/* Get argument rules */
const ArgumentRules& Func_Mcmc::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet )
{
argumentRules.push_back( new ArgumentRule("model" , Model::getClassTypeSpec() , ArgumentRule::BY_VALUE ) );
argumentRules.push_back( new ArgumentRule("monitors", WorkspaceVector<Monitor>::getClassTypeSpec(), ArgumentRule::BY_VALUE ) );
argumentRules.push_back( new ArgumentRule("moves" , WorkspaceVector<Move>::getClassTypeSpec() , ArgumentRule::BY_VALUE ) );
std::vector<std::string> options;
options.push_back( "sequential" );
options.push_back( "random" );
options.push_back( "single" );
argumentRules.push_back( new OptionRule( "moveschedule", new RlString( "random" ), options ) );
argumentRules.push_back( new ArgumentRule("nruns" , Natural::getClassTypeSpec() , ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Natural(1) ) );
rulesSet = true;
}
return argumentRules;
}
/** Make member methods for this class */
RevLanguage::MethodTable TimeTree::makeMethods( void ) const
{
MethodTable methods = MethodTable();
ArgumentRules* nnodesArgRules = new ArgumentRules();
methods.addFunction("nnodes", new MemberProcedure(Natural::getClassTypeSpec(), nnodesArgRules ) );
ArgumentRules* ntipsArgRules = new ArgumentRules();
methods.addFunction("ntips", new MemberProcedure(Natural::getClassTypeSpec(), ntipsArgRules ) );
ArgumentRules* heightArgRules = new ArgumentRules();
methods.addFunction("rootAge", new MemberProcedure(RealPos::getClassTypeSpec(), heightArgRules ) );
ArgumentRules* namesArgRules = new ArgumentRules();
methods.addFunction("names", new MemberProcedure(ModelVector<RlString>::getClassTypeSpec(), namesArgRules ) );
ArgumentRules* rescaleArgRules = new ArgumentRules();
rescaleArgRules->push_back( new ArgumentRule( "factor", RealPos::getClassTypeSpec(), ArgumentRule::BY_VALUE ) );
methods.addFunction("rescale", new MemberProcedure(RlUtils::Void, rescaleArgRules ) );
// Insert inherited methods
methods.insertInheritedMethods( ModelObject<RevBayesCore::TimeTree>::makeMethods() );
return methods;
}
/* Get method specifications */
const MethodTable& RateMatrix::getMethods(void) const {
static MethodTable methods = MethodTable();
static bool methodsSet = false;
if ( methodsSet == false ) {
// add method for call "x[]" as a function
ArgumentRules* squareBracketArgRules = new ArgumentRules();
squareBracketArgRules->push_back( new ArgumentRule( "index" , true, Natural::getClassTypeSpec() ) );
methods.addFunction("[]", new MemberProcedure( ModelVector<RealPos>::getClassTypeSpec(), squareBracketArgRules) );
// add method for call "x[]" as a function
ArgumentRules* sizeArgRules = new ArgumentRules();
methods.addFunction("size", new MemberProcedure( Natural::getClassTypeSpec(), sizeArgRules) );
// necessary call for proper inheritance
methods.setParentTable( &ModelObject<RevBayesCore::RateMatrix>::getMethods() );
methodsSet = true;
}
return methods;
}
/* Get method specifications */
const RevLanguage::MethodTable& RealNodeValTree::getMethods(void) const {
static MethodTable methods = MethodTable();
static bool methodsSet = false;
if ( methodsSet == false )
{
ArgumentRules* meanArgRules = new ArgumentRules();
methods.addFunction("mean", new MemberFunction<RealNodeValTree,Real>( this, meanArgRules ) );
ArgumentRules* tipmeanArgRules = new ArgumentRules();
methods.addFunction("tipMean", new MemberFunction<RealNodeValTree,Real>( this, tipmeanArgRules ) );
ArgumentRules* stdevArgRules = new ArgumentRules();
methods.addFunction("stdev", new MemberFunction<RealNodeValTree,RealPos>( this, stdevArgRules ) );
ArgumentRules* rootArgRules = new ArgumentRules();
methods.addFunction("rootVal", new MemberProcedure(Real::getClassTypeSpec(), rootArgRules ) );
ArgumentRules* clampArgRules = new ArgumentRules();
clampArgRules->push_back(new ArgumentRule("data", false, AbstractCharacterData::getClassTypeSpec()));
clampArgRules->push_back(new ArgumentRule("dataIndex", false, Natural::getClassTypeSpec()));
