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bnlearn-continuous-prediction-2days.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"El objetivo de este documento es probar una red bayesiana para realizar predicción sobre los datos de sensores. Para ello aprendemos una red bayesiana y ajustamos sus parámetros, considerando los datos de entrada como continuos (no realizamos discretización), por eso veremos que se samplean la distribución de cada nodo/variable a una gaussiana.\n",
"\n",
"El dataset utilizado es de 20 sensores cercanos entre sí, distribuidos en una parcela de 100x100, más los sensores de una estación meteorológica (variables cuyo nombre empieza con Est\\_ ). Estos datos se han agrupado de forma diaria (dataset sensores.csv) creando variables como la media, máxima, mínima, temperatura a las 15,12 y 18 hs de cada sensor.\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Attaching package: ‘bnlearn’\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" sigma\n",
"\n",
"Loading required package: zoo\n",
"\n",
"Attaching package: ‘zoo’\n",
"\n",
"The following objects are masked from ‘package:base’:\n",
"\n",
" as.Date, as.Date.numeric\n",
"\n",
"Loading required package: timeDate\n",
"This is forecast 5.8 \n",
"\n"
]
}
],
"source": [
"library(bnlearn) \n",
"library(forecast)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Preprocesando el dataset "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Warning message:\n",
"“Missing column names filled in: 'X1' [1]”Parsed with column specification:\n",
"cols(\n",
" .default = col_double(),\n",
" X1 = col_datetime(format = \"\")\n",
")\n",
"See spec(...) for full column specifications.\n"
]
},
{
"data": {
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"\t<li>'Est.humedad_med'</li>\n",
"\t<li>'Est.humedad_max'</li>\n",
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"\t<li>'Est.temp_max'</li>\n",
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"</ol>\n"
],
"text/latex": [
"\\begin{enumerate*}\n",
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],
"text/markdown": [
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"\n",
"\n"
],
"text/plain": [
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" [57] \"S5.min\" \"S6.min\" \"S7.min\" \"S8.min\" \n",
" [61] \"S9.min\" \"S10.15hs\" \"S11.15hs\" \"S12.15hs\" \n",
" [65] \"S13.15hs\" \"S14.15hs\" \"S15.15hs\" \"S16.15hs\" \n",
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" [77] \"S5.15hs\" \"S6.15hs\" \"S7.15hs\" \"S8.15hs\" \n",
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" [85] \"S13.12hs\" \"S14.12hs\" \"S15.12hs\" \"S16.12hs\" \n",
" [89] \"S17.12hs\" \"S18.12hs\" \"S19.12hs\" \"S1.12hs\" \n",
" [93] \"S20.12hs\" \"S2.12hs\" \"S3.12hs\" \"S4.12hs\" \n",
" [97] \"S5.12hs\" \"S6.12hs\" \"S7.12hs\" \"S8.12hs\" \n",
"[101] \"S9.12hs\" \"S10.18hs\" \"S11.18hs\" \"S12.18hs\" \n",
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"[109] \"S17.18hs\" \"S18.18hs\" \"S19.18hs\" \"S1.18hs\" \n",
"[113] \"S20.18hs\" \"S2.18hs\" \"S3.18hs\" \"S4.18hs\" \n",
"[117] \"S5.18hs\" \"S6.18hs\" \"S7.18hs\" \"S8.18hs\" \n",
"[121] \"S9.18hs\" \"Est.humedad_min\" \"Est.humedad_med\" \"Est.humedad_max\"\n",
"[125] \"Est.temp_min\" \"Est.temp_max\" \"Est.temp_med\" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"library(readr)\n",
"sensores <- read_csv(\"../data/sensores.csv\")\n",
"colnames(sensores)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"465"
],
"text/latex": [
"465"
],
"text/markdown": [
"465"
],
"text/plain": [
"[1] 465"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nrow(sensores)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Procedemos a armar un dataset con las variables, colocando los datos de hace dos días, luego hace un día y luego día presente. Por ello, desfazamos el dataset para que queden primero las variables en T-2, T-1 y luego en t o tiempo presente.\n",
"\n",
"Más adelante nos preguntaremos por la predicción de la temperatura mínima en t (por ejemplo para un sensor especifico S11.min_t"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"# como denomino a las variables que quiero predecir\n",
"\n",
"pred_sensores = c(\"S10.min_t\",\"S11.min_t\",\"S12.min_t\",\"S13.min_t\",\"S14.min_t\",\"S15.min_t\",\"S16.min_t\",\"S18.min_t\", \"S19.min_t\",\"S1.min_t\",\"S20.min_t\",\"S2.min_t\",\"S3.min_t\",\"S4.min_t\",\"S5.min_t\",\n",
" \"S6.min_t\",\"S7.min_t\",\"S8.min_t\",\"S9.min_t\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<ol class=list-inline>\n",
"\t<li>'S10.max_T_2'</li>\n",
"\t<li>'S11.max_T_2'</li>\n",
"\t<li>'S12.max_T_2'</li>\n",
"\t<li>'S13.max_T_2'</li>\n",
"\t<li>'S14.max_T_2'</li>\n",
"\t<li>'S15.max_T_2'</li>\n",
"\t<li>'S16.max_T_2'</li>\n",
"\t<li>'S17.max_T_2'</li>\n",
"\t<li>'S18.max_T_2'</li>\n",
"\t<li>'S19.max_T_2'</li>\n",
"\t<li>'S1.max_T_2'</li>\n",
"\t<li>'S20.max_T_2'</li>\n",
"\t<li>'S2.max_T_2'</li>\n",
"\t<li>'S3.max_T_2'</li>\n",
"\t<li>'S4.max_T_2'</li>\n",
"\t<li>'S5.max_T_2'</li>\n",
"\t<li>'S6.max_T_2'</li>\n",
"\t<li>'S7.max_T_2'</li>\n",
"\t<li>'S8.max_T_2'</li>\n",
"\t<li>'S9.max_T_2'</li>\n",
"\t<li>'S10.media_T_2'</li>\n",
"\t<li>'S11.media_T_2'</li>\n",
"\t<li>'S12.media_T_2'</li>\n",
"\t<li>'S13.media_T_2'</li>\n",
"\t<li>'S14.media_T_2'</li>\n",
"\t<li>'S15.media_T_2'</li>\n",
"\t<li>'S16.media_T_2'</li>\n",
"\t<li>'S17.media_T_2'</li>\n",
"\t<li>'S18.media_T_2'</li>\n",
"\t<li>'S19.media_T_2'</li>\n",
"\t<li>'S1.media_T_2'</li>\n",
"\t<li>'S20.media_T_2'</li>\n",
"\t<li>'S2.media_T_2'</li>\n",
"\t<li>'S3.media_T_2'</li>\n",
"\t<li>'S4.media_T_2'</li>\n",
"\t<li>'S5.media_T_2'</li>\n",
"\t<li>'S6.media_T_2'</li>\n",
"\t<li>'S7.media_T_2'</li>\n",
"\t<li>'S8.media_T_2'</li>\n",
"\t<li>'S9.media_T_2'</li>\n",
"\t<li>'S10.min_T_2'</li>\n",
"\t<li>'S11.min_T_2'</li>\n",
"\t<li>'S12.min_T_2'</li>\n",
"\t<li>'S13.min_T_2'</li>\n",
"\t<li>'S14.min_T_2'</li>\n",
"\t<li>'S15.min_T_2'</li>\n",
"\t<li>'S16.min_T_2'</li>\n",
"\t<li>'S17.min_T_2'</li>\n",
"\t<li>'S18.min_T_2'</li>\n",
"\t<li>'S19.min_T_2'</li>\n",
"\t<li>'S1.min_T_2'</li>\n",
"\t<li>'S20.min_T_2'</li>\n",
"\t<li>'S2.min_T_2'</li>\n",
"\t<li>'S3.min_T_2'</li>\n",
"\t<li>'S4.min_T_2'</li>\n",
"\t<li>'S5.min_T_2'</li>\n",
"\t<li>'S6.min_T_2'</li>\n",
"\t<li>'S7.min_T_2'</li>\n",
"\t<li>'S8.min_T_2'</li>\n",
"\t<li>'S9.min_T_2'</li>\n",
"\t<li>'S10.15hs_T_2'</li>\n",
"\t<li>'S11.15hs_T_2'</li>\n",
"\t<li>'S12.15hs_T_2'</li>\n",
"\t<li>'S13.15hs_T_2'</li>\n",
"\t<li>'S14.15hs_T_2'</li>\n",
"\t<li>'S15.15hs_T_2'</li>\n",
"\t<li>'S16.15hs_T_2'</li>\n",
"\t<li>'S17.15hs_T_2'</li>\n",
"\t<li>'S18.15hs_T_2'</li>\n",
"\t<li>'S19.15hs_T_2'</li>\n",
"\t<li>'S1.15hs_T_2'</li>\n",
"\t<li>'S20.15hs_T_2'</li>\n",
"\t<li>'S2.15hs_T_2'</li>\n",
"\t<li>'S3.15hs_T_2'</li>\n",
"\t<li>'S4.15hs_T_2'</li>\n",
"\t<li>'S5.15hs_T_2'</li>\n",
"\t<li>'S6.15hs_T_2'</li>\n",
"\t<li>'S7.15hs_T_2'</li>\n",
"\t<li>'S8.15hs_T_2'</li>\n",
"\t<li>'S9.15hs_T_2'</li>\n",
"\t<li>'S10.12hs_T_2'</li>\n",
"\t<li>'S11.12hs_T_2'</li>\n",
"\t<li>'S12.12hs_T_2'</li>\n",
"\t<li>'S13.12hs_T_2'</li>\n",
"\t<li>'S14.12hs_T_2'</li>\n",
"\t<li>'S15.12hs_T_2'</li>\n",
"\t<li>'S16.12hs_T_2'</li>\n",
"\t<li>'S17.12hs_T_2'</li>\n",
"\t<li>'S18.12hs_T_2'</li>\n",
"\t<li>'S19.12hs_T_2'</li>\n",
"\t<li>'S1.12hs_T_2'</li>\n",
"\t<li>'S20.12hs_T_2'</li>\n",
"\t<li>'S2.12hs_T_2'</li>\n",
"\t<li>'S3.12hs_T_2'</li>\n",
"\t<li>'S4.12hs_T_2'</li>\n",
"\t<li>'S5.12hs_T_2'</li>\n",
"\t<li>'S6.12hs_T_2'</li>\n",
"\t<li>'S7.12hs_T_2'</li>\n",
"\t<li>'S8.12hs_T_2'</li>\n",
"\t<li>'S9.12hs_T_2'</li>\n",
"\t<li>'S10.18hs_T_2'</li>\n",
"\t<li>'S11.18hs_T_2'</li>\n",
"\t<li>'S12.18hs_T_2'</li>\n",
"\t<li>'S13.18hs_T_2'</li>\n",
"\t<li>'S14.18hs_T_2'</li>\n",
"\t<li>'S15.18hs_T_2'</li>\n",
"\t<li>'S16.18hs_T_2'</li>\n",
"\t<li>'S17.18hs_T_2'</li>\n",
"\t<li>'S18.18hs_T_2'</li>\n",
"\t<li>'S19.18hs_T_2'</li>\n",
"\t<li>'S1.18hs_T_2'</li>\n",
"\t<li>'S20.18hs_T_2'</li>\n",
"\t<li>'S2.18hs_T_2'</li>\n",
"\t<li>'S3.18hs_T_2'</li>\n",
"\t<li>'S4.18hs_T_2'</li>\n",
"\t<li>'S5.18hs_T_2'</li>\n",
"\t<li>'S6.18hs_T_2'</li>\n",
"\t<li>'S7.18hs_T_2'</li>\n",
"\t<li>'S8.18hs_T_2'</li>\n",
"\t<li>'S9.18hs_T_2'</li>\n",
"\t<li>'Est.humedad_min_T_2'</li>\n",
"\t<li>'Est.humedad_med_T_2'</li>\n",
"\t<li>'Est.humedad_max_T_2'</li>\n",
"\t<li>'Est.temp_min_T_2'</li>\n",
"\t<li>'Est.temp_max_T_2'</li>\n",
"\t<li>'Est.temp_med_T_2'</li>\n",
"\t<li>'S10.max_T_1'</li>\n",
"\t<li>'S11.max_T_1'</li>\n",
"\t<li>'S12.max_T_1'</li>\n",
"\t<li>'S13.max_T_1'</li>\n",
"\t<li>'S14.max_T_1'</li>\n",
"\t<li>'S15.max_T_1'</li>\n",
"\t<li>'S16.max_T_1'</li>\n",
"\t<li>'S17.max_T_1'</li>\n",
"\t<li>'S18.max_T_1'</li>\n",
"\t<li>'S19.max_T_1'</li>\n",
"\t<li>'S1.max_T_1'</li>\n",
"\t<li>'S20.max_T_1'</li>\n",
"\t<li>'S2.max_T_1'</li>\n",
"\t<li>'S3.max_T_1'</li>\n",
"\t<li>'S4.max_T_1'</li>\n",
"\t<li>'S5.max_T_1'</li>\n",
"\t<li>'S6.max_T_1'</li>\n",
"\t<li>'S7.max_T_1'</li>\n",
"\t<li>'S8.max_T_1'</li>\n",
"\t<li>'S9.max_T_1'</li>\n",
"\t<li>'S10.media_T_1'</li>\n",
"\t<li>'S11.media_T_1'</li>\n",
"\t<li>'S12.media_T_1'</li>\n",
"\t<li>'S13.media_T_1'</li>\n",
"\t<li>'S14.media_T_1'</li>\n",
"\t<li>'S15.media_T_1'</li>\n",
"\t<li>'S16.media_T_1'</li>\n",
"\t<li>'S17.media_T_1'</li>\n",
"\t<li>'S18.media_T_1'</li>\n",
"\t<li>'S19.media_T_1'</li>\n",
"\t<li>'S1.media_T_1'</li>\n",
"\t<li>'S20.media_T_1'</li>\n",
"\t<li>'S2.media_T_1'</li>\n",
"\t<li>'S3.media_T_1'</li>\n",
"\t<li>'S4.media_T_1'</li>\n",
"\t<li>'S5.media_T_1'</li>\n",
"\t<li>'S6.media_T_1'</li>\n",
"\t<li>'S7.media_T_1'</li>\n",
"\t<li>'S8.media_T_1'</li>\n",
"\t<li>'S9.media_T_1'</li>\n",
"\t<li>'S10.min_T_1'</li>\n",
"\t<li>'S11.min_T_1'</li>\n",
"\t<li>'S12.min_T_1'</li>\n",
"\t<li>'S13.min_T_1'</li>\n",
"\t<li>'S14.min_T_1'</li>\n",
"\t<li>'S15.min_T_1'</li>\n",
"\t<li>'S16.min_T_1'</li>\n",
"\t<li>'S17.min_T_1'</li>\n",
"\t<li>'S18.min_T_1'</li>\n",
"\t<li>'S19.min_T_1'</li>\n",
"\t<li>'S1.min_T_1'</li>\n",
"\t<li>'S20.min_T_1'</li>\n",
"\t<li>'S2.min_T_1'</li>\n",
"\t<li>'S3.min_T_1'</li>\n",
"\t<li>'S4.min_T_1'</li>\n",
"\t<li>'S5.min_T_1'</li>\n",
"\t<li>'S6.min_T_1'</li>\n",
"\t<li>'S7.min_T_1'</li>\n",
"\t<li>'S8.min_T_1'</li>\n",
"\t<li>'S9.min_T_1'</li>\n",
"\t<li>'S10.15hs_T_1'</li>\n",
"\t<li>'S11.15hs_T_1'</li>\n",
"\t<li>'S12.15hs_T_1'</li>\n",
"\t<li>'S13.15hs_T_1'</li>\n",
"\t<li>'S14.15hs_T_1'</li>\n",
"\t<li>'S15.15hs_T_1'</li>\n",
"\t<li>'S16.15hs_T_1'</li>\n",
"\t<li>'S17.15hs_T_1'</li>\n",
"\t<li>'S18.15hs_T_1'</li>\n",
"\t<li>'S19.15hs_T_1'</li>\n",
"\t<li>'S1.15hs_T_1'</li>\n",
"\t<li>'S20.15hs_T_1'</li>\n",
"\t<li>'S2.15hs_T_1'</li>\n",
"\t<li>'S3.15hs_T_1'</li>\n",
"\t<li>'S4.15hs_T_1'</li>\n",
"\t<li>'S5.15hs_T_1'</li>\n",
"\t<li>'S6.15hs_T_1'</li>\n",
"\t<li>'S7.15hs_T_1'</li>\n",
"\t<li>'S8.15hs_T_1'</li>\n",
"\t<li>'S9.15hs_T_1'</li>\n",
"\t<li>'S10.12hs_T_1'</li>\n",
"\t<li>'S11.12hs_T_1'</li>\n",
"\t<li>'S12.12hs_T_1'</li>\n",
"\t<li>'S13.12hs_T_1'</li>\n",
"\t<li>'S14.12hs_T_1'</li>\n",
"\t<li>'S15.12hs_T_1'</li>\n",
"\t<li>'S16.12hs_T_1'</li>\n",
"\t<li>'S17.12hs_T_1'</li>\n",
"\t<li>'S18.12hs_T_1'</li>\n",
"\t<li>'S19.12hs_T_1'</li>\n",
"\t<li>'S1.12hs_T_1'</li>\n",
"\t<li>'S20.12hs_T_1'</li>\n",
"\t<li>'S2.12hs_T_1'</li>\n",
"\t<li>'S3.12hs_T_1'</li>\n",
"\t<li>'S4.12hs_T_1'</li>\n",
"\t<li>'S5.12hs_T_1'</li>\n",
"\t<li>'S6.12hs_T_1'</li>\n",
"\t<li>'S7.12hs_T_1'</li>\n",
"\t<li>'S8.12hs_T_1'</li>\n",
"\t<li>'S9.12hs_T_1'</li>\n",
"\t<li>'S10.18hs_T_1'</li>\n",
"\t<li>'S11.18hs_T_1'</li>\n",
"\t<li>'S12.18hs_T_1'</li>\n",
"\t<li>'S13.18hs_T_1'</li>\n",
"\t<li>'S14.18hs_T_1'</li>\n",
"\t<li>'S15.18hs_T_1'</li>\n",
"\t<li>'S16.18hs_T_1'</li>\n",
"\t<li>'S17.18hs_T_1'</li>\n",
"\t<li>'S18.18hs_T_1'</li>\n",
"\t<li>'S19.18hs_T_1'</li>\n",
"\t<li>'S1.18hs_T_1'</li>\n",
"\t<li>'S20.18hs_T_1'</li>\n",
"\t<li>'S2.18hs_T_1'</li>\n",
"\t<li>'S3.18hs_T_1'</li>\n",
"\t<li>'S4.18hs_T_1'</li>\n",
"\t<li>'S5.18hs_T_1'</li>\n",
"\t<li>'S6.18hs_T_1'</li>\n",
"\t<li>'S7.18hs_T_1'</li>\n",
"\t<li>'S8.18hs_T_1'</li>\n",
"\t<li>'S9.18hs_T_1'</li>\n",
"\t<li>'Est.humedad_min_T_1'</li>\n",
"\t<li>'Est.humedad_med_T_1'</li>\n",
"\t<li>'Est.humedad_max_T_1'</li>\n",
"\t<li>'Est.temp_min_T_1'</li>\n",
"\t<li>'Est.temp_max_T_1'</li>\n",
"\t<li>'Est.temp_med_T_1'</li>\n",
"\t<li>'S10.min_t'</li>\n",
"\t<li>'S11.min_t'</li>\n",
"\t<li>'S12.min_t'</li>\n",
"\t<li>'S13.min_t'</li>\n",
"\t<li>'S14.min_t'</li>\n",
"\t<li>'S15.min_t'</li>\n",
"\t<li>'S16.min_t'</li>\n",
"\t<li>'S18.min_t'</li>\n",
"\t<li>'S19.min_t'</li>\n",
"\t<li>'S1.min_t'</li>\n",
"\t<li>'S20.min_t'</li>\n",
"\t<li>'S2.min_t'</li>\n",
"\t<li>'S3.min_t'</li>\n",
"\t<li>'S4.min_t'</li>\n",
"\t<li>'S5.min_t'</li>\n",
"\t<li>'S6.min_t'</li>\n",
"\t<li>'S7.min_t'</li>\n",
"\t<li>'S8.min_t'</li>\n",
"\t<li>'S9.min_t'</li>\n",
"</ol>\n"
],
"text/latex": [
"\\begin{enumerate*}\n",
"\\item 'S10.max\\_T\\_2'\n",
"\\item 'S11.max\\_T\\_2'\n",
"\\item 'S12.max\\_T\\_2'\n",
"\\item 'S13.max\\_T\\_2'\n",
"\\item 'S14.max\\_T\\_2'\n",
"\\item 'S15.max\\_T\\_2'\n",
"\\item 'S16.max\\_T\\_2'\n",
"\\item 'S17.max\\_T\\_2'\n",
"\\item 'S18.max\\_T\\_2'\n",
"\\item 'S19.max\\_T\\_2'\n",
"\\item 'S1.max\\_T\\_2'\n",
"\\item 'S20.max\\_T\\_2'\n",
"\\item 'S2.max\\_T\\_2'\n",
"\\item 'S3.max\\_T\\_2'\n",
"\\item 'S4.max\\_T\\_2'\n",
"\\item 'S5.max\\_T\\_2'\n",
"\\item 'S6.max\\_T\\_2'\n",
"\\item 'S7.max\\_T\\_2'\n",
"\\item 'S8.max\\_T\\_2'\n",
"\\item 'S9.max\\_T\\_2'\n",
"\\item 'S10.media\\_T\\_2'\n",
"\\item 'S11.media\\_T\\_2'\n",
"\\item 'S12.media\\_T\\_2'\n",
"\\item 'S13.media\\_T\\_2'\n",
"\\item 'S14.media\\_T\\_2'\n",
"\\item 'S15.media\\_T\\_2'\n",
"\\item 'S16.media\\_T\\_2'\n",
"\\item 'S17.media\\_T\\_2'\n",
"\\item 'S18.media\\_T\\_2'\n",
"\\item 'S19.media\\_T\\_2'\n",
"\\item 'S1.media\\_T\\_2'\n",
"\\item 'S20.media\\_T\\_2'\n",
"\\item 'S2.media\\_T\\_2'\n",
"\\item 'S3.media\\_T\\_2'\n",
"\\item 'S4.media\\_T\\_2'\n",
"\\item 'S5.media\\_T\\_2'\n",
"\\item 'S6.media\\_T\\_2'\n",
"\\item 'S7.media\\_T\\_2'\n",
"\\item 'S8.media\\_T\\_2'\n",
"\\item 'S9.media\\_T\\_2'\n",
"\\item 'S10.min\\_T\\_2'\n",
"\\item 'S11.min\\_T\\_2'\n",
"\\item 'S12.min\\_T\\_2'\n",
"\\item 'S13.min\\_T\\_2'\n",
"\\item 'S14.min\\_T\\_2'\n",
"\\item 'S15.min\\_T\\_2'\n",
"\\item 'S16.min\\_T\\_2'\n",
"\\item 'S17.min\\_T\\_2'\n",
"\\item 'S18.min\\_T\\_2'\n",
"\\item 'S19.min\\_T\\_2'\n",
"\\item 'S1.min\\_T\\_2'\n",
"\\item 'S20.min\\_T\\_2'\n",
"\\item 'S2.min\\_T\\_2'\n",
"\\item 'S3.min\\_T\\_2'\n",
"\\item 'S4.min\\_T\\_2'\n",
"\\item 'S5.min\\_T\\_2'\n",
"\\item 'S6.min\\_T\\_2'\n",
"\\item 'S7.min\\_T\\_2'\n",
"\\item 'S8.min\\_T\\_2'\n",
"\\item 'S9.min\\_T\\_2'\n",
"\\item 'S10.15hs\\_T\\_2'\n",
"\\item 'S11.15hs\\_T\\_2'\n",
"\\item 'S12.15hs\\_T\\_2'\n",
"\\item 'S13.15hs\\_T\\_2'\n",
"\\item 'S14.15hs\\_T\\_2'\n",
"\\item 'S15.15hs\\_T\\_2'\n",
"\\item 'S16.15hs\\_T\\_2'\n",
"\\item 'S17.15hs\\_T\\_2'\n",
"\\item 'S18.15hs\\_T\\_2'\n",
"\\item 'S19.15hs\\_T\\_2'\n",
"\\item 'S1.15hs\\_T\\_2'\n",
"\\item 'S20.15hs\\_T\\_2'\n",
"\\item 'S2.15hs\\_T\\_2'\n",
"\\item 'S3.15hs\\_T\\_2'\n",
"\\item 'S4.15hs\\_T\\_2'\n",
"\\item 'S5.15hs\\_T\\_2'\n",
"\\item 'S6.15hs\\_T\\_2'\n",
"\\item 'S7.15hs\\_T\\_2'\n",
"\\item 'S8.15hs\\_T\\_2'\n",
"\\item 'S9.15hs\\_T\\_2'\n",
"\\item 'S10.12hs\\_T\\_2'\n",
"\\item 'S11.12hs\\_T\\_2'\n",
"\\item 'S12.12hs\\_T\\_2'\n",
"\\item 'S13.12hs\\_T\\_2'\n",
"\\item 'S14.12hs\\_T\\_2'\n",
"\\item 'S15.12hs\\_T\\_2'\n",
"\\item 'S16.12hs\\_T\\_2'\n",
"\\item 'S17.12hs\\_T\\_2'\n",
"\\item 'S18.12hs\\_T\\_2'\n",
"\\item 'S19.12hs\\_T\\_2'\n",
"\\item 'S1.12hs\\_T\\_2'\n",
"\\item 'S20.12hs\\_T\\_2'\n",
"\\item 'S2.12hs\\_T\\_2'\n",
"\\item 'S3.12hs\\_T\\_2'\n",
"\\item 'S4.12hs\\_T\\_2'\n",
"\\item 'S5.12hs\\_T\\_2'\n",
"\\item 'S6.12hs\\_T\\_2'\n",
"\\item 'S7.12hs\\_T\\_2'\n",
"\\item 'S8.12hs\\_T\\_2'\n",
"\\item 'S9.12hs\\_T\\_2'\n",
"\\item 'S10.18hs\\_T\\_2'\n",
"\\item 'S11.18hs\\_T\\_2'\n",
"\\item 'S12.18hs\\_T\\_2'\n",
"\\item 'S13.18hs\\_T\\_2'\n",
"\\item 'S14.18hs\\_T\\_2'\n",
"\\item 'S15.18hs\\_T\\_2'\n",
"\\item 'S16.18hs\\_T\\_2'\n",
"\\item 'S17.18hs\\_T\\_2'\n",
"\\item 'S18.18hs\\_T\\_2'\n",
"\\item 'S19.18hs\\_T\\_2'\n",
"\\item 'S1.18hs\\_T\\_2'\n",
"\\item 'S20.18hs\\_T\\_2'\n",
"\\item 'S2.18hs\\_T\\_2'\n",
"\\item 'S3.18hs\\_T\\_2'\n",
"\\item 'S4.18hs\\_T\\_2'\n",
"\\item 'S5.18hs\\_T\\_2'\n",
"\\item 'S6.18hs\\_T\\_2'\n",
"\\item 'S7.18hs\\_T\\_2'\n",
"\\item 'S8.18hs\\_T\\_2'\n",
"\\item 'S9.18hs\\_T\\_2'\n",
"\\item 'Est.humedad\\_min\\_T\\_2'\n",
"\\item 'Est.humedad\\_med\\_T\\_2'\n",
"\\item 'Est.humedad\\_max\\_T\\_2'\n",
"\\item 'Est.temp\\_min\\_T\\_2'\n",
"\\item 'Est.temp\\_max\\_T\\_2'\n",
"\\item 'Est.temp\\_med\\_T\\_2'\n",
"\\item 'S10.max\\_T\\_1'\n",
"\\item 'S11.max\\_T\\_1'\n",
"\\item 'S12.max\\_T\\_1'\n",
"\\item 'S13.max\\_T\\_1'\n",
"\\item 'S14.max\\_T\\_1'\n",
"\\item 'S15.max\\_T\\_1'\n",
"\\item 'S16.max\\_T\\_1'\n",
"\\item 'S17.max\\_T\\_1'\n",
"\\item 'S18.max\\_T\\_1'\n",
"\\item 'S19.max\\_T\\_1'\n",
"\\item 'S1.max\\_T\\_1'\n",
"\\item 'S20.max\\_T\\_1'\n",
"\\item 'S2.max\\_T\\_1'\n",
"\\item 'S3.max\\_T\\_1'\n",
"\\item 'S4.max\\_T\\_1'\n",
"\\item 'S5.max\\_T\\_1'\n",
"\\item 'S6.max\\_T\\_1'\n",
"\\item 'S7.max\\_T\\_1'\n",
"\\item 'S8.max\\_T\\_1'\n",
"\\item 'S9.max\\_T\\_1'\n",
"\\item 'S10.media\\_T\\_1'\n",
"\\item 'S11.media\\_T\\_1'\n",
"\\item 'S12.media\\_T\\_1'\n",
"\\item 'S13.media\\_T\\_1'\n",
"\\item 'S14.media\\_T\\_1'\n",
"\\item 'S15.media\\_T\\_1'\n",
"\\item 'S16.media\\_T\\_1'\n",
"\\item 'S17.media\\_T\\_1'\n",
"\\item 'S18.media\\_T\\_1'\n",
"\\item 'S19.media\\_T\\_1'\n",
"\\item 'S1.media\\_T\\_1'\n",
"\\item 'S20.media\\_T\\_1'\n",
"\\item 'S2.media\\_T\\_1'\n",
"\\item 'S3.media\\_T\\_1'\n",
"\\item 'S4.media\\_T\\_1'\n",
"\\item 'S5.media\\_T\\_1'\n",
"\\item 'S6.media\\_T\\_1'\n",
"\\item 'S7.media\\_T\\_1'\n",
"\\item 'S8.media\\_T\\_1'\n",
"\\item 'S9.media\\_T\\_1'\n",
"\\item 'S10.min\\_T\\_1'\n",
"\\item 'S11.min\\_T\\_1'\n",
"\\item 'S12.min\\_T\\_1'\n",
"\\item 'S13.min\\_T\\_1'\n",
"\\item 'S14.min\\_T\\_1'\n",
"\\item 'S15.min\\_T\\_1'\n",
"\\item 'S16.min\\_T\\_1'\n",
"\\item 'S17.min\\_T\\_1'\n",
"\\item 'S18.min\\_T\\_1'\n",
"\\item 'S19.min\\_T\\_1'\n",
"\\item 'S1.min\\_T\\_1'\n",
"\\item 'S20.min\\_T\\_1'\n",
"\\item 'S2.min\\_T\\_1'\n",
"\\item 'S3.min\\_T\\_1'\n",
"\\item 'S4.min\\_T\\_1'\n",
"\\item 'S5.min\\_T\\_1'\n",
"\\item 'S6.min\\_T\\_1'\n",
"\\item 'S7.min\\_T\\_1'\n",
"\\item 'S8.min\\_T\\_1'\n",
"\\item 'S9.min\\_T\\_1'\n",
"\\item 'S10.15hs\\_T\\_1'\n",
"\\item 'S11.15hs\\_T\\_1'\n",
"\\item 'S12.15hs\\_T\\_1'\n",
"\\item 'S13.15hs\\_T\\_1'\n",
"\\item 'S14.15hs\\_T\\_1'\n",
"\\item 'S15.15hs\\_T\\_1'\n",
"\\item 'S16.15hs\\_T\\_1'\n",
"\\item 'S17.15hs\\_T\\_1'\n",
"\\item 'S18.15hs\\_T\\_1'\n",
"\\item 'S19.15hs\\_T\\_1'\n",
"\\item 'S1.15hs\\_T\\_1'\n",
"\\item 'S20.15hs\\_T\\_1'\n",
"\\item 'S2.15hs\\_T\\_1'\n",
"\\item 'S3.15hs\\_T\\_1'\n",
"\\item 'S4.15hs\\_T\\_1'\n",
"\\item 'S5.15hs\\_T\\_1'\n",
"\\item 'S6.15hs\\_T\\_1'\n",
"\\item 'S7.15hs\\_T\\_1'\n",
"\\item 'S8.15hs\\_T\\_1'\n",
"\\item 'S9.15hs\\_T\\_1'\n",
"\\item 'S10.12hs\\_T\\_1'\n",
"\\item 'S11.12hs\\_T\\_1'\n",
"\\item 'S12.12hs\\_T\\_1'\n",
"\\item 'S13.12hs\\_T\\_1'\n",
"\\item 'S14.12hs\\_T\\_1'\n",
"\\item 'S15.12hs\\_T\\_1'\n",
"\\item 'S16.12hs\\_T\\_1'\n",
"\\item 'S17.12hs\\_T\\_1'\n",
"\\item 'S18.12hs\\_T\\_1'\n",
"\\item 'S19.12hs\\_T\\_1'\n",
"\\item 'S1.12hs\\_T\\_1'\n",
"\\item 'S20.12hs\\_T\\_1'\n",
"\\item 'S2.12hs\\_T\\_1'\n",
"\\item 'S3.12hs\\_T\\_1'\n",
"\\item 'S4.12hs\\_T\\_1'\n",
"\\item 'S5.12hs\\_T\\_1'\n",
"\\item 'S6.12hs\\_T\\_1'\n",
"\\item 'S7.12hs\\_T\\_1'\n",
"\\item 'S8.12hs\\_T\\_1'\n",
"\\item 'S9.12hs\\_T\\_1'\n",
"\\item 'S10.18hs\\_T\\_1'\n",
"\\item 'S11.18hs\\_T\\_1'\n",
"\\item 'S12.18hs\\_T\\_1'\n",
"\\item 'S13.18hs\\_T\\_1'\n",
"\\item 'S14.18hs\\_T\\_1'\n",
"\\item 'S15.18hs\\_T\\_1'\n",
"\\item 'S16.18hs\\_T\\_1'\n",
"\\item 'S17.18hs\\_T\\_1'\n",
"\\item 'S18.18hs\\_T\\_1'\n",
"\\item 'S19.18hs\\_T\\_1'\n",
"\\item 'S1.18hs\\_T\\_1'\n",
"\\item 'S20.18hs\\_T\\_1'\n",
"\\item 'S2.18hs\\_T\\_1'\n",
"\\item 'S3.18hs\\_T\\_1'\n",
"\\item 'S4.18hs\\_T\\_1'\n",
"\\item 'S5.18hs\\_T\\_1'\n",
"\\item 'S6.18hs\\_T\\_1'\n",
"\\item 'S7.18hs\\_T\\_1'\n",
"\\item 'S8.18hs\\_T\\_1'\n",
"\\item 'S9.18hs\\_T\\_1'\n",
"\\item 'Est.humedad\\_min\\_T\\_1'\n",
"\\item 'Est.humedad\\_med\\_T\\_1'\n",
"\\item 'Est.humedad\\_max\\_T\\_1'\n",
"\\item 'Est.temp\\_min\\_T\\_1'\n",
"\\item 'Est.temp\\_max\\_T\\_1'\n",
"\\item 'Est.temp\\_med\\_T\\_1'\n",
"\\item 'S10.min\\_t'\n",
"\\item 'S11.min\\_t'\n",
"\\item 'S12.min\\_t'\n",
"\\item 'S13.min\\_t'\n",
"\\item 'S14.min\\_t'\n",
"\\item 'S15.min\\_t'\n",
"\\item 'S16.min\\_t'\n",
"\\item 'S18.min\\_t'\n",
"\\item 'S19.min\\_t'\n",
"\\item 'S1.min\\_t'\n",
"\\item 'S20.min\\_t'\n",
"\\item 'S2.min\\_t'\n",
"\\item 'S3.min\\_t'\n",
"\\item 'S4.min\\_t'\n",
"\\item 'S5.min\\_t'\n",
"\\item 'S6.min\\_t'\n",
"\\item 'S7.min\\_t'\n",
"\\item 'S8.min\\_t'\n",
"\\item 'S9.min\\_t'\n",
"\\end{enumerate*}\n"
],
"text/markdown": [
"1. 'S10.max_T_2'\n",
"2. 'S11.max_T_2'\n",
"3. 'S12.max_T_2'\n",
"4. 'S13.max_T_2'\n",
"5. 'S14.max_T_2'\n",
"6. 'S15.max_T_2'\n",
"7. 'S16.max_T_2'\n",
"8. 'S17.max_T_2'\n",
"9. 'S18.max_T_2'\n",
"10. 'S19.max_T_2'\n",
"11. 'S1.max_T_2'\n",
"12. 'S20.max_T_2'\n",
"13. 'S2.max_T_2'\n",
"14. 'S3.max_T_2'\n",
"15. 'S4.max_T_2'\n",
"16. 'S5.max_T_2'\n",
"17. 'S6.max_T_2'\n",
"18. 'S7.max_T_2'\n",
"19. 'S8.max_T_2'\n",
"20. 'S9.max_T_2'\n",
"21. 'S10.media_T_2'\n",
"22. 'S11.media_T_2'\n",
"23. 'S12.media_T_2'\n",
"24. 'S13.media_T_2'\n",
"25. 'S14.media_T_2'\n",
"26. 'S15.media_T_2'\n",
"27. 'S16.media_T_2'\n",
"28. 'S17.media_T_2'\n",
"29. 'S18.media_T_2'\n",
"30. 'S19.media_T_2'\n",
"31. 'S1.media_T_2'\n",
"32. 'S20.media_T_2'\n",
"33. 'S2.media_T_2'\n",
"34. 'S3.media_T_2'\n",
"35. 'S4.media_T_2'\n",
"36. 'S5.media_T_2'\n",
"37. 'S6.media_T_2'\n",
"38. 'S7.media_T_2'\n",
"39. 'S8.media_T_2'\n",
"40. 'S9.media_T_2'\n",
"41. 'S10.min_T_2'\n",
"42. 'S11.min_T_2'\n",
"43. 'S12.min_T_2'\n",
"44. 'S13.min_T_2'\n",
"45. 'S14.min_T_2'\n",
"46. 'S15.min_T_2'\n",
"47. 'S16.min_T_2'\n",
"48. 'S17.min_T_2'\n",
"49. 'S18.min_T_2'\n",
"50. 'S19.min_T_2'\n",
"51. 'S1.min_T_2'\n",
"52. 'S20.min_T_2'\n",
"53. 'S2.min_T_2'\n",
"54. 'S3.min_T_2'\n",
"55. 'S4.min_T_2'\n",
"56. 'S5.min_T_2'\n",
"57. 'S6.min_T_2'\n",
"58. 'S7.min_T_2'\n",
"59. 'S8.min_T_2'\n",
"60. 'S9.min_T_2'\n",
"61. 'S10.15hs_T_2'\n",
"62. 'S11.15hs_T_2'\n",
"63. 'S12.15hs_T_2'\n",
"64. 'S13.15hs_T_2'\n",
"65. 'S14.15hs_T_2'\n",
"66. 'S15.15hs_T_2'\n",
"67. 'S16.15hs_T_2'\n",
"68. 'S17.15hs_T_2'\n",
"69. 'S18.15hs_T_2'\n",
"70. 'S19.15hs_T_2'\n",
"71. 'S1.15hs_T_2'\n",
"72. 'S20.15hs_T_2'\n",
"73. 'S2.15hs_T_2'\n",
"74. 'S3.15hs_T_2'\n",
"75. 'S4.15hs_T_2'\n",
"76. 'S5.15hs_T_2'\n",
"77. 'S6.15hs_T_2'\n",
"78. 'S7.15hs_T_2'\n",
"79. 'S8.15hs_T_2'\n",
"80. 'S9.15hs_T_2'\n",
"81. 'S10.12hs_T_2'\n",
"82. 'S11.12hs_T_2'\n",
"83. 'S12.12hs_T_2'\n",
"84. 'S13.12hs_T_2'\n",
"85. 'S14.12hs_T_2'\n",
"86. 'S15.12hs_T_2'\n",
"87. 'S16.12hs_T_2'\n",
"88. 'S17.12hs_T_2'\n",
"89. 'S18.12hs_T_2'\n",
"90. 'S19.12hs_T_2'\n",
"91. 'S1.12hs_T_2'\n",
"92. 'S20.12hs_T_2'\n",
"93. 'S2.12hs_T_2'\n",
"94. 'S3.12hs_T_2'\n",
"95. 'S4.12hs_T_2'\n",
"96. 'S5.12hs_T_2'\n",
"97. 'S6.12hs_T_2'\n",
"98. 'S7.12hs_T_2'\n",
"99. 'S8.12hs_T_2'\n",
"100. 'S9.12hs_T_2'\n",
"101. 'S10.18hs_T_2'\n",
"102. 'S11.18hs_T_2'\n",
"103. 'S12.18hs_T_2'\n",
"104. 'S13.18hs_T_2'\n",
"105. 'S14.18hs_T_2'\n",
"106. 'S15.18hs_T_2'\n",
"107. 'S16.18hs_T_2'\n",
"108. 'S17.18hs_T_2'\n",
"109. 'S18.18hs_T_2'\n",
"110. 'S19.18hs_T_2'\n",
"111. 'S1.18hs_T_2'\n",
"112. 'S20.18hs_T_2'\n",
"113. 'S2.18hs_T_2'\n",
"114. 'S3.18hs_T_2'\n",
"115. 'S4.18hs_T_2'\n",
"116. 'S5.18hs_T_2'\n",
"117. 'S6.18hs_T_2'\n",
"118. 'S7.18hs_T_2'\n",
"119. 'S8.18hs_T_2'\n",
"120. 'S9.18hs_T_2'\n",
"121. 'Est.humedad_min_T_2'\n",
"122. 'Est.humedad_med_T_2'\n",
"123. 'Est.humedad_max_T_2'\n",
"124. 'Est.temp_min_T_2'\n",
"125. 'Est.temp_max_T_2'\n",
"126. 'Est.temp_med_T_2'\n",
"127. 'S10.max_T_1'\n",
"128. 'S11.max_T_1'\n",
"129. 'S12.max_T_1'\n",
"130. 'S13.max_T_1'\n",
"131. 'S14.max_T_1'\n",
"132. 'S15.max_T_1'\n",
"133. 'S16.max_T_1'\n",
"134. 'S17.max_T_1'\n",
"135. 'S18.max_T_1'\n",
"136. 'S19.max_T_1'\n",
"137. 'S1.max_T_1'\n",
"138. 'S20.max_T_1'\n",
"139. 'S2.max_T_1'\n",
"140. 'S3.max_T_1'\n",
"141. 'S4.max_T_1'\n",
"142. 'S5.max_T_1'\n",
"143. 'S6.max_T_1'\n",
"144. 'S7.max_T_1'\n",
"145. 'S8.max_T_1'\n",
"146. 'S9.max_T_1'\n",
"147. 'S10.media_T_1'\n",
"148. 'S11.media_T_1'\n",
"149. 'S12.media_T_1'\n",
"150. 'S13.media_T_1'\n",
"151. 'S14.media_T_1'\n",
"152. 'S15.media_T_1'\n",
"153. 'S16.media_T_1'\n",
"154. 'S17.media_T_1'\n",
"155. 'S18.media_T_1'\n",
"156. 'S19.media_T_1'\n",
"157. 'S1.media_T_1'\n",
"158. 'S20.media_T_1'\n",
"159. 'S2.media_T_1'\n",
"160. 'S3.media_T_1'\n",
"161. 'S4.media_T_1'\n",
"162. 'S5.media_T_1'\n",
"163. 'S6.media_T_1'\n",
"164. 'S7.media_T_1'\n",
"165. 'S8.media_T_1'\n",
"166. 'S9.media_T_1'\n",
"167. 'S10.min_T_1'\n",
"168. 'S11.min_T_1'\n",
"169. 'S12.min_T_1'\n",
"170. 'S13.min_T_1'\n",
"171. 'S14.min_T_1'\n",
"172. 'S15.min_T_1'\n",
"173. 'S16.min_T_1'\n",
"174. 'S17.min_T_1'\n",
"175. 'S18.min_T_1'\n",
"176. 'S19.min_T_1'\n",
"177. 'S1.min_T_1'\n",
"178. 'S20.min_T_1'\n",
"179. 'S2.min_T_1'\n",
"180. 'S3.min_T_1'\n",
"181. 'S4.min_T_1'\n",
"182. 'S5.min_T_1'\n",
"183. 'S6.min_T_1'\n",
"184. 'S7.min_T_1'\n",
"185. 'S8.min_T_1'\n",
"186. 'S9.min_T_1'\n",
"187. 'S10.15hs_T_1'\n",
"188. 'S11.15hs_T_1'\n",
"189. 'S12.15hs_T_1'\n",
"190. 'S13.15hs_T_1'\n",
"191. 'S14.15hs_T_1'\n",
"192. 'S15.15hs_T_1'\n",
"193. 'S16.15hs_T_1'\n",
"194. 'S17.15hs_T_1'\n",
"195. 'S18.15hs_T_1'\n",
"196. 'S19.15hs_T_1'\n",
"197. 'S1.15hs_T_1'\n",
"198. 'S20.15hs_T_1'\n",
"199. 'S2.15hs_T_1'\n",
"200. 'S3.15hs_T_1'\n",
"201. 'S4.15hs_T_1'\n",
"202. 'S5.15hs_T_1'\n",
"203. 'S6.15hs_T_1'\n",
"204. 'S7.15hs_T_1'\n",
"205. 'S8.15hs_T_1'\n",
"206. 'S9.15hs_T_1'\n",
"207. 'S10.12hs_T_1'\n",
"208. 'S11.12hs_T_1'\n",
"209. 'S12.12hs_T_1'\n",
"210. 'S13.12hs_T_1'\n",
"211. 'S14.12hs_T_1'\n",
"212. 'S15.12hs_T_1'\n",
"213. 'S16.12hs_T_1'\n",
"214. 'S17.12hs_T_1'\n",
"215. 'S18.12hs_T_1'\n",
"216. 'S19.12hs_T_1'\n",
"217. 'S1.12hs_T_1'\n",
"218. 'S20.12hs_T_1'\n",
"219. 'S2.12hs_T_1'\n",
"220. 'S3.12hs_T_1'\n",
"221. 'S4.12hs_T_1'\n",
"222. 'S5.12hs_T_1'\n",
"223. 'S6.12hs_T_1'\n",
"224. 'S7.12hs_T_1'\n",
"225. 'S8.12hs_T_1'\n",
"226. 'S9.12hs_T_1'\n",
"227. 'S10.18hs_T_1'\n",
"228. 'S11.18hs_T_1'\n",
"229. 'S12.18hs_T_1'\n",
"230. 'S13.18hs_T_1'\n",
"231. 'S14.18hs_T_1'\n",
"232. 'S15.18hs_T_1'\n",
"233. 'S16.18hs_T_1'\n",
"234. 'S17.18hs_T_1'\n",
"235. 'S18.18hs_T_1'\n",
"236. 'S19.18hs_T_1'\n",
