'update'

[talweg.git] / reports / report_2017-03-01.average.ipynb

diff --git a/reports/report_2017-03-01.nbconvert.ipynb b/reports/report_2017-03-01.average.ipynb
similarity index 86%
rename from reports/report_2017-03-01.nbconvert.ipynb
rename to reports/report_2017-03-01.average.ipynb
index bd2e25e..4f563cc 100644 (file)
--- a/reports/report_2017-03-01.nbconvert.ipynb
+++ b/reports/report_2017-03-01.average.ipynb
@@ -53,7 +53,7 @@
     "indices = seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\")\n",
     "p_ch_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
     "p_ch_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=TRUE)\n",
-    "p_ch_az = getForecast(data, indices, \"Average\", \"Zero\", memory=183)\n",
+    "p_ch_az = getForecast(data, indices, \"Average\", \"Zero\") #, memory=183)\n",
     "#p_ch_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
     "#p_ch_l = getForecast(data, indices, \"Level\", same_day=FALSE)"
    ]
@@ -107,6 +107,26 @@
     "Prédictions d'autant plus lisses que le jour à prévoir est atypique (pollué)."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "par(mfrow=c(1,2))\n",
+    "plotPredReal(data, p_ch_az, 3)\n",
+    "plotPredReal(data, p_ch_az, 4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les erreurs sont proches, mais les courbes prédites très différentes : avantage à \"Neighbors\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -181,7 +201,7 @@
     "indices = seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\")\n",
     "p_ep_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
     "p_ep_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=TRUE)\n",
-    "p_ep_az = getForecast(data, indices, \"Average\", \"Zero\", memory=183)\n",
+    "p_ep_az = getForecast(data, indices, \"Average\", \"Zero\") #, memory=183)\n",
     "#p_ep_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
     "#p_ep_l = getForecast(data, indices, \"Level\", same_day=TRUE)"
    ]
@@ -223,7 +243,9 @@
     "par(mfrow=c(1,2))\n",
     "options(repr.plot.width=9, repr.plot.height=4)\n",
     "plotPredReal(data, p_ep_nn, 4)\n",
-    "plotPredReal(data, p_ep_nn, 6)"
+    "plotPredReal(data, p_ep_nn, 6)\n",
+    "\n",
+    "#Bleu: prévue, noir: réalisée"
    ]
   },
   {
@@ -233,6 +255,26 @@
     "À gauche un jour \"bien\" prévu, à droite le pic d'erreur (jour 6)."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "par(mfrow=c(1,2))\n",
+    "plotPredReal(data, p_ep_pz, 4)\n",
+    "plotPredReal(data, p_ep_pz, 6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Bonnes performances de la persistence (par chance...)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -284,7 +326,7 @@
     "indices = seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\")\n",
     "p_np_nn = getForecast(data,indices,\"Neighbors\",\"Neighbors\",simtype=\"mix\",same_season=FALSE,mix_strategy=\"mult\")\n",
     "p_np_pz = getForecast(data, indices, \"Persistence\", \"Zero\", same_day=FALSE)\n",
-    "p_np_az = getForecast(data, indices, \"Average\", \"Zero\", memory=183)\n",
+    "p_np_az = getForecast(data, indices, \"Average\", \"Zero\") #, memory=183)\n",
     "#p_np_zz = getForecast(data, indices, \"Zero\", \"Zero\")\n",
     "#p_np_l = getForecast(data, indices, \"Level\", same_day=FALSE)"
    ]
@@ -326,7 +368,9 @@
     "par(mfrow=c(1,2))\n",
     "options(repr.plot.width=9, repr.plot.height=4)\n",
     "plotPredReal(data, p_np_nn, 3)\n",
-    "plotPredReal(data, p_np_nn, 6)"
+    "plotPredReal(data, p_np_nn, 6)\n",
+    "\n",
+    "#Bleu: prévue, noir: réalisée"
    ]
   },
   {
@@ -336,6 +380,26 @@
     "Les \"bonnes\" prédictions (à gauche) sont tout de même trop lissées."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "par(mfrow=c(1,2))\n",
+    "plotPredReal(data, p_np_az, 3)\n",
+    "plotPredReal(data, p_np_az, 6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Légèrement meilleur ajustement par la méthode \"Average\" ; très net à droite."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,