'update'

diff --git a/reports/report.gj b/reports/report.gj
index 3524e10..088b43e 100644 (file)
--- a/reports/report.gj
+++ b/reports/report.gj
@@ -44,7 +44,7 @@ p_nn_mix = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors",
 p_az = computeForecast(data, ${list_indices[i]}, "Average", "Zero",
        horizon=${H})
 p_pz = computeForecast(data, ${list_indices[i]}, "Persistence", "Zero",
-       horizon=${H}, same_day=TRUE)
+       horizon=${H}, same_day=${'TRUE' if loop.index < 2 else 'FALSE'})
 -----r
 e_nn_exo = computeError(data, p_nn_exo, ${H})
 e_nn_mix = computeError(data, p_nn_mix, ${H})

diff --git a/reports/report.ipynb b/reports/report.ipynb
index bdf1723..74d6880 100644 (file)
--- a/reports/report.ipynb
+++ b/reports/report.ipynb
@@ -29,22 +29,19 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "library(talweg)\n",
     "\n",
     "ts_data = read.csv(system.file(\"extdata\",\"pm10_mesures_H_loc_report.csv\",package=\"talweg\"))\n",
     "exo_data = read.csv(system.file(\"extdata\",\"meteo_extra_noNAs.csv\",package=\"talweg\"))\n",
-    "data = getData(ts_data, exo_data, input_tz = \"Europe/Paris\", working_tz=\"Europe/Paris\", predict_at=7)\n",
+    "data = getData(ts_data, exo_data, input_tz = \"Europe/Paris\", working_tz=\"Europe/Paris\",\n",
+    "\tpredict_at=7) #predict from P+1 to P+H included\n",
     "\n",
     "indices_ch = seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\")\n",
     "indices_ep = seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\")\n",
-    "indices_np = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")\n",
-    "\n",
-    "H = 3 #predict from 2pm to 4pm"
+    "indices_np = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")\n"
    ]
   },
   {
@@ -59,30 +56,29 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "p_nn_exo = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\", simtype=\"exo\", horizon=H)\n",
-    "p_nn_mix = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\", simtype=\"mix\", horizon=H)\n",
-    "p_az = computeForecast(data, indices_ch, \"Average\", \"Zero\", horizon=H) #, memory=183)\n",
-    "p_pz = computeForecast(data, indices_ch, \"Persistence\", \"Zero\", horizon=H, same_day=TRUE)"
+    "p_nn_exo = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"exo\")\n",
+    "p_nn_mix = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"mix\")\n",
+    "p_az = computeForecast(data, indices_ch, \"Average\", \"Zero\",\n",
+    "\thorizon=3)\n",
+    "p_pz = computeForecast(data, indices_ch, \"Persistence\", \"Zero\",\n",
+    "\thorizon=3, same_day=TRUE)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, H)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, H)\n",
-    "e_az = computeError(data, p_az, H)\n",
-    "e_pz = computeError(data, p_pz, H)\n",
-    "\n",
+    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
+    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
+    "e_az = computeError(data, p_az, 3)\n",
+    "e_pz = computeError(data, p_pz, 3)\n",
     "options(repr.plot.width=9, repr.plot.height=7)\n",
     "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
     "\n",
@@ -95,9 +91,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "options(repr.plot.width=9, repr.plot.height=4)\n",
@@ -118,9 +112,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -134,9 +126,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -150,9 +140,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -168,9 +156,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -186,9 +172,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",
@@ -211,29 +195,29 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "p_nn_exo = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\", simtype=\"exo\", horizon=H)\n",
-    "p_nn_mix = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\", simtype=\"mix\", horizon=H)\n",
-    "p_az = computeForecast(data, indices_ep, \"Average\", \"Zero\", horizon=H) #, memory=183)\n",
-    "p_pz = computeForecast(data, indices_ep, \"Persistence\", \"Zero\", horizon=H, same_day=TRUE)"
+    "p_nn_exo = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"exo\")\n",
+    "p_nn_mix = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"mix\")\n",
+    "p_az = computeForecast(data, indices_ep, \"Average\", \"Zero\",\n",
+    "\thorizon=3)\n",
+    "p_pz = computeForecast(data, indices_ep, \"Persistence\", \"Zero\",\n",
+    "\thorizon=3, same_day=TRUE)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, H)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, H)\n",
-    "e_az = computeError(data, p_az, H)\n",
-    "e_pz = computeError(data, p_pz, H)\n",
+    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
+    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
+    "e_az = computeError(data, p_az, 3)\n",
+    "e_pz = computeError(data, p_pz, 3)\n",
     "options(repr.plot.width=9, repr.plot.height=7)\n",
     "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
     "\n",
@@ -246,9 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "options(repr.plot.width=9, repr.plot.height=4)\n",
@@ -269,9 +251,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -285,9 +265,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -301,9 +279,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -319,9 +295,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -337,9 +311,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",
@@ -362,29 +334,29 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "p_nn_exo = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\", simtype=\"exo\", horizon=H)\n",
-    "p_nn_mix = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\", simtype=\"mix\", horizon=H)\n",
-    "p_az = computeForecast(data, indices_np, \"Average\", \"Zero\", horizon=H) #, memory=183)\n",
-    "p_pz = computeForecast(data, indices_np, \"Persistence\", \"Zero\", horizon=H, same_day=FALSE)"
+    "p_nn_exo = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"exo\")\n",
+    "p_nn_mix = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\",\n",
+    "\thorizon=3, simtype=\"mix\")\n",
+    "p_az = computeForecast(data, indices_np, \"Average\", \"Zero\",\n",
+    "\thorizon=3)\n",
+    "p_pz = computeForecast(data, indices_np, \"Persistence\", \"Zero\",\n",
+    "\thorizon=3, same_day=FALSE)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, H)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, H)\n",
-    "e_az = computeError(data, p_az, H)\n",
-    "e_pz = computeError(data, p_pz, H)\n",
+    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
+    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
+    "e_az = computeError(data, p_az, 3)\n",
+    "e_pz = computeError(data, p_pz, 3)\n",
     "options(repr.plot.width=9, repr.plot.height=7)\n",
     "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
     "\n",
@@ -397,9 +369,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "options(repr.plot.width=9, repr.plot.height=4)\n",
@@ -420,9 +390,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -436,9 +404,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -452,9 +418,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -470,9 +434,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "par(mfrow=c(1,2))\n",
@@ -488,9 +450,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",

diff --git a/reports/report_7h_H3.ipynb b/reports/report_7h_H3.ipynb
deleted file mode 100644 (file)
index 5cb789a..0000000
--- a/reports/report_7h_H3.ipynb
+++ /dev/null
@@ -1,548 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "<h2>Introduction</h2>\n",
-    "\n",
-    "J'ai fait quelques essais dans différentes configurations pour la méthode \"Neighbors\"\n",
-    "(la seule dont on a parlé).<br>Il semble que le mieux soit\n",
-    "\n",
-    " * simtype=\"exo\" ou \"mix\" : similarités exogènes avec/sans endogènes (fenêtre optimisée par VC)\n",
-    " * 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 une approche naïve : la moyennes des lendemains des jours\n",
-    "\"similaires\" dans tout le passé ; à chaque fois sans prédiction du saut (sauf pour Neighbors :\n",
-    "prédiction basée sur les poids calculés).\n",
-    "\n",
-    "Ensuite j'affiche les erreurs, quelques courbes prévues/mesurées, quelques filaments puis les\n",
-    "histogrammes de quelques poids. Concernant les graphes de filaments, la moitié gauche du graphe\n",
-    "correspond aux jours similaires au jour courant, tandis que la moitié droite affiche les\n",
-    "lendemains : ce sont donc les voisinages tels qu'utilisés dans l'algorithme.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "library(talweg)\n",
-    "\n",
-    "ts_data = read.csv(system.file(\"extdata\",\"pm10_mesures_H_loc_report.csv\",package=\"talweg\"))\n",
-    "exo_data = read.csv(system.file(\"extdata\",\"meteo_extra_noNAs.csv\",package=\"talweg\"))\n",
-    "data = getData(ts_data, exo_data, input_tz = \"Europe/Paris\", working_tz=\"Europe/Paris\",\n",
-    "\tpredict_at=7) #predict from P+1 to P+H included\n",
-    "\n",
-    "indices_ch = seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\")\n",
-    "indices_ep = seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\")\n",
-    "indices_np = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "<h2 style=\"color:blue;font-size:2em\">Pollution par chauffage</h2>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "p_nn_exo = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"exo\")\n",
-    "p_nn_mix = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"mix\")\n",
-    "p_az = computeForecast(data, indices_ch, \"Average\", \"Zero\",\n",
-    "\thorizon=3)\n",
-    "p_pz = computeForecast(data, indices_ch, \"Persistence\", \"Zero\",\n",
-    "\thorizon=3, same_day=TRUE)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
-    "e_az = computeError(data, p_az, 3)\n",
-    "e_pz = computeError(data, p_pz, 3)\n",
-    "options(repr.plot.width=9, repr.plot.height=7)\n",
-    "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
-    "\n",
-    "# Noir: neighbors_mix, bleu: neighbors_exo, vert: moyenne, rouge: persistence\n",
-    "\n",
-    "i_np = which.min(e_nn_exo$abs$indices)\n",
-    "i_p = which.max(e_nn_exo$abs$indices)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "options(repr.plot.width=9, repr.plot.height=4)\n",
-    "par(mfrow=c(1,2))\n",
-    "\n",
-    "plotPredReal(data, p_nn_exo, i_np); title(paste(\"PredReal nn exo day\",i_np))\n",
-    "plotPredReal(data, p_nn_exo, i_p); title(paste(\"PredReal nn exo day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_nn_mix, i_np); title(paste(\"PredReal nn mix day\",i_np))\n",
-    "plotPredReal(data, p_nn_mix, i_p); title(paste(\"PredReal nn mix day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
-    "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
-    "\n",
-    "# Bleu: prévue, noir: réalisée"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "f_np_exo = computeFilaments(data, p_nn_exo, i_np, plot=TRUE); title(paste(\"Filaments nn exo day\",i_np))\n",
-    "f_p_exo = computeFilaments(data, p_nn_exo, i_p, plot=TRUE); title(paste(\"Filaments nn exo day\",i_p))\n",
-    "\n",
-    "f_np_mix = computeFilaments(data, p_nn_mix, i_np, plot=TRUE); title(paste(\"Filaments nn mix day\",i_np))\n",
-    "f_p_mix = computeFilaments(data, p_nn_mix, i_p, plot=TRUE); title(paste(\"Filaments nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotFilamentsBox(data, f_np_exo); title(paste(\"FilBox nn exo day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_exo); title(paste(\"FilBox nn exo day\",i_p))\n",
-    "\n",
-    "plotFilamentsBox(data, f_np_mix); title(paste(\"FilBox nn mix day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_mix); title(paste(\"FilBox nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotRelVar(data, f_np_exo); title(paste(\"StdDev nn exo day\",i_np))\n",
-    "plotRelVar(data, f_p_exo); title(paste(\"StdDev nn exo day\",i_p))\n",
-    "\n",
-    "plotRelVar(data, f_np_mix); title(paste(\"StdDev nn mix day\",i_np))\n",
-    "plotRelVar(data, f_p_mix); title(paste(\"StdDev nn mix day\",i_p))\n",
-    "\n",
-    "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotSimils(p_nn_exo, i_np); title(paste(\"Weights nn exo day\",i_np))\n",
-    "plotSimils(p_nn_exo, i_p); title(paste(\"Weights nn exo day\",i_p))\n",
-    "\n",
-    "plotSimils(p_nn_mix, i_np); title(paste(\"Weights nn mix day\",i_np))\n",
-    "plotSimils(p_nn_mix, i_p); title(paste(\"Weights nn mix day\",i_p))\n",
-    "\n",
-    "# - pollué à gauche, + pollué à droite"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",
-    "p_nn_exo$getParams(i_np)$window\n",
