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

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "library(talweg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = getData(ts_data=\"../data/pm10_mesures_H_loc.csv\", exo_data=\"../data/meteo_extra_noNAs.csv\",\n",
    "               input_tz = \"Europe/Paris\", working_tz=\"Europe/Paris\", predict_at=7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pollution par chauffage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "p_ch_nn = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
    "                   \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
    "p_ch_pz = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
    "                   \"Persistence\", \"Zero\")\n",
    "p_ch_az = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
    "                   \"Average\", \"Zero\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "e_ch_nn = getError(data, p_ch_nn, 17)\n",
    "e_ch_pz = getError(data, p_ch_pz, 17)\n",
    "e_ch_az = getError(data, p_ch_az, 17)\n",
    "options(repr.plot.width=9, repr.plot.height=6)\n",
    "plotError(list(e_ch_nn, e_ch_pz, e_ch_az), cols=c(1,2,colors()[258]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,2))\n",
    "options(repr.plot.width=9, repr.plot.height=4)\n",
    "plotPredReal(data, p_ch_nn, 3)\n",
    "plotPredReal(data, p_ch_nn, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,2))\n",
    "plotFilaments(data, p_ch_nn$getIndexInData(3))\n",
    "plotFilaments(data, p_ch_nn$getIndexInData(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,3))\n",
    "plotSimils(p_ch_nn, 3)\n",
    "plotSimils(p_ch_nn, 4)\n",
    "plotSimils(p_ch_nn, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pollution par épandage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "p_ep_nn = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
    "                   \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
    "p_ep_pz = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
    "                   \"Persistence\", \"Zero\")\n",
    "p_ep_az = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
    "                   \"Average\", \"Zero\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "e_ep_nn = getError(data, p_ep_nn, 17)\n",
    "e_ep_pz = getError(data, p_ep_pz, 17)\n",
    "e_ep_az = getError(data, p_ep_az, 17)\n",
    "options(repr.plot.width=9, repr.plot.height=6)\n",
    "plotError(list(e_ep_nn, e_ep_pz, e_ep_az), cols=c(1,2,colors()[258]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,2))\n",
    "options(repr.plot.width=9, repr.plot.height=4)\n",
    "plotPredReal(data, p_ep_nn, 3)\n",
    "plotPredReal(data, p_ep_nn, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,2))\n",
    "plotFilaments(data, p_ep_nn$getIndexInData(3))\n",
    "plotFilaments(data, p_ep_nn$getIndexInData(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,3))\n",
    "plotSimils(p_ep_nn, 3)\n",
    "plotSimils(p_ep_nn, 4)\n",
    "plotSimils(p_ep_nn, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Semaine non polluée"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "p_np_nn = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
    "                   \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
    "p_np_pz = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
    "                   \"Persistence\", \"Zero\")\n",
    "p_np_az = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
    "                   \"Average\", \"Zero\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "e_np_nn = getError(data, p_np_nn, 17)\n",
    "e_np_pz = getError(data, p_np_pz, 17)\n",
    "e_np_az = getError(data, p_np_az, 17)\n",
    "options(repr.plot.width=9, repr.plot.height=6)\n",
    "plotError(list(e_np_nn, e_np_pz, e_np_az), cols=c(1,2,colors()[258]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "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, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,2))\n",
    "plotFilaments(data, p_np_nn$getIndexInData(3))\n",
    "plotFilaments(data, p_np_nn$getIndexInData(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "par(mfrow=c(1,3))\n",
    "plotSimils(p_np_nn, 3)\n",
    "plotSimils(p_np_nn, 4)\n",
    "plotSimils(p_np_nn, 5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
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Commit	Line	Data
09cf9c19 BA	1	{
	2	"cells": [
	3	{
	4	"cell_type": "code",
	5	"execution_count": null,
	6	"metadata": {
	7	"collapsed": false
	8	},
	9	"outputs": [],
	10	"source": [
	11	"library(talweg)"
	12	]
	13	},
	14	{
	15	"cell_type": "code",
	16	"execution_count": null,
	17	"metadata": {
	18	"collapsed": false
	19	},
	20	"outputs": [],
	21	"source": [
	22	"data = getData(ts_data=\"../data/pm10_mesures_H_loc.csv\", exo_data=\"../data/meteo_extra_noNAs.csv\",\n",
	23	" input_tz = \"Europe/Paris\", working_tz=\"Europe/Paris\", predict_at=7)"
	24	]
	25	},
	26	{
	27	"cell_type": "markdown",
	28	"metadata": {},
	29	"source": [
	30	"## Pollution par chauffage"
	31	]
	32	},
	33	{
	34	"cell_type": "code",
	35	"execution_count": null,
	36	"metadata": {
	37	"collapsed": false
	38	},
	39	"outputs": [],
	40	"source": [
	41	"p_ch_nn = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
	42	" \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
	43	"p_ch_pz = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
	44	" \"Persistence\", \"Zero\")\n",
	45	"p_ch_az = getForecast(data, seq(as.Date(\"2015-01-18\"),as.Date(\"2015-01-24\"),\"days\"), Inf, 17,\n",
	46	" \"Average\", \"Zero\")"
	47	]
	48	},
	49	{
	50	"cell_type": "code",
	51	"execution_count": null,
	52	"metadata": {
	53	"collapsed": false
	54	},
	55	"outputs": [],
	56	"source": [
	57	"e_ch_nn = getError(data, p_ch_nn, 17)\n",
	58	"e_ch_pz = getError(data, p_ch_pz, 17)\n",
	59	"e_ch_az = getError(data, p_ch_az, 17)\n",
	60	"options(repr.plot.width=9, repr.plot.height=6)\n",
	61	"plotError(list(e_ch_nn, e_ch_pz, e_ch_az), cols=c(1,2,colors()[258]))"
	62	]
	63	},
	64	{
65	"cell_type": "code",
66	"execution_count": null,
67	"metadata": {
68	"collapsed": false
69	},
70	"outputs": [],
71	"source": [
72	"par(mfrow=c(1,2))\n",
73	"options(repr.plot.width=9, repr.plot.height=4)\n",
74	"plotPredReal(data, p_ch_nn, 3)\n",
75	"plotPredReal(data, p_ch_nn, 4)"
76	]
77	},
78	{
79	"cell_type": "code",
80	"execution_count": null,
81	"metadata": {
82	"collapsed": false
83	},
84	"outputs": [],
85	"source": [
86	"par(mfrow=c(1,2))\n",
87	"plotFilaments(data, p_ch_nn$getIndexInData(3))\n",
88	"plotFilaments(data, p_ch_nn$getIndexInData(4))"
89	]
90	},
91	{
92	"cell_type": "code",
93	"execution_count": null,
94	"metadata": {
95	"collapsed": false
96	},
97	"outputs": [],
98	"source": [
99	"par(mfrow=c(1,3))\n",
100	"plotSimils(p_ch_nn, 3)\n",
101	"plotSimils(p_ch_nn, 4)\n",
102	"plotSimils(p_ch_nn, 5)"
103	]
104	},
105	{
106	"cell_type": "markdown",
107	"metadata": {},
108	"source": [
109	"## Pollution par épandage"
110	]
111	},
112	{
113	"cell_type": "code",
114	"execution_count": null,
115	"metadata": {
116	"collapsed": false
117	},
118	"outputs": [],
119	"source": [
120	"p_ep_nn = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
121	" \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
122	"p_ep_pz = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
123	" \"Persistence\", \"Zero\")\n",
124	"p_ep_az = getForecast(data, seq(as.Date(\"2015-03-15\"),as.Date(\"2015-03-21\"),\"days\"), Inf, 17,\n",
125	" \"Average\", \"Zero\")"
126	]
127	},
128	{
129	"cell_type": "code",
130	"execution_count": null,
131	"metadata": {
132	"collapsed": false
133	},
134	"outputs": [],
135	"source": [
136	"e_ep_nn = getError(data, p_ep_nn, 17)\n",
137	"e_ep_pz = getError(data, p_ep_pz, 17)\n",
138	"e_ep_az = getError(data, p_ep_az, 17)\n",
139	"options(repr.plot.width=9, repr.plot.height=6)\n",
140	"plotError(list(e_ep_nn, e_ep_pz, e_ep_az), cols=c(1,2,colors()[258]))"
141	]
142	},
143	{
144	"cell_type": "code",
145	"execution_count": null,
146	"metadata": {
147	"collapsed": false
148	},
149	"outputs": [],
150	"source": [
151	"par(mfrow=c(1,2))\n",
152	"options(repr.plot.width=9, repr.plot.height=4)\n",
153	"plotPredReal(data, p_ep_nn, 3)\n",
154	"plotPredReal(data, p_ep_nn, 4)"
155	]
156	},
157	{
158	"cell_type": "code",
159	"execution_count": null,
160	"metadata": {
161	"collapsed": false
162	},
163	"outputs": [],
164	"source": [
165	"par(mfrow=c(1,2))\n",
166	"plotFilaments(data, p_ep_nn$getIndexInData(3))\n",
167	"plotFilaments(data, p_ep_nn$getIndexInData(4))"
168	]
169	},
170	{
171	"cell_type": "code",
172	"execution_count": null,
173	"metadata": {
174	"collapsed": false
175	},
176	"outputs": [],
177	"source": [
178	"par(mfrow=c(1,3))\n",
179	"plotSimils(p_ep_nn, 3)\n",
180	"plotSimils(p_ep_nn, 4)\n",
181	"plotSimils(p_ep_nn, 5)"
182	]
183	},
184	{
185	"cell_type": "markdown",
186	"metadata": {},
187	"source": [
188	"## Semaine non polluée"
189	]
190	},
191	{
192	"cell_type": "code",
193	"execution_count": null,
194	"metadata": {
195	"collapsed": false
196	},
197	"outputs": [],
198	"source": [
199	"p_np_nn = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
200	" \"Neighbors\", \"Neighbors\", simtype=\"mix\", same_season=FALSE, mix_strategy=\"mult\")\n",
201	"p_np_pz = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
202	" \"Persistence\", \"Zero\")\n",
203	"p_np_az = getForecast(data, seq(as.Date(\"2015-04-26\"),as.Date(\"2015-05-02\"),\"days\"), Inf, 17,\n",
204	" \"Average\", \"Zero\")"
205	]
206	},
207	{
208	"cell_type": "code",
209	"execution_count": null,
210	"metadata": {
211	"collapsed": false
212	},
213	"outputs": [],
214	"source": [
215	"e_np_nn = getError(data, p_np_nn, 17)\n",
216	"e_np_pz = getError(data, p_np_pz, 17)\n",
217	"e_np_az = getError(data, p_np_az, 17)\n",
218	"options(repr.plot.width=9, repr.plot.height=6)\n",
219	"plotError(list(e_np_nn, e_np_pz, e_np_az), cols=c(1,2,colors()[258]))"
220	]
221	},
222	{
223	"cell_type": "code",
224	"execution_count": null,
225	"metadata": {
226	"collapsed": false
227	},
228	"outputs": [],
229	"source": [
230	"par(mfrow=c(1,2))\n",
231	"options(repr.plot.width=9, repr.plot.height=4)\n",
232	"plotPredReal(data, p_np_nn, 3)\n",
233	"plotPredReal(data, p_np_nn, 4)"
234	]
235	},
236	{
237	"cell_type": "code",
238	"execution_count": null,
239	"metadata": {
240	"collapsed": false
241	},
242	"outputs": [],
243	"source": [
244	"par(mfrow=c(1,2))\n",
245	"plotFilaments(data, p_np_nn$getIndexInData(3))\n",
246	"plotFilaments(data, p_np_nn$getIndexInData(4))"
247	]
248	},
249	{
250	"cell_type": "code",
251	"execution_count": null,
252	"metadata": {
253	"collapsed": false
254	},
255	"outputs": [],
256	"source": [
257	"par(mfrow=c(1,3))\n",
258	"plotSimils(p_np_nn, 3)\n",
259	"plotSimils(p_np_nn, 4)\n",
260	"plotSimils(p_np_nn, 5)"
261	]
262	}
263	],
264	"metadata": {
265	"kernelspec": {
266	"display_name": "R",
267	"language": "R",
268	"name": "ir"
269	},
270	"language_info": {
271	"codemirror_mode": "r",
272	"file_extension": ".r",
273	"mimetype": "text/x-r-source",
274	"name": "R",
275	"pygments_lexer": "r",
276	"version": "3.3.2"
277	}
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279	"nbformat": 4,
280	"nbformat_minor": 2
281	}