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java.lang.Objectorg.apache.commons.math.random.RandomDataImpl
public class RandomDataImpl
Implements the RandomData interface using a RandomGenerator
instance to generate non-secure data and a SecureRandom
instance to provide data for the nextSecureXxx methods. If no
RandomGenerator is provided in the constructor, the default is
to use a generator based on Random. To plug in a different
implementation, either implement RandomGenerator directly or
extend AbstractRandomGenerator.
Supports reseeding the underlying pseudo-random number generator (PRNG). The
SecurityProvider and Algorithm used by the
SecureRandom instance can also be reset.
For details on the default PRNGs, see Random and
SecureRandom.
Usage Notes:
RandomGenerator and
SecureRandom instances used in data generation. Therefore, to
generate a random sequence of values or strings, you should use just
one RandomDataImpl instance repeatedly.RandomDataImpl is created, the underlying random
number generators are not intialized. If you do not
explicitly seed the default non-secure generator, it is seeded with the
current time in milliseconds on first use. The same holds for the secure
generator. If you provide a RandomGenerator to the constructor,
however, this generator is not reseeded by the constructor nor is it reseeded
on first use.reSeed and reSeedSecure methods delegate to the
corresponding methods on the underlying RandomGenerator and
SecureRandom instances. Therefore, reSeed(long)
fully resets the initial state of the non-secure random number generator (so
that reseeding with a specific value always results in the same subsequent
random sequence); whereas reSeedSecure(long) does not
reinitialize the secure random number generator (so secure sequences started
with calls to reseedSecure(long) won't be identical).
| Constructor Summary | |
|---|---|
RandomDataImpl()
Construct a RandomDataImpl. |
|
RandomDataImpl(RandomGenerator rand)
Construct a RandomDataImpl using the supplied RandomGenerator as
the source of (non-secure) random data. |
|
| Method Summary | |
|---|---|
double |
nextExponential(double mean)
Returns a random value from an Exponential distribution with the given mean. |
double |
nextGaussian(double mu,
double sigma)
Generate a random value from a Normal (a.k.a. |
String |
nextHexString(int len)
Generates a random string of hex characters of length len. |
int |
nextInt(int lower,
int upper)
Generate a random int value uniformly distributed between lower and upper, inclusive. |
long |
nextLong(long lower,
long upper)
Generate a random long value uniformly distributed between lower and upper, inclusive. |
int[] |
nextPermutation(int n,
int k)
Generates an integer array of length k whose entries are
selected randomly, without repetition, from the integers
0 through n-1 (inclusive). |
long |
nextPoisson(double mean)
Generates a random value from the Poisson distribution with the given mean. |
Object[] |
nextSample(Collection<?> c,
int k)
Uses a 2-cycle permutation shuffle to generate a random permutation. |
String |
nextSecureHexString(int len)
Generates a random string of hex characters from a secure random sequence. |
int |
nextSecureInt(int lower,
int upper)
Generate a random int value uniformly distributed between lower and upper, inclusive. |
long |
nextSecureLong(long lower,
long upper)
Generate a random long value uniformly distributed between lower and upper, inclusive. |
double |
nextUniform(double lower,
double upper)
Generates a uniformly distributed random value from the open interval ( lower,upper) (i.e., endpoints excluded). |
void |
reSeed()
Reseeds the random number generator with the current time in milliseconds. |
void |
reSeed(long seed)
Reseeds the random number generator with the supplied seed. |
void |
reSeedSecure()
Reseeds the secure random number generator with the current time in milliseconds. |
void |
reSeedSecure(long seed)
Reseeds the secure random number generator with the supplied seed. |
void |
setSecureAlgorithm(String algorithm,
String provider)
Sets the PRNG algorithm for the underlying SecureRandom instance using the Security Provider API. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public RandomDataImpl()
public RandomDataImpl(RandomGenerator rand)
RandomGenerator as
the source of (non-secure) random data.
rand - the source of (non-secure) random data| Method Detail |
|---|
public String nextHexString(int len)
len.
