improvements, updated report

diff --git a/R/F_Level.R b/R/F_Level.R
index e0132ae..a186c1a 100644 (file)
--- a/R/F_Level.R
+++ b/R/F_Level.R
@@ -2,8 +2,7 @@
 #'
 #' @title Level Forecaster
 #'
-#' @description Return flat serie of last observed level (on similar day).
-#'   Inherits \code{\link{ShapeForecaster}}
+#' @description Return flat serie of last observed level. Inherits \code{\link{ShapeForecaster}}
 LevelForecaster = setRefClass(
        Class = "LevelForecaster",
        contains = "Forecaster",
@@ -13,39 +12,23 @@ LevelForecaster = setRefClass(
                {
                        callSuper(...)
                },
-               predict = function(today, memory, horizon, all_memory=TRUE, ...)
+               predict = function(today, memory, horizon, ...)
                {
-                       #return last (similar) day level, or on all memory if all_memory==TRUE
+                       #return last day level
                        first_day = max(1, today-memory)
-                       index = today-7 + 1
-                       if (all_memory)
-                       {
-                               sum_level = 0.
-                               nb_series = 0
-                       }
+                       same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE)
+                       index = today - ifelse(same_day,6,0)
                        repeat
                        {
                                {
-                                       last_similar_serie = data$getSerie(index)[1:horizon]
-                                       index = index - 7
+                                       last_serie = data$getSerie(index)[1:horizon]
+                                       index = index - ifelse(same_day,7,1)
                                };
                                #TODO: next test is too strict
-                               if (!any(is.na(last_similar_serie)))
-                               {
-                                       if (all_memory)
-                                       {
-                                               sum_level = sum_level + mean(last_similar_serie)
-                                               nb_series = nb_series + 1
-                                       }
-                                       else
-                                               return (rep(mean(last_similar_serie), horizon))
-                               };
+                               if (!any(is.na(last_serie)))
+                                       return (rep(mean(last_serie), horizon));
                                if (index < first_day)
-                               {
-                                       if (all_memory)
-                                               return (rep(sum_level / nb_series, horizon))
                                        return (NA)
-                               }
                        }
                }
        )

diff --git a/R/F_Persistence.R b/R/F_Persistence.R
index f078484..19cf2e4 100644 (file)
--- a/R/F_Persistence.R
+++ b/R/F_Persistence.R
@@ -2,7 +2,7 @@
 #'
 #' @title Persistence Forecaster
 #'
-#' @description Return the last centered last (similar) day curve.
+#' @description Return the last centered (similar) day curve.
 #'   Inherits \code{\link{Forecaster}}
 PersistenceForecaster = setRefClass(
        Class = "PersistenceForecaster",
@@ -15,17 +15,19 @@ PersistenceForecaster = setRefClass(
                },
                predictShape = function(today, memory, horizon, ...)
                {
-                       #return centered last (similar) day curve, avoiding NAs until memory is run
+                       # Return centered last (similar) day curve, avoiding NAs until memory is run
                        first_day = max(1, today-memory)
-                       index = today-7 + 1
+                       same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE)
+                       # If 'same_day', get the last known future of similar day: -7 + 1 == -6
+                       index = today - ifelse(same_day,6,0)
                        repeat
                        {
                                {
-                                       last_similar_serie = data$getCenteredSerie(index)[1:horizon]
-                                       index = index - 7
+                                       last_serie = data$getCenteredSerie(index)[1:horizon]
+                                       index = index - ifelse(same_day,7,1)
                                };
-                               if (!any(is.na(last_similar_serie)))
-                                       return (last_similar_serie);
+                               if (!any(is.na(last_serie)))
+                                       return (last_serie);
                                if (index < first_day)
                                        return (NA)
                        }

diff --git a/R/J_Persistence.R b/R/J_Persistence.R
index 744b42a..8ac597c 100644 (file)
--- a/R/J_Persistence.R
+++ b/R/J_Persistence.R
@@ -6,16 +6,17 @@ 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)
-       index = today-7
+       same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE)
+       index = today - ifelse(same_day,7,1)
        repeat
        {
                {
-                       last_similar_serie_end = tail( data$getCenteredSerie(index), 1)
-                       last_similar_tomorrow_begin = data$getCenteredSerie(index+1)[1]
-                       index = index - 7
+                       last_serie_end = tail( data$getSerie(index), 1)
+                       last_tomorrow_begin = data$getSerie(index+1)[1]
+                       index = index - ifelse(same_day,7,1)
                };
-               if (!is.na(last_similar_serie_end) && !is.na(last_similar_tomorrow_begin))
-                       return (last_similar_tomorrow_begin - last_similar_serie_end);
+               if (!is.na(last_serie_end) && !is.na(last_tomorrow_begin))
+                       return (last_tomorrow_begin - last_serie_end);
                if (index < first_day)
                        return (NA)
        }

