From: Benjamin Auder <benjamin.auder@somewhere>
Date: Thu, 6 Apr 2017 16:14:41 +0000 (+0200)
Subject: on the way back without realtime
X-Git-Url: https://git.auder.net/variants/Dynamo/%7B%7B%20asset%28%27mixstore/doc/rpsls.js?a=commitdiff_plain;h=2057c793ad9929ed5bef8663ea28b896c84df0fc;p=talweg.git

on the way back without realtime
---

diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION
index b1697df..a897984 100644
--- a/pkg/DESCRIPTION
+++ b/pkg/DESCRIPTION
@@ -2,7 +2,7 @@ Package: talweg
 Title: Time-Series Samples Forecasted With Exogenous Variables
 Version: 0.1-0
 Description: Forecast a curve sampled within the day (seconds, minutes,
-    hours...), using past measured curves + paste exogenous informations, which
+    hours...), using past measured curves + past exogenous informations, which
     could be some aggregated measure on the past curves, the weather... Main
     starting point: computeForecast().
 Author: Benjamin Auder <Benjamin.Auder@math.u-psud.fr> [aut,cre],
@@ -23,8 +23,8 @@ Suggests:
 LazyData: yes
 URL: http://git.auder.net/?p=talweg.git
 License: MIT + file LICENSE
-RoxygenNote: 6.0.1
-Collate: 
+RoxygenNote: 5.0.1
+Collate:
     'A_NAMESPACE.R'
     'Data.R'
     'Forecaster.R'
diff --git a/pkg/R/A_NAMESPACE.R b/pkg/R/A_NAMESPACE.R
index 4558e59..bcd5df1 100644
--- a/pkg/R/A_NAMESPACE.R
+++ b/pkg/R/A_NAMESPACE.R
@@ -1,3 +1,7 @@
+#' @include Data.R
+#' @include Forecast.R
+#' @include Forecaster.R
+#'
 #' @importFrom grDevices colors gray.colors
 #' @importFrom graphics abline hist par plot
 #' @importFrom methods hasArg is
diff --git a/pkg/R/Data.R b/pkg/R/Data.R
index 551cfaf..53a8d5b 100644
--- a/pkg/R/Data.R
+++ b/pkg/R/Data.R
@@ -5,12 +5,14 @@
 #' @docType class
 #' @importFrom R6 R6Class
 #'
-#' @field .data List of \itemize{
+#' @field .data List of
+#' \itemize{
 #'   \item time: vector of times
-#'   \item serie: centered series
+#'   \item centered_serie: centered series
 #'   \item level: corresponding levels
 #'   \item exo: exogenous variables
-#'   \item exo_hat: predicted exogenous variables}
+#'   \item exo_hat: predicted exogenous variables
+#' }
 #'
 #' @section Methods:
 #' \describe{
@@ -18,24 +20,30 @@
 #'   Return number of series in dataset.}
 #' \item{\code{getStdHorizon()}}{
 #'   Return number of time steps from serie[1] until midnight}
-#' \item{\code{appendHat(time, hat_serie, hat_exo)}}{
-#'   New estimated data + time.}
+#' \item{\code{appendHat(time, exo_hat)}}{
+#'   New estimated exogenous variables + time}
 #' \item{\code{append(serie, exo)}}{
 #'   New measured data; call *after* \code{appendHat()}}
 #' \item{\code{getTime(index)}}{
 #'   Get times at specified index.}
-#' \item{\code{getCenteredSerie(index, hat=FALSE)}}{
+#' \item{\code{getCenteredSerie(index)}}{
 #'   Get (measured or predicted) centered serie at specified index.}
-#' \item{\code{getCenteredSeries(indices, hat=FALSE)}}{
+#' \item{\code{getCenteredSeries(indices)}}{
 #'   Get centered series at specified indices (in columns).}
-#' \item{\code{getLevel(index, hat=FALSE)}}{
+#' \item{\code{getLevel(index)}}{
 #'   Get level at specified index.}
-#' \item{\code{getSerie(index, hat=FALSE)}}{
+#' \item{\code{getSerie(index)}}{
 #'   Get serie (centered+level) at specified index.}
-#' \item{\code{getSeries(indices, hat=FALSE)}}{
+#' \item{\code{getSeries(indices)}}{
 #'   Get series at specified indices (in columns).}
-#' \item{\code{getExo(index, hat=FALSE)}}{
+#' \item{\code{getExoHat(index)}}{
+#'   Get predicted exogenous variables at specified index.}
+#' \item{\code{getExo(index)}}{
 #'   Get exogenous variables at specified index.}
+#' \item{\code{removeFirst()}}{
