Package ec.gp.breed

# Class RehangPipeline

java.lang.Object
ec.BreedingSource
ec.BreedingPipeline
ec.gp.GPBreedingPipeline
ec.gp.breed.RehangPipeline

All Implemented Interfaces:
  `Prototype`, `Setup`, `SteadyStateBSourceForm`, `RandomChoiceChooserD`, `Serializable`, `Cloneable`

public class RehangPipeline extends GPBreedingPipeline
RehangPipeline picks a nonterminal node other than the root and "rehangs" it as a new root. Imagine if the tree were nodes connected with string. Grab the new node and pick it up, letting the other nodes hang underneath it as a new "root". That's in effect what you're doing.

Important Note: Because it must be free of any constraints by nature, RehangPipeline does not work with strong typing. You must not have more than one type defined in order to use RehangPipeline.

RehangPipeline picks a random tree, then picks randomly from all the nonterminals in the tree other than the root, and rehangs the chosen nonterminal as the new root. If its chosen tree has no nonterminals, it repeats the choose-tree process. If after tries times it has failed to find a tree with nonterminals (other than the root), it gives up and simply copies the individual. As you might guess, determining if a tree has nonterminals is very fast, so tries can be pretty large with little to no detriment to evolution speed.

"Rehanging" is complicated to describe. First, you pick a random child of your chosen nonterminal n, and remove this subtree from the tree. Call this subtree T. Next, you set the nonterminal as a new root; its former parent p now fills the slot left behind by the missing subtree. The p's former parent q now fills the slot left behind by n. q's former parent r now fills the slot left behind by p, and so on. This proceeds all the way up to the old root, which will be left with one empty slot (where its former child was that is now its new parent). This slot is then filled with T

Typical Number of Individuals Produced Per `produce(...)` call
...as many as the source produces

Number of Sources
1

Parameters

base.`tries` int >= 1 | (number of times to try finding valid pairs of nodes)
base.`tree.0` 0 < int < (num trees in individuals), if exists | (tree chosen for mutation; if parameter doesn't exist, tree is picked at random)

Default Base
gp.breed.rehang

See Also:
  - Serialized Form

- ## Field Summary

  Fields
  Modifier and Type
  Field
  Description
  `static final int`
  `NUM_SOURCES`
  `static final String`
  `P_NUM_TRIES`
  `static final String`
  `P_REHANG`

  ### Fields inherited from class ec.gp.GPBreedingPipeline

  `P_NODESELECTOR, P_TREE, TREE_UNFIXED`

  ### Fields inherited from class ec.BreedingPipeline

  `DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME, V_STUB`

  ### Fields inherited from class ec.BreedingSource

  `NO_PROBABILITY, P_PROB, probability`

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `RehangPipeline()`

- ## Method Summary

  Modifier and Type
  Method
  Description
  `Parameter`
  `defaultBase()`
  Returns the default base for this prototype.
  `int`
  `numSources()`
  Returns the number of sources to this pipeline.
  `int`
  `produce(int min, int max, int subpopulation, ArrayList<Individual> inds, EvolutionState state, int thread, HashMap<String,Object> misc)`
  Produces n individuals from the given subpopulation and puts them into inds[start...start+n-1], where n = Min(Max(q,min),max), where q is the "typical" number of individuals the BreedingSource produces in one shot, and returns n.
  `void`
  `setup(EvolutionState state, Parameter base)`
  Sets up the BreedingPipeline.

  ### Methods inherited from class ec.gp.GPBreedingPipeline

  `produces`

  ### Methods inherited from class ec.BreedingPipeline

  `clone, fillStubs, finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, sourcesAreProperForm, typicalIndsProduced`

  ### Methods inherited from class ec.BreedingSource

  `getProbability, pickRandom, setProbability, setupProbabilities`

  ### Methods inherited from class java.lang.Object

  `equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- ## Field Details

  - ### P_REHANG

    public static final String P_REHANG
    See Also:
      - Constant Field Values

  - ### P_NUM_TRIES

    public static final String P_NUM_TRIES
    See Also:
      - Constant Field Values

  - ### NUM_SOURCES

    public static final int NUM_SOURCES
    See Also:
      - Constant Field Values

- ## Constructor Details

  - ### RehangPipeline

    public RehangPipeline()

- ## Method Details

  - ### defaultBase

    public Parameter defaultBase()
    Description copied from interface: `Prototype`
    Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).

  - ### numSources

    public int numSources()
    Description copied from class: `BreedingPipeline`
    Returns the number of sources to this pipeline. Called during BreedingPipeline's setup. Be sure to return a value > 0, or DYNAMIC_SOURCES which indicates that setup should check the parameter file for the parameter "num-sources" to make its determination.
    Specified by:
      `numSources` in class `BreedingPipeline`

  - ### setup

    public void setup(EvolutionState state, Parameter base)
    Description copied from class: `BreedingSource`
    Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

    The most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.

    Specified by:
      `setup` in interface `Prototype`
    Specified by:
      `setup` in interface `Setup`
    Overrides:
      `setup` in class `BreedingPipeline`
    See Also:
      - `Prototype.setup(EvolutionState,Parameter)`

  - ### produce

    public int produce(int min, int max, int subpopulation, ArrayList<Individual> inds, EvolutionState state, int thread, HashMap<String,Object> misc)
    Description copied from class: `BreedingSource`
    Produces n individuals from the given subpopulation and puts them into inds[start...start+n-1], where n = Min(Max(q,min),max), where q is the "typical" number of individuals the BreedingSource produces in one shot, and returns n. max must be >= min, and min must be >= 1. For example, crossover might typically produce two individuals, tournament selection might typically produce a single individual, etc.
    Specified by:
      `produce` in class `BreedingSource`