public class InternalCrossoverPipeline extends GPBreedingPipeline
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.maxdepth int >= 1 |
(maximum valid depth of the crossed-over individual's trees) |
base.ns.0 classname, inherits and != GPNodeSelector |
(GPNodeSelector for subtree 0. |
base.ns.1 classname, inherits and != GPNodeSelector, or String same |
(GPNodeSelector for subtree 1. If value is same, then ns.1 a copy of whatever ns.0 is) |
base.tree.0 0 < int < (num trees in individuals), if exists |
(first tree for the crossover; if parameter doesn't exist, tree is picked at random) |
base.tree.1 0 < int < (num trees in individuals), if exists |
(second tree for the crossover; if parameter doesn't exist, tree is picked at random. This tree must have the same GPTreeConstraints as tree.0, if tree.0 is defined.) |
Default Base
gp.breed.internal-xover
Parameter bases
base.ns.n | nodeselectn (n is 0 or 1) |
Modifier and Type | Field and Description |
---|---|
static java.lang.String |
KEY_PARENTS |
int |
maxDepth
The deepest tree the pipeline is allowed to form.
|
GPNodeSelector |
nodeselect0
How the pipeline chooses the first subtree
|
GPNodeSelector |
nodeselect1
How the pipeline chooses the second subtree
|
static int |
NUM_SOURCES |
int |
numTries
How many times the pipeline attempts to pick nodes until it gives up.
|
static java.lang.String |
P_INTERNALCROSSOVER |
static java.lang.String |
P_MAXDEPTH |
static java.lang.String |
P_NUM_TRIES |
int |
tree1
Is the first tree fixed? If not, this is -1
|
int |
tree2
Is the second tree fixed? If not, this is -1
|
P_NODESELECTOR, P_TREE, TREE_UNFIXED
DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME, V_STUB
NO_PROBABILITY, P_PROB, probability
Constructor and Description |
---|
InternalCrossoverPipeline() |
Modifier and Type | Method and Description |
---|---|
java.lang.Object |
clone()
Creates a new individual cloned from a prototype,
and suitable to begin use in its own evolutionary
context.
|
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,
java.util.ArrayList<Individual> inds,
EvolutionState state,
int thread,
java.util.HashMap<java.lang.String,java.lang.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.
|
produces
fillStubs, finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, sourcesAreProperForm, typicalIndsProduced
getProbability, pickRandom, setProbability, setupProbabilities
public static final java.lang.String P_INTERNALCROSSOVER
public static final java.lang.String P_NUM_TRIES
public static final java.lang.String P_MAXDEPTH
public static final int NUM_SOURCES
public static final java.lang.String KEY_PARENTS
public GPNodeSelector nodeselect0
public GPNodeSelector nodeselect1
public int numTries
public int maxDepth
public int tree1
public int tree2
public Parameter defaultBase()
Prototype
public int numSources()
BreedingPipeline
numSources
in class BreedingPipeline
public java.lang.Object clone()
Prototype
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:
Implementations.
public Object clone()
{
try
{
return super.clone();
}
catch ((CloneNotSupportedException e)
{ throw new InternalError(); } // never happens
}
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;
}
public Object clone()
{
MyObject myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
return myobj;
}
clone
in interface Prototype
clone
in class BreedingPipeline
public void setup(EvolutionState state, Parameter base)
BreedingSource
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}.
setup
in interface Prototype
setup
in interface Setup
setup
in class BreedingPipeline
Prototype.setup(EvolutionState,Parameter)
public int produce(int min, int max, int subpopulation, java.util.ArrayList<Individual> inds, EvolutionState state, int thread, java.util.HashMap<java.lang.String,java.lang.Object> misc)
BreedingSource
produce
in class BreedingSource