError(1/3) 0.3333333333333333 = 0.333333333333333
roundError(3723513756.7000005) = 3.7235137567E9 (3723513756.7)
roundError(3723513756123.7000005) = 3.7235137561237E12 (3723513756123.7)
roundError(372351375612.7000005) = 3.723513756127E11 (372351375612.7)
roundError(1.7976931348623157) = 1.797693134862316
Do not waste your efford using BigDecimal. In 99.99999% cases you don't need it. java double type is of cource approximate but in almost all cases, it is sufficiently precise. Mind that your have an error at 14th significant digit. This is really negligible!
To get nice output use:
System.out.printf("%.2f\n", total);
I am writing a function round:
static float round(float number, precision){}
The function should work like this: round(12.3456f, 3) = 12.345
My definition of function is like this:
public static float round(float value, int precision) {
float result;
if(precision <= 0){
throw new RuntimeException("Precision can not be zero or less");
}
int number = (int) power(10,precision);
value = value * number;
result = (float)Math.round(value)/number;
return result;
}
But the issue is that, my unit test case for this function doesn't pass,
public void mathTestNew() {
assertEquals("MathTest",12.341,OOTBFunctions.round(12.3416f,3));
}
The result is
junit.framework.AssertionFailedError: MathTest expected:<12.341> but was:<12.342>
I am not sure how to overcome this error. I am not sure if BigDecimal will help me in this.
Rounding normally occurs towards the nearest integer. So 12.3416 is correctly rounded to 12.342
If you want the rounding behaviour you seem to be asking for (where the number is rounded down towards negative infinity) then you should use Math.floor(x) instead of Math.round(x)
Also be careful with rounding floats / doubles as they both suffer from numerical inaccuracy. If you really want high accuracy on decimal places, you may be better using BigDecimal instead.
Math.round is "round-to-nearest". You probably want Math.floor.
If you did want to use BigDecimal:
public static float round(float value, int precision) {
if (precision <= 0) {
throw new IllegalArgumentException("Precision cannot be zero or less.");
}
BigDecimal decimal = BigDecimal.valueOf(value);
return decimal.setScale(precision, RoundingMode.FLOOR).floatValue();
}
You may lose accuracy when converting from BigDecimal to float, so if accuracy is a must, do not convert; keep the value as a BigDecimal.
As mentioned in other answers, float is an approximation of a base 10 number. The following demonstrates just that:
System.out.println(BigDecimal.valueOf(12.3416f)); // outputs 12.34160041809082
System.out.println(new BigDecimal("12.3416")); // outputs 12.3416
12.3416 rounded is 12.342. There in lies your problem. You probably want Math.Floor instead. I would recomend against constantly multiplying as that can ruin the number. However, by 10 does not lower precision.
You can't write such a method. Floating point doesn't have decimal places, it has binary places. Ergo you cannot round to a specified number of decimal places. If you want decimmal places you must use a decimal radix, i.e. BigDecimal, or DecimalFormat. Apart from the error in expectation noted by #ColeJohnson, code like you have written will fail in over 90% of cases.
I'm searching for the best practice to convert Float to Double without loosing precision. So far I only found that a proper way to do so is to convert the Float to String and the String to Double.
Searching the Float API I stumbled upon this method doubleValue(). I thought this is a static constructor that will return a double from my Float without loosing precision but the following code behaves like a cast:
public class Main {
public static void main(String[] args) {
Float floatNumber= 4.95f;
Double doubleNumber= floatNumber.doubleValue();
System.out.println(doubleNumber);
}
}
The output is 4.949999809265137
Searching any other documentation about this from the Float API I didn't find any documentation to tell me what exactly happens when I call that method. Does anybody have any idea? Or can someone confirm that all the method does is perform a cast my Float to a double and unbox it?
The simple primitive-type cast (or even an implicit conversion) will do all you need, if you really want to preserve the value of a float:
float f = 4.95f;
double d = f;
Fundamentally 4.95f is already inaccurate - you can't represent that number exactly as a float. The exact value of floatNumber is represented in doubleNumber too - it's just that that value is not 4.95.
If you really care about the exact decimal digits, you should be using BigDecimal instead (or a scaled integer).
Widening float to double conversion doesn't lose precision in java.
When you use floating point, you get rounding errors which can be potentially "corrected" by rounding the result (assuming you know the precision you want). BigDecimal handles this by always knowing the precision.
float floatNumber= 4.95f;
double doubleNumber = (double) floatNumber;
System.out.println("After cast " + doubleNumber);
System.out.printf("Show two decimal places. %.2f%n", doubleNumber);
doubleNumber = Math.round(doubleNumber * 100) / 100.0;
System.out.println("After rounding to two places " + doubleNumber);
prints
After cast 4.949999809265137
Show two decimal places. 4.95
After rounding to two places 4.95
In Java, I want to convert a double to an integer, I know if you do this:
double x = 1.5;
int y = (int)x;
you get y=1. If you do this:
int y = (int)Math.round(x);
You'll likely get 2. However, I am wondering: since double representations of integers sometimes look like 1.9999999998 or something, is there a possibility that casting a double created via Math.round() will still result in a truncated down number, rather than the rounded number we are looking for (i.e.: 1 instead of 2 in the code as represented) ?
(and yes, I do mean it as such: Is there any value for x, where y will show a result that is a truncated rather than a rounded representation of x?)
If so: Is there a better way to make a double into a rounded int without running the risk of truncation?
Figured something: Math.round(x) returns a long, not a double. Hence: it is impossible for Math.round() to return a number looking like 3.9999998. Therefore, int(Math.round()) will never need to truncate anything and will always work.
is there a possibility that casting a double created via Math.round() will still result in a truncated down number
No, round() will always round your double to the correct value, and then, it will be cast to an long which will truncate any decimal places. But after rounding, there will not be any fractional parts remaining.
Here are the docs from Math.round(double):
Returns the closest long to the argument. The result is rounded to an integer by adding 1/2, taking the floor of the result, and casting the result to type long. In other words, the result is equal to the value of the expression:
(long)Math.floor(a + 0.5d)
For the datatype Double to int, you can use the following:
Double double = 5.00;
int integer = double.intValue();
Double perValue = 96.57;
int roundVal= (int) Math.round(perValue);
Solved my purpose.