+#'   Remove first list element (if truncated).}
+#' \item{\code{removeLast()}}{
+#'   Remove last list element (if truncated).}
 #' }
 #'
 Data = R6::R6Class("Data",
@@ -49,64 +57,54 @@ Data = R6::R6Class("Data",
 		getStdHorizon = function()
 			24 - as.POSIXlt( private$.data[[1]]$time[1] )$hour + 1
 		,
-		appendHat = function(time, hat_serie, hat_exo)
-		{
-			hat_level = mean(hat_serie, na.rm=TRUE)
-			hat_centered_serie = hat_serie - hat_level
-			private$.data[[length(private$.data)+1]] <- list(
-				"time"=time, "hat_centered_serie"=hat_centered_serie,
-				"hat_level"=hat_level, "hat_exo"=hat_exo )
-		},
-		append = function(serie, exo)
+		appendHat = function(time, exo_hat)
+			private$.data[[length(private$.data)+1]] <- list("time"=time,"exo_hat"=exo_hat)
+		,
+		append = function(time, serie, exo)
 		{
+			index <- length(private$.data)
 			level = mean(serie, na.rm=TRUE)
 			centered_serie = serie - level
-			private$.data[[length(private$.data)]]$centered_serie <- centered_serie,
-			private$.data[[length(private$.data)]]$level <- level,
-			private$.data[[length(private$.data)]]$exo <- exo,
+			private$.data[[index]]$time <- time
+			private$.data[[index]]$centered_serie <- centered_serie
+			private$.data[[index]]$level <- level
+			private$.data[[index]]$exo <- exo
 		},
 		getTime = function(index)
 		{
 			index = dateIndexToInteger(index, self)
 			private$.data[[index]]$time
 		},
-		getCenteredSerie = function(index, hat=FALSE)
+		getCenteredSerie = function(index)
 		{
 			index = dateIndexToInteger(index, self)
-			if (hat)
-				private$.data[[index]]$hat_centered_serie
-			else
-				private$.data[[index]]$centered_serie
+			private$.data[[index]]$centered_serie
 		},
-		getCenteredSeries = function(indices, hat=FALSE)
-			sapply(indices, function(i) self$getCenteredSerie(i, hat))
+		getCenteredSeries = function(indices)
+			sapply(indices, function(i) self$getCenteredSerie(i))
 		,
-		getLevel = function(index, hat=FALSE)
+		getLevel = function(index)
 		{
 			index = dateIndexToInteger(index, self)
-			if (hat)
-				private$.data[[index]]$hat_level
-			else
-				private$.data[[index]]$level
+			private$.data[[index]]$level
 		},
-		getSerie = function(index, hat=FALSE)
+		getSerie = function(index)
 		{
 			index = dateIndexToInteger(index, self)
-			if (hat)
-				private$.data[[index]]$hat_centered_serie + private$.data[[index]]$hat_level
-			else
-				private$.data[[index]]$centered_serie + private$.data[[index]]$level
+			private$.data[[index]]$centered_serie + private$.data[[index]]$level
 		},
-		getSeries = function(indices, hat=FALSE)
-				sapply(indices, function(i) self$getSerie(i, hat))
+		getSeries = function(indices)
+			sapply(indices, function(i) self$getSerie(i))
 		,
-		getExo = function(index, hat=FALSE)
+		getExoHat = function(index)
+		{
+			index = dateIndexToInteger(index, self)
+			private$.data[[index]]$exo_hat
+		},
+		getExo = function(index)
 		{
 			index = dateIndexToInteger(index, self)
-			if (hat)
-				private$.data[[index]]$hat_exo
-			else
-				private$.data[[index]]$exo
+			private$.data[[index]]$exo
 		},
 		removeFirst = function()
 			private$.data <- private$.data[2:length(private$.data)]
diff --git a/pkg/R/F_Average.R b/pkg/R/F_Average.R
index c28125e..a5e3c3e 100644
--- a/pkg/R/F_Average.R
+++ b/pkg/R/F_Average.R
@@ -1,10 +1,9 @@
-#' @include Forecaster.R
-#'
 #' Average Forecaster
 #'
 #' Return the (pointwise) average of the all the (similar) centered day curves
 #' in the past. Inherits \code{\link{Forecaster}}
 #'
+#' @export
 AverageForecaster = R6::R6Class("AverageForecaster",
 	inherit = Forecaster,
 
diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index c9eda05..52c2b35 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -1,5 +1,3 @@
-#' @include Forecaster.R
-#'
 #' Neighbors Forecaster
 #'
 #' Predict tomorrow as a weighted combination of "futures of the past" days.
@@ -125,7 +123,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 						private$.params$indices <- fdays
 						private$.params$window <- 1
 					}
-					return ( data$getSerie(fdays[1])[1:horizon] ) #what else?!
+					return ( data$getSerie(fdays[1])[1:horizon] )
 				}
 			}
 			else
diff --git a/pkg/R/F_Persistence.R b/pkg/R/F_Persistence.R
index 79cfe3c..ad83449 100644
--- a/pkg/R/F_Persistence.R
+++ b/pkg/R/F_Persistence.R
@@ -1,5 +1,3 @@
-#' @include Forecaster.R
-#'
 #' Persistence Forecaster
 #'
 #' Return the last centered (similar) day curve.
@@ -14,14 +12,12 @@ PersistenceForecaster = R6::R6Class("PersistenceForecaster",
 			# Return centered last (similar) day curve, avoiding NAs until memory is run
 			first_day = max(1, today-memory)
 			same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE)
-			realtime = ifelse(hasArg("realtime"), list(...)$realtime, FALSE)
 			# If 'same_day', get the last known future of similar day: -7 + 1 == -6
 			index = today - ifelse(same_day,6,0)
 			repeat
 			{
 				{
-					last_serie =
-						data$getCenteredSerie(index,hat=(index==today && realtime))[1:horizon]
+					last_serie = data$getCenteredSerie(index)[1:horizon]
 					index = index - ifelse(same_day,7,1)
 				};
 				if (!any(is.na(last_serie)))
diff --git a/pkg/R/F_Zero.R b/pkg/R/F_Zero.R
index f5d6b89..ac970c4 100644
--- a/pkg/R/F_Zero.R
+++ b/pkg/R/F_Zero.R
@@ -1,5 +1,3 @@
-#' @include Forecaster.R
-#'
 #' Zero Forecaster
 #'
 #' Return 0 (and then adjust). Inherits \code{\link{Forecaster}}
@@ -9,6 +7,6 @@ ZeroForecaster = R6::R6Class("ZeroForecaster",
 
 	public = list(
 		predictShape = function(data, today, memory, horizon, ...)
-			rep(0., horizon)
+			rep(0, horizon)
 	)
 )
diff --git a/pkg/R/J_Neighbors.R b/pkg/R/J_Neighbors.R
index 351fbf9..12fc9d4 100644
--- a/pkg/R/J_Neighbors.R
+++ b/pkg/R/J_Neighbors.R
@@ -9,13 +9,12 @@ getNeighborsJumpPredict = function(data, today, memory, horizon, params, ...)
 	filter = (params$indices >= first_day)
 	indices = params$indices[filter]
 	weights = params$weights[filter]
-	realtime = ifelse(hasArg("realtime"), list(...)$realtime, FALSE)
 
 	if (any(is.na(weights) | is.na(indices)))
 		return (NA)
 
