How to get the numbers after the decimal point? (java) [duplicate] - java

This question already has answers here:
How do I get whole and fractional parts from double in JSP/Java?
(18 answers)
Closed 9 years ago.
double d = 4.321562;
Is there an easy way to extract the 0.321562 on it's own from d? I tried looking in the math class but no luck. If this can be done without converting to string or casting to anything else, even better.

Well, you can use:
double x = d - Math.floor(d);
Note that due to the way that binary floating point works, that won't give you exactly 0.321562, as the original value isn't exactly 4.321562. If you're really interested in exact digits, you should use BigDecimal instead.

Another way to get the fraction without using Math is to cast to a long.
double x = d - (long) d;
When you print a double the toString will perform a small amount of rounding so you don't see any rounding error. However, when you remove the integer part, the rounding is no longer enough and the rounding error becomes obvious.
The way around this is to do the rounding yourself or use BigDecimal which allows you to control the rounding.
double d = 4.321562;
System.out.println("Double value from toString " + d);
System.out.println("Exact representation " + new BigDecimal(d));
double x = d - (long) d;
System.out.println("Fraction from toString " + x);
System.out.println("Exact value of fraction " + new BigDecimal(x));
System.out.printf("Rounded to 6 places %.6f%n", x);
double x2 = Math.round(x * 1e9) / 1e9;
System.out.println("After rounding to 9 places toString " + x2);
System.out.println("After rounding to 9 places, exact value " + new BigDecimal(x2));
prints
Double value from toString 4.321562
Exact representation 4.321562000000000125510268844664096832275390625
Fraction from toString 0.3215620000000001
Exact value of fraction 0.321562000000000125510268844664096832275390625
Rounded to 6 places 0.321562
After rounding to 9 places toString 0.321562
After rounding to 9 places, exact value 0.32156200000000001448796638214844278991222381591796875
NOTE: double has limited precision and you can see representation issue creep in if you don't use appropriate rounding. This can happen in any calculation you use with double esp numbers which are not an exact sum of powers of 2.

Use modulo:
double d = 3.123 % 1;
assertEquals(0.123, d,0.000001);

Related

Java - double constant number of decimal places [duplicate]

This question already has answers here:
fixed point arithmetics in java with fast performance
(4 answers)
Closed 7 years ago.
I have two double variables:
double a = 1.109
double b = 5.0E-5;
But b is changable and I want to achieve fixed numbers of decimal places depending of b number, for example above I want achieve this result:
Result = 1.10900
But not only print, I need to send it to other method and my double must have fixed numbers of decimal places like in example.
It sounds like you want arbitrary precision on the actual value (as opposed to just output). double doesn't give you that. BigDecimal does though. Its BigDecimal(String) constructor sets the value and the scale (number of places to the right of the decimal) from a string, so:
BigDecimal d = new BigDecimal("1.10900");
BigDecimal then gives you various math operations to stay within that scale, with various rounding options.
If at some point you need to get the double value of the BigDecimal, you can use its doubleValue method. But note that at that point, again, you don't have a fixed number of places to the right of the decimal anymore.
Here's an example contrasting BigDecimal and double (Live Copy):
import java.math.*;
class Example
{
public static void main (String[] args) throws java.lang.Exception
{
BigDecimal bd = new BigDecimal("1.10900");
bd = bd.divide(new BigDecimal("27"), BigDecimal.ROUND_HALF_DOWN);
System.out.println("1.109 / 27 using BigDecimal to five places: " + bd);
double d = 1.109;
d = d / 27.0;
System.out.println("1.109 / 27 using double: " + d);
}
}
Output:
1.109 / 27 using BigDecimal to five places: 0.04107
1.109 / 27 using double: 0.041074074074074075
Try using a number formatter:
NumberFormat formatter = new DecimalFormat("#0.00000");
double a = 1.109;
double b = 5.0E-5;
System.out.println(a);
System.out.println(b);
Output:
1.10900
0.00005
A simple solution is to round the result as needed. This is not only faster than using BigDecimal it can be less error prone as Java doesn't have language support for BigDecimal making it harder to write/read and validate. A simple method for rounding half up for 5 decimal spaces is
public static double round5(double d) {
final double factor = 1e5;
return d > Long.MAX_VALUE / factor || d < -Long.MAX_VALUE / factor ? d :
(long) (d < 0 ? d * factor - 0.5 : d * factor + 0.5) / factor;
}
Note: when you print the double you will still need to specify the number of decimal places you need e.g.
System.out.printf("%.5f", value);
Use java printf-like routine (note it produces platform dependent decimal separators):
String.format("%.5f", a)

