EnumeratedDistribution.Sampler (Apache Commons Math 4.0-SNAPSHOT)

java.lang.Object
- org.apache.commons.math4.legacy.distribution.EnumeratedDistribution.Sampler

Enclosing class:

EnumeratedDistribution<T>
```
public class EnumeratedDistribution.Sampler
extends Object
```
Sampler functionality.
- The cumulative probability distribution is created (and sampled from) using the input order of the constructor arguments: A different input order will create a different sequence of samples. The samples will only be reproducible with the same RNG starting from the same RNG state and the same input order to constructor.
- The minimum supported probability is 2^-53.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`T`	`sample()`	Generates a random value sampled from this distribution.
`Object[]`	`sample(int sampleSize)`	Generates a random sample from the distribution.
`T[]`	`sample(int sampleSize, T[] array)`	Generates a random sample from the distribution.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - sample
```
public T sample()
```
    Generates a random value sampled from this distribution.
    
    Returns:
    
    a random value.
  - sample
```
public Object[] sample(int sampleSize)
                throws NotStrictlyPositiveException
```
    Generates a random sample from the distribution.
    
    Parameters:
    
    sampleSize - the number of random values to generate.
    
    Returns:
    
    an array representing the random sample.
    
    Throws:
    
    NotStrictlyPositiveException - if sampleSize is not positive.
  - sample
```
public T[] sample(int sampleSize,
                  T[] array)
           throws NotStrictlyPositiveException
```
    Generates a random sample from the distribution.
    If the requested samples fit in the specified array, it is returned therein. Otherwise, a new array is allocated with the runtime type of the specified array and the size of this collection.
    
    Parameters:
    
    sampleSize - the number of random values to generate.
    
    array - the array to populate.
    
    Returns:
    
    an array representing the random sample.
    
    Throws:
    
    NotStrictlyPositiveException - if sampleSize is not positive.
    
    NullArgumentException - if array is null