No longer direct predict for Neighbors2: recollement comme Neighbors (better)
[talweg.git] / reports / report.ipynb
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9 "source": [
10 "\n",
11 "\n",
12 "<h2>Introduction</h2>\n",
13 "\n",
14 "J'ai fait quelques essais dans différentes configurations pour la méthode \"Neighbors\"\n",
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15 "(la seule dont on a parlé) et sa variante récente appelée pour l'instant \"Neighbors2\",\n",
16 "avec simtype=\"mix\" : deux types de similarités prises en compte, puis multiplication des poids.\n",
17 "Pour Neighbors on prédit le saut (par la moyenne pondérée des sauts passés), et pour Neighbors2\n",
18 "on n'effectue aucun raccordement (prévision directe).\n",
ff5df8e3 19 "\n",
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20 "J'ai systématiquement comparé à une approche naïve : la moyenne des lendemains des jours\n",
21 "\"similaires\" dans tout le passé, ainsi qu'à la persistence -- reproduisant le jour courant ou\n",
22 "allant chercher le futur similaire une semaine avant.\n",
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23 "\n",
24 "Ensuite j'affiche les erreurs, quelques courbes prévues/mesurées, quelques filaments puis les\n",
25 "histogrammes de quelques poids. Concernant les graphes de filaments, la moitié gauche du graphe\n",
26 "correspond aux jours similaires au jour courant, tandis que la moitié droite affiche les\n",
27 "lendemains : ce sont donc les voisinages tels qu'utilisés dans l'algorithme.\n",
28 "\n"
29 ]
30 },
31 {
32 "cell_type": "code",
33 "execution_count": null,
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34 "metadata": {
35 "collapsed": false,
36 "deletable": true,
37 "editable": true
38 },
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39 "outputs": [],
40 "source": [
41 "library(talweg)\n",
42 "\n",
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43 "P = 7 #instant de prévision\n",
44 "H = 17 #horizon (en heures)\n",
45 "\n",
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46 "ts_data = read.csv(system.file(\"extdata\",\"pm10_mesures_H_loc_report.csv\",package=\"talweg\"))\n",
47 "exo_data = read.csv(system.file(\"extdata\",\"meteo_extra_noNAs.csv\",package=\"talweg\"))\n",
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48 "# NOTE: 'GMT' because DST gaps are filled and multiple values merged in above dataset.\n",
49 "# Prediction from P+1 to P+H included.\n",
50 "data = getData(ts_data, exo_data, input_tz = \"GMT\", working_tz=\"GMT\", predict_at=P)\n",
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51 "\n",
52 "indices_ch = seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\")\n",
53 "indices_ep = seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\")\n",
6774e53d 54 "indices_np = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")\n"
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55 ]
56 },
57 {
58 "cell_type": "markdown",
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59 "metadata": {
60 "deletable": true,
61 "editable": true
62 },
ff5df8e3 63 "source": [
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64 "\n",
65 "\n",
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66 "<h2 style=\"color:blue;font-size:2em\">Pollution par chauffage</h2>"
67 ]
68 },
69 {
70 "cell_type": "code",
71 "execution_count": null,
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72 "metadata": {
73 "collapsed": false,
74 "deletable": true,
75 "editable": true
76 },
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77 "outputs": [],
78 "source": [
5e838b3e 79 "reload(\"../pkg\")\n",
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80 "p_nn = computeForecast(data, indices_ch, \"Neighbors\", \"Neighbors\", horizon=H)\n",
81 "p_nn2 = computeForecast(data, indices_ch, \"Neighbors2\", \"Neighbors\", horizon=H)\n",
82 "p_az = computeForecast(data, indices_ch, \"Average\", \"Zero\", horizon=H)\n",
83 "p_pz = computeForecast(data, indices_ch, \"Persistence\", \"Zero\", horizon=H, same_day=TRUE)"
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84 ]
85 },
86 {
87 "cell_type": "code",
88 "execution_count": null,
89 "metadata": {
6774e53d 90 "collapsed": false
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91 },
