addmtoolbox: addmtoolbox

# This file was generated by Rcpp::compileAttributes
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' Simulate aDDM process by unique trial condition (2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by condition, 2 items)
#' \code{aevacc2_by_condition()}
#' @return vector that stores decisions and rts for each simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevacc2_by_condition <- function(parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc2_by_condition', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial (2 items)
#' \code{aevacc2_by_trial()}
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by trial, 2 items)
#' @return numeric variable that provides a success count (runs that predicted a reaction time in the correct rt-bin and simultaneously the correct decision)
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur numeric variable that supplies the maximum reaction time considered a success in simulations
#' @param mindur numeric variable that supplies the minimum reaction time considered a succes in simulations
#' @param cur_decision numeric variable that provides the empirical decision taken in trial
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param cur_maxfix integer that provides number of fixation in trial
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevacc2_by_trial <- function(parameters, maxdur = 0L, mindur = 0L, cur_decision = 0L, update = 0L, nr_attributes = 0L, fixpos = 0L, fixdur = 0L, nr_reps = 0L, timestep = 0L) {
    .Call('addmtoolbox_aevacc2_by_trial', PACKAGE = 'addmtoolbox', parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep)
}

#' Simulate aDDM process (2 items) with detailed output
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (2 items) with detailed output
#' \code{aevacc2_full_output()}
#' @return vector that stores detailed output by simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @param gamma placeholder for interface consistency / see multiattribute versions for specification
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevacc2_full_output <- function(parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc2_full_output', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial condition (>2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process by unique trial condition (>2 items)
#' \code{aevacc_by_condition()}
#' @return vector that stores decisions and rts for each simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param fixdursamples Vector from which fixation duration can be sampled once supplied fixations run out
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevacc_by_condition <- function(parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc_by_condition', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial condition (>2 items, allow memory effects)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process by unique trial condition (>2 items, allow memory effects)
#' \code{aevacc_by_condition_memnoise()}
#' @return vector that stores decisions and rts for each simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma, scalar_items_seen_drift, scala_items_seen_noise])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param fixdursamples Vector from which fixation duration can be sampled once supplied fixations run out
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @export
aevacc_by_condition_memnoise <- function(parameters, maxdur, update, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc_by_condition_memnoise', PACKAGE = 'addmtoolbox', parameters, maxdur, update, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial (>2 items)
#' \code{aevacc_by_trial()}
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process by unique trial (>2 items)
#' @return Returns a numeric variable that provides a success count (runs that predicted a reaction time in the correct rt-bin and simultaneously the correct decision)
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur numeric variable that supplies the maximum reaction time considered a success in simulations
#' @param mindur numeric variable that supplies the minimum reaction time considered a succes in simulations
#' @param cur_decision numeric variable that provides the empirical decision taken in trial
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevacc_by_trial <- function(parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc_by_trial', PACKAGE = 'addmtoolbox', parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial (>2 items, allow memory effects)
#' \code{aevacc_by_trial_memnoise}
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process by unique trial (>2 items, allow memory effects)
#' @return numeric variable that provides a success count (runs that predicted a reaction time in the correct rt-bin and simultaneously the correct decision)
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma, scalar_items_seen_drift, scala_items_seen_noise])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur numeric variable that supplies the maximum reaction time considered a success in simulations
#' @param mindur numeric variable that supplies the minimum reaction time considered a succes in simulations
#' @param cur_decision numeric variable that provides the empirical decision taken in trial
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param items_seen_bias Numeric Variable storing the relative amount of drift that unseen items receive
#' @param items_seen_noise_bias Numeric Variable storing the relative noise sd that unseen items receive
#' @export
aevacc_by_trial_memnoise <- function(parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc_by_trial_memnoise', PACKAGE = 'addmtoolbox', parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep)
}

#' Simulate aDDM process (>2 items, allow memory effects) for detailed model output
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (>2 items, allow memory effects) for detailed model output
#' \code{aevacc_full_output_memnoise()}
#' @return vector that stores detailed output by simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma, scalar_items_seen_drift, scala_items_seen_noise])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @export
aevacc_full_output_memnoise <- function(parameters, maxdur, update, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevacc_full_output_memnoise', PACKAGE = 'addmtoolbox', parameters, maxdur, update, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial condition (2 items, multiattribute)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by condition, 2 items)
#' \code{aevaccma2_by_condition()}
#' @return vector that stores decisions and rts for each simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @export
aevaccma2_by_condition <- function(parameters, maxdur = 0L, update = 0L, nr_attributes = 1L, fixation_model = 0L, nr_reps = 0L, timestep = 0L) {
    .Call('addmtoolbox_aevaccma2_by_condition', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

#' Simulate aDDM process by unique trial (2 items // multiattribute)
#' \code{aevaccma2_by_trial()}
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by trial, 2 items, multiattribute)
#' @return numeric variable that provides a success count (runs that predicted a reaction time in the correct rt-bin and simultaneously the correct decision)
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur numeric variable that supplies the maximum reaction time considered a success in simulations
#' @param mindur numeric variable that supplies the minimum reaction time considered a succes in simulations
#' @param cur_decision numeric variable that provides the empirical decision taken in trial
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector that stores the locations for a supplied fixed fixation pathway
#' @param fixdur Vector that stores the fixation durations for a supplied fixed fixation pathway
#' @param cur_maxfix integer that provides number of fixation in trial
#' @export
aevaccma2_by_trial <- function(parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep) {
    .Call('addmtoolbox_aevaccma2_by_trial', PACKAGE = 'addmtoolbox', parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep)
}

