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## Uses of Class
cc.mallet.grmm.types.Assignment

Packages that use Assignment
cc.mallet.grmm.inference |
cc.mallet.grmm.inference.gbp |
cc.mallet.grmm.learning |
cc.mallet.grmm.types |
cc.mallet.grmm.util |

Uses of Assignment in cc.mallet.grmm.inference

Methods in cc.mallet.grmm.inference that return Assignment
`Assignment` | `TRP.bestAssignment()`
`Assignment` | `Sampler.sample(FactorGraph mdl, int N)` Samples from the distribution of a given undirected model.
`Assignment` | `GibbsSampler.sample(FactorGraph mdl, int N)`
`Assignment` | `ExactSampler.sample(FactorGraph mdl, int N)`

Methods in cc.mallet.grmm.inference with parameters of type Assignment
`double` | `JunctionTree.dumpLogJoint(Assignment assn)`
`double` | `JunctionTreeInferencer.dumpLogJoint(Assignment assn)`
`double` | `AbstractInferencer.lookupJoint(Assignment assn)`
`double` | `Inferencer.lookupJoint(Assignment assn)` Returns the joint probability of a given assignment, computed in some factorized fashion.
`double` | `BruteForceInferencer.lookupJoint(Assignment assn)`
`double` | `AbstractBeliefPropagation.lookupLogJoint(Assignment assn)`
`double` | `AbstractInferencer.lookupLogJoint(Assignment assn)`
`double` | `JunctionTree.lookupLogJoint(Assignment assn)`
`double` | `Inferencer.lookupLogJoint(Assignment assn)` Returns the natural logarithm of the joint probability of a given assignment, computed in some factorized fashion.
`double` | `JunctionTreeInferencer.lookupLogJoint(Assignment assn)`
`double` | `BruteForceInferencer.lookupLogJoint(Assignment assn)`
`double` | `AbstractInferencer.query(FactorGraph mdl, Assignment assn)`
`double` | `Inferencer.query(FactorGraph mdl, Assignment assn)` Computes the marginal probability of a given assignment to a small number of model variables.

Uses of Assignment in cc.mallet.grmm.inference.gbp

Methods in cc.mallet.grmm.inference.gbp with parameters of type Assignment
`double` | `ParentChildGBP.lookupLogJoint(Assignment assn)`

Uses of Assignment in cc.mallet.grmm.learning

Methods in cc.mallet.grmm.learning that return Assignment
`Assignment` | `ACRF.bestAssignment(Instance inst)`
`protected Assignment` | `ACRF.Template.computeAssignment(Assignment graphAssn, VarSet vs)`
`Assignment` | `ACRF.UnrolledGraph.getAssignment()` Returns an Assignment object that corresponds to the LabelSequence for which this graph was unrolled.
`Assignment` | `ACRF.UnrolledVarSet.lookupAssignment()`

Methods in cc.mallet.grmm.learning with parameters of type Assignment
`protected Assignment` | `ACRF.Template.computeAssignment(Assignment graphAssn, VarSet vs)`
`int` | `ACRF.UnrolledVarSet.lookupNumberOfAssignment(Assignment assn)`

Uses of Assignment in cc.mallet.grmm.types

Methods in cc.mallet.grmm.types that return Assignment
`Assignment` | `AssignmentIterator.assignment()`
`Assignment` | `Assignment.getRow(int ridx)`
`static Assignment` | `Assignment.makeFromSingleIndex(VarSet clique, int idx)`
`static Assignment` | `Assignment.restriction(Assignment assn, VarSet varSet)` Deprecated. marginalize
`Assignment` | `SkeletonFactor.sample(Randoms r)`
`Assignment` | `CPT.sample(Randoms r)`
`Assignment` | `UniNormalFactor.sample(Randoms r)`
`Assignment` | `Factor.sample(Randoms r)` Return an assignment sampled from this factor, interpreting it as an unnormalized probability distribution.
`Assignment` | `NormalFactor.sample(Randoms r)`
`Assignment` | `BoltzmannUnaryFactor.sample(Randoms r)`
`Assignment` | `AbstractTableFactor.sample(Randoms r)`
`Assignment` | `ConstantFactor.sample(Randoms r)`
`Assignment` | `FactorGraph.sample(Randoms r)`
`Assignment` | `UniformFactor.sample(Randoms r)`
`Assignment` | `BinaryUnaryFactor.sample(Randoms r)`
`Assignment` | `PottsTableFactor.sample(Randoms r)`
`Assignment` | `Assignment.sample(Randoms r)`
`Assignment` | `BoltzmannPairFactor.sample(Randoms r)`
`Assignment` | `BetaFactor.sample(Randoms r)`
`Assignment` | `AbstractFactor.sample(Randoms r)`
`Assignment` | `FactorGraph.sampleContinuousVars(Randoms r)` Samples the continuous variables in this factor graph.
`Assignment` | `Assignment.subAssn(int start, int end)`
`static Assignment` | `Assignment.union(Assignment assn1, Assignment assn2)` Returns the union of two Assignments.