"237. 'S1.18hs_T_1'\n",
"238. 'S20.18hs_T_1'\n",
"239. 'S2.18hs_T_1'\n",
"240. 'S3.18hs_T_1'\n",
"241. 'S4.18hs_T_1'\n",
"242. 'S5.18hs_T_1'\n",
"243. 'S6.18hs_T_1'\n",
"244. 'S7.18hs_T_1'\n",
"245. 'S8.18hs_T_1'\n",
"246. 'S9.18hs_T_1'\n",
"247. 'Est.humedad_min_T_1'\n",
"248. 'Est.humedad_med_T_1'\n",
"249. 'Est.humedad_max_T_1'\n",
"250. 'Est.temp_min_T_1'\n",
"251. 'Est.temp_max_T_1'\n",
"252. 'Est.temp_med_T_1'\n",
"253. 'S10.min_t'\n",
"254. 'S11.min_t'\n",
"255. 'S12.min_t'\n",
"256. 'S13.min_t'\n",
"257. 'S14.min_t'\n",
"258. 'S15.min_t'\n",
"259. 'S16.min_t'\n",
"260. 'S18.min_t'\n",
"261. 'S19.min_t'\n",
"262. 'S1.min_t'\n",
"263. 'S20.min_t'\n",
"264. 'S2.min_t'\n",
"265. 'S3.min_t'\n",
"266. 'S4.min_t'\n",
"267. 'S5.min_t'\n",
"268. 'S6.min_t'\n",
"269. 'S7.min_t'\n",
"270. 'S8.min_t'\n",
"271. 'S9.min_t'\n",
"\n",
"\n"
],
"text/plain": [
" [1] \"S10.max_T_2\" \"S11.max_T_2\" \"S12.max_T_2\" \n",
" [4] \"S13.max_T_2\" \"S14.max_T_2\" \"S15.max_T_2\" \n",
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" [10] \"S19.max_T_2\" \"S1.max_T_2\" \"S20.max_T_2\" \n",
" [13] \"S2.max_T_2\" \"S3.max_T_2\" \"S4.max_T_2\" \n",
" [16] \"S5.max_T_2\" \"S6.max_T_2\" \"S7.max_T_2\" \n",
" [19] \"S8.max_T_2\" \"S9.max_T_2\" \"S10.media_T_2\" \n",
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" [40] \"S9.media_T_2\" \"S10.min_T_2\" \"S11.min_T_2\" \n",
" [43] \"S12.min_T_2\" \"S13.min_T_2\" \"S14.min_T_2\" \n",
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" [94] \"S3.12hs_T_2\" \"S4.12hs_T_2\" \"S5.12hs_T_2\" \n",
" [97] \"S6.12hs_T_2\" \"S7.12hs_T_2\" \"S8.12hs_T_2\" \n",
"[100] \"S9.12hs_T_2\" \"S10.18hs_T_2\" \"S11.18hs_T_2\" \n",
"[103] \"S12.18hs_T_2\" \"S13.18hs_T_2\" \"S14.18hs_T_2\" \n",
"[106] \"S15.18hs_T_2\" \"S16.18hs_T_2\" \"S17.18hs_T_2\" \n",
"[109] \"S18.18hs_T_2\" \"S19.18hs_T_2\" \"S1.18hs_T_2\" \n",
"[112] \"S20.18hs_T_2\" \"S2.18hs_T_2\" \"S3.18hs_T_2\" \n",
"[115] \"S4.18hs_T_2\" \"S5.18hs_T_2\" \"S6.18hs_T_2\" \n",
"[118] \"S7.18hs_T_2\" \"S8.18hs_T_2\" \"S9.18hs_T_2\" \n",
"[121] \"Est.humedad_min_T_2\" \"Est.humedad_med_T_2\" \"Est.humedad_max_T_2\"\n",
"[124] \"Est.temp_min_T_2\" \"Est.temp_max_T_2\" \"Est.temp_med_T_2\" \n",
"[127] \"S10.max_T_1\" \"S11.max_T_1\" \"S12.max_T_1\" \n",
"[130] \"S13.max_T_1\" \"S14.max_T_1\" \"S15.max_T_1\" \n",
"[133] \"S16.max_T_1\" \"S17.max_T_1\" \"S18.max_T_1\" \n",
"[136] \"S19.max_T_1\" \"S1.max_T_1\" \"S20.max_T_1\" \n",
"[139] \"S2.max_T_1\" \"S3.max_T_1\" \"S4.max_T_1\" \n",
"[142] \"S5.max_T_1\" \"S6.max_T_1\" \"S7.max_T_1\" \n",
"[145] \"S8.max_T_1\" \"S9.max_T_1\" \"S10.media_T_1\" \n",
"[148] \"S11.media_T_1\" \"S12.media_T_1\" \"S13.media_T_1\" \n",
"[151] \"S14.media_T_1\" \"S15.media_T_1\" \"S16.media_T_1\" \n",
"[154] \"S17.media_T_1\" \"S18.media_T_1\" \"S19.media_T_1\" \n",
"[157] \"S1.media_T_1\" \"S20.media_T_1\" \"S2.media_T_1\" \n",
"[160] \"S3.media_T_1\" \"S4.media_T_1\" \"S5.media_T_1\" \n",
"[163] \"S6.media_T_1\" \"S7.media_T_1\" \"S8.media_T_1\" \n",
"[166] \"S9.media_T_1\" \"S10.min_T_1\" \"S11.min_T_1\" \n",
"[169] \"S12.min_T_1\" \"S13.min_T_1\" \"S14.min_T_1\" \n",
"[172] \"S15.min_T_1\" \"S16.min_T_1\" \"S17.min_T_1\" \n",
"[175] \"S18.min_T_1\" \"S19.min_T_1\" \"S1.min_T_1\" \n",
"[178] \"S20.min_T_1\" \"S2.min_T_1\" \"S3.min_T_1\" \n",
"[181] \"S4.min_T_1\" \"S5.min_T_1\" \"S6.min_T_1\" \n",
"[184] \"S7.min_T_1\" \"S8.min_T_1\" \"S9.min_T_1\" \n",
"[187] \"S10.15hs_T_1\" \"S11.15hs_T_1\" \"S12.15hs_T_1\" \n",
"[190] \"S13.15hs_T_1\" \"S14.15hs_T_1\" \"S15.15hs_T_1\" \n",
"[193] \"S16.15hs_T_1\" \"S17.15hs_T_1\" \"S18.15hs_T_1\" \n",
"[196] \"S19.15hs_T_1\" \"S1.15hs_T_1\" \"S20.15hs_T_1\" \n",
"[199] \"S2.15hs_T_1\" \"S3.15hs_T_1\" \"S4.15hs_T_1\" \n",
"[202] \"S5.15hs_T_1\" \"S6.15hs_T_1\" \"S7.15hs_T_1\" \n",
"[205] \"S8.15hs_T_1\" \"S9.15hs_T_1\" \"S10.12hs_T_1\" \n",
"[208] \"S11.12hs_T_1\" \"S12.12hs_T_1\" \"S13.12hs_T_1\" \n",
"[211] \"S14.12hs_T_1\" \"S15.12hs_T_1\" \"S16.12hs_T_1\" \n",
"[214] \"S17.12hs_T_1\" \"S18.12hs_T_1\" \"S19.12hs_T_1\" \n",
"[217] \"S1.12hs_T_1\" \"S20.12hs_T_1\" \"S2.12hs_T_1\" \n",
"[220] \"S3.12hs_T_1\" \"S4.12hs_T_1\" \"S5.12hs_T_1\" \n",
"[223] \"S6.12hs_T_1\" \"S7.12hs_T_1\" \"S8.12hs_T_1\" \n",
"[226] \"S9.12hs_T_1\" \"S10.18hs_T_1\" \"S11.18hs_T_1\" \n",
"[229] \"S12.18hs_T_1\" \"S13.18hs_T_1\" \"S14.18hs_T_1\" \n",
"[232] \"S15.18hs_T_1\" \"S16.18hs_T_1\" \"S17.18hs_T_1\" \n",
"[235] \"S18.18hs_T_1\" \"S19.18hs_T_1\" \"S1.18hs_T_1\" \n",
"[238] \"S20.18hs_T_1\" \"S2.18hs_T_1\" \"S3.18hs_T_1\" \n",
"[241] \"S4.18hs_T_1\" \"S5.18hs_T_1\" \"S6.18hs_T_1\" \n",
"[244] \"S7.18hs_T_1\" \"S8.18hs_T_1\" \"S9.18hs_T_1\" \n",
"[247] \"Est.humedad_min_T_1\" \"Est.humedad_med_T_1\" \"Est.humedad_max_T_1\"\n",
"[250] \"Est.temp_min_T_1\" \"Est.temp_max_T_1\" \"Est.temp_med_T_1\" \n",
"[253] \"S10.min_t\" \"S11.min_t\" \"S12.min_t\" \n",
"[256] \"S13.min_t\" \"S14.min_t\" \"S15.min_t\" \n",
"[259] \"S16.min_t\" \"S18.min_t\" \"S19.min_t\" \n",
"[262] \"S1.min_t\" \"S20.min_t\" \"S2.min_t\" \n",
"[265] \"S3.min_t\" \"S4.min_t\" \"S5.min_t\" \n",
"[268] \"S6.min_t\" \"S7.min_t\" \"S8.min_t\" \n",
"[271] \"S9.min_t\" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"#, descarto la primer columna que es el timestamp o fecha\n",
"sensores_T_2 <- sensores[1:(nrow(sensores)-2),-1] \n",
"sensores_T_1 <- sensores[2:(nrow(sensores)-1),-1] # no incluyo la primera fila\n",
"sensores_t <- sensores[3:nrow(sensores),] \n",
"\n",
"\n",
"# renombro las columnas \n",
"colnames(sensores_T_2) <- paste(colnames(sensores_T_2),\"_T_2\",sep=\"\")\n",
"colnames(sensores_T_1) <- paste(colnames(sensores_T_1),\"_T_1\",sep=\"\")\n",
"colnames(sensores_t) <- paste(colnames(sensores_t),\"_t\",sep=\"\")\n",
"\n",
"\n",
"#del tiempo presente solo me interesa la temperatura mínima\n",
"sensores_t <- sensores_t[,pred_sensores]\n",
"\n",
"# creo dataset de datos de T-2, T-1 y t\n",
"df <- cbind.data.frame(sensores_T_2,sensores_T_1,sensores_t)\n",
"\n",
"colnames(df)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"271"
],
"text/latex": [
"271"
],
"text/markdown": [
"271"
],
"text/plain": [
"[1] 271"
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"463"
],
"text/latex": [
"463"
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"text/markdown": [
"463"
],
"text/plain": [
"[1] 463"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# muestro cantidad de filas y columnas \n",
"ncol(df)\n",
"nrow(df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Separación de los datos en conjunto de entrenamiento y testeo"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"324.1"
],
"text/latex": [
"324.1"
],
"text/markdown": [
"324.1"
],
"text/plain": [
"[1] 324.1"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"463*.70"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"training.set = df[1:324, ] # This is training set to learn the parameters\n",
"test.set = df[325:nrow(df), ] # This is test set to give as evidence"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Plot de mínimas diarias del conjunto de testeo"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
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K3eH+u5mn1gILlb9Uknqv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WqnT6VjTLVR91ymxRfY+kQZ1LiZWO+krc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\nwP8DwYgRm6Gks/EAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x = seq(from=325,to=(325+nrow(test.set)-1),by=1)\n",
"plot(x, test.set[,\"S10.min_t\"],type=\"l\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Entrenando una Bayesian network con hill-climbing"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Armando la blacklist: arcos que no serán incluidos en la red bayesiana. No nos interesa relacionar las variables _t entre sí, \n",
"pues a priori sabemos que no contamos con dicha información"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"'data.frame':\t0 obs. of 2 variables:\n",
" $ from: atomic \n",
" ..- attr(*, \"levels\")= chr \"S10.min_t\" \"S11.min_t\" \"S12.min_t\" \"S13.min_t\" ...\n",
" $ to : atomic \n",
" ..- attr(*, \"levels\")= chr \"S10.min_t\" \"S11.min_t\" \"S12.min_t\" \"S13.min_t\" ...\n"
]
}
],
"source": [
"bl <- data.frame(from=character(),to=character(),stringsAsFactors=FALSE)\n",
"levels(bl$from) <- pred_sensores\n",
"levels(bl$to) <- pred_sensores\n",
"str(bl)\n",
"total <- length(pred_sensores)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" from to\n",
"1 S10.min_t S10.min_t\n",
"2 S10.min_t S11.min_t\n",
"3 S10.min_t S12.min_t\n",
"4 S10.min_t S13.min_t\n",
"5 S10.min_t S14.min_t\n",
"6 S10.min_t S15.min_t\n",
"7 S10.min_t S16.min_t\n",
"8 S10.min_t S18.min_t\n",
"9 S10.min_t S19.min_t\n",
"10 S10.min_t S1.min_t\n",
"11 S10.min_t S20.min_t\n",
"12 S10.min_t S2.min_t\n",
"13 S10.min_t S3.min_t\n",
"14 S10.min_t S4.min_t\n",
"15 S10.min_t S5.min_t\n",
"16 S10.min_t S6.min_t\n",
"17 S10.min_t S7.min_t\n",
"18 S10.min_t S8.min_t\n",
"19 S10.min_t S9.min_t\n",
"20 S10.min_t S10.min_t\n",
"21 S11.min_t S10.min_t\n",
"22 S12.min_t S10.min_t\n",
"23 S13.min_t S10.min_t\n",
"24 S14.min_t S10.min_t\n",
"25 S15.min_t S10.min_t\n",
"26 S16.min_t S10.min_t\n",
"27 S18.min_t S10.min_t\n",
"28 S19.min_t S10.min_t\n",
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]
}
],
"source": [
"\n",
"for(i in 1:total)\n",
"{\n",
" bl1 = data.frame(from = rep(pred_sensores[i],total), to = pred_sensores)\n",
" bl2 = data.frame(from = pred_sensores, to = rep(pred_sensores[i],total))\n",
" bl = rbind.data.frame(bl,bl1,bl2)\n",
"}\n",
"\n",
"print(bl)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Armaremos una whitelist, lista de arcos que si o sí tiene que tener la red bayesiana.\n",
"Consideraremos arcos dirigidos desde las variables _T_1 y _T_2 hacia t de un mismo sensor\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"'data.frame':\t0 obs. of 2 variables:\n",
" $ from: chr \n",
" $ to : chr \n"
]
}
],
"source": [
"wl <- data.frame(from=character(),to=character(),stringsAsFactors=FALSE)\n",
"#levels(bl$from) <- pred_sensores\n",
"#levels(bl$to) <- pred_sensores\n",
"str(wl)\n",
"total <- length(pred_sensores)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
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"\\item 'S1.12hs\\_T\\_2'\n",
"\\item 'S1.18hs\\_T\\_2'\n",
"\\item 'S1.max\\_T\\_1'\n",
"\\item 'S1.media\\_T\\_1'\n",
"\\item 'S1.min\\_T\\_1'\n",
"\\item 'S1.15hs\\_T\\_1'\n",
"\\item 'S1.12hs\\_T\\_1'\n",
"\\item 'S1.18hs\\_T\\_1'\n",
"\\end{enumerate*}\n"
],
"text/markdown": [
"1. 'S1.max_T_2'\n",
"2. 'S1.media_T_2'\n",
"3. 'S1.min_T_2'\n",
"4. 'S1.15hs_T_2'\n",
"5. 'S1.12hs_T_2'\n",
"6. 'S1.18hs_T_2'\n",
"7. 'S1.max_T_1'\n",
"8. 'S1.media_T_1'\n",
"9. 'S1.min_T_1'\n",
"10. 'S1.15hs_T_1'\n",
"11. 'S1.12hs_T_1'\n",
"12. 'S1.18hs_T_1'\n",
"\n",
"\n"
],
"text/plain": [
" [1] \"S1.max_T_2\" \"S1.media_T_2\" \"S1.min_T_2\" \"S1.15hs_T_2\" \"S1.12hs_T_2\" \n",
" [6] \"S1.18hs_T_2\" \"S1.max_T_1\" \"S1.media_T_1\" \"S1.min_T_1\" \"S1.15hs_T_1\" \n",
"[11] \"S1.12hs_T_1\" \"S1.18hs_T_1\" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"s <- unlist(strsplit(pred_sensores,split=\".\",fixed = TRUE))\n",
"sensors <- s[grep(\"S\",s)]\n",
"sensors\n",
"\n",
"v <- colnames(training.set)\n",
"\n",
"#vars_ejemplo <- v[grepl( sensors[1] , v)] # extraigo todas las variables relacionadas con sensor\n",
"#vars_ejemplo <- vars_ejemplo[-length(vars)] # quito la última variable min_t\n",
"#vars_ejemplo\n",
"\n",
"sensor <- unlist(strsplit(pred_sensores[10],split=\".\",fixed = TRUE))[1]\n",
"sensor\n",
"sensor <- paste(sensor,\".\",sep=\"\")\n",
"sensor\n",
"vars <- v[grepl( sensor, v, fixed = TRUE)] # extraigo todas las variables relacionadas con sensor\n",
"vars\n",
"vars <- vars[-length(vars)] # quito la última variable min_t\n",
"vars"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" from to\n",
"1 S10.max_T_2 S10.min_t\n",
"2 S10.media_T_2 S10.min_t\n",
"3 S10.min_T_2 S10.min_t\n",
"4 S10.15hs_T_2 S10.min_t\n",
"5 S10.12hs_T_2 S10.min_t\n",
"6 S10.18hs_T_2 S10.min_t\n",
"7 S10.max_T_1 S10.min_t\n",
"8 S10.media_T_1 S10.min_t\n",
"9 S10.min_T_1 S10.min_t\n",
"10 S10.15hs_T_1 S10.min_t\n",
"11 S10.12hs_T_1 S10.min_t\n",
"12 S10.18hs_T_1 S10.min_t\n",
"13 S11.max_T_2 S11.min_t\n",
"14 S11.media_T_2 S11.min_t\n",
"15 S11.min_T_2 S11.min_t\n",
"16 S11.15hs_T_2 S11.min_t\n",
"17 S11.12hs_T_2 S11.min_t\n",
"18 S11.18hs_T_2 S11.min_t\n",
"19 S11.max_T_1 S11.min_t\n",
"20 S11.media_T_1 S11.min_t\n",
"21 S11.min_T_1 S11.min_t\n",
"22 S11.15hs_T_1 S11.min_t\n",
"23 S11.12hs_T_1 S11.min_t\n",
"24 S11.18hs_T_1 S11.min_t\n",
"25 S12.max_T_2 S12.min_t\n",
"26 S12.media_T_2 S12.min_t\n",
"27 S12.min_T_2 S12.min_t\n",
"28 S12.15hs_T_2 S12.min_t\n",
"29 S12.12hs_T_2 S12.min_t\n",
"30 S12.18hs_T_2 S12.min_t\n",
"31 S12.max_T_1 S12.min_t\n",
"32 S12.media_T_1 S12.min_t\n",
"33 S12.min_T_1 S12.min_t\n",
"34 S12.15hs_T_1 S12.min_t\n",
"35 S12.12hs_T_1 S12.min_t\n",
"36 S12.18hs_T_1 S12.min_t\n",
"37 S13.max_T_2 S13.min_t\n",
"38 S13.media_T_2 S13.min_t\n",
"39 S13.min_T_2 S13.min_t\n",
"40 S13.15hs_T_2 S13.min_t\n",
"41 S13.12hs_T_2 S13.min_t\n",
"42 S13.18hs_T_2 S13.min_t\n",
"43 S13.max_T_1 S13.min_t\n",
"44 S13.media_T_1 S13.min_t\n",
"45 S13.min_T_1 S13.min_t\n",
"46 S13.15hs_T_1 S13.min_t\n",
"47 S13.12hs_T_1 S13.min_t\n",
"48 S13.18hs_T_1 S13.min_t\n",
"49 S14.max_T_2 S14.min_t\n",
"50 S14.media_T_2 S14.min_t\n",
"51 S14.min_T_2 S14.min_t\n",
"52 S14.15hs_T_2 S14.min_t\n",
"53 S14.12hs_T_2 S14.min_t\n",
"54 S14.18hs_T_2 S14.min_t\n",
"55 S14.max_T_1 S14.min_t\n",
"56 S14.media_T_1 S14.min_t\n",
"57 S14.min_T_1 S14.min_t\n",
"58 S14.15hs_T_1 S14.min_t\n",
"59 S14.12hs_T_1 S14.min_t\n",
"60 S14.18hs_T_1 S14.min_t\n",
"61 S15.max_T_2 S15.min_t\n",
"62 S15.media_T_2 S15.min_t\n",
"63 S15.min_T_2 S15.min_t\n",
"64 S15.15hs_T_2 S15.min_t\n",
"65 S15.12hs_T_2 S15.min_t\n",
"66 S15.18hs_T_2 S15.min_t\n",
"67 S15.max_T_1 S15.min_t\n",
"68 S15.media_T_1 S15.min_t\n",
"69 S15.min_T_1 S15.min_t\n",
"70 S15.15hs_T_1 S15.min_t\n",
"71 S15.12hs_T_1 S15.min_t\n",
"72 S15.18hs_T_1 S15.min_t\n",
"73 S16.max_T_2 S16.min_t\n",
"74 S16.media_T_2 S16.min_t\n",
"75 S16.min_T_2 S16.min_t\n",
"76 S16.15hs_T_2 S16.min_t\n",
"77 S16.12hs_T_2 S16.min_t\n",
"78 S16.18hs_T_2 S16.min_t\n",
"79 S16.max_T_1 S16.min_t\n",
"80 S16.media_T_1 S16.min_t\n",
"81 S16.min_T_1 S16.min_t\n",
"82 S16.15hs_T_1 S16.min_t\n",
"83 S16.12hs_T_1 S16.min_t\n",
"84 S16.18hs_T_1 S16.min_t\n",
"85 S18.max_T_2 S18.min_t\n",
"86 S18.media_T_2 S18.min_t\n",
"87 S18.min_T_2 S18.min_t\n",
"88 S18.15hs_T_2 S18.min_t\n",
"89 S18.12hs_T_2 S18.min_t\n",
"90 S18.18hs_T_2 S18.min_t\n",
"91 S18.max_T_1 S18.min_t\n",
"92 S18.media_T_1 S18.min_t\n",
"93 S18.min_T_1 S18.min_t\n",
"94 S18.15hs_T_1 S18.min_t\n",
"95 S18.12hs_T_1 S18.min_t\n",
"96 S18.18hs_T_1 S18.min_t\n",
"97 S19.max_T_2 S19.min_t\n",
"98 S19.media_T_2 S19.min_t\n",
"99 S19.min_T_2 S19.min_t\n",
"100 S19.15hs_T_2 S19.min_t\n",
"101 S19.12hs_T_2 S19.min_t\n",
"102 S19.18hs_T_2 S19.min_t\n",
"103 S19.max_T_1 S19.min_t\n",
"104 S19.media_T_1 S19.min_t\n",
"105 S19.min_T_1 S19.min_t\n",
"106 S19.15hs_T_1 S19.min_t\n",
"107 S19.12hs_T_1 S19.min_t\n",
"108 S19.18hs_T_1 S19.min_t\n",
"109 S1.max_T_2 S1.min_t\n",
"110 S1.media_T_2 S1.min_t\n",
"111 S1.min_T_2 S1.min_t\n",
"112 S1.15hs_T_2 S1.min_t\n",
"113 S1.12hs_T_2 S1.min_t\n",
"114 S1.18hs_T_2 S1.min_t\n",
"115 S1.max_T_1 S1.min_t\n",
"116 S1.media_T_1 S1.min_t\n",
"117 S1.min_T_1 S1.min_t\n",
"118 S1.15hs_T_1 S1.min_t\n",
"119 S1.12hs_T_1 S1.min_t\n",
"120 S1.18hs_T_1 S1.min_t\n",
"121 S20.max_T_2 S20.min_t\n",
"122 S20.media_T_2 S20.min_t\n",
"123 S20.min_T_2 S20.min_t\n",
"124 S20.15hs_T_2 S20.min_t\n",
"125 S20.12hs_T_2 S20.min_t\n",
"126 S20.18hs_T_2 S20.min_t\n",
"127 S20.max_T_1 S20.min_t\n",
"128 S20.media_T_1 S20.min_t\n",
"129 S20.min_T_1 S20.min_t\n",
"130 S20.15hs_T_1 S20.min_t\n",
"131 S20.12hs_T_1 S20.min_t\n",
"132 S20.18hs_T_1 S20.min_t\n",
"133 S2.max_T_2 S2.min_t\n",
"134 S2.media_T_2 S2.min_t\n",
"135 S2.min_T_2 S2.min_t\n",
"136 S2.15hs_T_2 S2.min_t\n",
"137 S2.12hs_T_2 S2.min_t\n",
"138 S2.18hs_T_2 S2.min_t\n",
"139 S2.max_T_1 S2.min_t\n",
"140 S2.media_T_1 S2.min_t\n",
"141 S2.min_T_1 S2.min_t\n",
"142 S2.15hs_T_1 S2.min_t\n",
"143 S2.12hs_T_1 S2.min_t\n",
"144 S2.18hs_T_1 S2.min_t\n",
"145 S3.max_T_2 S3.min_t\n",
"146 S3.media_T_2 S3.min_t\n",
"147 S3.min_T_2 S3.min_t\n",
"148 S3.15hs_T_2 S3.min_t\n",
"149 S3.12hs_T_2 S3.min_t\n",
"150 S3.18hs_T_2 S3.min_t\n",
"151 S3.max_T_1 S3.min_t\n",
"152 S3.media_T_1 S3.min_t\n",
"153 S3.min_T_1 S3.min_t\n",
"154 S3.15hs_T_1 S3.min_t\n",
"155 S3.12hs_T_1 S3.min_t\n",
"156 S3.18hs_T_1 S3.min_t\n",
"157 S4.max_T_2 S4.min_t\n",
"158 S4.media_T_2 S4.min_t\n",
"159 S4.min_T_2 S4.min_t\n",
"160 S4.15hs_T_2 S4.min_t\n",
"161 S4.12hs_T_2 S4.min_t\n",
"162 S4.18hs_T_2 S4.min_t\n",
"163 S4.max_T_1 S4.min_t\n",
"164 S4.media_T_1 S4.min_t\n",
"165 S4.min_T_1 S4.min_t\n",
"166 S4.15hs_T_1 S4.min_t\n",
"167 S4.12hs_T_1 S4.min_t\n",
"168 S4.18hs_T_1 S4.min_t\n",
"169 S5.max_T_2 S5.min_t\n",
"170 S5.media_T_2 S5.min_t\n",
"171 S5.min_T_2 S5.min_t\n",
"172 S5.15hs_T_2 S5.min_t\n",
"173 S5.12hs_T_2 S5.min_t\n",
"174 S5.18hs_T_2 S5.min_t\n",
"175 S5.max_T_1 S5.min_t\n",
"176 S5.media_T_1 S5.min_t\n",
"177 S5.min_T_1 S5.min_t\n",
"178 S5.15hs_T_1 S5.min_t\n",
"179 S5.12hs_T_1 S5.min_t\n",
"180 S5.18hs_T_1 S5.min_t\n",
"181 S6.max_T_2 S6.min_t\n",
"182 S6.media_T_2 S6.min_t\n",
"183 S6.min_T_2 S6.min_t\n",
"184 S6.15hs_T_2 S6.min_t\n",
"185 S6.12hs_T_2 S6.min_t\n",
"186 S6.18hs_T_2 S6.min_t\n",
"187 S6.max_T_1 S6.min_t\n",
"188 S6.media_T_1 S6.min_t\n",
"189 S6.min_T_1 S6.min_t\n",
"190 S6.15hs_T_1 S6.min_t\n",
"191 S6.12hs_T_1 S6.min_t\n",
"192 S6.18hs_T_1 S6.min_t\n",
"193 S7.max_T_2 S7.min_t\n",
"194 S7.media_T_2 S7.min_t\n",
"195 S7.min_T_2 S7.min_t\n",
"196 S7.15hs_T_2 S7.min_t\n",
"197 S7.12hs_T_2 S7.min_t\n",
"198 S7.18hs_T_2 S7.min_t\n",
"199 S7.max_T_1 S7.min_t\n",
"200 S7.media_T_1 S7.min_t\n",
"201 S7.min_T_1 S7.min_t\n",
"202 S7.15hs_T_1 S7.min_t\n",
"203 S7.12hs_T_1 S7.min_t\n",
"204 S7.18hs_T_1 S7.min_t\n",
"205 S8.max_T_2 S8.min_t\n",
"206 S8.media_T_2 S8.min_t\n",
"207 S8.min_T_2 S8.min_t\n",
"208 S8.15hs_T_2 S8.min_t\n",
"209 S8.12hs_T_2 S8.min_t\n",
"210 S8.18hs_T_2 S8.min_t\n",
"211 S8.max_T_1 S8.min_t\n",
"212 S8.media_T_1 S8.min_t\n",
"213 S8.min_T_1 S8.min_t\n",
"214 S8.15hs_T_1 S8.min_t\n",
"215 S8.12hs_T_1 S8.min_t\n",
"216 S8.18hs_T_1 S8.min_t\n",
"217 S9.max_T_2 S9.min_t\n",
"218 S9.media_T_2 S9.min_t\n",
"219 S9.min_T_2 S9.min_t\n",
"220 S9.15hs_T_2 S9.min_t\n",
"221 S9.12hs_T_2 S9.min_t\n",
"222 S9.18hs_T_2 S9.min_t\n",
"223 S9.max_T_1 S9.min_t\n",
"224 S9.media_T_1 S9.min_t\n",
"225 S9.min_T_1 S9.min_t\n",
"226 S9.15hs_T_1 S9.min_t\n",
"227 S9.12hs_T_1 S9.min_t\n",
"228 S9.18hs_T_1 S9.min_t\n"
]
}
],
"source": [
"\n",
"for(i in 1:total)\n",
"{\n",
" sensor <- unlist(strsplit(pred_sensores[i],split=\".\",fixed = TRUE))[1]\n",
" sensor <- paste(sensor,\".\",sep=\"\")\n",
" vars <- v[grepl( sensor, v, fixed = TRUE)] # extraigo todas las variables relacionadas con sensor\n",
" vars <- vars[-length(vars)] # quito la última variable min_t\n",
"\n",
" wl1 = data.frame(from = vars, to = pred_sensores[i])\n",
" wl = rbind.data.frame(wl,wl1)\n",
"}\n",
"print(wl)\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Time difference of 10.39911 mins"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"start_time <- Sys.time()\n",
"# learn BN structure on training set data , restart por defecto es 0\n",
"# modificar restart a 10 no hizo mucho efecto en los resultados de predicción\n",
"res = hc(training.set, whitelist=wl,blacklist = bl)\n",
"end_time <- Sys.time()\n",
"end_time - start_time"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Mostramos la estructura de la red bayesiana creada con hc"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\n",
" Bayesian network learned via Score-based methods\n",
"\n",
" model:\n",
" [S12.max_T_1][S13.max_T_1|S12.max_T_1][S14.max_T_1|S12.max_T_1:S13.max_T_1]\n",
" [S17.max_T_1|S12.max_T_1:S14.max_T_1][S14.15hs_T_1|S14.max_T_1]\n",
" [S18.max_T_1|S13.max_T_1:S14.max_T_1:S17.max_T_1]\n",
" [S2.max_T_1|S13.max_T_1:S17.max_T_1:S18.max_T_1]\n",
" [S11.max_T_1|S13.max_T_1:S14.max_T_1:S2.max_T_1]\n",
" [S15.max_T_1|S11.max_T_1:S12.max_T_1:S14.max_T_1:S17.max_T_1:S18.max_T_1]\n",
" [S9.max_T_1|S11.max_T_1:S12.max_T_1:S15.max_T_1:S2.max_T_1:S14.15hs_T_1]\n",
" [S19.max_T_1|S11.max_T_1:S12.max_T_1:S15.max_T_1:S9.max_T_1]\n",
" [S4.max_T_1|S11.max_T_1:S12.max_T_1:S15.max_T_1:S17.max_T_1:S19.max_T_1:S2.max_T_1:S9.max_T_1]\n",
" [S11.18hs_T_1|S19.max_T_1]\n",
" [S6.max_T_1|S11.max_T_1:S15.max_T_1:S18.max_T_1:S2.max_T_1:S4.max_T_1:S9.max_T_1:S14.15hs_T_1]\n",
" [S17.15hs_T_1|S14.max_T_1:S17.max_T_1:S19.max_T_1:S4.max_T_1:S14.15hs_T_1]\n",
" [S10.max_T_1|S12.max_T_1:S17.max_T_1:S2.max_T_1:S6.max_T_1]\n",
" [S7.max_T_1|S12.max_T_1:S13.max_T_1:S14.max_T_1:S6.max_T_1:S9.max_T_1]\n",
" [S16.18hs_T_1|S13.max_T_1:S18.max_T_1:S19.max_T_1:S4.max_T_1:S6.max_T_1:S11.18hs_T_1]\n",
" [S20.12hs_T_1|S10.max_T_1:S11.max_T_1:S14.max_T_1]\n",
" [S18.15hs_T_1|S14.max_T_1:S17.max_T_1:S18.max_T_1:S2.max_T_1:S14.15hs_T_1:S17.15hs_T_1:S20.12hs_T_1]\n",
" [S16.15hs_T_1|S10.max_T_1:S15.max_T_1:S19.max_T_1:S9.max_T_1:S14.15hs_T_1:S17.15hs_T_1:S18.15hs_T_1]\n",
" [S16.max_T_1|S11.max_T_1:S14.max_T_1:S15.max_T_1:S17.max_T_1:S18.max_T_1:S19.max_T_1:S4.max_T_1:S7.max_T_1:S14.15hs_T_1:S16.15hs_T_1:S17.15hs_T_1:S18.15hs_T_1]\n",
" [S19.18hs_T_1|S16.max_T_1:S17.max_T_1:S18.max_T_1:S19.max_T_1:S6.max_T_1:S11.18hs_T_1:S16.18hs_T_1]\n",
" [S19.15hs_T_1|S15.max_T_1:S16.max_T_1:S18.max_T_1:S19.max_T_1:S16.15hs_T_1:S18.15hs_T_1:S19.18hs_T_1]\n",
" [S6.18hs_T_1|S11.max_T_1:S6.max_T_1:S7.max_T_1:S11.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1]\n",
" [S11.15hs_T_1|S10.max_T_1:S11.max_T_1:S12.max_T_1:S15.max_T_1:S18.max_T_1:S19.max_T_1:S18.15hs_T_1:S19.15hs_T_1]\n",
" [S5.18hs_T_1|S11.15hs_T_1:S14.15hs_T_1:S11.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1:S6.18hs_T_1]\n",
" [S12.18hs_T_1|S13.max_T_1:S15.max_T_1:S18.max_T_1:S19.max_T_1:S11.18hs_T_1:S16.18hs_T_1:S5.18hs_T_1]\n",
" [S2.18hs_T_1|S11.18hs_T_1:S12.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1:S5.18hs_T_1:S6.18hs_T_1]\n",
" [S9.18hs_T_1|S6.max_T_1:S9.max_T_1:S19.15hs_T_1:S20.12hs_T_1:S11.18hs_T_1:S19.18hs_T_1:S2.18hs_T_1]\n",
" [S15.15hs_T_1|S10.max_T_1:S14.max_T_1:S15.max_T_1:S16.max_T_1:S18.max_T_1:S14.15hs_T_1:S19.15hs_T_1:S9.18hs_T_1]\n",
" [S10.18hs_T_1|S10.max_T_1:S14.max_T_1:S19.max_T_1:S4.max_T_1:S16.15hs_T_1:S17.15hs_T_1:S12.18hs_T_1:S19.18hs_T_1:S2.18hs_T_1:S6.18hs_T_1:S9.18hs_T_1]\n",
" [S9.15hs_T_1|S14.max_T_1:S15.max_T_1:S16.max_T_1:S9.max_T_1:S14.15hs_T_1:S15.15hs_T_1:S16.15hs_T_1:S17.15hs_T_1]\n",
" [S13.18hs_T_1|S11.max_T_1:S13.max_T_1:S6.max_T_1:S17.15hs_T_1:S19.15hs_T_1:S9.15hs_T_1:S10.18hs_T_1:S11.18hs_T_1:S12.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1]\n",
" [S4.18hs_T_1|S4.max_T_1:S6.max_T_1:S16.15hs_T_1:S13.18hs_T_1:S16.18hs_T_1:S2.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1]\n",
" [S3.18hs_T_1|S10.max_T_1:S18.max_T_1:S4.max_T_1:S7.max_T_1:S10.18hs_T_1:S13.18hs_T_1:S19.18hs_T_1:S2.18hs_T_1:S4.18hs_T_1:S6.18hs_T_1]\n",
" [S14.18hs_T_1|S14.max_T_1:S16.max_T_1:S7.max_T_1:S10.18hs_T_1:S11.18hs_T_1:S12.18hs_T_1:S13.18hs_T_1:S16.18hs_T_1:S2.18hs_T_1:S3.18hs_T_1:S6.18hs_T_1]\n",
" [S15.18hs_T_1|S11.max_T_1:S15.max_T_1:S7.max_T_1:S19.15hs_T_1:S9.15hs_T_1:S10.18hs_T_1:S11.18hs_T_1:S12.18hs_T_1:S13.18hs_T_1:S14.18hs_T_1:S5.18hs_T_1:S6.18hs_T_1:S9.18hs_T_1]\n",
" [S17.18hs_T_1|S16.max_T_1:S4.max_T_1:S15.15hs_T_1:S17.15hs_T_1:S10.18hs_T_1:S11.18hs_T_1:S13.18hs_T_1:S15.18hs_T_1:S2.18hs_T_1:S9.18hs_T_1]\n",
" [S18.18hs_T_1|S10.18hs_T_1:S11.18hs_T_1:S17.18hs_T_1:S19.18hs_T_1:S3.18hs_T_1:S5.18hs_T_1:S6.18hs_T_1:S9.18hs_T_1]\n",
" [S20.18hs_T_1|S11.18hs_T_1:S15.18hs_T_1:S18.18hs_T_1:S2.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1]\n",
" [S20.max_T_1|S11.max_T_1:S13.max_T_1:S14.max_T_1:S15.max_T_1:S18.max_T_1:S19.max_T_1:S2.max_T_1:S7.max_T_1:S16.15hs_T_1:S17.18hs_T_1:S18.18hs_T_1:S20.18hs_T_1:S2.18hs_T_1]\n",
" [S20.15hs_T_1|S11.max_T_1:S14.max_T_1:S19.max_T_1:S20.max_T_1:S6.max_T_1:S11.15hs_T_1:S14.15hs_T_1:S18.15hs_T_1:S9.15hs_T_1:S20.12hs_T_1]\n",
" [S2.15hs_T_1|S13.max_T_1:S2.max_T_1:S6.max_T_1:S7.max_T_1:S11.15hs_T_1:S17.15hs_T_1:S20.15hs_T_1:S9.15hs_T_1]\n",
" [S10.15hs_T_1|S10.max_T_1:S14.max_T_1:S15.max_T_1:S2.max_T_1:S11.15hs_T_1:S15.15hs_T_1:S16.15hs_T_1:S19.15hs_T_1:S20.15hs_T_1:S2.15hs_T_1:S9.15hs_T_1]\n",
" [S12.15hs_T_1|S10.max_T_1:S12.max_T_1:S13.max_T_1:S15.max_T_1:S4.max_T_1:S7.max_T_1:S10.15hs_T_1:S11.15hs_T_1:S15.15hs_T_1:S16.15hs_T_1:S19.15hs_T_1:S2.15hs_T_1:S9.15hs_T_1]\n",
" [S8.15hs_T_1|S10.15hs_T_1:S12.15hs_T_1:S2.15hs_T_1:S9.15hs_T_1]\n",
" [S1.18hs_T_1|S19.max_T_1:S12.15hs_T_1:S14.15hs_T_1:S15.15hs_T_1:S12.18hs_T_1:S18.18hs_T_1:S3.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1]\n",
" [S4.15hs_T_1|S12.max_T_1:S20.max_T_1:S2.max_T_1:S4.max_T_1:S16.15hs_T_1:S17.15hs_T_1:S20.15hs_T_1:S2.15hs_T_1:S8.15hs_T_1:S9.15hs_T_1:S3.18hs_T_1:S4.18hs_T_1]\n",
" [S2.12hs_T_1|S11.15hs_T_1:S12.15hs_T_1:S14.15hs_T_1:S15.15hs_T_1:S4.15hs_T_1:S20.12hs_T_1]\n",
" [S3.12hs_T_1|S10.max_T_1:S13.max_T_1:S16.max_T_1:S19.max_T_1:S20.max_T_1:S9.max_T_1:S14.15hs_T_1:S15.15hs_T_1:S20.12hs_T_1:S2.12hs_T_1]\n",
" [S9.12hs_T_1|S11.max_T_1:S19.max_T_1:S2.max_T_1:S9.max_T_1:S20.12hs_T_1:S2.12hs_T_1:S2.18hs_T_1:S3.18hs_T_1]\n",
" [S12.12hs_T_1|S18.max_T_1:S19.max_T_1:S12.15hs_T_1:S9.15hs_T_1:S20.12hs_T_1:S2.12hs_T_1:S9.12hs_T_1:S10.18hs_T_1:S12.18hs_T_1:S19.18hs_T_1]\n",
" [S4.12hs_T_1|S11.max_T_1:S19.max_T_1:S14.15hs_T_1:S15.15hs_T_1:S4.15hs_T_1:S8.15hs_T_1:S2.12hs_T_1:S3.12hs_T_1:S9.12hs_T_1:S14.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1:S4.18hs_T_1]\n",
" [S11.12hs_T_1|S11.15hs_T_1:S16.15hs_T_1:S18.15hs_T_1:S19.15hs_T_1:S12.12hs_T_1:S20.12hs_T_1:S4.12hs_T_1:S19.18hs_T_1:S20.18hs_T_1]\n",
" [S13.12hs_T_1|S12.12hs_T_1:S3.12hs_T_1:S4.12hs_T_1:S9.12hs_T_1]\n",
" [S7.12hs_T_1|S13.12hs_T_1:S20.12hs_T_1:S4.12hs_T_1]\n",
" [S7.15hs_T_1|S18.max_T_1:S2.max_T_1:S7.max_T_1:S10.15hs_T_1:S12.15hs_T_1:S17.15hs_T_1:S20.15hs_T_1:S4.15hs_T_1:S13.12hs_T_1:S3.12hs_T_1:S7.12hs_T_1:S12.18hs_T_1:S3.18hs_T_1]\n",
" [S6.15hs_T_1|S13.max_T_1:S18.max_T_1:S4.max_T_1:S6.max_T_1:S11.15hs_T_1:S19.15hs_T_1:S20.15hs_T_1:S2.15hs_T_1:S4.15hs_T_1:S7.15hs_T_1]\n",
" [S5.12hs_T_1|S19.max_T_1:S7.max_T_1:S2.15hs_T_1:S6.15hs_T_1:S7.15hs_T_1:S8.15hs_T_1:S2.12hs_T_1:S3.12hs_T_1:S4.12hs_T_1:S9.12hs_T_1]\n",
" [S17.media_T_1|S11.12hs_T_1:S2.12hs_T_1:S4.12hs_T_1:S5.12hs_T_1:S10.18hs_T_1:S11.18hs_T_1:S12.18hs_T_1:S15.18hs_T_1:S17.18hs_T_1:S1.18hs_T_1:S9.18hs_T_1]\n",
" [S14.12hs_T_1|S11.15hs_T_1:S14.15hs_T_1:S16.15hs_T_1:S8.15hs_T_1:S13.12hs_T_1:S20.12hs_T_1:S3.12hs_T_1:S5.12hs_T_1:S7.12hs_T_1:S9.12hs_T_1:S14.18hs_T_1:S6.18hs_T_1]\n",