methods.addFunction("clampAt", new MemberProcedure(RealNodeValTree::getClassTypeSpec(), clampArgRules ) );
// necessary call for proper inheritance
methods.setParentTable( &ModelObject<RevBayesCore::RealNodeContainer>::getMethods() );
methodsSet = true;
}
return methods;
}
/* Get method specifications */
const MethodTable& ParallelMcmcmc::getMethods(void) const {
static MethodTable methods = MethodTable();
static bool methodsSet = false;
if ( methodsSet == false ) {
ArgumentRules* runArgRules = new ArgumentRules();
runArgRules->push_back( new ArgumentRule("generations", true, Natural::getClassTypeSpec()) );
methods.addFunction("run", new MemberProcedure( RlUtils::Void, runArgRules) );
ArgumentRules* burninArgRules = new ArgumentRules();
burninArgRules->push_back( new ArgumentRule("generations", true, Natural::getClassTypeSpec()) );
burninArgRules->push_back( new ArgumentRule("tuningInterval", true, Natural::getClassTypeSpec()) );
methods.addFunction("burnin", new MemberProcedure( RlUtils::Void, burninArgRules) );
ArgumentRules* operatorSummaryArgRules = new ArgumentRules();
methods.addFunction("operatorSummary", new MemberProcedure( RlUtils::Void, operatorSummaryArgRules) );
// necessary call for proper inheritance
methods.setParentTable( &RevObject::getMethods() );
methodsSet = true;
}
return methods;
}
RlAtlas::RlAtlas( RevBayesCore::TypedDagNode<RevBayesCore::TimeAtlas> *m) : ModelObject<RevBayesCore::TimeAtlas>( m ),
atlas(&m->getValue())
{
ArgumentRules* nAreasArgRules = new ArgumentRules();
ArgumentRules* nEpochsArgRules = new ArgumentRules();
ArgumentRules* namesArgRules = new ArgumentRules();
ArgumentRules* epochsArgRules = new ArgumentRules();
methods.addFunction( new MemberProcedure( "names", ModelVector<RlString>::getClassTypeSpec(), namesArgRules ) );
methods.addFunction( new MemberProcedure( "nAreas", Natural::getClassTypeSpec(), nAreasArgRules ) );
methods.addFunction( new MemberProcedure( "nEpochs", Natural::getClassTypeSpec(), nEpochsArgRules ) );
methods.addFunction( new MemberProcedure( "epochTimes", ModelVector<RealPos>::getClassTypeSpec(), epochsArgRules ) );
ArgumentRules* adjacentArgRules = new ArgumentRules();
std::vector<std::string> optionsValue;
optionsValue.push_back( "dispersal" );
optionsValue.push_back( "dispersal-upper" );
optionsValue.push_back( "extinction" );
optionsValue.push_back( "latlon" );
optionsValue.push_back( "altitude" );
optionsValue.push_back( "size" );
adjacentArgRules->push_back( new OptionRule( "value", new RlString( "dispersal" ), optionsValue, "" ) );
// adjacentArgRules->push_back( new OptionRule( "elements", new RlString( "off-diagonal" ), optionsElements ) );
// adjacentArgRules->push_back( new ArgumentRule("symmetric", RlBoolean::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ) );
methods.addFunction( new MemberProcedure( "getValues", RlUtils::Void, adjacentArgRules) );
// Add method for call "size" as a function
ArgumentRules* sizeArgRules = new ArgumentRules();
methods.addFunction( new MemberProcedure( "size", Natural::getClassTypeSpec(), sizeArgRules) );
}
AncestralStateTrace::AncestralStateTrace() : WorkspaceToCoreWrapperObject<RevBayesCore::AncestralStateTrace>()
{
ArgumentRules* summarizeArgRules = new ArgumentRules();
summarizeArgRules->push_back( new ArgumentRule("burnin", Natural::getClassTypeSpec(), "The number of iterations to discard as burnin.", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Natural(0)) );
}
Trace::Trace(const RevBayesCore::Trace &t) : WorkspaceToCoreWrapperObject<RevBayesCore::Trace>( new RevBayesCore::Trace( t ) )
{
ArgumentRules* summarizeArgRules = new ArgumentRules();
summarizeArgRules->push_back( new ArgumentRule("burnin", Natural::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Natural(0)) );
methods.addFunction("summarize", new MemberProcedure( RlUtils::Void, summarizeArgRules) );
}
/**
* Default constructor.
*
* The default constructor does nothing except allocating the object.