Methods in cc.mallet.grmm.types with parameters of type Assignment
`void` | `Assignment.addRow(Assignment other)`
`double` | `FactorGraph.factorProduct(Assignment assn)` Returns the unnormalized probability for an assignment to the model.
`double` | `CPT.logValue(Assignment assn)`
`double` | `Factor.logValue(Assignment assn)`
`double` | `LogTableFactor.logValue(Assignment assn)`
`double` | `FactorGraph.logValue(Assignment assn)`
`double` | `TableFactor.logValue(Assignment assn)`
`double` | `AbstractFactor.logValue(Assignment assn)`
`void` | `FactorGraph.printAsDot(java.io.PrintWriter out, Assignment assn)`
`protected double` | `LogTableFactor.rawValue(Assignment assn)`
`protected double` | `TableFactor.rawValue(Assignment assn)`
`static Assignment` | `Assignment.restriction(Assignment assn, VarSet varSet)` Deprecated. marginalize
`double` | `PottsTableFactor.secondDerivative(Factor q, Variable param, Assignment theta)`
`abstract void` | `AbstractTableFactor.setLogValue(Assignment assn, double logValue)` Use of this method is discouraged.
`void` | `LogTableFactor.setLogValue(Assignment assn, double logValue)`
`void` | `TableFactor.setLogValue(Assignment assn, double logValue)`
`void` | `AbstractTableFactor.setRawValue(Assignment assn, double value)`
`void` | `Assignment.setRow(int ridx, Assignment other)`
`protected abstract Factor` | `AbstractTableFactor.slice_general(Variable[] vars, Assignment observed)`
`protected Factor` | `LogTableFactor.slice_general(Variable[] vars, Assignment observed)`
`protected Factor` | `TableFactor.slice_general(Variable[] vars, Assignment observed)`
`protected abstract Factor` | `AbstractTableFactor.slice_onevar(Variable var, Assignment observed)`
`protected Factor` | `LogTableFactor.slice_onevar(Variable var, Assignment observed)`
`protected Factor` | `TableFactor.slice_onevar(Variable var, Assignment observed)` Creates a new potential from another by restricting it to a given assignment.
`protected abstract Factor` | `AbstractTableFactor.slice_twovar(Variable v1, Variable v2, Assignment observed)`
`protected Factor` | `LogTableFactor.slice_twovar(Variable v1, Variable v2, Assignment observed)`
`protected Factor` | `TableFactor.slice_twovar(Variable v1, Variable v2, Assignment observed)`
`Factor` | `SkeletonFactor.slice(Assignment assn)`
`Factor` | `CPT.slice(Assignment assn)`
`Factor` | `UniNormalFactor.slice(Assignment assn)`
`Factor` | `Factor.slice(Assignment assn)`
`Factor` | `NormalFactor.slice(Assignment assn)`
`Factor` | `BoltzmannUnaryFactor.slice(Assignment assn)`
`Factor` | `AbstractTableFactor.slice(Assignment assn)` Creates a new potential that is equal to this one, restricted to a given assignment.
`Factor` | `ConstantFactor.slice(Assignment assn)`
`Factor` | `FactorGraph.slice(Assignment assn)`
`Factor` | `UniformFactor.slice(Assignment assn)`
`Factor` | `BinaryUnaryFactor.slice(Assignment assn)`
`Factor` | `PottsTableFactor.slice(Assignment assn)`
`Factor` | `Assignment.slice(Assignment assn)`
`Factor` | `BoltzmannPairFactor.slice(Assignment assn)`
`Factor` | `BetaFactor.slice(Assignment assn)`
`Factor` | `FactorGraph.slice(Assignment assn, java.util.Map toSlicedMap)`
`double` | `ParameterizedFactor.sumGradLog(Factor q, Variable param, Assignment assn)` Computes the expected derivative of the log factor value.
`double` | `BoltzmannUnaryFactor.sumGradLog(Factor q, Variable param, Assignment paramAssn)`
`double` | `BinaryUnaryFactor.sumGradLog(Factor q, Variable param, Assignment paramAssn)`
`double` | `PottsTableFactor.sumGradLog(Factor q, Variable param, Assignment theta)`
`double` | `BoltzmannPairFactor.sumGradLog(Factor q, Variable param, Assignment paramAssn)`
`static Assignment` | `Assignment.union(Assignment assn1, Assignment assn2)` Returns the union of two Assignments.
`double` | `CPT.value(Assignment assn)`
`double` | `UniNormalFactor.value(Assignment assn)`
`double` | `Factor.value(Assignment assn)` Returns the value of the local function for a given assignment.
`double` | `NormalFactor.value(Assignment assn)`
`abstract double` | `AbstractTableFactor.value(Assignment assn)`
`double` | `LogTableFactor.value(Assignment assn)`
`double` | `FactorGraph.value(Assignment assn)` FACTOR IMPLEMENTATION
`double` | `UniformFactor.value(Assignment assn)`
`double` | `TableFactor.value(Assignment assn)`
`double` | `BetaFactor.value(Assignment assn)`
`double` | `AbstractFactor.value(Assignment assn)`

Uses of Assignment in cc.mallet.grmm.util

Subclasses of Assignment in cc.mallet.grmm.util
`class` | `LabelsAssignment` A special kind of assignment for Variables that can be arranged in a LabelsSequence.

Methods in cc.mallet.grmm.util that return Assignment
`static Assignment` | `Models.bestAssignment(FactorGraph mdl, Inferencer inf)` Returns the highest-score Assignment in a model according to a given inferencer.
`static Assignment` | `ModelReader.readFromMatrix(VarSet vars, java.io.Reader in)`

Methods in cc.mallet.grmm.util with parameters of type Assignment
`static FactorGraph` | `Models.addEvidence(FactorGraph mdl, Assignment assn)` Returns a new factor graph, the same as a given one, except that all the nodes in the given Assignment are clamped as evidence.
`static FactorGraph` | `Models.addEvidence(FactorGraph mdl, Assignment assn, java.util.Map toSlicedMap)`
`static UndirectedModel` | `Models.addEvidence(UndirectedModel mdl, Assignment assn)`
`LabelsSequence` | `LabelsAssignment.toLabelsSequence(Assignment assn)`

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