# TensorFactorStatistics2

#### trait TensorFactorStatistics2[N1 <: TensorVar, N2 <: TensorVar] extends TensorFactor2[N1, N2]

A trait for 2-neighbor Factor whose neighbors have Tensor values, and whose statistics are the outer product of those values. Only "statisticsScore" method is abstract. DotFactorWithStatistics2 is also a subclass of this.

Linear Supertypes
TensorFactor2[N1, N2], Factor2[N1, N2], Factor, Ordered[Factor], Comparable[Factor], AnyRef, Any
Known Subclasses
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Inherited
1. TensorFactorStatistics2
2. TensorFactor2
3. Factor2
4. Factor
5. Ordered
6. Comparable
7. AnyRef
8. Any
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### Type Members

1. #### type NeighborType1 = N1

Definition Classes
Factor2
2. #### type NeighborType2 = N2

Definition Classes
Factor2
3. #### type StatisticsType = Tensor

Definition Classes
TensorFactor2Factor

### Abstract Value Members

1. #### abstract def statisticsScore(t: Tensor): Double

Definition Classes
TensorFactor2

### Concrete Value Members

1. #### final def !=(arg0: AnyRef): Boolean

Definition Classes
AnyRef
2. #### final def !=(arg0: Any): Boolean

Definition Classes
Any
3. #### final def ##(): Int

Definition Classes
AnyRef → Any
4. #### def <(that: Factor): Boolean

Definition Classes
Ordered
5. #### def <=(that: Factor): Boolean

Definition Classes
Ordered
6. #### final def ==(arg0: AnyRef): Boolean

Definition Classes
AnyRef
7. #### final def ==(arg0: Any): Boolean

Definition Classes
Any
8. #### def >(that: Factor): Boolean

Definition Classes
Ordered
9. #### def >=(that: Factor): Boolean

Definition Classes
Ordered
10. #### val _1: N1

Definition Classes
TensorFactor2Factor2
11. #### val _2: N2

Definition Classes
TensorFactor2Factor2
12. #### var _hashCode: Int

Definition Classes
Factor
13. #### def addLimitedDiscreteCurrentValues1(): Unit

Definition Classes
Factor2
14. #### def addLimitedDiscreteCurrentValues12(): Unit

Definition Classes
Factor2
15. #### def addLimitedDiscreteValues1(i: Int): Unit

Definition Classes
Factor2
16. #### def addLimitedDiscreteValues12(i: Int, j: Int): Unit

Definition Classes
Factor2
17. #### final def asInstanceOf[T0]: T0

Definition Classes
Any
18. #### def assignmentScore(a: variable.Assignment): Double

The ability to score a Values object is now removed, and this is its closest alternative.

The ability to score a Values object is now removed, and this is its closest alternative.

Definition Classes
Factor2Factor
19. #### def assignmentScoreAndStatistics(a: variable.Assignment): (Double, StatisticsType)

Definition Classes
Factor
20. #### final def assignmentStatistics(a: variable.Assignment): StatisticsType

Return this Factor's sufficient statistics for the values in the Assignment.

Return this Factor's sufficient statistics for the values in the Assignment.

Definition Classes
Factor2Factor
21. #### def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
22. #### def compare(that: Factor): Int

Return an object that can iterate over all value assignments to the neighbors of this Factor

Return an object that can iterate over all value assignments to the neighbors of this Factor

Definition Classes
Factor → Ordered
23. #### def compareTo(that: Factor): Int

Definition Classes
Ordered → Comparable
24. #### def currentAssignment: Assignment2[N1, N2]

Return a record of the current values of this Factor's neighbors.

Return a record of the current values of this Factor's neighbors.

Definition Classes
Factor2Factor
25. #### def currentScore: Double

This factor's contribution to the unnormalized log-probability of the current possible world.

This factor's contribution to the unnormalized log-probability of the current possible world.

Definition Classes
Factor2Factor
26. #### def currentScoreAndStatistics: (Double, StatisticsType)

Return the score and statistics of the current neighbor values; this method enables special cases in which it is more efficient to calculate them together.

Return the score and statistics of the current neighbor values; this method enables special cases in which it is more efficient to calculate them together.

Definition Classes
Factor2Factor
27. #### def currentStatistics: StatisticsType

Return this Factor's sufficient statistics of the current values of the Factor's neighbors.

Return this Factor's sufficient statistics of the current values of the Factor's neighbors.

Definition Classes
Factor2Factor
28. #### final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
29. #### def equalityPrerequisite: AnyRef

In order to two Factors to satisfy "equals", the value returned by this method for each Factor must by "eq".