" [S1.12hs_T_1|S13.max_T_1:S16.max_T_1:S19.max_T_1:S12.15hs_T_1:S16.15hs_T_1:S2.15hs_T_1:S7.15hs_T_1:S11.12hs_T_1:S3.12hs_T_1:S5.12hs_T_1:S7.12hs_T_1]\n",
" [S16.12hs_T_1|S15.max_T_1:S4.max_T_1:S15.15hs_T_1:S16.15hs_T_1:S18.15hs_T_1:S2.15hs_T_1:S1.12hs_T_1:S3.12hs_T_1:S9.12hs_T_1]\n",
" [S8.12hs_T_1|S17.media_T_1:S13.12hs_T_1:S16.12hs_T_1:S1.12hs_T_1:S2.12hs_T_1:S3.12hs_T_1:S4.12hs_T_1:S7.12hs_T_1:S9.12hs_T_1]\n",
" [S10.12hs_T_1|S17.media_T_1:S10.15hs_T_1:S15.15hs_T_1:S6.15hs_T_1:S8.15hs_T_1:S9.15hs_T_1:S12.12hs_T_1:S1.12hs_T_1:S20.12hs_T_1:S3.12hs_T_1:S4.12hs_T_1:S7.12hs_T_1:S8.12hs_T_1:S9.12hs_T_1:S16.18hs_T_1:S4.18hs_T_1]\n",
" [S17.12hs_T_1|S10.max_T_1:S17.max_T_1:S6.max_T_1:S17.media_T_1:S10.12hs_T_1:S11.12hs_T_1:S13.12hs_T_1:S16.12hs_T_1:S4.12hs_T_1:S7.12hs_T_1:S8.12hs_T_1]\n",
" [S18.media_T_1|S17.max_T_1:S18.max_T_1:S17.media_T_1:S16.15hs_T_1:S17.15hs_T_1:S18.15hs_T_1:S10.12hs_T_1:S11.12hs_T_1:S17.12hs_T_1:S2.12hs_T_1:S4.12hs_T_1:S16.18hs_T_1:S17.18hs_T_1]\n",
" [S18.12hs_T_1|S17.media_T_1:S10.12hs_T_1:S11.12hs_T_1:S14.12hs_T_1:S16.12hs_T_1:S17.12hs_T_1:S5.12hs_T_1:S9.12hs_T_1]\n",
" [S14.media_T_1|S14.max_T_1:S18.max_T_1:S18.media_T_1:S14.12hs_T_1:S18.12hs_T_1:S4.12hs_T_1:S10.18hs_T_1:S13.18hs_T_1:S14.18hs_T_1:S18.18hs_T_1:S19.18hs_T_1:S1.18hs_T_1:S20.18hs_T_1]\n",
" [S6.12hs_T_1|S11.12hs_T_1:S17.12hs_T_1:S18.12hs_T_1:S20.12hs_T_1:S4.12hs_T_1:S5.12hs_T_1:S7.12hs_T_1]\n",
" [S16.media_T_1|S15.max_T_1:S19.max_T_1:S14.media_T_1:S18.media_T_1:S12.15hs_T_1:S16.15hs_T_1:S18.15hs_T_1:S6.15hs_T_1:S8.15hs_T_1:S12.12hs_T_1:S14.12hs_T_1:S16.12hs_T_1]\n",
" [S3.15hs_T_1|S11.15hs_T_1:S16.15hs_T_1:S18.15hs_T_1:S2.15hs_T_1:S4.15hs_T_1:S6.15hs_T_1:S11.12hs_T_1:S16.12hs_T_1:S18.12hs_T_1:S20.12hs_T_1:S3.12hs_T_1:S6.12hs_T_1]\n",
" [S3.max_T_1|S2.max_T_1:S7.max_T_1:S2.15hs_T_1:S3.15hs_T_1:S7.15hs_T_1]\n",
" [S19.media_T_1|S18.max_T_1:S19.max_T_1:S7.max_T_1:S14.media_T_1:S16.media_T_1:S17.media_T_1:S18.media_T_1:S10.15hs_T_1:S11.15hs_T_1:S16.15hs_T_1:S18.15hs_T_1:S19.15hs_T_1:S11.12hs_T_1:S4.12hs_T_1:S6.12hs_T_1:S9.12hs_T_1:S12.18hs_T_1:S14.18hs_T_1:S16.18hs_T_1:S17.18hs_T_1:S18.18hs_T_1:S19.18hs_T_1:S3.18hs_T_1]\n",
" [S1.media_T_1|S16.media_T_1:S18.media_T_1:S16.12hs_T_1:S17.12hs_T_1:S1.12hs_T_1:S6.12hs_T_1:S9.12hs_T_1]\n",
" [S15.media_T_1|S14.max_T_1:S15.max_T_1:S14.media_T_1:S19.media_T_1:S15.15hs_T_1:S19.15hs_T_1:S6.15hs_T_1:S10.12hs_T_1:S16.12hs_T_1:S1.12hs_T_1:S14.18hs_T_1:S15.18hs_T_1:S19.18hs_T_1]\n",
" [S12.media_T_1|S10.max_T_1:S12.max_T_1:S17.max_T_1:S19.max_T_1:S20.max_T_1:S7.max_T_1:S15.media_T_1:S16.media_T_1:S1.media_T_1:S12.12hs_T_1:S16.12hs_T_1:S18.12hs_T_1:S1.12hs_T_1:S8.12hs_T_1]\n",
" [S20.media_T_1|S14.max_T_1:S2.max_T_1:S12.media_T_1:S15.media_T_1:S18.media_T_1:S15.15hs_T_1:S19.15hs_T_1:S20.15hs_T_1:S2.15hs_T_1:S15.18hs_T_1:S20.18hs_T_1]\n",
" [S11.media_T_1|S12.media_T_1:S14.media_T_1:S17.media_T_1:S18.media_T_1:S20.media_T_1:S11.12hs_T_1:S17.12hs_T_1:S7.12hs_T_1:S8.12hs_T_1:S11.18hs_T_1:S18.18hs_T_1:S20.18hs_T_1:S4.18hs_T_1]\n",
" [S6.media_T_1|S12.media_T_1:S14.media_T_1:S17.media_T_1:S18.media_T_1:S1.media_T_1:S20.media_T_1:S20.15hs_T_1:S3.15hs_T_1:S6.15hs_T_1:S10.18hs_T_1:S12.18hs_T_1:S13.18hs_T_1:S14.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1:S20.18hs_T_1:S2.18hs_T_1:S6.18hs_T_1]\n",
" [S20.12hs_T_2|S11.media_T_1:S4.18hs_T_1]\n",
" [S7.18hs_T_1|S11.media_T_1:S20.12hs_T_1:S5.12hs_T_1:S7.12hs_T_1:S10.18hs_T_1:S13.18hs_T_1:S15.18hs_T_1:S17.18hs_T_1:S18.18hs_T_1:S19.18hs_T_1:S2.18hs_T_1:S3.18hs_T_1:S5.18hs_T_1:S6.18hs_T_1]\n",
" [S3.12hs_T_2|S20.12hs_T_2][S11.15hs_T_2|S3.12hs_T_2:S11.15hs_T_1:S2.15hs_T_1]\n",
" [S20.15hs_T_2|S11.15hs_T_2:S14.18hs_T_1:S15.18hs_T_1:S18.18hs_T_1:S5.18hs_T_1]\n",
" [S12.15hs_T_2|S11.15hs_T_2:S20.15hs_T_2:S3.12hs_T_2:S10.18hs_T_1:S15.18hs_T_1:S16.18hs_T_1:S19.18hs_T_1:S5.18hs_T_1]\n",
" [S2.15hs_T_2|S11.15hs_T_2:S12.15hs_T_2:S20.15hs_T_2:S11.media_T_1:S12.media_T_1:S17.18hs_T_1:S18.18hs_T_1:S20.18hs_T_1]\n",
" [S4.15hs_T_2|S20.15hs_T_2:S2.15hs_T_2:S20.12hs_T_2:S19.max_T_1:S2.max_T_1:S4.max_T_1:S15.18hs_T_1]\n",
" [S2.media_T_1|S2.15hs_T_2:S11.max_T_1:S16.max_T_1:S2.max_T_1:S14.media_T_1:S16.media_T_1:S20.media_T_1:S6.media_T_1:S19.15hs_T_1:S6.15hs_T_1:S13.12hs_T_1:S1.12hs_T_1:S2.12hs_T_1]\n",
" [S9.15hs_T_2|S11.15hs_T_2:S12.15hs_T_2:S20.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2]\n",
" [S10.15hs_T_2|S11.15hs_T_2:S12.15hs_T_2:S2.15hs_T_2:S9.15hs_T_2]\n",
" [S2.12hs_T_2|S11.15hs_T_2:S12.15hs_T_2:S4.15hs_T_2:S9.15hs_T_2:S20.12hs_T_2:S3.12hs_T_2]\n",
" [S9.12hs_T_2|S20.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2:S9.15hs_T_2:S20.12hs_T_2:S2.12hs_T_2]\n",
" [S7.media_T_1|S10.15hs_T_2:S9.15hs_T_2:S6.max_T_1:S7.max_T_1:S12.media_T_1:S17.media_T_1:S19.media_T_1:S20.media_T_1:S6.media_T_1:S14.15hs_T_1:S15.15hs_T_1:S20.15hs_T_1:S4.15hs_T_1:S7.15hs_T_1]\n",
" [S12.12hs_T_2|S12.15hs_T_2:S9.15hs_T_2:S20.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S9.12hs_T_2:S10.18hs_T_1:S13.18hs_T_1:S14.18hs_T_1:S19.18hs_T_1:S6.18hs_T_1]\n",
" [S10.media_T_1|S10.max_T_1:S15.max_T_1:S7.max_T_1:S12.media_T_1:S15.media_T_1:S17.media_T_1:S7.media_T_1:S10.15hs_T_1:S15.15hs_T_1:S20.15hs_T_1:S9.15hs_T_1:S10.12hs_T_1:S12.12hs_T_1:S13.12hs_T_1:S3.12hs_T_1]\n",
" [S8.media_T_1|S4.15hs_T_2:S12.max_T_1:S19.max_T_1:S9.max_T_1:S10.media_T_1:S11.media_T_1:S12.media_T_1:S16.media_T_1:S18.media_T_1:S19.media_T_1:S20.media_T_1:S2.media_T_1:S10.15hs_T_1:S2.15hs_T_1:S4.15hs_T_1:S6.15hs_T_1:S8.15hs_T_1:S10.12hs_T_1:S16.12hs_T_1:S4.12hs_T_1:S6.12hs_T_1:S8.12hs_T_1]\n",
" [S5.media_T_1|S10.media_T_1:S11.media_T_1:S15.media_T_1:S19.media_T_1:S1.media_T_1:S2.media_T_1:S6.media_T_1:S7.media_T_1:S8.media_T_1]\n",
" [S4.media_T_1|S12.15hs_T_2:S9.max_T_1:S11.media_T_1:S18.media_T_1:S2.media_T_1:S5.media_T_1:S7.media_T_1:S8.media_T_1:S11.15hs_T_1:S4.15hs_T_1:S14.12hs_T_1:S2.12hs_T_1:S4.12hs_T_1:S7.12hs_T_1:S2.18hs_T_1:S4.18hs_T_1:S7.18hs_T_1:S9.18hs_T_1]\n",
" [S4.12hs_T_2|S2.12hs_T_2:S9.12hs_T_2:S2.media_T_1:S4.media_T_1:S5.media_T_1:S11.15hs_T_1:S3.12hs_T_1:S5.12hs_T_1]\n",
" [S9.media_T_1|S10.media_T_1:S14.media_T_1:S15.media_T_1:S16.media_T_1:S17.media_T_1:S1.media_T_1:S4.media_T_1:S5.media_T_1:S10.15hs_T_1:S15.15hs_T_1:S17.15hs_T_1:S9.15hs_T_1:S10.12hs_T_1:S17.12hs_T_1:S6.12hs_T_1:S8.12hs_T_1:S9.12hs_T_1:S10.18hs_T_1:S12.18hs_T_1:S3.18hs_T_1:S9.18hs_T_1]\n",
" [S5.12hs_T_2|S12.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S9.12hs_T_2]\n",
" [S13.12hs_T_2|S12.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S5.12hs_T_2:S9.12hs_T_2]\n",
" [S15.12hs_T_2|S13.12hs_T_2:S20.12hs_T_2:S2.12hs_T_2:S9.12hs_T_2:S11.15hs_T_1:S15.15hs_T_1:S6.15hs_T_1:S9.15hs_T_1]\n",
" [S7.12hs_T_2|S13.12hs_T_2:S20.12hs_T_2:S4.12hs_T_2]\n",
" [S14.12hs_T_2|S13.12hs_T_2:S15.12hs_T_2:S3.12hs_T_2:S5.12hs_T_2:S7.12hs_T_2:S9.12hs_T_2:S18.18hs_T_1:S19.18hs_T_1]\n",
" [S6.12hs_T_2|S14.12hs_T_2:S15.12hs_T_2:S4.12hs_T_2:S5.12hs_T_2:S7.12hs_T_2:S9.12hs_T_2:S13.max_T_1:S9.max_T_1:S18.media_T_1:S6.media_T_1]\n",
" [S18.12hs_T_2|S14.12hs_T_2:S20.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S5.12hs_T_2:S6.12hs_T_2:S9.12hs_T_2:S18.media_T_1:S19.media_T_1:S2.media_T_1:S7.media_T_1:S9.media_T_1]\n",
" [S1.12hs_T_2|S20.12hs_T_2:S3.12hs_T_2:S5.12hs_T_2:S6.12hs_T_2:S7.12hs_T_2:S9.12hs_T_2]\n",
" [S19.12hs_T_2|S15.12hs_T_2:S18.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S6.12hs_T_2:S9.12hs_T_2:S20.max_T_1:S11.media_T_1:S19.media_T_1:S5.media_T_1:S6.media_T_1]\n",
" [S8.12hs_T_2|S13.12hs_T_2:S1.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S7.12hs_T_2]\n",
" [S11.12hs_T_2|S12.12hs_T_2:S19.12hs_T_2:S1.12hs_T_2:S20.12hs_T_2:S6.12hs_T_2:S7.12hs_T_2:S8.12hs_T_2]\n",
" [S17.media_T_2|S12.15hs_T_2:S11.12hs_T_2:S12.12hs_T_2:S19.12hs_T_2:S5.12hs_T_2:S4.max_T_1:S15.media_T_1:S11.15hs_T_1]\n",
" [S20.max_T_2|S17.media_T_2:S20.15hs_T_2:S9.15hs_T_2:S12.18hs_T_1:S14.18hs_T_1]\n",
" [S16.12hs_T_2|S17.media_T_2:S18.12hs_T_2:S1.12hs_T_2:S6.12hs_T_2:S8.12hs_T_2:S9.12hs_T_2]\n",
" [S2.max_T_2|S20.max_T_2:S11.15hs_T_2:S20.15hs_T_2:S2.15hs_T_2:S9.15hs_T_2:S20.12hs_T_2:S5.12hs_T_2:S11.media_T_1:S15.media_T_1]\n",
" [S17.12hs_T_2|S11.12hs_T_2:S13.12hs_T_2:S16.12hs_T_2:S18.12hs_T_2:S19.12hs_T_2:S1.12hs_T_2:S20.12hs_T_2:S4.12hs_T_2:S7.12hs_T_2:S8.12hs_T_2:S18.max_T_1:S7.max_T_1:S14.media_T_1:S1.media_T_1]\n",
" [S9.max_T_2|S2.max_T_2:S17.media_T_2:S2.15hs_T_2:S9.15hs_T_2]\n",
" [S10.12hs_T_2|S15.12hs_T_2:S17.12hs_T_2:S18.12hs_T_2:S1.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S4.12hs_T_2:S7.12hs_T_2:S8.12hs_T_2:S9.12hs_T_2:S10.18hs_T_1:S19.18hs_T_1]\n",
" [S10.max_T_2|S2.max_T_2:S9.max_T_2:S10.15hs_T_2:S9.15hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S6.12hs_T_2]\n",
" [S18.media_T_2|S17.media_T_2:S10.12hs_T_2:S11.12hs_T_2:S17.12hs_T_2:S18.12hs_T_2:S20.12hs_T_2:S2.12hs_T_2:S4.12hs_T_2:S5.12hs_T_2]\n",
" [S3.15hs_T_2|S20.max_T_2:S9.max_T_2:S11.15hs_T_2:S12.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2:S11.12hs_T_2:S18.12hs_T_2:S3.12hs_T_2:S6.12hs_T_2]\n",
" [S15.max_T_2|S10.max_T_2:S2.max_T_2:S9.max_T_2:S17.media_T_2:S15.12hs_T_2:S19.12hs_T_2:S20.12hs_T_2:S8.12hs_T_2:S9.12hs_T_2]\n",
" [S14.15hs_T_2|S17.media_T_2:S18.media_T_2:S11.15hs_T_2:S3.15hs_T_2:S9.15hs_T_2:S12.12hs_T_2:S14.12hs_T_2:S16.12hs_T_2:S20.12hs_T_2:S5.12hs_T_2:S8.12hs_T_2:S14.15hs_T_1:S16.15hs_T_1:S9.15hs_T_1]\n",
" [S19.max_T_2|S15.max_T_2:S20.max_T_2:S9.max_T_2:S12.12hs_T_2:S13.12hs_T_2:S19.12hs_T_2:S20.12hs_T_2:S5.12hs_T_2:S13.max_T_1:S19.max_T_1:S18.media_T_1:S19.media_T_1:S20.media_T_1:S20.18hs_T_1]\n",
" [S12.max_T_2|S10.max_T_2:S15.max_T_2:S19.max_T_2:S20.max_T_2:S9.max_T_2:S10.15hs_T_2:S12.15hs_T_2:S9.15hs_T_2]\n",
" [S17.15hs_T_2|S19.max_T_2:S14.15hs_T_2:S4.15hs_T_2:S14.12hs_T_2:S18.12hs_T_2:S1.12hs_T_2:S2.12hs_T_2:S9.12hs_T_2]\n",
" [S11.max_T_2|S15.max_T_2:S19.max_T_2:S20.max_T_2:S2.max_T_2:S9.max_T_2:S11.15hs_T_2:S14.15hs_T_2:S17.15hs_T_2:S20.15hs_T_2:S4.15hs_T_2:S20.12hs_T_2:S4.12hs_T_2]\n",
" [S6.max_T_2|S11.max_T_2:S15.max_T_2:S2.max_T_2:S9.max_T_2:S12.12hs_T_1:S17.12hs_T_1:S6.12hs_T_1]\n",
" [S7.max_T_2|S12.max_T_2:S20.max_T_2:S6.max_T_2:S9.max_T_2:S10.15hs_T_2:S20.15hs_T_2:S2.15hs_T_2]\n",
" [S13.max_T_2|S11.max_T_2:S12.max_T_2:S7.max_T_2:S9.max_T_2:S14.15hs_T_2:S4.15hs_T_2:S13.12hs_T_2:S6.12hs_T_2]\n",
" [S7.15hs_T_2|S12.max_T_2:S2.max_T_2:S7.max_T_2:S18.media_T_2:S10.15hs_T_2:S12.15hs_T_2:S20.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2:S12.12hs_T_2:S1.12hs_T_2:S3.12hs_T_2:S5.12hs_T_2:S7.12hs_T_2]\n",
" [S3.max_T_2|S11.max_T_2:S2.max_T_2:S7.max_T_2:S17.media_T_2:S2.15hs_T_2:S3.15hs_T_2:S7.15hs_T_2]\n",
" [S18.15hs_T_2|S19.max_T_2:S12.15hs_T_2:S14.15hs_T_2:S17.15hs_T_2:S20.15hs_T_2:S3.15hs_T_2:S7.15hs_T_2:S15.12hs_T_2:S18.12hs_T_2:S3.12hs_T_2]\n",
" [S18.max_T_2|S12.max_T_2:S13.max_T_2:S20.max_T_2:S2.max_T_2:S12.15hs_T_2:S18.15hs_T_2:S2.15hs_T_2:S7.15hs_T_2]\n",
" [S16.15hs_T_2|S15.max_T_2:S19.max_T_2:S10.15hs_T_2:S17.15hs_T_2:S18.15hs_T_2:S20.15hs_T_2:S3.15hs_T_2:S4.15hs_T_2:S9.15hs_T_2:S16.12hs_T_2:S18.12hs_T_2:S1.12hs_T_2:S3.12hs_T_2]\n",
" [S16.max_T_2|S11.max_T_2:S18.max_T_2:S19.max_T_2:S7.max_T_2:S9.max_T_2:S16.15hs_T_2:S18.15hs_T_2:S9.15hs_T_2]\n",
" [S19.15hs_T_2|S16.max_T_2:S19.max_T_2:S20.max_T_2:S17.media_T_2:S10.15hs_T_2:S12.15hs_T_2:S16.15hs_T_2:S18.15hs_T_2]\n",
" [S15.15hs_T_2|S10.max_T_2:S11.max_T_2:S15.max_T_2:S16.max_T_2:S19.max_T_2:S9.max_T_2:S10.15hs_T_2:S14.15hs_T_2:S19.15hs_T_2:S9.15hs_T_2]\n",
" [S14.max_T_2|S13.max_T_2:S15.max_T_2:S18.max_T_2:S9.max_T_2:S14.15hs_T_2:S15.15hs_T_2:S18.15hs_T_2:S7.15hs_T_2]\n",
" [S14.media_T_2|S10.max_T_2:S14.max_T_2:S18.max_T_2:S7.max_T_2:S18.media_T_2:S14.12hs_T_2:S18.12hs_T_2:S4.12hs_T_2]\n",
" [S16.media_T_2|S18.max_T_2:S19.max_T_2:S14.media_T_2:S17.media_T_2:S18.media_T_2:S14.15hs_T_2:S15.15hs_T_2:S16.15hs_T_2:S17.15hs_T_2:S18.15hs_T_2:S16.12hs_T_2:S19.12hs_T_2:S4.12hs_T_2:S6.12hs_T_2:S16.15hs_T_1:S18.18hs_T_1:S1.18hs_T_1:S20.18hs_T_1:S7.18hs_T_1]\n",
" [S19.media_T_2|S18.max_T_2:S19.max_T_2:S14.media_T_2:S16.media_T_2:S17.media_T_2:S18.media_T_2:S14.15hs_T_2:S16.15hs_T_2:S19.15hs_T_2:S20.15hs_T_2:S14.12hs_T_2:S15.12hs_T_2:S16.12hs_T_2:S19.12hs_T_2:S9.12hs_T_2:S19.18hs_T_1:S20.18hs_T_1]\n",
" [S12.media_T_2|S10.max_T_2:S19.max_T_2:S20.max_T_2:S6.max_T_2:S7.max_T_2:S14.media_T_2:S16.media_T_2:S18.media_T_2:S19.media_T_2:S12.15hs_T_2:S14.15hs_T_2:S17.15hs_T_2:S12.12hs_T_2:S16.12hs_T_2:S18.12hs_T_2:S1.12hs_T_2]\n",
" [S20.media_T_2|S11.max_T_2:S18.max_T_2:S20.max_T_2:S12.media_T_2:S18.media_T_2:S15.15hs_T_2:S17.15hs_T_2:S19.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2]\n",
" [S2.media_T_2|S15.max_T_2:S20.max_T_2:S2.max_T_2:S6.max_T_2:S14.media_T_2:S16.media_T_2:S20.media_T_2:S3.15hs_T_2:S9.15hs_T_2:S11.12hs_T_2:S14.12hs_T_2:S20.12hs_T_2:S2.12hs_T_2]\n",
" [S11.18hs_T_2|S10.max_T_2:S19.max_T_2:S17.media_T_2:S20.media_T_2:S15.15hs_T_2:S13.12hs_T_2:S14.12hs_T_2:S8.12hs_T_2:S2.media_T_1:S7.media_T_1:S17.18hs_T_1:S18.18hs_T_1]\n",
" [S16.18hs_T_2|S15.max_T_2:S19.max_T_2:S12.15hs_T_2:S18.15hs_T_2:S11.18hs_T_2]\n",
" [S19.18hs_T_2|S19.max_T_2:S6.max_T_2:S12.media_T_2:S14.media_T_2:S18.media_T_2:S19.media_T_2:S2.media_T_2:S12.15hs_T_2:S19.15hs_T_2:S3.15hs_T_2:S4.15hs_T_2:S15.12hs_T_2:S18.12hs_T_2:S19.12hs_T_2:S4.12hs_T_2:S11.18hs_T_2:S16.18hs_T_2]\n",
" [S19.12hs_T_1|S16.18hs_T_2:S16.media_T_1:S19.media_T_1:S20.media_T_1:S9.media_T_1:S11.12hs_T_1:S16.12hs_T_1:S18.12hs_T_1:S1.12hs_T_1:S3.12hs_T_1:S4.12hs_T_1:S7.12hs_T_1:S19.18hs_T_1:S9.18hs_T_1]\n",
" [S6.18hs_T_2|S20.15hs_T_2:S7.15hs_T_2:S11.18hs_T_2:S16.18hs_T_2:S19.18hs_T_2]\n",
" [Est.humedad_min_T_1|S19.18hs_T_2:S12.max_T_1:S15.max_T_1:S2.max_T_1:S12.media_T_1:S20.media_T_1:S7.media_T_1]\n",
" [S2.18hs_T_2|S17.12hs_T_2:S19.12hs_T_2:S3.12hs_T_2:S5.12hs_T_2:S11.18hs_T_2:S16.18hs_T_2:S6.18hs_T_2:S12.18hs_T_1:S19.18hs_T_1:S20.18hs_T_1:S2.18hs_T_1]\n",
" [Est.humedad_med_T_1|S3.max_T_1:S7.max_T_1:Est.humedad_min_T_1]\n",
" [Est.humedad_min_T_2|S19.media_T_1:Est.humedad_med_T_1]\n",
" [Est.humedad_max_T_1|Est.humedad_min_T_1:Est.humedad_med_T_1]\n",
" [S5.18hs_T_2|S18.max_T_2:S20.max_T_2:S11.15hs_T_2:S14.15hs_T_2:S11.18hs_T_2:S16.18hs_T_2:S19.18hs_T_2:S6.18hs_T_2:S6.media_T_1:S9.media_T_1:Est.humedad_max_T_1]\n",
" [Est.humedad_med_T_2|S3.max_T_2:S7.max_T_2:Est.humedad_min_T_2]\n",
" [S4.18hs_T_2|S12.15hs_T_2:S9.15hs_T_2:S16.18hs_T_2:S2.18hs_T_2:S5.18hs_T_2]\n",
" [Est.humedad_max_T_2|Est.humedad_min_T_2:Est.humedad_med_T_2]\n",
" [S6.media_T_2|S12.media_T_2:S14.media_T_2:S17.media_T_2:S18.media_T_2:S19.media_T_2:S2.media_T_2:S16.18hs_T_2:S2.18hs_T_2:S5.18hs_T_2:S6.18hs_T_2:Est.humedad_min_T_2:Est.humedad_max_T_2]\n",
" [S5.15hs_T_2|S12.15hs_T_2:S14.15hs_T_2:S17.15hs_T_2:S2.15hs_T_2:S3.15hs_T_2:S19.18hs_T_2:S6.18hs_T_2:Est.humedad_max_T_2:S12.media_T_1:S18.media_T_1:S1.media_T_1:S5.media_T_1]\n",
" [S1.media_T_2|S12.media_T_2:S16.media_T_2:S17.media_T_2:S19.media_T_2:S6.media_T_2:S10.12hs_T_2:S13.12hs_T_2:S17.12hs_T_2:S1.12hs_T_2:Est.humedad_min_T_2]\n",
" [S7.media_T_2|S12.media_T_2:S17.media_T_2:S20.media_T_2:S2.media_T_2:S6.media_T_2:Est.humedad_min_T_2:Est.humedad_max_T_2:Est.humedad_min_T_1:Est.humedad_max_T_1]\n",
" [S6.15hs_T_2|S18.max_T_2:S20.max_T_2:S6.max_T_2:S7.max_T_2:S12.media_T_2:S14.media_T_2:S19.media_T_2:S6.media_T_2:S11.15hs_T_2:S3.15hs_T_2:S4.15hs_T_2:S5.15hs_T_2:S7.15hs_T_2]\n",
" [S4.max_T_2|S10.max_T_2:S14.max_T_2:S19.max_T_2:S20.max_T_2:S6.max_T_2:S20.15hs_T_2:S4.15hs_T_2:S6.15hs_T_2:S9.15hs_T_2:S19.12hs_T_2:S5.12hs_T_2:S8.media_T_1]\n",
" [S17.max_T_2|S10.max_T_2:S11.max_T_2:S14.max_T_2:S15.max_T_2:S18.max_T_2:S4.max_T_2:S19.18hs_T_2:S4.18hs_T_2]\n",
" [S5.max_T_2|S11.max_T_2:S13.max_T_2:S14.max_T_2:S17.max_T_2:S18.max_T_2:S2.max_T_2:S6.max_T_2:S14.15hs_T_2:S18.15hs_T_2:S5.15hs_T_2:S7.15hs_T_2]\n",
" [S8.max_T_2|S10.max_T_2:S13.max_T_2:S19.max_T_2:S20.max_T_2:S5.max_T_2:S17.media_T_2:S10.15hs_T_2:S14.15hs_T_2:S2.15hs_T_2:S7.15hs_T_2:S10.12hs_T_2:S12.12hs_T_2:S4.12hs_T_2:S8.12hs_T_2]\n",
" [S1.max_T_2|S10.max_T_2:S12.max_T_2:S13.max_T_2:S15.max_T_2:S17.max_T_2:S19.max_T_2:S3.max_T_2:S5.max_T_2:S8.max_T_2:Est.humedad_min_T_2]\n",
" [S13.15hs_T_2|S13.max_T_2:S14.max_T_2:S19.max_T_2:S1.max_T_2:S12.15hs_T_2:S14.15hs_T_2:S15.15hs_T_2:S20.15hs_T_2:S3.15hs_T_2:S4.15hs_T_2]\n",
" [S1.15hs_T_2|S10.max_T_2:S15.max_T_2:S19.max_T_2:S1.max_T_2:S2.max_T_2:S5.max_T_2:S12.15hs_T_2:S14.15hs_T_2:S16.15hs_T_2:S17.15hs_T_2:S18.15hs_T_2:S19.15hs_T_2:S2.15hs_T_2:S5.15hs_T_2:Est.humedad_min_T_1]\n",
" [S15.media_T_2|S11.max_T_2:S13.max_T_2:S14.max_T_2:S15.max_T_2:S14.media_T_2:S18.media_T_2:S19.media_T_2:S1.media_T_2:S7.media_T_2:S15.15hs_T_2:S19.15hs_T_2:S1.15hs_T_2:S7.15hs_T_2:S14.12hs_T_2:S15.12hs_T_2:S16.12hs_T_2:S11.18hs_T_2:S19.18hs_T_2:S3.max_T_1:S6.max_T_1:S12.18hs_T_1:S15.18hs_T_1]\n",
" [S8.15hs_T_2|S17.max_T_2:S20.max_T_2:S5.max_T_2:S8.max_T_2:S9.max_T_2:S10.15hs_T_2:S14.15hs_T_2:S16.15hs_T_2:S1.15hs_T_2:S2.15hs_T_2:S4.15hs_T_2:S5.15hs_T_2:S6.15hs_T_2]\n",
" [S10.media_T_2|S10.max_T_2:S15.max_T_2:S7.max_T_2:S12.media_T_2:S15.media_T_2:S17.media_T_2:S7.media_T_2:S10.15hs_T_2:S13.15hs_T_2:S15.15hs_T_2:S20.15hs_T_2:S9.15hs_T_2:S10.12hs_T_2:S12.12hs_T_2:S15.12hs_T_2:S3.12hs_T_2]\n",
" [S8.media_T_2|S10.media_T_2:S12.media_T_2:S16.media_T_2:S17.media_T_2:S1.media_T_2:S10.12hs_T_2:S12.12hs_T_2:S16.12hs_T_2:S4.12hs_T_2:S6.12hs_T_2:S8.12hs_T_2]\n",
" [S4.media_T_2|S20.max_T_2:S4.max_T_2:S8.max_T_2:S10.media_T_2:S17.media_T_2:S20.media_T_2:S2.media_T_2:S7.media_T_2:S8.media_T_2:S14.15hs_T_2:S3.15hs_T_2:S4.15hs_T_2:S7.15hs_T_2:S9.15hs_T_2:S17.12hs_T_2:S2.12hs_T_2:S4.12hs_T_2:S7.12hs_T_2:S2.18hs_T_2:S4.18hs_T_2:S12.18hs_T_1:S17.18hs_T_1]\n",
" [S9.media_T_2|S10.media_T_2:S16.media_T_2:S17.media_T_2:S1.media_T_2:S4.media_T_2:Est.humedad_max_T_1]\n",
" [S10.min_T_1|S10.media_T_2:S4.media_T_2:S16.18hs_T_2:S8.media_T_1:S12.15hs_T_1:S16.12hs_T_1:S4.12hs_T_1:S16.18hs_T_1]\n",
" [S9.18hs_T_2|S12.media_T_2:S19.media_T_2:S20.media_T_2:S6.media_T_2:S9.media_T_2:S12.15hs_T_2:S13.15hs_T_2:S2.15hs_T_2:S7.15hs_T_2:S9.15hs_T_2:S11.18hs_T_2:S19.18hs_T_2:S2.18hs_T_2]\n",
" [S11.min_T_1|S19.media_T_1:S10.min_T_1:S3.12hs_T_1]\n",
" [S3.media_T_2|S10.max_T_2:S12.max_T_2:S14.max_T_2:S3.max_T_2:S6.max_T_2:S10.media_T_2:S14.media_T_2:S20.media_T_2:S2.media_T_2:S6.media_T_2:S7.media_T_2:S8.media_T_2:S9.media_T_2:S12.12hs_T_2:S18.12hs_T_2:S1.12hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S6.12hs_T_2:S19.18hs_T_2:S9.18hs_T_2:S10.min_T_1]\n",
" [S7.min_T_1|S10.min_T_1:S11.min_T_1]\n",
" [S12.18hs_T_2|S12.media_T_2:S19.media_T_2:S3.media_T_2:S6.media_T_2:S8.media_T_2:S11.18hs_T_2:S16.18hs_T_2:S4.18hs_T_2:S5.18hs_T_2]\n",
" [S10.18hs_T_2|S12.max_T_2:S4.max_T_2:S16.15hs_T_2:S17.15hs_T_2:S12.18hs_T_2:S5.18hs_T_2:S6.18hs_T_2:S9.18hs_T_2:S10.18hs_T_1:S12.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1:Est.humedad_max_T_1]\n",
" [S13.18hs_T_2|S11.max_T_2:S13.max_T_2:S14.max_T_2:S17.15hs_T_2:S19.15hs_T_2:S2.15hs_T_2:S9.15hs_T_2:S1.12hs_T_2:S6.12hs_T_2:S10.18hs_T_2:S11.18hs_T_2:S12.18hs_T_2:S5.18hs_T_2]\n",
" [S3.18hs_T_2|S20.max_T_2:S4.max_T_2:S10.18hs_T_2:S13.18hs_T_2:S19.18hs_T_2:S2.18hs_T_2:S4.18hs_T_2:S6.18hs_T_2:S13.18hs_T_1:S3.18hs_T_1:S6.18hs_T_1]\n",
" [S13.media_T_2|S12.media_T_2:S14.media_T_2:S15.media_T_2:S20.media_T_2:S9.media_T_2:S12.15hs_T_2:S13.15hs_T_2:S20.15hs_T_2:S3.18hs_T_2:S9.18hs_T_2]\n",
" [S15.18hs_T_2|S13.media_T_2:S15.media_T_2:S18.media_T_2:S4.media_T_2:S7.media_T_2:S9.media_T_2:S13.18hs_T_2:S5.18hs_T_2:S19.media_T_1]\n",
" [S20.18hs_T_2|S19.max_T_2:S20.max_T_2:S2.max_T_2:S7.max_T_2:S11.18hs_T_2:S15.18hs_T_2:S2.18hs_T_2:S3.18hs_T_2:S5.18hs_T_2:S9.18hs_T_2:Est.humedad_med_T_2:S7.min_T_1]\n",
" [S18.18hs_T_2|S10.max_T_2:S12.max_T_2:S15.max_T_2:S18.max_T_2:S5.max_T_2:S10.18hs_T_2:S11.18hs_T_2:S15.18hs_T_2:S20.18hs_T_2:S3.18hs_T_2:S4.18hs_T_2:S9.18hs_T_2]\n",
" [S7.18hs_T_2|S19.12hs_T_2:S20.12hs_T_2:S5.12hs_T_2:S7.12hs_T_2:S8.12hs_T_2:S10.18hs_T_2:S13.18hs_T_2:S15.18hs_T_2:S18.18hs_T_2:S20.18hs_T_2:S4.18hs_T_2:S5.18hs_T_2:S6.18hs_T_2:S11.min_T_1]\n",
" [S11.media_T_2|S10.media_T_2:S13.media_T_2:S18.media_T_2:S20.media_T_2:S2.media_T_2:S4.media_T_2:S9.media_T_2:S11.12hs_T_2:S13.12hs_T_2:S17.12hs_T_2:S4.12hs_T_2:S11.18hs_T_2:S18.18hs_T_2:S20.18hs_T_2:S4.18hs_T_2:S7.18hs_T_2:S11.media_T_1:S17.media_T_1:S5.media_T_1:S20.15hs_T_1:S4.15hs_T_1]\n",
" [S17.18hs_T_2|S15.media_T_2:S17.media_T_2:S4.media_T_2:S6.media_T_2:S11.15hs_T_2:S10.18hs_T_2:S13.18hs_T_2:S15.18hs_T_2:S16.18hs_T_2:S18.18hs_T_2:S7.18hs_T_2:S9.18hs_T_2]\n",
" [S1.18hs_T_2|S14.15hs_T_2:S1.15hs_T_2:S2.15hs_T_2:S12.18hs_T_2:S16.18hs_T_2:S17.18hs_T_2:S18.18hs_T_2:S2.18hs_T_2:S5.18hs_T_2:S9.18hs_T_2:Est.humedad_max_T_1]\n",
" [S5.media_T_2|S12.media_T_2:S1.media_T_2:S2.media_T_2:S6.media_T_2:S8.media_T_2:S9.media_T_2:S12.15hs_T_2:S17.15hs_T_2:S5.15hs_T_2:S7.15hs_T_2:S12.12hs_T_2:S4.12hs_T_2:S5.12hs_T_2:S9.12hs_T_2:S11.18hs_T_2:S1.18hs_T_2:S3.18hs_T_2:S5.18hs_T_2]\n",
" [S14.18hs_T_2|S14.media_T_2:S18.media_T_2:S20.media_T_2:S6.media_T_2:S12.18hs_T_2:S13.18hs_T_2:S16.18hs_T_2:S18.18hs_T_2:S1.18hs_T_2:S20.18hs_T_2:S6.18hs_T_2]\n",
" [S20.min_T_1|S14.18hs_T_2:S20.18hs_T_2:S10.min_T_1:S11.min_T_1:S7.min_T_1]\n",
" [S4.min_T_1|S11.media_T_2:S12.media_T_2:S19.media_T_2:S1.media_T_2:S4.media_T_2:S11.min_T_1:S20.min_T_1:S7.min_T_1]\n",
" [S10.min_T_2|S10.media_T_2:S18.media_T_2:S4.media_T_2:S12.15hs_T_2:S16.15hs_T_2:S10.12hs_T_2:S17.12hs_T_2:S4.12hs_T_2:S6.12hs_T_2:S16.18hs_T_2:S10.min_T_1:S4.min_T_1]\n",
" [S6.min_T_1|S11.media_T_2:S19.media_T_2:S7.media_T_2:S10.min_T_1:S4.min_T_1:S7.min_T_1]\n",
" [S11.min_T_2|S19.media_T_2:S10.min_T_2:S3.12hs_T_2]\n",
" [S5.min_T_1|S10.min_T_1:S20.min_T_1:S6.min_T_1:S2.15hs_T_1:S7.15hs_T_1]\n",
" [S15.min_T_2|S10.min_T_2:S11.min_T_2][S12.min_T_1|S11.min_T_1:S5.min_T_1]\n",
" [S11.min_t|S11.max_T_2:S11.media_T_2:S2.media_T_2:S5.media_T_2:S11.min_T_2:S11.15hs_T_2:S15.15hs_T_2:S11.12hs_T_2:S11.18hs_T_2:S11.max_T_1:S19.max_T_1:S11.media_T_1:S11.min_T_1:S11.15hs_T_1:S15.15hs_T_1:S11.12hs_T_1:S11.18hs_T_1:S20.18hs_T_1:Est.humedad_min_T_1]\n",
" [S1.min_T_1|S12.min_T_1:S20.min_T_1:S5.min_T_1:Est.humedad_max_T_1]\n",
" [S3.min_T_1|S10.min_T_1:S11.min_T_1:S12.min_T_1:S4.min_T_1:S6.min_T_1]\n",
" [S15.min_T_1|S10.min_T_1:S11.min_T_1:S3.min_T_1]\n",
" [S2.min_T_1|S14.media_T_1:S1.min_T_1:S3.min_T_1:S4.min_T_1:S5.min_T_1]\n",
" [S13.min_T_1|S10.media_T_1:S15.media_T_1:S20.media_T_1:S12.min_T_1:S15.min_T_1:S2.min_T_1:S3.min_T_1:S11.min_t]\n",
" [S14.min_T_1|S4.15hs_T_2:S7.15hs_T_2:Est.humedad_min_T_2:S11.min_T_1:S13.min_T_1:S15.min_T_1:S6.min_T_1:S11.min_t]\n",
" [S17.min_T_1|S14.min_T_1:S15.min_T_1:S1.min_T_1]\n",
" [S18.min_T_1|S14.min_T_1:S15.min_T_1:S17.min_T_1:S1.min_T_1:S9.18hs_T_1]\n",
" [S15.12hs_T_1|Est.humedad_min_T_2:S18.min_T_1:S1.min_T_1:S10.15hs_T_1:S11.15hs_T_1:S15.15hs_T_1:S16.15hs_T_1:S9.15hs_T_1:S10.12hs_T_1:S13.12hs_T_1:S14.12hs_T_1:S19.12hs_T_1:S1.12hs_T_1:S9.12hs_T_1]\n",
" [S5.15hs_T_1|S19.max_T_2:S11.min_T_2:S4.15hs_T_2:S5.15hs_T_2:S9.15hs_T_2:S14.15hs_T_1:S6.15hs_T_1:S7.15hs_T_1:S8.15hs_T_1:S9.15hs_T_1:S11.12hs_T_1:S15.12hs_T_1:S5.12hs_T_1:S19.18hs_T_1:S20.18hs_T_1]\n",
" [S5.max_T_1|S11.max_T_1:S13.max_T_1:S14.max_T_1:S17.max_T_1:S18.max_T_1:S2.max_T_1:S6.max_T_1:S14.15hs_T_1:S18.15hs_T_1:S5.15hs_T_1:S7.15hs_T_1]\n",
" [S8.max_T_1|S13.18hs_T_2:S20.18hs_T_2:S10.max_T_1:S13.max_T_1:S18.max_T_1:S19.max_T_1:S20.max_T_1:S5.max_T_1:S10.15hs_T_1:S18.15hs_T_1:S5.15hs_T_1:S8.15hs_T_1]\n",
" [S1.max_T_1|S10.max_T_1:S12.max_T_1:S13.max_T_1:S15.max_T_1:S17.max_T_1:S19.max_T_1:S3.max_T_1:S5.max_T_1:S8.max_T_1:Est.humedad_min_T_1]\n",
" [S8.18hs_T_1|S18.max_T_1:S8.max_T_1:S12.min_T_1:S14.12hs_T_1:S1.12hs_T_1:S5.12hs_T_1:S6.12hs_T_1:S13.18hs_T_1:S15.18hs_T_1:S16.18hs_T_1:S20.18hs_T_1:S4.18hs_T_1:S5.18hs_T_1:S9.18hs_T_1]\n",
" [S13.15hs_T_1|S13.max_T_1:S14.max_T_1:S19.max_T_1:S1.max_T_1:S12.15hs_T_1:S14.15hs_T_1:S15.15hs_T_1:S20.15hs_T_1:S3.15hs_T_1:S4.15hs_T_1:S19.18hs_T_1:S7.18hs_T_1:S9.18hs_T_1]\n",
" [S1.15hs_T_1|S10.max_T_1:S15.max_T_1:S19.max_T_1:S1.max_T_1:S3.max_T_1:S5.max_T_1:S12.15hs_T_1:S16.15hs_T_1:S17.15hs_T_1:S19.15hs_T_1:S2.15hs_T_1:S3.15hs_T_1:S5.15hs_T_1]\n",
" [S7.min_T_2|S10.min_T_2:S11.min_T_2:S1.15hs_T_1:S8.15hs_T_1:S19.18hs_T_1]\n",
" [S13.media_T_1|S13.12hs_T_2:S14.12hs_T_2:S19.18hs_T_2:S11.media_T_1:S12.media_T_1:S14.media_T_1:S15.media_T_1:S20.media_T_1:S5.media_T_1:S9.media_T_1:S12.15hs_T_1:S13.15hs_T_1:S20.15hs_T_1:S3.18hs_T_1]\n",
" [S20.min_T_2|S10.min_T_2:S11.min_T_2:S7.min_T_2:Est.humedad_min_T_1]\n",
" [S5.min_T_2|S10.min_T_2:S20.min_T_2:S7.min_T_2:S2.15hs_T_2:S7.15hs_T_2]\n",
" [S12.min_T_2|S11.min_T_2:S5.min_T_2]\n",
" [S2.min_T_2|S19.media_T_2:S11.min_T_2:S5.min_T_2:S7.min_T_2:S15.18hs_T_2]\n",
" [S5.min_t|S5.max_T_2:S2.media_T_2:S5.media_T_2:S5.min_T_2:S5.15hs_T_2:S5.12hs_T_2:S5.18hs_T_2:Est.humedad_min_T_2:S5.max_T_1:S5.media_T_1:S5.min_T_1:S17.15hs_T_1:S1.15hs_T_1:S5.15hs_T_1:S5.12hs_T_1:S5.18hs_T_1]\n",
" [S13.min_T_2|S10.media_T_2:S15.media_T_2:S6.media_T_2:S11.min_T_2:S12.min_T_2:S15.min_T_2:S2.min_T_2:S17.min_T_1]\n",
" [S8.18hs_T_2|S18.max_T_2:S8.max_T_2:S12.min_T_2:S14.12hs_T_2:S1.12hs_T_2:S5.12hs_T_2:S6.12hs_T_2:S13.18hs_T_2:S15.18hs_T_2:S16.18hs_T_2:S20.18hs_T_2:S4.18hs_T_2:S5.18hs_T_2:S9.18hs_T_2]\n",
" [Est.temp_max_T_1|S4.media_T_2:Est.humedad_min_T_1:S5.min_t]\n",
" [S14.min_T_2|S11.min_T_2:S13.min_T_2:S15.min_T_2]\n",
" [S3.min_T_2|S11.min_T_2:S13.min_T_2:S20.min_T_2:S2.min_T_2:Est.humedad_med_T_1:Est.humedad_max_T_1]\n",
" [S9.min_T_1|Est.humedad_max_T_2:S10.min_T_1:S14.min_T_1:S15.min_T_1:S3.min_T_1:S5.min_T_1:S7.min_T_1:Est.temp_max_T_1]\n",
" [S9.min_T_2|S10.min_T_2:S14.min_T_2:S15.min_T_2:S3.min_T_2:S5.min_T_2:S7.min_T_2:S5.min_t]\n",
" [S8.min_T_1|S12.min_T_1:S1.min_T_1:S9.min_T_1]\n",
" [S8.min_T_2|S12.min_T_2:S5.min_T_2:S9.min_T_2]\n",
" [S19.min_T_1|S12.min_T_1:S18.min_T_1:S20.min_T_1:S8.min_T_1:S1.12hs_T_1:S6.12hs_T_1]\n",
" [Est.temp_med_T_1|S9.min_T_2:S11.15hs_T_2:S7.15hs_T_2:S4.12hs_T_2:Est.humedad_med_T_1:Est.humedad_max_T_1:Est.temp_max_T_1]\n",
" [S1.min_T_2|S12.min_T_2:S20.min_T_2:S2.min_T_2:S8.min_T_2]\n",
" [S16.min_T_1|S12.min_T_1:S18.min_T_1:S19.min_T_1:S4.min_T_1:S8.min_T_1:S9.min_T_1]\n",
" [Est.temp_min_T_1|Est.temp_max_T_1:Est.temp_med_T_1]\n",
" [S17.min_T_2|S14.min_T_2:S15.min_T_2:S1.min_T_2]\n",
