Develop Reference

Generating random doubles in Java between 0 and 1 inclusively or [0..1] [duplicate]

We can easily get random floating point numbers within a desired range [X,Y) (note that X is inclusive and Y is exclusive) with the function listed below since Math.random() (and most pseudorandom number generators, AFAIK) produce numbers in [0,1):
function randomInRange(min, max) {
return Math.random() * (max-min) + min;
}
// Notice that we can get "min" exactly but never "max".
How can we get a random number in a desired range inclusive to both bounds, i.e. [X,Y]?
I suppose we could "increment" our value from Math.random() (or equivalent) by "rolling" the bits of an IEE-754 floating point double precision to put the maximum possible value at 1.0 exactly but that seems like a pain to get right, especially in languages poorly suited for bit manipulation. Is there an easier way?
(As an aside, why do random number generators produce numbers in [0,1) instead of [0,1]?)
[Edit] Please note that I have no need for this and I am fully aware that the distinction is pedantic. Just being curious and hoping for some interesting answers. Feel free to vote to close if this question is inappropriate.

I believe there is much better decision but this one should work :)
function randomInRange(min, max) {
return Math.random() < 0.5 ? ((1-Math.random()) * (max-min) + min) : (Math.random() * (max-min) + min);
}

First off, there's a problem in your code: Try randomInRange(0,5e-324) or just enter Math.random()*5e-324 in your browser's JavaScript console.
Even without overflow/underflow/denorms, it's difficult to reason reliably about floating point ops. After a bit of digging, I can find a counterexample:
>>> a=1.0
>>> b=2**-54
>>> rand=a-2*b
>>> a
1.0
>>> b
5.551115123125783e-17
>>> rand
0.9999999999999999
>>> (a-b)*rand+b
1.0
It's easier to explain why this happens with a=253 and b=0.5: 253-1 is the next representable number down. The default rounding mode ("round to nearest even") rounds 253-0.5 up (because 253 is "even" [LSB = 0] and 253-1 is "odd" [LSB = 1]), so you subtract b and get 253, multiply to get 253-1, and add b to get 253 again.
To answer your second question: Because the underlying PRNG almost always generates a random number in the interval [0,2n-1], i.e. it generates random bits. It's very easy to pick a suitable n (the bits of precision in your floating point representation) and divide by 2n and get a predictable distribution. Note that there are some numbers in [0,1) that you will will never generate using this method (anything in (0,2-53) with IEEE doubles).
It also means that you can do a[Math.floor(Math.random()*a.length)] and not worry about overflow (homework: In IEEE binary floating point, prove that b < 1 implies a*b < a for positive integer a).
The other nice thing is that you can think of each random output x as representing an interval [x,x+2-53) (the not-so-nice thing is that the average value returned is slightly less than 0.5). If you return in [0,1], do you return the endpoints with the same probability as everything else, or should they only have half the probability because they only represent half the interval as everything else?
To answer the simpler question of returning a number in [0,1], the method below effectively generates an integer [0,2n] (by generating an integer in [0,2n+1-1] and throwing it away if it's too big) and dividing by 2n:
function randominclusive() {
// Generate a random "top bit". Is it set?
while (Math.random() >= 0.5) {
// Generate the rest of the random bits. Are they zero?
// If so, then we've generated 2^n, and dividing by 2^n gives us 1.
if (Math.random() == 0) { return 1.0; }
// If not, generate a new random number.
}
// If the top bits are not set, just divide by 2^n.
return Math.random();
}
The comments imply base 2, but I think the assumptions are thus:
0 and 1 should be returned equiprobably (i.e. the Math.random() doesn't make use of the closer spacing of floating point numbers near 0).
Math.random() >= 0.5 with probability 1/2 (should be true for even bases)
The underlying PRNG is good enough that we can do this.
Note that random numbers are always generated in pairs: the one in the while (a) is always followed by either the one in the if or the one at the end (b). It's fairly easy to verify that it's sensible by considering a PRNG that returns either 0 or 0.5:
a=0   b=0  : return 0
a=0   b=0.5: return 0.5
a=0.5 b=0  : return 1
a=0.5 b=0.5: loop
Problems:
The assumptions might not be true. In particular, a common PRNG is to take the top 32 bits of a 48-bit LCG (Firefox and Java do this). To generate a double, you take 53 bits from two consecutive outputs and divide by 253, but some outputs are impossible (you can't generate 253 outputs with 48 bits of state!). I suspect some of them never return 0 (assuming single-threaded access), but I don't feel like checking Java's implementation right now.
Math.random() is twice for every potential output as a consequence of needing to get the extra bit, but this places more constraints on the PRNG (requiring us to reason about four consecutive outputs of the above LCG).
Math.random() is called on average about four times per output. A bit slow.
It throws away results deterministically (assuming single-threaded access), so is pretty much guaranteed to reduce the output space.