92 "outputs": [],
93 "source": [
6774e53d 94 "p_nn2$getParams(5)$weights"
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95 ]
96 },
97 {
98 "cell_type": "code",
99 "execution_count": null,
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100 "metadata": {
101 "collapsed": false,
102 "deletable": true,
103 "editable": true
104 },
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105 "outputs": [],
106 "source": [
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107 "e_nn = computeError(data, p_nn, H)\n",
108 "e_nn2 = computeError(data, p_nn2, H)\n",
109 "e_az = computeError(data, p_az, H)\n",
110 "e_pz = computeError(data, p_pz, H)\n",
111 "options(repr.plot.width=9, repr.plot.height=7)\n",
112 "plotError(list(e_nn, e_pz, e_az, e_nn2), cols=c(1,2,colors()[258], 4))\n",
113 "\n",
114 "# Noir: Neighbors, bleu: Neighbors2, vert: moyenne, rouge: persistence\n",
115 "\n",
116 "i_np = which.min(e_nn$abs$indices)\n",
117 "i_p = which.max(e_nn$abs$indices)"
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118 ]
119 },
120 {
121 "cell_type": "code",
122 "execution_count": null,
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123 "metadata": {
124 "collapsed": false,
125 "deletable": true,
126 "editable": true
127 },
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128 "outputs": [],
129 "source": [
130 "options(repr.plot.width=9, repr.plot.height=4)\n",
131 "par(mfrow=c(1,2))\n",
132 "\n",
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133 "plotPredReal(data, p_nn, i_np); title(paste(\"PredReal nn day\",i_np))\n",
134 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn day\",i_p))\n",
135 "\n",
136 "plotPredReal(data, p_nn2, i_np); title(paste(\"PredReal nn2 day\",i_np))\n",
137 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn2 day\",i_p))\n",
ff5df8e3 138 "\n",
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139 "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
140 "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
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141 "\n",
142 "# Bleu: prévue, noir: réalisée"
143 ]
144 },
145 {
146 "cell_type": "code",
147 "execution_count": null,
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148 "metadata": {
149 "collapsed": false,
150 "deletable": true,
151 "editable": true
152 },
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153 "outputs": [],
154 "source": [
155 "par(mfrow=c(1,2))\n",
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156 "f_np = computeFilaments(data, p_nn, i_np, plot=TRUE); title(paste(\"Filaments nn day\",i_np))\n",
157 "f_p = computeFilaments(data, p_nn, i_p, plot=TRUE); title(paste(\"Filaments nn day\",i_p))\n",
ff5df8e3 158 "\n",
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159 "f_np2 = computeFilaments(data, p_nn2, i_np, plot=TRUE); title(paste(\"Filaments nn2 day\",i_np))\n",
160 "f_p2 = computeFilaments(data, p_nn2, i_p, plot=TRUE); title(paste(\"Filaments nn2 day\",i_p))"
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161 ]
162 },
163 {
164 "cell_type": "code",
165 "execution_count": null,
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166 "metadata": {
167 "collapsed": false,
168 "deletable": true,
169 "editable": true
170 },
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171 "outputs": [],
172 "source": [
173 "par(mfrow=c(1,2))\n",
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174 "plotFilamentsBox(data, f_np); title(paste(\"FilBox nn day\",i_np))\n",
175 "plotFilamentsBox(data, f_p); title(paste(\"FilBox nn day\",i_p))\n",
ff5df8e3 176 "\n",
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177 "plotFilamentsBox(data, f_np2); title(paste(\"FilBox nn2 day\",i_np))\n",
178 "plotFilamentsBox(data, f_p2); title(paste(\"FilBox nn2 day\",i_p))"
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179 ]
180 },
181 {
182 "cell_type": "code",
183 "execution_count": null,
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184 "metadata": {
185 "collapsed": false,
186 "deletable": true,
187 "editable": true
188 },
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189 "outputs": [],
190 "source": [
191 "par(mfrow=c(1,2))\n",
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192 "plotRelVar(data, f_np); title(paste(\"StdDev nn day\",i_np))\n",
193 "plotRelVar(data, f_p); title(paste(\"StdDev nn day\",i_p))\n",
ff5df8e3 194 "\n",
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195 "plotRelVar(data, f_np2); title(paste(\"StdDev nn2 day\",i_np))\n",
196 "plotRelVar(data, f_p2); title(paste(\"StdDev nn2 day\",i_p))\n",
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197 "\n",
198 "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
199 ]
200 },
201 {
202 "cell_type": "code",
203 "execution_count": null,
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204 "metadata": {
205 "collapsed": false,
206 "deletable": true,
207 "editable": true
208 },
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209 "outputs": [],
210 "source": [
211 "par(mfrow=c(1,2))\n",
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212 "plotSimils(p_nn, i_np); title(paste(\"Weights nn day\",i_np))\n",
213 "plotSimils(p_nn, i_p); title(paste(\"Weights nn day\",i_p))\n",
ff5df8e3 214 "\n",
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215 "plotSimils(p_nn2, i_np); title(paste(\"Weights nn2 day\",i_np))\n",
216 "plotSimils(p_nn2, i_p); title(paste(\"Weights nn2 day\",i_p))\n",
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217 "\n",
218 "# - pollué à gauche, + pollué à droite"
219 ]
220 },
221 {
222 "cell_type": "code",
223 "execution_count": null,
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224 "metadata": {
225 "collapsed": false,
226 "deletable": true,
227 "editable": true
228 },
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229 "outputs": [],
230 "source": [
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231 "# Fenêtres sélectionnées dans ]0,7] / nn à gauche, nn2 à droite\n",
232 "p_nn$getParams(i_np)$window\n",
233 "p_nn$getParams(i_p)$window\n",
ff5df8e3 234 "\n",
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235 "p_nn2$getParams(i_np)$window\n",
236 "p_nn2$getParams(i_p)$window"
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237 ]
238 },
239 {
240 "cell_type": "markdown",
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241 "metadata": {
242 "deletable": true,
243 "editable": true
244 },
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245 "source": [
246 "\n",
247 "\n",
248 "<h2 style=\"color:blue;font-size:2em\">Pollution par épandage</h2>"
249 ]
250 },
251 {
252 "cell_type": "code",
253 "execution_count": null,
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254 "metadata": {
255 "collapsed": false,
256 "deletable": true,
257 "editable": true
258 },
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259 "outputs": [],
260 "source": [
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261 "p_nn = computeForecast(data, indices_ep, \"Neighbors\", \"Neighbors\", horizon=H)\n",
262 "p_nn2 = computeForecast(data, indices_ep, \"Neighbors2\", \"Zero\", horizon=H)\n",
263 "p_az = computeForecast(data, indices_ep, \"Average\", \"Zero\", horizon=H)\n",
264 "p_pz = computeForecast(data, indices_ep, \"Persistence\", \"Zero\", horizon=H, same_day=TRUE)"
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265 ]
266 },
267 {
268 "cell_type": "code",
269 "execution_count": null,
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270 "metadata": {
271 "collapsed": false,
272 "deletable": true,
273 "editable": true
274 },
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275 "outputs": [],
276 "source": [
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277 "e_nn = computeError(data, p_nn, H)\n",
278 "e_nn2 = computeError(data, p_nn2, H)\n",
279 "e_az = computeError(data, p_az, H)\n",
280 "e_pz = computeError(data, p_pz, H)\n",
ff5df8e3 281 "options(repr.plot.width=9, repr.plot.height=7)\n",
6774e53d 282 "plotError(list(e_nn, e_pz, e_az, e_nn2), cols=c(1,2,colors()[258], 4))\n",
ff5df8e3 283 "\n",
6774e53d 284 "# Noir: Neighbors, bleu: Neighbors2, vert: moyenne, rouge: persistence\n",
ff5df8e3 285 "\n",
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286 "i_np = which.min(e_nn$abs$indices)\n",
287 "i_p = which.max(e_nn$abs$indices)"
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288 ]
289 },
290 {
291 "cell_type": "code",
292 "execution_count": null,
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293 "metadata": {
294 "collapsed": false,