Trouble evaluating decimal values in java [duplicate]

This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 7 years ago.
double x = 0.00090;
double b = 0.00100;
double c = x - b;
produces
-1.0000000000000005E-4
instead of
-0.0001
and
double x = -0.09;
double b = 0.001;
double c = x * b;
produces
-8.999999999999999E-5
instead of
-0.00009
I also tried with
Math.round(c) and Math.round(c*100.0)/100.0
but it is producing same results or results with incomplete number range after decimal.
That's how numeric operations are defined in the specification.
Decimal numbers are internally represented as the closest approximation, which in some cases is not the exact literal value.
If you need precise numeric computation, you have to use BigDecimal.
The answers are correct. You might want to read up on how doubles are stored in binary digits. its because it's base 2. If we used something like base 3, then in normal digits, 2/3 would be 0.66666666... but in the "tridigit" it would be 0.2
The E notation is confusing you (explanation on how it works here)
-1.0000000000000005E-4
is
-0.00010000000000000005
in standard notation and
-8.999999999999999E-5
is
-0.00008999999999999999
in standard notation. All the answer you see are correct (almost, but they are very close, decimal math isn't always precise), just using the E notation.
try this:
double x = 0.00090;
double b = 0.00100;
BigDecimal xd = new BigDecimal(x).setScale(10, RoundingMode.HALF_UP);
BigDecimal bd = new BigDecimal(b).setScale(10, RoundingMode.HALF_UP);
BigDecimal cd = xd.multiply(bd);
double c = cd.doubleValue();
System.out.println(c);
For precise calculations, like money calculations, you should use BigDecimals, because they have desired precision, and don't lost any accuracy.
If you prefer printing without "E", try this line:
System.out.println(cd.toPlainString());

multiply Bigdecimal and int generating error [duplicate]

This question already has answers here:
How to multiply a BigDecimal by an integer in Java
(3 answers)
Closed 8 years ago.
I have one value like 0.0004 when I store this in Integer it is converting into Exponential format, So I have used Bigdecimal to convert it to normal value like below
Bigdecimal x=BigDecimal.valueOf(0.0004)
Now I am trying to multiply as x*100 but I am getting below error.
Error: The operator * is undefined for the argument type(s) BigDecimal, int
Because of this error if I use this without bigdecimal again it is converting to EXponential.
Can any one please suggest me the way to multiply Bigdecimal and int.
googled a lot but couldn't find the correct solution.
Thanks for your time
You can use BigDecimal.multiply to multiply your BigDecimal.
However, the int value of 0.0004 * 100 will be 0, which is probably not what you want.
Finally, you can alter the how the BigDecimal is represented in terms of fractional digits by using a NumberFormat instance and formatting your Number.
Here's an example:
BigDecimal x= BigDecimal.valueOf(0.0004);
BigDecimal y = x.multiply(new BigDecimal("100"));
int z = y.intValue();
System.out.printf("y is %s\tz is %d%n", y, z);
// edit to truncate fractional digits
NumberFormat nf = NumberFormat.getInstance();
nf.setMaximumFractionDigits(2);
System.out.printf("y (2 fraction digits) is %s", nf.format(y));
Output
y is 0.04000 z is 0
y (2 fraction digits) is 0.04
BigDecimal's are objects. They don't have normal operators.
Instead of a normal multiplication operator like x*10, you need to call the method multiply in BigDecimal:
x = x.multiply(new BigDecimal(10));
If you want to store it in a new value:
BigDecimal n = x.multiply(new BigDecimal(10));
And to convert that to a primative:
double d = n.doubleValue();
int i = n.intValue();
However, if you're trying to use decimals, why not just use a double:
double x = 0.0004;
double n = x*100;