My solution to this problem has always been to use the following in place of your upper bound.
Math.nextAfter(upperBound,upperBound+1)
or
upperBound + Double.MIN_VALUE
So your code would look like this:
double myRandomNum = Math.random() * Math.nextAfter(upperBound,upperBound+1) + lowerBound;
or
double myRandomNum = Math.random() * (upperBound + Double.MIN_VALUE) + lowerBound;
This simply increments your upper bound by the smallest double (Double.MIN_VALUE) so that your upper bound will be included as a possibility in the random calculation.
This is a good way to go about it because it does not skew the probabilities in favor of any one number.
The only case this wouldn't work is where your upper bound is equal to Double.MAX_VALUE

Just pick your half-open interval slightly bigger, so that your chosen closed interval is a subset. Then, keep generating the random variable until it lands in said closed interval.
Example: If you want something uniform in [3,8], then repeatedly regenerate a uniform random variable in [3,9) until it happens to land in [3,8].
function randomInRangeInclusive(min,max) {
var ret;
for (;;) {
ret = min + ( Math.random() * (max-min) * 1.1 );
if ( ret <= max ) { break; }
}
return ret;
}
Note: The amount of times you generate the half-open R.V. is random and potentially infinite, but you can make the expected number of calls otherwise as close to 1 as you like, and I don't think there exists a solution that doesn't potentially call infinitely many times.

Given the "extremely large" number of values between 0 and 1, does it really matter? The chances of actually hitting 1 are tiny, so it's very unlikely to make a significant difference to anything you're doing.

What would be a situation where you would NEED a floating point value to be inclusive of the upper bound? For integers I understand, but for a float, the difference between between inclusive and exclusive is what like 1.0e-32.

Think of it this way. If you imagine that floating-point numbers have arbitrary precision, the chances of getting exactly min are zero. So are the chances of getting max. I'll let you draw your own conclusion on that.
This 'problem' is equivalent to getting a random point on the real line between 0 and 1. There is no 'inclusive' and 'exclusive'.

The question is akin to asking, what is the floating point number right before 1.0? There is such a floating point number, but it is one in 2^24 (for an IEEE float) or one in 2^53 (for a double).
The difference is negligible in practice.

private static double random(double min, double max) {
final double r = Math.random();
return (r >= 0.5d ? 1.5d - r : r) * (max - min) + min;
}

Math.round() will help to include the bound value. If you have 0 <= value < 1 (1 is exclusive), then Math.round(value * 100) / 100 returns 0 <= value <= 1 (1 is inclusive). A note here is that the value now has only 2 digits in its decimal place. If you want 3 digits, try Math.round(value * 1000) / 1000 and so on. The following function has one more parameter, that is the number of digits in decimal place - I called as precision:
function randomInRange(min, max, precision) {
return Math.round(Math.random() * Math.pow(10, precision)) /
Math.pow(10, precision) * (max - min) + min;
}

How about this?
function randomInRange(min, max){
var n = Math.random() * (max - min + 0.1) + min;
return n > max ? randomInRange(min, max) : n;
}
If you get stack overflow on this I'll buy you a present.
--
EDIT: never mind about the present. I got wild with:
randomInRange(0, 0.0000000000000000001)
and got stack overflow.

I am fairly less experienced, So I am also looking for solutions as well.
This is my rough thought:
Random number generators produce numbers in [0,1) instead of [0,1],
Because [0,1) is an unit length that can be followed by [1,2) and so on without overlapping.
For random[x, y],
You can do this:
float randomInclusive(x, y){
float MIN = smallest_value_above_zero;
float result;
do{
result = random(x, (y + MIN));
} while(result > y);
return result;
}
Where all values in [x, y] has the same possibility to be picked, and you can reach y now.

Generating a "uniform" floating-point number in a range is non-trivial. For example, the common practice of multiplying or dividing a random integer by a constant, or by scaling a "uniform" floating-point number to the desired range, have the disadvantage that not all numbers a floating-point format can represent in the range can be covered this way, and may have subtle bias problems. These problems are discussed in detail in "Generating Random Floating-Point Numbers by Dividing Integers: a Case Study" by F. Goualard.
Just to show how non-trivial the problem is, the following pseudocode generates a random "uniform-behaving" floating-point number in the closed interval [lo, hi], where the number is of the form FPSign * FPSignificand * FPRADIX^FPExponent. The pseudocode below was reproduced from my section on floating-point number generation. Note that it works for any precision and any base (including binary and decimal) of floating-point numbers.
METHOD RNDRANGE(lo, hi)
losgn = FPSign(lo)
hisgn = FPSign(hi)
loexp = FPExponent(lo)
hiexp = FPExponent(hi)
losig = FPSignificand(lo)
hisig = FPSignificand(hi)
if lo > hi: return error
if losgn == 1 and hisgn == -1: return error
if losgn == -1 and hisgn == 1
// Straddles negative and positive ranges
// NOTE: Changes negative zero to positive
mabs = max(abs(lo),abs(hi))
while true
ret=RNDRANGE(0, mabs)
neg=RNDINT(1)
if neg==0: ret=-ret
if ret>=lo and ret<=hi: return ret
end
end
if lo == hi: return lo
if losgn == -1
// Negative range
return -RNDRANGE(abs(lo), abs(hi))
end
// Positive range
expdiff=hiexp-loexp
if loexp==hiexp
// Exponents are the same
// NOTE: Automatically handles
// subnormals
s=RNDINTRANGE(losig, hisig)
return s*1.0*pow(FPRADIX, loexp)
end
while true
ex=hiexp
while ex>MINEXP
v=RNDINTEXC(FPRADIX)
if v==0: ex=ex-1
else: break
end
s=0
if ex==MINEXP
// Has FPPRECISION or fewer digits
// and so can be normal or subnormal
s=RNDINTEXC(pow(FPRADIX,FPPRECISION))
else if FPRADIX != 2
// Has FPPRECISION digits
s=RNDINTEXCRANGE(
pow(FPRADIX,FPPRECISION-1),
pow(FPRADIX,FPPRECISION))
else
// Has FPPRECISION digits (bits), the highest
// of which is always 1 because it's the
// only nonzero bit
sm=pow(FPRADIX,FPPRECISION-1)
s=RNDINTEXC(sm)+sm
end
ret=s*1.0*pow(FPRADIX, ex)
if ret>=lo and ret<=hi: return ret
end
END METHOD

Math in Java when precision is lost

The below algorithm works to identify a factor of a small number but fails completely when using a large one such as 7534534523.0
double result = 7; // 7534534523.0;
double divisor = 1;
for (int i = 2; i < result; i++){
double r = result / (double)i;
if (Math.floor(r) == r){
divisor = i;
break;
}
}
System.out.println(result + "/" + divisor + "=" + (result/divisor));
The number 7534534523.0 divided by 2 on a calculator can give a decimal part or round it (losing the 0.5). How can I perform such a check on large numbers? Do I have to use BigDecimal for this? Or is there another way?

If your goal is to represent a number with exactly n significant figures to the right of the decimal, BigDecimal is the class to use.
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).
Additionally, you can have a better control over scale manipulation, rounding and format conversion.

I don't see what the problem is in your code. It works exactly like it should.
When I run your code I get this output:
7.534534523E9/77359.0=97397.0
That may have confused you, but its perfectly fine. It's just using scientific notation, but there is nothing wrong with that.
7.534534523E9 = 7.534534523 * 109 = 7,534,534,523
If you want to see it in normal notation, you can use System.out.format to print the result:
System.out.format("%.0f/%.0f=%.0f\n", result, divisor, result / divisor);
Shows:
7534534523/77359=97397
But you don't need double or BigDecimal to check if a number is divisible by another number. You can use the modulo operator on integral types to check if one number is divisible by another. As long as your numbers fit in a long, this works, otherwise you can move on to a BigInteger:
long result = 7534534523L;
long divisor = 1;
for (int i = 2; i < result; i++) {
if (result % i == 0) {
divisor = i;
break;
}
}
System.out.println(result + "/" + divisor + "=" + (result / divisor));

