Uses of Class
org.aika.Iteration

Packages that use Iteration

Package	Description
org.aika
org.aika.corpus
org.aika.lattice
org.aika.neuron

Uses of Iteration in org.aika

Methods in org.aika that return Iteration

Modifier and Type	Method and Description
Iteration	Model.startIteration(Document doc, int threadId)

Methods in org.aika with parameters of type Iteration

Modifier and Type	Method and Description
static Activation	Activation.get(Iteration t, Node n, Activation.Key ak)
static Activation	Activation.get(Iteration t, Node n, Integer rid, Range r, Range.Relation rr, Option o, Option.Relation or)
static Activation	Activation.getNextSignal(Node n, Iteration t, int from, Integer rid, Option o, boolean dir, boolean inv)
void	Writable.readFields(DataInput in, Iteration t) Deserialize the fields of this object from in.
void	Model.readFields(DataInput in, Iteration t)
void	Activation.register(Iteration t)
static Stream<Activation>	Activation.select(Iteration t, Node n, Integer rid, Range r, Range.Relation rr, Option o, Option.Relation or)
void	Activation.unregister(Iteration t)

Uses of Iteration in org.aika.corpus

Methods in org.aika.corpus with parameters of type Iteration

Modifier and Type	Method and Description
static void	Conflicts.add(Iteration t, Activation act, Option primary, Option secondary)
void	ExpandNode.computeSelectedOption(Iteration t)
void	ExpandNode.generateInitialCandidates(Iteration t)
void	ExpandNode.generateNextLevelCandidates(Iteration t, ExpandNode selectedParent, ExpandNode excludedParent)
Stream<Activation>	Range.Relation.getActivations(Iteration t, Node n, Integer rid, Range r, Option o, Option.Relation or)
Stream<Activation>	Range.SynapseRangeMatcher.getActivations(Iteration t, Node n, Integer rid, Range r, Option o, Option.Relation or)
Stream<Activation>	Range.BeginEndMatcher.getActivations(Iteration t, Node n, Integer rid, Range r, Option o, Option.Relation or)
static void	Conflicts.remove(Iteration t, Activation act, Option primary, Option secondary)