295 "deletable": true,
296 "editable": true
297 },
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298 "outputs": [],
299 "source": [
300 "options(repr.plot.width=9, repr.plot.height=4)\n",
301 "par(mfrow=c(1,2))\n",
302 "\n",
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303 "plotPredReal(data, p_nn, i_np); title(paste(\"PredReal nn day\",i_np))\n",
304 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn day\",i_p))\n",
ff5df8e3 305 "\n",
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306 "plotPredReal(data, p_nn2, i_np); title(paste(\"PredReal nn2 day\",i_np))\n",
307 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn2 day\",i_p))\n",
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308 "\n",
309 "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
310 "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
311 "\n",
312 "# Bleu: prévue, noir: réalisée"
313 ]
314 },
315 {
316 "cell_type": "code",
317 "execution_count": null,
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318 "metadata": {
319 "collapsed": false,
320 "deletable": true,
321 "editable": true
322 },
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323 "outputs": [],
324 "source": [
325 "par(mfrow=c(1,2))\n",
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326 "f_np = computeFilaments(data, p_nn, i_np, plot=TRUE); title(paste(\"Filaments nn day\",i_np))\n",
327 "f_p = computeFilaments(data, p_nn, i_p, plot=TRUE); title(paste(\"Filaments nn day\",i_p))\n",
ff5df8e3 328 "\n",
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329 "f_np2 = computeFilaments(data, p_nn2, i_np, plot=TRUE); title(paste(\"Filaments nn2 day\",i_np))\n",
330 "f_p2 = computeFilaments(data, p_nn2, i_p, plot=TRUE); title(paste(\"Filaments nn2 day\",i_p))"
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331 ]
332 },
333 {
334 "cell_type": "code",
335 "execution_count": null,
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336 "metadata": {
337 "collapsed": false,
338 "deletable": true,
339 "editable": true
340 },
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341 "outputs": [],
342 "source": [
343 "par(mfrow=c(1,2))\n",
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344 "plotFilamentsBox(data, f_np); title(paste(\"FilBox nn day\",i_np))\n",
345 "plotFilamentsBox(data, f_p); title(paste(\"FilBox nn day\",i_p))\n",
ff5df8e3 346 "\n",
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347 "plotFilamentsBox(data, f_np2); title(paste(\"FilBox nn2 day\",i_np))\n",
348 "plotFilamentsBox(data, f_p2); title(paste(\"FilBox nn2 day\",i_p))"
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349 ]
350 },
351 {
352 "cell_type": "code",
353 "execution_count": null,
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354 "metadata": {
355 "collapsed": false,
356 "deletable": true,
357 "editable": true
358 },
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359 "outputs": [],
360 "source": [
361 "par(mfrow=c(1,2))\n",
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362 "plotRelVar(data, f_np); title(paste(\"StdDev nn day\",i_np))\n",
363 "plotRelVar(data, f_p); title(paste(\"StdDev nn day\",i_p))\n",
ff5df8e3 364 "\n",
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365 "plotRelVar(data, f_np2); title(paste(\"StdDev nn2 day\",i_np))\n",
366 "plotRelVar(data, f_p2); title(paste(\"StdDev nn2 day\",i_p))\n",
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367 "\n",
368 "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
369 ]
370 },
371 {
372 "cell_type": "code",
373 "execution_count": null,
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374 "metadata": {
375 "collapsed": false,
376 "deletable": true,
377 "editable": true
378 },
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379 "outputs": [],
380 "source": [
381 "par(mfrow=c(1,2))\n",
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382 "plotSimils(p_nn, i_np); title(paste(\"Weights nn day\",i_np))\n",
383 "plotSimils(p_nn, i_p); title(paste(\"Weights nn day\",i_p))\n",
ff5df8e3 384 "\n",
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385 "plotSimils(p_nn2, i_np); title(paste(\"Weights nn2 day\",i_np))\n",
386 "plotSimils(p_nn2, i_p); title(paste(\"Weights nn2 day\",i_p))\n",
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387 "\n",
