R/Forecaster.R

   1 #' @title Forecaster (abstract class)
   2 #'
   3 #' @description Abstract class to represent a forecaster (they all inherit this)
   4 #'
   5 #' @field params List of computed parameters, for post-run analysis (dev)
   6 #' @field data Dataset, object of class Data
   7 #' @field pjump Function: how to predict the jump at day interface ?
   8 Forecaster = setRefClass(
   9     Class = "Forecaster",
  10
  11     fields = list(
  12         params = "list",
  13         data = "Data",
  14         pjump = "function"
  15     ),
  16
  17     methods = list(
  18         initialize = function(...)
  19         {
  20             "Initialize (generic) Forecaster object"
  21
  22             callSuper(...)
  23             if (!hasArg(data))
  24                 stop("Forecaster must be initialized with a Data object")
  25             params <<- list()
  26         },
  27         predict = function(today, memory, horizon, ...)
  28         {
  29             "Obtain a new forecasted time-serie"
  30
  31             # Parameters (potentially) computed during shape prediction stage
  32             predicted_shape = predictShape(today, memory, horizon, ...)
  33             predicted_delta = pjump(data, today, memory, horizon, params, ...)
  34             # Predicted shape is aligned it on the end of current day + jump
  35             predicted_shape + tail(data$getSerie(today),1) - predicted_shape[1] + predicted_delta
  36         },
  37         predictShape = function(today, memory, horizon, ...)
  38         {
  39             "Shape prediction (centered curve)"
  40
  41             #empty default implementation: to implement in inherited classes
  42         },
  43         getParameters = function()
  44         {
  45             params
  46         }
  47     )
  48 )