Merge branch 'hashmap_replace' into 'master'

Hashmap C++ module replacement

See merge request millerp/sourceR!2

DESCRIPTION

@@ -19,8 +19,9 @@ Depends:
     tensorA,
     assertthat
 Imports:
+    methods,
+    Rcpp (>= 1.0.4),
     gtools,
-    hashmap,
     R6,
     cluster,
     stats,
@@ -28,7 +29,9 @@ Imports:
     SPIn,
     grDevices,
     reshape2
-RoxygenNote: 6.0.1
+LinkingTo: Rcpp
+DynLib: sourceR
+RoxygenNote: 7.1.0
 KeepSource: TRUE
 LazyData: TRUE
 Suggests:

NAMESPACE

@@ -24,3 +24,5 @@ importFrom(SPIn,SPIn)
 importFrom(grDevices,col2rgb)
 importFrom(grDevices,colorRampPalette)
 importFrom(stats,median)
+importFrom(Rcpp, sourceCpp)
+useDynLib(sourceR)

R/HashTable.R

+HashTable = function(keys=character(0), vals=numeric(0)) {
+  new("Rcpp_HashTable", keys, vals)
+}

R/mcmc.R

@@ -515,7 +515,7 @@ PoisGammaDPUpdate <- R6::R6Class(
           names(nk_local) <- names(nk)
           nk_local[self$node$s[i]] <- nk_local[self$node$s[i]] - 1
 
-          theta <- self$node$theta$values()
+          theta <- self$node$theta$find(names(nk))
 
           logpi <- log(nk_local) + y[i] * log(theta) - theta * aX[i]
           logpiplus <- log(self$node$conc) +
@@ -554,13 +554,11 @@ PoisGammaDPUpdate <- R6::R6Class(
             self$node$theta$erase(s_old)
             enqueue(self$node$idBucket, s_old)
             nk <- nk[names(nk) != s_old]
-            if (any(is.na(nk)))
-              browser()
           }
           nk[self$node$s[i]] <- nk[self$node$s[i]] + 1
         }
 
-        # Update theta
+        # Sample theta from the conditional posterior
         for (label in self$node$theta$keys())
         {
           sumy <- sum(y[self$node$s == label])

R/node.R

@@ -354,14 +354,14 @@ DirichletProcessNode <- R6::R6Class( # TODO: Make this accept a generic base dis
       self$baseRate <- rate
       self$idBucket <- queue()
       for(i in 1:length(s)) enqueue(self$idBucket, as.character(i))
-      h = replicate(length(theta), dequeue(self$idBucket))
-      self$theta <- hashmap::hashmap(h, theta)
-      self$s <- h[s]
+      keys = replicate(length(theta), dequeue(self$idBucket))
+      self$theta <- HashTable(keys, theta)
+      self$s <- keys[s]
     },
     getData = function()
       self$theta$find(self$s),
     getDensity = function(i)
-      sum(self$base(self$theta[self$s[i]],shape=self$baseShape, rate=self$baseRate ,log = T))
+      sum(self$base(self$theta$find(self$s[i]),shape=self$baseShape, rate=self$baseRate ,log = T))
   )
 )
 

R/sourceR.R

@@ -7,4 +7,5 @@
 #' The main sourceR method is \code{\link{HaldDP}}.
 #' @docType package
 #' @name sourceR
+#' @useDynLib sourceR
 NULL

R/zzz.R

+Rcpp::loadModule("HashTable_module")
+

man/AdaptiveDirMRW.Rd

@@ -4,9 +4,8 @@
 \name{AdaptiveDirMRW}
 \alias{AdaptiveDirMRW}
 \title{AdaptiveDirMRW}
-\format{Object of \code{\link{R6Class}} with methods for updating a \link{DirichletNode} instance.}
-\usage{
-AdaptiveDirMRW
+\format{
+Object of \code{\link{R6Class}} with methods for updating a \link{DirichletNode} instance.
 }
 \value{
 Object of \code{\link{AdaptiveDirMRW}}
@@ -27,8 +26,22 @@ Please note that no checks are performed as to the suitability of this
 algorithm for a particular \link{StochasticNode}.  It is up to the user
 to use the correct update algorithm for the appropriate nodes.
 }
-\section{Fields}{
+\section{Methods}{
 