diff --git a/R/getForecast.R b/R/getForecast.R
index fde8e45..c07be7c 100644 (file)
--- a/R/getForecast.R
+++ b/R/getForecast.R
@@ -37,7 +37,7 @@
 #'   #do_something_with_pred
 #' }}
 #' @export
-getForecast = function(data, indices, forecaster, pjump,
+getForecast = function(data, indices, forecaster, pjump=NULL,
        memory=Inf, horizon=data$getStdHorizon(), ...)
 {
        # (basic) Arguments sanity checks
@@ -48,12 +48,16 @@ getForecast = function(data, indices, forecaster, pjump,
        if (any(indices<=0 | indices>data$getSize()))
                stop("Indices out of range")
        indices = sapply(indices, dateIndexToInteger, data)
-       if (!is.character(forecaster) || !is.character(pjump))
-               stop("forecaster and pjump should be of class character")
+       if (!is.character(forecaster))
+               stop("forecaster (name) should be of class character") #pjump could be NULL
 
        pred = list()
        forecaster = new(paste(forecaster,"Forecaster",sep=""), data=data,
-               pjump = getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
+               pjump =
+                       if (is.null(pjump))
+                               function() {}
+                       else
+                               getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
        for (today in indices)
        {
                pred[[length(pred)+1]] = list(

diff --git a/R/plot.R b/R/plot.R
index 9a0dbcd..b720e9a 100644 (file)
--- a/R/plot.R
+++ b/R/plot.R
@@ -71,7 +71,7 @@ plotFilaments <- function(data, index, limit=60)
                index = i - first_day + 1
                serie = c(data$getCenteredSerie(index), data$getCenteredSerie(index+1))
                if (!all(is.na(serie)))
-                       range(serie, na.rm=TRUE)
+                       return (range(serie, na.rm=TRUE))
                c()
        }) )
        grays = gray.colors(20, 0.1, 0.9) #TODO: 20 == magic number

