From 04860439450587a6a7ca6b77bedb6285cf4a9102 Mon Sep 17 00:00:00 2001
From: 0db2f0554d3b3bbdf0f34a0c1240bdef
 <0db2f0554d3b3bbdf0f34a0c1240bdef@app-learninglab.inria.fr>
Date: Tue, 16 Jun 2020 16:41:14 +0000
Subject: [PATCH] =?UTF-8?q?avec=20donn=C3=A9es=20moyenn=C3=A9es=20mensuell?=
 =?UTF-8?q?e=20et=20filtrage=20grossier=20par=20fft=20de=20la=20variation?=
 =?UTF-8?q?=20rapide?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 ...ans l'atmosph\303\250re depuis 1958.ipynb" | 1966 ++++++++++++++++-
 1 file changed, 1937 insertions(+), 29 deletions(-)

diff --git "a/module3/exo3/Concentration de CO2 dans l'atmosph\303\250re depuis 1958.ipynb" "b/module3/exo3/Concentration de CO2 dans l'atmosph\303\250re depuis 1958.ipynb"
index 7689440..d8fee86 100644
--- "a/module3/exo3/Concentration de CO2 dans l'atmosph\303\250re depuis 1958.ipynb"	
+++ "b/module3/exo3/Concentration de CO2 dans l'atmosph\303\250re depuis 1958.ipynb"	
@@ -22,6 +22,7 @@
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
     "import pandas as pd\n",
     "import isoweek\n",
     "import os\n",
@@ -491,7 +492,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Y a-t-il des points manquants dans ce jeux de données ?"
+    "Y a-t-il des lignes sans données valides dans ce jeux de données ?"
    ]
   },
   {
@@ -548,7 +549,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "À la date de création de ce document il n'y a pas de données manquante. Cependant on introduisons une procédure pour supprimer les lignes avec de telles données manquantes susceptibles d'être introduite dans la base de données par la suite."
+    "À la date de création de ce document il n'y a pas de données non valides. Cependant on introduisons une procédure pour supprimer les lignes avec de telles données manquantes susceptibles d'être introduite dans la base de données par la suite."
    ]
   },
   {
@@ -558,6 +559,13 @@
     "scrolled": false
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['date', 'CO2_concentration'], dtype='object')\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -968,6 +976,7 @@
    ],
    "source": [
     "data = raw_data.dropna().copy()\n",
+    "print (data.columns) #verification format du dataframe\n",
     "data"
    ]
   },
@@ -975,38 +984,402 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Le format de la date est conventionnelle et compris par la bibliothèque pandas. Nous pouvons utiliser les données telles quelles pour tracer un premier aperçu des données brutes."
+    "Le format de la date est conventionnelle et compris par la bibliothèque pandas.\n",
+    "En analysant rapidement les données, il est facile de constater qu'il n'y a pas toujours des relevés de la concentration par semaine. Nous pouvons néanmoins utiliser les données telles quelles pour tracer un premier aperçu des données brutes."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 13,
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tracé des données"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "sorted_data = data.set_index('date').sort_index()"
+    "Nous indexons les données de concentration de C02 avec la date"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>CO2_concentration</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1958-03-29</th>\n",
+       "      <td>316.19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-04-05</th>\n",
+       "      <td>317.31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-04-12</th>\n",
+       "      <td>317.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-04-19</th>\n",
+       "      <td>317.58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-04-26</th>\n",
+       "      <td>316.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-05-03</th>\n",
+       "      <td>316.95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-05-17</th>\n",
+       "      <td>317.56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-05-24</th>\n",
+       "      <td>317.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-07-05</th>\n",
+       "      <td>315.85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-07-12</th>\n",
+       "      <td>315.85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-07-19</th>\n",
+       "      <td>315.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-07-26</th>\n",
+       "      <td>315.59</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-08-02</th>\n",
+       "      <td>315.64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-08-09</th>\n",
+       "      <td>315.10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-08-16</th>\n",
+       "      <td>315.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-08-30</th>\n",
+       "      <td>314.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-09-06</th>\n",
+       "      <td>313.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-11-08</th>\n",
+       "      <td>313.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-11-15</th>\n",
+       "      <td>313.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-11-22</th>\n",
+       "      <td>313.57</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-11-29</th>\n",
+       "      <td>314.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-12-06</th>\n",
+       "      <td>314.56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-12-13</th>\n",
+       "      <td>314.41</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-12-20</th>\n",
+       "      <td>314.77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-12-27</th>\n",
+       "      <td>315.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01-03</th>\n",
+       "      <td>315.24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01-10</th>\n",
+       "      <td>315.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01-17</th>\n",
+       "      <td>315.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01-24</th>\n",
+       "      <td>315.86</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01-31</th>\n",
+       "      <td>315.42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-11-02</th>\n",
+       "      <td>409.86</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-11-09</th>\n",
+       "      <td>410.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-11-16</th>\n",
+       "      <td>410.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-11-23</th>\n",
+       "      <td>410.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-11-30</th>\n",
+       "      <td>410.92</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-12-07</th>\n",
+       "      <td>411.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-12-14</th>\n",
+       "      <td>411.67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-12-21</th>\n",
+       "      <td>412.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2019-12-28</th>\n",
+       "      <td>412.59</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-04</th>\n",
+       "      <td>413.19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-11</th>\n",
+       "      <td>413.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-25</th>\n",
+       "      <td>413.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-01</th>\n",
+       "      <td>413.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-08</th>\n",
+       "      <td>414.83</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-15</th>\n",
+       "      <td>413.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-22</th>\n",
+       "      <td>414.17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02-29</th>\n",
+       "      <td>413.89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-07</th>\n",
+       "      <td>414.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-14</th>\n",
+       "      <td>414.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-21</th>\n",
+       "      <td>414.62</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03-28</th>\n",
+       "      <td>415.57</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-04</th>\n",
+       "      <td>415.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-11</th>\n",
+       "      <td>416.47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-18</th>\n",
+       "      <td>416.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04-25</th>\n",
+       "      <td>415.86</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-02</th>\n",
+       "      <td>417.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-09</th>\n",
+       "      <td>416.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-16</th>\n",
+       "      <td>416.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-23</th>\n",
+       "      <td>417.49</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05-30</th>\n",
+       "      <td>417.19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3173 rows × 1 columns</p>\n",
+       "</div>"
+      ],
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25a1fc77f0>"
+       "            CO2_concentration\n",
+       "date                         \n",
+       "1958-03-29             316.19\n",
+       "1958-04-05             317.31\n",
+       "1958-04-12             317.69\n",
+       "1958-04-19             317.58\n",
+       "1958-04-26             316.48\n",
+       "1958-05-03             316.95\n",
+       "1958-05-17             317.56\n",
+       "1958-05-24             317.99\n",
+       "1958-07-05             315.85\n",
+       "1958-07-12             315.85\n",
+       "1958-07-19             315.46\n",
+       "1958-07-26             315.59\n",
+       "1958-08-02             315.64\n",
+       "1958-08-09             315.10\n",
+       "1958-08-16             315.09\n",
+       "1958-08-30             314.14\n",
+       "1958-09-06             313.54\n",
+       "1958-11-08             313.05\n",
+       "1958-11-15             313.26\n",
+       "1958-11-22             313.57\n",
+       "1958-11-29             314.01\n",
+       "1958-12-06             314.56\n",
+       "1958-12-13             314.41\n",
+       "1958-12-20             314.77\n",
+       "1958-12-27             315.21\n",
+       "1959-01-03             315.24\n",
+       "1959-01-10             315.50\n",
+       "1959-01-17             315.69\n",
+       "1959-01-24             315.86\n",
+       "1959-01-31             315.42\n",
+       "...                       ...\n",
+       "2019-11-02             409.86\n",
+       "2019-11-09             410.15\n",
+       "2019-11-16             410.22\n",
+       "2019-11-23             410.48\n",
+       "2019-11-30             410.92\n",
+       "2019-12-07             411.27\n",
+       "2019-12-14             411.67\n",
+       "2019-12-21             412.30\n",
+       "2019-12-28             412.59\n",
+       "2020-01-04             413.19\n",
+       "2020-01-11             413.39\n",
+       "2020-01-25             413.36\n",
+       "2020-02-01             413.99\n",
+       "2020-02-08             414.83\n",
+       "2020-02-15             413.81\n",
+       "2020-02-22             414.17\n",
+       "2020-02-29             413.89\n",
+       "2020-03-07             414.00\n",
+       "2020-03-14             414.30\n",
+       "2020-03-21             414.62\n",
+       "2020-03-28             415.57\n",
+       "2020-04-04             415.61\n",
+       "2020-04-11             416.47\n",
+       "2020-04-18             416.60\n",
+       "2020-04-25             415.86\n",
+       "2020-05-02             417.20\n",
+       "2020-05-09             416.99\n",
+       "2020-05-16             416.54\n",
+       "2020-05-23             417.49\n",
+       "2020-05-30             417.19\n",
+       "\n",
+       "[3173 rows x 1 columns]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
-    },
+    }
+   ],
+   "source": [
+    "sorted_data = data.set_index('date').sort_index()\n",
+    "sorted_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé de toute les données depuis fin mars 1958"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 720x576 with 1 Axes>"
       ]
      },
      "metadata": {
@@ -1016,7 +1389,9 @@
     }
    ],
    "source": [
-    "sorted_data.plot()"
+    "fig1 = data.plot(x='date',y='CO2_concentration',figsize=(10,8))\n",
+    "data_size = len(data['date'])\n",
+    "plt.grid()"
    ]
   },
   {
@@ -1028,24 +1403,910 @@
     "Étudions d'abors la tendance oscillatoire à court terme en traçant ces données sur les dernières années. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé des données sur les 110 données les plus récentes (>2*52 semaines = 2 ans si pas de trou)"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25a1e739e8>"
+       "<Figure size 720x576 with 1 Axes>"
       ]
      },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig2 = data[-110:].plot(x='date',y='CO2_concentration', figsize=(10,8))\n",
+    "plt.grid()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Ré-échantillonnage régulier des données"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pour avoir un échantillonnage régulier des données nous allons moyenner sur un mois à chaque fois.\n",
+    "Nous allons d'abord extraire les années et mois sous forme de 2 colonnes supplémentaires."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>CO2_concentration</th>\n",
+       "      <th>year</th>\n",
+       "      <th>month</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1958-03-29</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1958-04-05</td>\n",
+       "      <td>317.31</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1958-04-12</td>\n",
+       "      <td>317.69</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1958-04-19</td>\n",
+       "      <td>317.58</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1958-04-26</td>\n",
+       "      <td>316.48</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1958-05-03</td>\n",
+       "      <td>316.95</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1958-05-17</td>\n",
+       "      <td>317.56</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1958-05-24</td>\n",
+       "      <td>317.99</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1958-07-05</td>\n",
+       "      <td>315.85</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1958-07-12</td>\n",
+       "      <td>315.85</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1958-07-19</td>\n",
+       "      <td>315.46</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1958-07-26</td>\n",
+       "      <td>315.59</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1958-08-02</td>\n",
+       "      <td>315.64</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1958-08-09</td>\n",
+       "      <td>315.10</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1958-08-16</td>\n",
+       "      <td>315.09</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1958-08-30</td>\n",
+       "      <td>314.14</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1958-09-06</td>\n",
+       "      <td>313.54</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1958-11-08</td>\n",
+       "      <td>313.05</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1958-11-15</td>\n",
+       "      <td>313.26</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1958-11-22</td>\n",
+       "      <td>313.57</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1958-11-29</td>\n",
+       "      <td>314.01</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1958-12-06</td>\n",
+       "      <td>314.56</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1958-12-13</td>\n",
+       "      <td>314.41</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1958-12-20</td>\n",
+       "      <td>314.77</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1958-12-27</td>\n",
+       "      <td>315.21</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1959-01-03</td>\n",
+       "      <td>315.24</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1959-01-10</td>\n",
+       "      <td>315.50</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>1959-01-17</td>\n",
+       "      <td>315.69</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1959-01-24</td>\n",
+       "      <td>315.86</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1959-01-31</td>\n",
+       "      <td>315.42</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3143</th>\n",
+       "      <td>2019-11-02</td>\n",
+       "      <td>409.86</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3144</th>\n",
+       "      <td>2019-11-09</td>\n",
+       "      <td>410.15</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3145</th>\n",
+       "      <td>2019-11-16</td>\n",
+       "      <td>410.22</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3146</th>\n",
+       "      <td>2019-11-23</td>\n",
+       "      <td>410.48</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3147</th>\n",
+       "      <td>2019-11-30</td>\n",
+       "      <td>410.92</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3148</th>\n",
+       "      <td>2019-12-07</td>\n",
+       "      <td>411.27</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3149</th>\n",
+       "      <td>2019-12-14</td>\n",
+       "      <td>411.67</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3150</th>\n",
+       "      <td>2019-12-21</td>\n",
+       "      <td>412.30</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3151</th>\n",
+       "      <td>2019-12-28</td>\n",
+       "      <td>412.59</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3152</th>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>413.19</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3153</th>\n",
+       "      <td>2020-01-11</td>\n",
+       "      <td>413.39</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3154</th>\n",
+       "      <td>2020-01-25</td>\n",
+       "      <td>413.36</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3155</th>\n",
+       "      <td>2020-02-01</td>\n",
+       "      <td>413.99</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3156</th>\n",
+       "      <td>2020-02-08</td>\n",
+       "      <td>414.83</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3157</th>\n",
+       "      <td>2020-02-15</td>\n",
+       "      <td>413.81</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3158</th>\n",
+       "      <td>2020-02-22</td>\n",
+       "      <td>414.17</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3159</th>\n",
+       "      <td>2020-02-29</td>\n",
+       "      <td>413.89</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3160</th>\n",
+       "      <td>2020-03-07</td>\n",
+       "      <td>414.00</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3161</th>\n",
+       "      <td>2020-03-14</td>\n",
+       "      <td>414.30</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3162</th>\n",
+       "      <td>2020-03-21</td>\n",
+       "      <td>414.62</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3163</th>\n",
+       "      <td>2020-03-28</td>\n",
+       "      <td>415.57</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3164</th>\n",
+       "      <td>2020-04-04</td>\n",
+       "      <td>415.61</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3165</th>\n",
+       "      <td>2020-04-11</td>\n",
+       "      <td>416.47</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3166</th>\n",
+       "      <td>2020-04-18</td>\n",
+       "      <td>416.60</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3167</th>\n",
+       "      <td>2020-04-25</td>\n",
+       "      <td>415.86</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3168</th>\n",
+       "      <td>2020-05-02</td>\n",
+       "      <td>417.20</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3169</th>\n",
+       "      <td>2020-05-09</td>\n",
+       "      <td>416.99</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3170</th>\n",
+       "      <td>2020-05-16</td>\n",
+       "      <td>416.54</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3171</th>\n",
+       "      <td>2020-05-23</td>\n",
+       "      <td>417.49</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3172</th>\n",
+       "      <td>2020-05-30</td>\n",
+       "      <td>417.19</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3173 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            date  CO2_concentration  year  month\n",
+       "0     1958-03-29             316.19  1958      3\n",
+       "1     1958-04-05             317.31  1958      4\n",
+       "2     1958-04-12             317.69  1958      4\n",
+       "3     1958-04-19             317.58  1958      4\n",
+       "4     1958-04-26             316.48  1958      4\n",
+       "5     1958-05-03             316.95  1958      5\n",
+       "6     1958-05-17             317.56  1958      5\n",
+       "7     1958-05-24             317.99  1958      5\n",
+       "8     1958-07-05             315.85  1958      7\n",
+       "9     1958-07-12             315.85  1958      7\n",
