cc.factorie.directed.PlatedCategorical
The ability to score a Values object is now removed, and this is its closest alternative.
Return this Factor's sufficient statistics for the values in the Assignment.
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
Return a record of the current values of this Factor's neighbors.
This factor's contribution to the unnormalized log-probability of the current possible world.
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 this Factor's sufficient statistics of the current values of the Factor's neighbors.
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.
The number of variables neighboring this factor.
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.
Does this Factor have the given variable among its neighbors?
Does this Factor have the given variable among its neighbors?
Does this Factor have any of the given variables among its neighbors?
Does this Factor have any of the given variables among its neighbors?
Update sufficient statistics in collapsed parents, using current value of child, with weight.
Update sufficient statistics in collapsed parents, using current value of child, with weight. Return false on failure.
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).
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.
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
The Nth neighboring variable of this factor.
Returns the collection of variables neighboring this factor.