AbstractIncidenceMatrix: AbstractIncidenceMatrix

In ForecastFramework: A Basis for Modular Model Creation

Description

An abstract class for storing an actual matrix. It has an actual matrix of data mat, which it is responsible for storing. For creating matrices with particular metadata, consider extending IncidenceMatrix instead of this class. Extend this class if you have data which can be thought of as a matrix, but that is not its true form. ## TODO: Include an example of this.

Fields

cellData

A list of metadata associated with the cells of the data.

cnames

The names of columns in the data.

colData

A list of metadata associated with the columns of the data.

mat

This is the matrix. For extensibility, it cannot be written to directly and must be modified through methods.

metaData

Any data not part of the main data structure.

ncol

The number of columns in the data.

nrow

The number of rows in the data

rnames

The names of rows in the data.

rowData

A list of metadata associated with the columns of the data.

Methods

addColumns(columns,mutate=TRUE)

This method must be extended. This function adds empty columns to the right side of the data.

Arguments

columns	-	The number of columns to add.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

addRows(rows,mutate=TRUE)

This method must be extended. This function adds empty rows to the data.

Arguments

rows	-	The number of rows to add.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

debug(string)

A function for debugging the methods of this class. It calls the browser command. In order for methods to opt into to debugging, they need to implement the following code at the beginning: if(<method_name> %in% private$.debug){browser()}. This method exists, because the debugger is not always intuitive when it comes to debugging R6 methods.

Arguments

string	-	The name(s) of methods to debug as a character vector

diff(lag=1,mutate=TRUE)

This method must be extended. This function replaces the matrix value at column i with the difference. between the values at columns i and (i-lag).

Arguments

lag	-	How far back to diff. Defaults to 1.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

head(k,direction,mutate=TRUE...)

This method must be extended. Select the first k slices of the data in dimension direction.

Arguments

k	-	The number of slices to keep.
direction	-	The dimension to take a subset of. 1 for row, 2 for column.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

initialize(...)

This function should be extended. Create a new instance of this class.

Arguments

...	-	This function should take in any arguments just in case.

lag(indices,mutate=TRUE,na.rm=FALSE)

This method must be extended. This function replaces the current matrix with a new matrix with one column for every column, and a row for every row/index combination. The column corresponding to the row and index will have the value of the original matrix in the same row, but index columns previous. This shift will introduce NAs where it passes off the end of the matrix.

Arguments

indices	-	A sequence of lags to use as part of the data. Note that unless this list contains 0, the data will all be shifted back by at least one year.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.
na.rm	-	Whether to remove NA values generated by walking off the edge of the matrix.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

mutate(rows,cols,data)

This method must be extended. This function is a way to modify the data as though it were a matrix.

Arguments

rows	-	Which rows to modify. These can be numeric or names.
cols	-	Which cols to modify. These can be numeric or names.
data	-	The data to change the chosen values to. It needs to be the right shape.

scale(f,mutate=TRUE)

This method must be extended. This function rescales each element of our object according to f

Arguments

f	-	a function which takes in a number and outputs a rescaled version of that number
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

subset(rows,cols,mutate=TRUE...)

This method must be extended. Select the data corresponding to the rows rows and the columns columns. rows and columns can be either numeric or named indices.

Arguments

rows	-	An row index or list of row indices which can be either numeric or named.
cols	-	An column index or list of column indices which can be either numeric or named.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

tail(k,direction,mutate=TRUE...)

This method must be extended. Select the last k slices of the data in dimension direction.

Arguments

k	-	The number of slices to keep.
direction	-	The dimension to take a subset of. 1 for row, 2 for column.
mutate	-	Whether to change the original instance, or create a new one. If FALSE, the instance performing the method will be left unchanged, and a modified copy will be returned. If true, then the instance will modify itself and return nothing.

Value

If mutate=FALSE, a clone of this object will run the method and be returned. Otherwise, there is no return.

undebug(string)

A function for ceasing to debug methods. Normally a method will call the browser command every time it is run. This command will stop it from doing so.

Arguments

string	-	The name(s) of the methods to stop debugging.