+\describe{
+  \item{\code{new(node, toupdate = function() 1:length(node$getData()), tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
+  node, function to choose the indices of the elements to update (by default all elements), initial tuning vector (diagonal of adaptive tuning matrix), and the number of calls between
+  adaptations.}
+  \item{\code{update()}}{when called, updates \code{node}}
+  \item{\code{acceptance()}}{return the acceptance rate}
+}
+}
+
+\keyword{DAG}
+\keyword{MCMC}
+\keyword{node}
+\section{Public fields}{
+\if{html}{\out{<div class="r6-fields">}}
 \describe{
 \item{\code{cov}}{the current covariance}
 
@@ -41,19 +54,75 @@ to use the correct update algorithm for the appropriate nodes.
 \item{\code{ncalls}}{the number of times \code{update} has been called}
 
 \item{\code{node}}{the node to which the updater is attached}
-}}
+}
+\if{html}{\out{</div>}}
+}
+\section{Active bindings}{
+\if{html}{\out{<div class="r6-active-bindings">}}
+\describe{
+\item{\code{cov}}{the current covariance}
 
+\item{\code{burnin}}{the number of updates to burn in}
+}
+\if{html}{\out{</div>}}
+}
 \section{Methods}{
+\subsection{Public methods}{
+\itemize{
+\item \href{#method-new}{\code{AdaptiveDirMRW$new()}}
+\item \href{#method-update}{\code{AdaptiveDirMRW$update()}}
+\item \href{#method-acceptance}{\code{AdaptiveDirMRW$acceptance()}}
+\item \href{#method-clone}{\code{AdaptiveDirMRW$clone()}}
+}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-new"></a>}}
+\if{latex}{\out{\hypertarget{method-new}{}}}
+\subsection{Method \code{new()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveDirMRW$new(
+  node,
+  toupdate = function() 1:length(node$getData()),
+  tune = rep(0.1, length(node$getData())),
+  batchsize = 50,
+  name = "name"
+)}\if{html}{\out{</div>}}
+}
 
-\describe{
-  \item{\code{new(node, toupdate = function() 1:length(node$getData()), tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
-  node, function to choose the indices of the elements to update (by default all elements), initial tuning vector (diagonal of adaptive tuning matrix), and the number of calls between
-  adaptations.}
-  \item{\code{update()}}{when called, updates \code{node}}
-  \item{\code{acceptance()}}{return the acceptance rate}
 }
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-update"></a>}}
+\if{latex}{\out{\hypertarget{method-update}{}}}
+\subsection{Method \code{update()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveDirMRW$update()}\if{html}{\out{</div>}}
 }
 
-\keyword{DAG}
-\keyword{MCMC}
-\keyword{node}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-acceptance"></a>}}
+\if{latex}{\out{\hypertarget{method-acceptance}{}}}
+\subsection{Method \code{acceptance()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveDirMRW$acceptance()}\if{html}{\out{</div>}}
+}
+
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-clone"></a>}}
+\if{latex}{\out{\hypertarget{method-clone}{}}}
+\subsection{Method \code{clone()}}{
+The objects of this class are cloneable with this method.
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveDirMRW$clone(deep = FALSE)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
+\item{\code{deep}}{Whether to make a deep clone.}
+}
+\if{html}{\out{</div>}}
+}
+}
+}

man/AdaptiveLogDirMRW.Rd

@@ -4,9 +4,8 @@
 \name{AdaptiveLogDirMRW}
 \alias{AdaptiveLogDirMRW}
 \title{AdaptiveLogDirMRW}
-\format{Object of \code{\link{R6Class}} with methods for updating a \link{DirichletNode} instance.}
-\usage{
-AdaptiveLogDirMRW
+\format{
+Object of \code{\link{R6Class}} with methods for updating a \link{DirichletNode} instance.
 }
 \value{
 Object of \code{\link{AdaptiveLogDirMRW}}
@@ -28,8 +27,22 @@ Please note that no checks are performed as to the suitability of this
 algorithm for a particular \link{StochasticNode}.  It is up to the user
 to use the correct update algorithm for the appropriate nodes.
 }
-\section{Fields}{
+\section{Methods}{
 