 	gaps = sapply(indices, function(i) {
-		data$getSerie(i+1,hat=(realtime && i+1==today))[1] - tail(data$getSerie(i), 1)
+		head( data$getSerie(i+1), 1) - tail( data$getSerie(i), 1)
 	})
 	scal_product = weights * gaps
 	norm_fact = sum( weights[!is.na(scal_product)] )
diff --git a/pkg/R/J_Persistence.R b/pkg/R/J_Persistence.R
index 4d3abd2..a85a42a 100644
--- a/pkg/R/J_Persistence.R
+++ b/pkg/R/J_Persistence.R
@@ -8,13 +8,12 @@ getPersistenceJumpPredict = function(data, today, memory, horizon, params, ...)
 	#return gap between end of similar day curve and first day of tomorrow (in the past)
 	first_day = max(1, today-memory)
 	same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE)
-	realtime = ifelse(hasArg("realtime"), list(...)$realtime, FALSE)
 	index = today - ifelse(same_day,7,1)
 	repeat
 	{
 		{
 			last_serie_end = tail( data$getSerie(index), 1)
-			last_tomorrow_begin = data$getSerie(index+1,hat=(realtime && index+1==today))[1]
+			last_tomorrow_begin = head( data$getSerie(index+1), 1)
 			index = index - ifelse(same_day,7,1)
 		};
 		if (!is.na(last_serie_end) && !is.na(last_tomorrow_begin))
diff --git a/pkg/R/computeError.R b/pkg/R/computeError.R
index ce05fdb..7da1032 100644
--- a/pkg/R/computeError.R
+++ b/pkg/R/computeError.R
@@ -4,7 +4,8 @@
 #'
 #' @param data Dataset, object of class \code{Data} output of \code{getData}
 #' @param pred Forecast object, class \code{Forecast} output of \code{computeForecast}
-#' @param horizon Horizon where to compute the error (<= horizon used in \code{computeForecast})
+#' @param horizon Horizon where to compute the error
+#'   (<= horizon used in \code{computeForecast})
 #'
 #' @return A list (abs,MAPE) of lists (day,indices)
 #'
diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
index 198f6ec..1e79118 100644
--- a/pkg/R/computeForecast.R
+++ b/pkg/R/computeForecast.R
@@ -2,8 +2,9 @@
 #'
 #' Predict time-series curves for the selected days indices (lines in data).
 #'
-#' @param data Dataset, object of type \code{Data} output of \code{getData}
-#' @param indices Days indices where to forecast (the day after)
+#' @param data Object of type \code{Data}, output of \code{getData()}
+#' @param indices Indices where to forecast (the day after); integers relative to the
+#'   beginning of data, or (convertible to) Date objects
 #' @param forecaster Name of the main forcaster
 #' \itemize{
 #'   \item Persistence : use values of last (similar, next) day
@@ -20,8 +21,7 @@
 #' @param memory Data depth (in days) to be used for prediction
 #' @param horizon Number of time steps to predict
 #' @param ncores Number of cores for parallel execution (1 to disable)
-#' @param ... Additional parameters for the forecasting models;
-#'   In particular, realtime=TRUE to use predictions instead of measurements
+#' @param ... Additional parameters for the forecasting models
 #'
 #' @return An object of class Forecast
 #'
diff --git a/pkg/R/getData.R b/pkg/R/getData.R
index b944dfb..b095d01 100644
--- a/pkg/R/getData.R
+++ b/pkg/R/getData.R
@@ -71,12 +71,10 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:%
 	{
 		time = c()
 		serie = c()
-		hat_serie = c()
 		repeat
 		{
 			{
 				time = c(time, ts_df[line,1])
-				hat_serie = c(serie, ts_df[line,3])
 				serie = c(serie, ts_df[line,2])
 				line = line + 1
 			};
@@ -89,7 +87,7 @@ getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:%
 
 		hat_exo = as.data.frame( exo_df[i,(1+nb_exos+1):(1+2*nb_exos)] )
 		exo = as.data.frame( exo_df[i,2:(1+nb_exos)] )
-		data$appendHat(time, hat_serie, hat_exo)
+		data$appendHat(time, hat_exo)
 		data$append(serie, exo) #in realtime, this call comes hours later
 		if (i >= limit)
 			break