| 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 | ) |