In order to two Factors to satisfy "equals", the value returned by this method for each Factor must by "eq". This method is overridden in Family to deal with Factors that are inner classes.

Definition Classes
Factor
30. #### def equals(other: Any): Boolean

Definition Classes
Factor → AnyRef → Any
31. #### def factorName: String

Definition Classes
Factor
32. #### def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
33. #### final def getClass(): Class[_]

Definition Classes
AnyRef → Any
34. #### def hasLimitedDiscreteValues1: Boolean

Definition Classes
Factor2
35. #### def hasLimitedDiscreteValues12: Boolean

Definition Classes
Factor2
36. #### def hashCode(): Int

Definition Classes
Factor → AnyRef → Any
37. #### final def isInstanceOf[T0]: Boolean

Definition Classes
Any
38. #### def limitedDiscreteValues1: SparseBinaryTensor1

Definition Classes
Factor2
39. #### def limitedDiscreteValues12: SparseBinaryTensor2

Definition Classes
Factor2
40. #### final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
41. #### final def notify(): Unit

Definition Classes
AnyRef
42. #### final def notifyAll(): Unit

Definition Classes
AnyRef
43. #### def numVariables: Int

The number of variables neighboring this factor.

The number of variables neighboring this factor.

Definition Classes
Factor2Factor
44. #### final def score(v1: N1.Value, v2: N2.Value): Double

Definition Classes
TensorFactor2Factor2
45. #### def scoreAndStatistics(v1: N1.Value, v2: N2.Value): (Double, Tensor)

Definition Classes
TensorFactor2Factor2
46. #### final def statistics(v1: N1.Value, v2: N2.Value): Tensor

Definition Classes
TensorFactorStatistics2TensorFactor2Factor2
47. #### final def statisticsAreValues: Boolean

True iff the statistics are the values (without transformation), e.

True iff the statistics are the values (without transformation), e.g. valuesStatistics simply returns its argument.

Definition Classes
TensorFactorStatistics2Factor
48. #### final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
49. #### def toString(): String

Definition Classes
Factor → AnyRef → Any
50. #### def touches(variable: variable.Var): Boolean

Does this Factor have the given variable among its neighbors?

Does this Factor have the given variable among its neighbors?

Definition Classes
Factor
51. #### def touchesAny(variables: Iterable[variable.Var]): Boolean

Does this Factor have any of the given variables among its neighbors?

Does this Factor have any of the given variables among its neighbors?

Definition Classes
Factor
52. #### def valuesScore(tensor: Tensor): Double

Return the score for Factors whose values can be represented as a Tensor, otherwise throw an Error.

Return the score for Factors whose values can be represented as a Tensor, otherwise throw an Error. For Factors/Family in which the Statistics are the values, this method simply calls statisticsScore(Tensor).

Definition Classes
Factor
53. #### def valuesScore1(tensor1: Tensor, tensor2: Tensor): la.Tensor1

Given multiplicative factors on values of neighbor _1 (which allow for limited iteration), and given the Tensor value of neighbor _2, return a Tensor1 containing the scores for each possible value neighbor _1, which must be a DiscreteVar.

Given multiplicative factors on values of neighbor _1 (which allow for limited iteration), and given the Tensor value of neighbor _2, return a Tensor1 containing the scores for each possible value neighbor _1, which must be a DiscreteVar. Note that the returned Tensor may be sparse if this factor is set up for limited values iteration. If _1 is not a DiscreteVar then throws an Error.

Definition Classes
Factor2
54. #### def valuesScore2(tensor1: Tensor, tensor2: Tensor): la.Tensor1

Definition Classes
Factor2
55. #### def valuesScoreAndStatistics(t: Tensor): (Double, Tensor)

Definition Classes
Factor
56. #### final def valuesStatistics(tensor: Tensor): Tensor

Given a Tensor representation of the values, return a Tensor representation of the statistics.

Given a Tensor representation of the values, return a Tensor representation of the statistics. We assume that if the values have Tensor representation that the StatisticsType does also. Note that (e.g. in BP) the Tensor may represent not just a single value for each neighbor, but a distribution over values

Definition Classes
TensorFactorStatistics2Factor
57. #### def variable(i: Int): variable.Var

The Nth neighboring variable of this factor.

The Nth neighboring variable of this factor.

Definition Classes
Factor2Factor
58. #### def variables: IndexedSeq[variable.Var]

Returns the collection of variables neighboring this factor.

Returns the collection of variables neighboring this factor.

Definition Classes
Factor2Factor
59. #### final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
60. #### final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
61. #### final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )