From: Benjamin Auder Date: Thu, 16 Mar 2017 20:46:10 +0000 (+0100) Subject: 'update' X-Git-Url: https://git.auder.net/%7B%7B%20asset%28%27mixstore/images/img/doc/scripts/index.css?a=commitdiff_plain;h=55639673dd1510a02671c4646813ae346cdca4d6;p=talweg.git 'update' --- diff --git a/reports/report.gj b/reports/report.gj index 3524e10..088b43e 100644 --- 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 --- 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 index 5cb789a..0000000 --- a/reports/report_7h_H3.ipynb +++ /dev/null @@ -1,548 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "

Introduction

\n", - "\n", - "J'ai fait quelques essais dans différentes configurations pour la méthode \"Neighbors\"\n", - "(la seule dont on a parlé).
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", - "

Pollution par chauffage

" - ] - }, - { - "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", - "

Pollution par épandage

" - ] - }, - { - "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", - "

Semaine non polluée

" - ] - }, - { - "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", - "

Bilan

\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 same_day).\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 -}