*/
Move_SpeciesSubtreeScale::Move_SpeciesSubtreeScale() : Move()
{
// add method for call "addGeneTreeVariable" as a function
ArgumentRules* addGeneTreeArgRules = new ArgumentRules();
addGeneTreeArgRules->push_back( new ArgumentRule( "geneTree" , TimeTree::getClassTypeSpec(), "A gene tree to scale.", ArgumentRule::BY_REFERENCE, ArgumentRule::STOCHASTIC ) );
methods.addFunction( new MemberProcedure( "addGeneTreeVariable", RlUtils::Void, addGeneTreeArgRules) );
}
/** Construct from bool */
BranchLengthTree::BranchLengthTree(RevBayesCore::TypedDagNode<RevBayesCore::Tree> *n) : Tree( n )
{
ArgumentRules* rerootArgRules = new ArgumentRules();
rerootArgRules->push_back( new ArgumentRule("leaf", RlString::getClassTypeSpec(), "The outgroup leaf.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
methods.addFunction( new MemberProcedure( "reroot", RlUtils::Void, rerootArgRules ) );
}
Model::Model() : WorkspaceToCoreWrapperObject<RevBayesCore::Model>()
{
ArgumentRules* dotArgRules = new ArgumentRules();
dotArgRules->push_back( new ArgumentRule("file", RlString::getClassTypeSpec() , ArgumentRule::BY_VALUE ) );
dotArgRules->push_back( new ArgumentRule("verbose", RlBoolean::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ) );
dotArgRules->push_back( new ArgumentRule("bg", RlString::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlString("lavenderblush2") ) );
methods.addFunction("graph", new MemberProcedure( RlUtils::Void, dotArgRules) );
}
TraceTree::TraceTree(const RevBayesCore::TraceTree &m) : WorkspaceToCoreWrapperObject<RevBayesCore::TraceTree>( new RevBayesCore::TraceTree( m ) )
{
ArgumentRules* summarizeArgRules = new ArgumentRules();
summarizeArgRules->push_back( new ArgumentRule("burninFraction", Probability::getClassTypeSpec(), "The fraction of samples to disregard as burnin.", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Probability(0.1)) );
summarizeArgRules->push_back( new ArgumentRule("credibleTreeSetSize", Probability::getClassTypeSpec(), "The size of the credible set to print.", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Probability(0.95)) );
summarizeArgRules->push_back( new ArgumentRule("minCladeProbability", Probability::getClassTypeSpec(), "The minimum clade probability used when printing.", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new Probability(0.05)) );
this->methods.addFunction( new MemberProcedure( "summarize", RlUtils::Void, summarizeArgRules) );
}
MethodTable Dist_CharacterDependentCladoBirthDeathProcess::getDistributionMethods( void ) const
{
MethodTable methods = TypedDistribution<TimeTree>::getDistributionMethods();
ArgumentRules* clampCharDataArgRules = new ArgumentRules();
clampCharDataArgRules->push_back( new ArgumentRule( "value", AbstractHomologousDiscreteCharacterData::getClassTypeSpec(), "The observed value.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
methods.addFunction( new MemberProcedure( "clampCharData", RlUtils::Void, clampCharDataArgRules ) );
return methods;
}
/** Get argument rules */
const ArgumentRules& Func_readBranchLengthTrees::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if (!rulesSet) {
argumentRules.push_back( new ArgumentRule( "file", RlString::getClassTypeSpec(), ArgumentRule::BY_VALUE ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_readCharacterDataUniversal::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if (!rulesSet)
{
argumentRules.push_back( new ArgumentRule( "file", RlString::getClassTypeSpec(), ArgumentRule::BY_VALUE ) );
argumentRules.push_back( new ArgumentRule( "alwaysReturnAsVector", RlBoolean::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ) );
rulesSet = true;
}
return argumentRules;
}
/* Get argument rules */
const ArgumentRules& Func_varianceCovarianceMatrix::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet )
{
argumentRules.push_back( new ArgumentRule( "standardDeviations" , ModelVector<RealPos>::getClassTypeSpec(), ArgumentRule::BY_CONSTANT_REFERENCE ) );
argumentRules.push_back( new ArgumentRule( "correlationCoefficients", ModelVector<Real>::getClassTypeSpec(), ArgumentRule::BY_CONSTANT_REFERENCE ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_readCharacterDataUniversal::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rules_set = false;
if (!rules_set)
{
argumentRules.push_back( new ArgumentRule( "file", RlString::getClassTypeSpec(), "File or directory names where to find the character data.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
argumentRules.push_back( new ArgumentRule( "alwaysReturnAsVector", RlBoolean::getClassTypeSpec(), "Should the value be returned as a vector even it is only a single matrix?", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ) );
rules_set = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_contributors::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "all", true, RlBoolean::getClassTypeSpec(), new RlBoolean(false) ) );
rulesSet = true;
}
return argumentRules;
}
PowerPosteriorAnalysis::PowerPosteriorAnalysis() : WorkspaceToCoreWrapperObject<RevBayesCore::PowerPosteriorAnalysis>()