NumberFormat Parse Issue

I am quite confused about this peculiar 'error' I am getting when parsing a String to a Double.
I've already set up the NumberFormat properties and symbols.
When passing a String with 15 digits and 2 decimals (ex. str = "333333333333333,33")
and parsing it with Number num = NumberFormat.parse(str) the result is omitting a digit.
The actual value of num is 3.333333333333333E14.
It seems to be working with Strings with all 1's, 2's and 4's though...
Anyone can enlighten me?
Cheers
Enrico
The short answer; due to round error
(double) 111111111111111.11 != (double) 111111111111111.1
but
(double) 333333333333333.33 == (double) 333333333333333.3
If you want more precision, use setParseBigDecimal and parse will return a BigDecimal.
Why does this happen? This is because you are at the limit of the precision of double. The 17 ones is fine as it can just be represented. The 2's is just double this and as double stores powers of two, every power of two of all 17 ones, so 17 fours and 17 eights is fine.
However, 17 threes takes one more bit than double has to represent the value and this last bit is truncated. Similarly 17 fives, sixes and nines also have rounding errors.
double[] ds = {
111111111111111.11,
222222222222222.22,
333333333333333.33,
444444444444444.44,
555555555555555.55,
666666666666666.66,
777777777777777.77,
888888888888888.88,
999999999999999.99};
for (double d : ds) {
System.out.println(d + " - " + new BigDecimal(d));
}
prints the following. The double is rounded slightly before printing and the BigDecimal shows you the exact values the double represents.
1.1111111111111111E14 - 111111111111111.109375
2.2222222222222222E14 - 222222222222222.21875
3.333333333333333E14 - 333333333333333.3125
4.4444444444444444E14 - 444444444444444.4375
5.5555555555555556E14 - 555555555555555.5625
6.666666666666666E14 - 666666666666666.625
7.777777777777778E14 - 777777777777777.75
8.888888888888889E14 - 888888888888888.875
1.0E15 - 1000000000000000
The DecimalFormat.parse method will in this case return a Double, which has limited precision.
You can't expect it to always be able to return a Number that represents the input exactly.
You can use BigDecimal.setParseBigDecimal to allow the number format to return a BigDecimal from the parse method. This Number is capable of representing your values with arbitrary precision. (Thanks #Peter Lawrey for pointing that out!)

Double vs. BigDecimal?