+\describe{
+  \item{\code{new(node, toupdate = function() 1:length(node$getData()), tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
+  node, function to choose the indices of the elements to update (by default all elements), initial tuning vector (diagonal of adaptive tuning matrix), and number of calls between
+  adaptations.}
+  \item{\code{update()}}{when called, updates \code{node}}
+  \item{\code{acceptance()}}{return the acceptance rate}
+}
+}
+
+\keyword{DAG}
+\keyword{MCMC}
+\keyword{node}
+\section{Public fields}{
+\if{html}{\out{<div class="r6-fields">}}
 \describe{
 \item{\code{cov}}{the current covariance}
 
@@ -42,19 +55,75 @@ to use the correct update algorithm for the appropriate nodes.
 \item{\code{ncalls}}{the number of times \code{update} has been called}
 
 \item{\code{node}}{the node to which the updater is attached}
-}}
+}
+\if{html}{\out{</div>}}
+}
+\section{Active bindings}{
+\if{html}{\out{<div class="r6-active-bindings">}}
+\describe{
+\item{\code{cov}}{the current covariance}
 
+\item{\code{burnin}}{the number of updates to burn in}
+}
+\if{html}{\out{</div>}}
+}
 \section{Methods}{
+\subsection{Public methods}{
+\itemize{
+\item \href{#method-new}{\code{AdaptiveLogDirMRW$new()}}
+\item \href{#method-update}{\code{AdaptiveLogDirMRW$update()}}
+\item \href{#method-acceptance}{\code{AdaptiveLogDirMRW$acceptance()}}
+\item \href{#method-clone}{\code{AdaptiveLogDirMRW$clone()}}
+}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-new"></a>}}
+\if{latex}{\out{\hypertarget{method-new}{}}}
+\subsection{Method \code{new()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveLogDirMRW$new(
+  node,
+  toupdate = function() 1:length(node$getData()),
+  tune = rep(0.1, length(node$getData())),
+  batchsize = 50,
+  name = "name"
+)}\if{html}{\out{</div>}}
+}
 
-\describe{
-  \item{\code{new(node, toupdate = function() 1:length(node$getData()), tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
-  node, function to choose the indices of the elements to update (by default all elements), initial tuning vector (diagonal of adaptive tuning matrix), and number of calls between
-  adaptations.}
-  \item{\code{update()}}{when called, updates \code{node}}
-  \item{\code{acceptance()}}{return the acceptance rate}
 }
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-update"></a>}}
+\if{latex}{\out{\hypertarget{method-update}{}}}
+\subsection{Method \code{update()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveLogDirMRW$update()}\if{html}{\out{</div>}}
 }
 
-\keyword{DAG}
-\keyword{MCMC}
-\keyword{node}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-acceptance"></a>}}
+\if{latex}{\out{\hypertarget{method-acceptance}{}}}
+\subsection{Method \code{acceptance()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveLogDirMRW$acceptance()}\if{html}{\out{</div>}}
+}
+
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-clone"></a>}}
+\if{latex}{\out{\hypertarget{method-clone}{}}}
+\subsection{Method \code{clone()}}{
+The objects of this class are cloneable with this method.
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveLogDirMRW$clone(deep = FALSE)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
+\item{\code{deep}}{Whether to make a deep clone.}
+}
+\if{html}{\out{</div>}}
+}
+}
+}

man/AdaptiveMultiMRW.Rd

@@ -4,9 +4,8 @@
 \name{AdaptiveMultiMRW}
 \alias{AdaptiveMultiMRW}
 \title{AdaptiveMultiMRW}
-\format{Object of \code{\link{R6Class}} with methods for updating a \link{Node} instance.}
-\usage{
-AdaptiveMultiMRW
+\format{
+Object of \code{\link{R6Class}} with methods for updating a \link{Node} instance.
 }
 \value{
 Object of \code{\link{AdaptiveMultiMRW}}
@@ -25,8 +24,21 @@ Please note that no checks are performed as to the suitability of this
 algorithm for a particular \link{StochasticNode}.  It is up to the user
 to use the correct update algorithm for the appropriate nodes.
 }
-\section{Fields}{
+\section{Methods}{
 
+\describe{
+  \item{\code{new(node, tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
+  node, initial tuning vector (diagonal of adaptive tuning matrix), and number of burnin calls.}
+  \item{\code{update()}}{when called, updates \code{node}}
+  \item{\code{acceptance()}}{return the acceptance rate}
+}
+}
+
+\keyword{DAG}
+\keyword{MCMC}
+\keyword{node}
+\section{Public fields}{
+\if{html}{\out{<div class="r6-fields">}}
 \describe{
 \item{\code{cov}}{the current covariance}
 