{
ArgumentRules* runArgRules = new ArgumentRules();
runArgRules->push_back( new ArgumentRule("generations", Natural::getClassTypeSpec(), "The number of generations to run.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
methods.addFunction( new MemberProcedure( "run", RlUtils::Void, runArgRules) );
ArgumentRules* burninArgRules = new ArgumentRules();
burninArgRules->push_back( new ArgumentRule("generations" , Natural::getClassTypeSpec(), "The number of generations to run.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
burninArgRules->push_back( new ArgumentRule("tuningInterval", Natural::getClassTypeSpec(), "The frequency when the moves are tuned (usually between 50 and 1000).", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
methods.addFunction( new MemberProcedure( "burnin", RlUtils::Void, burninArgRules) );
}
/** Get argument rules */
const ArgumentRules& Func_license::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "all", RlBoolean::getClassTypeSpec(), ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_type::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "x", true, RevObject::getClassTypeSpec() ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_simplexFromVector::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet )
{
argumentRules.push_back( new ArgumentRule( "x", ModelVector<RealPos>::getClassTypeSpec(), ArgumentRule::BY_CONSTANT_REFERENCE ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_treeTrace::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if (!rulesSet)
{
argumentRules.push_back( new ArgumentRule( "trees" , ModelVector<TimeTree>::getClassTypeSpec(), "Vector of TimeTrees.", ArgumentRule::BY_VALUE, ArgumentRule::ANY ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_simplex::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "", true, RealPos::getClassTypeSpec() ) );
argumentRules.push_back( new Ellipsis ( RealPos::getClassTypeSpec() ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_source::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "file", true, RlString::getClassTypeSpec() ) );
argumentRules.push_back( new ArgumentRule( "echo.on", true, RlBoolean::getClassTypeSpec(), new RlBoolean(false) ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_seed::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "seed1", true, Natural::getClassTypeSpec() ) );
argumentRules.push_back( new ArgumentRule( "seed2", true, Natural::getClassTypeSpec() ) );
rulesSet = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func__unot::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "", RlBoolean::getClassTypeSpec(), ArgumentRule::BY_CONSTANT_REFERENCE ) );
rulesSet = true;
}
return argumentRules;
}
/* Get argument rules */
const ArgumentRules& Func_f81::getArgumentRules( void ) const {
static ArgumentRules argumentRules = ArgumentRules();
static bool rulesSet = false;
if ( !rulesSet ) {
argumentRules.push_back( new ArgumentRule( "baseFrequencies", true, Simplex::getClassTypeSpec() ) );
rulesSet = true;
}
return argumentRules;
}
/* Get argument rules */
const ArgumentRules& Func_DECStationaryFrequencies::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rules_set = false;
if ( !rules_set )
{
argumentRules.push_back( new ArgumentRule( "dispersalRates" , ModelVector<ModelVector<RealPos> >::getClassTypeSpec(), "Matrix of dispersal rates between areas.", ArgumentRule::BY_CONSTANT_REFERENCE, ArgumentRule::ANY ) );
argumentRules.push_back( new ArgumentRule( "extirpationRates", ModelVector<RealPos>::getClassTypeSpec(), "The per area extinction rates.", ArgumentRule::BY_CONSTANT_REFERENCE, ArgumentRule::ANY ) );
argumentRules.push_back( new ArgumentRule( "rangeSize", Simplex::getClassTypeSpec(), "Relative proportions of range sizes.", ArgumentRule::BY_CONSTANT_REFERENCE, ArgumentRule::ANY, new Simplex( RevBayesCore::RbVector<double>() ) ) );
argumentRules.push_back( new ArgumentRule( "birthRate", RealPos::getClassTypeSpec(), "Birth rate.", ArgumentRule::BY_CONSTANT_REFERENCE, ArgumentRule::ANY, new RealPos(0.0)) );
argumentRules.push_back( new ArgumentRule( "cladoProbs", MatrixReal::getClassTypeSpec(), "Cladogenetic probabilities.", ArgumentRule::BY_CONSTANT_REFERENCE, ArgumentRule::DETERMINISTIC ) );
std::vector<std::string> options;
options.push_back( "CondSurv" );
options.push_back( "Exclude" );
// options.push_back( "Include" );
argumentRules.push_back( new OptionRule( "nullRange", new RlString("CondSurv"), options, "How should DEC handle the null range?" ) );
argumentRules.push_back( new ArgumentRule( "orderStatesBySize", RlBoolean::getClassTypeSpec(), "Order states by size?", ArgumentRule::BY_VALUE, ArgumentRule::ANY, new RlBoolean(false) ));
rules_set = true;
}
return argumentRules;
}
/** Get argument rules */
const ArgumentRules& Func_clear::getArgumentRules( void ) const
{
static ArgumentRules argumentRules = ArgumentRules();
static bool rules_set = false;
if ( !rules_set ) {
argumentRules.push_back( new Ellipsis( "Variables to remove.", RevObject::getClassTypeSpec() ) );
rules_set = true;
}
return argumentRules;
}