BigDecimal is the way to move ahead for preserving high precision in numbers.
DO NOT do not use constructor BigDecimal(double val) as the rounding is performed and the output is not always same. The same is mentioned in the implementation as well. According to it:
The results of this constructor can be somewhat unpredictable. One might assume that writing new BigDecimal(0.1) in Java creates a BigDecimal which is exactly equal to 0.1 (an unscaled value of 1, with a scale of 1), but it is actually equal to 0.1000000000000000055511151231257827021181583404541015625. This is because 0.1 cannot be represented exactly as a double (or, for that matter, as a binary fraction of any finite length). Thus, the value that is being passed in to the constructor is not exactly equal to 0.1, appearances notwithstanding.
ALWAYS try to use constructor BigDecimal(String val) as it preserves precision and gives same output each time.

How to calculate ((Integer)^(double)) % (Integer) in java?

I am trying to calculate the value of (10^5.102103)%24 that is 10 raised to power 5.102103 modulus 24 in Java ?
Which is the best and accurate method to do because
int a;
double b;
int m;
Calculate (a^b)%m
Where a can be very large like upto 10^9
b can be any double or float value which can be large
and m is any Integer
Example ---How you can calculate the value of
(10^10002.3443)%10000007
I know Math.pow(a,b) function works for small a and b only
While BigInteger function Uses only modPow(a,b) where a and b should be integer only(Correct me if i am wrong)

Unfortunately, it's not possible using the normal Java data types to get a correct answer to this. If you use double to store the exponent, you introduce an error, because double won't store most decimal numbers exactly. When you write double b = 10002.3443; the number that is stored in b is actually 10002.34430000000065774656832218170166015625. Even though it looks like 10002.3443 when you print it, that's a trick of the way Java prints numbers - basically it chooses the decimal number with the least number of decimal places that would be represented by that double.
Now this difference looks insignificant. But the difference between 10^10002.3443 and 10^10002.34430000000065774656832218170166015625 is approximately 3.346 x 10^9990, which is a 9991-digit number. Now, what will this difference become when we apply the modulus operator?
(10^10002.34430000000065774656832218170166015625 % 10000007) - (10^10002.3443 % 10000007)
= (10^10002.34430000000065774656832218170166015625 - 10^10002.3443) % 10000007
= (3.346 x 10^9990) % 10000007 (approximately)
Now, it's anybody's guess what that actually comes to. But you've got a better chance of being struck by lightning than of getting the correct answer, if you use double at any point in the calculation.
The other option might be BigDecimal. But the problem is that 10^10002.3443 is irrational - it's not a terminating decimal, so it can't be represented correctly in a BigDecimal.
So Java doesn't have a data type that will allow you to perform the calculation that you want to perform.
You are going to have to invent your own data type, then work out how to do all the bit-crunching to implement exponentiation and modulus. This is a huge project, and I suggest you start out by getting yourself a PhD in mathematics.
(Note: Obviously, I am using ^ to indicate exponentiation and x to indicate multiplication in the above, even though this is not the normal Java convention)

Let's think back to discrete math!
Given y = a b (mod m), we know that
y = ((a mod m)^b) mod m
For example, if we have
a = 2, b = 6, m = 5
a raised to the power of b is 64. 64 mod m is 64 % 5 == 4. Let's check our algorithm:
4 == ((a mod m)^b) mod m
4 == ((2 mod 5)^6) mod 5
...
4 == 64 % 5
4 == 4
This doesn't really help us all too much (in its current form), so let's use modular arithmetic at every step to save the day.
int a = 10;
int m = 10000007;
double b = 10002.3443;
int holder = (int) b;
double delta = b - holder; // as close as we're going to get
int total = 1;
for (int i = 0; i < holder; i++) {
total *= (a % m); // multiply by the modulus
total %= m; // take the modulus again
}
total *= (Math.round(Math.pow(a, delta)) % m);
total %= m;

How can I round manually?

