Class PowerLawDistribution
- java.lang.Object
- 
- org.apache.tinkerpop.gremlin.algorithm.generator.PowerLawDistribution
 
- 
- All Implemented Interfaces:
- Distribution
 
 public class PowerLawDistribution extends Object implements Distribution Generates values according to a scale-free distribution with the configured gamma value.- Author:
- Matthias Broecheler (me@matthiasb.com)
 
- 
- 
Constructor SummaryConstructors Constructor Description PowerLawDistribution(double gamma)Constructs a new scale-free distribution for the provided gamma value.
 - 
Method SummaryAll Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static intgetValue(Random random, double multiplier, double beta)Distributioninitialize(int invocations, int expectedTotal)Initializes the distribution such that expectedTotal is equal to the expected sum of generated values after the given number of invocatiosn.intnextConditionalValue(Random random, int otherValue)Returns the next value conditional on another given value.intnextValue(Random random)Returns the next value.StringtoString()
 
- 
- 
- 
Method Detail- 
initializepublic Distribution initialize(int invocations, int expectedTotal) Description copied from interface:DistributionInitializes the distribution such that expectedTotal is equal to the expected sum of generated values after the given number of invocatiosn. Since most distributions have an element of randomness, these values are the expected values.- Specified by:
- initializein interface- Distribution
- Returns:
- A new distribution configured to match the expected total for the number of invocations.
 
 - 
nextValuepublic int nextValue(Random random) Description copied from interface:DistributionReturns the next value. If this value is randomly generated, the randomness must be drawn from the provided random generator. DO NOT use your own internal random generator as this makes the generated values non-reproducible and leads to faulty behavior.- Specified by:
- nextValuein interface- Distribution
- Parameters:
- random- random generator to use for randomness
- Returns:
- next value
 
 - 
nextConditionalValuepublic int nextConditionalValue(Random random, int otherValue) Description copied from interface:DistributionReturns the next value conditional on another given value. This can be used, for instance, to define conditional degree distributions where the in-degree is conditional on the out-degree. If this value is randomly generated, the randomness must be drawn from the provided random generator. DO NOT use your own internal random generator as this makes the generated values non-reproducible and leads to faulty behavior.- Specified by:
- nextConditionalValuein interface- Distribution
- Parameters:
- random- random generator to use for randomness
- otherValue- The prior value
- Returns:
- next value
 
 - 
getValuepublic static int getValue(Random random, double multiplier, double beta) 
 
- 
 
-