See Also

Inherits from : MatrixData

Is inherited by : IncidenceMatrix

Examples

IncidenceMatrix <- R6Class(
  classname = "IncidenceMatrix",
  inherit = AbstractIncidenceMatrix,
  public = list(
    initialize = function(
      data=matrix(),
      metaData=list(),
      rowData=list(),
      colData=list()
    ){
      if(Reduce(
        '&&',
        c('MatrixData','DataContainer','Generic','R6') %in% class(data))
      ){
        private$.mat <- data$mat
        private$.metaData <- data$metaData
        private$.nrow <- data$nrow
        private$.ncol <- data$ncol
        private$.rnames <- data$rnames
        private$.cnames <- data$cnames
        private$.rowData <- data$rowData
        private$.colData <- data$colData
        private$.metaData <- data$metaData
        private$.cellData <- data$cellData
      }
      else{
        rtoggle = FALSE
        ctoggle = FALSE
        try({
          rnames <- dimnames(data)[[1]]
          rtoggle = TRUE
        })
        try({
          cnames <- dimnames(data)[[2]]
          ctoggle = TRUE
        })
        if(!private$checkType(name='.mat',val=data,type='private')){
          data <- as.matrix(data)
          if(rtoggle){
            rownames(data) = rnames
          }
          if(ctoggle){
            colnames(data) = cnames
          }
        }
        if(!private$checkType(name='.mat',val=data,type='private')){
          stop(paste(
            "invalid data of type",
            paste(class(data),collapse=','),
            "expected",
            paste(class(private$.mat),collapse = ',')
          ))
        }
        if(length(dim(data)) > 2){
          stop("The matrix is not intended to hold things with more than 3 dimensions.")
        }
        ndim = dim(data)
        private$.nrow = ndim[[1]]
        private$.ncol = ndim[[2]]
        private$.rnames = rownames(data)
        private$.cnames = colnames(data)
        private$.mat <- 0+data
        self$rowData <- rowData
        self$colData <- colData
        self$metaData <- metaData
      }
    },
    subset = function(rows,cols,mutate=TRUE){
      if('subset' %in% private$.debug){
        browser()
      }
      if(!mutate){
        temp = self$clone(TRUE)
        temp$subset(rows,cols,mutate=TRUE)
        return(temp)
      }
      if(missing(rows) && missing(cols)){
      }
      else if(missing(rows)){
        private$.mat = self$mat[,cols,drop=FALSE]
        if(length(private$.colData) > 0){
          private$.colData <- lapply(
            private$.colData,function(x){x[cols,drop=FALSE]}
          )
        }
      }
      else if(missing(cols)){
        private$.mat = self$mat[rows,,drop=FALSE]
        if(length(private$.rowData) > 0){
          private$.rowData <- lapply(
            private$.rowData,function(x){x[rows,drop=FALSE]}
          )
        }
      }
      else{
        private$.mat = self$mat[rows,cols,drop=FALSE]
        if(length(private$.rowData)>0){
          private$.rowData <- lapply(
            private$.rowData,function(x){x[rows,drop=FALSE]}
          )
        }
        if(length(private$.colData)>0){
          private$.colData <- lapply(
            private$.colData,function(x){x[cols,drop=FALSE]}
          )
        }
      }
      private$.nrow = nrow(private$.mat)
      private$.rnames = rownames(private$.mat)
      private$.ncol = ncol(private$.mat)
      private$.cnames = colnames(private$.mat)
    },
    head = function(k,direction=2){
      if('head' %in% private$.debug){
        browser()
      }
      if(k>dim(private$.mat)[[direction]]){
        stop("The size of the head is too large.")
      }
      indices = 1:k
      if(direction==1){
        private$.mat = self$mat[indices,,drop=FALSE]
        if(length(private$.rowData)>0){
          for(i in 1:length(private$.rowData)){
            private$.rowData[[i]] = private$.rowData[[i]][indices,drop=FALSE]
          }
        }
      }
      else if(direction==2){
        private$.mat = self$mat[,indices,drop=FALSE]
        if(length(private$.colData)>0){
          for(i in 1:length(private$.colData)){
            private$.colData[[i]] = private$.colData[[i]][indices,drop=FALSE]
          }
        }
      }
      else{
        stop("This direction is not allowed.")
      }
      private$.nrow = nrow(private$.mat)
      private$.ncol = ncol(private$.mat)
      private$.cnames = colnames(private$.mat)
      private$.rnames = rownames(private$.mat)
    },
    tail = function(k,direction=2){
      if('tail' %in% private$.debug){
        browser()
      }
      if(k>dim(private$.mat)[[direction]]){
        stop("The size of the tail is too large.")
      }
      indices = (dim(self$mat)[[direction]]-k+1):dim(self$mat)[[direction]]
      if(direction==1){
        private$.mat = self$mat[indices,,drop=FALSE]
        if(length(private$.rowData)>0){
          for(i in 1:length(private$.rowData)){
            private$.rowData[[i]] = private$.rowData[[i]][indices,drop=FALSE]
          }
        }
      }
      else if(direction==2){
        private$.mat = self$mat[,indices,drop=FALSE]
        if(length(private$.colData)>0){
          for(i in 1:length(private$.colData)){
            private$.colData[[i]] = private$.colData[[i]][indices,drop=FALSE]
          }
        }
      }
      else{
        stop("This direction is not allowed.")
      }
      private$.nrow = nrow(private$.mat)
      private$.ncol = ncol(private$.mat)
      private$.cnames = colnames(private$.mat)
      private$.rnames = rownames(private$.mat)
    },
    lag = function(indices,mutate=TRUE,na.rm=FALSE){
      if('lag' %in% private$.debug){
        browser()
      }
      if(mutate==FALSE){
        tmp = self$clone(TRUE)
        tmp$lag(indices=indices,mutate=TRUE,na.rm=na.rm)
        return(tmp)
      }
      if((1+max(indices)) > self$ncol){
        stop("We cannot go further back than the start of the matrix")
      }
      numLags = length(indices)
      oldNrow = self$nrow
      if(is.null(rownames(private$.mat))){
        rownames(private$.mat) = 1:(dim(private$.mat)[[1]])
      }
      rownames = replicate(numLags,rownames(private$.mat))
      colnames = colnames(private$.mat)
      private$.mat <- 0+array(self$mat,c(dim(self$mat),numLags))
      if(numLags <= 0){
        stop("indices must be nonempty for the calculation of lags to make sense.")
      }
      for(lag in 1:numLags){
        private$.mat[,(1+indices[[lag]]):self$ncol,lag] <-
          private$.mat[,1:(self$ncol-indices[[lag]]),lag]
        if(indices[[lag]] > 0){
          private$.mat[,1:(indices[[lag]]),lag] = NA
        }
      }
      private$.mat = aperm(private$.mat,c(1,3,2))
      private$.mat = matrix(private$.mat,self$nrow*numLags,self$ncol)
      lagnames = t(replicate(self$nrow,paste('L',indices,sep='')))
      rownames(private$.mat) <-
        as.character(paste(lagnames,"R",rownames,sep=''),numLags*self$nrow)
      colnames(private$.mat) <- colnames
      private$.nrow = self$nrow * numLags
      private$.rnames = rownames(private$.mat)
      if(length(private$.rowData) > 0){
        private$.rowData <- lapply(
          private$.rowData,
          function(x){
            c(unlist(recursive=FALSE,lapply(1:numLags,function(y){x})))
          }
        )
      }
      if(na.rm==T){
        self$subset(cols=!apply(private$.mat,2,function(x){any(is.na(x))}))
      }
    },
    scale = function(f,mutate=TRUE){
      if('scale' %in% private$.debug){
        browser()
      }
      if(!mutate){
        tmp = self$clone(TRUE)
        tmp$scale(f=f,mutate=TRUE)
        return(tmp)
      }
      private$.mat[] = f(private$.mat[])
    },
    diff = function(lag = 1,mutate=TRUE){
      if('diff' %in% private$.debug){
        browser()
      }
      if(lag == 0){
        if(!is.null(private$.rnames)){
          rownames(private$.mat) =
            paste("D",lag,"R",private$.rnames,sep='')
          private$.rnames = rownames(private$.mat)
        } else {
          rownames(private$.mat) =
            paste("D",lag,"R",1:private$.nrow,sep='')
          private$.rnames = rownames(private$.mat)
        }
        return()
      }
      if(lag < 0){
        stop("Lag should be non-negative.")
      }
      if(!mutate){
        tmp = self$clone(TRUE)
        tmp$diff(lag=lag,mutate=TRUE)
        return(tmp)
      }
      private$.mat <-
        self$mat - self$lag(indices=lag,mutate=FALSE,na.rm=FALSE)$mat
      if(!is.null(private$.rnames)){
        rownames(private$.mat) =
          paste("D",lag,"R",private$.rnames,sep='')
        private$.rnames = rownames(private$.mat)
      } else {
        rownames(private$.mat) =
          paste("D",lag,"R",1:private$.nrow,sep='')
        private$.rnames = rownames(private$.mat)
      }
    },
    addColumns = function(columns){
      if('addColumns' %in% private$.debug){
        browser()
      }
      if(columns == 0){
        return()
      }
      cbind(private$.mat , matrix(NA,private$.nrow,columns)) -> private$.mat
      private$.ncol = ncol(private$.mat)
      if(!is.null(private$.cnames)){
        colnames(private$.mat) = c(private$.cnames,replicate(columns,"NA"))
        private$.cnames = colnames(private$.mat)
      }
      if(length(private$.colData) > 0){
        private$.colData <- lapply(
          private$.colData,
          function(x){
            c(x,replicate(columns,NA))
          }
        )
      }
    },
    addRows = function(rows){
      if('addRows' %in% private$.debug){
        browser()
      }
      if(rows == 0){
        return()
      }
      rbind(private$.mat , matrix(NA,rows,private$.ncol)) -> private$.mat
      private$.nrow = nrow(private$.mat)
      if(!is.null(private$.rnames)){
        rownames(private$.mat) = c(private$.rnames,replicate(rows,"NA"))
        private$.rnames = rownames(private$.mat)
      }
      if(length(private$.rowData) > 0){
        private$.rowData <- lapply(
          private$.rowData,
          function(x){
            c(x,replicate(rows,NA))
          }
        )
      }
    },
    mutate = function(rows,cols,data){
      if('mutate' %in% private$.debug){
        browser()
      }
      data = as.matrix(data)
      if(missing(rows)){
        rows = 1:private$.nrow
        if(!(is.null(private$.cnames) || is.null(colnames(data)))){
          private$.cnames[cols] = colnames(data)
          colnames(private$.mat) = private$.cnames
        }
      }
      if(missing(cols)){
        cols = 1:private$.ncol
        if(!(is.null(private$.rnames) || is.null(rownames(data)))){
          private$.rnames[rows] = rownames(data)
          rownames(private$.mat) = private$.rnames
        }
      }
      if(is.null(dim(data))){
        stop("Not yet implemented for non-matrixlike objects")
      }
      if(length(dim(data)) > 2){
        stop("There are too many dimensions in data.")
      }
      if(length(dim(data)) == 2){
        private$.mat[rows,cols] = data
      }
    }
  ),
  active = list(
    mat = function(value){
      "The matrix of data."
      if('mat' %in% private$.debug){
        browser()
      }
      if(missing(value)){
        return(private$.mat)
      }
      stop(
        "Do not write directly to the mat. Either use methods to modify the mat,
         or create a new instance."
      )
    },
    colData = function(value){
      "The metaData associated with column in the matrix"
      if('colData' %in% private$.debug){
        browser()
      }
      if(missing(value)){
        if(length(private$.colData) > 0){
          for(i in 1:length(private$.colData)){
            if(private$.ncol != length(private$.colData[[i]])){
              stop("If you alter the matrix, please also edit the column metaData.")
            }
          }
        }
        return(private$.colData)
      }
      if(class(value) != 'list'){
        stop("Column metaData should be a list of lists.")
      }
      if(length(value)>0){
        for(i in 1:length(value)){
          if(
            Reduce(
              '&&',
              class(value[[i]]) !=
                c(
                  'list',
                  'character',
                  'numeric',
                  'integer',
                  'logical',
                  'raw',
                  'complex'
                )
            )
          ){
            if(dim(as.matrix(value[[i]]))[[1]] != private$.ncol){
              stop(paste(
                'The ',
                i,
                'th element of column metaData does not have one element for',
                'each column.',
                sep=''
              ))
            }
          }
          else{
            if(length(value[[i]])!=private$.ncol){
              stop(paste(
                'The ',
                i,
                'th element of column metaData does not have one element for',
                'each column.',
                sep=''
              ))
            }
          }
        }
      }
      private$.colData <- value
      if(length(private$.colData) > 0){
        for(i in 1:length(private$.colData)){
          names(private$.colData[[i]]) <- colnames(self$mat)
        }
      }
    },
    rowData = function(value){
      "The metaData associated with rows in the matrix"
      if('rowData' %in% private$.debug){
        browser()
      }
      if(missing(value)){
        if(length(private$.rowData) > 0){
          for(i in 1:length(private$.rowData)){
            if(private$.nrow != length(private$.rowData[[i]])){
              stop("If you alter the matrix, please also edit the row metaData.")
            }
          }
        }
        return(private$.rowData)
      }
      if(class(value) != 'list'){
        stop("row metaData should be a list of lists.")
      }
      if(length(value) > 0){
        for(i in 1:length(value)){
          if(
            Reduce('&&',
              class(value[[i]]) !=
                c(
                  'list',
                  'character',
                  'numeric',
                  'integer',
                  'logical',
                  'raw',
                  'complex'
                )
            )
          ){
            if(dim(as.matrix(value[[i]]))[[1]] != private$.nrow){
              stop(paste(
                'The ',
                i,
                'th element of row metaData does not have one element for each',
                'row.',
                sep=''
              ))
            }
          }
          else{
            if(length(value[[i]])!=private$.nrow){
              stop(paste(
                'The ',
                i,
                'th element of row metaData does not have one element for each',
                'row.',
                sep=''
              ))
            }
          }
        }
      }
      private$.rowData <- value
      if(length(private$.rowData)>0){
        for(i in 1:length(value)){
          names(private$.rowData[[i]]) <- rownames(self$mat)
        }
      }
    }
  )
)

ForecastFramework documentation built on April 14, 2020, 7:39 p.m.