HAPI::AbsExpression | Expression class representing the Abs () function |
HAPI::AddExpression | Expression class representing the + operator |
HAPI::AndExpression | Expression class representing the and () function |
HAPI::Attribute | Attributes can be used to associate arbitrary data with a node or a NetworkModel (i.e., a Class or a Domain) |
HAPI::BetaDistribution | Expression class representing the Beta distribution function |
HAPI::BinomialDistribution | Expression class representing the Binomial distribution function |
HAPI::BooleanDCNode | Boolean discrete chance node. The node has two states, true and false |
HAPI::BooleanDDNode | Boolean discrete decision node |
HAPI::BooleanExpression | A Boolean constant expression |
HAPI::CeilExpression | Expression class representing the ceil () function |
HAPI::CGDistribution | The CGDistribution encapsulates all information regarding the distribution of a ContinuousChanceNode |
HAPI::Class | The Class class is one of the principal structures in HUGIN |
HAPI::ClassCollection | A ClassCollection is one of the principal structures in HUGIN |
HAPI::ClassParseListener | The ClassParseListener interface is used when one wants to call the parseClasses (String, ParseListener) method of the ClassCollection class |
HAPI::Clique | Represents the cliques in the junction tree |
HAPI::CompositeExpression | The ancestor class of all composite expressions (for example arithmetic operators and standard distribution functions) |
HAPI::ConstantExpression | The ancestor of all expression classes representing a constant (label, number, or Boolean) |
HAPI::ContinuousChanceNode | The Continuous chance node |
HAPI::CosExpression | Expression class representing the Cos () function |
HAPI::CoshExpression | Expression class representing the Cosh () function |
HAPI::DefaultParseListener | Provides a simple implementation of the ParseListener class |
HAPI::DiscreteChanceNode | This class is the ancestor of all discrete chance nodes |
HAPI::DiscreteDecisionNode | The discrete decision node. Base class for all decision nodes |
HAPI::DistributionDistribution | Expression class representing the Distribution () function |
HAPI::DivideExpression | Expression class representing the / operator |
HAPI::Domain | A domain is the HUGIN representation of a network |
HAPI::EqualsExpression | Expression class representing the == operator |
HAPI::ExceptionAttribute | Attempted to read a value associated with a non-existing attribute |
HAPI::ExceptionBadFile | H_error_bad_file: An attempt to load a domain failed due to a bad file |
HAPI::ExceptionBadVersion | H_error_bad_version: The knowledgde base has a wrong version number |
HAPI::ExceptionCGEvidenceIncorporated | H_error_cg_evidence_incorporated: This operation is not supported when the junction tree potentials have CG evidence incorporated |
HAPI::ExceptionCGInfluenceDiagramsNotSupported | Influence diagrams with CG nodes are not supported |
HAPI::ExceptionChainGraph | H_error_chain_graph: Chain graph: Zero probability found in parent potential |
HAPI::ExceptionCompressed | H_error_compressed: The operation is not supported on compressed domains |
HAPI::ExceptionComputationFailed | H_error_computation_failed: The probability/density function could not be computed |
HAPI::ExceptionCyclicInstanceHierarchy | Cyclic hierarchies of class instances are not allowed |
HAPI::ExceptionCyclicNetwork | H_error_cyclic_network: A cycle has been detected in the network of a domain |
HAPI::ExceptionDecisionOrder | H_error_decision_order: The set of decisions in an influence diagram must be linearly ordered |
HAPI::ExceptionDemo | Attempted to work on domain, which exceeds the limits of the demo version |
HAPI::ExceptionDivisionByZero | H_error_division_by_zero: Division by zero has been attempted |
HAPI::ExceptionEnumeration | H_error_enumeration: The specified elimination sequence is invalid |
HAPI::ExceptionError | H_error_error: This is an impossible error |
HAPI::ExceptionExpiredLicense | The time limited evaluation license has expired |
HAPI::ExceptionFastRetraction | H_error_fast_retraction: Logical relations in the distribution has caused a fast-retraction propagation to fail |
HAPI::ExceptionFormat | H_error_format: Some data item had a bad format |
HAPI::ExceptionHugin | The generic Hugin Exception |
HAPI::ExceptionIllegalBinding | An actual input node is incompatible with the formal input node, or there are multiple occurrences of the same parent |
HAPI::ExceptionInappropriateArguments | H_error_inappropriate_arguments: Illegal arguments have been given to a standard probability/density function |
HAPI::ExceptionInconsistencyOrUnderflow | H_error_inconsistency_or_underflow: Propagation of inconsistent evidence has been attempted |
HAPI::ExceptionInsufficientStateRange | H_error_insufficient_state_range: The state range of the node is insufficient for the chosen standard distribution |
HAPI::ExceptionInvalidExpression | H_error_invalid_expression: The supplied expression is invalid (for example, wrong type) |
HAPI::ExceptionInvalidLicense | Attempted to work on domain with invalid license information |
HAPI::ExceptionInvalidName | H_error_invalid_name: Names used as node identifiers or attribute names must have the same form as a C identifier |
HAPI::ExceptionInvalidPassword | An invalid password has been given for a hkb-load operation |
HAPI::ExceptionInvalidStateValues | H_error_invalid_state_values: The state values of a numeric node do not form an increasing sequence |
HAPI::ExceptionIO | H_error_io: A fatal error occurred during an input or output operation |
HAPI::ExceptionLocale | H_error_locale: The Hugin API could not establish the C locale |
HAPI::ExceptionLowDensity | H_error_low_density: The density of the evidence presented is too low to represent as a positive floating-point number |
HAPI::ExceptionMemory | H_error_no_memory: Hugin ran out of memory while carrying out some operation |
HAPI::ExceptionNegativeProbability | H_error_negative_probability: A negative probability was found in a conditional probability or a chain graph potential |
HAPI::ExceptionNoEquilibrium | H_error_no_equilibrium: The junction tree potentials are inconsistent |
