Alchemy Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

AddGroundClauseStruct
ARGS
argsAction
Array< Type >
ArraysAccessor< Type >
AuxClauseData
CacheCount
Clause
ClauseAndICDArray
ClauseFactory
ClauseSampler
ConstDualMap
ConvergenceTest
Database
Domain
DualMap
EqualClause
EqualClauseOp
EqualFunction
EqualGroundClause
EqualGroundPredicate
EqualHashFormulaAndClauses
EqualIndexClause
EqualInt
EqualIntClause
EqualPredicate
EqualStr
EqualString
EqualStrInt
ExistFormula
FormulaAndClauses
FormulaClauseIndexes
FreeStoreManager
Function
FunctionTemplate
GelmanConvergenceTest
GibbsParams	This struct holds parameters needed to run Gibbs sampling
GibbsSampler	Gibbs sampling algorithm
GroundClause	Represents a grounded clause
GroundPredicate
GroundPreds
Hash
HashArray< Type, HashFn, EqualFn >
HashClause
HashFormulaAndClauses
HashFunction
HashGroundClause
HashGroundPredicate
HashIndexClause
HashInt
HashIntClause
HashList< Type, HashFn, EqualFn >
HashPredicate
HashString
HashStrInt
IdxDiv
IndexAndCount
IndexClause
IndexCountDomainIdx
IndexTranslator
Inference	Abstract class from which all inference algorithms are derived
IntClause
Internals
LazyInfo
LazyUtil
LazyWalksat
LBFGSB
ListObj
LitIdxVarIdsGndings
LWInfo
LWUtil
MaxWalkSat	The MaxWalkSat algorithm
MaxWalksatParams	This struct holds parameters needed to run MaxWalksat
MCMC	Superclass of all MCMC inference algorithms
MCMCParams	This struct holds parameters common to all MCMC inference algorithms
MCSAT	MC-SAT is an MCMC inference algorithm designed to deal efficiently with probabilistic and deterministic dependencies (See Poon and Domingos, 2006)
MCSatParams	This struct holds parameters needed to run MC-SAT
MeanVariance
MLN
MLNClauseInfo
MRF
MultDArray< Type >
NumTrueFalse
Permutation< Type >
PowerSet
PowerSetInstanceVars
Predicate
PredicateTemplate
PredIdClauseIndex
PseudoLogLikelihood
Random
SampledGndings
SampleSat
SampleSatParams	This struct holds parameters needed to run SampleSat
SAT	Superclass of all satisfiability solvers
SimulatedTempering	Simulated Tempering algorithm
SimulatedTemperingParams	This struct holds parameters needed to run Simulated Tempering
StrFifoList
StrInt
StructLearn
Term
Timer
TrueFalseGndings
TrueFalseGroundingsStore
UndoInfo
unionClass
UnitPropagation
Util
VariableState	Represents the state of propositional variables and clauses
VarsGroundedType
VarsTypeId
VotedPerceptron	VotedPerceptron algorithm (see "Discriminative Training of Markov Logic Networks", Singla and Domingos, 2005)
WSUtil
yy_buffer_state
yyGLRStack
yyGLRStackItem	Type of the items in the GLR stack
yyGLRState
yyGLRStateSet
YYLTYPE
yySemanticOption
ZZFileState
ZZFormulaInfo
ZZUnknownEqPredInfo
ZZUnknownIntFuncInfo
ZZUnknownIntPredInfo
ZZVarIdType

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