난 Java에서 Random 클래스를 의사 난수 생성기로 사용하고 있습니다. nextDouble 함수를 많이 사용하고 있습니다 (~ 10^5). 동일한 번호를 얻지 못하게하기 위해 다시 채워야하는 횟수는 몇 번입니까? 다시 시드해야합니까?다시 시드해야하기 전에 randomGenerator.nextDouble()을 몇 번 사용할 수 있습니까?
이것은 실험을위한 것으로 숫자는 공백의 점에 대한 좌표로 사용되므로 가능한 한 균일하게 분포 시키길 원합니다.
어떻게 다시 시드합니까? 어디에서 int 시드를 얻을 수 있습니까?
LinkedHashSet. 내부 시드는 48 비트이므로 무작위 순서는 2^48 int 값 또는 2^47 이중 값 다음에 반복됩니다.
+1 : SecureRandom을 사용하는 경우 다시 시드하지 않아도됩니다. –
죄송합니다. 직접 질문에 답변 할 수 없습니다. Java의 난수 생성기의 순환 시간을 기억하지 못합니다. 비록 당신이 생성하고있는 숫자의 양과 가까이서 자르고 있다고 생각합니다.
하지만 컴퓨터 공학 통계 수업에서 내가 배운 것은 당신을 도울 수 있습니다.
대부분의 난수를 생성하는 가장 좋은 방법은 Mersenne Twister 난수 생성기를 사용하는 것입니다. 이 발전기는 시드 할 필요가 없습니다 충분한 임의의 숫자를 제공 할 것, 그것의 기간 (2^19937)이있다 - 여기
1 MerseeneTwister
에 대한 소스 코드를 여기에는 클래스이다 임의의 숫자를 생성합니다.
class RandomVariable {
/** Initialize Mersenne Twister generator. */
private static MersenneTwister rnd = new MersenneTwister();
public static double rand() {
return rnd.nextDouble();
}
/** Generate a random number from a uniform random variable.
*
* @param min Mininum value for the random variable.
* @param max Maximum value for the random variable.
*
* @return A random double between min and max.
*/
public static double uniform(double min, double max) {
return min + (max - min) * rand();
}
}
다음은 임의의 숫자를 생성하는 샘플입니다. 소스에서 주석을 제거했음을 유의하십시오. 이것은 코드의 오픈 소스 성격을 자극 할 수도 있지만, 모든 것을 복사 할 수는 없으며 코드로 형식화해야합니다.
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serializable;
public class sample{
public static void main(String args[]){
RandomVariable gen = new RandomVariable();
double num = gen.uniform(-1,1);
int n = 10000;
Set<Double> nums = new HashSet<Double>();
while (numbers.size() < n)
nums.add(gen.uniform(-1,1));
}
}
class RandomVariable {
/** Initialize Mersenne Twister generator. */
private static MersenneTwister rnd = new MersenneTwister();
public static double rand() {
return rnd.nextDouble();
}
/** Generate a random number from a uniform random variable.
*
* @param min Mininum value for the random variable.
* @param max Maximum value for the random variable.
*
* @return A random double between min and max.
*/
public static double uniform(double min, double max) {
return min + (max - min) * rand();
}
}
class MersenneTwister extends java.util.Random implements Serializable {
// Period parameters
private static final int N = 624;
private static final int M = 397;
private static final int MATRIX_A = 0x9908b0df; // private static final
//* constant vector a
private static final int UPPER_MASK = 0x80000000; // most significant
// w-r bits
private static final int LOWER_MASK = 0x7fffffff; // least significant
// r bits
// Tempering parameters
private static final int TEMPERING_MASK_B = 0x9d2c5680;
private static final int TEMPERING_MASK_C = 0xefc60000;
private int mt[]; // the array for the state vector
private int mti; // mti==N+1 means mt[N] is not initialized
private int mag01[];
// a good initial seed (of int size, though stored in a long)
// private static final long GOOD_SEED = 4357;
/* implemented here because there's a bug in Random's implementation
of the Gaussian code (divide by zero, and log(0), ugh!), yet its
gaussian variables are private so we can't access them here. :-(*/
private double __nextNextGaussian;
private boolean __haveNextNextGaussian;
/**
* Constructor using the default seed.
*/
public MersenneTwister() {
this(System.currentTimeMillis());
}
/**
* Constructor using a given seed. Though you pass this seed in
* as a long, it's best to make sure it's actually an integer.
*/
public MersenneTwister(final long seed) {
super(seed); /* just in case */
setSeed(seed);
}
/**
* Constructor using an array.
*/
public MersenneTwister(final int[] array) {
super(System.currentTimeMillis());
/* pick something at random just in case */
setSeed(array);
}
/**
* Initalize the pseudo random number generator. Don't
* pass in a long that's bigger than an int (Mersenne Twister
* only uses the first 32 bits for its seed).
*/
synchronized public void setSeed(final long seed) {
// it's always good style to call super
super.setSeed(seed);
// Due to a bug in java.util.Random clear up to 1.2, we're
// doing our own Gaussian variable.
__haveNextNextGaussian = false;
mt = new int[N];
mag01 = new int[2];
mag01[0] = 0x0;
mag01[1] = MATRIX_A;
mt[0] = (int) (seed & 0xfffffff);
for (mti = 1; mti < N; mti++) {
mt[mti] =
(1812433253 * (mt[mti - 1]^(mt[mti - 1] >>> 30)) + mti);
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
mt[mti] &= 0xffffffff;
/* for >32 bit machines */
}
}
/**
* An alternative, more complete, method of seeding the
* pseudo random number generator. array must be an
* array of 624 ints, and they can be any value as long as
* they're not *all* zero.
*/
synchronized public void setSeed(final int[] array) {
int i, j, k;
setSeed(19650218);
i = 1;
j = 0;
k = (N > array.length ? N : array.length);
for (; k != 0; k--) {
mt[i] = (mt[i]^((mt[i - 1]^(mt[i - 1] >>> 30)) * 1664525))
+ array[j] + j; /* non linear */
mt[i] &= 0xffffffff; /* for WORDSIZE > 32 machines */
i++;
j++;
if (i >= N) {
mt[0] = mt[N - 1];
i = 1;
}
if (j >= array.length) {
j = 0;
}
}
for (k = N - 1; k != 0; k--) {
mt[i] = (mt[i]^((mt[i - 1]^(mt[i - 1] >>> 30)) * 1566083941))
- i; /* non linear */
mt[i] &= 0xffffffff; /* for WORDSIZE > 32 machines */
i++;
if (i >= N) {
mt[0] = mt[N - 1];
i = 1;
}
}
mt[0] = 0x80000000; /* MSB is 1; assuring non-zero initial array */
}
/**
* Returns an integer with <em>bits</em> bits filled with a random number.
*/
synchronized protected int next(final int bits) {
int y;
if (mti >= N) // generate N words at one time
{
int kk;
final int[] mt = this.mt; // locals are slightly faster
final int[] mag01 = this.mag01; // locals are slightly faster
for (kk = 0; kk < N - M; kk++) {
y = (mt[kk] & UPPER_MASK) | (mt[kk + 1] & LOWER_MASK);
mt[kk] = mt[kk + M]^(y >>> 1)^mag01[y & 0x1];
}
for (; kk < N - 1; kk++) {
y = (mt[kk] & UPPER_MASK) | (mt[kk + 1] & LOWER_MASK);
mt[kk] = mt[kk + (M - N)]^(y >>> 1)^mag01[y & 0x1];
}
y = (mt[N - 1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
mt[N - 1] = mt[M - 1]^(y >>> 1)^mag01[y & 0x1];
mti = 0;
}
y = mt[mti++];
y ^= y >>> 11; // TEMPERING_SHIFT_U(y)
y ^= (y << 7) & TEMPERING_MASK_B; // TEMPERING_SHIFT_S(y)
y ^= (y << 15) & TEMPERING_MASK_C; // TEMPERING_SHIFT_T(y)
y ^= (y >>> 18); // TEMPERING_SHIFT_L(y)
return y >>> (32 - bits); // hope that's right!
}
/* If you've got a truly old version of Java, you can omit these
two next methods. */
private synchronized void writeObject(final ObjectOutputStream out)
throws IOException {
// just so we're synchronized.
out.defaultWriteObject();
}
private synchronized void readObject(final ObjectInputStream in)
throws IOException, ClassNotFoundException {
// just so we're synchronized.