Uses of Iteration in org.aika.lattice

Methods in org.aika.lattice with parameters of type Iteration

Modifier and Type	Method and Description
static InputNode	InputNode.add(Iteration t, Synapse.Key key, Neuron input)
void	AndNode.addActivation(Iteration t, Activation.Key ak, Collection<Activation> directInputActs)
void	InputNode.addActivation(Iteration t, Activation inputAct)
void	OrNode.addActivation(Iteration t, Integer ridOffset, Activation inputAct)
static void	Node.addActivationAndPropagate(Iteration t, Activation.Key ak, Collection<Activation> inputActs)
Activation	Node.addActivationInternal(Iteration t, Activation.Key ak, Collection<Activation> inputActs, boolean isTrainingAct)
static void	Node.addConflict(Iteration t, Option io, Option o, Activation act, Collection<Activation> inputActs, long v)
void	OrNode.addInput(Iteration t, Integer ridOffset, Node in)
static void	AndNode.addNextLevelActivation(Iteration t, Activation act, Activation secondAct, AndNode nlp, Option conflict)
void	Node.addOrChild(Iteration t, OrNode.OrEntry oe)
static boolean	Node.adjust(Iteration t, Neuron neuron, int dir)
void	OrNode.apply(Iteration t, Activation act, Option conflict)
abstract void	Node.apply(Iteration t, Activation act, Option conflict)
void	InputNode.apply(Iteration t, Activation act, Option removedConflict)
void	AndNode.apply(Iteration t, Activation act, Option removedConflict)
protected void	OrNode.changeNumberOfNeuronRefs(Iteration t, long v, int d)
protected abstract void	Node.changeNumberOfNeuronRefs(Iteration t, long v, int d)
protected void	InputNode.changeNumberOfNeuronRefs(Iteration t, long v, int d)
protected void	AndNode.changeNumberOfNeuronRefs(Iteration t, long v, int d)
void	OrNode.cleanup(Iteration t)
abstract void	Node.cleanup(Iteration t)
void	InputNode.cleanup(Iteration t)
void	AndNode.cleanup(Iteration t)
void	Node.clearActivations(Iteration t)
boolean	Node.computeAndParents(Iteration t, Integer offset, SortedSet<AndNode.Refinement> inputs, Map<AndNode.Refinement,Node> parents, boolean discoverPatterns, long v)
static SortedMap<AndNode.Refinement,Node>	AndNode.computeNextLevelParents(Iteration t, Node pa, AndNode.Refinement ref, boolean discoverPatterns)
static void	Node.computeRefinements(Iteration t, TreeSet<Node.RSKey> queue, Neuron n, Node.RSKey rsk, long v, List<Node.RSKey> outputs, List<Node.RSKey> cleanup)
void	Node.count(Iteration t)
static AndNode	AndNode.createNextLevelNode(Iteration t, Node n, AndNode.Refinement ref, boolean discoverPatterns)
void	OrNode.deleteActivation(Iteration t, Activation act)
abstract void	Node.deleteActivation(Iteration t, Activation act)
void	InputNode.deleteActivation(Iteration t, Activation act)
void	AndNode.deleteActivation(Iteration t, Activation act)
void	OrNode.discover(Iteration t, Activation act)
abstract void	Node.discover(Iteration t, Activation act)
void	InputNode.discover(Iteration t, Activation act)
void	AndNode.discover(Iteration t, Activation act)
Collection<Activation>	Node.getActivations(Iteration t)
Activation	Node.getFirstActivation(Iteration t)
Node.ThreadState	Node.getThreadState(Iteration t)
void	OrNode.initActivation(Iteration t, Activation act)
abstract void	Node.initActivation(Iteration t, Activation act)
void	InputNode.initActivation(Iteration t, Activation act)
void	AndNode.initActivation(Iteration t, Activation act)
boolean	OrNode.isAllowedOption(Iteration t, Option n, Activation act, long v)
abstract boolean	Node.isAllowedOption(Iteration t, Option n, Activation act, long v)
boolean	InputNode.isAllowedOption(Iteration t, Option n, Activation act, long v)
boolean	AndNode.isAllowedOption(Iteration t, Option n, Activation act, long v)
boolean	Node.isCovered(Iteration t, Integer offset, long v)
boolean	AndNode.isCovered(Iteration t, Integer offset, long v)
Option	OrNode.lookupOrOption(Iteration t, Range r, boolean create)
protected void	Node.postProcessRemovedActivation(Iteration t, Activation act, Collection<Activation> inputActs)
protected void	InputNode.postProcessRemovedActivation(Iteration t, Activation act, Collection<Activation> inputActs)
protected void	Node.prepareResultsForPredefinedNodes(Iteration t, TreeSet<Node.RSKey> queue, long v, List<Node.RSKey> outputs, List<Node.RSKey> cleanup, Neuron n, Synapse s, Integer offset)
protected Range	Node.preProcessAddedActivation(Iteration t, Activation.Key ak, Collection<Activation> inputActs)
protected Range	InputNode.preProcessAddedActivation(Iteration t, Activation.Key ak, Collection<Activation> inputActs)
protected Range	AndNode.preProcessAddedActivation(Iteration t, Activation.Key ak, Collection<Activation> inputActs)
void	Node.processAddedActivation(Iteration t, Activation.Key ak, Collection<Activation> inputActs)
static void	OrNode.processCandidate(Iteration t, Node parentNode, Activation inputAct, boolean train)
void	Node.processChanges(Iteration t)
void	Node.processRemovedActivation(Iteration t, Activation act, Collection<Activation> inputActs)
void	OrNode.propagateAddedActivation(Iteration t, Activation act, Option removedConflict)
abstract void	Node.propagateAddedActivation(Iteration t, Activation act, Option conflict)
void	InputNode.propagateAddedActivation(Iteration t, Activation act, Option removedConflict)
void	AndNode.propagateAddedActivation(Iteration t, Activation act, Option removedConflict)
void	OrNode.propagateRemovedActivation(Iteration t, Activation act)
abstract void	Node.propagateRemovedActivation(Iteration t, Activation act)
void	InputNode.propagateRemovedActivation(Iteration t, Activation act)
void	AndNode.propagateRemovedActivation(Iteration t, Activation act)
static OrNode.OrEntry	OrNode.OrEntry.read(DataInput in, Iteration t)
static Node	Node.read(DataInput in, Iteration t)
static AndNode.Refinement	AndNode.Refinement.read(DataInput in, Iteration t)
void	OrNode.readFields(DataInput in, Iteration t)
void	OrNode.OrEntry.readFields(DataInput in, Iteration t)
void	Node.readFields(DataInput in, Iteration t)
void	InputNode.readFields(DataInput in, Iteration t)
void	AndNode.readFields(DataInput in, Iteration t)
void	AndNode.Refinement.readFields(DataInput in, Iteration t)
void	OrNode.remove(Iteration t)
void	Node.remove(Iteration t)
void	InputNode.remove(Iteration t)
void	AndNode.remove(Iteration t)
void	InputNode.removeActivation(Iteration t, Activation inputAct)
protected static void	AndNode.removeActivation(Iteration t, Activation iAct)
void	OrNode.removeActivation(Iteration t, Integer ridOffset, Activation inputAct)
static void	Node.removeActivationAndPropagate(Iteration t, Activation act, Collection<Activation> inputActs)
boolean	Node.removeActivationInternal(Iteration t, Activation act, Collection<Activation> inputActs)
void	OrNode.removeAllInputs(Iteration t)
static void	Node.removeConflict(Iteration t, Option io, Option o, Activation act, Activation nAct, long v)
void	Node.removeFromNextLevel(Iteration t, Activation iAct)
void	OrNode.removeInput(Iteration t, Integer ridOffset, Node in)
void	Node.removeOrChild(Iteration t, OrNode.OrEntry oe)
void	InputNode.setSynapse(Iteration t, InputNode.SynapseKey sk, Synapse s)
void	OrNode.updateActivation(Iteration t, Range inputR, Integer rid)
void	AndNode.updateWeight(Iteration t, long v)