" [S13.min_t|S13.max_T_2:S13.media_T_2:S13.min_T_2:S13.15hs_T_2:S13.12hs_T_2:S13.18hs_T_2:S13.max_T_1:S13.media_T_1:S13.min_T_1:S15.min_T_1:S13.15hs_T_1:S13.12hs_T_1:S13.18hs_T_1:S20.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S15.min_t|S15.max_T_2:S10.media_T_2:S15.media_T_2:S15.min_T_2:S15.15hs_T_2:S15.12hs_T_2:S15.18hs_T_2:S14.max_T_1:S15.max_T_1:S15.media_T_1:S6.media_T_1:S14.min_T_1:S15.min_T_1:S15.15hs_T_1:S15.12hs_T_1:S15.18hs_T_1:S20.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S1.min_t|S17.max_T_2:S1.max_T_2:S1.media_T_2:S1.min_T_2:S1.15hs_T_2:S1.12hs_T_2:S1.18hs_T_2:S1.max_T_1:S1.media_T_1:S1.min_T_1:S1.15hs_T_1:S9.15hs_T_1:S1.12hs_T_1:S1.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S2.min_t|S2.max_T_2:S2.media_T_2:S2.min_T_2:S2.15hs_T_2:S2.12hs_T_2:S2.18hs_T_2:S2.max_T_1:S2.media_T_1:S9.media_T_1:S2.min_T_1:S2.15hs_T_1:S2.12hs_T_1:S15.18hs_T_1:S2.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S7.min_t|S7.max_T_2:S7.media_T_2:S7.min_T_2:S7.15hs_T_2:S7.12hs_T_2:S7.18hs_T_2:S7.max_T_1:S7.media_T_1:S9.media_T_1:S7.min_T_1:S7.15hs_T_1:S7.12hs_T_1:S6.18hs_T_1:S7.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S9.min_t|S9.max_T_2:S9.media_T_2:S9.min_T_2:S9.15hs_T_2:S9.12hs_T_2:S9.18hs_T_2:S14.max_T_1:S9.max_T_1:S2.media_T_1:S9.media_T_1:S9.min_T_1:S9.15hs_T_1:S9.12hs_T_1:S9.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S18.min_T_2|S11.min_T_2:S14.min_T_2:S17.min_T_2:S1.min_T_2:S6.media_T_1:S17.12hs_T_1]\n",
" [S19.min_T_2|S12.min_T_2:S18.min_T_2:S20.min_T_2:S8.min_T_2:Est.humedad_min_T_1]\n",
" [S16.min_T_2|S12.min_T_2:S18.min_T_2:S19.min_T_2:S3.min_T_2:S8.min_T_2:S9.min_T_2]\n",
" [S19.min_t|S19.max_T_2:S19.media_T_2:S19.min_T_2:S19.15hs_T_2:S19.12hs_T_2:S19.18hs_T_2:S19.max_T_1:S15.media_T_1:S19.media_T_1:S19.min_T_1:S19.15hs_T_1:S19.12hs_T_1:S15.18hs_T_1:S19.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S12.min_t|S12.max_T_2:S12.media_T_2:S12.min_T_2:S16.min_T_2:S12.15hs_T_2:S12.12hs_T_2:S12.18hs_T_2:S12.max_T_1:S12.media_T_1:S12.min_T_1:S12.15hs_T_1:S1.15hs_T_1:S12.12hs_T_1:S12.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S16.min_t|S16.max_T_2:S16.media_T_2:S16.min_T_2:S16.15hs_T_2:S16.12hs_T_2:S16.18hs_T_2:S16.max_T_1:S16.media_T_1:S16.min_T_1:S7.min_T_1:S16.15hs_T_1:S16.12hs_T_1:S16.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S4.min_T_2|S11.min_T_2:S16.min_T_2:S17.min_T_2:S20.min_T_2:S2.min_T_2:S3.min_T_2:S12.min_t:S13.min_t]\n",
" [Est.temp_max_T_2|S3.min_T_2:S9.min_T_2:S16.18hs_T_2:Est.humedad_min_T_2:Est.humedad_min_T_1:Est.temp_min_T_1:S15.min_t:S16.min_t]\n",
" [S3.media_T_1|S19.max_T_1:S3.max_T_1:S6.max_T_1:S10.media_T_1:S14.media_T_1:S20.media_T_1:S2.media_T_1:S6.media_T_1:S7.media_T_1:S8.media_T_1:S9.media_T_1:S12.12hs_T_1:S18.12hs_T_1:S1.12hs_T_1:S2.12hs_T_1:S3.12hs_T_1:S6.12hs_T_1:S16.18hs_T_1:S2.18hs_T_1:S3.18hs_T_1:S6.18hs_T_1:S9.18hs_T_1:S12.min_t]\n",
" [S6.min_T_2|S14.min_T_2:S19.min_T_2:S3.min_T_2:S4.min_T_2:S5.min_T_2:S7.min_T_2:S17.media_T_1]\n",
" [Est.temp_med_T_2|S4.min_T_2:Est.humedad_med_T_2:Est.humedad_max_T_2:Est.temp_max_T_2:S20.max_T_1:S11.15hs_T_1:S10.18hs_T_1:S6.18hs_T_1:Est.humedad_max_T_1]\n",
" [S3.min_t|S3.max_T_2:S19.media_T_2:S3.media_T_2:S3.min_T_2:S4.min_T_2:S3.15hs_T_2:S2.12hs_T_2:S3.12hs_T_2:S14.18hs_T_2:S3.18hs_T_2:S19.max_T_1:S3.max_T_1:S10.media_T_1:S3.media_T_1:S3.min_T_1:S3.15hs_T_1:S3.12hs_T_1:S20.18hs_T_1:S3.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [S8.min_t|S8.max_T_2:S8.media_T_2:S8.min_T_2:S8.15hs_T_2:S8.12hs_T_2:S1.18hs_T_2:S8.18hs_T_2:S8.max_T_1:S3.media_T_1:S8.media_T_1:S8.min_T_1:S10.15hs_T_1:S8.15hs_T_1:S8.12hs_T_1:S20.18hs_T_1:S8.18hs_T_1:Est.humedad_min_T_1:Est.temp_min_T_1]\n",
" [Est.temp_min_T_2|Est.temp_max_T_2:Est.temp_med_T_2]\n",
" [S10.min_t|S10.max_T_2:S10.media_T_2:S2.media_T_2:S10.min_T_2:S10.15hs_T_2:S10.12hs_T_2:S10.18hs_T_2:Est.humedad_med_T_2:Est.temp_min_T_2:S10.max_T_1:S10.media_T_1:S3.media_T_1:S10.min_T_1:S10.15hs_T_1:S10.12hs_T_1:S10.18hs_T_1:S20.18hs_T_1]\n",
" [S14.min_t|S14.max_T_2:S14.media_T_2:S14.min_T_2:S14.15hs_T_2:S14.12hs_T_2:S14.18hs_T_2:Est.humedad_med_T_2:Est.temp_min_T_2:S14.max_T_1:S14.media_T_1:S14.min_T_1:S15.min_T_1:S14.15hs_T_1:S14.12hs_T_1:S14.18hs_T_1:S20.18hs_T_1]\n",
" [S18.min_t|S18.max_T_2:S18.media_T_2:S18.min_T_2:S18.15hs_T_2:S18.12hs_T_2:S18.18hs_T_2:Est.humedad_med_T_2:Est.temp_min_T_2:S18.max_T_1:S18.media_T_1:S18.min_T_1:S18.15hs_T_1:S18.12hs_T_1:S18.18hs_T_1]\n",
" [S20.min_t|S20.max_T_2:S20.media_T_2:S20.min_T_2:S3.min_T_2:S20.15hs_T_2:S20.12hs_T_2:S20.18hs_T_2:Est.humedad_min_T_2:Est.temp_min_T_2:S20.max_T_1:S20.media_T_1:S3.media_T_1:S20.min_T_1:S20.15hs_T_1:S20.12hs_T_1:S20.18hs_T_1]\n",
" [S4.min_t|S4.max_T_2:S4.media_T_2:S2.min_T_2:S4.min_T_2:S4.15hs_T_2:S4.12hs_T_2:S4.18hs_T_2:Est.humedad_min_T_2:Est.temp_min_T_2:S4.max_T_1:S4.media_T_1:S4.min_T_1:S4.15hs_T_1:S4.12hs_T_1:S4.18hs_T_1]\n",
" [S6.min_t|S6.max_T_2:S6.media_T_2:S6.min_T_2:S6.15hs_T_2:S6.12hs_T_2:S6.18hs_T_2:Est.humedad_med_T_2:Est.temp_min_T_2:S6.max_T_1:S3.media_T_1:S6.media_T_1:S6.min_T_1:S6.15hs_T_1:S6.12hs_T_1:S20.18hs_T_1:S6.18hs_T_1]\n",
" nodes: 271 \n",
" arcs: 2538 \n",
" undirected arcs: 0 \n",
" directed arcs: 2538 \n",
" average markov blanket size: 71.56 \n",
" average neighbourhood size: 18.73 \n",
" average branching factor: 9.37 \n",
"\n",
" learning algorithm: Hill-Climbing \n",
" score: BIC (Gauss.) \n",
" penalization coefficient: 2.890372 \n",
" tests used in the learning procedure: 813259 \n",
" optimized: TRUE \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"res"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Aprendizaje de parámetros "
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Time difference of 0.2008607 secs"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"start_time <- Sys.time()\n",
"fitted = bn.fit(res, training.set) # learning of parameters\n",
"end_time <- Sys.time()\n",
"end_time - start_time"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Imprimimos los parámetros para los nodos que nos interesan predecir"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"$S10.min_t\n",
"\n",
" Parameters of node S10.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S10.min_t | S10.max_T_2 + S10.media_T_2 + S2.media_T_2 + S10.min_T_2 + S10.15hs_T_2 + S10.12hs_T_2 + S10.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S10.max_T_1 + S10.media_T_1 + S3.media_T_1 + S10.min_T_1 + S10.15hs_T_1 + S10.12hs_T_1 + S10.18hs_T_1 + S20.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S10.max_T_2 S10.media_T_2 \n",
" -9.30256424 -0.01342298 -2.18785524 \n",
" S2.media_T_2 S10.min_T_2 S10.15hs_T_2 \n",
" 2.04693362 0.07033331 0.02792178 \n",
" S10.12hs_T_2 S10.18hs_T_2 Est.humedad_med_T_2 \n",
" 0.04512678 -0.12284425 0.04598495 \n",
" Est.temp_min_T_2 S10.max_T_1 S10.media_T_1 \n",
" 0.24185197 0.25488694 -2.04556827 \n",
" S3.media_T_1 S10.min_T_1 S10.15hs_T_1 \n",
" 2.69639834 0.25275199 -0.39643405 \n",
" S10.12hs_T_1 S10.18hs_T_1 S20.18hs_T_1 \n",
" 0.06819790 0.81450382 -0.68024661 \n",
"Standard deviation of the residuals: 2.228639 \n",
"\n",
"$S11.min_t\n",
"\n",
" Parameters of node S11.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S11.min_t | S11.max_T_2 + S11.media_T_2 + S2.media_T_2 + S5.media_T_2 + S11.min_T_2 + S11.15hs_T_2 + S15.15hs_T_2 + S11.12hs_T_2 + S11.18hs_T_2 + S11.max_T_1 + S19.max_T_1 + S11.media_T_1 + S11.min_T_1 + S11.15hs_T_1 + S15.15hs_T_1 + S11.12hs_T_1 + S11.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1\n",
"Coefficients:\n",
" (Intercept) S11.max_T_2 S11.media_T_2 \n",
" -5.38359328 -0.20043180 -1.11795025 \n",
" S2.media_T_2 S5.media_T_2 S11.min_T_2 \n",
" 4.21979095 -2.91111488 0.05962590 \n",
" S11.15hs_T_2 S15.15hs_T_2 S11.12hs_T_2 \n",
" -0.37360605 0.44116203 -0.03912620 \n",
" S11.18hs_T_2 S11.max_T_1 S19.max_T_1 \n",
" -0.05618647 -0.24507901 0.42936685 \n",
" S11.media_T_1 S11.min_T_1 S11.15hs_T_1 \n",
" 0.22925314 0.40319749 0.75161803 \n",
" S15.15hs_T_1 S11.12hs_T_1 S11.18hs_T_1 \n",
" -0.87003622 0.10404014 0.84433628 \n",
" S20.18hs_T_1 Est.humedad_min_T_1 \n",
" -0.71349952 0.02866686 \n",
"Standard deviation of the residuals: 2.226363 \n",
"\n",
"$S12.min_t\n",
"\n",
" Parameters of node S12.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S12.min_t | S12.max_T_2 + S12.media_T_2 + S12.min_T_2 + S16.min_T_2 + S12.15hs_T_2 + S12.12hs_T_2 + S12.18hs_T_2 + S12.max_T_1 + S12.media_T_1 + S12.min_T_1 + S12.15hs_T_1 + S1.15hs_T_1 + S12.12hs_T_1 + S12.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S12.max_T_2 S12.media_T_2 \n",
" -7.749959867 0.043205249 -0.194179764 \n",
" S12.min_T_2 S16.min_T_2 S12.15hs_T_2 \n",
" 1.127017439 -1.044164790 0.110098741 \n",
" S12.12hs_T_2 S12.18hs_T_2 S12.max_T_1 \n",
" -0.056579122 -0.117054485 0.189635592 \n",
" S12.media_T_1 S12.min_T_1 S12.15hs_T_1 \n",
" 0.545632236 0.297248162 -0.807042915 \n",
" S1.15hs_T_1 S12.12hs_T_1 S12.18hs_T_1 \n",
" 0.666320530 0.010365299 0.006321899 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.043774947 0.219336586 \n",
"Standard deviation of the residuals: 2.292081 \n",
"\n",
"$S13.min_t\n",
"\n",
" Parameters of node S13.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S13.min_t | S13.max_T_2 + S13.media_T_2 + S13.min_T_2 + S13.15hs_T_2 + S13.12hs_T_2 + S13.18hs_T_2 + S13.max_T_1 + S13.media_T_1 + S13.min_T_1 + S15.min_T_1 + S13.15hs_T_1 + S13.12hs_T_1 + S13.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S13.max_T_2 S13.media_T_2 \n",
" -6.83383972 -0.12427548 -0.15131542 \n",
" S13.min_T_2 S13.15hs_T_2 S13.12hs_T_2 \n",
" 0.05200633 0.19147116 -0.01945470 \n",
" S13.18hs_T_2 S13.max_T_1 S13.media_T_1 \n",
" -0.09897215 0.16469518 0.56219955 \n",
" S13.min_T_1 S15.min_T_1 S13.15hs_T_1 \n",
" -0.92642247 1.19115489 -0.34846207 \n",
" S13.12hs_T_1 S13.18hs_T_1 S20.18hs_T_1 \n",
" 0.08314260 0.70759974 -0.47771001 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.04125450 0.21469573 \n",
"Standard deviation of the residuals: 2.208016 \n",
"\n",
"$S14.min_t\n",
"\n",
" Parameters of node S14.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S14.min_t | S14.max_T_2 + S14.media_T_2 + S14.min_T_2 + S14.15hs_T_2 + S14.12hs_T_2 + S14.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S14.max_T_1 + S14.media_T_1 + S14.min_T_1 + S15.min_T_1 + S14.15hs_T_1 + S14.12hs_T_1 + S14.18hs_T_1 + S20.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S14.max_T_2 S14.media_T_2 \n",
" -8.50029907 -0.01882879 -0.09106967 \n",
" S14.min_T_2 S14.15hs_T_2 S14.12hs_T_2 \n",
" -0.02081119 0.10540607 -0.01690430 \n",
" S14.18hs_T_2 Est.humedad_med_T_2 Est.temp_min_T_2 \n",
" -0.11868927 0.04797588 0.22398188 \n",
" S14.max_T_1 S14.media_T_1 S14.min_T_1 \n",
" 0.30250116 0.59488988 -1.24604528 \n",
" S15.min_T_1 S14.15hs_T_1 S14.12hs_T_1 \n",
" 1.51159671 -0.38648711 0.02508990 \n",
" S14.18hs_T_1 S20.18hs_T_1 \n",
" 0.55221527 -0.40713132 \n",
"Standard deviation of the residuals: 2.179948 \n",
"\n",
"$S15.min_t\n",
"\n",
" Parameters of node S15.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S15.min_t | S15.max_T_2 + S10.media_T_2 + S15.media_T_2 + S15.min_T_2 + S15.15hs_T_2 + S15.12hs_T_2 + S15.18hs_T_2 + S14.max_T_1 + S15.max_T_1 + S15.media_T_1 + S6.media_T_1 + S14.min_T_1 + S15.min_T_1 + S15.15hs_T_1 + S15.12hs_T_1 + S15.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S15.max_T_2 S10.media_T_2 \n",
" -7.65859467 -0.15853132 -2.04584818 \n",
" S15.media_T_2 S15.min_T_2 S15.15hs_T_2 \n",
" 1.89879881 0.04976466 0.15325134 \n",
" S15.12hs_T_2 S15.18hs_T_2 S14.max_T_1 \n",
" 0.02541374 -0.05664806 0.61480362 \n",
" S15.max_T_1 S15.media_T_1 S6.media_T_1 \n",
" -0.41025521 -1.48825774 2.05819697 \n",
" S14.min_T_1 S15.min_T_1 S15.15hs_T_1 \n",
" -1.57308927 1.84347073 -0.40493602 \n",
" S15.12hs_T_1 S15.18hs_T_1 S20.18hs_T_1 \n",
" 0.06550042 0.74962225 -0.51106179 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.04258080 0.21974087 \n",
"Standard deviation of the residuals: 2.170958 \n",
"\n",
"$S16.min_t\n",
"\n",
" Parameters of node S16.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S16.min_t | S16.max_T_2 + S16.media_T_2 + S16.min_T_2 + S16.15hs_T_2 + S16.12hs_T_2 + S16.18hs_T_2 + S16.max_T_1 + S16.media_T_1 + S16.min_T_1 + S7.min_T_1 + S16.15hs_T_1 + S16.12hs_T_1 + S16.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S16.max_T_2 S16.media_T_2 \n",
" -5.873193621 -0.051999793 -0.130875105 \n",
" S16.min_T_2 S16.15hs_T_2 S16.12hs_T_2 \n",
" 0.001309272 0.075069501 -0.003014525 \n",
" S16.18hs_T_2 S16.max_T_1 S16.media_T_1 \n",
" -0.073414904 0.329203616 0.446353835 \n",
" S16.min_T_1 S7.min_T_1 S16.15hs_T_1 \n",
" -0.432078137 0.800558946 -0.353596401 \n",
" S16.12hs_T_1 S16.18hs_T_1 Est.humedad_min_T_1 \n",
" 0.102530401 0.033597051 0.029310002 \n",
" Est.temp_min_T_1 \n",
" 0.207942901 \n",
"Standard deviation of the residuals: 2.338585 \n",
"\n",
"$S18.min_t\n",
"\n",
" Parameters of node S18.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S18.min_t | S18.max_T_2 + S18.media_T_2 + S18.min_T_2 + S18.15hs_T_2 + S18.12hs_T_2 + S18.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S18.max_T_1 + S18.media_T_1 + S18.min_T_1 + S18.15hs_T_1 + S18.12hs_T_1 + S18.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S18.max_T_2 S18.media_T_2 \n",
" -8.4210379742 0.0755565813 -0.1841843927 \n",
" S18.min_T_2 S18.15hs_T_2 S18.12hs_T_2 \n",
" 0.0195152679 -0.0018178534 -0.0030741372 \n",
" S18.18hs_T_2 Est.humedad_med_T_2 Est.temp_min_T_2 \n",
" -0.0864903219 0.0426711399 0.2346367993 \n",
" S18.max_T_1 S18.media_T_1 S18.min_T_1 \n",
" 0.3310856673 0.5707137368 0.3067404307 \n",
" S18.15hs_T_1 S18.12hs_T_1 S18.18hs_T_1 \n",
" -0.3128770827 0.0406207875 0.0007854315 \n",
"Standard deviation of the residuals: 2.264661 \n",
"\n",
"$S19.min_t\n",
"\n",
" Parameters of node S19.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S19.min_t | S19.max_T_2 + S19.media_T_2 + S19.min_T_2 + S19.15hs_T_2 + S19.12hs_T_2 + S19.18hs_T_2 + S19.max_T_1 + S15.media_T_1 + S19.media_T_1 + S19.min_T_1 + S19.15hs_T_1 + S19.12hs_T_1 + S15.18hs_T_1 + S19.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S19.max_T_2 S19.media_T_2 \n",
" -7.43753153 -0.07157427 -0.12836954 \n",
" S19.min_T_2 S19.15hs_T_2 S19.12hs_T_2 \n",
" 0.03741751 0.07970556 -0.03115687 \n",
" S19.18hs_T_2 S19.max_T_1 S15.media_T_1 \n",
" -0.04809304 0.42050548 -1.72540628 \n",
" S19.media_T_1 S19.min_T_1 S19.15hs_T_1 \n",
" 2.15761365 0.30363606 -0.46857670 \n",
" S19.12hs_T_1 S15.18hs_T_1 S19.18hs_T_1 \n",
" 0.15443943 0.69656993 -0.59536324 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.03503915 0.20683282 \n",
"Standard deviation of the residuals: 2.278494 \n",
"\n",
"$S1.min_t\n",
"\n",
" Parameters of node S1.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S1.min_t | S17.max_T_2 + S1.max_T_2 + S1.media_T_2 + S1.min_T_2 + S1.15hs_T_2 + S1.12hs_T_2 + S1.18hs_T_2 + S1.max_T_1 + S1.media_T_1 + S1.min_T_1 + S1.15hs_T_1 + S9.15hs_T_1 + S1.12hs_T_1 + S1.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S17.max_T_2 S1.max_T_2 \n",
" -6.7623568100 0.5272223661 -0.6225668341 \n",
" S1.media_T_2 S1.min_T_2 S1.15hs_T_2 \n",
" -0.0916903847 0.0494900343 0.0527190576 \n",
" S1.12hs_T_2 S1.18hs_T_2 S1.max_T_1 \n",
" -0.0009521682 -0.0419176512 0.0553057017 \n",
" S1.media_T_1 S1.min_T_1 S1.15hs_T_1 \n",
" 0.4135229680 0.3482358427 0.5764928457 \n",
" S9.15hs_T_1 S1.12hs_T_1 S1.18hs_T_1 \n",
" -0.6266113744 0.0862743370 0.0712484807 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.0375717608 0.2320723004 \n",
"Standard deviation of the residuals: 2.28297 \n",
"\n",
"$S20.min_t\n",
"\n",
" Parameters of node S20.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S20.min_t | S20.max_T_2 + S20.media_T_2 + S20.min_T_2 + S3.min_T_2 + S20.15hs_T_2 + S20.12hs_T_2 + S20.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + S20.max_T_1 + S20.media_T_1 + S3.media_T_1 + S20.min_T_1 + S20.15hs_T_1 + S20.12hs_T_1 + S20.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S20.max_T_2 S20.media_T_2 \n",
" -8.742566079 0.055605013 -0.038156817 \n",
" S20.min_T_2 S3.min_T_2 S20.15hs_T_2 \n",
" 1.210793069 -1.282903924 -0.019091052 \n",
" S20.12hs_T_2 S20.18hs_T_2 Est.humedad_min_T_2 \n",
" -0.003420068 -0.116277204 0.042472321 \n",
" Est.temp_min_T_2 S20.max_T_1 S20.media_T_1 \n",
" 0.245548968 0.161767158 -1.704109345 \n",
" S3.media_T_1 S20.min_T_1 S20.15hs_T_1 \n",
" 2.428011220 0.266384144 -0.216215257 \n",
" S20.12hs_T_1 S20.18hs_T_1 \n",
" 0.055707408 -0.011477621 \n",
"Standard deviation of the residuals: 2.251307 \n",
"\n",
"$S2.min_t\n",
"\n",
" Parameters of node S2.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S2.min_t | S2.max_T_2 + S2.media_T_2 + S2.min_T_2 + S2.15hs_T_2 + S2.12hs_T_2 + S2.18hs_T_2 + S2.max_T_1 + S2.media_T_1 + S9.media_T_1 + S2.min_T_1 + S2.15hs_T_1 + S2.12hs_T_1 + S15.18hs_T_1 + S2.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S2.max_T_2 S2.media_T_2 \n",
" -6.889469578 -0.176402372 -0.068139935 \n",
" S2.min_T_2 S2.15hs_T_2 S2.12hs_T_2 \n",
" 0.020624789 0.195937882 0.003598383 \n",
" S2.18hs_T_2 S2.max_T_1 S2.media_T_1 \n",
" -0.143194983 0.362734688 3.071550994 \n",
" S9.media_T_1 S2.min_T_1 S2.15hs_T_1 \n",
" -2.577398607 0.385674554 -0.394713741 \n",
" S2.12hs_T_1 S15.18hs_T_1 S2.18hs_T_1 \n",
" 0.033929944 0.551457531 -0.431775186 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.039118224 0.199926206 \n",
"Standard deviation of the residuals: 2.193549 \n",
"\n",
"$S3.min_t\n",
"\n",
" Parameters of node S3.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S3.min_t | S3.max_T_2 + S19.media_T_2 + S3.media_T_2 + S3.min_T_2 + S4.min_T_2 + S3.15hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S14.18hs_T_2 + S3.18hs_T_2 + S19.max_T_1 + S3.max_T_1 + S10.media_T_1 + S3.media_T_1 + S3.min_T_1 + S3.15hs_T_1 + S3.12hs_T_1 + S20.18hs_T_1 + S3.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S3.max_T_2 S19.media_T_2 \n",
" -5.97211128 -0.10992528 -1.83521843 \n",
" S3.media_T_2 S3.min_T_2 S4.min_T_2 \n",
" 1.80667331 -1.35411379 1.43076766 \n",
" S3.15hs_T_2 S2.12hs_T_2 S3.12hs_T_2 \n",
" 0.14707226 0.64007409 -0.76789585 \n",
" S14.18hs_T_2 S3.18hs_T_2 S19.max_T_1 \n",
" 0.78417566 -0.88820362 0.80628659 \n",
" S3.max_T_1 S10.media_T_1 S3.media_T_1 \n",
" -0.59969095 -3.00259517 3.51056035 \n",
" S3.min_T_1 S3.15hs_T_1 S3.12hs_T_1 \n",
" 0.32253213 -0.26665794 0.16228082 \n",
" S20.18hs_T_1 S3.18hs_T_1 Est.humedad_min_T_1 \n",
" -1.01476874 1.02881248 0.03079648 \n",
" Est.temp_min_T_1 \n",
" 0.21588943 \n",
"Standard deviation of the residuals: 2.066144 \n",
"\n",
"$S4.min_t\n",
"\n",
" Parameters of node S4.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S4.min_t | S4.max_T_2 + S4.media_T_2 + S2.min_T_2 + S4.min_T_2 + S4.15hs_T_2 + S4.12hs_T_2 + S4.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + S4.max_T_1 + S4.media_T_1 + S4.min_T_1 + S4.15hs_T_1 + S4.12hs_T_1 + S4.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S4.max_T_2 S4.media_T_2 \n",
" -7.578250595 -0.030993294 -0.147853553 \n",
" S2.min_T_2 S4.min_T_2 S4.15hs_T_2 \n",
" -1.099932833 1.127160180 0.127682713 \n",
" S4.12hs_T_2 S4.18hs_T_2 Est.humedad_min_T_2 \n",
" -0.001900020 -0.119673151 0.040657791 \n",
" Est.temp_min_T_2 S4.max_T_1 S4.media_T_1 \n",
" 0.210646632 0.393414676 0.443989716 \n",
" S4.min_T_1 S4.15hs_T_1 S4.12hs_T_1 \n",
" 0.364058038 -0.345019721 0.064783528 \n",
" S4.18hs_T_1 \n",
" -0.001810854 \n",
"Standard deviation of the residuals: 2.173136 \n",
"\n",
"$S5.min_t\n",
"\n",
" Parameters of node S5.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S5.min_t | S5.max_T_2 + S2.media_T_2 + S5.media_T_2 + S5.min_T_2 + S5.15hs_T_2 + S5.12hs_T_2 + S5.18hs_T_2 + Est.humedad_min_T_2 + S5.max_T_1 + S5.media_T_1 + S5.min_T_1 + S17.15hs_T_1 + S1.15hs_T_1 + S5.15hs_T_1 + S5.12hs_T_1 + S5.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S5.max_T_2 S2.media_T_2 \n",
" -6.529999890 0.006592258 4.049314112 \n",
" S5.media_T_2 S5.min_T_2 S5.15hs_T_2 \n",
" -4.008203178 0.127735661 0.034194876 \n",
" S5.12hs_T_2 S5.18hs_T_2 Est.humedad_min_T_2 \n",
" -0.019197348 -0.129232361 0.030275470 \n",
" S5.max_T_1 S5.media_T_1 S5.min_T_1 \n",
" 0.333359232 0.261861924 0.425484233 \n",
" S17.15hs_T_1 S1.15hs_T_1 S5.15hs_T_1 \n",
" -0.561460709 0.908684642 -0.551950919 \n",
" S5.12hs_T_1 S5.18hs_T_1 \n",
" 0.070570257 0.034146104 \n",
"Standard deviation of the residuals: 2.294514 \n",
"\n",
"$S6.min_t\n",
"\n",
" Parameters of node S6.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S6.min_t | S6.max_T_2 + S6.media_T_2 + S6.min_T_2 + S6.15hs_T_2 + S6.12hs_T_2 + S6.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S6.max_T_1 + S3.media_T_1 + S6.media_T_1 + S6.min_T_1 + S6.15hs_T_1 + S6.12hs_T_1 + S20.18hs_T_1 + S6.18hs_T_1\n",
"Coefficients:\n",
" (Intercept) S6.max_T_2 S6.media_T_2 \n",
" -8.790456136 -0.084717177 -0.097490791 \n",
" S6.min_T_2 S6.15hs_T_2 S6.12hs_T_2 \n",
" -0.001825582 0.154641990 -0.012737325 \n",
" S6.18hs_T_2 Est.humedad_med_T_2 Est.temp_min_T_2 \n",
" -0.133343160 0.046651245 0.245336765 \n",
" S6.max_T_1 S3.media_T_1 S6.media_T_1 \n",
" 0.271448558 1.369492230 -0.728650017 \n",
" S6.min_T_1 S6.15hs_T_1 S6.12hs_T_1 \n",
" 0.269578707 -0.324135355 0.023756305 \n",
" S20.18hs_T_1 S6.18hs_T_1 \n",
" -0.536702739 0.633381112 \n",
"Standard deviation of the residuals: 2.205021 \n",
"\n",
"$S7.min_t\n",
"\n",
" Parameters of node S7.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S7.min_t | S7.max_T_2 + S7.media_T_2 + S7.min_T_2 + S7.15hs_T_2 + S7.12hs_T_2 + S7.18hs_T_2 + S7.max_T_1 + S7.media_T_1 + S9.media_T_1 + S7.min_T_1 + S7.15hs_T_1 + S7.12hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S7.max_T_2 S7.media_T_2 \n",
" -7.56322558 -0.16158885 -0.09059050 \n",
" S7.min_T_2 S7.15hs_T_2 S7.12hs_T_2 \n",
" 0.03310885 0.20480927 -0.04025249 \n",
" S7.18hs_T_2 S7.max_T_1 S7.media_T_1 \n",
" -0.09182653 0.26504258 2.16842383 \n",
" S9.media_T_1 S7.min_T_1 S7.15hs_T_1 \n",
" -1.82739253 0.36543042 -0.28027740 \n",
" S7.12hs_T_1 S6.18hs_T_1 S7.18hs_T_1 \n",
" 0.04852016 1.50203484 -1.32668137 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.03556491 0.21446792 \n",
"Standard deviation of the residuals: 2.289497 \n",
"\n",
"$S8.min_t\n",
"\n",
" Parameters of node S8.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S8.min_t | S8.max_T_2 + S8.media_T_2 + S8.min_T_2 + S8.15hs_T_2 + S8.12hs_T_2 + S1.18hs_T_2 + S8.18hs_T_2 + S8.max_T_1 + S3.media_T_1 + S8.media_T_1 + S8.min_T_1 + S10.15hs_T_1 + S8.15hs_T_1 + S8.12hs_T_1 + S20.18hs_T_1 + S8.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S8.max_T_2 S8.media_T_2 \n",
" -8.34568696 -0.19894680 -0.12587194 \n",
" S8.min_T_2 S8.15hs_T_2 S8.12hs_T_2 \n",
" 0.05293500 0.21616698 0.01027862 \n",
" S1.18hs_T_2 S8.18hs_T_2 S8.max_T_1 \n",
" -0.71567476 0.60749562 0.16733804 \n",
" S3.media_T_1 S8.media_T_1 S8.min_T_1 \n",
" 3.00422064 -2.41558499 0.31100690 \n",
" S10.15hs_T_1 S8.15hs_T_1 S8.12hs_T_1 \n",
" -0.83434695 0.53924651 0.09393669 \n",
" S20.18hs_T_1 S8.18hs_T_1 Est.humedad_min_T_1 \n",
" -0.56014153 0.68362056 0.04191800 \n",
" Est.temp_min_T_1 \n",
" 0.24031405 \n",
"Standard deviation of the residuals: 2.297344 \n",
"\n",
"$S9.min_t\n",
"\n",
" Parameters of node S9.min_t (Gaussian distribution)\n",
"\n",
"Conditional density: S9.min_t | S9.max_T_2 + S9.media_T_2 + S9.min_T_2 + S9.15hs_T_2 + S9.12hs_T_2 + S9.18hs_T_2 + S14.max_T_1 + S9.max_T_1 + S2.media_T_1 + S9.media_T_1 + S9.min_T_1 + S9.15hs_T_1 + S9.12hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1\n",
"Coefficients:\n",
" (Intercept) S9.max_T_2 S9.media_T_2 \n",
" -6.691344831 -0.126087737 -0.153631113 \n",
" S9.min_T_2 S9.15hs_T_2 S9.12hs_T_2 \n",
" 0.043145482 0.143037770 -0.003607565 \n",
" S9.18hs_T_2 S14.max_T_1 S9.max_T_1 \n",
" -0.102104927 0.534993300 -0.226922148 \n",
" S2.media_T_1 S9.media_T_1 S9.min_T_1 \n",
" 2.273437776 -1.644002708 0.336861563 \n",
" S9.15hs_T_1 S9.12hs_T_1 S9.18hs_T_1 \n",
" -0.333622768 0.041907474 0.017032990 \n",
"Est.humedad_min_T_1 Est.temp_min_T_1 \n",
" 0.034171910 0.239195693 \n",