@@ -39,18 +51,64 @@ to use the correct update algorithm for the appropriate nodes.
 \item{\code{ncalls}}{the number of times \code{update} has been called}
 
 \item{\code{node}}{the node to which the updater is attached}
-}}
-
+}
+\if{html}{\out{</div>}}
+}
 \section{Methods}{
+\subsection{Public methods}{
+\itemize{
+\item \href{#method-new}{\code{AdaptiveMultiMRW$new()}}
+\item \href{#method-update}{\code{AdaptiveMultiMRW$update()}}
+\item \href{#method-acceptance}{\code{AdaptiveMultiMRW$acceptance()}}
+\item \href{#method-clone}{\code{AdaptiveMultiMRW$clone()}}
+}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-new"></a>}}
+\if{latex}{\out{\hypertarget{method-new}{}}}
+\subsection{Method \code{new()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveMultiMRW$new(
+  node,
+  tune = rep(0.1, length(node$getData())),
+  burnin = 100
+)}\if{html}{\out{</div>}}
+}
 
-\describe{
-  \item{\code{new(node, tune = rep(0.1, length(node$getData())), burning = 100)}}{constructor takes an instance of a \link{StochasticNode}
-  node, initial tuning vector (diagonal of adaptive tuning matrix), and number of burnin calls.}
-  \item{\code{update()}}{when called, updates \code{node}}
-  \item{\code{acceptance()}}{return the acceptance rate}
 }
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-update"></a>}}
+\if{latex}{\out{\hypertarget{method-update}{}}}
+\subsection{Method \code{update()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveMultiMRW$update()}\if{html}{\out{</div>}}
 }
 
-\keyword{DAG}
-\keyword{MCMC}
-\keyword{node}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-acceptance"></a>}}
+\if{latex}{\out{\hypertarget{method-acceptance}{}}}
+\subsection{Method \code{acceptance()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveMultiMRW$acceptance()}\if{html}{\out{</div>}}
+}
+
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-clone"></a>}}
+\if{latex}{\out{\hypertarget{method-clone}{}}}
+\subsection{Method \code{clone()}}{
+The objects of this class are cloneable with this method.
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{AdaptiveMultiMRW$clone(deep = FALSE)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
+\item{\code{deep}}{Whether to make a deep clone.}
+}
+\if{html}{\out{</div>}}
+}
+}
+}

man/Alpha_.Rd

 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/data.R
-\docType{data}
 \name{Alpha_}
 \alias{Alpha_}
 \title{Alpha prior hyperparameter class}
-\format{An object of class \code{R6ClassGenerator} of length 24.}
-\usage{
-Alpha_
-}
 \description{
 Alpha prior hyperparameter class
+
+Alpha prior hyperparameter class
+}
+\section{Super class}{
+\code{\link[sourceR:Data]{sourceR::Data}} -> \code{Alpha}
+}
+\section{Methods}{
+\subsection{Public methods}{
+\itemize{
+\item \href{#method-clone}{\code{Alpha_$clone()}}
+}
+}
+\if{html}{
+\out{<details open ><summary>Inherited methods</summary>}
+\itemize{
+\item \out{<span class="pkg-link" data-pkg="sourceR" data-topic="Data" data-id="initialize">}\href{../../sourceR/html/Data.html#method-initialize}{\code{sourceR::Data$initialize()}}\out{</span>}
+}
+\out{</details>}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-clone"></a>}}
+\if{latex}{\out{\hypertarget{method-clone}{}}}
+\subsection{Method \code{clone()}}{
+The objects of this class are cloneable with this method.
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{Alpha_$clone(deep = FALSE)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
+\item{\code{deep}}{Whether to make a deep clone.}
+}
+\if{html}{\out{</div>}}
+}
+}
 }
-\keyword{datasets}