-    "p_nn_exo$getParams(i_p)$window\n",
-    "\n",
-    "p_nn_mix$getParams(i_np)$window\n",
-    "p_nn_mix$getParams(i_p)$window"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "<h2 style=\"color:blue;font-size:2em\">Pollution par épandage</h2>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "p_nn_exo = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"exo\")\n",
-    "p_nn_mix = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"mix\")\n",
-    "p_az = computeForecast(data, indices_ep, \"Average\", \"Zero\",\n",
-    "\thorizon=3)\n",
-    "p_pz = computeForecast(data, indices_ep, \"Persistence\", \"Zero\",\n",
-    "\thorizon=3, same_day=TRUE)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
-    "e_az = computeError(data, p_az, 3)\n",
-    "e_pz = computeError(data, p_pz, 3)\n",
-    "options(repr.plot.width=9, repr.plot.height=7)\n",
-    "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
-    "\n",
-    "# Noir: neighbors_mix, bleu: neighbors_exo, vert: moyenne, rouge: persistence\n",
-    "\n",
-    "i_np = which.min(e_nn_exo$abs$indices)\n",
-    "i_p = which.max(e_nn_exo$abs$indices)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "options(repr.plot.width=9, repr.plot.height=4)\n",
-    "par(mfrow=c(1,2))\n",
-    "\n",
-    "plotPredReal(data, p_nn_exo, i_np); title(paste(\"PredReal nn exo day\",i_np))\n",
-    "plotPredReal(data, p_nn_exo, i_p); title(paste(\"PredReal nn exo day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_nn_mix, i_np); title(paste(\"PredReal nn mix day\",i_np))\n",
-    "plotPredReal(data, p_nn_mix, i_p); title(paste(\"PredReal nn mix day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
-    "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
-    "\n",
-    "# Bleu: prévue, noir: réalisée"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "f_np_exo = computeFilaments(data, p_nn_exo, i_np, plot=TRUE); title(paste(\"Filaments nn exo day\",i_np))\n",
-    "f_p_exo = computeFilaments(data, p_nn_exo, i_p, plot=TRUE); title(paste(\"Filaments nn exo day\",i_p))\n",
-    "\n",
-    "f_np_mix = computeFilaments(data, p_nn_mix, i_np, plot=TRUE); title(paste(\"Filaments nn mix day\",i_np))\n",
-    "f_p_mix = computeFilaments(data, p_nn_mix, i_p, plot=TRUE); title(paste(\"Filaments nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotFilamentsBox(data, f_np_exo); title(paste(\"FilBox nn exo day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_exo); title(paste(\"FilBox nn exo day\",i_p))\n",
-    "\n",
-    "plotFilamentsBox(data, f_np_mix); title(paste(\"FilBox nn mix day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_mix); title(paste(\"FilBox nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotRelVar(data, f_np_exo); title(paste(\"StdDev nn exo day\",i_np))\n",
-    "plotRelVar(data, f_p_exo); title(paste(\"StdDev nn exo day\",i_p))\n",
-    "\n",
-    "plotRelVar(data, f_np_mix); title(paste(\"StdDev nn mix day\",i_np))\n",
-    "plotRelVar(data, f_p_mix); title(paste(\"StdDev nn mix day\",i_p))\n",
-    "\n",
-    "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotSimils(p_nn_exo, i_np); title(paste(\"Weights nn exo day\",i_np))\n",
-    "plotSimils(p_nn_exo, i_p); title(paste(\"Weights nn exo day\",i_p))\n",
-    "\n",
-    "plotSimils(p_nn_mix, i_np); title(paste(\"Weights nn mix day\",i_np))\n",
-    "plotSimils(p_nn_mix, i_p); title(paste(\"Weights nn mix day\",i_p))\n",
-    "\n",
-    "# - pollué à gauche, + pollué à droite"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",
-    "p_nn_exo$getParams(i_np)$window\n",
-    "p_nn_exo$getParams(i_p)$window\n",
-    "\n",
-    "p_nn_mix$getParams(i_np)$window\n",
-    "p_nn_mix$getParams(i_p)$window"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "<h2 style=\"color:blue;font-size:2em\">Semaine non polluée</h2>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "p_nn_exo = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"exo\")\n",
-    "p_nn_mix = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\",\n",
-    "\thorizon=3, simtype=\"mix\")\n",
-    "p_az = computeForecast(data, indices_np, \"Average\", \"Zero\",\n",
-    "\thorizon=3)\n",