+       "10    1958-07-19             315.46  1958      7\n",
+       "11    1958-07-26             315.59  1958      7\n",
+       "12    1958-08-02             315.64  1958      8\n",
+       "13    1958-08-09             315.10  1958      8\n",
+       "14    1958-08-16             315.09  1958      8\n",
+       "15    1958-08-30             314.14  1958      8\n",
+       "16    1958-09-06             313.54  1958      9\n",
+       "17    1958-11-08             313.05  1958     11\n",
+       "18    1958-11-15             313.26  1958     11\n",
+       "19    1958-11-22             313.57  1958     11\n",
+       "20    1958-11-29             314.01  1958     11\n",
+       "21    1958-12-06             314.56  1958     12\n",
+       "22    1958-12-13             314.41  1958     12\n",
+       "23    1958-12-20             314.77  1958     12\n",
+       "24    1958-12-27             315.21  1958     12\n",
+       "25    1959-01-03             315.24  1959      1\n",
+       "26    1959-01-10             315.50  1959      1\n",
+       "27    1959-01-17             315.69  1959      1\n",
+       "28    1959-01-24             315.86  1959      1\n",
+       "29    1959-01-31             315.42  1959      1\n",
+       "...          ...                ...   ...    ...\n",
+       "3143  2019-11-02             409.86  2019     11\n",
+       "3144  2019-11-09             410.15  2019     11\n",
+       "3145  2019-11-16             410.22  2019     11\n",
+       "3146  2019-11-23             410.48  2019     11\n",
+       "3147  2019-11-30             410.92  2019     11\n",
+       "3148  2019-12-07             411.27  2019     12\n",
+       "3149  2019-12-14             411.67  2019     12\n",
+       "3150  2019-12-21             412.30  2019     12\n",
+       "3151  2019-12-28             412.59  2019     12\n",
+       "3152  2020-01-04             413.19  2020      1\n",
+       "3153  2020-01-11             413.39  2020      1\n",
+       "3154  2020-01-25             413.36  2020      1\n",
+       "3155  2020-02-01             413.99  2020      2\n",
+       "3156  2020-02-08             414.83  2020      2\n",
+       "3157  2020-02-15             413.81  2020      2\n",
+       "3158  2020-02-22             414.17  2020      2\n",
+       "3159  2020-02-29             413.89  2020      2\n",
+       "3160  2020-03-07             414.00  2020      3\n",
+       "3161  2020-03-14             414.30  2020      3\n",
+       "3162  2020-03-21             414.62  2020      3\n",
+       "3163  2020-03-28             415.57  2020      3\n",
+       "3164  2020-04-04             415.61  2020      4\n",
+       "3165  2020-04-11             416.47  2020      4\n",
+       "3166  2020-04-18             416.60  2020      4\n",
+       "3167  2020-04-25             415.86  2020      4\n",
+       "3168  2020-05-02             417.20  2020      5\n",
+       "3169  2020-05-09             416.99  2020      5\n",
+       "3170  2020-05-16             416.54  2020      5\n",
+       "3171  2020-05-23             417.49  2020      5\n",
+       "3172  2020-05-30             417.19  2020      5\n",
+       "\n",
+       "[3173 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data['year'] = pd.DatetimeIndex(data['date']).year\n",
+    "data['month'] = pd.DatetimeIndex(data['date']).month\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons maintenant sélectionner les éléments de la base de donnée qui se référent à une année. Puis au sein de ceux-ci nous sélectionnons les mesures d'un même mois et nous en prenons la moyenne. Nous recréons ensuite un dataframe avec ces nouvelles données.\n",
+    "*NB : Cela revient à un léger filtrage pase-bas des fluctuations observées dans un mois.*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Monthly_data_list=[]\n",
+    "years=data['year'].unique()\n",
+    "for a in years:\n",
+    "    months_per_year = data['month'][(data.year == a)].unique()\n",
+    "    for b in months_per_year:\n",
+    "        date = str(a) + \"-\" + str(b)\n",
+    "        Monthly_data_per_year = [date, round(data['CO2_concentration'][(data.year == a) & (data.month == b)].mean(),2),a,b]\n",
+    "        Monthly_data_list.append(Monthly_data_per_year)\n",
+    "\n",
+    "Monthly_data=pd.DataFrame(Monthly_data_list)        \n",
+    "Monthly_data.columns = ['date','CO2_concentration_moyenne_mensuelle','year','month']\n",
+    "Monthly_data\n",
+    "database_size = len(Monthly_data['date'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé des  données moyennées par mois depuis fin mars 1958"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1440x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig3 = Monthly_data.plot(x = 'date',y = 'CO2_concentration_moyenne_mensuelle',figsize=(20,10))\n",
+    "plt.grid()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé des  données sur les deux année 2018 et 2019"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig4 = Monthly_data[(Monthly_data.year == 2018) | (Monthly_data.year == 2019)].plot(x = 'date',y = 'CO2_concentration_moyenne_mensuelle',figsize=(15,8))\n",
+    "#fig4.set_xticklabels(Monthly_data['date'][(Monthly_data.year == 2018) | (Monthly_data.year == 2019)])\n",
+    "plt.grid()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Filtrage des données pour séparer les deux phénomènes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Calcul du spectre sur toutes les données \n",
+    "\n",
+    "\n",
+    "**Attention les fréquences négatives de la FFT sont situées dans le seconde moitiée du spectre**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_pour_fft = np.array(Monthly_data['CO2_concentration_moyenne_mensuelle'])\n",
+    "data_pour_fft\n",
+    "fft_data = np.fft.fft(data_pour_fft)\n",
+    "freq_pos = np.fft.fftfreq(len(fft_data))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Creation d'un tableau avec les fréquences negatives pour affichage courbe et classement du tableau des données fft  de la même façon pour obtenir spectre classique symétrique par rapport à la fréquence nulle (concentration constante de C02) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "freq = [] \n",
+    "freq.extend(freq_pos[int(len(freq_pos)/2):len(freq_pos)-1]-freq_pos[len(freq_pos)-1])\n",
+    "freq.extend(freq_pos[0:int(len(freq_pos)/2)])\n",
+    "\n",
+    "fft_data_plot = [] \n",
+    "fft_data_plot.extend(fft_data[int(len(freq_pos)/2):len(freq_pos)-1])\n",
+    "fft_data_plot.extend(fft_data[0:int(len(freq_pos)/2)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé du spectre complet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0, 4000)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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htQQknPIKAmYWIxUAvuvuPwyKDwYpHoL7Q0F5GzAv6/RmYF9Q3pyjXCQ0BhKeWS8INERUwi+f0UEGfAvY4e5fzXppE3Bz8Phm4P6s8rVmVmFm80l1AD8VpIw6zWxl8J43ZZ0jEgrxZDLz6x80Y1jCryyPY64EbgS2mtlzQdn/BL4IbDSzjwN7gA8BuPs2M9sIbCc1suhWd08E590C3ANUAQ8FN5HQ6I8nKc9qCVSUpQa+9Wt0kITUqEHA3R8ldz4f4N3DnLMeWJ+jvAVYUkgFRc4m/fEk5WXZQSD1uG8gMdwpImc1zRgWKUB/YpggEFc6SMJJQUCkAMOmgxQEJKQUBEQKMDQdVK6WgIScgoBIAfqGDQLqE5BwUhAQKUBfPJnpB4DUhvOxqCkdJKGlICBSgP54YlCfAEB5NKJ0kISWgoBIAYaODgKoiEWVDpLQUhAQKcDQjmFIDRNVOkjCSkFAJE/xRJKknxoWmlZepnSQhJeCgEie+oP1gXK1BPoGFAQknBQERPKUTvmc1jFcFskECJGwURAQyVMmCJzWElDHsISXgoBInvqGDQLqGJbwUhAQyVNPf+rXfk354MV31TEsYaYgIJKnnv44ANXlg0cHqWNYwkxBQCRP6ZZA1WlBIKqOYQktBQGRPI2YDtKmMhJSCgIieUqng05vCahPQMIrn43mv21mh8zsxayyPzWzN8zsueB2fdZrt5lZq5ntNLNrs8qXmdnW4LXbg83mRUIj3RIY2idQrtFBEmL5tATuAVbnKP9bd18a3B4EMLNLgLXApcE5d5hZ+l/MncA6YFFwy/WeImet4YJAap6AgoCE06hBwN1/ARzN8/3WAPe5e5+77wJagRVmNgeoc/fH3d2Be4EbxlppkTPhZGZ00OA+gYpgxnAy6WeiWiLjMp4+gU+Z2QtBumhaUNYE7M06pi0oawoeDy3PyczWmVmLmbW0t7ePo4oixdPTn6AsYqdNFks/1wghCaOxBoE7gQXAUmA/8JWgPFee30coz8nd73L35e6+vKGhYYxVFCmunv7EaZ3CQGanMaWEJIzGFATc/aC7J9w9CdwNrAheagPmZR3aDOwLyptzlIuERk9//LT+AEhtKgPaZ1jCaUxBIMjxp30ASI8c2gSsNbMKM5tPqgP4KXffD3Sa2cpgVNBNwP3jqLdIyfX0J06bIwBQEawqqhFCEkan/0UPYWbfA1YBM82sDfgCsMrMlpJK6bwOfALA3beZ2UZgOxAHbnX39M+jW0iNNKoCHgpuIqExXDooXZYePSQSJqMGAXf/SI7ib41w/HpgfY7yFmBJQbUTOYsMlw6qq4oB0Nk7UOoqiYybZgyL5Olkf+K04aEAdZWpso6T8VJXSWTcFARE8tTdn8jZEqgPWgInTqolIOGjICCSp5PD9Amk00EdSgdJCCkIiORpuD6BKZl0kIKAhI+CgEiehh0iWhalMhaho1d9AhI+CgIieUgknb54Mmc6CKC2oozuPgUBCR8FAZE8DLe1ZFp1eZnmCUgoKQiI5OFkZhnp3FNrqsujdKklICGkICCSh+5h9hJIq6koy7QWRMJEQUAkD6Ong6J09ykdJOGjICCSh3Q6qGqYdFCtWgISUgoCInlIp4NqRugYVktAwkhBQCQP6a0lhxsiWlMRVUtAQklBQCadz2x8nj/43rNFfc/0RLApFbGcr9dWlNHZGy/qPsPHuvu56PMP8fTr+W7xLVI4BQGZdH7wTBubni/uxnXtnX0ANEypyPl645QK4knnWE9/0T5zy+5j9MWTfOORV4v2niJDKQiI5OFgRy91lWXDpoNm1VUGx/WVsloi46YgIJKHgx29mS/6XBrTQaCzt+ifXbwEk8jpFARE8tDe2UdjXe5UEKTSQQDtRWwJmBXtrUSGNWoQMLNvm9khM3sxq2y6mW02s1eC+2lZr91mZq1mttPMrs0qX2ZmW4PXbg82nBcJheMnB5haXT7s61OrtbGMhFM+LYF7gNVDyj4HPOzui4CHg+eY2SXAWuDS4Jw7zCydRL0TWAcsCm5D31PkrHWiZyCzg1gutRVlRCPG8ZPF6xgWKYVRg4C7/wIYOkZtDbAheLwBuCGr/D5373P3XUArsMLM5gB17v64uztwb9Y5Imc1d+fEyQGmjhAEzIz6qphaAhI6Y+0TmOXu+wGC+8agvAnYm3VcW1DWFDweWp6Tma0zsxYza2lvbx9jFUWKo7s/QTzpI7YEAKZWxTjeoyAg4VLsjuFceX4foTwnd7/L3Ze7+/KGhoaiVU5kLNK/7tN5/+HUqSUgITTWIHAwSPEQ3B8KytuAeVnHNQP7gvLmHOUiZ71j3ak8f33V8B3DANOqY0WdLJYeOpHKoIpMjLEGgU3AzcHjm4H7s8rXmlmFmc0n1QH8VJAy6jSzlcGooJuyzhE5qx3sSI39nzXCENHU65WaLCahk3td3Cxm9j1gFTDTzNqALwBfBDaa2ceBPcCHANx9m5ltBLYDceBWd08vrXgLqZFGVcBDwU3krJf+Yh9pshikJowd7uojnkhSFtUUHAmHUYOAu39kmJfePczx64H1OcpbgCUF1U7kLHCwoxez4dcNSptdV4k7tHf1Mae+qmifr2SQTCT9XBEZxcGOXmbUVBAb5dd9Ol2klJCEiYKAyChS6waN3AqAU+miAyeKs36Q5RxUJ1JcCgIiozjY0cfsUfoD4FQQOFSsReQUA6QEFARERnGwozezSuhIZtSUUxaxorUE0jRCVCaSgoDICNo7+zjS3c+86aN39EYiRtO0Kl4+2FWCmokUh4KAyAh+/nJq2ZKrFuc3c/2qxQ082tpOfzw5/g9XC0BKQEFAZAQ7D3RQURbh4tl1eR2/dN5UegeS7DnaM+7PdkUBKQEFAZERvNrezYUNtUQj+fXSLmioDc4bf0ooWYTGhMhoFARERrD3aA/n5dEfkHb+jGoA2o6dHPdnJ9UjLCWgICAygq6+OHWVI68emq22IjUJv6s3Pu7PVgiQUlAQEBlBV2+c2spRV1fJKItGqIpF6eob/5LS6dVDFQxkIikIiAwjmXS6+uOZX/f5qq0so6tv/C2BpL79pQQUBESGceO3n8SdgoNAe2cf33tqL1t2HxvX56tPQEpBQUBkGL9qPQJAdYFBIO2hrfvH9flqCUgpKAiI5JA92WusE7+Odo9vlzHtKCaloCAgksN3ntideTzWkT7/9sK+cQUCxQApBQUBkRy27DnGlIoy3vfmOXxs5XkFnfv3H7mcVRc1MJDwcfULqE9ASkFBQCSH7fs6ePvCGXz9o1cwo3b0vQSy/cZlc/nGx5YRjRjP7z0+5jqk+wSUFpKJNK4gYGavm9lWM3vOzFqCsulmttnMXgnup2Udf5uZtZrZTjO7dryVF5kIXX1xdh3uZsnc+jG/R2UsygUzqnn5YOeY30MtASmFYrQErnb3pe6+PHj+OeBhd18EPBw8x8wuAdYClwKrgTvMLFqEzxfJKMav5m1vnADg0qb8Fo0bzuJZU3jpwNiDgFoAUgoTkQ5aA2wIHm8Absgqv8/d+9x9F9AKrJiAz5dzWPawyrF+id7z2OuURyMsO3/6uOqy8sIZ7DnawyM7D43pfA0RlVIYbxBw4D/MbIuZrQvKZrn7foDgvjEobwL2Zp3bFpSJFE12CmUsMWD3kW4eevEAv3HZXOqr8l8zKJcbljZRW1HGN37+6pjOV0NASmFss2BOudLd95lZI7DZzF4a4dhca/Hm/DMPAso6gPPOK2xkhpzbsoNA0p1IgRv1plf//OCy5nHXpb46xrvf1Mgze8Y2Qkh9AlIK