I'd like to round manually without the round()-Method.
So I can tell my program that's my number, on this point i want you to round.
Let me give you some examples:
Input number: 144
Input rounding: 2
Output rounded number: 140
Input number: 123456
Input rounding: 3
Output rounded number: 123500
And as a litte addon maybe to round behind the comma:
Input number: 123.456
Input rounding: -1
Output rounded number: 123.460
I don't know how to start programming that...
Has anyone a clue how I can get started with that problem?
Thanks for helping me :)
I'd like to learn better programming, so i don't want to use the round and make my own one, so i can understand it a better way :)

A simple way to do it is:
Divide the number by a power of ten
Round it by any desired method
Multiply the result by the same power of ten in step 1
Let me show you an example:
You want to round the number 1234.567 to two decimal positions (the desired result is 1234.57).
x = 1234.567;
p = 2;
x = x * pow(10, p); // x = 123456.7
x = floor(x + 0.5); // x = floor(123456.7 + 0.5) = floor(123457.2) = 123457
x = x / pow(10,p); // x = 1234.57
return x;
Of course you can compact all these steps in one. I made it step-by-step to show you how it works. In a compact java form it would be something like:
public double roundItTheHardWay(double x, int p) {
return ((double) Math.floor(x * pow(10,p) + 0.5)) / pow(10,p);
}
As for the integer positions, you can easily check that this also works (with p < 0).
Hope this helps

if you need some advice how to start,
step by step write down calculations what you need to do to get from 144,2 --> 140
replace your math with java commands, that should be easy, but if you have problem, just look here and here

public static int round (int input, int places) {
int factor = (int)java.lang.Math.pow(10, places);
return (input / factor) * factor;
}
Basically, what this does is dividing the input by your factor, then multiplying again. When dividing integers in languages like Java, the remainder of the division is dropped from the results.
edit: the code was faulty, fixed it. Also, the java.lang.Math.pow is so that you get 10 to the n-th power, where n is the value of places. In the OP's example, the number of places to consider is upped by one.
Re-edit: as pointed out in the comments, the above will give you the floor, that is, the result of rounding down. If you don't want to always round down, you must also keep the modulus in another variable. Like this:
int mod = input % factor;
If you want to always get the ceiling, that is, rounding up, check whether mod is zero. If it is, leave it at that. Otherwise, add factor to the result.
int ceil = input + (mod == 0 ? 0 : factor);
If you want to round to nearest, then get the floor if mod is smaller than factor / 2, or the ceiling otherwise.

Divide (positive)/Multiply (negative) by the "input rounding" times 10 - 1 (144 / (10 * (2 - 1)). This will give you the same in this instance. Get the remainder of the last digit (4). Determine if it is greater than or equal to 5 (less than). Make it equal to 0 or add 10, depending on the previous answer. Multiply/Divide it back by the "input rounding" times 10 - 1. This should give you your value.
If this is for homework. The purpose is to teach you to think for yourself. I may have given you the answer, but you still need to write the code by yourself.
Next time, you should write your own code and ask what is wrong

For integers, one way would be to use a combination of the mod operator, which is the percent symbol %, and the divide operator. In your first example, you would compute 144 % 10, resulting in 4. And compute 144 / 10, which gives 14 (as an integer). You can compare the result of the mod operation to half of the denominator, to find out if you should round the 14 up to 15 or not (in this case not), and then multiply back by the denominator to get your answer.
In psuedo code, assuming n is the number to round, p is the power of 10 representing the position of the significant digits:
denom = power(10, p)
remainder = n % denom
dividend = n / denom
if (remainder < denom/2)
return dividend * denom
else
return (dividend + 1) * denom

How to round *down* integers in Java?

I'd like to round integers down to their nearest 1000 in Java.
So for example:
13,623 rounds to 13,000
18,999 rounds to 18,000
etc

Simply divide by 1000 to lose the digits that are not interesting to you, and multiply by 1000:
i = i/1000 * 1000
Or, you can also try:
i = i - (i % 1000)

You could divide the number by 1000, apply Math.floor, multiply by 1000 and cast back to integer.

int i = Math.floorDiv(-13623, 1000) * 1000
//i => -14000
The above code will always round down (towards negative infinity) assuming the divisor (1000 in the example) is positive.
The other answer (i = i/1000 * 1000) rounds down when i is positive, but up when i is negative.
-13623 / 1000 * 1000 == -13000
There is also a version of Math.floorDiv for longs which will work for very large numbers where the Math.floor method might fail due to the precision of double.
There are also Math.floorMod methods to go with the floorDivs which might allow you to shorten it a bit:
int i = -13623;
i -= Math.floorMod(i, 1000);
//i => -14000