-    "p_pz = computeForecast(data, indices_np, \"Persistence\", \"Zero\",\n",
-    "\thorizon=3, same_day=TRUE)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "e_nn_exo = computeError(data, p_nn_exo, 3)\n",
-    "e_nn_mix = computeError(data, p_nn_mix, 3)\n",
-    "e_az = computeError(data, p_az, 3)\n",
-    "e_pz = computeError(data, p_pz, 3)\n",
-    "options(repr.plot.width=9, repr.plot.height=7)\n",
-    "plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))\n",
-    "\n",
-    "# Noir: neighbors_mix, bleu: neighbors_exo, vert: moyenne, rouge: persistence\n",
-    "\n",
-    "i_np = which.min(e_nn_exo$abs$indices)\n",
-    "i_p = which.max(e_nn_exo$abs$indices)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "options(repr.plot.width=9, repr.plot.height=4)\n",
-    "par(mfrow=c(1,2))\n",
-    "\n",
-    "plotPredReal(data, p_nn_exo, i_np); title(paste(\"PredReal nn exo day\",i_np))\n",
-    "plotPredReal(data, p_nn_exo, i_p); title(paste(\"PredReal nn exo day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_nn_mix, i_np); title(paste(\"PredReal nn mix day\",i_np))\n",
-    "plotPredReal(data, p_nn_mix, i_p); title(paste(\"PredReal nn mix day\",i_p))\n",
-    "\n",
-    "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
-    "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
-    "\n",
-    "# Bleu: prévue, noir: réalisée"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "f_np_exo = computeFilaments(data, p_nn_exo, i_np, plot=TRUE); title(paste(\"Filaments nn exo day\",i_np))\n",
-    "f_p_exo = computeFilaments(data, p_nn_exo, i_p, plot=TRUE); title(paste(\"Filaments nn exo day\",i_p))\n",
-    "\n",
-    "f_np_mix = computeFilaments(data, p_nn_mix, i_np, plot=TRUE); title(paste(\"Filaments nn mix day\",i_np))\n",
-    "f_p_mix = computeFilaments(data, p_nn_mix, i_p, plot=TRUE); title(paste(\"Filaments nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotFilamentsBox(data, f_np_exo); title(paste(\"FilBox nn exo day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_exo); title(paste(\"FilBox nn exo day\",i_p))\n",
-    "\n",
-    "plotFilamentsBox(data, f_np_mix); title(paste(\"FilBox nn mix day\",i_np))\n",
-    "plotFilamentsBox(data, f_p_mix); title(paste(\"FilBox nn mix day\",i_p))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotRelVar(data, f_np_exo); title(paste(\"StdDev nn exo day\",i_np))\n",
-    "plotRelVar(data, f_p_exo); title(paste(\"StdDev nn exo day\",i_p))\n",
-    "\n",
-    "plotRelVar(data, f_np_mix); title(paste(\"StdDev nn mix day\",i_np))\n",
-    "plotRelVar(data, f_p_mix); title(paste(\"StdDev nn mix day\",i_p))\n",
-    "\n",
-    "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "par(mfrow=c(1,2))\n",
-    "plotSimils(p_nn_exo, i_np); title(paste(\"Weights nn exo day\",i_np))\n",
-    "plotSimils(p_nn_exo, i_p); title(paste(\"Weights nn exo day\",i_p))\n",
-    "\n",
-    "plotSimils(p_nn_mix, i_np); title(paste(\"Weights nn mix day\",i_np))\n",
-    "plotSimils(p_nn_mix, i_p); title(paste(\"Weights nn mix day\",i_p))\n",
-    "\n",
-    "# - pollué à gauche, + pollué à droite"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "# Fenêtres sélectionnées dans ]0,10] / endo à gauche, exo à droite\n",
-    "p_nn_exo$getParams(i_np)$window\n",
-    "p_nn_exo$getParams(i_p)$window\n",
-    "\n",
-    "p_nn_mix$getParams(i_np)$window\n",
-    "p_nn_mix$getParams(i_p)$window"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "<h2>Bilan</h2>\n",
-    "\n",
-    "Problème difficile : on ne fait guère mieux qu'une naïve moyenne des lendemains des jours\n",
-    "similaires dans le passé, ce qui n'est pas loin de prédire une série constante égale à la\n",
-    "dernière valeur observée (méthode \"zéro\"). La persistence donne parfois de bons résultats\n",
-    "mais est trop instable (sensibilité à l'argument <code>same_day</code>).\n",
-    "\n",
-    "Comment améliorer la méthode ?"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "R",
-   "language": "R",
-   "name": "ir"
-  },
-  "language_info": {
-   "codemirror_mode": "r",
-   "file_extension": ".r",
-   "mimetype": "text/x-r-source",
-   "name": "R",
-   "pygments_lexer": "r",
-   "version": "3.3.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}