Class VectorCrossoverPipeline
- java.lang.Object
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- ec.BreedingSource
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- ec.BreedingPipeline
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- ec.vector.breed.VectorCrossoverPipeline
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- All Implemented Interfaces:
- Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable
public class VectorCrossoverPipeline extends BreedingPipeline
VectorCrossoverPipeline is a BreedingPipeline which implements a simple default crossover for VectorIndividuals. Normally it takes two individuals and returns two crossed-over child individuals. Optionally, it can take two individuals, cross them over, but throw away the second child (a one-child crossover). VectorCrossoverPipeline works by calling defaultCrossover(...) on the first parent individual.Typical Number of Individuals Produced Per produce(...) call
2 * minimum typical number of individuals produced by each source, unless tossSecondParent is set, in which case it's simply the minimum typical number.Number of Sources
2Parameters
base.toss
bool = true or false (default)/td>(after crossing over with the first new individual, should its second sibling individual be thrown away instead of adding it to the population?) Default Base
vector.xover- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field and Description static intNUM_SOURCESstatic java.lang.StringP_CROSSOVERstatic java.lang.StringP_TOSSbooleantossSecondParentShould the pipeline discard the second parent after crossing over?-
Fields inherited from class ec.BreedingPipeline
DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME
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Fields inherited from class ec.BreedingSource
NO_PROBABILITY, P_PROB, probability
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Constructor Summary
Constructors Constructor and Description VectorCrossoverPipeline()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description java.lang.Objectclone()Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.ParameterdefaultBase()Returns the default base for this prototype.intnumSources()Returns 2intproduce(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)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.voidsetup(EvolutionState state, Parameter base)Sets up the BreedingPipeline.inttypicalIndsProduced()Returns 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.-
Methods inherited from class ec.BreedingPipeline
finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, reproduce, sourcesAreProperForm
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Methods inherited from class ec.BreedingSource
getProbability, pickRandom, setProbability, setupProbabilities
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Field Detail
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P_TOSS
public static final java.lang.String P_TOSS
- See Also:
- Constant Field Values
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P_CROSSOVER
public static final java.lang.String P_CROSSOVER
- See Also:
- Constant Field Values
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NUM_SOURCES
public static final int NUM_SOURCES
- See Also:
- Constant Field Values
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tossSecondParent
public boolean tossSecondParent
Should the pipeline discard the second parent after crossing over?
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Method Detail
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defaultBase
public Parameter defaultBase()
Description copied from interface:PrototypeReturns 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(...).
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numSources
public int numSources()
Returns 2- Specified by:
numSourcesin classBreedingPipeline
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clone
public java.lang.Object clone()
Description copied from interface:PrototypeCreates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.Typically this should be a full "deep" clone. However, you may share certain elements with other objects rather than clone hem, depending on the situation:
- If you hold objects which are shared with other instances, don't clone them.
- If you hold objects which must be unique, clone them.
- If you hold objects which were given to you as a gesture of kindness, and aren't owned by you, you probably shouldn't clone them.
- DON'T attempt to clone: Singletons, Cliques, or Groups.
- Arrays are not cloned automatically; you may need to clone an array if you're not sharing it with other instances. Arrays have the nice feature of being copyable by calling clone() on them.
Implementations.
- If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are abstract, then you should not declare clone().
- If no ancestor of yours implements clone(),
and you have no need to do clone deeply,
and you are not abstract, then you should implement
it as follows:
public Object clone() { try { return super.clone(); } catch ((CloneNotSupportedException e) { throw new InternalError(); } // never happens } - If no ancestor of yours implements clone(), but you
need to deep-clone some things, then you should implement it
as follows:
public Object clone() { try { MyObject myobj = (MyObject) (super.clone()); // put your deep-cloning code here... } catch ((CloneNotSupportedException e) { throw new InternalError(); } // never happens return myobj; } - If an ancestor has implemented clone(), and you also need
to deep clone some things, then you should implement it as follows:
public Object clone() { MyObject myobj = (MyObject) (super.clone()); // put your deep-cloning code here... return myobj; }
- Specified by:
clonein interfacePrototype- Overrides:
clonein classBreedingPipeline
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setup
public void setup(EvolutionState state, Parameter base)
Description copied from class:BreedingSourceSets 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:
setupin interfacePrototype- Specified by:
setupin interfaceSetup- Overrides:
setupin classBreedingPipeline- See Also:
Prototype.setup(EvolutionState,Parameter)
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typicalIndsProduced
public int typicalIndsProduced()
Returns 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.- Overrides:
typicalIndsProducedin classBreedingPipeline
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produce
public int produce(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)Description copied from class:BreedingSourceProduces 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:
producein classBreedingSource
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