"Standard deviation of the residuals: 2.320973 \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fitted[pred_sensores]"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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h5ko43XY41NPRCXjrh0JD/yFEwPR2TrUbPMY3tm63HwFpp45OOIGo1m2LBhS5cu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\ngEZQ7AAAADSCYgcAAKARFDsAAACN+P9EXGmDdeOZYgAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bn.fit.qqplot(fitted$S14.min_t)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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m177xp8tYVkM665ukJAYirfbmVcz7SqDnAy8Xhj9oQzdnOOCjugsh//1yU3U4lI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Sl8m35/CN4Mokdb8MMNKlngUXo5Q7Ti5F\nY65ffjeVMhCUSFY+Pq7K6z4NmHSopBf5qTtP0nj/ON3q4hdJeAoXopjRqkTFhS8nPIVfrhCU\niLaIJrZ87FVSt2xIQxacY3ZrhTd/0QVsjWn7GlGNdQF8eZbUXAx1ycrH25kVfRjkRgcH1gUQ\nEIehLp94MbGFCq/OoyYnHyk3Pp8Mx0hX/ZKwjW1ZdJHOjspfqHOP6aPukfbt7LkzjSsxhKdg\nYUCr2q/rOr8+9S1YVYKyRbXzjR8/XWRqS9kMlcMPGbCTT7z4vpibezycNTcIS8FMn7Z2fNlR\nQdnn1lO6/kkjG77rgpURgQl86cvfQRwdJftcnX/C2gCuTpIHeoc0pH0dPj7FkIZqEAkqOZ0d\nAVZc46MXmp1jMvjrPr/0Kj8zBNSC4Ni9Idib0aMe805yaIQ8bnc3nhXXVMwpUi/fnuMHf4Y3\nZnhjsvLZFcjaAI6OpGUpVenDU/DZSVoe3s5YG3E4lJ8ustqbKR5oifjclw9PYqJHZj7uNpwa\nQ1O1dgX+y8xWLPRXGMEelMgnp5nsUalbw55HE4vHGg2K1f6/BEMdDgzn5CPZfPq29izuoYYS\nq013mH6ENnb0daZQwoEQ/viNbYNUuKHFmeLB3gc0+52P2sm6Yjfe5vQjDo4odXb4X36+xPfn\nWdKTCc3R1+ZhMrOP034jd6ZhY/zq4aefeOGzk6a2TGwuU6K+EsPs48xqrf55X72dqGXKlMP8\n4SP7XhdJWXSB4CT2DFXzXoCOFh3q0OHtloILTGDRBY6MlKfge9bH25l3/mJoI9xfKLicfJg/\n7zC6CT3rkyFmdxB/3uX4KDz/+ekYf5B3XNgyUJbc7+PEiMa0XMdv1/mwLcDuIPo6K6fvp3nw\ngz9HHjJerX3fL8dcn197MeUwocm82xATPW7E8dNFmtdUkN0RqBKIpG+BCuHJkyd9fHzy8iqx\nPqw6iEqn+xYy8xndhDrmXI9lVyDDGrN5gAbV7M5G0msbh0fIfwQLJUw6xMUogmeV4tZbJMVj\nLbXN2DFYVpsllbLqBvNOEjCFJrZk5XMvXtbs2dhGg4XSEikzjrL+Fl0caWLLw2ROPmJAA7YN\nqtR6Tql52C7h6ChlgbfPffGL5KoGopsl5FEqDVfxay9m/BP2k0pZcJ5frxI+p0QxiQIJq2+w\nLoDwFMz18arDom5lb/ROF1NzKev7M+qFgtQCCa3W0bN+SUcD/36TT89Q2xS36jzN5EYck1vw\nvz5l9zVfwr14Bu0iM58+Thjp4htJQjZ/9Jc1u6ikUMLK6xwOlVWFDm7IVA+Zb1EG7jzjWixa\nIjztFNyayszRMA6GEJWOnRl9nV/2XhXnu/McDeNasa+M5wb6OMvnIO8NZvQ+/MfLG18kUiYf\n5vxjQmaho0VQIo1X83guDoqFud/7cyiUG5MB+u2ggTVLin3qOm+mS135XuXG+Sd8foaAp+QX\nYWfGrNbM86zUD7SVAUNDw/379/fuXaw0u+IQInZvDnXMuT+D365z7jEXnlDPgoMjylgXUnI2\n3WGwm0J1uY4W/+uDzRL8n9CtxML0z2cWnRojr7gXiZjVmkOhrA1gVV9M9GhXLgXFWiJ+f4dx\nzTgQwpN03Koz15Pu9cgv4n4CtU0r6UxxCwNGujPnOCdGy28kvpGsuMYa74o0bPs9GtvIvTpA\nJOKbTmy6w94HJdK309Xi/Ta830Y99lyJRoryaEtdLUa4v6yDODmXoATszWXyhNNaMqAB+0N4\nkIinHWv7adDjaWJL0Ew23ebWU7ILGN+MiS1e5hAn59JnGxGpTPbgXXMiUvn8DH8HcWRkqQOK\nsZlMP8KJcOpZIIWIVHxcWeVdqdsX8osYvocjD+nvirstUemM3EuXuuwdWtKXH5tJfVViePUt\niX1h8ODWu4x0V2hn1hLxc3dqLuNyNB0diErHUEfZqwNcrYhKl/23lSFPVU3be5ZVMT0rnRy4\nPJFCCflFag4/Z+WzP4SwZMz08aojz4cIaALBsXuj0Nfmw7ayIH/5EJasQtfUXJ96FoSnlMKx\nC0rAxQqbf24Y+UUEJvA4DUcL7sWrzdqS42knz6ckZDPlMH/elQ3LalWLX3qVdNJAebKyL4N3\n0WgVA92wNSY4iVOP+KhdBWdSwlLkajV+j5l/jrvPKJSgq8Xx8LILF5eZDDFm+ipCa1aGZIhV\nHP8olQ9OyhUfGljzv970rE8Nk/Irb9fXVnijCiQsvsTxcGIzcKzGsMZMeGE88aenycznwUz5\nt2muJ+03Mv9cSeOR/+7SdzsmegTPkjk6ocmM2cc7f3F1kuokQF4h8dnUNq1I5ZEfLnA1hnvT\n5fWOkWl0/ZMvz/JryWrFqhupHtoWk6HQrBqRSrdi40+sjahtSmQaHR2wMCCvkLQ85frIZ1ly\nAUJvFyYcJDJNrmcOHA8nPEW5F7s80dFS81/wbCTjD5JTQMPqZIj57Awj3Pn9HY0oGwgg6NgJ\nvCbGeqpHoKblle6BT1cbcaHsv89E0GQNHusYf5D1AdyIZUegGkwtG/HZtFrP7WccH0XCxzyY\nSRs7uvzJ/pAKM+m/MNXj1Bj+GoyJHsFJNKrOzSn82K38DIjJ4JcrzDrGt+fwjZQt/jtBYell\nem7F1YqNPmwfjLE+x8J4/0T5mfecuhYk5RBbLExyN17F0ILoDNpuQFzI3WkUfE3sB/R3xfsv\n9gaXj7EqiM+m1TqWXaGdPfPa0tiGuSfw/ou8QoD8InYG8mM3uVcH1DZlQWc23ynd9M89D4hK\n58hIefjK1YojIwlJ4nAxYbObcXTYhPEiHJdjvIhR+1S8w+WAVMq6AL7qqNDFUrca33Vh0+2S\n9hF7u3A5mptxCos347gYpdAxY6avQnBHIiUtT5Z28KiFtRFrFeUG84vYeJte/zhtg91oWYsO\nG9kRSFwmkWksu8K7u/m0veqoYVUkNJm+2/Fx5clczo/j9lSuTeZ6LOMOVLRlby5CxE7gtejo\nwLZ7LOisUIfxvAyoVCXYrWvzKJX7CWSK6budGa3wH4+1Ee5rsDFm7H5EMLyxihMDE7jzDAtD\nWtfWSBPZkkuY6eM/XjY7oboRK/tgZcisY/R3rYyjePu7yhVPypM1N/n4FLXNaFide/EsukBv\nJ/4aTEcHph8l4Clf+LJ1oOyP+CiVhCyW9OTDkwxrVE5J9ud41KSBNZ+c5s8B8rDE3Xg23WbN\nO8oHLziHixVHR8n+0LVM+bk7xrrMPcHABmWvWnsd5p0ACJ4pLwmY0wavjfx0kfmdicsku0C5\nNR5oWoPEHNLEpRhWcTmazo7Kx9sY074Ol6Llc+eAs5H03saQhlyaQF0LAuJY6E+rdVyfXN6N\n5GlinmXhVeyXx8uedDFPM0ukQ9nWjvea0nMrX3WUfZUOP2ShP2OaKHxQu9VjdxBfKI5SPRBC\nbqEsnK+rxbJeTDhIUg4TmmNlSFAi3/qRmMPn7WXHa4k4PoqF/ow7IEsIWBqyok+5tk1omhXX\naGPHij7yFY+abB9E6/XKoUoBdSE4dgKvxezWrA+g3w6W98bNmkIJe4N5/zhTPXAszTe2qS39\nXBi+B2NdhjZieW+Sc5l4iLhMTo9hbQCf+zKskTzfBISlMOMovhHUMiUrn/wiPvbi645qTiIc\nC2N6K+WJWO97suA8t5+WuvP3TcU3kjnH+f0deU4wJIlBu5h6mC0DWXYFnx3UMGV4YyRSzkYy\n6xidHXm/NUdC2Rtcro6dloitA+mxlaa/M6IxFobcecaWuwxrpNBO8ZyTj/i+i7L7PrUl354j\nKLECOgmyC9gXzKERCoWejtX4uiM/XmR+Z4z1ABVB9LQ8tESlC6LnFarOlBnpyoPrz5l1jCke\n8nFqfZ3pUR+vP5h/jg39VVxBIuVJOtn5OFupuSHpuYx58dlozyeClGSS73PW96NlLb4/z4en\nAGyNWdBZuWxgrieb79B7G6v60rA64iK23eODk3zWXv6EOaYJ1Qz44CRLL8tWhjRk2yBqvKAM\nZ6DDwq5804nwFPR1cKxWGR8XX4frscolrUDLWlQ35nqs4NhpBMGxE3gtLA3xG8eMozRchY0x\nWflIpXzUjq9L38+1dRBTDrM7iGfZtP2Du8+oa8GJ0dQyZZQ7350nKkNeiZycS+fNNLUlap4s\nKnD4IZMPkZxTonmdJScpR4U+p4UBBjpqnnxQpVl+leGNmdhcvtLAmtXedNvCsl4cH0XnPwlO\nxGoxRRKy8pnUgsU9EIlwtlIoSC8fWtTk4Wx+vMCRh6Tl4WQpH9ehRGou1Ys1ClgbIYLU3HKw\nVJknaYiLVAfkotIRF1HdiIbV2X5f+Zjt9/C0K50X1cCaNTeQSBUCk4USrsfKA07Ao1SCkzg4\nQuFcXS1mtOJzX+VrSqWsv8VXZ0nMAdDRYlpLvuuitqG3hjo0r8H+YOXJDfuCcbZUSE+/HB0t\nZrZiZisSc5BKVZ9oYYD/eOaeoNFqjHXJK8TcgB+6Kos+9nOhnwuxmSTnUM8Ck2Ia8s/R06Zh\n9ZKaV7V4XlBbHF2tSi35XqURHDuB18XZktNjCEniYTImejSxLWM/l7k+WwayO4hR7tga820n\nutWT/SI8rz5+cYTGimuY6yuImfVzYccQum/hE68SJVxKSC1THiYrL0ZnkFeIvfp2qercfaZi\nOkVHB3S1uB9Pz/qMa8qfd1nSA20tGtvIlW9jM3CoiEd2K0OW9nz1YXXMeZCIt6IUcHAiUtT5\nGSs5/wbklFyNtDz0tdHTAljUjSG7MdZlrifVDEjOZfElNt3h5OjS7TXSnfnnmH+O+Z1lvl2R\nlC/PkpWvEIB5/nhTPOVqb67iyecrP1Ze45tODHTDWJerMXzhy+VoLk9UW+huQRcG7aKmKe+3\nQUcLiZTfb/KDP38OLMvVXl7d4WDO/mFEZ3D3GVZGNLX9z1vbYWQAACAASURBVJhobdOKV3uu\nKJrY4veYuZ4Kiw+TicusMuo5VQ7BsRNQDw2s1SC7r69NHXPszJSfem8/k/2vf/F/wiA35QfB\nLo5UN+JClIqcWpkZ0pA1N5nioeCtfnceVysaqnvMQNVFJEKiqjBfyj/SrM587ouJnsIguJAk\nTkewf1g5GVkGhjfmf1cZ00SeOyuS8tVZPO1KV2mgLuqY4ViN7fdZ0Flhffs9OjjIkuA+ruwY\nzLyTLDiPmT4ZYupZcHA4XUvcov6cmiZsH8R7+9kfQicHpOAXybMsdgxW+C4891cepdBY8Sb9\nKIVaiq5MVDqLL7F3KC1q8oUvZyOJz6aOOU/SWXuTOWqSs+nnwp8D+OAkiy5Qx5yYDKRS1rzD\nCFUVumrB3gz7SjyTpsKZ6kGHTawLYHIL2Uc0MYcph2lnTxPNiMwLCI6dQOVifDMWXaCPk7xF\nMTmXT0/zbiOFLEZ2Puaq0jfmBuQUqNOeD9pyKJQma/igLY1tSMph422uxnBqjELB31uOR01O\nPWKcYsX3uccUSWhaA8Ddhlmt6beDhV3p54KOFmcj+eQ0fZwqUtbhlXzsxclHNFrNzFa4VSch\nmz9uEZfJ+fEVY49IxI/deG8/+trMao2ZPgnZLLrA7iDOjZMfNqQh3i7cj5cJFLvbljEe1t+V\n0Nn8dp3ABETwbiNmt1aOx9uZ4WnH9/7sHCz/RmSI+fUqQxoqHHk2Ehtj7MxotJrGNvzQDVtj\nQpP56ixf+zG2mXwS7msy0p13XPB/QlgK9S3o6FDGCYcCaqGdPSv7MPcEq27QoiYZYs5EUM+C\nwyNefa5A2RAmTwhULsRFDNyJ32NGN6GpLWEpbL1LXQtOjcHqhYLxUfsoKGL3uwrnJuVQaxkn\nx9DFUc0m/XKFP+/wKBVrIzo5sKibCmmMt5nL0XTazM/dmespC9HdecbAXXSvx/p+smMkUjbd\n4Rs/4jIBLA35vD1z2lR2XftCCatvsP0+kanYGMvmAVSIeOy//HWfj07xNEsWkHOxYlVfuhfT\nVCs37sbTcRMNqzOrNfUsCIhj6WWM9bg4QaF47terbL2Ljhb1LNjxghf4pS+/XmVW69LJ7AlU\nLZ6ks/mOTKC4nT0j3N+cHpFKOHlCcOzeHKLSORRKaDJ1q+HtgqtVRRv0GuwKYmcgIUnUrUZ/\nVya1UO51PRNB720cHUWv+rKVAgkTDnIthgczK1If9a1l+33mHMfKkEY2JOdwNYZhjVnXT7mh\nGHiSTkER9S2EkGfZySngfoJMoLixTcU7xzEZfHmWs5E8zaSuBcMb81l75abaPQ+YcJDMfAJn\n0OiFRoHR+whLJiWPsNnlbLWAgBqohI6dkIp9Q1hymfnncLLEyZJrMXx2hnlt+bFbxUhtvT7D\nGjGsWIf8i3Svx+cd6Lsdb2da1iIrnwMhpIs5Nkrw6iqGUe70dmJfMPfjaV2bX3r9pxZM8SFL\nAqXFSJc2taG27J8nwll6meAk9LVpXpMFnZUr3kpOah7XY//P3nkGNHW2YfgKe+8hoLhAHOAC\nFw5wb3HvWbfW1lZrrZ+tra2ttmq1WrUWt3VvRcSBe+8BKojKEAFlzwDhfD+IjcFUBQMBzPWL\nvDnjSUhynvO+z3PfRKVQ2ZQmFTH+jy7OAlQ0YUPPd2zTobr058jZQjZ4LZqdwXzbip/OFDHg\nss6TJPIEqpmp73PUKA11Ylce2HyH706y1ofYNA6GkJSFqw3LrmCqx6wW7969jPJja3q4sOIq\nAWEY6TDIjS+bKa1MR00RsNRnbENVB/HxMe0oyy4zqgHD6yGWcCiEBn+xzoehdQt9KN8bzDxO\nVi7VzAlNwFyP3zu94xbr/THRZV5bPj1Mj6180gBDHc5H8PslhtejkqmKV7dLHomA7w2+P0VM\nGoCVAbNbMamRYmUQNWoKhTqxKw/8ep7PmvDreaJSGN2AvrUJTyI0gTknGftWv/AyRGo2a25w\nNw5BwM2WMQ0x1qGRPet8VB2ZmtLE0yQikqlt/bEkCmcjWHKJwBF4vWo3HtuQ3y8x0Y+OTgq+\n+7diCAgjKgVXG3rXktvgn7tMPszCDkzwQFuDrFx+v8TQPRjpFBR8KTKTG7HwIk+SmHqE1Gzq\nV2BbXzo70XIdXWu8e/fyxOj97H/IL23p7IyGiOOP+foYl6LY2kfVkakp+6gTuzJPtoR7cVQz\nJ1tCyBRZtfKQutRdyWf+5eGX4kw4A3ehpUELR0Qillzit/Ns6YN3leI9b55ARs5/aoqqKVUE\nPuHzI9yLkz7s7MTSznKrfuWSbffoWF2W1eWTf5t3KETOmSorl8mH2XibJg7YGHIsjJnH+b2j\nrJf5u5N824opjaUP9bT4pgUv0vn+VBETu6QsfrtA4BPiM2hQgRktcLdjdTe6/sOwenzRFFsj\nHrykzQaiUkq16o3SuRbN5juc+4SmFaUjo+rjYY/Hak4+VXLvl5qPEHViV+bJ1w878RhfH2lW\nl19YfSsG4FAIEqFs9x8lZtFnB/3rsKiD1BRILOGro/TZQcgUuVZZJXI7lhnHOBtOZi42hoys\nz+xW71tvpKbk2RXMwF183hT/IdgZ8+AlXx+jqS9Xx5bz/uX86ckCaIpwsSQiWW5w6hGOhnFx\ntLT2URBYdZ2xB6lkStuqPE/jcSK9ahU8VK9aLLmEWFJowZQrz+j8DzkSUrMBQhPYeZ+JHvzZ\nhXOf8GUAdVcigLYGA1zZ0a+g6F35xv8RjR1kWV0+bja0qcqhEHVip+ZDUSd2ZQyxhGNhhCZg\nokvTitSxRk+L6hY8SqCeLbySQkjIlM4zpWWzO1iBVV8ZYts9tDX4vaOs9U9Xk0Ud2fuArXf5\ntPFbdy4SR8PotoUeLuwbSCVTLkXx81n8QrgwGhN1DV/pQxCYcYyvWzDvlftFHWsODKLdRuac\nYlORLAfKCuZ6xKZL/87NY+U1Nt/hSSIpYvIEJjeSLkkni1l3iz0DZB0tIhETPaTSJG2rkpUL\nKDCHNdRGAHFu4RK7bAl9dpAmpnVV5rammjkRyXx+hBVXqW3N5Eac+4SkLCJTqKFsu9gywYt0\n7BQlsnZGaqNCNUpAXahZljj1FNcVDNzFrmAWnKPuSj7ZT0aOdPXkcCjb7jFyH9M8OT4cTQ2G\n1wMYuocLkaoN/IMIiqO5Y0FBB20Nmlci6IXyT5cnMP4QU5qwqz/tqhGXTqqYr5uTIua3C+/e\nXU3JE5rAkyTGu8sNaogY507AIxXFVFJ0dOJQCM/TyMzFez3fn6KzE9M8yc4jLp2ay6Vr0/fi\nyJHQ/g2tu45OXI8GcDDGWEfBD8X5SOyNC30/c+opz1NpXx3/ITR2wMqAhnacHUUVM+aekm5j\npoebzceY1QEOJgqMCoHQBLWJhRoloE7sygxhiXTbQofqRE/j/CeETOHsKE6HM+4gUxpjb8xX\nRxmxD2dLtt/Daz09XNDVpIkDg9347uSHnj1FrIzXUCS0NRHnKhgXS4qlg+xWDE+T+MqT68/x\nWE3nzfje4KczRKey6hrZEuWfUc0HkpgFYP2GU7uVAUnlXLySga7UscZrHeMPEZ7MxdE4mrLg\nHJMbETwZryqMOQCQJyhW0/h3TEeTUQ2YHciTJNmzwS/4+Szj3BXs+HZCEsgT+LRxwZN2cSYu\no/z/U95Jz5o8eMneB9KHgsDWe3iv51wEF6P4+waS8i8vq6YYUSd2ZYbFF6lry59dZHfPnpXY\n0JMtd3mazNY+aGiQLaGWFT41OToMQ23W32JBewa6cjZCsZXnO0nMYtxBLBZgOh/T+QzZI23O\nL0kaO3A2gmT5zDJFzNlwGjv8xz4fQGw6+lrk5tFuI642PJvGnYk8ncpsLxIymeKv/DOq+UAc\nTRFBUFzB8eAXVFaFo2tJoini8BB6uLD5NlEpuCxn+lF+aM2STmiImNeGy894kkQdazREnHhS\ncPejYdSvIP37l7Y4WVD7T4bu4ccz9N9J/VU0r8Q3hZdM0hQhIDPY/Zd8Ofz4zEIfsJzhYskc\nL/rvZKIf2+7R4C+G7+VsBC0cqWHJV0fxXCO9XVGjpgioE7syw5Vn+NQsONjCEUsDrjyjVWV8\nuwPsvs+v52m3keOPCRiGV2VM9ciWkJNX6DNGJFN/FRci+bMrl8ewpgePEqi7kuBiWAB9C31q\nYWdEr208TpSOPE2izw6sDOhXDLWDtoZk5vLTGZwtWN9T1mVspE0VM3xvEJmi/JOq+RDsjPCq\nwpxT5L72IX+ZweKLZbu69D0x0WVhBwx1WNiB2xOI+4opjaX9UjUsEUFEMhb6jKjHlMOyrmFB\nYNMd1t9iShPpiIE2R4exqRd6WpyPwFyffQPZ1b8othYdqgHseyg3KJaw7wGaIgUJ30fI7FYc\nHsLdWEbu404crjbsHcDZUazsSuhnpGUz/aiqQ1RTZlE3T5QZcv6jMU1XU3o961uH8Yf4vRP2\nxjhZUNNK+uN+9RmOpkWpZfn2JBWMOD1S2ova2IFetei5jelHOTzkQ15K4dDRxG8In+zHZTlu\nNgD34mhWicNDiqVAp34FqphxIIRPG8l8O1LE/HWdwW6svMrFSCp9BOlC2WJVN1qto94qxjTE\nzoiH8fx5harmRZltKqOY62GqS11bucHYdASkNydLOzNsD/VX0bQiNobcf0l4Egva011eQK5v\nbfrW/tBgqltQw5J5Z3C2oF9tdDS5F8fUABIyaVddQYvGx0n7arSvht0i5ngxwUM2bm3AT20Y\nsps/u0h/e9WoKRSld8Zu165dTZs2NTMza9u27bVr11QdjupxteFcRMHBJ0lEp0qNFw216V+H\nVddoXok61tKs7nEi88/JyVm9J4LA3vvMbCH3y6Ip4uvmHA2TShiUGFXNODmC48MZ4MoAV44O\n4/TI4pKx0BDxVzdiUtkexNEw7r9k3S3cV6OryVeeGOogLlNldmIJ4clyU1nlEhdL7k+mfTXW\n3WSKP34hzGzBuU8+Ig3Cjk743ij4j151DQdjqb2YoTZ7BnB8OO2rY2fMmIbc/5QvmhZXPMeG\nYajNsL3oz0NvHm4ruRKFkS6/d5R24KoBUrOJSaPRGyUljezJzCVKvTigpkiU0tsBPz+/AQMG\nDBw4cMyYMRs3bmzXrt21a9ecnJxUHZcqmdSIVutYe5NR9aUlyS8yGLUPz0qyKpnfO9FhEzWW\nMawezhbcjuWfO3hXYWbh5y1SsknNpuobJUpVzZEIxKZhXOLSr16VCwqxvg+ZudyNRVeLOtbv\nayPboTodqnMrlp7b5HTsEjKJSqGmleK9xBLW3eTGc8QSalkxpqGKzQ9uxvBlAGfDkQjoaNKz\nJgs7lOeeOwt9lpQiG+6S5jsv3P+i42Z+8KaRA+FJrLjKn1fZ2kfOMNq7SrHLeufjaMrTqXxz\ngv0PiU3D3pi6tjxJxG0FAjhb8GMb+imaGswTCE3gwUuqmBXiO1tG0ddCU6SgmyS/pNjwo7kt\nUaNcRIJQGttv2rRpIxKJjh8/LhKJUlNTXVxchg8fPn/+/KIdLSAgwMfHJyurzBejrrjK9KO4\nWNHSkRcZHA6lmjkHB1Hxtat1bh6+NzgaxrNUqpjRu1YRrR7zBIx/YVvfgis1l6JovpaEr8uA\nK2tqNj+eZullaSurmR4/eDO58XvJNQc+ocMmtvelo5N01ic1m4G7iEnj2lgFDYZ3Yum9nbRs\nvKqgq8mlKF5msMaHXm+URZYMZyNotxEfFyY1wsGE0Hh+OUdIPFfGUtlUNSGpKW7CEvkygAOv\nKttqWrGkEx2rv22XjBz+uMzZCBIyqW7O6IbFpY47O5BfzzO1KV2cEYk4Fsaii4xzZ6l8Ln41\nmsl+XI3GRJcUMdXNWdKJbuXabazVOmpasbq73OC3J9kRxMNPVRSTmsKgr6+/d+/eTp1K0W1l\naUzs4uPjraysVq9ePXbs2PyR8ePHBwYGhoaGFu2A5SaxA8KTWX+L0HhMdPGsxCC3YnSV6L2d\nxCyOD5edQhAYuJvoVM6OKq6TFgqJwKUoQuMx1cPDXm46KjePFmuJz+SPznhXQZzLvgdMP8oA\nV/7s8l4H/+Uc353EsxLudqSIORSCkQ7+QxW4VIkl1PkTd3t8e0jdKSQCP5/l57METVKN80H9\nVTRy4O/Xrha5eXivp6p5ORfsVZMi5kkSNobYvatHITSBdhvJE+hXG0NtbsXg/4hx7vzZRbE2\nSpF58BLXFewZQA8X2eC5CLzWc2Us7nbSkduxeK6hfx3mt8PWkBQxCy/wyzl29qOnim6QSoDT\n4bTfyJfNmOONvhY5eSy+yOxAtvWlzxtGIGpKIaUwsSuNS7HPnj0D6tSRTTTVrl17w4YNgiCI\nlPt7UwapbMocrxI61/x2NPWlwyZmNJdqx88/x4VITo0soQDeztVoxh0kJJ7q5iSLiUnjsyb8\n3FYqbrczmAcvCZqMgzGAvhYj6+Nkgdd6JjWSViW+nW9a0MOFv6/zMB4TXWa1ZLyH4naNo2E8\nT2N1d5nnmKaI2S3Zc5/1t5jbWlmv+H2JSuF2LJt7yw1qaTC5MZP9PvTgz9PQ1cSieJzc1Hw4\nJrpSE5p8JAIPXxKaQHVzalnL3QcO24OrDVMa89UxabesvhZ/36CJAyMKX5X7FvY9oF4FuawO\naOFIS0f23JcldrMD6eTEOh/ZC5nbmjyBr46V58TOqzIHBjHFn8UXsTcmJg0rA/7p/b5ZXYpY\nbYejpiClMbGLjY0FzM1lEx0WFhZisTg1NdXE5D9LhK5evRoYGKjwqZCQkNzc3AULFig91HLP\nmEwOB9B1MxIBDRHVzRnvQuAmFL/RJUhSFksuUcear1zQTwF4lMrqpZzbIr0G7AymmsDmFQV3\ntLnJzO9p4fi+J7KD/OtO5iOWnFK8zcknWMezaknBcaMQ9pzB8Mr7nktZRKfCZXZp4Sf//X6a\nROI1fhHkiq7ek9w8jj3mfIS0PF9Xk3bVaVFJyVM7apTLk0QOhPA8FV0txLnYGNLDBScLgNh0\nLl+kQ3W6rqdJRSbboadJZCL7HjDhAlGtlFncdvAh2WIWJBYcTwsmQMDkqvRhwEkGubJAXmxP\nnMGjC8xMkAkPlUtG5vEsk5cvsdCnogZPDrHg0Nu2TxHj/4gHL8nMQU+LWlZ0ci4D5THlkpyc\nnK1bt96+fVvhs23atGnUqFEJh1QaE7t8Xp+cy18vzsnJecv2fn5+hw4p/iqkpKTk5eXt3LlT\nuRF+JOhBPciRoK2BKIEzYaoOCIDIFDSz4QWHgmWDFcRcuknGLbQ1CUtAR4udwQV3TI/nejDP\nleo4HpNGUhY731B/jUgmN4+dDxXtU5zk5kEsO+IwkNeViM9EO4Xdb1xf34f7L8nIQUcTWz1E\nIhIz8bvLOV1plqBGteQpStZTxYQmYG1APWO0NJDk8TycNVepboGpLklZaCZx4j4VjclO4NId\n6V626USlsPqpAiePIvM8jeQsBV+E0HgMtKVfUgFynnM5miD5joH8D/PBF+iX3ouVMnkM79SA\nEOfy4CW6WtgZoqNFtoTQ+9w9iYuVWh5FBUgkkjNnzgQFBSl8Nisrq+QTO4TSx61bt4ALFy78\nO7J06VIdHZ28vLyiHfDIkSO6urpKik5NqcBjtTD/XMHBvDzBfL6wK1gQBGHKYaHDpoIbSPIE\n+0XC2ptKDubkE0F7rhCZLDeYLRGc/hB+Pa/kc70nrdYJPbcJkte+MWnZgtsKYbJfUY629qYg\n+l6Y6Cd3wM/9Bb4Xjj7+0FDV/BfnI4RJfkKnzcLwvcLam3Jvfj7p2cKck0KVJQLfC5YLhGF7\n5D6ELdYKo/cX3OWLI4L7X4IgCEfDBK25gtHPgjhXboOllwTLBULHN747H8K1aEHjB+F8hNzg\nrRhBa65w8olspNJiYfmVgvueeCxozRUSM5UZT1nHZ6vQdoOQ+9rnQZIndNgkdP1HdTF9xOjp\n6fn7+6s6CjlKYyt5xYoVgYcPZfd3ISEhFStWVBfYqfmXrFwFMqciEQbaUmPZga4cf8zJp3Ib\nLLtCchZdnJUcjFdlmlak5zZCE6QjCZkM2U1aNmMaKvlc78mKrpx+Sqt17H3AlWdsvkPDvxBL\n+KFIBX9rbqKrxR+d5KaFlnRCT4tF55UVshoZgsCnh2m1jqdJ1LFGEJh6hCa+vMiQbROficdq\nNt3he28ujWGtD1Ep1FnBjecAWblciGRkfYDwZIbuwWEx2j+y+z7XnxOTRhMHRGCoI2cskSew\nI4ia1sSmK/PluNsxpiFdt/DbBW7HcieWpZdpt5F+teW0V4bV49fzPH/NtDA9h9mBdK+BWble\nhy0UYgn+j5jmKVcuqSFiuidHw8hUawSqKZ1LsZaWlt7e3rt37x45ciQgFov9/Pz69eun6rjU\nlCJqWnE+kk8byw3myzXn68x5VmJaMzpsYmR9WjoilnA4lIMPWeODrfLWmPIRidjVn7EHcVuB\nmy26mtyNw8mCgKEqKwyqY03QZP53gvEHeZFBJROG1OV/LYso2BuTiq2RgqIrCz2iUj88WDUF\nWXeLDbc5MwrPStKRFxl03sy4g+wdIB2Zfw6JwI3xssqq7jUYsofxh7g6lrRs8gTM9LgaTZsN\nNKjAL22xMeRcBPPO0m4TF0cz0I3Nt1l3k1ENpKf4zJ+gF/SqqeTEDljRlQYVmHuaGccArA2Y\n3YpJ8itU/2vJmXBqLeeTBjhb8iyF9bfQ12ZnfyUHU6ZJzCRbokhh1IycPBIype1iaj5mSmNi\nB0yfPr179+7Tpk1r06aNr69vYmLi+PHjVR2UmlLEOHc6b2agKz6vWu1SxEzyw92eBq/kmn9t\nT7tq/HaBw6HoalK/AjfGF/RcUhY2huwfyOVnnI8gM5fZrehQvSg9CkrEzoi1PgDpOR9q4mRh\nQGh8wcE8gUQxVVQh5lLuWX2diR6yrA6wNuD3TnivJzZdemeyO5ivW8jVy4tEfO+Ny3LCk6lk\ngoU+t2P57Ty9arLxlcZNRg4G2qRls+AcK7uwJ5iJh/nsCOZ6PEulsQObezN0D4s7KvkVaYqY\n4MEED15kIAjYKLq5MtDm9Eh8b7ArmEMhOJgwsRFfNvtYquveE3N9dDQJTy6olB6ejLaGul1d\nDZTaxK5r167btm377bfffH193d3dT5w4Ub36W3U21ZRZniax4bZUi86zEoNc3ysfal+NH1rT\ndwctHGlQgWQxh0Iw1eXwELk+zXwPiRKjiQNN3nAHUjkfbs050JVpAey+LyfBsPQSWTl0d/nv\n3dQUlQcv+aZlwcFmFQEevpQmdtGpCqZtqpgBPEuhsikDXZlzkrBE2YxXspjvTzGgDq42rLnJ\nT21Y48OwPXhWxs0WNxsSMxmxlwYVGF6vuF6a9VvtWDREjHNnnHtxnb0coKtJZycWX6RdNdlq\nbJ7Aogt0qK5OgtVAqU3sgP79+/fvr56CL+csv8JXx6hpRf0KPE9l4iEWX+TAoPdaTfhfS3xc\n8L3Bw3hMdZndinHuinXm1HwgXzZlyUX67aBfHca78yKdmSd4mgTwzXG23uW39iWaQJd79LRI\nf8OOOTOXPEHW9mhlQOQbXqL57qL582Hz2nDsMcDq61QzJzyJdbewNeTX9lyKIjIZYEAdnC34\n/AjLLpMtwcGYL5vxZbNilD0vJjJyOPaYsAQs9PGsRA1LVQdUnCzsQFNfWq9ndiuqmvM0iXln\nuBvHxdGqjkxN6aD0JnZqyj1nI5h6BN8e0hJvIC6dvjsYvJvTI9/rCK42H7U9aEkSNIm+O9kZ\nxI5XTf31bNnYGz1N1tyk2xb+6s4oparafsx4VmLPfQa7yQ3uuY+xjqyWoGsNVl5lWF257oel\nl6lhKdWgMdNjR18a/MWlKPY/oJIpM5ozpTE6mjxPkxkZN7Tj7Chy8xBLZJO7iVncjcXBhOpl\nYandL5SJh0jMopo5CZnEpDHRg0UdpVrl5Q8nC25PZOZxem+XFlr41GRzbzlvSTUfMx+U2OXl\n5YWHh9vY2BgaKrsc/ePD/xHHHxOdShUz+taWqbGrkPQcbsWQlEX9CsVSkLviKj41GVmfyBS+\nO8mJx7zIoIYld2K5E1tcxXBqioaxLgFDiU5ldiCHH3F0GHVtpE8taIeDMV8GMKBOQeU8NUVj\ndiuareGrY8xtLV1c2xnMZ/5801I2YzfHi0Z/03Ids1vhYklsOn9dY0cQfkNkx6lnSxUzmldi\nfjvZoFjCqmt0lTdg1dKQNsc8TWLaUfbcl447W7Ckk/IbyZXIrRh6b2daM2a3kn78jj9mxD6A\nPzqrNrRixMGYTb2Q9OR5KnbGZW+GVU2xUrg7mjNnzowaNSo4OBiIj4/38PCoVq2aqanp1KlT\nJRJJ8URY/snIoftWfLbyKAE7Iy5F0fhvvghAhS6+EoHFF3FYhPd6+u+k4mIG7OKZsvsf78Xh\nXYVjj6m5nKgUFrRnd3/61UYkYvQBJKXOxLh4CU1gZzCb7nAtWtWh/Df2xoTEM66hLKvLZ5w7\nmTmci1BRWOWOhnYcHMTe+9j+Rv1V2C9i1D5mtmBmc9k29sZcHUsNS/ruwGU53ut5msT50bSv\nJttGJGJxRxZdZPwhgl7wIoPT4Xiv50U6s1spOG90Ks3WkJTFzfHkfEv0NPrXwWcbW+8V+0su\nMgvO074aP7eV3VS0q8aqbqy8RnymSiMrfjRFVDRRZ3VqClKIGbsjR4506dJFEIT8BtUffvjh\n5s2bbdu2TUpKWrp0ad26dT/55JNii7M8M/0owS+4N0lWF3I6nO5bcLFkgodqQvriCJvvsKwL\nA+qgo8mdWCb54bWOmxNkdqgfjrYGmTmMOcCo+izvIh30rsLCiwS/YMMtPmmgtHOVZlLETD3C\nhtuY6aGryfM0vCrzdw+cS6Wpw8sMHN5Y8dHTwtKAlxmKdlBTJDpUJ2gyZ8K5F0dFE1pVViDT\nY2/Mpl6s8yE6FWtDxYXzvWoSOIIJh1h9XTrStza7+ysW/Zl3FkdTjgyVLmLaGfFTG4x0+OII\n/Wor02RMiVx5xswWBQc7O6Eh4sZzuTRXTXGgNqst+mAWwwAAIABJREFUhRTimzpv3jx9ff3T\np083btw4Ly9vx44dHh4ex48fP3/+vKOjo6+vb/FFWY5Jz2H9LX5tL1ft61WZqU1ZcfW/dytO\nolJYcZUtfWTlO3VtOTqMPEHJITV2YNs9olP5qQ05efx+iSpLMPyZ5CwMtVX28kuewbu5GMWZ\nUcTPIHoajz/HQJu2G0gRqzoyRdgbK5A+ScriRbqChE/Nh6CrSftqfNGUfrXfJr6opYGj6dva\nIVs6EjSJ6GncmkDyTHb2w/4/KisCHjGyfsHStHHuxKZzK6ZIr6H4yZEoaJnKX1nO9zVWUxzE\npjP6ABYLMJ2P6XwG7CI8WdUxqXlFIRK7oKCg7t27t2rVSkNDIzg4ODY2dtCgQYCurm6rVq1C\nQ0OLLcjyzONEMnPl5Nfz8a7C/ZfkqWI58nQ4NoZ0cpIbNNCmfx1OPFbmiaZ5EvQCXS20Nemx\nlV/O0qsWdka0r0Zta24858+PILe7/Az/R+wZQPNXomVVzdgzAAF8b6g0sv+gb23W3ZJ2X/7L\nL+ewNpTqcagpndgZUc/2HZMriVkKMkgLfbQ1SMwqvtA+CFcbBTUAN56TmUMda1UE9BEQkUz9\nVdyO4a/u3J/Mpl7EplFvJffiVB2ZGqBQiZ1EItHTk+roHzt2DPD29s5/qKWllZGhXoYpCvmr\nG+I3fGDEEjRFqKR2IkWs2MDHXJ/UNyQYPgRnC37wJiMbu4UcC8PKgOVX6OLM/kG0rko1C2Yc\nk/NQKpdciMTVhlryWqN6WnSvwYVIFcX0Vsa6U8+W+quYf46zEey+T7ct/H4R3x5y7ZnliRcZ\nxCnbiaF04mhK8IuCg6EJ5OThaKqKgN6DyY1Zf4u9D2QjMWmMO0i3GiUU87NUAsI4HCoVAPoY\nmHmc6uZcHEO/2tS0oocLJ0fgVYXP/FUdmRqgUDV2zs7OJ06cSEtL09fX9/X1tbe3r1+/PpCd\nnZ2/GltsQZZnnC2w0Gf/QybKl9Ptf0AjB1TijlvVjCdJCionbscoX/tgcmPmncXGCGMdxjTE\nuwp1rMnIYeNthrqx4hpHwxji9u7jfCAf7s1QZBSa3gJGOkSUyqUNbQ2ODuPPq6y+zpxTmOrS\n3JHbEwvmpuUAicDf15l7WupeamPI/1oyqZGKS83iM1l9nfsv0NfGw17ByumHMNCVJZcY1UDW\nBZ8nMDuQBhVwKa3KcF2dmduagbtoVZm6tiRksu8Bta2ltivFSoqYmcdZfR1DHbQ0SMxkoCtL\nOin21Sg3CAIHHrKxl9wHTyRiRnNarSMpS23sq3oK8ZMwadKkqKgoV1dXd3f34ODgkSNHamho\nBAYGenp6hoaG9u3bt/iiLMdoaTCzBTOPsytY2gabk8fii6y5yf/ekJ4vGbyrYG3ArBNyC8Hn\nI9kVXFBY68Mx1uHntjxJwEyP9tWwMiAgDK/1iOCLZjiaEpv27oMUmYRMPvPHfhFGP2O/iCn+\nJJR4G11NK+7FkZFTcPxqdEHLoNKDlgafNyFoEuLZxH3F3gHlMKsDJvkx6wRzvAmfSsQX/NKW\nn85IdTRUxaEQai5n3U1EIhIzmXUCj9WEJijt+FOb4mKJ2wpmB7L1Hn9cxn01x8JKIkn6EGa2\n4M5EPOx5+BItDf7qxrlRMqG+4mPALk48wX8oiV8TP4PzowmJp+Nmcsp1bV9qNuk5Uo+T16lq\nRp5Q/tdYygSFmLEbOXJkVFTUH3/8ERUV1aNHj2+++QY4c+bM9evXu3XrNn369GILspwzvRnp\n2Qzby9QjVLfgXhwiWOtTsMqtxNDTYlNvum/hUhR9amOkw9VnbL3HpEbFImc1pTFb73H1GS7L\nAUQwrB4L2mGiS2QytkbKP2M+kSk088XKgCWdqGLG0yTmn8NtJRdGU7kEV506OWGuz6eH+au7\n7A541TXORfBnl7fuWQaJTmV7kNQeoGXlUt2xeDWaNTc4P1rmEdfRCbcKNPdlnDtelVUQ0pMk\n+u7gi2b82Fo6axifyYi9+Gzl7iTlaF7oanJiBH9dY+NtVl/H2hCvygQMLQNTUC6W/NK2RM94\n8imBT7g/mWqv1jGaVSRgGDWWsf0eQ+uWaDAlibEOhtqEJ9NQXmw1PBkN0Tss49SUDCKhkGpp\ngiDk5OTo6EhFLx4/fqyhoVG5cmWRSlYN34+AgAAfH5+srNJa/QtARDLnIqQCxW2qqt7L+Xka\n885w5Rlp2bhY8Wlj2lYtrnNtuctEPw4PwUSX6uZSPaq1N5niz9OpxfVLMWAX0amcGC6rDMvJ\no/1GrAzYVbJWdpef0Wsb5vp0r4GeFmcjuBjJ8i7lTe3lr+tMP4q9MU0rEp3K6ae0q8bWvnI2\n9qWHH04T8IgLo0nL5pdz/HWN+Ey0NTDWpVsNNvRUQUizTnDsMVfGyFVoxGdScTEHBpXqLLlc\n8sNpjoVx7g2NrwG7MNVldXdVxFRSDN7Ns1SOD5fdiwoCfXaQlEXgCJVGpgr09fX37t3bqVMp\nMkF6x4xdbu4bVf2goaHx73h+aV2+OrGWltqgrOg4mip/ofNDsDOSacsVNwNd2XSHPtv5sQ1a\nGqRnsz2IJZdY0qm4srqcPA48ZFd/uXp/bQ2+aYnPVsSKBBSKjyYOPJzCssucjyQjh4Z2rPUp\n0VnDEuDUUyb78WdXxjZEQwQQEk/v7Yw9wI5+qg5OEfnqLek5tFhLQiYVjEjLQZxLchabbuPj\nQu9aJR3SnVhaVylYd2upj6sNt2PUiV1Jk56NqaJiMlNd0t+orChnzG9HE1+a+fJ1C9xsCIln\n8UVuxihIc9WohHekYtrahSgpL+zknxo1+WiIODCIZZf54RTPUtEQ0dCOI0OLcY4wPoOsXAW9\nINXMEUt4mVEsFmpvwViHWSoqqSwZll5mkBvj3WUjNSzx7YHnGqJSSqPHpYMJZyNYfJHnaSRk\n0sKRpZ2pYITPNqJSGLiLlzNKWpdVQ6RYmE2Sh2YpkA6+/py5p7kdg0SgjjXftFTNgnWJ4WzJ\n5jvk5smaaS5EEviEfQ9oVqmcy/Y6mnJzPLNOMP4giVmY6NKxOrcnKCi8e52QeL47yZlwUsQ0\nsGNaM3rWLKmIPzLekdgNGTLk7RuoKR9IBFZf52gY0alUNaN/nZKekNDW4MtmfNmMuHQMtDFS\nnr+FQsz00NIgKqVgg0JUCpoizNVdXcrmdowCD6smDuhrcye2NCZ2vWrybSBp2WTkMKslP3gD\nHHvMk0T2DsRnK9+cKOkiSA97tt7j1/Zybbm3YrkTp/qW1ZXXmHKY3rX41gtNEafDabuBb72Y\n46XiwIqPXjWZcYwfTjPXm2Qxow/gF0JlM+Izuf4cl+Ws6Eqv8pu4VDBirQ9rfd43hd3/kP47\n6erMkk4Y6nA+gsG7GeyGb4/ij/Xj4x2J3ebNm0smDjUq5GUG3bcSGs9AVxrZ8zCegbvoWoPt\nfVWgTFYyZdp6WrStyh+XaVtVtrYlCPxxmdZV1U72ykckUqC2LYAgSFdmSxs1rfjOizmnEEG9\nChx7zKEQVl1juic9aqCryYknJR3SWHd+v8SEQ/zeCWMdzkYw4ZBUdq7rFtpW5Y/O1FaFJG9E\nMl8cYXV3WVXoyPr0qYXPNnxcqF9BBSGVAFYGbOzF4N34h5KeTWIWbrbciWV1d0bU4+ez9NvB\n1XE0KKcv/1/eJ6tLzWbMAWa1lCX6XZ3pU5vma+hZk241inLetGz2PSAkHhNdmlakhVpv7TWU\nM4O/aNGiGTNmKOVQakqez4+QIyH0M5Z3YVZLNvTk6jjOR7DsiqojK04WduDUUzr/w7HHhCZw\n/DFdt3DiMYs6qDqy8oi7HYff8KYJfIJYUnov/N95YWeEhoiRe+m9nSvP2NWfBe2IzyQ7j9QS\n78WyM+L4cC5EUmkxbivxWseDlzSy5+5ELo7GUIdma7j/sqSjAvY+oJIpo+rLDXarQdOK7AhS\nQTwlRvcaPPiUuhV4EI+DCR723JvE6AZoafCdFx2qs7xc/4S+P8fCyJbwjbylr7sd/eqw7V5R\nDuj/iJrLmXqE0+H8c5fWG+ixtfSao5Q8hWt3iIqKCgwMTEiQ003KzMz8/fffNTQ0fv31V6XG\npqYkSBGzK5jDQ+TWH+vZMt2TtTeZ1kx1kRUzrjZcG8eXAXT5R1oo064ac1vje4O0bBraMbxe\nea6SKWGmedJiLfPPMc1T2kl3LZoJhxhejwrFpmjz4XR2Zu1N7k2S8zD47TxG2ji+tZyomHC3\n49YE9j7gM3+aVuIHb1nPxL4BdP6H/51gz4CSjioimVpWCtTU61iXUpFtJeJgTGcnDj3k+riC\nT3V0Yt1NVcRU+ohMoaqZgvWfGpYcCyv00R7G03s7nzdhjrfUIjn4BYN2M2wPhwYrIdpyQCES\nuxs3brRp0yY5WcE3VUtLS53VlVEeJ5ItwcO+4LiHPf8LJK+0rpQphRqWHBpMtoTnaWRkM2wv\n887Sugr62iy7wk9nWNeTzipSEyxnNHFgUy8+Pcwfl/GwJzqVmzEMdC3tWn0LO7DxNvVXsaA9\nbjYkZLLhNnvuY6ansrpvHU1aOBKXzonhuNrIxkUixnswdI8KQjLXI1aR5Vpseuk1IlMigqDY\nIkgE6nbCfPI/IW++UTFpmBde2Cv/N2R+O9lIbWs29qL+KoJeqA2CoVCJ3Y8//piSkrJ48WJ3\nd/epU6dWqFDhu+++e/r06Zw5c2rUqDF16tTii1JN8aGvDZCWXVBOLD0HPa3ynNX9i44mFU2o\ntxJ7Y44MlQrW5+Yx5xR9thM0maqqmJspfwx0paMT+x8QlkjrqqzqpuB2orRhrsemXgzezWf+\nZOWiq0lVc6wMMNHDXI+zEXjYS+cMSpLETEDBTGcFIzJyFIv1ZOay9ia3YsiRUNuaMQ2VqZTZ\noTrfn+LGcznF2seJHH/Mto/AkKiBHXHp3I6lnq3c+NGw8l9g9560qUp8Bvsfyt0OJWSyM4jv\nvQt9tOvR+LxxW1XPloom3HiuTuygUDV2ly9fbtOmzRdffNGqVavhw4dHR0c3bdp04MCBx44d\nCwgI2LhxY/FFqab4cLbA3pgtdwuOb7lbztUKXufUUx4lsLm3zIZIS4N5bahry1/XPujIGTlE\nJCNR37kDYK7HyPr82JovmpaBrC6fga5cHkuziuhqIpYQm444lycJ/HyWdhtxWcae+yUdkoMJ\nmiIevFFO9/AltoYKsrrrz6m1nHlnSBVL+99rLMPvjZLHItPYgSF16fwPW+6SIiY9hwMPabOB\nlo50KwavmtKGswWdnRi9nydJ0pHQBFqu5XAo9+L4/AiRKSqNrxRQ0YSvWzB8L79dICyRmDT2\nPaDlOhxMGN2w0EcTUDzjoKGoQ+vjpBA3my9fvqxaVSos5unpOX369PT0dENDQ0dHR29v740b\nN44Y8fFpTpd9NER858Vn/uho8mljNEWkZTPrBHvvf0Rqk7djqGOjoCHXuwp3Yot4zAuRTDvK\n5SgE0NVksBu/tMO21FszqXmTRvYEjkAicOQRPbfxdXNmt0JPi2wJCy8wYBe7+9PDpeTiMdej\nkxNzTuE/RFa3lJTFgvMMdC24cUYOvbfjVZmV3TDUBsjN4/tTDNjJg0+VJjTj24PfLzLhEKnZ\nAHpaTPfkmxaK1yjLHxt70X8ntZZLFexuxqApokdNXK059phay9nQiz4lrmhdqpjrjaMpswOZ\ncQxAU8R4D35qUxQp+Hq2nHzC183lBsMSiUwuOGn60VKIxM7a2jo6Ojr/bzc3N0EQTp8+3aVL\nF8DCwsLf379YAlRT/Ix3R1PEV8eYeRxbQ56l4mDM0Hr8cRl9bRraMaq+CnRPSpL/kn7NzXvH\nlSk9h4RMHIwL3kH6hdJzG6Mb4NsDG0OC4ph5nMZ/c3VsGbDdVKMQTRE/nWG8Oz+1kY7oaDKr\nJSliZp0o0cQOWNaFlmtxX83UplQ0ITSeBeex1FewsHXgIUlZrOgqzeoALQ3mtmbPfdbd4ts3\nxAWLhrYGM5rzRTPuxZGbh5sNeh+TD5GVAYEjOByKfygrr9PThVXdpN/0H1sz7ywj99G8Uqnu\nEypuRCLGNmR0A8KTSc/G2bLo7j6fNsZjNb9dYFoz6Q9vdCpD9+BVpfS22JcwhViKbdq0aUBA\nwJ49e3Jzc/X19WvWrLlv3z5AEIQrV66YmJQ+jVE1782YhoROYc8AvvViVksSszgbjkhEYibf\nBuK6gqAXRT94QiYXo7gaTYpYeRErlYZ2BMURLt8XlCdw5FFBo+t/OR1Oo78x/hnH3zH8mQmH\neJkh23GyH195sqobdayxNsC7CqdGYqHPvLMfFGd6DpEp6uUG1ZCVy+UoBr3h+zfYjaAXsv9+\nyVDVjKDJdHLit/P02MrfN5jciMWd+PsG351k8x2Zq1XQCxrZF1T81hDhVYWgOCVHpa1Bgwo0\nsv+4srp/6eKMvQkuluzuL7t/E4n4piWW+uwMVmlwpQMNEVXNcLX5IM/GurZs6s0vZ6m7klH7\n6bODWn+ipcHWPsoLtIxTiMTu22+/NTQ07NOnz/r164GOHTv+/fffffv29fLyevLkSf7UnZqy\ni5UBnZ1oVZkF55jZguDJbOjJjn48+oy6tvTeTrak0MdMzGKiHza/4bmGxn9ju5DZgWQp8B9W\nMS0daVKRQbsIS5SOpGYz+TCRKUzwULD97vu020iDClwZS/Q0tvThUhTN1kiFlO7FEZ7MlCZy\nu+hpMc4dv5AiRngtmia+sjzyM3/pmpeaEiMjBwGM3/BEMdYFVGAPaqrLb+158Cni2ZwcwflI\nOm5iz32uP+eLAFyWceQRgLYGYkXfXHEu2uV6Gl4lhMbjYV9wml9TREM7HiUo3iUnjxvP2XOf\nS1Hl32RWWQyoQ8gURjdEEHA0ZWMvzoz8qCdEC1CIG6v69etfv35948aN+ZV2c+bMuXfv3u7d\nu4H27dvPmzevuGJUU4L43qCurZySpIkuq7vjsJhjj+lamFJoiUDXf0jK4uBgvCqTk8eRR0w/\nSkh8qfN9F4nY1Z+he6j9J2426GtzNxZLAw4OUmAam5PHp4eZ4yXzyOpVk47V8VjNr+f5pS0v\nM9AUUeGNJVcH4yLO6+x7QL+dDHLl945YGnAnltmBHH/M+dFq97OSw1wPKwOuRlNXvo7n6jOM\ndLBT6UVl2F6epXBnIrWsADJz+f4UvbZzewKNHfjlHDFpcpe9rFyOP+ar5v91PDVFxFCHSEXS\nfSli2VL465x8ymQ/7r/ERJcUMRWM+LU9w+oWd5jlASsDvmiq6iBKK4WbMXdycpo7d27+36am\npkePHo2JidHV1TU3f8NNXU3Z5F4cXlUKDlroU9eWoLjCJXa7grkbR8gU2TVvQB1qWdHgLy5F\n0bSiUuJVGnZGnBjO8cdcf05mDp82xsdF8YrS9Whi0/i0sdyggTajG7LhFr+0xcEEicDjJKrL\nfy1C4rF/I018JxKBKf5804K5raUjLpZ0csJjNUsuST1M1ZQAIhGj6vPjaTpUp9KrwpPYdL47\nyRA3VRah3o3jcCjBk6VZHaCvxYJ2XIpi2RWWdqKuLb22809vqpkDvMxg7EEEGFn/LUctz8Sk\ncTcOcS61rAt+ST+QVpUZc4C4dLlS2ohkLkQy3bPgxlee0WkzYxtyciS2hqRms/IqYw4A6txO\nzQfxoaUQFSqoixXLFdoaipdci7Bwc+IxnZwKzmTUtcXdjhNPSl1il0+7arSrJnsolnAsjNAE\nTHVpVkl64XyZgaEOZm9Mlf07IediiZsNc0+zoafs2YRMll9heL1Ch3TjOc9SmCp/b2qsw5iG\nbLmrTuxKlO+9uRZNreUMcqOqGRHJbL1HHWsWtFdlVDeeU8lEltX9S8fqHApBQ8S+gYzeT50V\nuNmgrcndWGpaETBUwbJyuScjh9mBUqcvLQ0yc+lZk2WdldYd3LsWCy/QcTPre0o7NK9GM3If\nTSrSsXrBjeecomdNlr8qYjLWYUZzsiXMOsFQt4+loVhNcVCIxG7o0KFv32Dz5s0fFowa1dPY\ngQ23pRZb/3LzOXfjqFVI4ccUsUwW7nWsDEpvF8XrXIpi1H4ikqluTrKYZyl82phf2+NgQlo2\n0akFp99en5D7uwdtN/A0iYkeOJpy5RkLL2BjyIzCL37FpmGoo0BOtpIJsWlFemFlmfhMttyV\nOX93cy54/RMENt/lr2s8SsBUj+aV+KG1bILtAzHQ5sRw/rnL/ofsf0hFExZ3ZFR9Fet45wlo\nKiqW1hBJnQ/sjDg8hAuRXIxCnMscL9pV+yi0x99k1H4uR7FnAB2d0BJxI4bP/Wm7kVsTlCM0\nrSni0GCmBdBgFdaGCALxmYxuwK/tFSRqp58qEHAeUpdvTxKWiJOF3HhqNvPOsCuYp0k4mNC+\nGj+1UVeVqVFMIT7L//zzz3895ejoqK2tqIJATVljvAdLLzN0D390xsaQi1GMPSBtie28Ca8q\nLOuCm827jgJANXPORhQcFASCX5SENsStGPwfEZmMoyldnAvWRb2TsETabaRvbS6Olk7OHX/M\nqP2kZvN3d5ws+PEMK7vKto9LZ9U1PnvVMNHEgXuTmHWCaUeJS6eaORM8mO5ZlG5Be2PSs3mR\ngbV8lvwkCbvCL+yWabYHMfEQJrrUr0CKmN8v4mHPzv4ydUCJQJ/tHH/MxEZMbERyFlvuUms5\nh4fQSklq2yIRQ+sytDStlNWzJTyJkHhqWMqNHw2T+9h7VsKzkvLPfimK5Ve4HYuFPt5VmNas\n9Dos33jOziBujJeJYrjb4T8U5z9Ye5PJjZRzFmsDNvbih9ZcfYaGiMYOin3VJAJiiYKJ//yR\nAl0ULzPwXENmLl83x9mSqBSWXqLOCs59omCmVo2aQlxncnLkPmuCILx48eLKlStz5syxtrY+\ncOCAsmNTowIs9TkylFH7qLyEqmZSdfvWVVjVjcQs5pzEcw3nP3mvPGmQG7+eZ2cw/WrLBhdd\nJD6TXsWp1Zkn8PkRVl7F1QYTXY6GMTuQz5uyUNFN83+x9BJ1bVnnI9ulXTU296bNBn5szZoe\ndNxMaDzj3HEw4VIUCy9Q2ZTPX1swrWLGFmW039evQCVTfjrD0k6ywaQs/rrGqAZKOH5Z4U4s\nQ/fwUxumNZNOJ0ckM2AXg3YR+EoZfcMtTj7l5gScX812TGrEJD9G7CN0itwkdD734jgdzssM\n6tnS2fmDJBhUSEM7WlVm5D6295POTebmsfAC5yJY2vkd+4olxKThYKzgzXkfZh5n0UUGuzHe\nnRQxW++x+jpHhpZSndgz4dS2Lih1ZqxDDxfOhCstscunqtk7rAg1RVQ148bzgrcct2PQ1qCK\n/L4/nkFXi6vjZMaPw+vhs5UvjnDkHQtpaj5GCpHYaWkV3Nje3r5nz55eXl716tX79ttvFy1a\npNTY1KiGBhW4Pp6jYYw9SOOKLOtMo1fuT/5D8NnGrBMcGvzu47jZsKA9g3Zx0I02VcnN42AI\nRx6xvmfxGjD8doEtdxnsxs5g9LQw1EYi8Mdl9LVk0rLv5EIkA10LJoKtHDHV5VIUvWtxdyKz\nTvD5EeIzqGbOF02Z2rRYKug1RPzVje5biU5lZH0s9bkXx/xzGOvyZTPln67UsvwKXpXl5OYd\nTVnnQ60/uRUjvVpvu8fI+rKsLp+5rVl9nUtRtHCUDabn8Jk/G29Ls//lVzDVxbcH3lVK4rUo\nna196bcDl2V4V8FCn/ORpIjZ3Pttk+u3YvgygDPhSAS0NehZk4UdFM8t/Rf+j1h8kYChtJEa\nEvFVc0bsZdAu7k5Cs/Qt9abnKJghA0z1iE4t8WhgVAMWnKe7i6yBIymLaUfpXaugc/eOIOa3\nkxvU1uA7L5qvJTFL3RqvpiBKKCswNzfv2rXr1q1b1YlduUFTRBMHolPYPxD31xR6RSImeNB7\nO3nCe9XoTGuGdxXmn+OH02hr0KwS9yYVvO4qlzyBJZeoacXxx+zuTxdngIhk2m9i/jmmeyr+\nZX8TsQT9N4oLRCL0taWqYE4WJSfa0smJq2P56hj9dpCZi40hnzTgfy0Lqs6Wb27H0vuNid6a\nVjiacjtWmthFJNOndsFtrAywNSJCXoTik/1ci+biaKllbWYuM4/TdQu3JxSsbSoT2BlxdhQH\nQ7gURWo2XzZjsBuWb9Rl/sv5SNpuoG9tro/HwZiQeL49icdqLo99xzzT66y7ySA3WVYHaGvw\nR2fsFnExUi6NLiU4WRD0gmxJwRuwm89xU8UU41eeXI6i7krGuVPDkmcprLmJrSHL5DVhsyXE\npCn42XS2JE8gKkWd2KkpiHIEwsVicWJi4ru3U1N2iM9EQEFxrp0xYglp2e9bSeNux84SVK2L\nSycmjdg0zn5C81cVRY6mbOpNk79ZeJGfWr91/1fUtuZcRMHVmceJPE+ldiGbSJRC/QocG0ae\nQEbOx5XP/YsIxZYbr99jmOsraCjJySMpC/PXspynSewM4sKrrA7Q12JpJ27HsPgiK7oWPEKZ\nQCSih8v7Vq9OOczweqzuLn1oZcDRYbTbyOxA/un9vmcMTWDEG13eVgZUMuFRwn8mdjl5RKdi\nZ6QCgZiuzuhqMuMYizrKJhS33OXUUxZ2KOlgAB1NDgxiVzBb7nLkEVXMmN2K8e4Fl8V1NDHR\nJeaND3b+yFvSdzUfLR+a2EkkkhMnTmzdurVGjRpKCUhNKcHOCG0NQuMLKvSGxGOmV3qFEvKv\n8TZGsqwuHy0RwMXI9z3O6AZ0/od+tWWzRCliJvnhYU/d9+sd+UAevOR2LDkSalvLbM00RB9p\nVge423M0TE46Gwh+QVSK7P3pWJ1/7jLdE4PXZls33kZDJJdnXI3GykCB4E53F7beLY7YSxfR\nqdyMYUMvuUFNEZMaMbYwldKG2iRlFRwUBJLFcu//v4QmMC0A/0fSpvt21fi9IzVLsPbfSIct\nfeizg8An9KmNoTZHwzj5lIUdVOkx2rc2fd+YZi5A+2osv0LPmnLrJCuu4mpTFGlMNeWeQiR2\nRkYKWquzs7PzmypmzJihtKDUlAKMdOjuwnfqWsFsAAAgAElEQVQnOTZcVlSems1PZxQUn5Ue\nrA0w1+PN6I6GYaGP+L3dzDpU5wdvBuyihSMNKpAs5lAIprr4Dy32156QyRR/tt7FQh9tTWLS\naF+N1d0L1lN/bHzWhPqrmHWCH1qjrQEQmsCg3XR1ps6rOdQvmrH5Dm02sKQTDe1IFrPmBj+c\nZkE7uVuRHIliUUZtDXLziv+VvIvUbH47z8mnxKVT1Yxh9Rj8Yd+4nDxy82RyHvlqi29aqjgY\nkywmJ0/69r6TVpXZEcTsVnIzTP6PSM5SMF0X/IJma2jigN9gqpoTnsSSSzT6m7OjSjSpalOV\nh5+y8AJnwxFLqGXFrQmyz0+pZV5bPNfgs41ZLXG2ICqF3y6wI4jDQ1QdmZpSSSESO29vb4Xj\nVlZW/fr169q1bC5gqPlvlnSi+Rrqr2JaMyqZEpbAr+cx1ClEC0LJIxIx0I2VV9l8l6Gv/Np3\nBfPjGZwtcLZ8687yzG6FT03W3OBhPKa6fNuKce7Fvn4kCPTdwcsMLo2hsQNASDwT/Wi/iTsT\nlSO1VUbJ91Yfe5B/7tKgAiliLkbRvprczJOpLmc/4etjeK6RSrhVMmF9TwbUkTtUHRuiU3kY\nj4v85+HUU9XUWr3OowS812OsywQPbAwJfsEkP7bcZe+Aonz2/EL5NpC7cUjyqGLGV80Z546d\nMSIITaCJg9zGIfFYG7xvVgd80Yy1N/HZxqIO1LQiW8KuYD4/wpQmCqaRvjpGC0cODZJmqM4W\ntKtG3x18GSBrai4ZbAz5VaWC0kXAxZJr45jkh+ca6Uj9CgSOoGXpK2RUUxoQCYKiupXyRUBA\ngI+PT1bWG8sGat5FUhb/C8QvhKgUKpvRtzZzvBSvs5QexLlUWESKmOoW1LYi+AWRKfSpxdZ7\nBI7AS0l6ZsVE4BM6biZ0itz8XFo21ZbyYxvGu6sustJBWja7grkdi7ke3lX+U50uRcydWKwN\ncbZQ3OXTah0iETv7Sa2fBIH1txlzgNMji73q/8FLZp3gXATJYpwsGOfO5EaySS/v9ehrs3+g\nLI17kkRTX77yVOBJ9Xbmn2N2IBM86FULXU1Oh/PLWTo7s7MfrTdgpMP+gbI3Jz2Hpr60dCxc\nieGDl0z049RTDLXJykVXi6+bM6tlwSqxbAlGP3NwcEH3hTPhtN5A8syPt8CgsCRlSQWKrRVp\nv6tRCfr6+nv37u3UqdO7Ny0pPuIZADXvgZkef3bhzy7v3rL0oKvFkaF0/ofkLCJTcLLAwYRt\n95jjVdqzOuBCJI3sC666GunQ2ZkLkerEDiOd93I4NdF9R362pQ89tuK8jLZVMdXj5nNC4lnW\nudizuoAwum+hfXWWdsZUl9ux/HSGfQ8IGIqOJhHJnA7nzkS5ybmqZkxtyuY7hUvsolP5/hQb\nezH41bx1C0e616DR3xwN488utFxHE18+a4KTBbdiWHgBTZHMj/g9qWnFyRHcfyn1Aqlnq8Ai\nBaQrvG/adlU0IU8gIVP1iZ0gEPSCRwmY61PP9n1750seMz1VlgOqKSu8I7ErlBVsTEzMhwWj\npryRlo2BtgrMi5o4EPYZiy5wNZpkMS6WLOogK7EvzWTlYqjoImekIy2NKm5y84hJw964nFtO\nVTTh6ji23uViFMlZ9KrFiHrKrGLME3iWioU+hq9Nb+fmMeYAnzflt1dLgV2cGV6PeitZfZ1P\nG/MkCQ2RgpIvVxt+KaTqgF8oFYxkWV0+dW3pVoM991nVjXuTmB3I7ECepVDFjH61+V+rIjZF\n1bJ6h/+BuR76WoQlFHxpjxPR1sC6OFUt34c7sUz040IkRjpk5mCgzbdeTGtWzr8CxUFiFvPP\ncTachEyqWzC6gQKJIjUlwDsSOycnp9cfRkREREZGAhUqVLC3t4+JiYmOjgbatGlTq5b6H6hG\nSnoO88/he4OYNPS08KzEr+3l9PBKAHO9Ul0L+F/UtOKv6wqktq4+o7Nz8Z46LJEZxzgcSlYu\nJroMdOWnNuV5xUezeMzBXmQwO5CNt8nKRQTu9izqIF0yvvKMmDRmtZTb3sGYTxqw9wGfNsZE\nlzyB+MyCb/vLjEL7dD1Loaq5gvGqZjyMB7AzYk2Pwh2zyGhp0LMmC87TyUn2wc7N4+ezdK3x\ntsrR9ByuPCM8iVrWNLQrRP3f+xOZQusNeFf5P3vnGRDF1YXhZ6nSpAoCKoqACggCAlaw9xZb\njL1GY4smGjXN+CXGFBNrLFFjizH2EsXeu1QVKyqChaL0upTd7webrAursLgUcZ5f5rozc9bA\nzJlzz3lf7k+lvinifLZc59OjpIlVrl++49yIp/1GzPUZ3BgzPa7HMXgXfRqypV9lVKuu2hST\n2J0/f/6/P1+7ds3Pz8/f33/p0qVubrLb4a1bt6ZMmRIUFLR48eIyDFPg7SEzl9Z/kJTN/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V/C/g/eqAL6JrhYYqzLrluFFZ123aalio0f\n5cn0Zgxz4+pTYtKpZ0KzWq9rF152lfWhCoKFAREM2Y2dMZ80L59431HeyHRTIpFERUVZWloa\nGFSE+6CAQNlga4TtSzIf56P5PZj7iRhXo2VtpjUr0RZzA3OujOWjg/iula00r8XlseVUehQQ\nKIqNEREJhRcfJpMvVZLwVRKGuTN6H+O85N5lEikzjlLfTDX5pPFedLRnZRDX4tDTYpI3k3zK\nY/T1Vehq8qWfbIB0kCtAdh7zzrDrFudHV1hUJcFCn24l6MgEllzmK3+F7fJujsz1Z9Flpjer\njJO/VQbVEruzZ8+uX79+5syZzs7OCQkJHTt2DA0N1dTUnDx58i+//KKpWVkryAICpeWTIyy5\ngpUBqWKy8zgZyS+XODuqRPmZkzknhpOYRXQKtapXRmligXeK/s4sv8poD4Uuz/+dobGlyk1y\n5cZAZ47cp/laJnrjZUNKNhuvEZHA4aGFp9eLxd6UnzuWTZSl4tPm5EsZ9w/Tj2BlQGQy5nrs\n/6CKDB8kZROZTMciO90d6zP9CAlZwv2wDFEhsTt8+HC3bt2kUmlBs928efNCQ0Pbt2+fnJy8\nZMkSNze30aMr94uGQNmTk8+9BBKysDeldmWtAZScPXdYfhWgRW2GumGmx/GH/HCBVn+Q+Bma\nJduiNdMrq2mJp2ncT8RMDyfzCttREniL+KwlB+7htpIZLfCxJTqFlUEEP+PEa5vfKxaRiD96\n08+Z5VfZdhMLfdrW5fPW/HmdeWdwNKO/c+UV9X09IhGzWjKqCWejeJyKSw387FRWVqoknIwk\n6BmZuTS0oHdD9LR4/SylMGhZpohKPsraunXrkJCQQ4cOtWrVCrCxsaldu3ZgYKBYLHZycrK1\ntb148WJZhlp6jhw50rt37+zsIiYGAmplQxhzThCbLvvPjvYs71aaxurKQ7ctnHrE1/7MaSVf\nvPSEFuv4Xxu55lb5E5HI1EMcvi+zaLTQZ0F7JfZrAu8yzzNZeJGQGLJyaVSDj31xtSQrj18u\nsvk6D5OwNMDfjgUdsCtOLbnykJ3H6H3svEWfhtiZEJnE/rsMdeP3nqXshRV4Q2LTGbaHs1G4\nWqKvTXg8ptVY3wd/O+ouZpIPM1sofP7XSyy6TPS0qrMVq6ent2fPni5dulR0IHJUeDu4efNm\nz549/fz8gPDw8Li4uM8++wzQ1dX18/MrULwTeGdZdpXPjvFNG0Y2wUyPG3F8eZJWfxAyXokt\n+tvCjXik0sJ9vs1roa/N/rsVltjFpNP6DzytuT+V+qZk57E2hCmHSBGXlcKfwFvH6Ue8t41a\n1envjIE2xx/isZofO/BJc770U0Hat7LxzWlOPSJ4vLwXIjSWTpv56QKfq298WKCESKUM3EGu\nhFuTZCrc6TnMPk7Pv7g1iam+zD2NpzXt/7WGOxjB3NN85Vd1srrKiQqJXX5+frVqMp2GY8eO\nAW3atJGdRUsrM7PEU1UCVY6sPL48ya+d+aipbMXTmn8G47uGH86zvFuFBvcGaIiorlt4lzNf\nSr6E5FdILcRl8Od1rsVSw4B29Uqk+6oqP56ntjH7P5CVKKppMdkHAx2mHuJDr4rsBxcoT+Iy\nWHiR0Bhy8mlUg+nN5JJsGbkM3sVQNxZ3kTWizWjBtpsM3oV/3dJ4wFQS8qWsC+Xnjgodrh41\n+V9b5p9lTishXShvLj7hwmPuT5VPKBvqsLQrZ6NYEcj8diRl0/VPGltR14RHyYTFMsmbGS1e\ne1KBN0aF4rWjo+OJEyfS09Pz8/PXrl1rY2PTpEkTICcn58KFC3XqvJ1tDgLqIPApGTkMV3QB\n1xQx3J0TkRUUkzpwsyQxC7Gi5/q+O+RKlO9erQ+jwTI2X0NTg8gkBu2kwyYSVLHRLAknIvnA\ntfDG0+DGiPO48kTN1xKonBx9gNMyjj/E25a29bifiNtKVgTK/vZQBOk5/NhBYbzgfRfa1GVj\nWIXEqx7i0nmRScsij5qWtXmaRpLQa1PuhMTQyKKw7oyGiK6OhMQgEvFtW4LHM8AZKwP6OxP8\nIUu7CiJ2ZY4Kid3EiROfPHni6urq5eV169atkSNHamhonDx5skWLFhEREf379y+7KAUqOali\n9LSV1Ios9FUQEa2E/NgRiZRma3mQBJArYeM1xu5HV4v3GhX+8IXHjN3Pd+0IHc/63ux+n1uT\nSMpm+B41R6VUslVXEwOdt/tfW6CEpIgZspsPvbg0BlsjIhKopkWbukw5RHg8wP1EXCyVCIx5\n2xCRWP7xqo2Cl5nsIiZgBSvawvxQuSORKp8h0xTJxyMaWzK7FSu6M6eVYDtRTqiQ2I0cOXLe\nvHnp6enh4eG9evWaM2cOcPbs2eDg4B49esyYMaPMghSo7NQzJT2HR8mF18Pj1WOKKs4vXDYr\nH5xrMKsl1+JwWEqNnzFawIQDiES41JBL2P/HykDea8hkH0QipFIeJXM/kW/8CYjgXhHxsDfB\n3pSw2MKLj5JJyaZe5bOgLWt23KLTZmouxHM1c06Q8g6ktvvvIpUy2gO3lXx7Fj1tGpiTK0Eq\nZWIAgIEOKcrKVyniYnbqs/OISiFPUiZhvzmWBtQzYd+dwuv77tLIAqM3NjAUUBV3K249lw/M\n/cepRyUyMhEoI1TosdPQ0Pj666+/+uqr3NzcApMxYPjw4SNHjrSzsxMJ3Q3vDPcSWBnEvQSq\n69KiNhOa4lIDT2tmHGVrf7k10O0XrAzihw6lv5BUyl/hfHdWpqrqaM7X/gxyKddOmgUd8K3F\nJ0eJTAIw0GGcJ1/4KZEXuRbHhKYAobFMDuDiv96UmiLWhKhTQGuYG9MOM8YTlxqylTwJnx2j\nsRVu75L6cb6UgTs4cp8pvoxsQkIWa4LZEMaJ4TjXKP7wt5f7ibhZMWIP9c3Y1l/u7dtzKwfv\ncewhfnZ8fIhrcQpWxRm5HLhXeETxP4JjmH6YC4+RSNHRpL8zP3XE1qjMv4uqfOnHpABqVWe4\nOxoi8qX8EcrCiyq7OVcNErL4/hwXokkR42DGeC96lMw8V1342eFuxdDdbO1PDX2APAn/O0NY\nLH/2LddIBF5GZc2cggTu5s2bKSkpDRo0qFevnpDSvVMsu8rMo3jb4m1DqpjvzrImmH0fsLEP\n7TfhuoJRTbCtzqXHrA+jh5OSylbJmXqYDWF87U/n+kjhyH0+/IcrT1hcvnPlfRrSpyEpYtJz\nsDF8ZVopgjwJt1/gv56ujtycSAMLYtJwWsaiy3hZy/Tl35yRTTj6AK/VjGiCmxWJWfx1g4RM\njg9/t5rHfw/mVCQh4+WSOhOaMnAHI/dydVyFRlbGGGgTm86dFzz4WJ7VAeZ62JmwNoRt/Rnk\nSq+tLOtKdyc0RYTFMuUQ1bQYo+z38dQjOm+mvzPnR2NvSvAzvjuL9+9cHVfpRtpHe5CczZRD\nzDhKbWOiU8iT8GtnBjeu6MjUTa6EJZdZGURUMub6dLBneTdMX7KZDnpG5z+xMWKEO5YGnI+m\n33YGN+aPXuV3H9AQset9+m+n4XLa1UNfmytPSMpmxwDZkKxAhaCCjh0QExMze/bs7du3F2jC\nHTp0SCwWr1ixYtGiRc7OzmUW5Jsi6Nipi/PR+G9gbS9GNZGtJGbxwS6SsrgylhQxC85z7AEx\n6TS25EMv+r/BD0XQM5qt5cwoBefEs5blnj8AACAASURBVFG028jVcXhWvsm+Uft4loaxLili\nDg+R3VsLRO8+bsauW0RNU2fX8O7brAvlQSJmerSqw5zWCjf9d4EW6+hYn3ltFBYfJVNvCbcn\nyUdEqx6Xn9ByHRYGxL3U/5IipsEy2tUjPJ7rH5GVx1cnWXoFXS2qafEik14NWNaVOsqGfpx/\no209fntpej1XQqs/cLVkXa8y/zqlICads1E8TqGOMf51sSpfS8uMXO68ICuXhhZlZZ+QlE2r\nddxPIl+KrRHZuTzPRFeL86NlQ80SKS4r8LZhfR/5iExYLC3/YE3P8k5zJVJ23eZcFOk5eFgz\n3B1j3eKPqjK83Tp28fHxrVu3fvDggYeHh7u7+4YNGwALC4vTp0+3bt06MDDQ3r6Ie4hAJSM9\nh98CCX5GVh6NLPjIWwUjbeD3YN5rKM/qADM91vSk3hJCY/G05scO/KjK3mtBzW/XbaKSsa1O\n5/p82052m953l+a1C/th+9nhY8v+u5UxsZvejKa/o6XBqp6yrO56HKP3McCZT5uz5DL3EtSZ\nbfRtRN8iAxzvFJHJSrZc65qgr01kclVO7JrVoqktQc848wj/ugB3Exi1F3N9GlvJxiP0tFjY\niZktuREn+2V3MFN+todJ3H7B3kEKi9oaTPRm1rGy/SKlxtqQ910UVp5ncuUJydk0qYlrmTUk\n5Er4+QLfnyMjF0AEw935qSOW6s4s553mXiJt6rKhj2xDPOgZ7TbScROJswCuPuVeAidHKAw+\nN6nJCHf+vF7eiZ2GiAHODKi8tZ13DhWGJ+bPn//gwYMff/wxODh4wYIFBYstW7a8ePFiWlra\n999/XzYRCqiNoGc0WM6qIGyMcLPiTBQuv7EuVIUzhMcr0RqoY0yt6tx8rnI88Rl4rGbPHT5t\nzsEhfO1PcAyuK7ibABCbrlxSxM5ESa9uZcDNiu0DyMpjagD+G2iyCo/VuNRgbS/Za70wsqpe\njHR4UUQ9Mz2H7DyFDcoqyZ/9kEppvwnzn7D+hYbLsa3O0aH8c5cWL70LWRnQwZ6eTjiYIZGy\nLpTOf+K0jDYb+O4smbmA7N+w6JZr7eq8yCzGGKoykCvhq1PUWcTQ3cw+TuOVdNrM/bIZ/p0c\nwJIr/NadxFlkfcHx4VyPo8MmJYO6b8jm6xjrcnCwvM2xqQ1/DyApmwP3ACKTsTLA2rDwge41\neZik5mAE3jpUqNjt27fP09Nz5syZhZrqvLy8OnXqdOrUKXXHJqBOsvMYsIOO9qzqIbMjnN+O\n1cGM/wcf2xJZ2gM6mspvYdl56KiuNfDFSarrcnEMev/+GI5qQve/mBLA0WHUNOSkMg28yCS6\nOKh8rfKhT0MczPCxpb4pxtVoWZtmtQACnyGCuqoURwWKpb09m64xoalC0WJDGEY6b7EGbwlx\nNOUjb3beYqI3DczxsqGGPtMOc+s5fysTnsrKo+ufhMYyzpPh7jxIZHUw68M4PRIbI4AHSYVv\nAg+SsDF6C7o2Pz7E7tvsGCCbG3icyof/0GYD1z9Ss0fz3QTWBHNmFK3/fbltV4+TI3BcxsZr\njPdS24WkUpKy6eFU+KbqVwfg2EN6OFFdlxQxuRL5sFoBLzKr/luNQLGoULF7/vy5i4uL0lGJ\nGjVqxMYWEWAQqEwcfcDzDH7rrmAyPd4LPzv+KHHRrlkt9txGovgSf/Ex8Rn42Koc0q5bzGgh\nz+oADRFftOZEJEnZ9G7A5Seci1Y45PQjAp/Rq4HK1yo3Rrhz5hHjvPi0uSyry85j1jE6O6h/\nv+Yd5/PWPEyi11ZCY8mVEJvOgvPMPMb89m+rk7pKLOrMMDe+P8es4/Tbhu2vhMVybLjyLrof\nzvMwiVuTWNiJIY352p97U7A1YtJBalWneS2+PaNQnEvLYdGlN+qRLR8ik1kdzPYB8mnQ2tXZ\nNwhDHZZfVfO1TkVS30ye1RVgUo33Gip/BS01IhHaIvKLCDwV7FQUiPm1qI1EyrZwhQ/k5LPl\nOu2Flqh3HhXufy4uLkFBQfn5+ZqaCu8RUqk0PDy8UaN3u9+n0nPnBS6WSlSsfGy5FlfSk0z1\n5Y9QPjrITx1l7bGnHjFyLx+4qtarB2TmkpSNY5G+H0dzJFJi02lqw0Rvuv7JJ81pb49UyolI\nFl1isk9lbLD7jxktOP0It5VM9aWRBTHprAwkV8LpkRUdWSXmcSq/XeXWc3S18KjJZJ8SVR1q\nV+fsKKYE4LlatmJtyOoehR1Qqio6mizsxFRfzkfzIhM3K1rbKRQvX2bzNT5rqSBfoqfFDx3w\nW09CFit74L+e5uuY4iubil14EX3tCnNDLjnno7E2xM9OYVFHk37OnI1S87WSs5WPSljoE5Wi\n5ms5mnP+MRKpwrjV0qtoIMssTavxlR8fHeRFJiObUF2XkBg+O0aquLC3tcA7iAqJXY8ePebO\nnTt16tSFCxf+tyiVSn///fegoKDZs2eXQXgCakNXi4wcJesZuSqUN+xNOTGCkXuxXoiDGali\nHqcyzI3fuqscj54WBto8TSu8/iwNkN1Al3bB15b55/j+HICjOWt6Mcil8CGVimpaHB3Gxmts\nvsbqIOoYM8SNGS3Kz8L1ehzrQrmfiLEuLeswzrM0u+TlyaZrfHSQRhZ0qk9WHutCWXaVXQMV\nesVeRSMLjg/ncSoPkzDXw8m8sn9ZtVPHuPhOeYmUqBQlIwWuluRLiU7BoyY3J/HFCWYfJyaN\neqYMc2d2q7fAdzgjByNl7wBGOrL5BjVSz5SIBCW7n7eeq0eG/WWWdaPdRlxWsKYnDS14lsby\nq6wNwcJA3ogypxVmenx5kk+OoKdNZi49nTg7SqYnJ/Auo4LcSW5urr+//6VLl6ysrLy8vAIC\nAjp16pSUlBQYGOjq6nr16lU9PbV2NKgPQe4ECHqGzxpuTJSr2gLifJyWMdnnlbKlSsnJ59hD\nmUCxry1xGawP5UESZnr42THVV2F39TUM3EFSNoeHKpQZRu3j1nOujFX4ZIHtRFFN4CqGOJ+7\nL0jKxsGslNqw/zvD/87gZ0eTmqSI+ecupnocGqL+B4+6uJdA45X81JGpPrJ2rpx8JgdwMIJ7\nUyp7YpGew/fn2H6TR8nYGNHBnvntlfSzVwaMf2Bdr8Jbqw+TqL+U+1PfYsmx4w/p/hcxnxZu\np+u3HQNtNr2nzmuliqm/lA+9mN9Ovnj0Ad22FFZlKgXHHxIcQ1YujWrQuwHVtFh8mZnH5C4g\n2hoY6XJgMM1rKRyYncfdBFKycTCTtUsKlDOVUO5ENR277Ozs5cuXL168+OnTpwUr5ubmEyZM\nmDVrlpFR5f2ZEhK7Anr/zZ0XrO0lK+Y/SmZSANdiuTmplLJDUinjD/BHKP2dcbUkMYvtN9HR\n5NjwEj0qHiThuwYPa75ti4MZj1OZfZyTkfjY4m5FzwZ0raxDEmXBmhC+OMHzf8c8uzmytKtq\nT9zD9+m5ld3v0/PffqNUMQN2kJLN5bGvPbLimHOC4w8JVNQTzsjF5hfW9GRgJa7OJmTRYh15\nEqY3w9Gcp6msCuJ+IudGK7w7VRLe20ZuPgcGKyx+eZItN3g49S2YkHgVuRIaLadlHdb2khfS\nAiLotZVjw2lbV82XOxjBgO20qkN/Z/S0ORfFH6HMbsV37Yo/9lU8S2Pobi4+xtUSPW1uxGGh\nz4Y+tKrD0zR+vkhYDEa6NK9V0hYFgXLmrU/s/iMtLS06Otra2trM7BXiSJUJIbErIFXM9CNs\nCKOmIQba3E+kngmWhiRkUseYng2Y6F14l+H1bL7ORwc4NRJvG9lKZi59t5GWw4XRJTpDZDIz\njrL/LnkSCh4u/vVoas3TVPbeoYM9f/dX4mVe9fj5IvNOM68tw9ww1eNaLHNOcDOe0AkqiK8O\n2IGuZmEnn/uJOC3j2kclHXwuZ97bhp2xEisR/w20r8fXlbjHa8ohTkVyZZy8rCiV0mcbKdmV\nsZ8yPJ5ma+nVgLltaGBObDpLr/DzRbb2ewsmJF5P4DO6b8FUj94NMNQh8BmHIvjSj2/alMnl\n7ifyxUmCnsmqa3Na0eENhhUkUlr+gaaIzX1lbcppOcw8yt/h3J5cSau/AoWohImdCj12Uqn0\nv5FYIyMjFxf527REIlm+fPnUqVPVHJ2AWqmuy7pezGlFaCzPM1h0hcQMBrhgZ0JkEt+cZtM1\nTgzHpMQGBhvDGOspz+oAfW0WdcH5N+4nvlIQ9WXqmbBrIFl5LDjPoksEDJEPnT1IotNmZhxl\nheoNfOolLJazUcRnYG9KDyf1D7emivnmNMu7yZWfm9oQMASv1fx8gYWdSnqeW8+Z7FN40cEM\nK0NuPa+kiV01LeW9UJm56Fbuydbdt/m2rcJmsUjEl374ruFFZlkZEpQaV0tOj2RyAA2XY6BN\nRi71TNg5kN6VeMC8hHjbcG8Kv1zi6lPSc2hgzuWxmOqx45bMHMLbRp0lSQcztikTlCkdFx4T\n+JTIadT+V0fQSIcV3Tkbxe/BzK3ELzYClZni751hYWGzZ88OCQlJTU318PD49ttvO3TokJqa\nun79+pCQkMTExPj4+Ojo6NjYWCGxeytwMMPBjAkH0NXg1mR5QWh6c9puYO5plpT4xeNuAqM8\nCi82ssBQh7sJJUrsCtDTYu9tZrZQkBKob8qizgzayc+dKqzXKiefiQdZH4abFXWM2RDGp0f5\ntbOC98abc/kJ+ZLCLfDaGgx1Y2v4K45Rhq4mWUWSJKmUrNzK257YojY/XSArT6Ev82ESYbEs\n6lxxYRVHnoSYNBzNC687miGFJ6llm9gFRHD8ITHp1DOhv3NJh8Sb2nBpDFEpRCZjY4S9qWrl\n+cqMSTW+bSv7c3oOnxxhXSjGuuhp8yyNVnVkIwiVkKBnNLaSZ3UFaIjo4kDwswqKSeDtp5jE\nLjw83NvbOy8vD9DT07t8+XKXLl1OnDgxc+bMwMDAlz9Zmb1iBQqRJ2FrOH/0Vtjmszbka3+m\nHGJR55Jamuprk1bETSEnn+w81fZPJVJuv6BVEU+LlnXIyuNhEenUcuOzYxy+z9l/O6PzpawM\n5MN/qF39jfZfCpEqxkhXSe5loa+aWUWL2uy+zfRmCvWJE5Gk58gU9Soho5qw6BK9t7Kiu+xN\n4NITxu6nbV0lPw+VBy0NTKopcUApWCm7rC4jl4E7OP6Q9vWwMeJcND9dYFozfu5YoqKUSERd\nkyoulD18D+HxnBoh00CJSmFyAO03ET6xMpop50tkunSF0NIoLBcqIFByinllmzt3bl5e3vTp\n01NTUzMyMiIiIpo2bdq9e/fAwMDx48dfu3YtNjY2NjY2Kyvr5s2b5ROxwJsTl0GqGHerwuvu\nNUnMIiGrpOfxs+Pv8MKmQztuoaOpsD9bLCLQFMlGX19GnAcov/GVA6liVgaxtKt83k1TxGQf\nhjRm4UV1XqieKQmZxBTJEsLjVZtmndGCG/GM3k/Kv+ngsYcM28NH3tSsrM06hjocHUaeBKdl\nOC6j1q+0XEdTG7YPqOjIiqO7E8uvyocWC1h8GXcrJfZc6uKTI9xLIHwiAUNY24tzozg2nNXB\nrFXFGLAsyJfydzizjjPtML8Hk65MWakcCI1l7x12DsTPjvB4vjjJnOPUNSFPwuqgignp9bjX\n5EZcYWc8qZTTj3Arcn9+FxDnE/SM3be5+pQsdRu1vTsU88wMDg6uU6fOzz//bGRkJBKJHBwc\nlixZkpGR4eTktGLFCjc3NysrKysrq2rVKt+rkMCrMdRBBMlFhkmSs9EQqbDvOacVYbEM3SO7\nMUmlbLrGRwf4ojWGOirEIxLhbcu+O4XX993FTE+JiHH5EB5Pbj7dHAuvd3MkOEadF/KsiXMN\nZhxVyBJuxLM2hKFuKpynrglHhxESg80vuK3EbjE9/mKYG79W4j1NwMGMkyMI/JCv/fm1M3cm\ns7GPCo2eFcV37bjzgo6bufiYF5lci2PYHjaEsaxbWV0xPYeNYfzcUeE3om1dpvqyIvCVR5UD\n9xLwXM3Hh3mUTGIWP12g4XJOvMKM4VEyAREceaBEw/LNuRBNAwvcrPjyJB6rORWJnjaPkknI\n5JdL8heeykO7etibMmS3/HU6T8LnJ7n5nPFNKzSyiiAgApff8F3Lx4dpsY4Gy9h1u6Jjejsp\nZiv28ePHnTp1etlqonHjxkDDhg01NKpKg8a7h7EuXjasD6OpYl1tfSjNa6mwi2pvyskRTDiA\n1UJsjUjMQkuDeW2Z5qtySF+0pudWHM2Z6ou2BlIpu24z+zhftK6wil3BVkjRXWlNDTU7o4tE\nbO5Lx024r2KEOzUNufiY9WEMcGaYKokd4GtLyHjORXEtjhr6tKqj3GCqEuJl/ZYZvNoZc2Us\nkwJo+YdsxaMm50cX/p1SI/cTEefTpm7h9TZ1WXgRqbRiVEtyJfT5m/pmnB4p2+vMlTD7OO/9\nzZ3JCspqcRlMP8zf4ehqIZGSL+FDL37ooETC41EyRx4QnUKt6nSwV+HVTpyPoQ5bw/nlEvsG\nyd/KpgSwPoxJBwvPjFc4miL2fUD/7TRcTtu66Glz6TFJ2ewciN1b8purLk5G0vtvPmnO7FaY\nViNVzKLLDNpZRUZ8ypliEjuJRGJgoDAEqK+vD2hrvwMSFFWab9vS4y90NfnKH9NqJGQx7zSb\nrnFyhGrn8bTm8ljCYrkRj7UhPralrLV0cWBdLz45wrdnqGfKszRSxcxqqZpysnpxsURTg9OP\n6FRfYf1UJO411Xwtj5rcm8L35/jrBvEZuFmxfUApb2eaItrUVfL4F3gTUsTMP8vRBzxNo64J\n/RoxvTl1TTg4mORsmUBxWXsBF7zhFO1YyMlHU1RhWnSH7xOVwsUx8l98bQ1+7sixB6wNkQvW\n5Ero+icaIi6MwdcWiZRTj5gcwMAdHB6qcML55/juLLWq41KDXbeYdpiZLfi2bYm+YEMLbj/n\nt0DGeynU2u8l0tGebTdZ1q3Sddo5mhH0IRvCZBIqozwY51nppqrLgS9PMqoJP3aQ/Wd1Xeb6\nk57D5yeExE5lKreigECZ0cWBgCFMOMCiy1TXJVWMgxlHhpWmY11DhKe1Gvxbh7vTw4mTkbLH\nZIVXm0yrMbIJEw+yd5DMjkkqZcsNfg9m1/vqv5yZngrKJgLlyaNkWv2BvjaTfHA041ocS6+w\nNZwzIzGphkk1mqg70VdKAwtMqnHwHqMVR9EP3MPHtjwCUMq1WDxqFn6d0xDhX1fBhHpbOA+S\neDBVlrJoiOhoz4HBOP/GqUdyJeF1oXx/jo195NrU/9xj6G4s9JnWrPhgOthjZUjgUz5+adNg\nXSgnHnJ5HPvucuv5m1pElAXaGozzZJxnRcdRcYjzufyEBR0Krxc0ND/PFHzSVENI7N5dOtXn\n1iRuxPM4hTrGuFqqYBpbRpjpVS651CVdGLaHJqtobYedMYHPiEzihw5yaweBd4Eph3A058hQ\nmRFtN0cmeuO7RjVtoDdHW4NZLfnkCJYG9HACyJey7AprQzg4uLiDywwNEfnKOhPyJQptDGej\n6Fy/cCHK0QxfW85GyRO7ny4ws4WC40hPJ7725+eLfOxbfNFOV5PtA/BZw7TDBD9DT5vz0ZyP\nZkV3nC2QVtwklsDrycxFipLdnoKVjBwhsVONin6SC1Qo1bTwtlFtgvWdQl+bXQM5E8XpR8Rn\nMNqDfo3UrBaRmYu2ZtVRFKt6JGdzKIITI2RZXQHGunzWkjknyjWxA2a1JDOX/tupa4KNERGJ\nZOexoU/hboHyxNOaeWeITVeYvM6TcPQBY14qQWXkKm/SMK5Gxr8jtOk53Euge5G3pu6OzDhK\nbEaJnBi8rOloz/NMwuNJz8HDmtU9sDdl+030tSupTLeAiS419Al8WlirIfAZBtqCB67KFJ/Y\nnTt3rqhXhtLFw4cPqy0uAYFKg78d/nZqPmeuhN+usvgyUSloa+BekwXt1amNJ6AunqaRL8W5\niP2rcw3iM8jOK2WdOyefdaGExpCTT6MafOhVot4vkYj/tWWMJ8cfEpXMOC+6OFRw01jH+rha\nMmgnG9+T9funiJl+mKRsxr6U2DmacTCi8LH5Uq7HyTuoXjWuVLBScl23r/xps4H+zsxsISvR\nHXvIpACmN3sn/AnfRkQiRnnw3Vk6O8jlmuMy+OokQ9wU3qkESkLx96T4+PgjR46UZFFAQFWS\nstl3hwdJmOnRqs67UjuUSOnzN4FPmdOadvVIE7M1nG5b+KUzU4p4gglULAVpU1x64c2g+Az0\ntUtp6XHrOf23k5iFf110NFkTzOLLbHqPjiXL7O2MGVPE8aWi0BSx532G7Kbhclwt0dXkRjw1\nDTk4WOFfbIgbC86zOpjxXrIVqZT/nSFNTN9GspXqutQz4diDwvPRxx5iaaCCcWrL2mztx5RD\nLL+KkznxGdxPZFoz5rUt/liBimKuP0HPaLicYW64WnI3gU3XcK7BTx0rOrK3kGISu4iIIi9Z\nAgJqYttNJgegKaKhBYlZzDjKIFfW9Kz6b9Xbb3L6ETc+kusPt6qDpzVTAnjfpcyHKwVUwsaI\nxpasCVHYdZVKWRNCp/qlmUXNyafnVlxqsOk92e5kTj5fnqTP39ybgu1buOtUx5izIzn6kNAY\nxPl83IzeDQpXWRzNWNGdiQf55y7t7cmXcOAewTFs6avQeDetGV+dwstGnuOei2buKaY3L6kd\nTgH9nelUn8P3CY+ntjHt66mm9S1Q/uhrc3wYW26w7y6br1OrOr90YrSHav/fBQoQSdUryVUp\nOXLkSO/evbOziwjyClQcV5/S8g++bcunLWQdZsExvL+DVnXY0KeigytjPtiFjiYbFb+mRIr1\nLyzspLJ2nUBZcyKSrn8y3J3pzWVTsd+d5fQjLo1RskVbLPvuMnQ3Tz7BWBfgXgLBMVTT5POT\nDGnMl35qD78SEZHIwosEPkVLgxa1+axl4fYpqZSZx1h8GQ9rXC2584KrT5nQlKVd0RQe8AKV\nEj09vT179hRtTqtAhOEJgYph8WV6ODG7lXzFy5rVPem0mR87KpjYlj/77rIykOtxWBrQ3p4v\nWmOmp87zx6YradrTEFHHmLgixmICaiRPwolIbj/HQAdvm5LKlLSvx8kRTD2E6wrZSrt6XCxV\nVgdci8XTGmNdnqQy9RB77mBtiDif5Gw2XeeT5lW5Yu1oxuoer/uASMTCToxowsF7RKfQ04nf\nuqlBSklA4J1CSOwEKobAZ3zWsvBi27roahIaQxeHCggJkEgZsZedt5jsw3B3krJZH8rGMI4N\nx0N9WmU1DYlMVnLp6BSsKqupaxXgRjwj93IzHkdzMnKITmFEE5Z2LZGHXqs6hIzneSZPU6lr\n8kaOZ5oa5EnIyqPjZsz1uDsZJ3OA3ls5EcnwPewcWPqTVw0aWwrjqwICpUdI7AQqBolUiaaU\nhghNDeWyWOXDlhvsvcOVsXIH7glNGbGHobu58ZHauj16N2DMfr72p/5LfT/rw0gT07nidCuq\nNvEZtNlAu3ocGiLrYrz0hBF7GLyLfYNKepIa+mrQ02pqw7dnWHKZlGyujsNIByBXwo14Jniz\n6BJBz8rQl0wi5dhDgp+hq0XL2jSrVVYXEhAQqCgE+SyBisHdilNFbMKvPiUjR55UlT+brzHG\nQyEATRELO3HnBSExarvKQBf87Wi2ll8vcS2O89FMCmDCAX7sKExOlBWrgqhpyLb+8n/h5rXY\nM4h/7nLzeblG0sEe5xr8eok2dWVZXUIWQ3eTKmZ2S9ytOBtVVpe+HofPGgbuICCCv8Npu5Fe\nW4nLKKvLCQgIVAhCxU6gYvi4Ge034mcnF7uKTGbMfvo5y3WMyp+HSbzvWnixpiHmekQmq62O\noiFi3wcyHbtPj8p07AKGlFTtQqAUXHxMT6fCNVeXGtQ340I0LqXqlisdmiIODsF9JTtuEZGI\njibh8dQ0JGAIFvoY6pCRWybXTcqm/Sb87TgyDHM9gAdJDN5F322cH1VhVrMCAgJqR0jsBCoG\nfztWdGf6EVYG4W5FYhZHH+Bfl7W9KjKq6rq8yCy8mJNPWg7VddV5IW0NpjVjWjPBeaKcEOej\np6yXTk8LcX55B2NtyDB3jj6gXyNy8pn2rz5Idh7h8XzkXSYXXR+KkQ5/9ZMLkdQ3Zc/72C/h\n5CPa1yuTiwoICJQ/QmInUGF86EUPJ7bc4HocjuZM9K5IZ6QC2tvz53U+aa6Qaf11AxE0L5tu\npCo8Aqkqh+6zLZx7Cdib0qehml2DXS05H1148UUmdxNwrYg+/eHuLLlMreoM/VfdRiJlzgm0\nNWU+sGrn6lM6OxSWl7MxwtOaq0+FxE5AoOogJHYCFYmNETNblMmZg2M4cp8nqdQxpodTSR/e\nM1uw5Tpd/2RBB5rUJCmLP6/z9SnmtlFzxU7gZXIlDN7FgXsMbkwPJ6JTGLWP34PZM6hEI6sl\nYawnnqtZGyLf+k8VM2of9qb4vdYvLjGLOy/Q1qSBuTp/Btyt+LUzo/axIYxWdRDnExBBVDI7\nB8oa79ROrkTJuBKgrUmepEyuKCAgUCEIiZ1AVSNfyuQAfg/G15YGFuy6zVenmN6MHzsU30hk\nacC50Uw9hM8a2UoNfRZ1YZznaw8TeDN+OM/5aELH09BCtvKFH202MPs4y7qq5xLuVqztxeQA\n1oXSrBYZORyMQFPEP4NfqXybmMXnJ1gbgrYmEikaIma24PPWpTSHLcpUXzrYs/gyJyLR1aRT\nfSZ6cyGar09RXZdmtWhVRz0XKsDVkj23kUoVfgtSxYTEML2ZOi8kICBQsQiJnUBVY8E5dt7i\nzEj5c/HoA/pvp44xk0vgxFrflIODeZrG/URMq9HAopR+oAIlZ3UQX/nJszqgdnV+7MDoffzS\nSW0W4KOa0KYuv13lzgsMdJjejIner9wKz5PQbQvpOZwdRfNa5Es5fJ+PDhKRyNZ+6okHcK7B\n7z1lfz4YQas/EOfhYkmqmNnH6e7Exj5vpJn3MqM9+PkC887wpZ+sdJeew/gDWOi/TjZy5y3W\nh/EgETM9/OyY3Upt8QgICJQRuSUseAAAIABJREFUQmInUKXIl7L0Cv9rq1Dt6FSf2a1YfLlE\niV0BtkZvpWvn20haDk/T8C3SwuhjS1oOT1LV6fJZz4SFnUr0ye03uZvA3ckyeRQtET2cqGOM\n52o+aY63unXm7ryg3zbGN2VBe1muGRLDkN0M38P+D9RzCTtjtvZn1F623KB5LcT5nI1CT4s9\n7yuvQeZLGbSTA/cY1YRBrjxNZUMYG8I4PrxiuhIFBARKiJDYCVQpnqXxPFOJbkjH+nxxkvQc\nDMumgUmg1OhqIoL0nMLrBSvq2vdUlRORdHHA0oBcCb9dZU0IEQmY6mGky9/h6k/sll/FtxZL\nXnKb9LTmr354ruZuAg3M1XOV3g2ImMraEG49x1iXr/wY7fHKf+F1IRx7QMh4Gv1bSf20BYN2\nMmIvwR+qJx4BAYGyQEjsBKoUBUJlkiLeFQUrglhXJURHk6Y27LhZ2D93xy3qmRQ2iS83UsVY\nGZCTT6fN3HrOtOYYaHP7OX/fZMllOtdX8wR30DP6NCy86FETa0OCn6ktsQPM9ZhVxMpPKZuv\n86GXPKsDtDX4qSMOS7n5vFyV/wQEBFRCkM8SqFJYG2JtyMEI+YpEytEHzD1NTUPuvKi4yARe\nzby2rA5m/jmy8wByJSy7yvfnmNe2nAI4G8VvgawIlLs+2JsSFsuqIG4+Z00vtoXz6REO3Sc1\nGw0Rg3a+bpI0VaxyAHkStJW1ElbgyOrDJNyL+CPXN8VQh8ikighIQECgZAgVO4EqhYaIGS34\n5jQOZvR04vYLRu4lNIZ8CeYG+K5hcGOWdxO0SyoXXR3Y/B6fHGHeaWyMiEnHUIfl3RjmVvyx\nb8jDJEbt49Jj7E2RwsMkWtVhfW8GN+aXiyRm0cOR93cwoglnR7EikAXnmNGSuaeYfqTwxO6T\nVGYd5+A9UsSYVKOnEz90KGnFsUlNTkXyaXOFxYhEHqfQpEh2VT5U1yWhiFh3Zi5ZucKvj4BA\npUZI7ASqGtOb8SKTftuoa0p0MpoaaGowry1zWhH0jOF76L+do8MqOkoBRQa50t2JK0+ISqFW\ndXxsMS376UtxPt22UKs696ZQ1wQgMpmx++m2hbAJfN+eWceJSadhDRpb8t7fXHzMpvcY6MLC\nC2wI49fOciHrewk0X0djS3YOxM6EyCS+O4v7Ki6NwcGs+Eg+8sZnDSuDmOAlaxh4lsaw3bSs\n86bWyTHp/BHKnRcYaONty3D3ktqctK/HpmtM8lGQg9l4DQMdvG3fKCQBAYEyRSSVFmlHqnIc\nOXKkd+/e2dnZFR2IQPlxL4HZJzgVyXft6O4oe2wD9xNpsJwrY9Vm/Crw9vLndSYHEDUd45dK\nUEnZ1F3Mqh584ErjFdxJwNoQC32a1OTz1jiYkZmLyQ/kSggZj8e/5bQefyGFfz6Q29HmS+n6\nJ/ra7B1U0mAmBWBnjJcNqWKOP6SeCfs/oI5x6b/g5utMOohzDZrXlkn3Geuy7wMcS5BrPk3D\nYxVeNixoj7sVSdmsCWHeaX7owFTf0ockIFDF0NPT27NnT5cuXYr/aHkhVOwEqiZO5kilDHdn\nkqLzpoMZLjW48FhI7AS4+pQ2dRWyOsC0Gv52XH3KB64MdOWb0/zSmQEv+ZutCsJIl6QsMnNl\nK1l5HHnA4aHyrA7QFPFpC3ptJSe/RFJ8Q91oW491IdxLwMqAZV0Z4vZK8eSScCOe0fv4tTOT\nvWVVwFQxg3fRfzsh44s/s60R50YzJQCP1ehrk5lLTUNWdGdkk9KHJCAgUA4IiZ1AlUWch56y\nH3A9bcR55R6NQBGSs7kWR1KWLNsu/5nlXIlysQ9dLXLzAaY14/tzTDwI0LI2cRmsC2F1MJ+3\n5ruz8rpXQiZ5EuyKlNbsjMnJJykbK4MSxWNrxNf+pfwuRVkdRJu6THlJu7G6Luv7YPsL56Jo\nU7f4MzQw5+gwnqTyIAkzPZzMBbFuAYG3AGEqVqDK4lxDie97qpjweJwFsYYKRSLlpwvUWUT7\njQzbQ+OVtFrPjfjyDsOlBpeeFB47zZVw5QkulgBGOnzThjQxw3Zj+yueqzkfza6BHH8oU7kr\nwFwfLQ0ikwufPzIZHc3yaBZUSng8LWsXXqyhj5M5N5+rcJ5a1fG3o7GlkNUJCLwdCImdQJVl\nZBOuPGXZVflKdh5TDlFDnw5FFIwFypN5Z1hwnsVdyPiCtDncn4q1IW028Di1XMP4oDHpOUw/\ngjhftpKdx7TDZOYyyFW2MqMFfRoikdK3EV/742fHuH9IzJJbgQF6WnSuzy8XFQQU86UsvEhX\nB7VZoqmKtqb8e72MOF9mKSYgIFAlEbZiBaosrpas7M6UQ2y+RovaZOVx9AE5+ewdVGF+BgJA\nipgfz7PxPd53ka3UN2X7AHzXsvCigvtCWWOux66BfLCL/XdlgsNH7pMnYff78jKbpoi/+3Pg\nHltucOQ+VobMbsUk78Lp2q+dab6O1uuZ0YJGFtx6zs8XuZ/IpTHl93UK4WPLvjvMb6fQ+Rce\nz/1EfIWxVgGBqovwfBOoyoz1pL09KwO5/QI9LcZ7MdlHcBWrYC4/QSSibyOFRQ0Rg1z583p5\nB9OmLncnsyaEK08ApjVjnBdGRX5CejjRw+l153Ey59oEZh1n1F65jt2ugRXmnAFM9mFlIKP2\n8WtnzPUAgmMYvofujhWmjScgIFAOCImdQBWnngk/dazoIAReosCxt6iammk10lT3bHhzqusW\nVgYuHbWqs6UvQKq4Ukj4WhtyaCij92H7C47mZOQQlcIAZ1b3LP5YAQGBtxchsRMQEChXHMxI\nyORxKrWrK6yHxeKoPlPUCqQyZHUF+NpybQLHH3LnBQY6eNsItToBgaqPkNgJCAiUK26WeFoz\nOYBt/eXNjpeesDaEDX0qNLKqiJYGXRzo4lDRcQgICJQXQmInICBQrohE/NmXTptxW8lwd0z1\nCI1h4zUmNFXQARYQEBAQKAVCYicgIFDeNLTg9mQWX+b4Q+IzcLPi+HD87So6LAEBAYG3HyGx\nExAQ+H979x0YVZW4ffyZ9JBCElogQAi9hbK0IC3SqzQpShOVVQSxAKK4rOUnL+KC7oKigoqC\niihVIDQFqSqgFEEQkBZCh5BAgLSZ949ggNAxyZ2c+X7+Ss7cTB7iMXnmzL3nWsDPUy830suN\nrM4BAGZhn0oAAABDsGIHAMAN7D+rdYd0PEkRQWpe2omudwZugWIHAMA10h16+Xu985NC/VUq\nSNuOy9tdE9tyfQ/yAIodjLX1uMau1fYTcndTZGG93FgVjNgmDUBOe32VPvpVs7qrQ3lJSk7X\n+PV6eLaK+KkxV/nAuXGOHcw0cYNqfajzKRpcVwP+oeNJipykaVutjoVscilNKw/ok81atEcn\nkqxOA0lSql2HE+VwWJ3jb7uYpvHrNbHt5VYnydtdIxupV6TGrLU0GXAHWLGDgf44raFL9Wkn\n9a52eeSpOpq4QU8uVLPSCrPu9p3IFkv2alCMDiWoWIBOJsndTaMaa/h9stlu/7XICbtOafhy\nLf9TyenK762+1fXa/Qr2sTrWvdp+Qkmpalcu63j78npioRWBgLvBih0MNOM31Qi90uoyDK6j\n4oGa9btFmZBNNh5Rx6/UpZLOjNDBZ3V+pN5rqzdWa9yPVidzVetjVfNDebppeV/tflrTOmv1\nQdWerJMXrE52r9LskuTlnnXc20Op6bkfB7g7FDsYaP9ZVS2cddBmU5XC2h9vRSBkn/9bpQ7l\n9Z8WCvCSJDeb+lbXf1pq9Gol80fXCgMXqXc1zemhRiVVLkQPVNCPjyvAS6+vsjrZvapQQB5u\nWnUw6/jK/Tf4xQI4G4odDBTorVM3Wi04deFWGxZsiNOHv2jCz/pun+x5/zwhU62PVbcqWQe7\nVVZCsnacsCKQa9sXr23HNfy+awZ9PTS4rubvsijT3xbiq4eq6rkl2n/2yuCSvfpgk56qY10s\n4M5wjh0M1CxCD89WbKJKBF4Z3HlKPx3WG01vcPzxJA34VjF7VCpI3h7ae0aRhTW1kyJ5de58\nLqXJ3yvroJ/X5YeQy44nSVJ4UNbx8KDLD+VR77ZV169V6V21LadSQdp4RD8d1vD7sp7gATgh\nVuxgoAcqqG6Ymn2mhbuVkq5LaZq9U20+V9tyN7ghqcOhrjN19Ly2DtTeIdrxlA4+q1JBajVd\nZy9ZkR63VLGgfj6cdXBjnNxtKs92NrmuiJ+kG5zhsD/+8kN5VKC3lvfRzG4KD9Kx82ocrl/+\nqf/XzOpYwB1gxQ4GcrNp/kP61wp1nik3mxwO2Wx6Lkr/bnKDg1ce0M9x+nOISua/PBLqry+6\nqvxEfbxZQ+vnZnDc3j9rafhytS2nqOKXR44nachida6kgvksTeaSSgerWhG9tU6fdLwyeDFN\nEzeoY0XrYmWTjhXUsYLVIYC7RLGDmfJ7a2IbvX6/dp2Su00VCir/Tc6u2xCnfxS90uoyeLur\nTVltiMuFpLg7A/6hX4+qwSdqV051wnTgrL7ZoUqF9H47q5OZIjH57u6d9X47NZumY+f1ZG2F\n+mvXKY1dp4upN34dhbuVkKzUdF604C5Q7GCyYB/VL36bY1Lt8r5uXwOxtYGzstn0QXv1qqZp\nW7V4j0rk18S26lNNbmxi9/ccOacXv9OC3Tp7Sfm91a68xjZX8cDbf+F9JbT5CQ1frodnKylV\nBXz1UKRez8v72DmJ+X9o1AptPyGHVCpIIxvpsZrMc9wexQ6urkoh/WedzqdkPSV/3SG1vW6H\nUjiJRiXVqKTVIQzyZ7yiPlKlgpr5oCKCdfCsRq9R9Q+0/rE7uhFfxYJa8JAcDp1LubvVPtzM\na6v05lq92FCfdZanm1Ye0IjlWnVAn3exOhmcHsUOrq5tORXy04AF+vgB5fOUJLtDb6zW7yc1\nq7vV4awTf0kXU1WMu3S4hmHLVDNUi3vL3SZJ5ULUNELtv9TzS7Xo4Tt9EpuNVpc99p7RG6s1\np8eVe5pVLazG4ao7Rf1qqEVpS8PB6VHs4Op8PDS7u7rMVJVJalVG3h5afVAHz+rLrip13SYO\nBthyTKsO6mSSSgerQwUVuvbcHYdDM3fo5RXaFy9J+b31fH0NbyBfflWYKyVdMXs0v+flVpfB\nzaZh96nV57qYxn/93LZoj8oXuNLqMlQvojZlNX8XxQ63wf+vgGqE6vdB+niz1sfq5AU9WFlP\n1DLwbOXkdD21SJ9uUaWCKuSnTzZr6DK900qP1LhyzOur9dY6vdJED1aWr6fWHNTw5Vp1UMv6\nXPNXHyaJv6SU9BvvRZdm1+kLd3SmHbLRsfPX7MGZqUR+HT2X62mQ11DsAEny8dCgOhpk9Lby\nw5dp2Z9a++jlC0rS7Jq0UQMWqGR+NY2QpEMJGr1a33S/ssVD9yqqX0KRkzRzux6OtCw5clSw\nj7zctT9elQpeM74/Xh5uKmDcKxznF+p/zU0vMu2PN/NtBGQvNigGXMK5FH34iya2uXKZsIeb\nhtTTQ1X19o+XR5b+qaIBWTfuKhGoThW1aE+upkVu8nJX23Ia/6PSr7qTnt2hcevVsgzvw1qg\nXTnti9e8a+/JtuWYlv5pwu6AyGkUO8AlbDuu1HS1ue4637bltOnI5Y9PXVDYja6WCAvUybx8\neyjc1riW2nZcDT7WnJ3adUpzd6nRVG08ordbWZ3MJZUN0b8aq+csDV+uFfu15pBGr9H9n6l7\nFU6ww+3xWgxwCel22Ww3OE/Ow032v9ZpwgL0Z7zSHVkP23NaYZxlZbQywdrypF78To99e2Uf\nu5kPcnadZV5poupF9MoP+u9PSrerdLDeaqHHalodC3kBxQ5wCVUKy82mVQfVLOKa8ZUHVD30\n8sdtyumpRfpwk5666lzDrcc1/w/N6ZF7UWGJsABN7yzd/Z0nkEM6VVSnikpJl90hH/5W444x\nWQCXUMBXfavryYVa+PCVLWe//E1TfrlS2grl039b68mF+vGwelSRn5e+26f//aRuldWOvZpd\nBq3OqXjd6L44wC1Q7FxdSrqW79Pu0wr0Vr0wVS1sdSDkmAlt1HuOqr+vFmVU2E87Tmjbcb3V\nQu2v2i7r8X+oamGNWqm+c3UxTZUK6oP26sX1sACQR1DsXNqaQ3psvg4nqmyIEpMVm6g+1fRe\nO/l5Wp0MOcDPU3N76IcDWrJXhxPVqaJmdlN4/qyHRRXX8j5W5AMA/G0UO9e1/6zafqHe1fRm\nc+X3lqSfDqvPXD02X189aHU45JjoUoouZXUIAEDOYLsT1/Xfn1S5kCa1vdzqJEUV1/TOmrlD\ne85YmgzAHYg7p23HdT7F6hwAnAkrdq5rQ5weqCDbtRtbRBVXqL82xKlciEWxANzOiv16cuGV\nF2C9IvV2KxX2szQTAOfAip3rSk2X942ut/J2V5o919MAuDNf/qaW09W6rH4fpOPD9F1f7Tql\nulN0gk2kAVDsXFnVwlp7KOvgoQQdSlCVQlYEAnA7aXYNXabRzTShjSoVVGE/NYvQ2kcV6K3x\nP97+ywEYj2LnugbW0cLd+njzlZH4S+o/X/WKq1ZR62IBuLlfjur4eT1Z+5pBHw89WlMx3M8X\nAOfYubJ6YXqvnYYs1tTNqhumxGQt2K2i/pr/UNYT7wA4iVMXlM/zygVPmYoG6NQFKwIBcDKs\n2Lm0J2pp5yA1jdCf8Uqz660W+uWJG2xsBsBJlMyvpFTFncs6vvu0SvJ/LgBW7FAyv16/3+oQ\nAO5M1UKqXEijVuiTjlcGYxP17ga92NC6WFc5nqTXftCqgzqZpNLB6ldD/6wld94EAHILxQ4A\n8gybTVM6qM0XOpig/jVUIJ9+O66x61SpoAbVsTqctOWYmn6mUkF6opYK+WnHCb38vb7ZocW9\nb3wNPnLHyQta8If2xauwnxqHq0ao1YGQkyh2AJCX3FdCO57S8OUavlynL6h0sF5ooGejnOJu\n8Y/OV8sy+rKr3P5aohtYR7U+1P9+0gsNLE3mwqZu0fNLlc9T5QvoRJKeW6r+NTSpnVNMGOQE\nih0A5DHFAzWjq9UhrrPrlDYf08xuV1qdpLAADaqrr7ZT7KyxYr/+uUDjW2pQ3ctviP94WN2/\n0bBlmtDG6nDIGVw8AQDIBocS5OV+g5vWVC6kQwlWBIL0n/V6OFJD6l05zbF+cU1oow9/UUKy\npcmQYyh2AIBsEOyrlHSduZh1/ESSgn2tCATplyNqWy7rYNtySk3X9hNWBELOo9gBALJBzVAV\n8dOUX68ZTLVr6ma1KmNRJpfn0DXvjGdws8lmk91hRSDkPIodACAbeLjp7Vb61wr9a4WOnlea\nXVuOqfXnOpyokY2sDueqqhfRyv1ZB384IDcbt440FhdPAACyx8ORyu+j55Zo9JrLI10qaf1j\nKhZgaSwX9myUusxU/RLqHXn5lkI7TmrgQvWtrhDeHzcUxQ5ALklKlY8He9Uarl05tSunP+MV\nl6jIIgr2sTqQa2tfXmNb6IkFenOt6hTToQStPqgHKnBJrMkodgBy1qU0jVuv9zfpyDl5u6tu\nmMa2UP3iVsdCTioTrDLBVoeAJOm5KHWppBm/afsJ1Q3Tv5soupTVmZCTKHYAclBKupp+pthE\njWykfxRVYrJm/KZGn2h6Fz1U1epwgGsIz+8sd5xDLqDYAchBH/6iPWe0/SkV8bs80qqMKhbU\n4Bh1rKB8npaGAwDjcFUsgBw0f5f6Vb/S6jIMqacLqVp90KJMAGAuih2AHHTsvCKuO9cqn6eK\n+Ol4khWBAMBoFDsAOSjUXwfOZh28lKYTSVmX8QAAfx/FDkAO6lhR07dmXZybuEG+nmocblEm\nADAXxQ5ADnqilkoHq+4Ufb5Nu05pQ5yeWqSXvtO7bblyAgCyH1fFAshBXu76vp/GrdfQZTqR\nJA831QvTmkfZxw4AcgTFDkDO8vXQqMYa1VhHzyvIR7781gGAHMOvWAC5pKi/1QkAwHScYwcA\nAGAIih0AAIAheCsWAIC8yuHQn/HacVIlAlW1sLzcrQ4Eq1HsAADIk7Yd1+AYrTmkAC+dT1Hx\nQI1vpW6VrY4FS1HsAADIe34/qQafqE1ZHXpOJQJ1IVUTflav2bqQqn7VrQ4H61DsgDzA7tDi\nvdp6TOkOVSmkByrIg/NjAdc2Zq2iimvmg7LZJCmfp15sKA83jViu3tXkbrM6HyzCHwfA2e09\no/ofq9vXmv+HFu9Rv3mq8YG2HLM6FgBLfb9P/apfbnWZ+tfU8SRtP2FRJjgBVuwAp5aSrg4z\nVCpIe4eoWIAknb6owTFq+4V2DlZ+b6vzAbDIuRQF+WQdDPKRTUpMtiIQnAMrdoBTW7hbhxP1\nZdfLrU5SAV9N7SibTV9sszQZAEtFBGnr8ayDW49JUpng3I8DZ0GxA5zapiOqX1zB174u9/FQ\n0wj9ctSiTACcQJ/qmvCz9p+9MpKcrhe/U3SpK68D4YJ4KxZwaumOG18n4eGmdHuupwHgNJ6p\npxX7FTlJ/WuqUkGdSNK0rUq164dHrE4GS7FiBzi16kW0IU5JqdcMptm15qCqh1qUCYAT8HJX\nzMN6v732nNb/ftb3+9W7mnYO4n1YV8eKHeDUOlfSyyvUf54+7qgAL0m6lKZnl+jsJfVlqyrA\ntdls6lNNfapZnQPOhGIHY+04qdm/a/dplQ5Wx4qqVdTqQPfE10PfPqTu36jCRDUpJXeb1sXK\n4dD8h1TA1+pwAAAnw1uxMJDdoeHLVfMD/XBAPh766bCiPtLARUp3WJ3snkQW1raBerO5gnzk\n66mRjbRzsBqUsDoWAMD5sGIHA034WR9u0uLeahZxeWRDnNp9qaL++ncTS5PdK0839a3Oe68A\ngNtgxQ4Gem+j/tX4SquTVDdMY5tr4oa8umgHAMCdYMUOpklK1d4zahqRdfz+CJ26oLhElcxv\nRazs5nBo2jYt3K1DCSoRqPbl1be63Lg7JAC4NlbsYJqMbpN23R5vGSNmVJ/zKYr+TINjFOyj\njhVUIJ+GLFb0pzqXYnUyAIClWLGDafJ5qlJBLdqjqOLXjC/arVB/QzZkH7VShxP1x+Ar/5xX\no9V4qkZ+r4ltLE0GALAUK3Yw0AsNNH69vtoux19n1C3ao1d/0LD7TFixS3fosy16pck1JbWo\nv16N1vStN1iqBAC4DlbsYKBHaujoeT06Xy99r4ggHUrQoQQNvU/PR1mdLDucuqD4S6pdLOt4\nnWJKSNaJJENWJZ1ZUqr8PG91QHK6dp9WiUAF+dzqMADIdhQ7mOmlhnqoqpb9qYMJ6lZFzSJU\nvoDVmbJJRqVISM46njHi55XbeVxHYrLeWK0Z23U4UYX91LGC/q+pivhdc8zR83rxO834Tal2\nSapfXP9trbphluQF4IoodjBWqSD9s5bVIXKAv5dqFdXM7ap/7UmEX21XjVDl97Yolunizqnh\nJ/L10NjmKhui2ESNW6+qk7T2UVX46zXDsfOqO0UlAvVdX1UqpOPnNeFnNfxECx5WqzKWpgfg\nMih2QN4zupnaf6n8PhrZSN7uSk7X2LWa8LPm97Q6mbleWakQX619VL4eklQ3TJ0rqsMMPR2j\nZX0uH/P6KoX664dH5OUuSYXyaXIH5ffRoEXa87Rsef/8TgDOj4sngLynVRnN7q5pWxU4RqX+\nq8Ax+mSzvummtuWsTmauOTs1osHlVpfBzaZ/N9H3+xV/6fLIoj36Z63LrS7TkHr6M167Tude\nVACujBU7IE96oIJaltGmI9p7RmVDVLuYfPi/OcdcSFX8JUUEZx2PCJLdoWPnFewjSacuKOy6\nK1eKBcgmnbqQGzkBgD8FQF7l46GGJdWwpNU5XICvh/w8FZugOtdejBybKJtUKN/lT4sFaM+Z\nrF+757QcukHhA4CcwFuxAHAbNpvaltO7191r+H8/qW6YCv5V7B6srAk/6+yla475v9WqGarS\n1632AUBOYMUOAG5vTHPVm6Jmn2lEQ5UN0eFETfxZi/dqZb8rx7zUUDF7FPm+htZXxYI6nqQp\nv2jr8WuOAYAcRbEDgNsrE6yN/9SwZeo4Q6l2udsUXUobBiiy8JVjAr310+N6a50mbdT+syri\np+hSmvGgSgRalxuAi6HYAcAdiQjS7O5KtevIOYX6y9v9Bsf4euiVJnqlSa6HAwBJFDsgb7mQ\nqrm79McpBXgrqrgaceVErvN0U3h+q0MAwE1Q7IA8Y/VBPTJPCcmqWljnkjXye7Uuq886KcTX\n6mQAAOdAsQPyhj1n1PpzDa6r1+6/vE3ulmPqNUe95yiml9XhAADOwUmL3aVLl44dO3b1iL+/\nf8GCBa3KA1juvQ2qWVRvtbgyUiNUXz2oau9rx0lVKWRdMgCA03DSfexiYmIirvXiiy9aHQqw\n0qYjalM262BkYZUI1C9HrAgEAHA+Trpit2/fvmLFir333nuZI+Hh4RbmASyXZpfnjS7D9HRX\nmj3X0wAAnJLzFrtKlSp16tTJ6iCAs6gRqpX7NaLBNYP7z+rAWdUItSgTAMDJOOlbsfv27Std\nurSktLQ0q7MATuHJ2lq+T2PXyf7XXa2Onlev2WpUUjUpdgAASc5c7Hbv3l2hQgUvL6/SpUuP\nGzcuPT3d6lCAlWqEanpnjVmjau+r/3w9+LUqvSu7QzMelM1mdTgAgHNwxrdi09PTDxw4cPr0\n6ddeey0iImLRokXDhw+/ePHiqFGjbvFVu3fv3rp16w0f2rp1q93OWUjI8x6OVHQpfbxZf5xS\nIT9NaKPe1eRGqwMAi9jt9jVr1pw7d+6Gj1avXr18+fK5HMnmcDhuf1QOs9vtmcXLZrOlpaXN\nnTu3Tp06ZcqUyRh87LHHvvrqq8TERHf3G509LkkaMmTI559/fsOHUlNTk5KS6HYAACAbubu7\n58uXz9PT84aP9u7de8KECbkcySmK3XfffdeixeXtuYYOHTpu3LgsB8ydO7dLly67d+8uV67c\nPTz/0qVLO3bseOnSpb8bFAAA4C++vr5z585t3bq11UGucIq3YuvVq7d58+aMjwsVKhQbG7tj\nx46WLVu6uV0+BTDjg8CU9EF0AAAWRUlEQVTAQMsiAgAAOD2nKHYBAQE1atTI/HTr1q1