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    \maketitle
    
    

    
    \subsection{Package R "talweg"}\label{package-r-talweg}

Le package \(-\) Time-series sAmpLes forecasted With ExoGenous variables
\(-\) contient le code permettant de (re)lancer les expériences
numériques décrites dans cette partie et la suivante. Les fonctions
principales sont respectivement * \textbf{getData()} pour construire un
objet R contenant les données à partir de fichiers CSV (extraits de
bases de données). Le format choisi en R est une classe R6 (du package
du même nom) exposant en particulier les méthodes \emph{getSerie(i)} et
\emph{getExo(i)} qui renvoient respectivement la \(i^{eme}\) série de
24h et les variables exogènes (mesurées) correspondantes. Voir ?Data
pour plus d'information, une fois le package chargé. *
\textbf{computeForecast()} pour calculer des prédictions sur une
certaine plage temporelle contenue dans \emph{data \textless{}-
getData(...)} * \textbf{computeError()} pour évaluer les erreurs
commises par différentes méthodes.

Le package contient en outre diverses fonctions graphiques
\emph{plotXXX()}, utilisées dans la partie suivante.

    \begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}3}]:} \PY{c+c1}{\PYZsh{} Chargement de la librairie (après compilation, \PYZdq{}R CMD INSTALL .\PYZdq{})}
        \PY{k+kn}{library}\PY{p}{(}talweg\PY{p}{)}
        
        \PY{c+c1}{\PYZsh{} Acquisition des données (depuis les fichiers CSV)}
        ts\PYZus{}data \PY{o}{\PYZlt{}\PYZhy{}} read.csv\PY{p}{(}\PY{k+kp}{system.file}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{extdata\PYZdq{}}\PY{p}{,}\PY{l+s}{\PYZdq{}}\PY{l+s}{pm10\PYZus{}mesures\PYZus{}H\PYZus{}loc.csv\PYZdq{}}\PY{p}{,}package\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{talweg\PYZdq{}}\PY{p}{)}\PY{p}{)}
        exo\PYZus{}data \PY{o}{\PYZlt{}\PYZhy{}} read.csv\PY{p}{(}\PY{k+kp}{system.file}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{extdata\PYZdq{}}\PY{p}{,}\PY{l+s}{\PYZdq{}}\PY{l+s}{meteo\PYZus{}extra\PYZus{}noNAs.csv\PYZdq{}}\PY{p}{,}package\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{talweg\PYZdq{}}\PY{p}{)}\PY{p}{)}
        data \PY{o}{\PYZlt{}\PYZhy{}} getData\PY{p}{(}ts\PYZus{}data\PY{p}{,} exo\PYZus{}data\PY{p}{,} input\PYZus{}tz\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{GMT\PYZdq{}}\PY{p}{,} date\PYZus{}format\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{\PYZpc{}d/\PYZpc{}m/\PYZpc{}Y \PYZpc{}H:\PYZpc{}M\PYZdq{}}\PY{p}{,}
            working\PYZus{}tz\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{GMT\PYZdq{}}\PY{p}{,} predict\PYZus{}at\PY{o}{=}\PY{l+m}{7}\PY{p}{,} limit\PY{o}{=}\PY{l+m}{120}\PY{p}{)}
        \PY{c+c1}{\PYZsh{} Plus de détails à la section 1 ci\PYZhy{}après.}
        
        \PY{c+c1}{\PYZsh{} Prédiction de 10 courbes (jours 102 à 111)}
        pred \PY{o}{\PYZlt{}\PYZhy{}} computeForecast\PY{p}{(}data\PY{p}{,} \PY{l+m}{101}\PY{o}{:}\PY{l+m}{110}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Persistence\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Zero\PYZdq{}}\PY{p}{,} memory\PY{o}{=}\PY{l+m}{50}\PY{p}{,} horizon\PY{o}{=}\PY{l+m}{12}\PY{p}{,} ncores\PY{o}{=}\PY{l+m}{1}\PY{p}{)}
        \PY{c+c1}{\PYZsh{} Plus de détails à la section 2 ci\PYZhy{}après.}
        
        \PY{c+c1}{\PYZsh{} Calcul des erreurs (sur un horizon arbitraire \PYZlt{}= horizon de prédiction)}
        err \PY{o}{\PYZlt{}\PYZhy{}} computeError\PY{p}{(}data\PY{p}{,} pred\PY{p}{,} horizon\PY{o}{=}\PY{l+m}{6}\PY{p}{)}
        \PY{c+c1}{\PYZsh{} Plus de détails à la section 3 ci\PYZhy{}après.}
        
        \PY{c+c1}{\PYZsh{} Puis voir ?plotError et les autres plot dans le paragraphe \PYZsq{}seealso\PYZsq{}}
\end{Verbatim}

    \subsubsection{getData()}\label{getdata}

Les arguments de cette fonction sont, dans l'ordre : 1.
\textbf{ts\_data} : séries temporelles (fichier CSV avec entête ou
data.frame) ; la première colonne contient les heures, la seconde les
valeurs. 2. \textbf{exo\_data} : variables exogènes (fichier CSV avec
entête ou data.frame) ; la première colonne contient les jours, les
\(m\) suivantes les variables mesurées pour ce jour, et les \(m\)
dernières les variables prédites pour ce même jour. Dans notre cas
\(m=4\) : pression, température, gradient de température, vitesse du
vent. 3. \textbf{input\_tz} : zone horaire pour ts\_data (défaut :
"GMT"). 4. \textbf{date\_format} : format des heures dans ts\_data
(défaut : "\%d/\%m/\%Y \%H:\%M", format du fichier transmis par Michel).
5. \textbf{working\_tz} : zone horaire dans laquelle on souhaite
travailler avec les données (défaut : "GMT"). 6. \textbf{predict\_at} :
heure à laquelle s'effectue la prévision \(-\) et donc dernière heure
d'un bloc de 24h, relativement à working\_tz. data\texttt{\$}getSerie(3)
renvoit ainsi les 24 valeurs de 8h à 7h pour le \(3^{eme}\) bloc de 24h
présent dans le jeu de données.