42oJuPu+4P4Q8C+k0jsHzWwOQHCfbgu3AfOyTm8G9g3zvne5+3J3X97QkN+OTiIw+NfzWNIp//R0qrHaNDX/5aNHMndqFXuPnqTtWOGbzKhPQEphzEHAzGrMbEr6MfBe4EVgE3BzcNjNwP3B403AWjOrMLP5wCLgqbF+vkguQ1sChdjadoJNz6d+l8yqL2xY6HBm1JQDcN3f/bLgc9UnIKUwnpbALOBRM3ue1Jf5v7v7j4AvAteY2SvANcFz3H0bsBHYDvwIuNXdE+OpvMhQgzuGCzv3R9tSa/18/n1voqKsOAPXPnB5E3PrK+nsjbO3wC0n00FMDQKZSGMOAu7+mrtfFtwudff1QfkRd3+3uy8K7o9mnbPe3Re4+0Xu/lAxLkAk21hbAv3xJA9uPcAV503ld3/9wqLVZ0ZtBRt+JzUI7l+efaOgc9USkFLQjGGZVDxrrbd8g4C78/c/fYVdh7tZ984FRa/TollTuPqiBr66+WXeOJ7/tpPqE5BSUBCQSWXQENE8z7n/uX38/U9bqa0o4+qLJ2YgwpqlqdHQ13z153TnueGMYoCUgoKATCqDgkAeK0Cf7E/wf3/xGlMqyrj/U1cWrS9gqN+8bC5//N7F9PQn+IesFUpHoiGiUgoKAjKpJAcNER39S/QLm15kx/4O/uT9l7CgoXbC6hWJGJ+4agG/Nn86X/rxTp7adXTUc9QnIKWgICCTihfQMby17QQbW9q4ZdUCPvzWeSMeWwyxaIRv3rycuVMr+T8PbCM5yre8WgJSCgoCMqkkR5ks1h9Pkkg6hzp7WfcPLUytjvF7VxW/M3g4Uypj/MG7FvHiGx38yf0vAtA7kHukdDqged69GyKFG++yESJ523W4m3d95RE2/9FVLGycmNTL4LWDTv/y/J17nmbX4e7MKJ37b71y3GsEFeqDy5p5du9xvvvkHrbt6+DFN07wpQ+9hQ9cPnipilKlg/7ywR08v/c4//SJt5XmA+WsopaAlMy/Pb8Pd7j/ucLGyxciOwjEk86uw90c6uwFYMvuozzaenjQMM3L5k2dsLoMx8z4ULA20XN7jxNPOn/14EsMJFI92VvbTtDVFy/Z6KC7fvEaT+bRRyGTk1oCUjLpL7XClnQb22cAfPb7L/Bo62EqYxG+edNb+di3nqS+KsaXP3QZD7ywj9uue9ME1mRkl583jTs+egU/2XGQqxY38On7nmPVlx7hv12zmM/88/MAvH3BDEBDRWViKQhIyWR+pdvEhYHslsCjrYcB6B1I8rFvPQnAn9+whGsumcU1l8yasDrk6/o3z+H6N8/B3bnzkVd56UBnJgAAPPbqEUAdxDKxlA6Skkl/lUUmIAakUylD8+j/77ffypqlc7lkTh13fvQKfvOyucX/8HEyMx74/Xfw4eXNXDq3jq/91lKuWzI783r2XsPp65wICY1JPSepJSAlk+6ojRSxJXC8p59VX36E4z0DfHLVAlZd1Djo9bcvmMHVQ8rORmXRCH/zwcsyz/vjSR568QAAhzv7ONTRy+/e28ILbSf4zDWL+f13Lyp6HXr640ypLG0nuZx5aglIyaTTGuMJAe7OPz29h9/d8DS9Awm+9pNXON4zAMAdj7zKfU/vyRxbGYtM2AzgibZo1qnRU68d7uavHnqJF9pSex9/ZfPLbNt3gsdePcxN336K3Ue6i7LO0Ml+Lep7LlJLQEomHqQb+kdIabg7ltVSWP/v2/mP7Qf5xseWcbxngI/c/UTmtYv/5EcAvHNxA1/64Ft4z1d/zg+fOTXy6IIZNcW+hJK5cObgIbT/8uwbrH3rPP7LlRfw/tsf5X23P5p57aovPcJl86byT+tWsuGx17nnsdf5yocv4+0LZmaOGfrfNZceBYFzkoKAlER7Z1/ml2bvQAJ3p+3YSQYSSebUV1EZi/D9LW3c8cir/PF7L2JqdYzdR3q4+5e7gMGbstyyagEzayv48we2M7uukvU3LGFWXSXvXNzAv7+wP3NcmINAffXpaZn3vWUOF8+u4y9uWMLnfriVCxtq+OSqhXz70V08v/c4V37xpxzp7gfgP9/9JD/741U8s/sYBzt7+f6WNu77ryupq4rhDq8d7qJ5WvWgORInTg5womcg52fL5KUgIEAqB/1oaztXX9Q46i9GgGQy9SXePK2KSMToHUjwxGtH2H+il/OnV7PzYCczaiv45i9fy6Qx0k4OJPj3rfv51D8+m/O9b/3HZzKPp9eU8wfvWsh3ntxD66EuvvAbl/DbV84H4NpLZzG9ppzq8tSf8YUzU1/6tRVldPXFOX9m9Zj+W5ytlsytB2DtivNYeeEMZtdXUhmL8p/4UacZAAAMoklEQVSuaOK6v/slLx3o5B0LZ3LV4gbWP7iDq7/8yKDzV/zlw4Oe11WW8fTn35N5vubrvwIgFjU+uGweCxtrWdBQw6HOPqZXl9MwpSIzr+J4Tz998SSz6irzqvuhzl72Hu1h2fnTx3r5MkEUBEKgP54kYqnOw2Lp6otTFjHcoao8yt2/fI0v/Xgnn1y1gD+6ZjFPvnaUC2ZWUxWLcqS7nx+9eICBRJKLZ9dxtLuPn7/czk92HGJ6TTlXLpzJnqM9PL/3eM7PKi+L0B8/lQI62Z9k03OpbRzfdXEjP33pEDNry1kxfzprljax7Y0T7DrSQ3dfnP92zWKWNNVz49suYM/RHi6YceqLvXna4C/5G992PrUVZRzrGeAbP3+Vi2dPKdp/rzNp8x+9kyd3HWVasFUlwAUzT7VyzIwf3PJ2jp8coGlqFe6O4/zylcMsaKilsa6CmTUVbHp+H4+2HmZufSUDSae9s49fvHz4tM8bSDjfe2rPaeUAH/2189i+v4OtbSdIuvOZ915EfVWMyliUnQc6WDRrCu9c1EBdVRnP7T1O89RqIhF4x1//DICX/nw1lbEoXX1xEkmntqKMaBGHi53sT1AZi+T1Q0ZS7GzfuGL58uXe0tIyrvcopInbF09wpKufuTk2Gu8dSNDRO0DjlFO/frJzra2HOmmsq6SuMsar7V3MrqukpqKMvniCrW0nmFIZ46LZUxhIJHlw6/7U+vUXNXKws5etbSeorShjy+5jXH1xI8/uOcbSedNYNKuWD9zxGAOJJNctmU19VYz5M2swS32Z/mTHQZY01XPhzBr++kcvccX501h+/jR2Huxk79EeDnf1D1qxsqIswsLGWrbt68iUXTCjmtePFL4R+sLGWhY11mZGsVw0awrXXDKLqvIoDbUVzJtezdTqGG+aU8crBzv54bNvcN9Te6itLGPv0ZN8ctUCPrv64oI/dzTdfXG+v6WNG1eeT2QixqOWyKvtXbx8oJPr3jyn6O/dO5Dgqi/9jOryMnYd7ubaS2dx6dx6br16Ib0DCbbt66AyFuFfn93Holm1bNl9jAe37qenP0HT1CquOH8am7cfoHeg8CGrTVOrBs3afsfCmZk5HWlrls6loixC87RqZtdV8sDW/ZRHUyux/vjFA0QixtsWzKA/niRqRsvuY0yvifGXD77E59/3Jj6y4jx+vO0As+srOXCil+6+OAsaa6kpL8ssWXLf03u5cuEMLpo1hUTSeezVIyxsrGVmbQXlZRHajvVQU15GXVWMvUd7mFZdTn117LT+lUTSOdjRm/M7I5F09h0/ybzp+bVKBxJJ+uNJaoLWbG3F2H+nm9kWd18+6nGTNQh876k93POr11k0q5YHXtjPzNpyEknnLc1T2bbvBP3xJP2JJIbRPK2K/kSSpfOm8ugrhznS3c+FDTWcN72azt44ffEEiSTsPtI9qPNsYWMtrYe6AKivinHiZGqUypSKMjqDjUOap1XRduzUH3xlLDKmfzgTwSw1G7VhSgXtnX2DXrtuyWwWNtYSjRh1lTF+7cLptLx+jL1He1gxfzoOXHtpaiz7lt1HaT3UxYeXzxv1F9gnv7uFB7ceoLaijMduexd1GpJ4xvxzy17++/dfAODe31nBOxePvKFOe2cf//JsG7+1/Dzqq2N09A5w/7NvMKO2gp/vbOfDb53H0e5+dh9Jrc3UPK2ar/+slaNBP0XatOoYx4IRXWeD6vLooH/XZlBTnvoShlR6bCCRHt58at7G3PpK9p3ozZx3/oxqKsoiRMxY2FjLSwc66emLs+9EL0ua6jhvejW/fPkwFzbW8vze41SXR5laFaMiFqWiLEJ3f5x9x3upjkW5dslsHn3lMD/+w3eOuY/mrA0CZrYa+DsgCnzT3b840vFjCQL98SRrvv4rduzvCD4T5tanfn1MqSgj6U53f4LGKRVEI0ZXbzzzpT29ppzZdZW8fLAzM5qlLGLEk87l503lzU31PLj1AIe7+nhzUz1b30jlu3990Ux+1XqYpMOqixp4S1M9Bzp62XO0h/54kg9c0cyhjl7eOHYSM6PtWA8LG2upLo8yraacy5qnsn1fB519cTpODrCgsZZk0jna3c/xnn5+5x3zeaHtBFt2H2NOfSW7j/awsKGWtSvm8eIbHfzb8/t45+IGlp0/jT1He2iaWsXjrx3hPW9qJJF0qmJRDnf1U1dVRk9/gnjCmV1/qkXzWnsXDixoqM1rJMlYfeeJ3Xz+X1/k4++Yz5+8/5IJ+QzJT388ybK/2Ex3X5znv/DeCZkjkP239IuX21l54QzKy06lNV860MHChlo6euO4OzNqKzjW3c/xkwO8cewk58+opi+eoK4qxj8+uYdYNMIHlzXT3Rfn7l/uonlaFe2dfTRPq2JBQy0DiSQtu49RU17GBTOr2Xu0h0Odfcyur2RqVTnTa2K0HuricFc/R7v7OdTZy+JZU+jqjfPW+dPZeaCTZ/cc48IgjdYfT/KjFw+w/0Qvv75oJnuP9vD6kR6m15RTUxFl79GTvH3BDObUV/Hzl9s53DX4x9T8mTVUxaJs33+q5d0UtBgOdfZSFolQU1HG8Z5+qsujxJNO70CCpMNNbzuf/7H6YmrG2Bo4K4OAmUWBl4FrgDbgaeAj7r59uHPG2hI43tNPZSzKQCKZ+eOOJ5JEI4aZcaJngLqqMsxSnZq9AwmiESMasUxH47HufipiEcqjEbr7EpmIPJBINUHTqYZ4IlnUfP1klkg6O/Z3sGhWbWjH8E8mB070MpBI5p2uONclkk7EyAS2vngi83fs7hzrGWB6TTmHOnuZWlWeCXhHuvqojEXpjyeZWh3DzOjqi1NRFiEWjTCQSFIWfDclk053ESbu5RsESt0xvAJodffXAMzsPmANMGwQGKup1alOtMrYqS+a7C/q7CZWZSw66Li07I64+upT58aGfOErAOQvGjGWNNWf6WpIILs1KKMb2omd/UPGzJgefGdk9xsCzKitAKCm4lRZdr4/+zslErGSztwudRBoAvZmPW8Dfm3oQWa2DlgXPO0ys50lqFsxzQROH3Yxuemazw265vA4P5+DSh0EciWaT8tHuftdwF0TX52JYWYt+TTDJhNd87lB1zz5lDqP0QZkb+baDOwrcR1ERCRQ6iDwNLDIzOabWTmwFthU4jqIiEigpOkgd4+b2aeAH5MaIvptd99WyjqUSGhTWeOgaz436JonmbN+spiIiEwcjW0UETmHKQiIiJzDFASKwMymm9lmM3sluJ82wrFRM3vWzB4oZR2LLZ9rNrN5ZvYzM9thZtvM7NNnoq7jZWarzWynmbWa2edyvG5mdnvw+gtmdsWZqGcx5XHNHw2u9QUze8zMLsv1PmEy2jVnHfdWM0uY2QdLWb+JoiBQHJ8DHnb3RcDDwfPhfBrYUZJaTax8rjkOfMbd3wSsBG41s1AtGBQsdfJ14DrgEuAjOa7hOmBRcFsH3FnSShZZnte8C7jK3d8C/Dkh7zzN85rTx/01qcEtk4KCQHGsATYEjzcAN+Q6yMyagfcB3yxRvSbSqNfs7vvd/ZngcSep4NdUshoWR2apE3fvB9JLnWRbA9zrKU8AU82s+Os/l86o1+zuj7n7seDpE6Tm/IRZPv+fAX4f+AFwqJSVm0gKAsUxy933Q+qLD2gc5rivAZ8Fzo61pMcn32sGwMwuAC4HnpzwmhVXrqVOhgayfI4Jk0Kv5+PAQxNao4k36jWbWRPwAeAbJazXhNPOYnkys58As3O89L/yPP/9wCF332Jmq4pZt4ky3mvOep9aUr+e/tDdO0Y7/iyTz1IneS2HEiJ5X4+ZXU0qCLxjQms08fK55q8B/8PdE5Np5zIFgTy5+3uGe83MDprZHHffH6QBcjUVrwR+08yuByqBOjP7jrt/bIKqPG5FuGbMLEYqAHzX3X84QVWdSPksdTLZlkPJ63rM7C2kUpvXufuREtVtouRzzcuB+4IAMBO43szi7v6vpanixFA6qDg2ATcHj28G7h96gLvf5u7N7n4BqeUyfno2B4A8jHrNlvrX8i1gh7t/tYR1K6Z8ljrZBNwUjBJaCZxIp8pCatRrNrPzgB8CN7r7y2egjsU26jW7+3x3vyD4N/x94JNhDwCgIFAsXwSuMbNXSG2Y80UAM5trZg+e0ZpNnHyu+UrgRuBdZvZccLv+zFR3bNw9DqSXOtkBbHT3bWb2e2b2e8FhDwKvAa3A3cAnz0hliyTPa/7fwAzgjuD/6/g2Aj/D8rzmSUnLRoiInMPUEhAROYcpCIiInMMUBEREzmEKAiIi5zAFARGRc5iCgIjIOUxBQETkHPb/AdRjJbPgIHmWAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "mod_fft_data_plot=[abs(fft_data_plot[i]) for i in range(len(fft_data_plot))]\n",
+    "plt.plot(freq,mod_fft_data_plot)\n",
+    "axes = plt.gca()\n",
+    "#axes.set_xlim() # non utilise \n",
+    "axes.set_ylim(0, 4000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tracé des fréquences positives uniquement"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0, 4000)"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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ERAbkVAiUFUZo61ZLQERkQE6FQEVRHm3dagmIiAzIqRAoL1J3kIhIspwKgYqiPFrVEhAROS7nQkDdQSIi70vnRvMPmFmTmW1JKvuame03s43B47qk9+4wsx1mtt3Mrk0qX2pmm4P37gpuNj+qygvz6OyL6cYyIiKBdFoCDwIrU5R/y92XBI8nAcxsIbAaWBRsc7eZhYP17wHWAPODR6rPzKiKIp01LCKSbNgQcPdfAkfS/LxVwCPu3uvuu4EdwHIzqwHK3X29uzvwMHDDmVb6TJUXJa4kqnEBEZGEsxkT+IKZbQq6iyqDslpgX9I6DUFZbbB8cnlKZrbGzOrNrL65ufksqniiiiAENC4gIpJwpiFwDzAPWAI0At8MylP18/spylNy9/vcfZm7L6uurj7DKg5WoZaAiMgJzigE3P2Qu8fcPQ78E7A8eKsBmJm0ah1wICivS1E+qga6g3SugIhIwhmFQNDHP+ATwMDMoceB1WZWYGZzSQwAb3D3RqDdzFYEs4JuAh47i3qfEbUEREROFBluBTP7V+BKYIqZNQBfBa40syUkunT2AJ8DcPetZrYO2AZEgdvcPRZ81K0kZhoVAU8Fj1E1qTgRAs3tvaO9axGRcWnYEHD3T6Uo/u4p1l8LrE1RXg8sPq3ajbCCSJhp5QU0HO0ey2qIiIwbOXXGMMDMymIajnaNdTVERMaFnAuBusoitQRERAI5GALFNLb2ENWlI0REci8EZlYVEYs7ja09Y10VEZExl3MhUFdZDKAuIRERcjAEppUXANDUrpaAiEjOhUB1aSGgcwVERCAHQ6C8KEJ+JKQQEBEhB0PAzKguLVAIiIiQgyEAUF1WQJNCQEQkN0NgaplaAiIikKMhUF1WQHOHQkBEJGdD4EhnH31RnTUsIrktJ0OgpiIxTXT/sfF/wtjPth7klgdfHetqiEiWyskQWDSjAoAt+1vHuCbD27jvGM9tbxrraohIlsrJEDhvWhn5kRCbGo6NdVWGFYs77olnEZGRlpMhkB8JcUFNOZsaxn9LIBpL/PGPxjV+ISIjLydDAGDxjHK2NbbhPr5/YceD+qklICKZMGwImNkDZtZkZluSyqrM7Bkzezd4rkx67w4z22Fm283s2qTypWa2OXjvruCG82Nm7pQS2nuiHOsa3zedH2gBRBUCIpIB6bQEHgRWnlR2O/Csu88Hng1eY2YLgdXAomCbu80sHGxzD7AGmB88Tv7MUTV7cgkAe4+M71tNDrQAYjGFgIiMvGFDwN1/CRw5qXgV8FCw/BBwQ1L5I+7e6+67gR3AcjOrAcrdfb0n+l8eTtpmTMyenLivwN6WzrGsxrAGQkAtARHJhDMdE5jm7o0AwfPUoLwW2Je0XkNQVhssn1yekpmtMbN6M6tvbm4+wyqe2qyqgRAY3y2BgT/+GhMQkUwY6YHhVP38forylNz9Pndf5u7LqqurR6xyyQrzwkwrLxj3IfB+S0Czg0Rk5J1pCBwKungIngfOZmoAZiatVwccCMrrUpSPqblTStjZ3DHW1TgltQREJJPONAQeB24Olm8GHksqX21mBWY2l8QA8Iagy6jdzFYEs4JuStpmzCyeUcFbjW30x8bvr+y4xgREJIPSmSL6r8B64HwzazCzW4A7gWvM7F3gmuA17r4VWAdsA54GbnP3WPBRtwL3kxgs3gk8NcLHctoumjmJ3mic7Qfbx7oqQxr44x/V7CARyYDIcCu4+6eGeOvqIdZfC6xNUV4PLD6t2mXYxXWJawhtamhlcW3FGNcmNY0JiEgm5ewZw5CYITSpOG9cX0MopjEBEcmgnA4BM+PC2greHMfXENJ5AiKSSTkdAgAX103inUPtdPfFhl95DAx0A6klICKZkPMhcFFdBbG4s61xfLYGBoYCNDAsIpmQ8yFwyaxKwiHjB6/uG37lMaCWgIhkUs6HQHVZAX/wobmsq29g24G2sa7OIJodJCKZlPMhALDmQ+cQMnh6S+NYV2UQnTEsIpmkEAAmlxawbE4VP992aKyrMohmB4lIJikEAleeX83bB9tp7R5fN5mJ6YxhEckghUBgZmXi0tKH2nrGuCYn0piAiGSSQiBQU1EIQGPrOAsB3WNYRDJIIRCYVp4IgYOt3cev3DkeDHQDaUxARDJBIRAYCIEv/2gztzz06hjX5n26dpCIZJJCIJAfCVEQSfzneH57M1190TGuUcJAd5BaAiKSCQqBJL3R9wdfH9mwD/ex/8N7vCUwjm98IyITl0IghTmTi/n6E9t49I39Y10VosEff7UERCQTFAJJ7v7dD/AnV8/nmT/9MBfUlHP3CzvHfJBYYwIikkkKgSTXXVjDn15zHnnhEH/wwbnsaOpgw54jY1onjQmISCadVQiY2R4z22xmG82sPiirMrNnzOzd4Lkyaf07zGyHmW03s2vPtvKZtHLxdAoiIZ7cPLbXE9IZwyKSSSPRErjK3Ze4+7Lg9e3As+4+H3g2eI2ZLQRWA4uAlcDdZhYegf1nRElBhI8smMqTmxvp6B27mULvX0BOA8MiMvIy0R20CngoWH4IuCGp/BF373X33cAOYHkG9j9i/uBDcznS2ccfPlTPruaOUd9/PO4MTFBSd5CIZMLZhoADPzez18xsTVA2zd0bAYLnqUF5LZB855aGoGzcWjq7iq9ev4j1u1r463/bNur7jyVNUdXAsIhkQuQst7/C3Q+Y2VTgGTN7+xTrWoqylH/ZgkBZAzBr1qyzrOLZufnyOWw/1M6/bTxALO6EQ6kOIzOS//CrJSAimXBWLQF3PxA8NwGPkujeOWRmNQDBc1OwegMwM2nzOuDAEJ97n7svc/dl1dXVZ1PFEbFsdiXtvVG+8cQ2WrtG71LTySGgloCIZMIZh4CZlZhZ2cAy8B+BLcDjwM3BajcDjwXLjwOrzazAzOYC84ENZ7r/0XTpnCoAHnxpD9d/+8VRu+dA9ISWgAaGRWTknU130DTgUTMb+Jzvu/vTZvYqsM7MbgHeA24EcPetZrYO2AZEgdvcPXZWtR8lM6uK+Z+/fRHRuPOVRzfzwIu7+a/XnJfx/aolICKZdsYh4O67gItTlLcAVw+xzVpg7Znucyz950sTPVm/ereZe17YyTnVJaxaktlx7eRf/zpPQEQyQWcMn6a//cSFXDyzgj9d9ybff+U99rZ0ZmxfyT1AagmISCYoBE5TZUk+/7D6EvLDIb7y6Gau+rsXeP7tpuE3PAPJLYF+hYCIZIBC4AzUTiri8S9cwQ/WrOCc6lJu//EmfvDqeyN+sbkTxwQ0MCwiI08hcIbmTyvjN86ZzDdvvJiKojy+/KPNrL7vZRqOdo3YPk44T0BjAiKSAQqBs3TxzEn87Ev/gf/