Documentation of 'ec.select.MultiSelection' Java class
MultiSelection
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ec.select

Class MultiSelection

  • All Implemented Interfaces:
    Prototype, Setup, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable

    public class MultiSelection
extends SelectionMethod
    MultiSelection is a SelectionMethod which stores some n subordinate SelectionMethods. Each time it must produce an individual, it picks one of these SelectionMethods at random and has it do the production instead.

    Typical Number of Individuals Produced Per produce(...) call
    Always 1.

    Parameters

    base.num-selects
    int >= 1    		 (The number of subordinate SelectionMethods)
    base.select.n
    classname, inherits and != SelectionMethod
    		(Subordinate SelectionMethod n)

    Default Base
    select.multiselect

    Parameter bases

    base.select.n
    		Subordinate SelectionMethod n
    See Also:
    Serialized Form

    • Constructor Detail

      • MultiSelection

        public MultiSelection()

    • Method Detail

      • 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(...).

      • clone

        public java.lang.Object clone()
        Description copied from interface: Prototype
        Creates 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:
        clone in interface Prototype
        Overrides:
        clone in class BreedingSource

      • 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 BreedingSource
        See Also:
        Prototype.setup(EvolutionState,Parameter)

      • produces

        public boolean produces(EvolutionState state,
                        Population newpop,
                        int subpopulation,
                        int thread)
        Description copied from class: SelectionMethod
        A default version of produces -- this method always returns true under the assumption that the selection method works with all Fitnesses. If this isn't the case, you should override this to return your own assessment.
        Overrides:
        produces in class SelectionMethod

      • produce

        public int produce(int subpopulation,
                   EvolutionState state,
                   int thread)
        Description copied from class: SelectionMethod
        An alternative form of "produce" special to Selection Methods; selects an individual from the given subpopulation and returns its position in that subpopulation.
        Specified by:
        produce in class SelectionMethod

      • produce

        public int produce(int min,
                   int max,
                   int start,
                   int subpopulation,
                   Individual[] inds,
                   EvolutionState state,
                   int thread)
        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.
        Overrides:
        produce in class SelectionMethod

      • preparePipeline

        public void preparePipeline(java.lang.Object hook)
        Description copied from class: BreedingSource
        A hook which should be passed to all your subsidiary breeding sources. The default does this for you already, so ordinarily you don't need to change anything. If you are a BreedingPipeline and you implement your sources in a way different than using the sources[] array, be sure to override this method so that it calls preparePipeline(hook) on all of your sources.

        ECJ at present does not custom-implement or call this method: it's available for you. Becuase it has custom functionality, this method might get called more than once, and by various objects as needed. If you use it, you should determine somehow how to use it to send information under the assumption that it might be sent by nested items in the pipeline; you don't want to scribble over each other's calls! Note that this method should travel *all* breeding source paths regardless of whether or not it's redundant to do so.

        Overrides:
        preparePipeline in class BreedingSource
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