HAPI::ExceptionNoFileName | The NetworkModel does not have a file name associated with it |
HAPI::ExceptionNormalization | H_error_normalization: Normalization with a zero normalization constant has been attempted |
HAPI::ExceptionNotCompiled | H_error_not_compiled: The operation requires a compiled domain |
HAPI::ExceptionNoValue | H_error_no_value: Zero variance detected during a conditioning operation |
HAPI::ExceptionOverflow | H_error_overflow: Overflow occurred during propagation |
HAPI::ExceptionParse | H_error_parse: An error occurred while parsing a NET specification |
HAPI::ExceptionRounding | H_error_rounding: Possibly significant floating-point rounding error detected |
HAPI::ExceptionSizeTooLarge | H_error_size_too_large: The true size is too large to represent within type `size_t' |
HAPI::ExceptionSyntax | H_error_syntax: A syntax error has been detected while parsing an expression |
HAPI::ExceptionTableSize | Attempted to use a table of wrong dimensions, e.g., while setting data of a table |
HAPI::ExceptionTableTooLarge | H_error_table_too_large: The compressed version of some non-clique table is too large |
HAPI::ExceptionTwice | H_error_twice: An attempt has been made to create a node with a name that is already in use in the domain |
HAPI::ExceptionUsage | H_error_usage: An API function was called with a bad argument or while in a state that is inconsistent with the function, e.g., asking for approximation in a domain that requires propagation |
HAPI::ExceptionZeroSum | H_error_zero_sum: A zero sum was found in a conditional probability potential |
HAPI::ExceptionZeroVariance | H_error_zero_variance: Zero variance detected during a conditioning operation |
HAPI::ExpExpression | Expression class representing the exp () function |
HAPI::ExponentialDistribution | Expression class representing the Exponential distribution function |
HAPI::Expression | Expression is the ancestor of all expression classes |
HAPI::FloorExpression | Expression class representing the floor () function |
HAPI::GammaDistribution | Expression class representing the Gamma distribution function |
HAPI::GeometricDistribution | Expression class representing the Geometric distribution function |
HAPI::GreaterThanExpression | Expression class representing the > operator |
HAPI::GreaterThanOrEqualsExpression | Expression class representing the >= operator |
HAPI::IfExpression | Expression class representing the "if(cond-expr,true-expr,false-expr)" function |
HAPI::InstanceNode | InstanceNodes are the key building block of object-oriented Bayesian networks and influence diagrams |
HAPI::IntervalDCNode | Interval discrete chance node. Each state represents an interval |
HAPI::IntervalDDNode | Interval discrete decision node |
HAPI::JunctionTree | Thic class represents the junction trees in the compiled domain |
HAPI::LabelExpression | A label constant expression |
HAPI::LabelledDCNode | Labelled discrete chance node. This is the most commonly used node |
HAPI::LabelledDDNode | Labelled discrete decision node |
HAPI::LessThanExpression | Expression class representing the < operator |
HAPI::LessThanOrEqualsExpression | Expression class representing the <= operator |
HAPI::Log10Expression | Expression class representing the Log10 () function |
HAPI::Log2Expression | Expression class representing the log2 () function |
HAPI::LogExpression | Expression class representing the log () function |
HAPI::MaxExpression | Expression class representing the max () function |
HAPI::MinExpression | Expression class representing the min () function |
HAPI::Model | A Model is a compact description of a table |
HAPI::ModExpression | Expression class representing the mod () function |
HAPI::MultiplyExpression | Expression class representing the * operator |
HAPI::NegateExpression | Expression class representing the unary - operator |
HAPI::NegativeBinomialDistribution | Expression class representing the Negative Binomial distribution function |
HAPI::NetworkModel | NetworkModel is the ancestor of both Domain and Class |
HAPI::Node | Nodes are one of the fundamental objects used in the construction of Bayesian belief networks and influence diagrams |
HAPI::NodeExpression | An expression representing the value of a discrete chance node or decision node |
HAPI::NoisyOrExpression | Expression class representing the NoisyOr () function |
HAPI::NormalDistribution | Expression class representing the Gaussian normal distribution function |
HAPI::NotEqualsExpression | Expression class representing the != operator |
HAPI::NotExpression | Expression class representing the Boolean not () function |
HAPI::NumberedDCNode | Numbered discrete chance node |
HAPI::NumberedDDNode | Numbered discrete decision node |
HAPI::NumberExpression | A numeric constant expression |
HAPI::OrExpression | Expression class representing the Boolean or () function |
HAPI::ParseListener | The ParseListener class is an abstract class, which provides an interface for the other parse listeners to use |
HAPI::PoissonDistribution | Expression class representing the Poisson distribution function |
HAPI::PowerExpression | Expression class representing the ^ operator |
HAPI::SinExpression | Expression class representing the Sin () function |
HAPI::SinhExpression | Expression class representing the Sinh () function |
HAPI::SqrtExpression | Expression class representing the sqrt () function |
HAPI::SubtractExpression | Expression class representing the binary - operator |
HAPI::Table | Hugin uses Tables for representing the conditional probability and utility potentials of individual Nodes, the probability and utility potentials on separators and Cliques of JunctionTrees, evidence potentials, etc |
HAPI::TanExpression | Expression class representing the Tan () function |
HAPI::TanhExpression | Expression class representing the Tanh () function |
HAPI::UniformDistribution | Expression class representing the Uniform distribution function |
HAPI::UtilityNode | A UtilityNode represents a utility function |
HAPI::WeibullDistribution | Expression class representing the Weibull distribution function |