1yYt4q7GNT9//yohdYkKzg0Qk0xQCI8DMuHHZTB78/Utpau/l6r//BX/+/948oXsoFvfTvhBdVGcMi0iGKQRG0NLZVfziv13FzZfN4YevNXDx13/Ov7y8l395eS/X/+OLXPY/nmXbgba0Py/bWgIb9x3j43f9is4xvCqriJxIITDCqssK+Or1C7lk1iTae6L85U+28Jc/2cKB1m7ae6Lc/M8b2Hdk8LhBa3c/r793lP5YnN5o4hy6WJadMfz63qNsPdDG3paRGzcRkbNztheQkxTMjAd/bzktnb3c/+JuPnjuFK67sIZ3DrVz473rueE7v2ZmVTF/c8NiFtdWsLO5gxu+82vae6IU54eZXlHIT//4Qyd0AWVDS+BoVx8Ahzt6x7gmIjJAIZAhFcV5VBTn8befuPB42XnTyvjh5y/jq49v5aWdLdz8wAaWzalkW2MbBtz+sQU89NIedjV38u3n3+XD5yWuwh0JWVaMCQyEQEunQkBkvFAIjLL508r4/h+uYPvBdu586i12NXcyrayQr//WYq5aMJXPf3gef7buTe775S6mlxcCkB8JDdkS6I/FyQtPjF69o8EVWFs6+sa4JiIyQCEwRs6fXsY/fzb1jdW+ct0Cfrb1IPf+YheQODltZ1MHXX1RivMTX9l3X9zN917ey56WTpbOrmT53Cpuu+rc4++PR0c7B7qDFAIi48XE+AmZYyaXFnDNwmnsP9YNwG8vraOzL8bPth4EEgHwjSe2MSVY79U9R/nO8zu56bsbThhU3nO4k9u+9zpf/7dttIyDfvj3WwJjXxcRSRi/Pxtz3McvrOHRN/YDsOKcycyqKub7r7xHYSTMN57YxspF0/n271xCOGRsP9TO9oPtfPGRjXz8rhf56AXTeHpLI3tauggZxB0e+PVuppYVYAZfu34RH7uwBgB359vP7eBQew8tHX18esVsrjh3ypD1cneCy4eftmMaGBYZdxQC49QH57//hzgvbNx02Wz+5qdv8cZ7x5gzuZhv/84lRIKxgAXTy1kwvZzO3hg/qN/Hvb/YyXnTSvnGqkUsmVlJd3+MV/ccYcv+VvYd7eKLj2zkSFcfL+86wqu7j3CwrQdIDED/fNshvnr9Qj56wTRqKgp5aWcLB1t7+NiF0/nVu4f5q8e2cM3CafzlxxdSmBcGIB53QiGjpz9Gc3svkbDhDjUVhScExvsDw33Htzvc0Ut1WcEZB4uInB1zH9+zTpYtW+b19fVjXY0xMef2nwLw9Jc+xIxJRVxx53O090T58soF3HrlvJTbuDub97eyYHo5+ZHBvX0tHb18/K4XOdjWQ1VJPh+YNYnzp5dx65XnEos5v3P/y2w90EY4ZJwzpYR3mxKXwBhoUcyoKORAaw8zq4qoKMqjMBLmjX3HqKkopOFo9wn7+saqRXzmsjkAdPfFuOCvngZgalkBP/z85Xz2wQ3sbO5kVlUxcXfywyGuWjCVK8+vprsvxu7DnUwtL+Bji2vYeqCVrQfaqKss4vJ5U1i/s4UlMydRWZI/6Bhbu/ppau9h7pSS40E50p7f3sTS2ZWUF+Zl5PNFzpaZvebuy4ZdTyEwft38wAZ+8U4zP/2TD7JoRgWH2nr40esN3HTZHEoLzrwR19kbZU9LJ+dOLaUgEj7hvWNdfby44zCv7T3K243trFw8nflTS/n1zsPMnVLK9RfX8Kt3DvPwy3uJhIyWzj7qKovYfrCdqy+YytSyQmLxOP/43A4MePS2K5hXXcqBY91cfudzzJlczJ7gZLHi/DCfWTGbLQdaKS2IcLSrnw27jwyqb17Y6E+6gF55YYS24JyKv7j2fC6bN4UHX9rDpoZjdPRGj5+MdsmsSfynS2pZcc5kXt7VQiQc4oPnTuFgWw+NrT288d5Rzp1aSnVpAR+YXUnYjP5YnCmlBXT0RXnjvWOU5IdZFtxe9GhnH3uPdLHncCdf+sFGPrV8Fl+9/v0WESRCuLs/RnF+hPaefvIjoUH/jceb3miMvFCIUEitsWyiEMgCbT39/Oi1Bn7v8jkTrrtkV3MHN967npg799+U+Hf4yXvXc++nl1JeGOHZt5u48vxqPjS/+oTttuxvpbs/RlFemKnlBWw/2M7TWw6yfG4VS2dX8vSWg7x9sJ0rzp3MYxsP8ML2ZgCK8sJcOreKsoIIi2sryAsb33rmHTr7hr6DaWFeiJ7+wWdiTyrOo7W7n4H/NS6fN5muvhiNrd0causlHLITpuyeM6WE+dNKKcoL09Tey0s7W1hcW847BzvICxuf//A8DrX30Nod5UhnL3OnlNDS0Ud1WQH/vu0Qk4rz6emP8ZEFU+nsixGNxfng/Ckc6+rnvSNd1E4qYlZVMW09/TS397LvaBeRUIiFM8q5fN5k8sMhfvFOM42tPexq7mDhjHI+MKuSkoIIhXlhdjV34A5zphRz4FgPv955mMvnTSFsxtYDrXzn+R18bHENX/n4BYQMivMjNLX3UL/nKE3tvXxyaR0l+WGe395MXtho7e7nqgVTeetAG939MSaXFFBVms/kknwK88LE4k5Tew8/3dTI7MklfGj+FEJmJ7RM23r6eW3PUfLCIZbMmkRe2MgPh074d97c3svB1h7mTys9HrQ9/TFCZmxrbOOi2orTDq7u4HucWVV8WlOre6MxDhzrYVZVMeEMhGVHb5RIyE74QdEXjadszadLISBjbm9LJ5/951dpau89/uv911/+CBXFI9OF4u48veUgzR29XHdhDVNKC054PxqLs/VAG5sajnHFuVPojcY0aSsKAAAIE0lEQVT5+dZDnFNdQn4kxDUXTGPX4Q6OdPazqeEYZkYkZGxqaGVmVRHLZlfxVmMb/+eXu6guK6AgEmLRjHLiDotry/nvj25hXnUJVSX5tHT00RuN09bdzw2X1LL1QCszq4ppDkKhOD9MZXE+eWFjT0sXJflheqJxPnrBVA539NHVF+OtxjaqSvLpj8Vp70lcXylVUOWHQ/TH47i/3003oLI47/gsrKGYwan+t0/1/sn7GUpRXpju/tigoAQoK4gQCRt54RBHu/qOt+4iIcOBWVXFlBSE2X+0m2hwwUX3xPuVJfnUVBSyZX8rk4rzOdLZR2FeCHcoLYjwH86r5s2GY/TH4syuKqG9N0o0OIcmPxxi/7FujnT2EY3H6Y851WUFLJpRTk9/jBXnTObNfcdwoKsvxuXzJjOpKI+fbDyAGcyoKOLNhmM0HO2mtCDCb15Uw5wpJbT39HOksw8zo6MnSntPP42tPce/u5KCMFedP5X9x7rZFnSxXjJrEqUFebzb1M6u5k7OqS4hEjKe395MeWGE37tiLuWFEV7ccZjNDa28dMdHzrglOW5DwMxWAv8bCAP3u/udp1pfITCxNRzt4re+/WuOdPbxR1fO4y9WLhjrKo0Id2f9rhYunVN1wi/Kk2dPRWNx3jnUwTnVJcd/5R3t7KO4IExPX/x4IMbjTltPP5OK8+mLxnlm2yHOn17GvOoSGo52c7Srj5KCCFNKCrAQNLX1cKSzn2ffOsT0ikKWzq7k/Oll5IdDHGrr5bW9R+nsi3Ksq4951aWJVsdbTURjcT734Xm8sL2JKaUFzJ9WSnlhHnc+9TbVZQXkh0O0B/W4dE4V0Xic595uoi8WZ9GMCsoKIxiwuaGV+dMSn9vS0ceRzj5aOhPPxflh+qJxblxWx3ee34m7M6+6lJbOPvpicbr7YlSXFXDV+VPpj8V5ZXcL/TFnc0Mr+ZEQtZVFGInrcJ07tZStB9poPNbN4Y4+ZlYV88L2JlYtqaWnP0Z+JMT+o908vfUgy2ZX0tMfo6M3yoxJRQC090RpONpFZXE+Vy2YSsgSY10/3dzIkc4+Ovui7GruZM7kRMvADN45lBgHO2dKCcUFYbr6Ykwte39s6sev7ycad0KWOJEzHofSwgh1lUWU5EcoLYwQMmhq7+WN945RO6mIusoi8sIh3j7YTmdvlPxIiA/Nn8Kelk6a23u5YUkt9XuP8treowDUVRZx3YU13HbVuVQUndmPpnEZAmYWBt4BrgEagFeBT7n7tqG2UQhMfEc6+9h3pIuFM8onzNnNMrEMzFBLpac/Rl44lLIbJx53jnT1ndCKbG7vJRZ3ppWnnrXW2tVPKMTxrq9o3MkL26Bf7O7Osa7+QZMX4nHHIWV9eqMx2nuiTC7JP+su4HRDYLSniC4Hdrj7LgAzewRYBQwZAjLxVZXkU5ViFo/ISDnV2EByP3uq7U7uRqwuKxhi7YTk7sxTfDRmlnL22qnqWhAJU1A6uhMJRjsEaoF9Sa8bgN84eSUzWwOsCV52mNn2M9jXFODwGWw3kemYc0cuHreO+fTMTmel0Q6BVBE4qD/K3e8D7jurHZnVp9MUyiY65tyRi8etY86M0e6gbQBmJr2uAw6Mch1ERCQw2iHwKjDfzOaaWT6wGnh8lOsgIiKBUe0OcveomX0B+BmJKaIPuPvWDO3urLqTJigdc+7IxePWMWfAuD9ZTEREMkeTtkVEcphCQEQkh034EDCzlWa23cx2mNntKd43M7sreH+TmX1gLOo5ktI45gVmtt7Mes3sz8eijiMtjWP+3eD73WRmL5nZxWNRz5GUxjGvCo53o5nVm9kHx6KeI224405a71Izi5nZJ0ezfpmQxnd9pZm1Bt/1RjP7qxHbubtP2AeJweWdwDlAPvAmsPCkda4DniJxjsIK4JWxrvcoHPNU4FJgLfDnY13nUTrmy4HKYPljOfI9l/L+uN5FwNtjXe/ROO6k9Z4DngQ+Odb1HoXv+krgiUzsf6K3BI5fhsLd+4CBy1AkWwU87AkvA5PMrGa0KzqChj1md29y91eBU19OcuJI55hfcvejwcuXSZyDMpGlc8wdHvyFAEpIceLlBJTO/9MAfwz8CGgazcplSLrHnBETPQRSXYai9gzWmUiy7XjScbrHfAuJ1t9EltYxm9knzOxt4KfA749S3TJp2OM2s1rgE8C9o1ivTEr33/dlZvammT1lZotGaucTPQTSuQxFWpeqmECy7XjSkfYxm9lVJELgyxmtUeale4mVR919AXAD8I2M1yrz0jnufwC+7O5D3zFoYknnmF8HZrv7xcA/Aj8ZqZ1P9BBI5zIU2Xapimw7nnSkdcxmdhFwP7DK3VtGqW6Zclrfs7v/EphnZlMyXbEMS+e4lwGPmNke4JPA3WZ2w+hULyOGPWZ3b3P3jmD5SSBvpL7riR4C6VyG4nHgpmCW0Aqg1d0bR7uiIygXL70x7DGb2Szgx8Bn3P2dMajjSEvnmM+14KLzway3fGCih9+wx+3uc919jrvPAX4I/JG7j9gv4zGQznc9Pem7Xk7ib/eIfNejfRXREeVDXIbCzD4fvH8vidkD1wE7gC7gs2NV35GQzjGb2XSgHigH4mb2JRKzDdrGrOJnIc3v+a+AySR+FQJEfQJfcTLNY/5tEj9w+oFu4L8kDRRPSGked1ZJ85g/CdxqZlES3/XqkfquddkIEZEcNtG7g0RE5CwoBEREcphCQEQkhykERERymEJARCSHKQRERHKYQkBEJIf9f7muhuDwygCeAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(freq[int(len(freq_pos)/2):len(freq_pos)-1],mod_fft_data_plot[int(len(freq_pos)/2):len(freq_pos)-1])\n",
+    "axes = plt.gca()\n",
+    "#axes.set_xlim(0, 0.1)\n",
+    "axes.set_ylim(0, 4000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous avons mis en évidence le comportement oscillant de la concentration de C02 visible au travers du contenu spectral très marqué autour de 0.1. On note aussi la présence d'un peu d'harmonique 2. Le phénomène n'est pas une oscillation pure mono-fréquentielle. Nous allons filtrer ce contenu."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cherchons l'index de la fréquence du maximum proche de fre=0.01 dans le tableau de la fft de départ\n",
+    "Pour cela nous traçons cette fois le spectre en fonction de l'indice du tableau de valeurs. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0, 4000)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(abs(fft_data[0:int(len(fft_data)/2)-1]))\n",
+    "axes = plt.gca()\n",
+    "axes.set_xlim(0, 200)\n",
+    "axes.set_ylim(0, 4000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "vmax =  (178.51619865797664+1126.1445008434132j)\n",
+      "index =  (array([62]),)\n"
+     ]
+    }
+   ],
+   "source": [
+    "vmax= fft_data[50:75].max()\n",
+    "print('vmax = ',vmax)\n",
+    "imax = np.where(fft_data == vmax)\n",
+    "print('index = ',imax)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons maintenant filtrer grossièrement les données spectrales en *supprimant* les pics parasites, tant sur les fréquences positives que négatives."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
      "data": {
-      "image/png": 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JE0tmxODvZ/3OecnsRDYfq8Ns0fiZlJtb5zzVbT309FvX2lQ0dzErMWLIch8XNRITGuARh+CMRHYqCyGcqqWrj2O17ZybEWu/tmpOIi1d/ewrb6awpo195c1ubKHzFNd32J+fah56aW1Naw//OlLLF/OnoZRnB0PP3SEhhPBKb+yvAmBp5umAcEF2Av4mxduHanivoAaTCT66d5W7mug0RXWnA0LFMAHhpU/LsWjNzefNmKxmjZsEBCGE02w8UsvP3jzCBdnxLB3UQ4gKCWBpRizP7ijBoq3XGjp6iQ/37CGU0RQ3dBIR5E+v2UKFMU8wWL/Zwl8/LefinASP35QGMmQkhHCSnn4zP3j1APNSI/nTLed8Zq5g9ZxELBpSoqxnB+8vb3FHM52quL6TmQlhpEeHUNHcTb/ZQnff6cnl9wpqqG/v5dblnt87AAkIQggnea+ghpaufu69LJewIfL1XLkwhUXTovnDzUvwMyn2n/L+gFBU30FWQjhpMSFUNHfxn28c5orffUS/2TrR/PzHZUyLDeGiHO9IxCBDRkIIp/jbrlOkx4SwIituyJ+nRIXwxl0rAZidFOH1AaGrb4Dq1h5mJoQRFODHm6eqOFHXQVefmbcPVZObHMnOkibu+3yu16yskoAghJiwssZOdhQ18h9rcjA58OGXNz2af+6vwmLRDpX3RMXG2cgzE8IxmRTtPQMARAb784cPiggP9ifQ38QX86e5s5ljIkNGQogJe6+gBoDrz0l3qPziadG09w5Q3NAxemEPdbiyFYC5KZGkx1gnjNOiQ/jRlXM4VtvOocpWfvPFRcSGBbqzmWMiPQQhxITtLWthRlwoqdEhDpW3rUB6alsJ/3PdQlc2zWUOVLQSGezPjLhQmrv6ALg6L5VrF6dT3NDJpXOTPfaozOFID0EIMSFaa/aWN7N4WrTD92TEh3HnxVn89dNTrN9X4cLWuc6hyhYWpkejlGJBWhTfWjWLr67MJNDfxP2fn+N1wQAkIAghJqiypZu69l6WjPED8Htrcjg3I5YHNhw5Y6mmN+jpN3Ospp0F6VEA+PuZ+I9LZ3t8aorRSEAQQkzIXmM/wZLpYwsI/n4mvn/ZbFq7+3l9f6UrmuYyhTXt9Js1i4yA4CskIAghJmRvWTMhAX7kJg+d2G0kSzNimJsSybPbS9Fau6B1rnGowhoEF6Q7PkzmDSQgCCEmZF95MwvTo+yZTcdCKcVXVmZwrLadT4qbXNA65zpU0cplj27lj1uKiA8PJNXYde0rJCAIIcat32zhaHU7eWOYUD7bFxamYlLwcXGjE1vmfP1mCz949QC17T34+SmuXJDi8dlLx0qWnQohxq2koZM+s4XclLEPF9mEBPqRlRDOkao2J7bM+R7fWkxhTTuP33oOl85LdndzXEJ6CEKIcTtW0w7A7KTICdUzJyWSo9WeHRBe/KSMi3ISfDYYgAQEIcQEHKtpx8+kyEqc2OHxc1MjqWzppsXY4OVpatt6qGrt4cKcBHc3xaUkIAghxu1YbTuZ8WEE+ftNqJ65KdYexhEP7SXsM5bWTmSuxBtIQBBCjMpi0Tz01hH7EJHNsZp2Zo9juenZ5tgCgofOI+w/1UKAn2Je6sSGxjydBAQhxKiK6jt44qMS/mUksQNr+ufypi5mJ008ICREBJEQEeSxPYT9p5qZkxJJcMDEekKezuGAoJTyU0rtU0q9aby+USlVoJSyKKXyB5Vbo5Tao5Q6ZDwOeXCqUuoBpVSlUmq/8eeKif86QghXsJ1d0N47YL92vNaaqdQZPQSwDht5Yg/BbNEcqmgdU64mbzWWHsI9wNFBrw8D1wFbzyrXAHxBa70AWAc8P0Kdj2qt84w/b4+hLUKISXTA2Jnb1t1vv2ZbFeSMHgLA4unRHKttp7691yn1OcuJunY6+8zkTZeAAIBSKh24EnjSdk1rfVRrfezsslrrfVrrKuNlARCslPLujE9CTHEHTllz/9sOgbFYNH/5uIwZcaFMj3XO4fGXz09Ga3h30LCUJ3j/SC0A+TNi3dwS13O0h/AYcC9gGWP91wP7tNbDhfy7lVIHlVJPK6WGzIyllLpDKbVbKbW7vr5+jG8vhJionn6zvTfQ1mPtIbxzuIaj1W1853PZTjvxbHZSBDMTwnj7YLVT6nOG3gEzz31cxoU5CUxzUuDzZKMGBKXUVUCd1nrPWCpWSs0DfgF8fZgifwSygDygGvj1UIW01o9rrfO11vkJCb69BlgIT1RQ1caAReNvUrQZPYTfbjrOrMRw1i5Kc9r7KGVNB7GzpJGGDs8YNnrzQDX17b3cfn6mu5syKRzpIawE1iqlSoGXgVVKqRdGusEYYloP3Ka1LhqqjNa6Vmtt1lpbgCeAc8fUciHEuBXWtJH7k3c41dQ1atkDxoTy4unRtPf0091n5nhtB9fkpTr98PjPz0/BomGjMUzjbn/5uJScpHAuyI53d1MmxagBQWt9v9Y6XWudAdwEbNZa3zJceaVUNPAWcL/WevsI5VIGvbwW6yS1EGISFNd30tNv4Xht+4jl2nr6eXp7CTMTwpiVGE5b94D9uMi4cOdPDc5JiSAxIoiPi9yf6K6zd4BDla1cPt/3ktgNZ9z7EJRS1yqlKoDlwFtKqfeMH90NzAJ+MmhJaaJxz5ODlqg+YixNPQhcAnx3/L+GEGIsOozlo4NX9LzwSRm/fK/wjHL/+fphqlt7+OUNC4kMDqC9p5+mTmtAiAl1/uHxSimWZsayq7TJ7ecjHKluw6LxuUNwRjKmbKda6y3AFuP5eqzDQmeXeRB4cJj7bx/0/NaxvLcQwnk6jYAweKz+9X2V7C1v5tZlGSRHBVPa0Mnr+6u4+5JZnDMjlo+LGukdsFDb1gNAXLjzAwLAuRmxvHWwmormbrdO5NqGyhZMoYAgO5WFmIK6jDOMB/cQqlt7sGj4x17rofe2zWhXLrSO7kaGBABQ1midd3BFDwFgaYZ1eeeuUvcemHOospWUqGASI3zrEJyRSEAQwkG2JZe+oMPeQ7AO/5gt2v7N/2+7TmGxaA5UtBAcYCI7MRyAiGDrgEJZYycAsWGuCQizkyOICPZ3f0CoaGVB2tTpHYAEBCEcsv1kA4t/tvEzyd28VedZcwgNHb0MWDRLM2Iob+rik+JGDla0Mj/19NGYEUHWHkJpYxdKQZTRY3A2P5Mif0YMn5a4LyC0dvdT3NDJwik0XAQSEIRwyKt7KjBbtNu/tTqLfVLZmEOoaukG4KsrM4kKCeCFnWUcrmxl4aBD5G1DRuVNXUSHBDh9yelgC9OjKarvpN881r2wzlFQ2Wpvx1QiAUGIYRytbuPq/9vOybp2+7r4gqpWN7fKObp6rXMIDUYPobrVOlw0Iy6Uaxen8fahGnoHLCyadvobsm3I6FRTFzEuGi6ySYiwLmlt7HDPgTk7ihrxMykWSUAQQoB1lcmBUy3c9PhOOnoHiAj253Cl52XjHI/OPmsPob13gO4+sz0gpEaF8KWl0+zlFg3RQxiwaOJcHBDijT0O7tqx/G5BDedlxhIV6pphMU8lAUGIYbQYmT0bOnqJDQvki/nTOFbTTt+Ae4YxnKljUBrrho5eqlu6CQ4wER0awJyUSBalRxEVEsCMuNPLPm09BHDdCiObhAhr/fVuCAgn69o5WdfB5fN99+zk4YxpH4IQvuyBDQWsnBXPmrlJgHViMcBP8cX8aWTGh5EUGcxT20o4UdfOvFTvnmzs7B0gOMBET7+F+o5eqlt7SIkKse/I/eWNi6hr6z1jh254oD9KgdauW2FkY+8huCEV9ruHrdlWL50rAUGIKcls0Tz/SRm1bT32gNDS1U9USCAPXbsAgJIG63LLveUtNHT0ccGseKdl+pxsnb1mZsSG2c8fqGrtJiXq9Hr7nKQIcs4658BkUoQH+dPeM+DyOYTTQ0aTP4fwzuEalkyPJjlq6uw/sJEhIyGAxo5ezBbNyboO+7XW7j6iQk5/Z5oRG0p4kD8PbChg3dOfsqmwzh1NdYrOvgEy4q3DQQ0dvdQYPYTRRAZbx9RjXTxkFBbkT0iAH42TPGR0oradgqo2rliQMnphHyQBQQigts36wVPa2MmAsdSxtbuf6EEffCaTYtnMWGJCAzEp605Wb9XZO2A/2KamtYfath5So0f/RmybR3B1DwEgPiJw0ieV/7G3Ej+T4uo856X19iYSEIQA+y7dfrOmzEgJ3dLVT/RZm69+/+UlbL/vEmYmhHPES5eg9g6Y6TdrokMDiQkN4EiVNYmbI0Mkth6Cq1cZgXXYaDKHjMwWzev7KrkoJ8G+7HWqkYAgBFDb3mN/bhs2ss4hnBkQggP8CPL3Y16qZx4I74hOYw9CaKAfCRFBbDluPYlwZnz4qPdGhkxiDyE8aFJ7CB8XNVLT1sP1S9In7T09jQQEIYDa1h5sC2psAaGtu3/YdejzUiOpau2hubOPI1VtmC3uTdU8Fra0FWFB/izNiCUjLpRfXL+AZTNHPzM4YpLmEGDyA8Lbh6sJC/Rj9ZzESXtPTyOrjITAOocQHx6En1IU1XXQb7bQ3jswbL6euSnWZad/2HKSJz4q4X//bTFfWJQ6mU0eN9umtPAgf/sKKkdF2ucQXL9hKyE8kKbOPswW7dI0GQBaaz4orOP87HiCA/xc+l6eTHoIQmAdMkqODGZWYjgn6ztoMzalnT2HYDMvNRKAJz4qAWBPWfPkNNQJBvcQxiojPoykyCDCx3HvWMVHBGHR2A/kcaXCmnaqW3tYlTt1ewcgAUEIwNpDSIoMYlZiOEV1HfZdytHDDI3EhAWSakzCBvmbOFDRMmltnagOYw4hPGjs34RvW57Blu9fMilHSk5m+orNxhLiS2ZLQBBiyqtt6yExMpisxHA6+8wUVlvTXI+U4nlpZiyzkyL48nnTKahqc1tmzrHqMnoIoYFj/5bvZ1KEBE7OkIotIOwoauS/3jjMkx8V21eDOduWY3XMT4skMXLqbUYbTOYQxJTXO2CmqbOPpIhgZiVYV9rYhoBGSm72i+sXYrZoNhXW8cz2Uo7VtDPfCw5UseUxmoxhn4mIN47ofOitIwBYtHXvx29vWuzU9ymq72BPWTPfXp3t1Hq9kfQQxJRnOyTGNmQEsKfMeu7BcHMIYF2CGhbkbz+E3dOHjbr7zLy+r3JCcwiTKd7YC6CBl/59GdcvSeeDwjr7xkFn+f3mkwT5+3HLshlOrdcbORwQlFJ+Sql9Sqk3jdc3KqUKlFIWpVT+WWXvV0qdVEodU0pdNkx9sUqpjUqpE8ZjzMR+FSHGx7ZLOSkymPjwQKJCAigw9hg4cirY9NhQokMDOHjKszeqvXWomu/8bT9bTzQAEDaOOYTJFBHkT05SON/7XA7LZsbxuTmJtPUMsNuJE/hF9R28sb+SW5fPsA9RTWVj6SHcAxwd9PowcB2wdXAhpdRc4CZgHnA58Ael1FD/8u4DNmmts4FNxmvhAsdr21n39Ke0dLnnsBFPV2eMSydFBqOUYlZiOAPGvgJHAoJSioXp0R7fQzhl7MD+pLiRAD9FkL9nBwSlFO9950K+ZQzlXJCTQKCfiU1Ha51S/zPbS7jm/7YTEuDHv18w0yl1ejuHAoJSKh24EnjSdk1rfVRrfWyI4lcDL2ute7XWJcBJ4Nxhyj1nPH8OuGYsDReOe3pbCR8er+evn55yd1M8Uo0REBIjrd8QbfMIEUH+9vOERzM7KZyShk4sHrxBrdI4JrOrz+zxw0U2Z6TfDvLnvJmxbDo68aSC+8qb+ek/j5A3LZr1d62csqkqzuZoD+Ex4F7AkcG7NGDwJ0+Fce1sSVrragDjcWqv93KRnn4zbx2sBuD5j0udPv7qC07UdRAR7G/Pz2ObR4gcwyHyGfFh9A5YqHbRKhhnqGzutj8PG8cKI0+wOjeR4oZOyhu7JlTPU9tKiAj254+3nPOZNN9T2agBQSl1FVCntd7jYJ1DLVAe99cmpdQdSqndSqnd9fX1461mSujoHbBPhtq8V1BDe+8AX12ZQVVrj/1sYHHa0eo25qZE2r+N2gJC9BiOT8yICwOgzDgzwRNVtnTb03N4+vzBcJZnxQOws6Rx3HVUNHfxzuEavnzudI9faTXZHOkhrATWKqVKgZeBVUqpF0YoXwFMG/Tn74tYAAAgAElEQVQ6HagaolytUioFwHgcsh+otX5ca52vtc5PSEhwoLlT17PbS/jinz85Y67gH3srSYsO4YdXzGF6bCi/3XRCegmDmC2awup25ho7j2GcASHeGhBKGj0zIFgsmurWbpZlxgGev8JoONmJ4cSEBrCzpGn0wsP4+y7rAMa6FRlOapXvGDUgaK3v11qna60zsE4Wb9Za3zLCLRuAm5RSQUqpTCAb+HSYcuuM5+uAN8bUcvEZR6qtSdaKjW+pxfUdfHSinuvPSSfAz8T9n8+lsKadZ3eUurehbtQ3YOHyx7by5EfFgPX8g+5+M3NTTgeEtOgQggNMDk0o26REBhPob6LUw3oIjR29vLqngrr2XvrNmkvnJRHoZ/Lab8Ymk2JpRiyfTiAgFNV3MiMulNTo0Q8EmmrGvQ9BKXWtUqoCWA68pZR6D0BrXQD8HTgCvAvcpbU2G/c8OWiJ6sPAGqXUCWCN8VpMwPFaa5bO4nrrh9Iz20sJMJm4Zdl0AC6fn8zFsxN4dONxnt5WQltPv9vaOtk+PF5Pd5+ZqpZuCmvaefCto/xtV7k9hfXgHoLJpLjz4lmsXeT4ISkmk2JGbCilExzbdqYBs4VvvLCH779ygPcKrOcEZ8SHcem8JBame/4GuuGcmxlLeVMX1a3doxceQvVZx4WK08b0NUFrvQXYYjxfD6wfptxDwENDXL990PNGYPVY3l8Mr2/AYv92WlzfQUtXH6/uqeDqvFQSI6z/+JVSPHjNfO56aR8/e/MIO0sa+fOt+SNV6xNONXWx7ulP+fk185lpDO2kx4Two/WHWT0nEX+Tsg8T2Yxn12pGfJhH9RB+vfE4u0qta/b/+mk5AOnRIfz+y0vc2awJO88Y9vq0pGlcJ5vVtPbY5yLEmWSnso8obey0r50vru9kw4EquvvNfO38zDPKpceE8sZdK7lucRp7yz173byz2M43KKnvtC+9/N2/LSYkwI/3CmqZlRjulDX5mfFhlDV1ecTS074BC09tK+GavFTmpERSWGPNzZQW4/3DJHNTI4kI8h/XAgmzRVPb3is9hGFIQPARx2uN/+GjQyhp6GTbiQamxYYwZ9DY+GCzkyOob++ltcv3h41scyrlTZ1UNltX2sxPjeI7a3KAM4eLJiIjLoy+AQtV4xzKcKbjte30DVhYPSeJC7Ot34ZjQgPGldDO0/iZFLcsn8GbB6vZfrJhTPc2dPRitmiHjgudiiQg+IjjtR2YFHxuTiIljZ18UtzIipnDd4ttQyQn69snq4luU9Jg7SGUNXZR2dJNYkQQgf4mbls+g2sXp3HtYuccqJ4RF2p/H3c7VGlNo7EwPYoLsq2r89JjQt3ZJKe6Z3U2mfFh3P/aIXr6zQ7fV91q3SciPYShSUDwESdq25kRF0ZuSiR9AxbaegZYMStu2PL2gGAMp/iyEnsPoYvK5m7SjNUlAX4mHv1Snv0Dc6Jsf6dbj7t/v8zBilYig/2ZHhtKfkYMQf4m++/tC4ID/PjhFXMob+oa0xLUGqP3Jj2EoUlA8BHHa9vJTgy3T5oCLM8aPiCkx4QS6G+aGgGhvhM/k6J3wMKhylaXLTdMjAzmuiVpPLO9dFInl7v7zGh95rzF4cpWFqRHoZQiOMCPX39xEd+8OGvS2jQZVs6Kw9+k+KTY8U1qp3sIvhMcnUkCgg+wWDRljV1kJYYz08jDk50Ybl9dNBQ/kyIrIZwTPh4QuvvMVLX2sHhaNGDdze3KidX7Ls8lwE/x4FtHRy/sBD39Zpb9zyZe2V1hv9Y7YKawpu2MsxmuWpjKIuPvwFeEBvqzMD2KnWMICDWtPQT6m4gZw6bDqUQCgg9o7x1gwKKJCwskPtx6tKMjZ8POSgz3+R5CqbFz+OLZp4eFXDl0khgZzK3LM9hcWGs/iMaV6tp6ae3uZ3vR6cnVYzXt9Js1C9N8KwAMZdnMOA5WtNLV59jfdXWr9ezsyTgC1BtJQPABtgPho0ICUErxzj0X8h+Xzh71vlkJ4VS2dNPd5/iknLexzR+cn52AyfgMcPVY+nkzY7FoOHjK9ct6643zhm2TyAAHKk5PKPu682bGMWDR9hPuRlPT2iPzByOQgOADWgcFBLAe+xjoP/p/2lmJ4WhtPSTEV9kCQnZiuH3uwNUpC5ZMs571tLfceQe5DMd22ltJQ6e9R/Lu4Wqmx4aS7gN7DkaTPyMGPwfmESwWTd+Aheo22aU8EgkIPuDsgOCovOnWIYVtY1zL7S12Fjfyt12nSIsOISzIuuIGXL85Kyo0gKyEsEnZ+Ndg9BC0hoLKVmpae9hR1Mg1i9OmxLBIWJA/52bE8rddp2g0/i7OZrZobv/Lbpb/zyaqW6SHMBIJCF7KbNF87+/7OXCq5XRAGONEWVp0CIvSo3j7ULUrmuhWe8qauOmJT7Boza9uXARYewnx4YFEBrt+QnHJ9Bj2lTd/ZvWPszUM+hA8XNXGhgOVaA3X5KW69H09yX+tnUtb9wA/fv3wkH/fj7xbyObCOkIC/RiwaNJ9aPmts0lA8FIlDZ28treSzYV1tHSNr4cA8PkFKRysaLUfr+gLLBbNz948SkJ4EO9+50L78tvvrsnh5TuWTUoblsyIobmr3z5k5SoNHb3EhAaQFBnE7tImXt1TwaJp0fbVZlNBbnIk312TwzuHa/jpP49gHpQ6pKi+gz9vLebm86az+T8u5n//bTHXn5PuxtZ6NgkIXuqEkaqisbN33ENGAFfMTwHgncO+0UuwWDTPf1LGgVMt/OCy2WekeY4ODWRW4uScjrVkunUewdHJzvGqb+8lPjyI+alRvHO4huO1HXxtZYZL39MTff3Cmdx+fibP7ijlB68esF+3/f1/7fxMAv1NfGFRqk+k73AVCQheypbquqG9j9bufgL9TIQEjD1B2/S4UOanRfJegfefpNbU2cfnfvMh/7WhgMXTo7luifu+CdqGp7a4eNdyQ0cfCRFBXJKbSFxYIE9/JX9cGUC9ncmk+PFVc7nz4ixe21vJDmMZ7sGKFiKC/MmMCxulBgESELzW8bozewiRxpLT8TgvM47Dla1ed5KaxaLPGDPeUdRAcUMnP796Hi/fsQw/k/smVU0mxefmJLGlsI7eAdct623osPYQbj5vOrt//DlW5Sa57L28wbdXZ5MeE8JPNxxhwGzhYIV1x7bJjf8WvIkEBC9lGzJq6OijrbufqJDxd4Pnp0XSO2ChqN5zcvmPpqffzPV/2sE9L++3B4UTRoK/G/OnOSWd9URdNi+Zzj4zO06O//zf0TQYQ0ZKqSmxqmg0wQF+/PjKORyrbeeVPRUcrW5jYbrvb9BzFgkIXqjfbLFPVjZ0WHsI45k/sJmfat3AdHjQ5iZP9/A7hewrb2HDgSr+ZeTFP1nXwfTYUILHMXTmCitmxREW6Me/jtS4pP6uvgE6+8zERwS6pH5vddm8ZHKSwnn4nUL6zZq8ab6/Qc9ZJCB4sL/vOsWfPiz6zPXShk76zZqshDDaewaob++dUECYmRBOSIAfh6u8IyC8uqeCZ3eUctvyGeQmR/DTDQV09Q1woq590iaNHRHk78fFuYlsPFLnkuWnDe19ACSEBzm9bm+mlOL282faF1tID8FxEhA82Ov7K3n+47LPXLdNKNuWU5Y0dk4oIPiZFHNTIymobBt3HZPlxZ1lfP+VA6zIiuOHV8zhJ1fNpaq1h3cO1VDS0ElOkmctt1w2M46Gjl57lk1nsqWtiI+QgHC2tXmpxIcHEh8eJDuTx0ACggdr6eqnurWb/rMme0/UtaMUnGucLds3YJlQQACYnxpJQVWrRxz/OBytNb987xjLZ8bx9FeWEhzgx7KZccSHB/LkthL6zZpsDwsIc5KtPZbCGucHW9umNOkhfFZwgB+/uH4hP75yjsytjIEEBA/W2t2PRUN1y5nfLssau0iNCjkjV81EA8K8tCg6+8z27KCeqKath5aufq5YkGyfJ/AzKVbnJnG02vqBm+1BQ0YAOUZAOFrt/JPpbHmMEqSHMKTVc5K4xkmn4U0VDgcEpZSfUmqfUupN43WsUmqjUuqE8RhjXL9ZKbV/0B+LUipviPoeUEpVDip3hfN+Ld9gy2J6qvnMXcTVrdYEXYO/GUZOMCAsMfIa3fvqQY/dtVxofKjmnnVO9OfmWpdaKgVZHrZDNzI4gLToEPsh985k6yHEhsmksnCOsfQQ7gEGn/pxH7BJa50NbDJeo7V+UWudp7XOA24FSrXW+4ep81FbWa312+Nov88aMFtoN7JXnv0BXW2k8I0LP/1BEB06sQ+FWYkRPPalPI7VtPP/nts1obpc5agx7DI7+cxewPmz4gkOMDEtJpSQQM9YYTTYnJQICqudP2RU29ZLbFggAX7S0RfO4dC/JKVUOnAl8OSgy1cDzxnPnwOuGeLWfwP+OpEGTlVtPacP/Kho7rY/11pT3dpDanQIoYH+hBofgBMdMgK4ZnEa316dzfHaDuranT8JOlGF1e2kRYd8JjldSKAf65ZnsHaRZyZ0y02OpLih0+kb1EobOsmIC3VqnWJqc/SrxWPAvcDg2c0krXU1gPE41BFdX2LkgHC3UuqgUupp25CTsGrp6rM/Hzxk1NzVT9+AheRI68oJWy/BGQEBrEnZAPaWuT5181gV1rQxJ2XoOYL7r5jD9y8b/VAgd8hNicBs0U4/na64oYPMeM8aIhPebdSAoJS6CqjTWu8ZS8VKqfOALq314WGK/BHIAvKAauDXw9Rzh1Jqt1Jqd329a/PCeBLbGmqlzhwyqmqx9hZSo42AEGadR3BWQJifFkmgn2lSDncZi94BM0X1nZ8ZLvIGucnWOY+CKucNG3X2DlDb1svMBMnRI5zHkR7CSmCtUqoUeBlYpZR6AahVSqUAGI91Z913EyP0DrTWtVprs9baAjwBnDtMuce11vla6/yEhIShivgkW0DISgg/Y8ioxljPnhxlXWEUH+7cgBDk78eC9CiXZ+kcq5N1HZgt2v7h6k0y4kJJiAjigQ0FPLej1Cl12naqz4yXgCCcZ9SAoLW+X2udrrXOwPohv1lrfQuwAVhnFFsHvGG7RyllAm7EGkCGZAsmhmuB4XoSU5ItIMxPjaSuvZeefuv4c3Wr0UMwNtvEO3nICOCcGTEcqmh1aVK2sfq4yJoPKNcLewj+fiZe++YK8jNi+a8NBXxw7OzvTmNXbASETOkhCCeayPKEh4E1SqkTwBrjtc2FQIXWunjwDUqpJ5VS+cbLR5RSh5RSB4FLgO9OoC0+xx4Q0qx5WGy9hOrWHvxNijijZzA7OYK06BCCA5y30mTJ9Bj6zBYOe8jO5cKaNn753jFWZMUxK9E7x8ynxYby5G35ZCWE8Z9vHLYH+PEqqe9EKciQtM7Cicb0KaK13qK1vsp43qi1Xq21zjYem84q95mjqbTWt2utdxvPb9VaL9BaL9Rar7VNUAurVuMUtLmp1iES2zxCdWsPSZHB9tTO65Zn8MH3L3bqbsz8jBiUgg+d8E3WGb7z8n4iQwL47U2LvXrXaaC/iZ9fM59TTd08ta1kQnWVNHSQGhXiMYn8hG+QBcweqqW7n7BAP+alRqEUHKywJp6zbUqzMZkUgf7O/c8YHx7Eyqx4XttX6fZUFlUt3RTWtPONi7J8Ykfuiqx4lmbETPgc6+KGTplQFk4nAcFD2VJaR4UEMCc5kk9LrWPotk1prnb9OWlUNHeze5Inl9t7+s/I+2Nb7bQ0w3dWJV+Sm0hBVRu1bePb66G1pqS+UyaUhdNJQPBQtlPQAM7NjGVPWTO9A2b7pjRXu2xeMmGBfry2t8Ll7zXYoxtPcPXvt9vH2PeUNRMcYGJOivetLhrOqlzrlp0PCsc3JFfR3E177wAzPSxNh/B+EhA8VGtXP9Gh1oBwXmYsPf0W3j1cc8amNFcKDfTnigUp/PNA1Rmb5Fxt64l6egcs9k1ce8uaWZQe7VPpGWYnRZAaFcymcQaEV3afQilYPWeovaBCjJ/v/F/mYwafgnZuZiwA9792iCB/E5+bMznn5t5+wUw6+8wTngB1VG1bjz0QHKlqo7vPTEFVG+fM8J3hIrAe4LJqTiLbTzaMeWlvv9nCy7tOcXFOAukxkrZCOJcEBA/V0t1HdIh1j0FceBCzEsPp6jPz3TU5TJ+k/DWzkyO4YkEyz24vta96cqUdRQ3250eq2zhY0cKARftcQABYmRVPV595zGmxNx2to669ly+fN8NFLRNTmQQED9Xa3U9U6OnNZtcuTuOC7HhuPz9zUtvx7dXZtPcO8MqeUy5/r20nGokJDSBvWjRHqtrYYWxGWzzd9wKCbX/JWM6x/ueBKu599QBp0SFcMnvq7NoXk0cCghvVtvXww/WH+N2mE2ckPuvpN9PTf+YpaHddMovn/995+E/yWHpuciQz4kLZVdo0euEJ0Fqzo6iB5VlxzE+L5Eh1G6/tq2BFVpxP5vtPjwkhOjTA4YBwvLadb/11H1mJ4bz075P/70BMDfKvyo3+tusUL+0s5zcbj3Pjn3ZQaqQjsB2M48x0FBNxzvQY9pS1uOSgeJu6duu5w+dmxDI3JYqO3gFONXXzxfxpLntPd1JKsSAtikMOBoStx62JHf9w8xJmyO5k4SISENxo6/F6FqZH8cH3Lwbgq8/uorW73562wlMCwpIZMTR09HKqqXv0wuNUZPSQspMi7LuzI4L8uWxessve093mp0VxvLbdoYnlT4obyYgLJSXK9UuOxdQlAcFNWrv62VvezEU5CWTGh/H4bfmcaurih+sP8eZB6y7WydiA5gjbpO6ectcNGxXVWwNCVkI4s5MiCPQ38YW8VI88Ac1Z5qdG0W/WHBvleE2zRbOzpIllM+MmqWViqvJ3dwOmqu1FDVg0XJRjnRxcmhHLd9fk8Mv3jgFw3ZI08j1kdU1OUgThQf7sKWvm2sXpLnmPovpOwgL9SIoMQinFa99cQYaP78RdYEwsH6psZWF69LDljlS10d4zwPIsCQjCtSQgTLK69h7+vusUO0uaiAj2J2/a6Q+Cb1yUxb5y61j9w9ct9JhEbn4mxeLp0exx4SlqRfUdZCWG239n2yocXzYtNoSokAD2l7dw8wjLSD8uti7HlR6CcDUJCJPspZ3lPPb+CQCuWphyxmoRP5PiidvO8ZhAMNjSjFgeff84de09JEY4fyiruL7TvgFvqlBKcVFOAhuP1tI3YBk2SeHW4w3MTAgjaRJ2qIupTeYQJtmesmZyksL5xzeX8/Or53/m554YDAAun5+M1vDOoRqn193VN0BlS/eUTNa2dlEqLV39bDs59PGwNa097Chq4MoFKUP+XAhnkoAwicwWzb7yFs7NjOWcGbHEeNH6+pykCHKSwnnzYJXT6y6uty63zfLSw28m4sKcBKJCAtiw3/r3eqqpi9++f8K+M/z1/ZVYNFy3xDVzN0IMJkNGk6iwpo2O3gHyZ3jn0MhVC1P5zcbjxpkMzlv+aDsOMmsKZu8M9DdxxYJkXt9XxY9fP8T6vZV09pnZVFjLU+uW8treCpZMjyZzCvaexOSTHsIksh1c7625ea5aaB22ePewc4eNiuo6MCmYMUk5mjzNzefNIDEyiNf2VrJ4egwPX7eAo9VtLH3ofY7XdnD9OdI7EJNDegiTaHdpM0mRQaTHeOfmopkJ4aREBXPglHNXG5U1dpIyhY+DnJ8WxYc/uOSMaznJEXxa0kSwv4kbJCCISSIBYRLtKWsmf0asx04cOyInKYJjtR2jFxyDiuZupsV6Z5B0lSXTY1jig0n9hGeTIaNJ0trVT2VLNwvTvXt9fW5yBEV1HfSbLU6r81RzF9Mkt78QbudwQFBK+Sml9iml3jRexyqlNiqlThiPMcb1DKVUt1Jqv/HnT8PUN+T9vsp2TvDs5Ag3t2RiZidH0Ge2UNbY6ZT6egfM1Lb1ymEvQniAsfQQ7gGODnp9H7BJa50NbDJe2xRprfOMP98Ypr6R7vc5hUa+Gm8/GzgnyRrQCkfJv+OoymZrwjxvnVcRwpc4FBCUUunAlcCTgy5fDTxnPH8OuGaM7z3R+71KYU0bMaEBJEYEubspEzIrMRw/kxo1IZujKoyAMC1WeghCuJujPYTHgHuBwQPHSVrragDjcfCJ35nG8NKHSqkLhqlzpPvtlFJ3KKV2K6V219cPvZvTGxytbic3OdKrJ5QBggP8yIgLdXpAkB6CEO43akBQSl0F1Gmt9zhYZzUwXWu9GPge8JJSatzjJFrrx7XW+Vrr/IQE7zw20GKxpjjOTfHu+QOb2ckRHKt1TkA41dxFgJ+SPD1CeABHeggrgbVKqVLgZWCVUuoFoFYplQJgPNYBaK17tdaNxvM9QBGQM0S9Q97vi8qbuujuNzMn2bvnD2zmJEdS3tRFbVvPhOuqaO4mNToEP5N395yE8AWjBgSt9f1a63StdQZwE7BZa30LsAFYZxRbB7wBoJRKUEr5Gc9nAtlA8RBVD3m/r+k3W9h6wjrU5Ss9hKvz0jApxRNbh/rPOjYVzV0yXCSEh5jIPoSHgTVKqRPAGuM1wIXAQaXUAeBV4Bta6yYApdSTSqn8Ue73Gb0DZi57bCv/+UYBYYF+ZCf6RkCYHhfK2kWpvLiznObOvgnVdaqpW/YgCOEhxrRTWWu9BdhiPG8EVg9R5h/AP4a5//ZBz4e835dsPlpHcX0nP7piDtcsTvOp4yC/eXEW6/dV8vwnZXx7dfa46ujuM9PQ0Ss9BCE8hOxUdqLNhbU89NYR++t/7K0gMSKIr52fSYKXLzc9W05SBEszYnivYPyJ7l7dWwEw4vGRQojJIwHBiZ7YWsITH5Wwu7SJho5ethyr59rFaT47YXpJbiIFVW3jmlxu6+nn0Y3HOS8zlguy413QOiHEWElAcJLuPrM9vfWftxbzxEfFDFi0Tx9ssirXunXkg0LHF4j1my38YctJvvzEJzR39fGTq+Z6/d4MIXyFBAQn2V3WRJ/ZwpLp0Ww8UsufPyzmusVpXp+7aCSzkyJIjQpm8xgCwp8/LOKRd48B8LO185if5t3J/oTwJRIQnGT7yUYC/BS/vWkxSZFB3LZ8Br+8cZG7m+VSSikuyU1k28kGegfMo5Y/WdfB7zad5IoFybz5rQu4dXmG6xsphHCYnIfgJNtPNrB4WgzTYkP5+L7VmHx03uBsK7LieXFnOSdqO0b9tv/L9woJDjDxwNp5k9Q6IcRYSA/BCVq7+zlc1cqKWXEAUyYYAMwxNtsdqW4bsVxPv5mtxxu4Oi+NxAhJUyGEJ5KA4AQnatvRGhZNweWTM+LCCAnwo7B65NxGu0qb6O43c0mud+ajEmIqmBIB4YVPyvjOy/tcVn9RvfVIyayEcJe9h6fyMylykiM4OkoP4YPCegL9TSyfKUtMhfBUUyIg1Lf38saBKtp6+l1Sf1F9J4H+JtKm6I7buSkRFNa0obUetsyW43UsmxnnU7u1hfA1UyIgnJsZi9bY9wk4W3F9B5lxYT67AW00ucmRNHf1U9vWO+TPyxu7KK7v5OIcGS4SwpNNiYCweHo0/ibFrpIml9RfVN9JVmKYS+r2BrZjQY/WDD1stPFoLXB6I5sQwjNNiYAQGujPvLQodpU6PyD0Dpgpb+qakvMHNrbNd794p5C1v9/2mQyo7xXUMDspgoz4qRs0hfAGUyIgAJybEcOBU6309I++gWosyhu7MFv0lA4IUSEB5CSFU9zQycGKVj48fvqo08aOXnaXNnHZvCQ3tlAI4YgpExCWZsTSZ7ZwsKLVqfVO5RVGg736zRXs+fHniAoJYPvJBvv1TYV1WDRcOi/Zja0TQjhiygSE/IxYAA6canFKfVpr/rGngn8dsY6PZyZM7eGQyOAAIoIDWD4zju0nG+wrjv5VUEtadAjzUn3j+FAhfNmUCQixYYFEBPlT2dLtlPoOVLTyH68c4LW9laRFhxAeJFlAAFZmx1PV2kNpYxe9A2Z2FDWwKjdRMpoK4QWm1KdYanSI0wLCMWNFza9uXESuD2c0HauVWdb0HdtPNjAzPoyuPjMXyXJTIbzCFAsIwVQ5KSAcr+0gOMDEdYvTplTuotFkxoeRGhXM24eqmZ8WRYCfYrkRJIQQnm3KDBmBtYfgvIDQzqzEcAkGZ1FK8bXzM9lR1MhLO8tZmhFLmAynCeEVHA4ISik/pdQ+pdSbxutYpdRGpdQJ4zHGuL5GKbVHKXXIeFw1TH0PKKUqlVL7jT9XOOdXGl5qdAjNXf1090186emJ2g6yE2WoaCjrVmQwKzGcjt4BGS4SwouMpYdwD3B00Ov7gE1a62xgk/EaoAH4gtZ6AbAOeH6EOh/VWucZf94eQ1vGJTXamna5qnVivYS2nn5q2nrITpraS02HE+Bn4mdXzyMuLJDLZLmpEF7DoYCglEoHrgSeHHT5auA54/lzwDUAWut9Wusq43oBEKyUCnJOcycmNcqafG6iw0Ynaq17D3KkhzCsFVnx7PnJGtmdLIQXcbSH8BhwL2AZdC1Ja10NYDwOlajmemCf1nrorGdwt1LqoFLqaduQkyulRjsrIFhz/+ckSUAQQviOUQOCUuoqoE5rvWcsFSul5gG/AL4+TJE/AllAHlAN/HqYeu5QSu1WSu2ur68fqojDkqOCUQqqWnomVI9thVH6FE13LYTwTY70EFYCa5VSpcDLwCql1AtArVIqBcB4rLPdYAwxrQdu01oXDVWp1rpWa23WWluAJ4Bzhyn3uNY6X2udn5AwsQnKAD8TiRFBE+4hHK1uIzsxQlYYCSF8yqgBQWt9v9Y6XWudAdwEbNZa3wJswDppjPH4BoBSKhp4C7hfa719uHptwcRwLXB4XL/BGKVGh0xoUnnAbOFARQtLpk+94zKFEL5tIvsQHgbWKKVOAGuM1wB3A7OAnwxaUpoIoJR6UimVb5R7xFiaehC4BPjuBNrisNSokAkNGR2tbqerz8w5Rm4kIYTwFWPaMaS13gJsMZ43AquHKPMg8A9qrS0AAAYYSURBVOAw998+6PmtY3lvZ0mPCWHj0Vq6+gYIDRz7hqndZdYzFfJnuHwOXAghJtWU2qkM1lO7+gYsvHu4Zlz37y5rJjUq2L5iSQghfMWUCwjnZsYyIy6UV3ZXjPlerTV7SptluEgI4ZOmXEBQSnHDknQ+Lm7kVFPXmO49UddBTVuPDBcJIXzSlAsIANefk45S8Ooex3sJJ2rbufWpnUSFBLB6jhwWL4TwPVMyIKRGh3D+rHhe3VOBxaIduufefxzEbIG/fX0Z6TGhLm6hEEJMvikZEABuOCedypZuPi5uHLVsa3c/B0618OXzppObLEdBCiF805QNCJfNSyYi2J9Xdp8ateynJU1YNKyQg16EED5sygaE4AA/rs5L5Z3DNZysax+x7I6iBoL8TSyW3clCCB82ZQMCwF2XzCIi2J9//8seWrv7hy2342QjSzNiCfL3m8TWCSHE5JrSASElKoQ/3HwOp5q6uPPFPVS3dnPrUzt5eluJvUx9ey/HatvlXGAhhM+b0gEBrBvVHrlhIdtPNnLRL7fw0YkGnvyoGK2tq48+OmFNub1yVrw7mymEEC435QMCwHVL0nngC3NJCA/i1mUzqGrt4WBFKwBvHqwmNSqYhWlRbm6lEEK41tizu/mor6zM5CsrM2np6uOvn5bzbkENGXFhfHSinq+syJCzD4QQPk8CwlmiQwNZnhXHu4drmB4bSr9Zc9XCVHc3SwghXE6GjIZw1cIUSho6uf+1Q0yPDWVhugwXCSF8n/QQhvDF/GmEBfnzaUkT58+KRykZLhJC+D4JCENQSnHVwlQZKhJCTCkyZCSEEAKQgCCEEMIgAUEIIQQgAUEIIYTB4YCglPJTSu1TSr1pvI5VSm1USp0wHmMGlb1fKXVSKXVMKXXZMPUNe78QQojJN5Yewj3A0UGv7wM2aa2zgU3Ga5RSc4GbgHnA5cAflFJDpQkd8n4hhBDu4VBAUEqlA1cCTw66fDXwnPH8OeCaQddf1lr3aq1LgJPAuUNUO9z9Qggh3MDRHsJjwL2AZdC1JK11NYDxaDt5Pg0YfAxZhXHtbMPdL4QQwg1G3ZimlLoKqNNa71FKXexAnUNt63XsJPuh3/8O4A7jZYdS6tg4q4oHGsbbDhfy1HaB57ZN2jU2ntou8Ny2+Vq7ZjhSyJGdyiuBtUqpK4BgIFIp9QJQq5RK0VpXK6VSgDqjfAUwbdD96UDVEPUOd/8ZtNaPA4878suMRCm1W2udP9F6nM1T2wWe2zZp19h4arvAc9s2Vds16pCR1vp+rXW61joD62TxZq31LcAGYJ1RbB3whvF8A3CTUipIKZUJZAOfDlH1cPcLIYRwg4nsQ3gYWKOUOgGsMV6jtS4A/g4cAd4F7tJamwGUUk8qpfJHul8IIYR7jCm5ndZ6C7DFeN4IrB6m3EPAQ0Ncv33Q82Hvd5EJDzu5iKe2Czy3bdKusfHUdoHntm1KtkvZzg4WQggxtUnqCiGEEIAEBCGEEAYJCEIIIQAJCEIIIQwSEIQQQgASEIQYE6XUA0qp74/w82uMjL9CeB0JCP9/e3fMkmUUhnH8fwUagS+0OPQdggQHoQiiXTCqKRKXwO/QFoEfIKKgoXdXEMKloaW9IIIIGsJJoiWLhKbb4RxERHw19IXo/xvPOc/DOdPF8xzOfaTTtQAYCPoneQ5BGiHJQ2CRVsX3O/AO2KYVXZyklXi/D8wAG71vG7jdX/EUmAZ2gAdV9Xmc85eOy0CQjpBkFhgCc7ST/e+B58DLftqeJI+Bb1X1JMkQ2Kiqtd73Bliuqi9J5oCVqro5/pVIo52odIX0H7oOrFfVDkCSV739cg+Ci8AU8Prgg0mmgKvAarJXFf78mc9Y+ksGgjTaYZ/RQ2Chqj4kWQJuHDLmHPCjqmbObmrS6XFTWTraW+BWkgtJBsB8bx8AW0kmgHv7xv/qfVTVT+BrkrsAaa6Mb+rSybiHII2wb1N5k3YB1CfgN+1a2U3gIzCoqqUk14AXwB/gDu3a2WfAJWCCdt/4o7EvQjoGA0GSBPjLSJLUGQiSJMBAkCR1BoIkCTAQJEmdgSBJAgwESVJnIEiSANgF6OKNSjxXiVwAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -1057,22 +2318,669 @@
     }
    ],
    "source": [
-    "sorted_data[-200:].plot()"
+    "fft_data_filtree = np.copy(fft_data)\n",
+    "for i in range(55,75):\n",
+    "    fft_data_filtree[i]=(fft_data_filtree[55]+fft_data_filtree[75])/2\n",
+    "for i in range(110,130):\n",
+    "    fft_data_filtree[i] = (fft_data_filtree[110]+fft_data_filtree[130])/2\n",
+    "for i in range(675,690):\n",
+    "    fft_data_filtree[i]=(fft_data_filtree[675]+fft_data_filtree[690])/2\n",
+    "for i in range(610,630):\n",
+    "    fft_data_filtree[i]=(fft_data_filtree[610]+fft_data_filtree[630])/2\n",
+    "    \n",
+    "    \n",
+    "mod_fft_data_filtree = np.abs(fft_data_filtree)\n",
+    "plt.plot(mod_fft_data_filtree)\n",
+    "axes = plt.gca()\n",
+    "#axes.set_xlim(0, 200)\n",
+    "axes.set_ylim(0, 4000)\n",
+    "plt.grid()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 72,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>CO2_concentration_moyenne_mensuelle</th>\n",
+       "      <th>year</th>\n",
+       "      <th>month</th>\n",
+       "      <th>filtered_data</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1958-3</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>3</td>\n",
+       "      <td>312.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1958-4</td>\n",
+       "      <td>317.26</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>4</td>\n",
+       "      <td>315.57</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1958-5</td>\n",
+       "      <td>317.50</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>5</td>\n",
+       "      <td>318.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1958-7</td>\n",
+       "      <td>315.69</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>7</td>\n",
+       "      <td>318.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1958-8</td>\n",
+       "      <td>314.99</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "      <td>318.58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1958-9</td>\n",
+       "      <td>313.54</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>9</td>\n",
+       "      <td>316.32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1958-11</td>\n",
+       "      <td>313.47</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "      <td>314.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1958-12</td>\n",
+       "      <td>314.74</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "      <td>315.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1959-1</td>\n",
+       "      <td>315.54</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "      <td>315.71</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1959-2</td>\n",
+       "      <td>316.72</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>2</td>\n",
+       "      <td>316.19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1959-3</td>\n",
+       "      <td>316.75</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>3</td>\n",
+       "      <td>314.88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1959-4</td>\n",
+       "      <td>317.70</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>4</td>\n",
+       "      <td>314.34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1959-5</td>\n",
+       "      <td>318.38</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>5</td>\n",
+       "      <td>314.49</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1959-6</td>\n",
+       "      <td>318.08</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>6</td>\n",
+       "      <td>315.38</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1959-7</td>\n",
+       "      <td>316.58</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>7</td>\n",
+       "      <td>316.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1959-8</td>\n",
+       "      <td>314.92</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>8</td>\n",
+       "      <td>317.24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1959-9</td>\n",
+       "      <td>313.87</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>9</td>\n",
+       "      <td>317.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1959-10</td>\n",
+       "      <td>313.44</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>10</td>\n",
+       "      <td>316.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1959-11</td>\n",
+       "      <td>314.90</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>11</td>\n",
+       "      <td>316.93</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1959-12</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>1959</td>\n",
+       "      <td>12</td>\n",
+       "      <td>316.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1960-1</td>\n",
+       "      <td>316.42</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1</td>\n",
+       "      <td>316.95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1960-2</td>\n",
+       "      <td>317.00</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>2</td>\n",
+       "      <td>316.89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1960-3</td>\n",