t2rRZ\nsGBB+/btM0YWLFgQHh5euHBhiwICAADkAU5R7LKoVq1a69at+/Xr99JLL4WFhS1fvnzq1Kmz\nZs2yce0fAADAzTljsbPZbDNmzBg5cuQ777yTkJBQrVq1mJiYNm3aWJ0LAADAqTljsZMUFBQ0\nadKkSZMmWR0EAAAgz3DSDYoBAABwtyh2AAAAhqDYAQAAGIJiBwAAYAiKHQAAgCEodgAAAIag\n2AEAABiCYgcAAGAIih0AAIAhKHYAAACGoNgBAAAYgmIHAABgCIodAACAISh2AAAAhqDYAQAA\nGIJiBwAAYAiKHQAAgCEodgAAAIag2AEAABiCYgcAAGAIih0AAIAhKHYAAACGoNgBAAAYgmIH\nAABgCIodAACAISh2AAAAhqDYAQAAGIJiBwAAYAiKHQAAgCEodgAAAIag2AEAABiCYgcAAGAI\nih0AAIAhKHYAAACGoNgBAAAYgmIHAABgCIodAACAISh2AAAAhqDYAQAAGIJiBwAAYAiKHQAA\ngCE8rA4AAMC9S7PrtxPaH6+iAYosLH8vqwMBlqLYAQDyqtUH9dQi7TipQG+dS1YhP73ZXP1r\nWB0LsA7FDgCQJ20+plafq191Le+rov46n6IPf9HAhbI79FhNq8MBFqHYAQDypFd/UOuy+qD9\n5U/9vTS0vtLtevl7PVJD7jZLwwEW4eIJAECetOqAekVmHexVTceT9McpKwIBToBiBwDIky6k\nKsgn62DGSFJq7scBnALFDgCQJ5UN0a9Hsw5uPip3m0oHWxEIcAIUOwBAntS/psat1x+nr4wk\nJGvoMj1QQQV8rYsFWIqLJwAAedKzUfoxVjU/0IBaqlhQR8/p480K8dWkdlYnA6xDsQMA5Eme\nbprTQ/N2afo2LftTJfPrxYZ6srY8eS8KLoxiBwDIwzpVVKeKVocAnAavawAAAAxBsQMAADAE\nxQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGxAwAAMATFDgAA\nwBAUOwAAAENQ7AAAAAxBsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7\nAAAAQ1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAENQ7AAAAAzhYXUAAADyvGPntfu0Ar1VoaB8\n+dMK6zD7AAC4d4cS9PxSzd55+dNgH70arafrymazNBZcFcUOAIB7lJCsJp+qeKDWParaxZSY\nrK93aOT3OpGkN5paHQ4uiWIHAMA9mvCzbNKyPpfffi2YT0/VUai/es7S4LoK9bc6H1wPF08A\nAHCPvt+nhyKznlTXqaICvLXmkEWZ4NoodgAA3KPEZBXMl3XQzaZgHyUmWxEILo9iBwDAPSod\nrN+OZx1MTFZsoiKCrAgEl0exAwDgHvWprhnb9XPclRG7Qy8sV7EANQq3LhZcGBdPAABwjzpW\n0CM11HiqnqytumFKTNbn27TjhBb1kicrJ7ACxQ4AgHv3fjt1qqgJP2v27wr2VXQpzemhIn5W\nx4KrotgBAPC3tCqjVmWsDgFI4hw7AAAAY1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAENQ7AAA\nAAxBsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGx\nAwAAMATFDgAAwBAUOwAAAENQ7AAAAAxBsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAw\nBMUOAADAEBQ7AAAAQ1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAEN4WB0AAADkSYv26Lt9On5e\nEcF6OFJVClkdCKzYAQCAu5WUqi4z1WWm9pyWr6dW7tc/PtSYtVbHAit2AADgbj2zWFuOafMT\nqvzXKt2cneo9RxFB6lnV0mQujxU7AABwFxKTNX2b3m17pdVJ6lJJA+to0kbrYkESxQ4AANyV\nnaeUkq77I7KOR5fS1uNWBMJVKHYAAOAuuNskKc2edTzNLjdb7sfBNSh2AADgLlQpLF8PLfgj\n63jMHtUuZkUgXIViBwAA7oKvhwbV1bNLtObQ5ZE0u8at16dbNLS+pcnAVbEAAOBuvdlcDoea\nfqZyISrir92ndT5Fk9qpdVmrk7k8ih0AALg77jaNa6l+NfTDAR0/r97V1L68ivhZHQsUOwAA\ncG8iCyuysNUhcC3OsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7AAAA\nQ1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAENQ7AAAAAxBsQMAADAExQ4AAMAQFDsAAABDUOwA\nAAAMQbEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAENQ7AAAAAxB\nsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGxAwAA\nMATFDgAAwBAUOwAAAEN4WB0gN3h4eCQnJ9tsNquDAAAAo3h6elod4Ro2h8NhdYYcl56evmbN\nmrS0tL//VNOmTdu2bdu4ceP+/lPh1hITE7t27Tp58uSIiAirs5hvzJgxvr6+zz77rNVBzPf7\n778/88wzMTExzvbHwEiDBg2Kjo7u1q2b1UHMt2zZsmnTpn3++edWB8ltHh4ejRo1cnd3tzrI\nFS6xYufu7h4dHZ0tT7V27drY2NjmzZtny7PhFk6fPi0pKioqMjLS6izmmzp1qr+/PxM7F/j5\n+Ulq2rSpt7e31VnMFxgYWK5cOSZ2LoiLi/Px8eFH7Qw4xw4AAMAQFDsAAABDUOwAAAAMQbED\nAAAwBMUOAADAEBQ7AAAAQ1DsAAAADOH+6quvWp0hL0lNTS1QoEBUVJTVQczn6el5+PDhbt26\n+fr6Wp3FfElJSeXLl69SpYrVQczn6emZkJDQqVMn7oWTC+Lj4+vXrx8eHm51EPPZbDZ3d/dm\nzZpZHQSucecJAAAAV8BbsQAAAIag2AEAABiCYgcAAGAIih0AAIAhKHYAAACGoNgBAAAYgmIH\nAABgCA+rA+Qxly5dOnbs2NUj/v7+BQsWtCoP8Hcwn+EKmOdwKazY3Z2YmJiIa7344otWhzLQ\nrFmzoqKigoKCmjVrtmnTJqvjGIv5nDuGDx8+bNiwLINM8hxy/U+beZ690tPT33777cqVK/v5\n+UVGRr777rvp6emZjzKxLceK3d3Zt29fsWLF3nvvvcwRblaT7RYtWtSjR4+ePXs+/vjj06ZN\na968+aZNm8qWLWt1LgMxn3PB3r17P/nkk/79+189yCTPITf8aTPPs9d//vOfkSNHPv3001FR\nUWvWrBkyZMiZM2f+/e9/i4ntJBy4GwMHDmzWrJnVKQx3//33N23a1G63OxyOxMTEokWLjhgx\nwupQZmI+56hVq1Y1bNjQw8ND0tChQ69+iEme7W7x02aeZyO73R4cHDxgwIDMkaefftrX1zc1\nNdXBxHYOvBV7d/bt21e6dGlJaWlpVmcx0+nTp1euXNmzZ8+MW6QHBAR06NBh9uzZVucyE/M5\nR4WEhHTs2HHMmDEhISFXjzPJc8LNftpinmerI0eOxMfHt2vXLnOkcePGFy9ejI2NZWI7CYrd\n3dm3b9/u3bsrVKjg5eVVunTpcePGXX1uAf6+uLg4SVWqVMkcqVy5cmxsrMPhsC6UsZjPOapq\n1arDhg0bNmxYcHDw1eNM8pxws5+2mOfZqkCBAjt37mzZsmXmyLp167y8vIoUKcLEdhKcY3cX\n0tPTDxw4cPr06ddeey0iImLRokXDhw+/ePHiqFGjrI5mjuPHj0u6+ldzSEhIcnLyuXPnAgMD\nrctlIOazVZjkuYl5nr18fHwqVqyY+emnn346ceLEwYMH58uXj4ntJCh2t2K32+12e8bHNpst\nLS1t2rRpderUKVOmjKR27dolJye/+eabI0eOdHd3tzSpaTJW8jNkvNpLTU21Lo6ZmM/WYpLn\nDuZ5DomLi3v22WdnzZr18MMPv/XWW5njTGzL8VbsraxYscLzLyNGjPD29u7Zs2fGb4cM7du3\nv3Dhwr59+ywMaZjChQtLio+Pzxw5e/asl5fX9efN4G9iPluFSZ6bmOc54Ztvvqlateqvv/46\nZ86cL774wsvLS0xsp0Gxu5V69ept/stzzz0XGxu7ZMmSzDU8SW5ubpJYZM5GxYsXl/THH39k\njuzevbt48eJXvwpEtmA+W4VJnpuY59lu1qxZ3bt379Kly44dOzp37pw5zsR2EhS7WwkICKjx\nl7CwsDNnzrRp0yYmJibzgAULFoSHh2e8TEG2KFCgQHR0dOaFVMnJyYsWLeratau1qYzEfLYK\nkzw3Mc+zV0pKyqBBgx577LGPPvrIx8fn6oeY2E6Cc+zuQrVq1Vq3bt2vX7+XXnopLCxs+fLl\nU6dOnTVrFi9HstewYcM6dOgwdOjQpk2bfvTRR/Hx8U888YTVoQzEfLYQkzzXMM+z19q1a0+c\nOOHl5TV+/PirxwcOHOjn58fEdgpWbqKXB8XHxw8cOLBYsWJ+fn7169ePiYmxOpGZZs6cWbt2\n7cDAwPvvv3/Tpk1WxzEW8zl3lClTJsuWuQ4meY65/qfNPM9GkydPvmGXOHr0aMYBTGzL2Rxs\nMAMAAGAEzrEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGxAwAAMATFDgAAwBAUOwAAAENQ7AAA\nAAxBsQMAADAExQ4AAMAQFDsAAABDUOwAAAAMQbEDAAAwBMUOAADAEBQ7AAAAQ1DsAAAADEGx\nAwAAMATFDgAAwBAUOwC5Z9OmTbabGzx4sKTatWvbbLYlS5bkaJKGDRuGhobm0JP37t3bZrOl\npaXl0PMDwM14WB0AgMsJCwuLioq6frxGjRpZRhYuXNihQ4fp06f37t37ZiMAgEwUOwC5rWHD\nhl999dXNHv32229TUlKKFCmSm5EAwAwUOwDOpVixYlZHAIC8inPsADiXJ5980maznT17tnXr\n1h06dJDUp08fm8126tSp60cyviQ1NfWNN96Iiory9/cvXbr0888/f+LEiauf8/fff+/cuXNY\nWFjx4sV79Oixbdu2WwTo27evzWZbu3bt1YOzZ8+22WwjRozI+HTLli3dunUrUaKEt7d38eLF\nu3Tp8uuvv97w2dq3b+/v73/1SFpams1mu/qt5Fvnt9vtn376ab169YKCggoUKNCkSZOlS5fe\n7qcIwEVR7AA4qaFDhz7zzDOSBgwYMHXqVH9//+tHJCUnJ0dHR48aNSohIaFz585BQUHvvPNO\ngwYNjh49mvE8q1atqlOnzrx588LDw++77741a9Y0atQoNjb2Zt+3W7dukubNm3f14Ndffy2p\nT58+kvbu3RsdHT137tzIyMg+ffqUL19+3rx5TZs2PXz48D38M2+bf/To0f3794+Li3vggQea\nNWu2adOmtm3brl69+h6+FwDzOQAgt2zcuFFSWFhY1+tMnDgx45gnnnhCUnx8vMPhWLBggaTp\n06dnPsP1I+PGjZM0cODAtLQ0h8Nht9vHjBkjqW/fvg6HIz09vXr16pJmzpyZcXxCQkKTJk0k\nFSlS5IYhL126FBgYWKZMGbvdnjGSlJSUL1++mjVrZnw6atQoSbNmzcr8kvHjx0v67LPPMj7t\n1auXpNTUVIfD0a5dOz8/v6ufPzU1VVKvXr3uJL/dbi9QoEB4ePi5c+cyjl+1apWkRx555O5+\n9ABcA+fYAchtcXFxs2fPzjKY5f3KO/fOO+8UKVJk/Pjx7u7ukmw22wsvvDBz5syvv/56ypQp\nmzdv3rp1a+fOnbt3755xfGBg4IQJEzLa3g15e3t37Nhx+vTp27dvj4yMlLR48eILFy5kLNdJ\natKkScmSJTt27Jj5JbVr15Z05syZbM8vKT4+vkSJEvny5cs4vmHDhj/++GNgYOA9fC8AxqPY\nAchtPXr0uMVVsXfl3LlzcXFxbdu2TUhISEhIyByvUaPGli1b9uzZs2fPHkmtW7e++quqVasW\nGhrqcDhu9rTdu3efPn36vHnzMordN9984+7u/tBDD2U82qxZs4wPLl68uH379vXr10+bNi2H\n8lepUqVdu3YLFiyoVq3a448/3qJFi0qVKt1wsxgAEMUOQJ526NAhSTExMUWLFr3+0YSEhGPH\njkm6/tFixYrFxcXd7GlbtGgRGBg4b968UaNGXbhwYeHChS1btszc0DghIeH1119funTprl27\nHA5H1apVw8LC7jzz1YXytvklffnll6NHj/7000+fe+45SaGhoT169Bg1alSBAgXu/JsCcBEU\nOwB5WEYfatmyZUbpyaJChQoZF0lk1LurXT9yNW9v706dOk2bNu3QoUMbN25MSkrq27dv5qPd\nu3dftmzZgAEDxo4dGx0d7efn99NPPy1evPgOM588efLO80vy9/cfM2bM6NGjN2/evGrVqi++\n+OJ///vf6tWrN23a5ObGBXAArkGxA5CHhYSEhISExMfHt2rVymazZY6vW7fu1KlTISEh5cuX\nl7RkyZIBAwZkPrpz584jR47ceg/kbt26TZs2bd68eevXrw8ICHjggQcyxo8dO7Zs2bKuXbtO\nnjw58+ADBw7c4qlSUlLS09MzTqGTlHEFyR3m37dv37Rp0xo3bty0adNatWrVqlXrueeea968\n+YoVKw4ePBgREXEHPyQALoRXewCcXXJy8i1GBg4cuHHjxilTpmS+xfnrr782a9Zs0qRJNput\nRo0adevWnTNnTsZ+JZLOnz//9NNP3/abtmjRIn/+/DNmzFi4cGG3bt0yr13w9vaWdOLEicxv\nFxsb++qrr0q6ePHi9c9TsGDB1NTU77//PuPT+Pj4V1555eoDbp3fzc3ttddeGzFiREpKSsaj\nKSkpCQkJ7u7uhQoVuu2/AoDLsfKSXAAuJmOxqkePHrc45urtTlasWCEpMjLypZdeytjv4/qR\nxMTEKlWqSKpTp07//v3bt2/v6ekZHBy8ffv2jCdcu3ZtxiW39evX7969e1hYWEBAQNOmTW+2\n3UmmzLdfV65cefV48+bNJZUuXbpnz56tWrXy9PRs3769h4dHoUKFxo8f77h2u5OM/Vl8fHwe\nffTRgQMHlihRomnTpiVLlszc7uTW+e12e7t27SSVL1/+0Ucf7dOnT3h4uKQhQ4bcy38AAKZj\nxQ6A82rQoEGXLl327NkzefLkjCWr60cCAgI2btz4wgsvpKamfvXVV9u3b+/du/fGjRsz2lLG\nl2zcuLFz586HDh1auHBhpUqV1q1bV6lSpdt+94wdUkqWLNm4ceOrx2fMmPH4448nJyfHxMSk\npKRMnjz522+/HTt2rM1mu/7Uvfbt20+fPr1cuXJffvnl3LlzH3zwwQULFnh6emYecOv8Npvt\niy++eOmllzK+76JFi0JDQ6dMmfL222//nR8sAFPZHDe/4B8AAAB5CCt2AAAAhqDYAQAAGIJi\nBwAAYAiKHQAAgCEodgAAAIag2AEAABiCYgcAAGAIih0AAIAhKHYAAACGoNgBAAAYgmIHAABg\nCIodAACAISh2AAAAhqDYAQAAGIJiBwAAYAiKHQAAgCEodgAAAIag2AEAABiCYgcAAGCI/w+w\nOx34eaTuiQAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bn.fit.xyplot(fitted$S14.min_t) #pred_sensores"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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TJliuoQTu/WW6VPH1YqBhSi2AFAU06flv37ZepU1TlcQWqqfPWV6hCA+6LYAUBT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\nOkGxAwAA0AmKHQAAgE78f3jZQblJp09mAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bn.fit.histogram(fitted$S14.min_t)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Visualizando la matriz de adyacencia"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" S10.max_T_2 S11.max_T_2 S12.max_T_2 S13.max_T_2 S14.max_T_2\n",
"S10.max_T_2 0 0 1 0 0\n",
"S11.max_T_2 0 0 0 1 0\n",
"S12.max_T_2 0 0 0 1 0\n",
"S13.max_T_2 0 0 0 0 1\n",
"S14.max_T_2 0 0 0 0 0\n",
"S15.max_T_2 0 1 1 0 1\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 1\n",
"S19.max_T_2 0 1 1 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 1 1 0 0\n",
"S2.max_T_2 1 1 0 0 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 0\n",
"S7.max_T_2 0 0 0 1 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 1 1 1 1 1\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 0 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 0 0 0 0\n",
"S11.min_T_2 0 0 0 0 0\n",
"S12.min_T_2 0 0 0 0 0\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 1 0 1 0 0\n",
"S11.15hs_T_2 0 1 0 0 0\n",
"S12.15hs_T_2 0 0 1 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 1 0 1 1\n",
"S15.15hs_T_2 0 0 0 0 1\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 1 0 0 0\n",
"S18.15hs_T_2 0 0 0 0 1\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 1 0 0 0\n",
"S2.15hs_T_2 0 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 1 0 1 0\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0 1\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 1 0 1 0 0\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 1 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 1 0 0 0\n",
"S2.12hs_T_2 1 0 0 0 0\n",
"S3.12hs_T_2 1 0 0 0 0\n",
"S4.12hs_T_2 0 1 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 1 0 0 1 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 0 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S15.max_T_2 S16.max_T_2 S17.max_T_2 S18.max_T_2 S19.max_T_2\n",
"S10.max_T_2 1 0 1 0 0\n",
"S11.max_T_2 0 1 1 0 0\n",
"S12.max_T_2 0 0 0 1 0\n",
"S13.max_T_2 0 0 0 1 0\n",
"S14.max_T_2 0 0 1 0 0\n",
"S15.max_T_2 0 0 1 0 1\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 1 1 0 0\n",
"S19.max_T_2 0 1 0 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 0 1 1\n",
"S2.max_T_2 1 0 0 1 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 1 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 0\n",
"S7.max_T_2 0 1 0 0 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 1 1 0 0 1\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 1 0 0 0 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 0 0 0 0\n",
"S11.min_T_2 0 0 0 0 0\n",
"S12.min_T_2 0 0 0 0 0\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 1 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 1 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 0 1 0 1 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 1 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 1 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 1 0 0 0\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 1\n",
"S13.12hs_T_2 0 0 0 0 1\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 1 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 1 0 0 0 1\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 1 0 0 0 1\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0 0\n",
"S4.12hs_T_2 0 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 1\n",
"S6.12hs_T_2 0 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 1 0 0 0 0\n",
"S9.12hs_T_2 1 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 1 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 1 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 1\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 1\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 0 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 1\n",
"S19.media_T_1 0 0 0 0 1\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 1\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 1\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S1.max_T_2 S20.max_T_2 S2.max_T_2 S3.max_T_2 S4.max_T_2\n",
"S10.max_T_2 1 0 0 0 1\n",
"S11.max_T_2 0 0 0 1 0\n",
"S12.max_T_2 1 0 0 0 0\n",
"S13.max_T_2 1 0 0 0 0\n",
"S14.max_T_2 0 0 0 0 1\n",
"S15.max_T_2 1 0 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 1 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 0\n",
"S19.max_T_2 1 0 0 0 1\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 1 0 1\n",
"S2.max_T_2 0 0 0 1 0\n",
"S3.max_T_2 1 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 1 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 1\n",
"S7.max_T_2 0 0 0 1 0\n",
"S8.max_T_2 1 0 0 0 0\n",
"S9.max_T_2 0 0 0 0 0\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 1 0 1 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 0 0 0 0\n",
"S11.min_T_2 0 0 0 0 0\n",
"S12.min_T_2 0 0 0 0 0\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 0 0 1 0 0\n",
"S12.15hs_T_2 0 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 1 1 0 1\n",
"S2.15hs_T_2 0 0 1 1 0\n",
"S3.15hs_T_2 0 0 0 1 0\n",
"S4.15hs_T_2 0 0 0 0 1\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 1\n",
"S7.15hs_T_2 0 0 0 1 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 1 1 0 1\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 1\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 1 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0 0\n",
"S4.12hs_T_2 0 0 0 0 0\n",
"S5.12hs_T_2 0 0 1 0 1\n",
"S6.12hs_T_2 0 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 1 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 1 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 1 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 1\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 1 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 1 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S5.max_T_2 S6.max_T_2 S7.max_T_2 S8.max_T_2 S9.max_T_2\n",
"S10.max_T_2 0 0 0 1 0\n",
"S11.max_T_2 1 1 0 0 0\n",
"S12.max_T_2 0 0 1 0 0\n",
"S13.max_T_2 1 0 0 1 0\n",
"S14.max_T_2 1 0 0 0 0\n",
"S15.max_T_2 0 1 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 1 0 0 0 0\n",
"S18.max_T_2 1 0 0 0 0\n",
"S19.max_T_2 0 0 0 1 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 1 1 0\n",
"S2.max_T_2 1 1 0 0 1\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 1 0\n",
"S6.max_T_2 1 0 1 0 0\n",
"S7.max_T_2 0 0 0 0 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 0 1 1 0 0\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 1 1\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 0 0 0 0\n",
"S11.min_T_2 0 0 0 0 0\n",
"S12.min_T_2 0 0 0 0 0\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 1 1 0\n",
"S11.15hs_T_2 0 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 1 0 0 1 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 1 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 0 1 0 0\n",
"S2.15hs_T_2 0 0 1 1 1\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0 0\n",
"S5.15hs_T_2 1 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 1 0 0 1 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0 1\n",
"S10.12hs_T_2 0 0 0 1 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 1 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0 0\n",
"S4.12hs_T_2 0 0 0 1 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 1 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 0 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 1 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 1 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 1 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S10.media_T_2 S11.media_T_2 S12.media_T_2 S13.media_T_2\n",
"S10.max_T_2 1 0 1 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 1 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 1 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 1 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 1 0\n",
"S7.max_T_2 1 0 1 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 1 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 1 0 0 1\n",
"S13.media_T_2 0 1 0 0\n",
"S14.media_T_2 0 0 1 1\n",
"S15.media_T_2 1 0 0 1\n",
"S16.media_T_2 0 0 1 0\n",
"S17.media_T_2 1 0 0 0\n",
"S18.media_T_2 0 1 1 0\n",
"S19.media_T_2 0 0 1 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 1 0 1\n",
"S2.media_T_2 0 1 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 1 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 1 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 1 0 1\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 1 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 1 1\n",
"S13.15hs_T_2 1 0 0 1\n",
"S14.15hs_T_2 0 0 1 0\n",
"S15.15hs_T_2 1 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 1 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 1 0 0 1\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 1 0 0 0\n",
"S10.12hs_T_2 1 0 0 0\n",
"S11.12hs_T_2 0 1 0 0\n",
"S12.12hs_T_2 1 0 1 0\n",
"S13.12hs_T_2 0 1 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 1 0 0 0\n",
"S16.12hs_T_2 0 0 1 0\n",
"S17.12hs_T_2 0 1 0 0\n",
"S18.12hs_T_2 0 0 1 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 1 0\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 1 0 0 0\n",
"S4.12hs_T_2 0 1 0 0\n",
"S5.12hs_T_2 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 1 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 1 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 1 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 1\n",
"S4.18hs_T_2 0 1 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 1 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 1\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 1 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 1 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 1 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 1 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 1 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S14.media_T_2 S15.media_T_2 S16.media_T_2 S17.media_T_2\n",
"S10.max_T_2 1 0 0 0\n",
"S11.max_T_2 0 1 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 1 0 0\n",
"S14.max_T_2 1 1 0 0\n",
"S15.max_T_2 0 1 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 1 0 1 0\n",
"S19.max_T_2 0 0 1 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 1 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 1 1 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 0 1 0\n",
"S18.media_T_2 1 1 1 0\n",
"S19.media_T_2 0 1 0 0\n",
"S1.media_T_2 0 1 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 1 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 1\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 1 0\n",
"S15.15hs_T_2 0 1 1 0\n",
"S16.15hs_T_2 0 0 1 0\n",
"S17.15hs_T_2 0 0 1 0\n",
"S18.15hs_T_2 0 0 1 0\n",
"S19.15hs_T_2 0 1 0 0\n",
"S1.15hs_T_2 0 1 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 1 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 1\n",
"S12.12hs_T_2 0 0 0 1\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 1 1 0 0\n",
"S15.12hs_T_2 0 1 0 0\n",
"S16.12hs_T_2 0 1 1 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 1 0 0 0\n",
"S19.12hs_T_2 0 0 1 1\n",
"S1.12hs_T_2 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0\n",
"S4.12hs_T_2 1 0 1 0\n",
"S5.12hs_T_2 0 0 0 1\n",
"S6.12hs_T_2 0 0 1 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 1 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 1 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 1 0 0\n",
"S4.max_T_1 0 0 0 1\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 1 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 1\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 1\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 1 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 1 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 1 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 1 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 1 0\n",
"S20.18hs_T_1 0 0 1 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 1 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S18.media_T_2 S19.media_T_2 S1.media_T_2 S20.media_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 1\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 1 0 1\n",
"S19.max_T_2 0 1 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 1\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 1 1\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 1 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 1 1 0\n",
"S17.media_T_2 1 1 1 0\n",
"S18.media_T_2 0 1 0 1\n",
"S19.media_T_2 0 0 1 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 1 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 1 0 0\n",
"S15.15hs_T_2 0 0 0 1\n",
"S16.15hs_T_2 0 1 0 0\n",
"S17.15hs_T_2 0 0 0 1\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 1 0 1\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 1 0 0\n",
"S2.15hs_T_2 0 0 0 1\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 1\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 1 0 1 0\n",
"S11.12hs_T_2 1 0 0 0\n",
"S12.12hs_T_2 0 0 0 0\n",
"S13.12hs_T_2 0 0 1 0\n",
"S14.12hs_T_2 0 1 0 0\n",
"S15.12hs_T_2 0 1 0 0\n",
"S16.12hs_T_2 0 1 0 0\n",
"S17.12hs_T_2 1 0 1 0\n",
"S18.12hs_T_2 1 0 0 0\n",
"S19.12hs_T_2 0 1 0 0\n",
"S1.12hs_T_2 0 0 1 0\n",
"S20.12hs_T_2 1 0 0 0\n",
"S2.12hs_T_2 1 0 0 0\n",
"S3.12hs_T_2 0 0 0 0\n",
"S4.12hs_T_2 1 0 0 0\n",
"S5.12hs_T_2 1 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 1 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 1 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 1 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 1 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S2.media_T_2 S3.media_T_2 S4.media_T_2 S5.media_T_2\n",
"S10.max_T_2 0 1 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 1 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 1 0 0\n",
"S15.max_T_2 1 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 1 0 1 0\n",
"S2.max_T_2 1 0 0 0\n",
"S3.max_T_2 0 1 0 0\n",
"S4.max_T_2 0 0 1 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 1 1 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 1 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 1 1 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 1\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 1 1 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 1 0 0 0\n",
"S17.media_T_2 0 0 1 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 1\n",
"S20.media_T_2 1 1 1 0\n",
"S2.media_T_2 0 1 1 1\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 1 0 1\n",
"S7.media_T_2 0 1 1 0\n",
"S8.media_T_2 0 1 1 1\n",
"S9.media_T_2 0 1 0 1\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 1\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 1 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 1\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 1 0 1 0\n",
"S4.15hs_T_2 0 0 1 0\n",
"S5.15hs_T_2 0 0 0 1\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 1 1\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 1 0 1 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 1 0 0 0\n",
"S12.12hs_T_2 0 1 0 1\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 1 0 0 0\n",
"S15.12hs_T_2 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 1 0\n",
"S18.12hs_T_2 0 1 0 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 1 0 0\n",
"S20.12hs_T_2 1 0 0 0\n",
"S2.12hs_T_2 1 1 1 0\n",
"S3.12hs_T_2 0 1 0 0\n",
"S4.12hs_T_2 0 0 1 1\n",
"S5.12hs_T_2 0 0 0 1\n",
"S6.12hs_T_2 0 1 0 0\n",
"S7.12hs_T_2 0 0 1 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 1\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 1\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 1 0 0\n",
"S1.18hs_T_2 0 0 0 1\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 1 0\n",
"S3.18hs_T_2 0 0 0 1\n",
"S4.18hs_T_2 0 0 1 0\n",
"S5.18hs_T_2 0 0 0 1\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 1 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 1 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 1 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 1 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S6.media_T_2 S7.media_T_2 S8.media_T_2 S9.media_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 1 1\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 1 1 1 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 1 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 1 1\n",
"S17.media_T_2 1 1 1 1\n",
"S18.media_T_2 1 0 0 0\n",
"S19.media_T_2 1 0 0 0\n",
"S1.media_T_2 0 0 1 1\n",
"S20.media_T_2 0 1 0 0\n",
"S2.media_T_2 1 1 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 1\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 1 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 0 0 1 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 0 0 1 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0\n",
"S16.12hs_T_2 0 0 1 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0\n",
"S4.12hs_T_2 0 0 1 0\n",
"S5.12hs_T_2 0 0 0 0\n",
"S6.12hs_T_2 0 0 1 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 1 0\n",
"S9.12hs_T_2 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 1 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 1 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 1 0 0 0\n",
"S6.18hs_T_2 1 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 1 1 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 1 1 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 1 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 1 0 1\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S10.min_T_2 S11.min_T_2 S12.min_T_2 S13.min_T_2 S14.min_T_2\n",
"S10.max_T_2 0 0 0 0 0\n",
"S11.max_T_2 0 0 0 0 0\n",
"S12.max_T_2 0 0 0 0 0\n",
"S13.max_T_2 0 0 0 0 0\n",
"S14.max_T_2 0 0 0 0 0\n",
"S15.max_T_2 0 0 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 0\n",
"S19.max_T_2 0 0 0 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 0 0 0\n",
"S2.max_T_2 0 0 0 0 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 0\n",
"S7.max_T_2 0 0 0 0 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 0 0 0 0 0\n",
"S10.media_T_2 1 0 0 1 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 1 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 0 0\n",
"S18.media_T_2 1 0 0 0 0\n",
"S19.media_T_2 0 1 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 1 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 1 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 1 0 0 0\n",
"S11.min_T_2 0 0 1 1 1\n",
"S12.min_T_2 0 0 0 1 0\n",