in.defaultReadObject();
}
/** This method is missing from jdk 1.0.x and below. JDK 1.1
includes this for us, but what the heck.*/
public boolean nextBoolean() {
return next(1) != 0;
}
/** This generates a coin flip with a probability <tt>probability</tt>
of returning true, else returning false. <tt>probability</tt> must
be between 0.0 and 1.0, inclusive. Not as precise a random real
event as nextBoolean(double), but twice as fast. To explicitly
use this, remember you may need to cast to float first. */
public boolean nextBoolean(final float probability) {
if (probability < 0.0f || probability > 1.0f) {
throw new IllegalArgumentException("probability must be between 0.0"
+ " and 1.0 inclusive.");
}
if (probability == 0.0f) {
return false; // fix half-open issues
} else if (probability == 1.0f) {
return true; // fix half-open issues
}
return nextFloat() < probability;
}
/** This generates a coin flip with a probability <tt>probability</tt>
of returning true, else returning false. <tt>probability</tt> must
be between 0.0 and 1.0, inclusive. */
public boolean nextBoolean(final double probability) {
if (probability < 0.0 || probability > 1.0) {
throw new IllegalArgumentException("probability must be between 0.0"
+ " and 1.0 inclusive.");
}
if (probability == 0.0) {
return false; // fix half-open issues
} else if (probability == 1.0) {
return true; // fix half-open issues
}
return nextDouble() < probability;
}
/** This method is missing from JDK 1.1 and below. JDK 1.2
includes this for us, but what the heck. */
public int nextInt(final int n) {
if (n <= 0) {
throw new IllegalArgumentException("n must be >= 0");
}
if ((n & -n) == n) {
return (int) ((n * (long) next(31)) >> 31);
}
int bits, val;
do {
bits = next(31);
val = bits % n;
} while (bits - val + (n - 1) < 0);
return val;
}
/** This method is for completness' sake.
Returns a long drawn uniformly from 0 to n-1. Suffice it to say,
n must be > 0, or an IllegalArgumentException is raised. */
public long nextLong(final long n) {
if (n <= 0) {
throw new IllegalArgumentException("n must be >= 0");
}
long bits, val;
do {
bits = (nextLong() >>> 1);
val = bits % n;
} while (bits - val + (n - 1) < 0);
return val;
}
/** A bug fix for versions of JDK 1.1 and below. JDK 1.2 fixes
this for us, but what the heck. */
public double nextDouble() {
return (((long) next(26) << 27) + next(27))
/(double) (1L << 53);
}
/** A bug fix for versions of JDK 1.1 and below. JDK 1.2 fixes
this for us, but what the heck. */
public float nextFloat() {
return next(24)/((float) (1 << 24));
}
/** A bug fix for all versions of the JDK. The JDK appears to
use all four bytes in an integer as independent byte values!
Totally wrong. I've submitted a bug report. */
public void nextBytes(final byte[] bytes) {
for (int x = 0; x < bytes.length; x++) {
bytes[x] = (byte) next(8);
}
}
/** For completeness' sake, though it's not in java.util.Random. */
public char nextChar() {
// chars are 16-bit UniCode values
return (char) (next(16));
}
/** For completeness' sake, though it's not in java.util.Random. */
public short nextShort() {
return (short) (next(16));
}
/** For completeness' sake, though it's not in java.util.Random. */
public byte nextByte() {
return (byte) (next(8));
}
/** A bug fix for all JDK code including 1.2. nextGaussian can theoretical
* ly
ask for the log of 0 and divide it by 0! See Java bug
<a href="http://developer.java.sun.com/developer/bugParade/bugs/4254501.h
* tml">
http://developer.java.sun.com/developer/bugParade/bugs/4254501.html</a>
*/
synchronized public double nextGaussian() {
if (__haveNextNextGaussian) {
__haveNextNextGaussian = false;
return __nextNextGaussian;
} else {
double v1, v2, s;
do {
v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0
v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0
s = v1 * v1 + v2 * v2;
} while (s >= 1 || s == 0);
double multiplier = /* Strict*/ Math.sqrt(-2
* /* Strict*/ Math.log(s)/s);
__nextNextGaussian = v2 * multiplier;
__haveNextNextGaussian = true;
return v1 * multiplier;
}
}
}
: 당신이 생각하는 것 무엇에도 불구하고
Random generator = new Random();
Set<Double> numbers = new HashSet<Double>();
while (numbers.size() < n)
numbers.add(generator.nextDouble());
, 이것은 매우 빠르게 실행 : 60 밀리 초 동안을 내 (일반) PC의 100000 번호.
정말로 원하는 배열이 있으면 집합에서 추출 할 수 있습니다.
사용, 그들은에서 생성 된 질서를 유지하려는 경우 난수 생성기는 임의의 두 INT 값에서 임의의 두 배를 생성합니다 (이 유사한 성능을 가지고 있었다)
http://stackoverflow.com/questions/7291911/을 보셨습니까? –
일반적으로 좋은 의사 난수 생성기는 반복하기 전에 나타내는 모든 정수 집합을 순환합니다. Random은 48 개의 유효 비트의 내부 정수를 갖는 것으로 보입니다. –
http://stackoverflow.com/questions/453479/how-good-is-java-util-random – Cratylus