pkg/R/Forecaster.R

   1 #' Forecaster
   2 #'
   3 #' Forecaster (abstract class, implemented by all forecasters)
   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 #'
   9 #' @docType class
  10 #' @importFrom R6 R6Class
  11 Forecaster = R6::R6Class("Forecaster",
  12     private = list(
  13         .params = "list",
  14         .data = "Data",
  15         .pjump = "function"
  16     ),
  17     public = list(
  18         initialize = function(data, pjump)
  19             initialize(self, private, data, pjump)
  20         ,
  21         predictSerie = function(today, memory, horizon, ...)
  22             predictSerie(private, today, memory, horizon, ...)
  23         ,
  24         predictShape = function(today, memory, horizon, ...)
  25             predictShape(private, today, memory, horizon, ...)
  26         ,
  27         getParameters = function()
  28             getParameters(private)
  29     )
  30 )
  31
  32 #' Initialize (generic) Forecaster object
  33 #'
  34 #' @param o Object of class Forecaster
  35 #' @param private List of private members in o
  36 #' @param data Object of class Data
  37 #' @param pjump Function to predict jump
  38 initialize = function(o, private, data, pjump)
  39 {
  40     .params <<- list()
  41     .data <<- data
  42     .pjump <<- pjump
  43     invisible(o)
  44 }
  45
  46 #' Obtain a new forecasted time-serie
  47 #'
  48 #' @inheritParams initialize
  49 #' @param today Index for current prediction
  50 #' @param memory Depth in data (in days)
  51 #' @param horizon Number of hours to forecast
  52 predictSerie = function(private, today, memory, horizon, ...)
  53 {
  54     # Parameters (potentially) computed during shape prediction stage
  55     predicted_shape = predictShape(today, memory, horizon, ...)
  56     predicted_delta = private$.pjump(private$.data, today, memory, horizon, params, ...)
  57     # Predicted shape is aligned it on the end of current day + jump
  58     predicted_shape + tail(private$.data$getSerie(today),1) - predicted_shape[1] + predicted_delta
  59 }
  60
  61 #' Shape prediction (centered curve)
  62 #'
  63 #' @inheritParams predictSerie
  64 predictShape = function(private, today, memory, horizon, ...)
  65     #empty default implementation: to implement in inherited classes
  66
  67 #' Get parameters list
  68 #'
  69 #' @inheritParams initialize
  70 getParameters = function(private)
  71     private$.params