The generated string will be random, but not cryptographically
secure. To generate cryptographically secure strings, use
nextSecureHexString
Preconditions:
len > 0 (otherwise an IllegalArgumentException
is thrown.)Algorithm Description: hex strings are generated using a 2-step process.
nextHexString in interface RandomDatalen - the desired string length.
public int nextInt(int lower,
int upper)
lower and upper, inclusive.
nextInt in interface RandomDatalower - the lower bound.upper - the upper bound.
public long nextLong(long lower,
long upper)
lower and upper, inclusive.
nextLong in interface RandomDatalower - the lower bound.upper - the upper bound.
public String nextSecureHexString(int len)
If cryptographic security is not required,
use nextHexString().
Preconditions:
len > 0 (otherwise an IllegalArgumentException
is thrown.)Algorithm Description: hex strings are generated in 40-byte segments using a 3-step process.
SecureRandom.
nextSecureHexString in interface RandomDatalen - the length of the generated string
public int nextSecureInt(int lower,
int upper)
lower and upper, inclusive. This algorithm uses
a secure random number generator.
nextSecureInt in interface RandomDatalower - the lower bound.upper - the upper bound.
public long nextSecureLong(long lower,
long upper)
lower and upper, inclusive. This algorithm uses
a secure random number generator.
nextSecureLong in interface RandomDatalower - the lower bound.upper - the upper bound.
public long nextPoisson(double mean)
Definition: Poisson Distribution
Preconditions:
Algorithm Description:
nextPoisson in interface RandomDatamean - mean of the Poisson distribution.
public double nextGaussian(double mu,
double sigma)
mu and the given standard deviation,
sigma.
nextGaussian in interface RandomDatamu - the mean of the distributionsigma - the standard deviation of the distribution
public double nextExponential(double mean)
Algorithm Description: Uses the Inversion Method to generate exponentially distributed random values from uniform deviates.
nextExponential in interface RandomDatamean - the mean of the distribution
public double nextUniform(double lower,
double upper)
lower,upper) (i.e., endpoints excluded).
Definition:
Uniform Distribution lower and
upper - lower are the
location and scale parameters, respectively.
Preconditions:
lower < upper (otherwise an IllegalArgumentException
is thrown.)Algorithm Description: scales the output of Random.nextDouble(), but rejects 0 values (i.e., will generate another random double if Random.nextDouble() returns 0). This is necessary to provide a symmetric output interval (both endpoints excluded).
nextUniform in interface RandomDatalower - the lower bound.upper - the upper bound.
public void reSeed(long seed)
Will create and initialize if null.
seed - the seed value to usepublic void reSeedSecure()
Will create and initialize if null.
public void reSeedSecure(long seed)
Will create and initialize if null.
seed - the seed value to usepublic void reSeed()
public void setSecureAlgorithm(String algorithm,
String provider)
throws NoSuchAlgorithmException,
NoSuchProviderException
USAGE NOTE: This method carries significant overhead and may take several seconds to execute.
algorithm - the name of the PRNG algorithmprovider - the name of the provider
NoSuchAlgorithmException - if the specified algorithm is not available
NoSuchProviderException - if the specified provider is not installed
public int[] nextPermutation(int n,
int k)
k whose entries are
selected randomly, without repetition, from the integers
0 through n-1 (inclusive).
Generated arrays represent permutations of n taken
k at a time.
Preconditions:
k <= nn > 0Uses a 2-cycle permutation shuffle. The shuffling process is described here.
nextPermutation in interface RandomDatan - domain of the permutation (must be positive)k - size of the permutation (must satisfy 0 < k <= n).
public Object[] nextSample(Collection<?> c,
int k)
c.size() and
then returns the elements whose indexes correspond to the elements of the
generated permutation. This technique is described, and proven to
generate random samples,
here
nextSample in interface RandomDatac - Collection to sample from.k - sample size.
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