diff --git a/reports/report_2017-03-01.ipynb b/reports/report_2017-03-01.ipynb
index 3e58706..26f4682 100644 (file)
--- a/reports/report_2017-03-01.ipynb
+++ b/reports/report_2017-03-01.ipynb
@@ -35,7 +35,7 @@
     " * same_season=FALSE : les indices pour la validation croisée ne tiennent pas compte des saisons\n",
     " * mix_strategy=\"mult\" : on multiplie les poids (au lieu d'en éteindre)\n",
     "\n",
-    "J'ai systématiquement comparé à deux autres approches : la persistence et la moyenne de tous les futurs des jours similaires du passé ; à chaque fois sans prédiction du saut (sauf pour Neighbors : prédiction basée sur les poids calculés).\n",
+    "J'ai systématiquement comparé à deux autres approches : la persistence et la répétition de la dernière valeur observée (sur tout l'horizon, donc \"zero\") ; à chaque fois sans prédiction du saut (sauf pour Neighbors : prédiction basée sur les poids calculés).\n",
     "\n",
     "Ensuite j'affiche les erreurs, quelques courbes prévues/mesurées, quelques filaments puis les histogrammes de quelques poids. Concernant les graphes de filaments, la moitié gauche du graphe correspond aux jours similaires au jour courant, tandis que la moitié droite affiche les lendemains : ce sont donc les voisinages tels qu'utilisés dans l'algorithme.\n",
     "\n",
@@ -52,9 +52,10 @@
    "source": [
     "indices = seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\")\n",
     "p_ch_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
-    "p_ch_pz = getForecast(data, indices, \"Persistence\", \"Zero\")\n",
-    "p_ch_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
-    "p_ch_zz = getForecast(data, indices, \"Zero\", \"Zero\")"
+    "p_ch_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=TRUE)\n",
+    "#p_ch_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
+    "p_ch_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
+    "#p_ch_l = getForecast(data, indices, \"Level\", same_day=FALSE)"
    ]
   },
   {
@@ -67,18 +68,20 @@
    "source": [
     "e_ch_nn = getError(data, p_ch_nn)\n",
     "e_ch_pz = getError(data, p_ch_pz)\n",
-    "e_ch_az = getError(data, p_ch_az)\n",
+    "#e_ch_az = getError(data, p_ch_az)\n",
+    "e_ch_zz = getError(data, p_ch_zz)\n",
+    "#e_ch_l = getError(data, p_ch_l)\n",
     "options(repr.plot.width=9, repr.plot.height=6)\n",
-    "plotError(list(e_ch_nn, e_ch_pz, e_ch_az), cols=c(1,2,colors()[258]))\n",
+    "plotError(list(e_ch_nn, e_ch_pz, e_ch_zz), cols=c(1,2,colors()[258]))\n",
     "\n",
-    "#Noir: neighbors, rouge: persistence, vert: moyenne"
+    "#Noir: neighbors, rouge: persistence, vert: zero"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "La méthode Neighbors fait assez nettement mieux qu'une simple moyenne dans ce cas."
+    "La méthode Neighbors fait assez nettement mieux que les autres dans ce cas."
    ]
   },
   {
@@ -177,10 +180,10 @@
    "source": [
     "indices = seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\")\n",
     "p_ep_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
-    "p_ep_pz = getForecast(data, indices, \"Persistence\", \"Zero\")\n",
-    "p_ep_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
+    "p_ep_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=TRUE)\n",
+    "#p_ep_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
     "p_ep_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
-    "p_ep_lz = getForecast(data, indices, \"Level\", \"Zero\")"
+    "#p_ep_l = getForecast(data, indices, \"Level\", same_day=TRUE)"
    ]
   },
   {
@@ -193,11 +196,13 @@
    "source": [
     "e_ep_nn = getError(data, p_ep_nn)\n",
     "e_ep_pz = getError(data, p_ep_pz)\n",
-    "e_ep_az = getError(data, p_ep_az)\n",
+    "#e_ep_az = getError(data, p_ep_az)\n",
+    "e_ep_zz = getError(data, p_ep_zz)\n",
+    "#e_ep_l = getError(data, p_ep_l)\n",
     "options(repr.plot.width=9, repr.plot.height=6)\n",
-    "plotError(list(e_ep_nn, e_ep_pz, e_ep_az), cols=c(1,2,colors()[258]))\n",
+    "plotError(list(e_ep_nn, e_ep_pz, e_ep_zz), cols=c(1,2,colors()[258]))\n",
     "\n",
-    "#Noir: neighbors, rouge: persistence, vert: moyenne"
+    "#Noir: neighbors, rouge: persistence, vert: zero"
    ]
   },
   {
@@ -278,10 +283,10 @@
    "source": [
     "indices = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")\n",
     "p_np_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
-    "p_np_pz = getForecast(data, indices, \"Persistence\", \"Zero\")\n",
-    "p_np_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
+    "p_np_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=FALSE)\n",
+    "#p_np_az = getForecast(data, indices, \"Average\", \"Zero\")\n",
     "p_np_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
-    "p_np_lz = getForecast(data, indices, \"Level\", \"Zero\")"
+    "#p_np_l = getForecast(data, indices, \"Level\", same_day=FALSE)"
    ]
   },
   {
@@ -294,18 +299,20 @@
    "source": [
     "e_np_nn = getError(data, p_np_nn)\n",
     "e_np_pz = getError(data, p_np_pz)\n",
-    "e_np_az = getError(data, p_np_az)\n",
+    "#e_np_az = getError(data, p_np_az)\n",
+    "e_np_zz = getError(data, p_np_zz)\n",
+    "#e_np_l = getError(data, p_np_l)\n",
     "options(repr.plot.width=9, repr.plot.height=6)\n",
-    "plotError(list(e_np_nn, e_np_pz, e_np_az), cols=c(1,2,colors()[258]))\n",
+    "plotError(list(e_np_nn, e_np_pz, e_np_zz), cols=c(1,2,colors()[258]))\n",
     "\n",
-    "#Noir: neighbors, rouge: persistence, vert: moyenne"
+    "#Noir: neighbors, rouge: persistence, vert: zero"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Performances des méthodes \"Average\" et \"Neighbors\" comparables ; mauvais résultats pour la persistence."
+    "Performances des méthodes \"Zero\" et \"Neighbors\" comparables ; mauvais résultats pour la persistence."
    ]
   },
   {
@@ -376,7 +383,7 @@
    "source": [
     "## Bilan\n",
     "\n",
-    "Problème difficile : on ne fait guère mieux qu'une naïve moyenne des lendemains des jours similaires dans le passé.\n",
+    "Problème difficile : on ne fait guère mieux qu'une naïve moyenne des lendemains des jours similaires dans le passé, ce qui est à peu près équivalent à prédire une série constante égale à la dernière valeur observée (méthode \"zéro\"). La persistence donne parfois de bons résultats mais est trop instable (sensibilité à l'argument <code>same_day</code>).\n",
     "\n",
     "Comment améliorer la méthode ?"
    ]