"S13.min_T_2 0 0 0 0 1\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 1 1\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 1 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 1 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0 0\n",
"S12.15hs_T_2 1 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 1 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0 0\n",
"S10.12hs_T_2 1 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 1 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 1 0 0 0\n",
"S4.12hs_T_2 1 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 1 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 1 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 0 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 1 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S15.min_T_2 S16.min_T_2 S17.min_T_2 S18.min_T_2 S19.min_T_2\n",
"S10.max_T_2 0 0 0 0 0\n",
"S11.max_T_2 0 0 0 0 0\n",
"S12.max_T_2 0 0 0 0 0\n",
"S13.max_T_2 0 0 0 0 0\n",
"S14.max_T_2 0 0 0 0 0\n",
"S15.max_T_2 0 0 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 0\n",
"S19.max_T_2 0 0 0 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 0 0 0\n",
"S2.max_T_2 0 0 0 0 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 0\n",
"S7.max_T_2 0 0 0 0 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 0 0 0 0 0\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 0 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 1 0 0 0 0\n",
"S11.min_T_2 1 0 0 1 0\n",
"S12.min_T_2 0 1 0 0 1\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 1 1 0\n",
"S15.min_T_2 0 0 1 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 1 0\n",
"S18.min_T_2 0 1 0 0 1\n",
"S19.min_T_2 0 1 0 0 0\n",
"S1.min_T_2 0 0 1 1 0\n",
"S20.min_T_2 0 0 0 0 1\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 1 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 1 0 0 1\n",
"S9.min_T_2 0 1 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0 0\n",
"S4.12hs_T_2 0 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 0 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 0 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 0 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 0 0 0 0 0\n",
"S12.media_T_1 0 0 0 0 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 0 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 0 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 1 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 1 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 1\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S1.min_T_2 S20.min_T_2 S2.min_T_2 S3.min_T_2 S4.min_T_2\n",
"S10.max_T_2 0 0 0 0 0\n",
"S11.max_T_2 0 0 0 0 0\n",
"S12.max_T_2 0 0 0 0 0\n",
"S13.max_T_2 0 0 0 0 0\n",
"S14.max_T_2 0 0 0 0 0\n",
"S15.max_T_2 0 0 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 0\n",
"S19.max_T_2 0 0 0 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 0 0 0 0\n",
"S2.max_T_2 0 0 0 0 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 0\n",
"S7.max_T_2 0 0 0 0 0\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 0 0 0 0 0\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 0\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 0\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 0 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 1 0 0\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 0\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 1 0 0 0\n",
"S11.min_T_2 0 1 1 1 1\n",
"S12.min_T_2 1 0 0 0 0\n",
"S13.min_T_2 0 0 0 1 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 1\n",
"S17.min_T_2 0 0 0 0 1\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 1 0 0 1 1\n",
"S2.min_T_2 1 0 0 1 1\n",
"S3.min_T_2 0 0 0 0 1\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 1 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 1 1 0 0\n",
"S8.min_T_2 1 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 0 0 0 0\n",
"S4.12hs_T_2 0 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 1 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
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"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 0 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
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"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
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"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
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"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 1 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 1 0\n",
"Est.humedad_max_T_1 0 0 0 1 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 1\n",
"S13.min_t 0 0 0 0 1\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
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"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S5.min_T_2 S6.min_T_2 S7.min_T_2 S8.min_T_2 S9.min_T_2\n",
"S10.max_T_2 0 0 0 0 0\n",
"S11.max_T_2 0 0 0 0 0\n",
"S12.max_T_2 0 0 0 0 0\n",
"S13.max_T_2 0 0 0 0 0\n",
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"S5.media_T_2 0 0 0 0 0\n",
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"S2.15hs_T_2 1 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0 0\n",
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"S5.15hs_T_2 0 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0 0\n",
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"S7.18hs_T_2 0 0 0 0 0\n",
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"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
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"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
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"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 1\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S10.15hs_T_2 S11.15hs_T_2 S12.15hs_T_2 S13.15hs_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 1\n",
"S14.max_T_2 0 0 0 1\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 1\n",
"S1.max_T_2 0 0 0 1\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 0 0 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 1 0 1 0\n",
"S12.15hs_T_2 1 0 0 1\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 1\n",
"S15.15hs_T_2 0 0 0 1\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 1 1\n",
"S2.15hs_T_2 1 0 0 0\n",
"S3.15hs_T_2 0 0 0 1\n",
"S4.15hs_T_2 0 0 0 1\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 1 0 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 0 1 1 0\n",
"S4.12hs_T_2 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 1 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 1 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 1 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 1 0\n",
"S16.18hs_T_1 0 0 1 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 1 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 1 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S14.15hs_T_2 S15.15hs_T_2 S16.15hs_T_2 S17.15hs_T_2\n",
"S10.max_T_2 0 1 0 0\n",
"S11.max_T_2 0 1 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 1 1 0\n",
"S16.max_T_2 0 1 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 1 1 1\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 1 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 1 0 0 0\n",
"S18.media_T_2 1 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 1 1 0\n",
"S11.15hs_T_2 1 0 0 0\n",
"S12.15hs_T_2 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 1 0 1\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 1 0\n",
"S18.15hs_T_2 0 0 1 0\n",
"S19.15hs_T_2 0 1 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 1 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 1 0 1 0\n",
"S4.15hs_T_2 0 0 1 1\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 1 1 1 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 1 0 0 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 1 0 0 1\n",
"S15.12hs_T_2 0 0 0 0\n",
"S16.12hs_T_2 1 0 1 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 0 0 1 1\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 1 1\n",
"S20.12hs_T_2 1 0 0 0\n",
"S2.12hs_T_2 0 0 0 1\n",
"S3.12hs_T_2 0 0 1 0\n",
"S4.12hs_T_2 0 0 0 0\n",
"S5.12hs_T_2 1 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 1 0 0 0\n",
"S9.12hs_T_2 0 0 0 1\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 1 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 1 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 1 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S18.15hs_T_2 S19.15hs_T_2 S1.15hs_T_2 S20.15hs_T_2\n",
"S10.max_T_2 0 0 1 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 1 0\n",
"S16.max_T_2 0 1 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 1 1 1 0\n",
"S1.max_T_2 0 0 1 0\n",
"S20.max_T_2 0 1 0 0\n",
"S2.max_T_2 0 0 1 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 1 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 1 0 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 1 0 0\n",
"S11.15hs_T_2 0 0 0 1\n",
"S12.15hs_T_2 1 1 1 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 1 0 1 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 1 1 0\n",
"S17.15hs_T_2 1 0 1 0\n",
"S18.15hs_T_2 0 1 1 0\n",
"S19.15hs_T_2 0 0 1 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 1 0 0 0\n",
"S2.15hs_T_2 0 0 1 0\n",
"S3.15hs_T_2 1 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 1 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 1 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 1 0 0 0\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 1 0 0 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 1 0 0 0\n",
"S4.12hs_T_2 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 1\n",
"S15.18hs_T_1 0 0 0 1\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 1\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 1\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 1 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S2.15hs_T_2 S3.15hs_T_2 S4.15hs_T_2 S5.15hs_T_2 S6.15hs_T_2\n",
"S10.max_T_2 0 0 0 0 0\n",
"S11.max_T_2 0 0 0 0 0\n",
"S12.max_T_2 0 0 0 0 0\n",
"S13.max_T_2 0 0 0 0 0\n",
"S14.max_T_2 0 0 0 0 0\n",
"S15.max_T_2 0 0 0 0 0\n",
"S16.max_T_2 0 0 0 0 0\n",
"S17.max_T_2 0 0 0 0 0\n",
"S18.max_T_2 0 0 0 0 1\n",
"S19.max_T_2 0 0 0 0 0\n",
"S1.max_T_2 0 0 0 0 0\n",
"S20.max_T_2 0 1 0 0 1\n",
"S2.max_T_2 0 0 0 0 0\n",
"S3.max_T_2 0 0 0 0 0\n",
"S4.max_T_2 0 0 0 0 0\n",
"S5.max_T_2 0 0 0 0 0\n",
"S6.max_T_2 0 0 0 0 1\n",
"S7.max_T_2 0 0 0 0 1\n",
"S8.max_T_2 0 0 0 0 0\n",
"S9.max_T_2 0 1 0 0 0\n",
"S10.media_T_2 0 0 0 0 0\n",
"S11.media_T_2 0 0 0 0 0\n",
"S12.media_T_2 0 0 0 0 1\n",
"S13.media_T_2 0 0 0 0 0\n",
"S14.media_T_2 0 0 0 0 1\n",
"S15.media_T_2 0 0 0 0 0\n",
"S16.media_T_2 0 0 0 0 0\n",
"S17.media_T_2 0 0 0 0 0\n",
"S18.media_T_2 0 0 0 0 0\n",
"S19.media_T_2 0 0 0 0 1\n",
"S1.media_T_2 0 0 0 0 0\n",
"S20.media_T_2 0 0 0 0 0\n",
"S2.media_T_2 0 0 0 0 0\n",
"S3.media_T_2 0 0 0 0 0\n",
"S4.media_T_2 0 0 0 0 0\n",
"S5.media_T_2 0 0 0 0 0\n",
"S6.media_T_2 0 0 0 0 1\n",
"S7.media_T_2 0 0 0 0 0\n",
"S8.media_T_2 0 0 0 0 0\n",
"S9.media_T_2 0 0 0 0 0\n",
"S10.min_T_2 0 0 0 0 0\n",
"S11.min_T_2 0 0 0 0 0\n",
"S12.min_T_2 0 0 0 0 0\n",
"S13.min_T_2 0 0 0 0 0\n",
"S14.min_T_2 0 0 0 0 0\n",
"S15.min_T_2 0 0 0 0 0\n",
"S16.min_T_2 0 0 0 0 0\n",
"S17.min_T_2 0 0 0 0 0\n",
"S18.min_T_2 0 0 0 0 0\n",
"S19.min_T_2 0 0 0 0 0\n",
"S1.min_T_2 0 0 0 0 0\n",
"S20.min_T_2 0 0 0 0 0\n",
"S2.min_T_2 0 0 0 0 0\n",
"S3.min_T_2 0 0 0 0 0\n",
"S4.min_T_2 0 0 0 0 0\n",
"S5.min_T_2 0 0 0 0 0\n",
"S6.min_T_2 0 0 0 0 0\n",
"S7.min_T_2 0 0 0 0 0\n",
"S8.min_T_2 0 0 0 0 0\n",
"S9.min_T_2 0 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0 0\n",
"S11.15hs_T_2 1 1 0 0 1\n",
"S12.15hs_T_2 1 1 0 1 0\n",
"S13.15hs_T_2 0 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 1 0\n",
"S15.15hs_T_2 0 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 1 0\n",
"S18.15hs_T_2 0 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0 0\n",
"S20.15hs_T_2 1 0 1 0 0\n",
"S2.15hs_T_2 0 1 1 1 0\n",
"S3.15hs_T_2 0 0 0 1 1\n",
"S4.15hs_T_2 0 1 0 0 1\n",
"S5.15hs_T_2 0 0 0 0 1\n",
"S6.15hs_T_2 0 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0 1\n",
"S8.15hs_T_2 0 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0 0\n",
"S11.12hs_T_2 0 1 0 0 0\n",
"S12.12hs_T_2 0 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 0 0\n",
"S16.12hs_T_2 0 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0 0\n",
"S18.12hs_T_2 0 1 0 0 0\n",
"S19.12hs_T_2 0 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0 0\n",
"S20.12hs_T_2 0 0 1 0 0\n",
"S2.12hs_T_2 0 0 0 0 0\n",
"S3.12hs_T_2 0 1 0 0 0\n",
"S4.12hs_T_2 0 0 0 0 0\n",
"S5.12hs_T_2 0 0 0 0 0\n",
"S6.12hs_T_2 0 1 0 0 0\n",
"S7.12hs_T_2 0 0 0 0 0\n",
"S8.12hs_T_2 0 0 0 0 0\n",
"S9.12hs_T_2 0 0 0 0 0\n",
"S10.18hs_T_2 0 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 1 0\n",
"S1.18hs_T_2 0 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 1 0\n",
"S7.18hs_T_2 0 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 1 0\n",
"Est.temp_min_T_2 0 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0 0\n",
"S10.max_T_1 0 0 0 0 0\n",
"S11.max_T_1 0 0 0 0 0\n",
"S12.max_T_1 0 0 0 0 0\n",
"S13.max_T_1 0 0 0 0 0\n",
"S14.max_T_1 0 0 0 0 0\n",
"S15.max_T_1 0 0 0 0 0\n",
"S16.max_T_1 0 0 0 0 0\n",
"S17.max_T_1 0 0 0 0 0\n",
"S18.max_T_1 0 0 0 0 0\n",
"S19.max_T_1 0 0 1 0 0\n",
"S1.max_T_1 0 0 0 0 0\n",
"S20.max_T_1 0 0 0 0 0\n",
"S2.max_T_1 0 0 1 0 0\n",
"S3.max_T_1 0 0 0 0 0\n",
"S4.max_T_1 0 0 1 0 0\n",
"S5.max_T_1 0 0 0 0 0\n",
"S6.max_T_1 0 0 0 0 0\n",
"S7.max_T_1 0 0 0 0 0\n",
"S8.max_T_1 0 0 0 0 0\n",
"S9.max_T_1 0 0 0 0 0\n",
"S10.media_T_1 0 0 0 0 0\n",
"S11.media_T_1 1 0 0 0 0\n",
"S12.media_T_1 1 0 0 1 0\n",
"S13.media_T_1 0 0 0 0 0\n",
"S14.media_T_1 0 0 0 0 0\n",
"S15.media_T_1 0 0 0 0 0\n",
"S16.media_T_1 0 0 0 0 0\n",
"S17.media_T_1 0 0 0 0 0\n",
"S18.media_T_1 0 0 0 1 0\n",
"S19.media_T_1 0 0 0 0 0\n",
"S1.media_T_1 0 0 0 1 0\n",
"S20.media_T_1 0 0 0 0 0\n",
"S2.media_T_1 0 0 0 0 0\n",
"S3.media_T_1 0 0 0 0 0\n",
"S4.media_T_1 0 0 0 0 0\n",
"S5.media_T_1 0 0 0 1 0\n",
"S6.media_T_1 0 0 0 0 0\n",
"S7.media_T_1 0 0 0 0 0\n",
"S8.media_T_1 0 0 0 0 0\n",
"S9.media_T_1 0 0 0 0 0\n",
"S10.min_T_1 0 0 0 0 0\n",
"S11.min_T_1 0 0 0 0 0\n",
"S12.min_T_1 0 0 0 0 0\n",
"S13.min_T_1 0 0 0 0 0\n",
"S14.min_T_1 0 0 0 0 0\n",
"S15.min_T_1 0 0 0 0 0\n",
"S16.min_T_1 0 0 0 0 0\n",
"S17.min_T_1 0 0 0 0 0\n",
"S18.min_T_1 0 0 0 0 0\n",
"S19.min_T_1 0 0 0 0 0\n",
"S1.min_T_1 0 0 0 0 0\n",
"S20.min_T_1 0 0 0 0 0\n",
"S2.min_T_1 0 0 0 0 0\n",
"S3.min_T_1 0 0 0 0 0\n",
"S4.min_T_1 0 0 0 0 0\n",
"S5.min_T_1 0 0 0 0 0\n",
"S6.min_T_1 0 0 0 0 0\n",
"S7.min_T_1 0 0 0 0 0\n",
"S8.min_T_1 0 0 0 0 0\n",
"S9.min_T_1 0 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0 0\n",
"S15.18hs_T_1 0 0 1 0 0\n",
"S16.18hs_T_1 0 0 0 0 0\n",
"S17.18hs_T_1 1 0 0 0 0\n",
"S18.18hs_T_1 1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0 0\n",
"S20.18hs_T_1 1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0 0\n",
"S10.min_t 0 0 0 0 0\n",
"S11.min_t 0 0 0 0 0\n",
"S12.min_t 0 0 0 0 0\n",
"S13.min_t 0 0 0 0 0\n",
"S14.min_t 0 0 0 0 0\n",
"S15.min_t 0 0 0 0 0\n",
"S16.min_t 0 0 0 0 0\n",
"S18.min_t 0 0 0 0 0\n",
"S19.min_t 0 0 0 0 0\n",
"S1.min_t 0 0 0 0 0\n",
"S20.min_t 0 0 0 0 0\n",
"S2.min_t 0 0 0 0 0\n",
"S3.min_t 0 0 0 0 0\n",
"S4.min_t 0 0 0 0 0\n",
"S5.min_t 0 0 0 0 0\n",
"S6.min_t 0 0 0 0 0\n",
"S7.min_t 0 0 0 0 0\n",
"S8.min_t 0 0 0 0 0\n",
"S9.min_t 0 0 0 0 0\n",
" S7.15hs_T_2 S8.15hs_T_2 S9.15hs_T_2 S10.12hs_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 1 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 1 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 1 0 0\n",
"S2.max_T_2 1 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 1 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 1 0 0 0\n",
"S8.max_T_2 0 1 0 0\n",
"S9.max_T_2 0 1 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 0 0 0\n",
"S18.media_T_2 1 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 1 1 0 0\n",
"S11.15hs_T_2 0 0 1 0\n",
"S12.15hs_T_2 1 0 1 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 1 0 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 1 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 1 0 0\n",
"S20.15hs_T_2 1 0 1 0\n",
"S2.15hs_T_2 1 1 1 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 1 1 1 0\n",
"S5.15hs_T_2 0 1 0 0\n",
"S6.15hs_T_2 0 1 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 1 0 0 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 1\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 1\n",
"S18.12hs_T_2 0 0 0 1\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 1 0 0 1\n",
"S20.12hs_T_2 0 0 0 0\n",
"S2.12hs_T_2 0 0 0 1\n",
"S3.12hs_T_2 1 0 0 1\n",
"S4.12hs_T_2 0 0 0 1\n",
"S5.12hs_T_2 1 0 0 0\n",
"S6.12hs_T_2 0 0 0 0\n",
"S7.12hs_T_2 1 0 0 1\n",
"S8.12hs_T_2 0 0 0 1\n",
"S9.12hs_T_2 0 0 0 1\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 1\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 1\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S11.12hs_T_2 S12.12hs_T_2 S13.12hs_T_2 S14.12hs_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 0 0 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 1 0 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 1 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 1 0 1 0\n",
"S13.12hs_T_2 0 0 0 1\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 0 0 0 1\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 0 0 0 0\n",
"S19.12hs_T_2 1 0 0 0\n",
"S1.12hs_T_2 1 0 0 0\n",
"S20.12hs_T_2 1 1 0 0\n",
"S2.12hs_T_2 0 1 0 0\n",
"S3.12hs_T_2 0 1 1 1\n",
"S4.12hs_T_2 0 0 1 0\n",
"S5.12hs_T_2 0 0 1 1\n",
"S6.12hs_T_2 1 0 0 0\n",
"S7.12hs_T_2 1 0 0 1\n",
"S8.12hs_T_2 1 0 0 0\n",
"S9.12hs_T_2 0 1 1 1\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 0 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 0 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 0 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 0 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 0 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 1 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 1 0 0\n",
"S14.18hs_T_1 0 1 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 1\n",
"S19.18hs_T_1 0 1 0 1\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 1 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S15.12hs_T_2 S16.12hs_T_2 S17.12hs_T_2 S18.12hs_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 1 0 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 0\n",
"S12.15hs_T_2 0 0 0 0\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 0\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 0\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 1 0\n",
"S12.12hs_T_2 0 0 0 0\n",
"S13.12hs_T_2 1 0 1 0\n",
"S14.12hs_T_2 0 0 0 1\n",
"S15.12hs_T_2 0 0 0 0\n",
"S16.12hs_T_2 0 0 1 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 0 1 1 0\n",
"S19.12hs_T_2 0 0 1 0\n",
"S1.12hs_T_2 0 1 1 0\n",
"S20.12hs_T_2 1 0 1 1\n",
"S2.12hs_T_2 1 0 0 1\n",
"S3.12hs_T_2 0 0 0 1\n",
"S4.12hs_T_2 0 0 1 1\n",
"S5.12hs_T_2 0 0 0 1\n",
"S6.12hs_T_2 0 1 0 1\n",
"S7.12hs_T_2 0 0 1 0\n",
"S8.12hs_T_2 0 1 1 0\n",
"S9.12hs_T_2 1 1 0 1\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 1 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 0 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 1 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 0 0 0 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 1 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 1\n",
"S19.media_T_1 0 0 0 1\n",
"S1.media_T_1 0 0 1 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 1\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 0 0 0 0\n",
"S6.media_T_1 0 0 0 0\n",
"S7.media_T_1 0 0 0 1\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 1\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
"S15.min_T_1 0 0 0 0\n",
"S16.min_T_1 0 0 0 0\n",
"S17.min_T_1 0 0 0 0\n",
"S18.min_T_1 0 0 0 0\n",
"S19.min_T_1 0 0 0 0\n",
"S1.min_T_1 0 0 0 0\n",
"S20.min_T_1 0 0 0 0\n",
"S2.min_T_1 0 0 0 0\n",
"S3.min_T_1 0 0 0 0\n",
"S4.min_T_1 0 0 0 0\n",
"S5.min_T_1 0 0 0 0\n",
"S6.min_T_1 0 0 0 0\n",
"S7.min_T_1 0 0 0 0\n",
"S8.min_T_1 0 0 0 0\n",
"S9.min_T_1 0 0 0 0\n",
"S10.15hs_T_1 0 0 0 0\n",
"S11.15hs_T_1 1 0 0 0\n",
"S12.15hs_T_1 0 0 0 0\n",
"S13.15hs_T_1 0 0 0 0\n",
"S14.15hs_T_1 0 0 0 0\n",
"S15.15hs_T_1 1 0 0 0\n",
"S16.15hs_T_1 0 0 0 0\n",
"S17.15hs_T_1 0 0 0 0\n",
"S18.15hs_T_1 0 0 0 0\n",
"S19.15hs_T_1 0 0 0 0\n",
"S1.15hs_T_1 0 0 0 0\n",
"S20.15hs_T_1 0 0 0 0\n",
"S2.15hs_T_1 0 0 0 0\n",
"S3.15hs_T_1 0 0 0 0\n",
"S4.15hs_T_1 0 0 0 0\n",
"S5.15hs_T_1 0 0 0 0\n",
"S6.15hs_T_1 1 0 0 0\n",
"S7.15hs_T_1 0 0 0 0\n",
"S8.15hs_T_1 0 0 0 0\n",
"S9.15hs_T_1 1 0 0 0\n",
"S10.12hs_T_1 0 0 0 0\n",
"S11.12hs_T_1 0 0 0 0\n",
"S12.12hs_T_1 0 0 0 0\n",
"S13.12hs_T_1 0 0 0 0\n",
"S14.12hs_T_1 0 0 0 0\n",
"S15.12hs_T_1 0 0 0 0\n",
"S16.12hs_T_1 0 0 0 0\n",
"S17.12hs_T_1 0 0 0 0\n",
"S18.12hs_T_1 0 0 0 0\n",
"S19.12hs_T_1 0 0 0 0\n",
"S1.12hs_T_1 0 0 0 0\n",
"S20.12hs_T_1 0 0 0 0\n",
"S2.12hs_T_1 0 0 0 0\n",
"S3.12hs_T_1 0 0 0 0\n",
"S4.12hs_T_1 0 0 0 0\n",
"S5.12hs_T_1 0 0 0 0\n",
"S6.12hs_T_1 0 0 0 0\n",
"S7.12hs_T_1 0 0 0 0\n",
"S8.12hs_T_1 0 0 0 0\n",
"S9.12hs_T_1 0 0 0 0\n",
"S10.18hs_T_1 0 0 0 0\n",
"S11.18hs_T_1 0 0 0 0\n",
"S12.18hs_T_1 0 0 0 0\n",
"S13.18hs_T_1 0 0 0 0\n",
"S14.18hs_T_1 0 0 0 0\n",
"S15.18hs_T_1 0 0 0 0\n",
"S16.18hs_T_1 0 0 0 0\n",
"S17.18hs_T_1 0 0 0 0\n",
"S18.18hs_T_1 0 0 0 0\n",
"S19.18hs_T_1 0 0 0 0\n",
"S1.18hs_T_1 0 0 0 0\n",
"S20.18hs_T_1 0 0 0 0\n",
"S2.18hs_T_1 0 0 0 0\n",
"S3.18hs_T_1 0 0 0 0\n",
"S4.18hs_T_1 0 0 0 0\n",
"S5.18hs_T_1 0 0 0 0\n",
"S6.18hs_T_1 0 0 0 0\n",
"S7.18hs_T_1 0 0 0 0\n",
"S8.18hs_T_1 0 0 0 0\n",
"S9.18hs_T_1 0 0 0 0\n",
"Est.humedad_min_T_1 0 0 0 0\n",
"Est.humedad_med_T_1 0 0 0 0\n",
"Est.humedad_max_T_1 0 0 0 0\n",
"Est.temp_min_T_1 0 0 0 0\n",
"Est.temp_max_T_1 0 0 0 0\n",
"Est.temp_med_T_1 0 0 0 0\n",
"S10.min_t 0 0 0 0\n",
"S11.min_t 0 0 0 0\n",
"S12.min_t 0 0 0 0\n",
"S13.min_t 0 0 0 0\n",
"S14.min_t 0 0 0 0\n",
"S15.min_t 0 0 0 0\n",
"S16.min_t 0 0 0 0\n",
"S18.min_t 0 0 0 0\n",
"S19.min_t 0 0 0 0\n",
"S1.min_t 0 0 0 0\n",
"S20.min_t 0 0 0 0\n",
"S2.min_t 0 0 0 0\n",
"S3.min_t 0 0 0 0\n",
"S4.min_t 0 0 0 0\n",
"S5.min_t 0 0 0 0\n",
"S6.min_t 0 0 0 0\n",
"S7.min_t 0 0 0 0\n",
"S8.min_t 0 0 0 0\n",
"S9.min_t 0 0 0 0\n",
" S19.12hs_T_2 S1.12hs_T_2 S20.12hs_T_2 S2.12hs_T_2\n",
"S10.max_T_2 0 0 0 0\n",
"S11.max_T_2 0 0 0 0\n",
"S12.max_T_2 0 0 0 0\n",
"S13.max_T_2 0 0 0 0\n",
"S14.max_T_2 0 0 0 0\n",
"S15.max_T_2 0 0 0 0\n",
"S16.max_T_2 0 0 0 0\n",
"S17.max_T_2 0 0 0 0\n",
"S18.max_T_2 0 0 0 0\n",
"S19.max_T_2 0 0 0 0\n",
"S1.max_T_2 0 0 0 0\n",
"S20.max_T_2 0 0 0 0\n",
"S2.max_T_2 0 0 0 0\n",
"S3.max_T_2 0 0 0 0\n",
"S4.max_T_2 0 0 0 0\n",
"S5.max_T_2 0 0 0 0\n",
"S6.max_T_2 0 0 0 0\n",
"S7.max_T_2 0 0 0 0\n",
"S8.max_T_2 0 0 0 0\n",
"S9.max_T_2 0 0 0 0\n",
"S10.media_T_2 0 0 0 0\n",
"S11.media_T_2 0 0 0 0\n",
"S12.media_T_2 0 0 0 0\n",
"S13.media_T_2 0 0 0 0\n",
"S14.media_T_2 0 0 0 0\n",
"S15.media_T_2 0 0 0 0\n",
"S16.media_T_2 0 0 0 0\n",
"S17.media_T_2 0 0 0 0\n",
"S18.media_T_2 0 0 0 0\n",
"S19.media_T_2 0 0 0 0\n",
"S1.media_T_2 0 0 0 0\n",
"S20.media_T_2 0 0 0 0\n",
"S2.media_T_2 0 0 0 0\n",
"S3.media_T_2 0 0 0 0\n",
"S4.media_T_2 0 0 0 0\n",
"S5.media_T_2 0 0 0 0\n",
"S6.media_T_2 0 0 0 0\n",
"S7.media_T_2 0 0 0 0\n",
"S8.media_T_2 0 0 0 0\n",
"S9.media_T_2 0 0 0 0\n",
"S10.min_T_2 0 0 0 0\n",
"S11.min_T_2 0 0 0 0\n",
"S12.min_T_2 0 0 0 0\n",
"S13.min_T_2 0 0 0 0\n",
"S14.min_T_2 0 0 0 0\n",
"S15.min_T_2 0 0 0 0\n",
"S16.min_T_2 0 0 0 0\n",
"S17.min_T_2 0 0 0 0\n",
"S18.min_T_2 0 0 0 0\n",
"S19.min_T_2 0 0 0 0\n",
"S1.min_T_2 0 0 0 0\n",
"S20.min_T_2 0 0 0 0\n",
"S2.min_T_2 0 0 0 0\n",
"S3.min_T_2 0 0 0 0\n",
"S4.min_T_2 0 0 0 0\n",
"S5.min_T_2 0 0 0 0\n",
"S6.min_T_2 0 0 0 0\n",
"S7.min_T_2 0 0 0 0\n",
"S8.min_T_2 0 0 0 0\n",
"S9.min_T_2 0 0 0 0\n",
"S10.15hs_T_2 0 0 0 0\n",
"S11.15hs_T_2 0 0 0 1\n",
"S12.15hs_T_2 0 0 0 1\n",
"S13.15hs_T_2 0 0 0 0\n",
"S14.15hs_T_2 0 0 0 0\n",
"S15.15hs_T_2 0 0 0 0\n",
"S16.15hs_T_2 0 0 0 0\n",
"S17.15hs_T_2 0 0 0 0\n",
"S18.15hs_T_2 0 0 0 0\n",
"S19.15hs_T_2 0 0 0 0\n",
"S1.15hs_T_2 0 0 0 0\n",
"S20.15hs_T_2 0 0 0 0\n",
"S2.15hs_T_2 0 0 0 0\n",
"S3.15hs_T_2 0 0 0 0\n",
"S4.15hs_T_2 0 0 0 1\n",
"S5.15hs_T_2 0 0 0 0\n",
"S6.15hs_T_2 0 0 0 0\n",
"S7.15hs_T_2 0 0 0 0\n",
"S8.15hs_T_2 0 0 0 0\n",
"S9.15hs_T_2 0 0 0 1\n",
"S10.12hs_T_2 0 0 0 0\n",
"S11.12hs_T_2 0 0 0 0\n",
"S12.12hs_T_2 0 0 0 0\n",
"S13.12hs_T_2 0 0 0 0\n",
"S14.12hs_T_2 0 0 0 0\n",
"S15.12hs_T_2 1 0 0 0\n",
"S16.12hs_T_2 0 0 0 0\n",
"S17.12hs_T_2 0 0 0 0\n",
"S18.12hs_T_2 1 0 0 0\n",
"S19.12hs_T_2 0 0 0 0\n",
"S1.12hs_T_2 0 0 0 0\n",
"S20.12hs_T_2 0 1 0 1\n",
"S2.12hs_T_2 0 0 0 0\n",
"S3.12hs_T_2 1 1 0 1\n",
"S4.12hs_T_2 1 0 0 0\n",
"S5.12hs_T_2 0 1 0 0\n",
"S6.12hs_T_2 1 1 0 0\n",
"S7.12hs_T_2 0 1 0 0\n",
"S8.12hs_T_2 0 0 0 0\n",
"S9.12hs_T_2 1 1 0 0\n",
"S10.18hs_T_2 0 0 0 0\n",
"S11.18hs_T_2 0 0 0 0\n",
"S12.18hs_T_2 0 0 0 0\n",
"S13.18hs_T_2 0 0 0 0\n",
"S14.18hs_T_2 0 0 0 0\n",
"S15.18hs_T_2 0 0 0 0\n",
"S16.18hs_T_2 0 0 0 0\n",
"S17.18hs_T_2 0 0 0 0\n",
"S18.18hs_T_2 0 0 0 0\n",
"S19.18hs_T_2 0 0 0 0\n",
"S1.18hs_T_2 0 0 0 0\n",
"S20.18hs_T_2 0 0 0 0\n",
"S2.18hs_T_2 0 0 0 0\n",
"S3.18hs_T_2 0 0 0 0\n",
"S4.18hs_T_2 0 0 0 0\n",
"S5.18hs_T_2 0 0 0 0\n",
"S6.18hs_T_2 0 0 0 0\n",
"S7.18hs_T_2 0 0 0 0\n",
"S8.18hs_T_2 0 0 0 0\n",
"S9.18hs_T_2 0 0 0 0\n",
"Est.humedad_min_T_2 0 0 0 0\n",
"Est.humedad_med_T_2 0 0 0 0\n",
"Est.humedad_max_T_2 0 0 0 0\n",
"Est.temp_min_T_2 0 0 0 0\n",
"Est.temp_max_T_2 0 0 0 0\n",
"Est.temp_med_T_2 0 0 0 0\n",
"S10.max_T_1 0 0 0 0\n",
"S11.max_T_1 0 0 0 0\n",
"S12.max_T_1 0 0 0 0\n",
"S13.max_T_1 0 0 0 0\n",
"S14.max_T_1 0 0 0 0\n",
"S15.max_T_1 0 0 0 0\n",
"S16.max_T_1 0 0 0 0\n",
"S17.max_T_1 0 0 0 0\n",
"S18.max_T_1 0 0 0 0\n",
"S19.max_T_1 0 0 0 0\n",
"S1.max_T_1 0 0 0 0\n",
"S20.max_T_1 1 0 0 0\n",
"S2.max_T_1 0 0 0 0\n",
"S3.max_T_1 0 0 0 0\n",
"S4.max_T_1 0 0 0 0\n",
"S5.max_T_1 0 0 0 0\n",
"S6.max_T_1 0 0 0 0\n",
"S7.max_T_1 0 0 0 0\n",
"S8.max_T_1 0 0 0 0\n",
"S9.max_T_1 0 0 0 0\n",
"S10.media_T_1 0 0 0 0\n",
"S11.media_T_1 1 0 1 0\n",
"S12.media_T_1 0 0 0 0\n",
"S13.media_T_1 0 0 0 0\n",
"S14.media_T_1 0 0 0 0\n",
"S15.media_T_1 0 0 0 0\n",
"S16.media_T_1 0 0 0 0\n",
"S17.media_T_1 0 0 0 0\n",
"S18.media_T_1 0 0 0 0\n",
"S19.media_T_1 1 0 0 0\n",
"S1.media_T_1 0 0 0 0\n",
"S20.media_T_1 0 0 0 0\n",
"S2.media_T_1 0 0 0 0\n",
"S3.media_T_1 0 0 0 0\n",
"S4.media_T_1 0 0 0 0\n",
"S5.media_T_1 1 0 0 0\n",
"S6.media_T_1 1 0 0 0\n",
"S7.media_T_1 0 0 0 0\n",
"S8.media_T_1 0 0 0 0\n",
"S9.media_T_1 0 0 0 0\n",
"S10.min_T_1 0 0 0 0\n",
"S11.min_T_1 0 0 0 0\n",
"S12.min_T_1 0 0 0 0\n",
"S13.min_T_1 0 0 0 0\n",
"S14.min_T_1 0 0 0 0\n",
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