388 "# - pollué à gauche, + pollué à droite"
389 ]
390 },
391 {
392 "cell_type": "code",
393 "execution_count": null,
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394 "metadata": {
395 "collapsed": false,
396 "deletable": true,
397 "editable": true
398 },
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399 "outputs": [],
400 "source": [
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401 "# Fenêtres sélectionnées dans ]0,7] / nn à gauche, nn2 à droite\n",
402 "p_nn$getParams(i_np)$window\n",
403 "p_nn$getParams(i_p)$window\n",
ff5df8e3 404 "\n",
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405 "p_nn2$getParams(i_np)$window\n",
406 "p_nn2$getParams(i_p)$window"
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407 ]
408 },
409 {
410 "cell_type": "markdown",
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411 "metadata": {
412 "deletable": true,
413 "editable": true
414 },
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415 "source": [
416 "\n",
417 "\n",
418 "<h2 style=\"color:blue;font-size:2em\">Semaine non polluée</h2>"
419 ]
420 },
421 {
422 "cell_type": "code",
423 "execution_count": null,
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424 "metadata": {
425 "collapsed": false,
426 "deletable": true,
427 "editable": true
428 },
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429 "outputs": [],
430 "source": [
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431 "p_nn = computeForecast(data, indices_np, \"Neighbors\", \"Neighbors\", horizon=H)\n",
432 "p_nn2 = computeForecast(data, indices_np, \"Neighbors2\", \"Zero\", horizon=H)\n",
433 "p_az = computeForecast(data, indices_np, \"Average\", \"Zero\", horizon=H)\n",
434 "p_pz = computeForecast(data, indices_np, \"Persistence\", \"Zero\", horizon=H, same_day=FALSE)"
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435 ]
436 },
437 {
438 "cell_type": "code",
439 "execution_count": null,
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440 "metadata": {
441 "collapsed": false,
442 "deletable": true,
443 "editable": true
444 },
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445 "outputs": [],
446 "source": [
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447 "e_nn = computeError(data, p_nn, H)\n",
448 "e_nn2 = computeError(data, p_nn2, H)\n",
449 "e_az = computeError(data, p_az, H)\n",
450 "e_pz = computeError(data, p_pz, H)\n",
ff5df8e3 451 "options(repr.plot.width=9, repr.plot.height=7)\n",
6774e53d 452 "plotError(list(e_nn, e_pz, e_az, e_nn2), cols=c(1,2,colors()[258], 4))\n",
ff5df8e3 453 "\n",
6774e53d 454 "# Noir: Neighbors, bleu: Neighbors2, vert: moyenne, rouge: persistence\n",
ff5df8e3 455 "\n",
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456 "i_np = which.min(e_nn$abs$indices)\n",
457 "i_p = which.max(e_nn$abs$indices)"
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458 ]
459 },
460 {
461 "cell_type": "code",
462 "execution_count": null,
5e838b3e
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463 "metadata": {
464 "collapsed": false,
465 "deletable": true,
466 "editable": true
467 },
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468 "outputs": [],
469 "source": [
470 "options(repr.plot.width=9, repr.plot.height=4)\n",
471 "par(mfrow=c(1,2))\n",
472 "\n",
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473 "plotPredReal(data, p_nn, i_np); title(paste(\"PredReal nn day\",i_np))\n",
474 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn day\",i_p))\n",
ff5df8e3 475 "\n",
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476 "plotPredReal(data, p_nn2, i_np); title(paste(\"PredReal nn2 day\",i_np))\n",
477 "plotPredReal(data, p_nn2, i_p); title(paste(\"PredReal nn2 day\",i_p))\n",
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478 "\n",
479 "plotPredReal(data, p_az, i_np); title(paste(\"PredReal az day\",i_np))\n",
480 "plotPredReal(data, p_az, i_p); title(paste(\"PredReal az day\",i_p))\n",
481 "\n",
482 "# Bleu: prévue, noir: réalisée"
483 ]
484 },
485 {
486 "cell_type": "code",
487 "execution_count": null,
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488 "metadata": {
489 "collapsed": false,
490 "deletable": true,
491 "editable": true
492 },
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493 "outputs": [],