man/DPModel_impl.Rd

 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/model.R
-\docType{data}
 \name{DPModel_impl}
 \alias{DPModel_impl}
 \title{Builds the source attribution model. Is not intended to be used by a regular user.
 Developers only here!}
-\format{\code{\link{R6Class}} object.}
-\usage{
-DPModel_impl
+\format{
+\code{\link{R6Class}} object.
 }
 \value{
 Object of \code{\link{R6Class}}.
 }
 \description{
+Builds the source attribution model. Is not intended to be used by a regular user.
+Developers only here!
+
 Builds the source attribution model. Is not intended to be used by a regular user.
 Developers only here!
 }
-\section{Fields}{
+\section{Public fields}{
+\if{html}{\out{<div class="r6-fields">}}
+\describe{
+\item{\code{y}}{3D array of [type, time, location] of the number of human cases}
+
+\item{\code{X}}{3D array of the number of positive samples for each type, source and time
+[type, source, time]}
+
+\item{\code{R}}{3D array of normalised relative prevalences for each timepoint
+[type, source, time]}
+
+\item{\code{Time}}{a character vector of timepoint ids matching time dimension in y and R}
+
+\item{\code{Location}}{a character vector of location ids matching location dimension in y}
+
+\item{\code{Sources}}{a character vector of source ids matching the source dimension in X}
+
+\item{\code{Type}}{a character vector of type ids matching the type dimension in X}
+
+\item{\code{prev}}{a 2D array (matrix) of [source, time].}
+
+\item{\code{a_q}}{concentration parameter for the DP}
+
+\item{\code{a_theta}}{shape parameter for the Gamma base distribution for the DP}
+
+\item{\code{b_theta}}{rate parameter for the Gamma base distribution for the DP}
+
+\item{\code{a_r}}{3D array of [type, src, time] for the hyperprior on the relative prevalences R}
+
+\item{\code{a_alpha}}{3D array of [source, time, location] for the prior on the alpha parameters}
+
+\item{\code{s}}{vector giving initial group allocation for each type for the DP}
 
+\item{\code{theta}}{vector giving initial values for each group in the DP}
+
+\item{\code{alpha}}{3D array of [source, time, location] giving initial values for the alpha
+parameters}
+}
+\if{html}{\out{</div>}}
+}
+\section{Active bindings}{
+\if{html}{\out{<div class="r6-active-bindings">}}
 \describe{
 \item{\code{y}}{3D array of [type, time, location] of the number of human cases}
 
@@ -53,6 +94,57 @@ Developers only here!
 
 \item{\code{alpha}}{3D array of [source, time, location] giving initial values for the alpha
 parameters}
-}}
+}
+\if{html}{\out{</div>}}
+}
+\section{Methods}{
+\subsection{Public methods}{
+\itemize{
+\item \href{#method-new}{\code{DPModel_impl$new()}}
+\item \href{#method-clone}{\code{DPModel_impl$clone()}}
+}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-new"></a>}}
+\if{latex}{\out{\hypertarget{method-new}{}}}
+\subsection{Method \code{new()}}{
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{DPModel_impl$new(
+  y,
+  X,
+  R,
+  Time,
+  Location,
+  Sources,
+  Type,
+  prev,
+  a_q,
+  a_theta,
+  b_theta,
+  a_r,
+  a_alpha,
+  s,
+  theta,
+  alpha
+)}\if{html}{\out{</div>}}
+}
 
-\keyword{datasets}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-clone"></a>}}
+\if{latex}{\out{\hypertarget{method-clone}{}}}
+\subsection{Method \code{clone()}}{
+The objects of this class are cloneable with this method.
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{DPModel_impl$clone(deep = FALSE)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
+\item{\code{deep}}{Whether to make a deep clone.}
+}
+\if{html}{\out{</div>}}
+}
+}
+}

man/DataNode.Rd

@@ -4,9 +4,8 @@
 \name{DataNode}
 \alias{DataNode}
 \title{DataNode}
-\format{Object of \code{\link{R6Class}} with methods for constructing a DAG.}
-\usage{
-DataNode
+\format{
+Object of \code{\link{R6Class}} with methods for constructing a DAG.
 }
 \value{
 Object of \code{\link{DataNode}}
@@ -17,12 +16,6 @@ Represents a static data node in a DAG.
 \details{
 Derived from \link{Node}, please see base class documentation.
 }
-\section{Fields}{
-
-\describe{
-\item{\code{data}}{the data}
-}}
-
 \section{Methods}{
 
 \describe{
@@ -32,3 +25,68 @@ Derived from \link{Node}, please see base class documentation.
 
 \keyword{DAG}
 \keyword{node}
+\section{Super class}{
+\code{\link[sourceR:Node]{sourceR::Node}} -> \code{DataNode}