    \begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}11}]:} \PY{k+kp}{print}\PY{p}{(}data\PY{p}{)}
         \PY{c+c1}{\PYZsh{}?Data}
\end{Verbatim}

    \begin{Verbatim}[commandchars=\\\{\}]
<Data>
  Public:
    append: function (time, serie, exo, exo\_hat) 
    clone: function (deep = FALSE) 
    getCenteredSerie: function (index) 
    getCenteredSeries: function (indices) 
    getExo: function (index) 
    getExoHat: function (index) 
    getLevel: function (index) 
    getSerie: function (index) 
    getSeries: function (indices) 
    getSize: function () 
    getStdHorizon: function () 
    getTime: function (index) 
    removeFirst: function () 
    removeLast: function () 
  Private:
    .data: list

    \end{Verbatim}

    \subsubsection{computeForecast()}\label{computeforecast}

Les arguments de cette fonction sont, dans l'ordre : 1. \textbf{data} :
le jeu de données renvoyé par getData() 2. \textbf{indices} : l'ensemble
de jours dont on veut prévoir les "lendemains" (prochains blocs de 24h)
; peut être donnée sous forme d'un vecteur de dates ou d'entiers
(correspondants aux numéros des jours). 3. \textbf{forecaster} : le nom
du prédicteur principal à utiliser ; voir ?computeForecast 4.
\textbf{pjump} : le nom du prédicteur de saut d'une série à l'autre ;
voir ?computeForecast 5. \textbf{memory} : le nombre de jours à prendre
en compte dans le passé pour chaque prévision (par défaut : Inf,
c'est-à-dire tout l'historique pris en compte). 6. \textbf{horizon} : le
nombre d'heures à prédire ; par défaut "data\texttt{\$}getStdHorizon()",
c'est-à-dire le nombre d'heures restantes à partir de l'instant de
prévision + 1 jusqu'à minuit (17 pour predict\_at=7 par exemple). 7.
\textbf{ncores} : le nombre de processus parallèles (utiliser 1 pour une
exécution séquentielle)

    \begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}8}]:} \PY{k+kp}{print}\PY{p}{(}pred\PY{p}{)}
        \PY{c+c1}{\PYZsh{}?computeForecast}
\end{Verbatim}

    \begin{Verbatim}[commandchars=\\\{\}]
<Forecast>
  Public:
    append: function (forecast, params, index\_in\_data) 
    clone: function (deep = FALSE) 
    getDates: function () 
    getForecast: function (index) 
    getIndexInData: function (index) 
    getParams: function (index) 
    getSize: function () 
    initialize: function (dates) 
  Private:
    .dates: 14323 14324 14325 14326 14327 14328 14329 14330 14331 14332
    .pred: list

    \end{Verbatim}

    \subsubsection{computeError()}\label{computeerror}

Les arguments de cette fonction sont, dans l'ordre : 1. \textbf{data} :
le jeu de données renvoyé par getData() 2. \textbf{pred} : les
prédictions renvoyées par computeForecast() 3. \textbf{horizon} : le
nombre d'heures à considérer pour le calcul de l'erreur ; doit être
inférieur ou égal à l'horizon utilisé pour la prédiction (même valeur
par défaut : "data\texttt{\$}getStdHorizon()")

    \begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}9}]:} \PY{k+kp}{summary}\PY{p}{(}err\PY{p}{)}
        \PY{k+kp}{summary}\PY{p}{(}err\PY{o}{\PYZdl{}}\PY{k+kp}{abs}\PY{p}{)}
        \PY{k+kp}{summary}\PY{p}{(}err\PY{o}{\PYZdl{}}MAPE\PY{p}{)}
\end{Verbatim}

    
    \begin{verbatim}
     Length Class  Mode
abs  2      -none- list
MAPE 2      -none- list
    \end{verbatim}

    
    
    \begin{verbatim}
        Length Class  Mode   
day      6     -none- numeric
indices 10     -none- numeric
    \end{verbatim}

    
    
    \begin{verbatim}
        Length Class  Mode   
day      6     -none- numeric
indices 10     -none- numeric
    \end{verbatim}

    
    \subsubsection{Graphiques}\label{graphiques}

Voir ?plotError : les autres fonctions graphiques sont dans la section
'seealso' :

\begin{verbatim}
 ‘plotCurves’, ‘plotPredReal’, ‘plotSimils’, ‘plotFbox’,
 ‘computeFilaments’, ‘plotFilamentsBox’, ‘plotRelVar’
\end{verbatim}

?plotXXX, etc.


    % Add a bibliography block to the postdoc
    
    
    
    \end{document}