Constructors in org.aika.lattice with parameters of type Iteration

Constructor and Description
AndNode(Iteration t, int level, SortedMap<AndNode.Refinement,Node> parents)
InputNode(Iteration t, Synapse.Key key)
Node(Iteration t, int level)
OrNode(Iteration t)

Uses of Iteration in org.aika.neuron

Methods in org.aika.neuron with parameters of type Iteration

Modifier and Type	Method and Description
void	InputNeuron.addInput(Iteration t, int begin, int end)
void	InputNeuron.addInput(Iteration t, int begin, int end, Integer rid)
void	InputNeuron.addInput(Iteration t, int begin, int end, Integer rid, Option o)
void	InputNeuron.addInput(Iteration t, int begin, int end, Option o)
void	Neuron.computeErrorSignal(Iteration t, Activation act)
void	Neuron.count(Iteration t)
static InputNeuron	InputNeuron.create(Iteration t, InputNeuron n)
static Neuron	Neuron.create(Iteration t, Neuron n, double bias, double negDirSum, double negRecSum, double posRecSum, Set<Synapse> inputs)
void	Synapse.link(Iteration t)
void	Neuron.propagateAddedActivation(Iteration t, Activation act)
void	InputNeuron.propagateAddedActivation(Iteration t, Activation act)
void	Neuron.propagateRemovedActivation(Iteration t, Activation act)
void	Neuron.publish(Iteration t)
static Synapse	Synapse.read(DataInput in, Iteration t)
static Synapse.Key	Synapse.Key.read(DataInput in, Iteration t)
static Neuron	Neuron.read(DataInput in, Iteration t)
void	Synapse.readFields(DataInput in, Iteration t)
void	Synapse.Key.readFields(DataInput in, Iteration t)
void	Neuron.readFields(DataInput in, Iteration t)
void	Neuron.remove(Iteration t)
void	InputNeuron.remove(Iteration t)
void	InputNeuron.removeInput(Iteration t, int begin, int end)
void	InputNeuron.removeInput(Iteration t, int begin, int end, Integer rid)
void	InputNeuron.removeInput(Iteration t, int begin, int end, Integer rid, Option o)
void	InputNeuron.removeInput(Iteration t, int begin, int end, Option o)
void	Neuron.train(Iteration t, Activation act)
void	Neuron.train(Iteration t, Activation iAct, Integer rid, double x, long v)
void	Neuron.unpublish(Iteration t)