#' Simulate aDDM process (2 items, multiattribute) with detailed output
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (2 items) with detailed output
#' \code{aevaccma2_full_output()}
#' @return vector that stores detailed output by simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model a user supplied fixation model that will be utilized to supply fixation locations and potentially fixation durations
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
aevaccma2_full_output <- function(parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_aevaccma2_full_output', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

defaultt <- function(x = 1L, y = 1L, z = 1L) {
    .Call('addmtoolbox_defaultt', PACKAGE = 'addmtoolbox', x, y, z)
}

#' Simulate aDDM process by unique trial condition (2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by condition, 2 items)
#' \code{dynamicaddm()}
#' @return numeric variable storing likelihood value
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma])
#' @param decision integer which gives choice in current trial (1 or 2)
#' @param rt reaction time of provided trial
#' @param valuations vector that stores the item valuations for the provided trial
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @param fixpos vector with all empirical fixations positions encountered in provided trial
#' @param fixdur vector with all empirical fixation durations encounrtered in provided trial
#' @param stateStep numeric variable between [0,1] that indicates how finegrained the vertical grid of the model space shall be computed
#' @export
dynamicaddm <- function(parameters, decision = 0L, valuations = 0L, nr_attributes = 0L, fixpos = 0L, fixdur = 0L, rt = 0L, stateStep = 0) {
    .Call('addmtoolbox_dynamicaddm', PACKAGE = 'addmtoolbox', parameters, decision, valuations, nr_attributes, fixpos, fixdur, rt, stateStep)
}

#' Simulate DDM process by unique trial condition (2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate DDM process (by condition, 2 items)
#' \code{dynamicddm()}
#' @return numeric variable storing likelihood value
#' @param decision integer which gives choice in current trial (1 or 2)
#' @param rt reaction time of provided trial
#' @param valuations vector that stores the item valuations for the provided trial
#' @param nr_attributes integer variable placeholder for interface consistency / see multiattribute versions for specification
#' @param fixpos vector placeholder for interface consistency / see attentional versions for specification
#' @param fixdur vector placeholder for interface consistency / see attentional versions for specification
#' @param stateStep numeric variable between [0,1] that indicates how finegrained the vertical grid of the model space shall be computed
#' @export
dynamicddm <- function(parameters, decision = 0L, valuations = 0L, nr_attributes = 0L, fixpos = 0L, fixdur = 0L, rt = 0L, stateStep = 0) {
    .Call('addmtoolbox_dynamicddm', PACKAGE = 'addmtoolbox', parameters, decision, valuations, nr_attributes, fixpos, fixdur, rt, stateStep)
}

#' Simulate aDDM process by unique trial condition (2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate aDDM process (by condition, 2 items)
#' \code{dynamicaddm()}
#' @return numeric variable storing likelihood value
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd, theta, gamma])
#' @param decision integer which gives choice in current trial (1 or 2)
#' @param rt reaction time of provided trial
#' @param valuations vector that stores the item valuations for the provided trial
#' @param nr_attributes integer which gives the number of attributes by item
#' @param fixpos vector with all empirical fixations positions encountered in provided trial
#' @param fixdur vector with all empirical fixation durations encounrtered in provided trial
#' @param stateStep numeric variable between [0,1] that indicates how finegrained the vertical grid of the model space shall be computed
#' @export
dynamicmaaddm <- function(parameters, decision = 0L, valuations = 0L, nr_attributes = 0L, fixpos = 0L, fixdur = 0L, rt = 0L, stateStep = 0) {
    .Call('addmtoolbox_dynamicmaaddm', PACKAGE = 'addmtoolbox', parameters, decision, valuations, nr_attributes, fixpos, fixdur, rt, stateStep)
}

#' Simulate DDM process by unique trial condition (2 items)
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate DDM process (by condition, 2 items)
#' \code{evacc2_by_condition()}
#' @return vector that stores decisions and rts for each simulation run
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur maximum duration in ms that the process is allowed to simulate
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixation_model placeholder for interface consistency / see attentional versions for specification
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
evacc2_by_condition <- function(parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep) {
    .Call('addmtoolbox_evacc2_by_condition', PACKAGE = 'addmtoolbox', parameters, maxdur, update, nr_attributes, fixation_model, nr_reps, timestep)
}

#' Simulate DDM process by unique trial (2 items)
#' \code{evacc2_by_trial()}
#' @author Alexander Fengler, \email{alexanderfengler@@gmx.de}
#' @title Simulate DDM process (by trial, 2 items)
#' @return numeric variable that provides a success count (runs that predicted a reaction time in the correct rt-bin and simultaneously the correct decision)
#' @param parameters vector that stores the parameters used for the simulations (Order: [non.decision.time, drift, sd])
#' @param timestep timestep in ms associated with each step in the drift diffusion process
#' @param nr_reps number of repitions (simulation runs)
#' @param maxdur numeric variable that supplies the maximum reaction time considered a success in simulations
#' @param mindur numeric variable that supplies the minimum reaction time considered a succes in simulations
#' @param cur_decision numeric variable that provides the empirical decision taken in trial
#' @param update Vector that stores the item valuations for the trial conditon simulated
#' @param fixpos Vector placeholder for interface consistency / see attentional versions for specification
#' @param fixdur Vector placeholder for interface consistency / see attentional versions for specification
#' @param cur_maxfix integer that provides number of fixation in trial
#' @param nr_attributes placeholder for interface consistency / see multiattribute versions for specification
#' @export
evacc2_by_trial <- function(parameters, maxdur = 0L, mindur = 0L, cur_decision = 0L, update = 0L, nr_attributes = 0L, fixpos = 0L, fixdur = 0L, nr_reps = 0L, timestep = 0L) {
    .Call('addmtoolbox_evacc2_by_trial', PACKAGE = 'addmtoolbox', parameters, maxdur, mindur, cur_decision, update, nr_attributes, fixpos, fixdur, nr_reps, timestep)
}