I have to calculate some floating point variables and my colleague suggest me to use BigDecimal instead of double since it will be more precise. But I want to know what it is and how to make most out of BigDecimal?
A BigDecimal is an exact way of representing numbers. A Double has a certain precision. Working with doubles of various magnitudes (say d1=1000.0 and d2=0.001) could result in the 0.001 being dropped altogether when summing as the difference in magnitude is so large. With BigDecimal this would not happen.
The disadvantage of BigDecimal is that it's slower, and it's a bit more difficult to program algorithms that way (due to + - * and / not being overloaded).
If you are dealing with money, or precision is a must, use BigDecimal. Otherwise Doubles tend to be good enough.
I do recommend reading the javadoc of BigDecimal as they do explain things better than I do here :)
My English is not good so I'll just write a simple example here.
double a = 0.02;
double b = 0.03;
double c = b - a;
System.out.println(c);
BigDecimal _a = new BigDecimal("0.02");
BigDecimal _b = new BigDecimal("0.03");
BigDecimal _c = _b.subtract(_a);
System.out.println(_c);
Program output:
0.009999999999999998
0.01
Does anyone still want to use double? ;)
There are two main differences from double:
Arbitrary precision, similarly to BigInteger they can contain number of arbitrary precision and size (whereas a double has a fixed number of bits)
Base 10 instead of Base 2, a BigDecimal is n*10^-scale where n is an arbitrary large signed integer and scale can be thought of as the number of digits to move the decimal point left or right
It is still not true to say that BigDecimal can represent any number. But two reasons you should use BigDecimal for monetary calculations are:
It can represent all numbers that can be represented in decimal notion and that includes virtually all numbers in the monetary world (you never transfer 1/3 $ to someone).
The precision can be controlled to avoid accumulated errors. With a double, as the magnitude of the value increases, its precision decreases and this can introduce significant error into the result.
If you write down a fractional value like 1 / 7 as decimal value you get
1/7 = 0.142857142857142857142857142857142857142857...
with an infinite repetition of the digits 142857. Since you can only write a finite number of digits you will inevitably introduce a rounding (or truncation) error.
Numbers like 1/10 or 1/100 expressed as binary numbers with a fractional part also have an infinite number of digits after the decimal point:
1/10 = binary 0.0001100110011001100110011001100110...
Doubles store values as binary and therefore might introduce an error solely by converting a decimal number to a binary number, without even doing any arithmetic.
Decimal numbers (like BigDecimal), on the other hand, store each decimal digit as is (binary coded, but each decimal on its own). This means that a decimal type is not more precise than a binary floating point or fixed point type in a general sense (i.e. it cannot store 1/7 without loss of precision), but it is more accurate for numbers that have a finite number of decimal digits as is often the case for money calculations.
Java's BigDecimal has the additional advantage that it can have an arbitrary (but finite) number of digits on both sides of the decimal point, limited only by the available memory.
If you are dealing with calculation, there are laws on how you should calculate and what precision you should use. If you fail that you will be doing something illegal.
The only real reason is that the bit representation of decimal cases are not precise. As Basil simply put, an example is the best explanation. Just to complement his example, here's what happens:
static void theDoubleProblem1() {
double d1 = 0.3;
double d2 = 0.2;
System.out.println("Double:\t 0,3 - 0,2 = " + (d1 - d2));
float f1 = 0.3f;
float f2 = 0.2f;
System.out.println("Float:\t 0,3 - 0,2 = " + (f1 - f2));
BigDecimal bd1 = new BigDecimal("0.3");
BigDecimal bd2 = new BigDecimal("0.2");
System.out.println("BigDec:\t 0,3 - 0,2 = " + (bd1.subtract(bd2)));
}
Output:
Double: 0,3 - 0,2 = 0.09999999999999998
Float: 0,3 - 0,2 = 0.10000001
BigDec: 0,3 - 0,2 = 0.1
Also we have that:
static void theDoubleProblem2() {
double d1 = 10;
double d2 = 3;
System.out.println("Double:\t 10 / 3 = " + (d1 / d2));
float f1 = 10f;
float f2 = 3f;
System.out.println("Float:\t 10 / 3 = " + (f1 / f2));
// Exception!
BigDecimal bd3 = new BigDecimal("10");
BigDecimal bd4 = new BigDecimal("3");
System.out.println("BigDec:\t 10 / 3 = " + (bd3.divide(bd4)));
}
Gives us the output:
Double: 10 / 3 = 3.3333333333333335
Float: 10 / 3 = 3.3333333
Exception in thread "main" java.lang.ArithmeticException: Non-terminating decimal expansion
But:
static void theDoubleProblem2() {
BigDecimal bd3 = new BigDecimal("10");
BigDecimal bd4 = new BigDecimal("3");
System.out.println("BigDec:\t 10 / 3 = " + (bd3.divide(bd4, 4, BigDecimal.ROUND_HALF_UP)));
}
Has the output:
BigDec: 10 / 3 = 3.3333
BigDecimal is Oracle's arbitrary-precision numerical library. BigDecimal is part of the Java language and is useful for a variety of applications ranging from the financial to the scientific (that's where sort of am).
There's nothing wrong with using doubles for certain calculations. Suppose, however, you wanted to calculate Math.Pi * Math.Pi / 6, that is, the value of the Riemann Zeta Function for a real argument of two (a project I'm currently working on). Floating-point division presents you with a painful problem of rounding error.
BigDecimal, on the other hand, includes many options for calculating expressions to arbitrary precision. The add, multiply, and divide methods as described in the Oracle documentation below "take the place" of +, *, and / in BigDecimal Java World:
http://docs.oracle.com/javase/7/docs/api/java/math/BigDecimal.html
The compareTo method is especially useful in while and for loops.
Be careful, however, in your use of constructors for BigDecimal. The string constructor is very useful in many cases. For instance, the code
BigDecimal onethird = new BigDecimal("0.33333333333");
utilizes a string representation of 1/3 to represent that infinitely-repeating number to a specified degree of accuracy. The round-off error is most likely somewhere so deep inside the JVM that the round-off errors won't disturb most of your practical calculations. I have, from personal experience, seen round-off creep up, however. The setScale method is important in these regards, as can be seen from the Oracle documentation.
If you need to use division in your arithmetic, you need to use double instead of BigDecimal. Division (divide(BigDecimal) method) in BigDecimal is pretty useless as BigDecimal can't handle repeating decimal rational numbers (division where divisors are and will throw java.lang.ArithmeticException: Non-terminating decimal expansion; no exact representable decimal result.
Just try BigDecimal.ONE.divide(new BigDecimal("3"));
Double, on the other hand, will handle division fine (with the understood precision which is roughly 15 significant digits)

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