494 "source": [
495 "par(mfrow=c(1,2))\n",
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496 "f_np = computeFilaments(data, p_nn, i_np, plot=TRUE); title(paste(\"Filaments nn day\",i_np))\n",
497 "f_p = computeFilaments(data, p_nn, i_p, plot=TRUE); title(paste(\"Filaments nn day\",i_p))\n",
ff5df8e3 498 "\n",
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499 "f_np2 = computeFilaments(data, p_nn2, i_np, plot=TRUE); title(paste(\"Filaments nn2 day\",i_np))\n",
500 "f_p2 = computeFilaments(data, p_nn2, i_p, plot=TRUE); title(paste(\"Filaments nn2 day\",i_p))"
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501 ]
502 },
503 {
504 "cell_type": "code",
505 "execution_count": null,
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506 "metadata": {
507 "collapsed": false,
508 "deletable": true,
509 "editable": true
510 },
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511 "outputs": [],
512 "source": [
513 "par(mfrow=c(1,2))\n",
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514 "plotFilamentsBox(data, f_np); title(paste(\"FilBox nn day\",i_np))\n",
515 "plotFilamentsBox(data, f_p); title(paste(\"FilBox nn day\",i_p))\n",
ff5df8e3 516 "\n",
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517 "plotFilamentsBox(data, f_np2); title(paste(\"FilBox nn2 day\",i_np))\n",
518 "plotFilamentsBox(data, f_p2); title(paste(\"FilBox nn2 day\",i_p))"
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519 ]
520 },
521 {
522 "cell_type": "code",
523 "execution_count": null,
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524 "metadata": {
525 "collapsed": false,
526 "deletable": true,
527 "editable": true
528 },
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529 "outputs": [],
530 "source": [
531 "par(mfrow=c(1,2))\n",
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532 "plotRelVar(data, f_np); title(paste(\"StdDev nn day\",i_np))\n",
533 "plotRelVar(data, f_p); title(paste(\"StdDev nn day\",i_p))\n",
ff5df8e3 534 "\n",
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535 "plotRelVar(data, f_np2); title(paste(\"StdDev nn2 day\",i_np))\n",
536 "plotRelVar(data, f_p2); title(paste(\"StdDev nn2 day\",i_p))\n",
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537 "\n",
538 "# Variabilité globale en rouge ; sur les 60 voisins (+ lendemains) en noir"
539 ]
540 },
541 {
542 "cell_type": "code",
543 "execution_count": null,
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544 "metadata": {
545 "collapsed": false,
546 "deletable": true,
547 "editable": true
548 },
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549 "outputs": [],
550 "source": [
551 "par(mfrow=c(1,2))\n",
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552 "plotSimils(p_nn, i_np); title(paste(\"Weights nn day\",i_np))\n",
553 "plotSimils(p_nn, i_p); title(paste(\"Weights nn day\",i_p))\n",
ff5df8e3 554 "\n",
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555 "plotSimils(p_nn2, i_np); title(paste(\"Weights nn2 day\",i_np))\n",
556 "plotSimils(p_nn2, i_p); title(paste(\"Weights nn2 day\",i_p))\n",
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557 "\n",
558 "# - pollué à gauche, + pollué à droite"
559 ]
560 },
561 {
562 "cell_type": "code",
563 "execution_count": null,
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564 "metadata": {
565 "collapsed": false,
566 "deletable": true,
567 "editable": true
568 },
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569 "outputs": [],
570 "source": [
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571 "# Fenêtres sélectionnées dans ]0,7] / nn à gauche, nn2 à droite\n",
572 "p_nn$getParams(i_np)$window\n",
573 "p_nn$getParams(i_p)$window\n",
ff5df8e3 574 "\n",
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575 "p_nn2$getParams(i_np)$window\n",
576 "p_nn2$getParams(i_p)$window"
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577 ]
578 }
579 ],
580 "metadata": {
581 "kernelspec": {
582 "display_name": "R",
583 "language": "R",
584 "name": "ir"
585 },
586 "language_info": {
587 "codemirror_mode": "r",
588 "file_extension": ".r",
589 "mimetype": "text/x-r-source",
590 "name": "R",
591 "pygments_lexer": "r",
592 "version": "3.3.3"
593 }
594 },
595 "nbformat": 4,
596 "nbformat_minor": 2
597}