scripts/make_summaries/modele.Rnw

   1 \documentclass[12pt]{article}
   2
   3 \usepackage{geometry}
   4 \geometry{
   5     a4paper,
   6     total={210mm,297mm},
   7     left=10mm,
   8     right=10mm,
   9     top=15mm,
  10     bottom=15mm,
  11 }
  12 \setlength{\parindent}{0pt}
  13 \usepackage[utf8]{inputenc}
  14 \usepackage[french]{babel}
  15 \usepackage{helvet}
  16 \renewcommand{\familydefault}{\sfdefault}
  17 \usepackage{amsmath,amsfonts,amssymb}
  18 \usepackage{float}
  19 \usepackage{graphicx}
  20 \usepackage{wrapfig}
  21 \usepackage{xcolor}
  22 \usepackage{cprotect}
  23 %\setcounter{section}{9}
  24
  25 \begin{document}
  26
  27 <<setup, include=FALSE, cache=FALSE, echo=FALSE>>=
  28 opts_chunk$set(fig.path="figs/", fig.align="center", fig.show="hold", echo=FALSE)
  29 options(replace.assign=TRUE,width=90)
  30 @
  31
  32 <<initialize>>=
  33 library(aggexp)
  34 station = "STATIONNAME"
  35 experts = aggexp:::expertsArray[EXPERTSINDICES]
  36 K = length(experts)
  37 @
  38
  39 \cprotect\section{\verb|STATIONNAME| - Résumé des données}
  40
  41 \vspace*{-0.5cm}
  42 <<plotCurves, out.width="12cm", out.height="9cm">>=
  43 mock_r = list(data = getData(experts, station), experts=experts, stations=station)
  44 plotCurves(mock_r)
  45 @
  46
  47 \vspace*{-0.8cm}
  48 \cprotect\section{\verb|STATIONNAME| - Performances en prédiction}
  49
  50 \vspace*{-0.5cm}
  51 <<computePredictions>>=
  52 r_ml = runAlgorithm("ml", experts=experts, stations=station, alpha=0.2, H=183, grad=TRUE)
  53 r_rr = runAlgorithm("rr", experts=experts, stations=station, H=183)
  54 r_be = r_ml
  55 be = which.max(getBestExpert(r_ml))
  56 r_be$data[,"Prediction"] = r_be$data[,experts[be]]
  57 @
  58
  59 <<plotPredictionClouds, out.width="6cm", out.height="6cm">>=
  60 plotCloud(r_be, 30, c(30,50,80), main=paste("Nuage Meilleur Expert (",experts[be],")",sep=""))
  61 plotCloud(r_ml, 30, c(30,50,80), main="Nuage ML")
  62 plotCloud(r_rr, 30, c(30,50,80), main="Nuage RR")
  63 @
  64
  65 \vspace*{-0.8cm}
  66 \cprotect\section{\verb|STATIONNAME| - Indicateurs d'alertes}
  67
  68 \vspace*{-0.5cm}
  69 <<computeAlertIndicators>>=
  70 indicators = matrix(nrow=5, ncol=4+K)
  71 indicators[,1] = as.numeric(getIndicators(r_ml, thresh=30))
  72 indicators[,2] = as.numeric(getIndicators(r_rr, thresh=30))
  73 for (i in 1:K) {
  74     r_be$data[,"Prediction"] = r_be$data[,experts[i]]
  75     indicators[,i+2] = as.numeric(getIndicators(r_be, thresh=30))
  76 }
  77 indicators = as.data.frame(indicators, row.names=c("TS","FA","MA","RMSE","EV"))
  78 names(indicators) = c("ML","RR", experts)
  79 @
  80
  81 <<plotAlertIndicators, results="asis">>=
  82 library(xtable)
  83 splitIndex = ifelse(length(experts) < 10, 7, 8)
  84 xtable(indicators[,1:splitIndex], caption="Indicateurs d'alertes ; partie 1")
  85 xtable(indicators[,(splitIndex+1):(2+K)], caption="Indicateurs d'alertes ; partie 2")
  86 @
  87
  88 \end{document}