+       "      <td>317.64</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>3</td>\n",
+       "      <td>316.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1960-4</td>\n",
+       "      <td>319.15</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>4</td>\n",
+       "      <td>316.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1960-5</td>\n",
+       "      <td>319.97</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>5</td>\n",
+       "      <td>316.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1960-6</td>\n",
+       "      <td>319.51</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>6</td>\n",
+       "      <td>316.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1960-7</td>\n",
+       "      <td>318.09</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>7</td>\n",
+       "      <td>317.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>1960-8</td>\n",
+       "      <td>315.80</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>8</td>\n",
+       "      <td>317.38</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1960-9</td>\n",
+       "      <td>314.23</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>9</td>\n",
+       "      <td>317.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1960-10</td>\n",
+       "      <td>313.88</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>10</td>\n",
+       "      <td>317.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>712</th>\n",
+       "      <td>2017-12</td>\n",
+       "      <td>406.76</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>12</td>\n",
+       "      <td>407.10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>713</th>\n",
+       "      <td>2018-1</td>\n",
+       "      <td>408.09</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>1</td>\n",
+       "      <td>407.51</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>714</th>\n",
+       "      <td>2018-2</td>\n",
+       "      <td>408.30</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>2</td>\n",
+       "      <td>407.17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>715</th>\n",
+       "      <td>2018-3</td>\n",
+       "      <td>409.30</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>3</td>\n",
+       "      <td>407.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>716</th>\n",
+       "      <td>2018-4</td>\n",
+       "      <td>410.36</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>4</td>\n",
+       "      <td>407.56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>717</th>\n",
+       "      <td>2018-5</td>\n",
+       "      <td>411.15</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>5</td>\n",
+       "      <td>407.95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>718</th>\n",
+       "      <td>2018-6</td>\n",
+       "      <td>410.79</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>6</td>\n",
+       "      <td>408.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>719</th>\n",
+       "      <td>2018-7</td>\n",
+       "      <td>408.73</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>7</td>\n",
+       "      <td>408.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>720</th>\n",
+       "      <td>2018-8</td>\n",
+       "      <td>407.08</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>8</td>\n",
+       "      <td>409.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>721</th>\n",
+       "      <td>2018-9</td>\n",
+       "      <td>405.69</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>9</td>\n",
+       "      <td>409.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722</th>\n",
+       "      <td>2018-10</td>\n",
+       "      <td>406.10</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>10</td>\n",
+       "      <td>409.52</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>723</th>\n",
+       "      <td>2018-11</td>\n",
+       "      <td>408.02</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>11</td>\n",
+       "      <td>410.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>724</th>\n",
+       "      <td>2018-12</td>\n",
+       "      <td>409.21</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>12</td>\n",
+       "      <td>409.84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>725</th>\n",
+       "      <td>2019-1</td>\n",
+       "      <td>410.82</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>1</td>\n",
+       "      <td>410.53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>726</th>\n",
+       "      <td>2019-2</td>\n",
+       "      <td>411.58</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>2</td>\n",
+       "      <td>410.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>727</th>\n",
+       "      <td>2019-3</td>\n",
+       "      <td>412.06</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>3</td>\n",
+       "      <td>410.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>728</th>\n",
+       "      <td>2019-4</td>\n",
+       "      <td>413.55</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>4</td>\n",
+       "      <td>410.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>729</th>\n",
+       "      <td>2019-5</td>\n",
+       "      <td>414.78</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>5</td>\n",
+       "      <td>411.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>730</th>\n",
+       "      <td>2019-6</td>\n",
+       "      <td>413.91</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>6</td>\n",
+       "      <td>411.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>731</th>\n",
+       "      <td>2019-7</td>\n",
+       "      <td>411.77</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>7</td>\n",
+       "      <td>411.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>732</th>\n",
+       "      <td>2019-8</td>\n",
+       "      <td>409.97</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>8</td>\n",
+       "      <td>411.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>733</th>\n",
+       "      <td>2019-9</td>\n",
+       "      <td>408.55</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>9</td>\n",
+       "      <td>411.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>734</th>\n",
+       "      <td>2019-10</td>\n",
+       "      <td>408.51</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>10</td>\n",
+       "      <td>412.02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>735</th>\n",
+       "      <td>2019-11</td>\n",
+       "      <td>410.33</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "      <td>412.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>736</th>\n",
+       "      <td>2019-12</td>\n",
+       "      <td>411.96</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "      <td>412.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>737</th>\n",
+       "      <td>2020-1</td>\n",
+       "      <td>413.31</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>413.47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>738</th>\n",
+       "      <td>2020-2</td>\n",
+       "      <td>414.14</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "      <td>413.78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>739</th>\n",
+       "      <td>2020-3</td>\n",
+       "      <td>414.62</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "      <td>413.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>740</th>\n",
+       "      <td>2020-4</td>\n",
+       "      <td>416.14</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "      <td>413.72</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>741</th>\n",
+       "      <td>2020-5</td>\n",
+       "      <td>417.08</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "      <td>413.58</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>742 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        date  CO2_concentration_moyenne_mensuelle  year  month  filtered_data\n",
+       "0     1958-3                               316.19  1958      3         312.80\n",
+       "1     1958-4                               317.26  1958      4         315.57\n",
+       "2     1958-5                               317.50  1958      5         318.40\n",
+       "3     1958-7                               315.69  1958      7         318.69\n",
+       "4     1958-8                               314.99  1958      8         318.58\n",
+       "5     1958-9                               313.54  1958      9         316.32\n",
+       "6    1958-11                               313.47  1958     11         314.99\n",
+       "7    1958-12                               314.74  1958     12         315.39\n",
+       "8     1959-1                               315.54  1959      1         315.71\n",
+       "9     1959-2                               316.72  1959      2         316.19\n",
+       "10    1959-3                               316.75  1959      3         314.88\n",
+       "11    1959-4                               317.70  1959      4         314.34\n",
+       "12    1959-5                               318.38  1959      5         314.49\n",
+       "13    1959-6                               318.08  1959      6         315.38\n",
+       "14    1959-7                               316.58  1959      7         316.40\n",
+       "15    1959-8                               314.92  1959      8         317.24\n",
+       "16    1959-9                               313.87  1959      9         317.39\n",
+       "17   1959-10                               313.44  1959     10         316.61\n",
+       "18   1959-11                               314.90  1959     11         316.93\n",
+       "19   1959-12                               315.58  1959     12         316.65\n",
+       "20    1960-1                               316.42  1960      1         316.95\n",
+       "21    1960-2                               317.00  1960      2         316.89\n",
+       "22    1960-3                               317.64  1960      3         316.26\n",
+       "23    1960-4                               319.15  1960      4         316.15\n",
+       "24    1960-5                               319.97  1960      5         316.03\n",
+       "25    1960-6                               319.51  1960      6         316.25\n",
+       "26    1960-7                               318.09  1960      7         317.05\n",
+       "27    1960-8                               315.80  1960      8         317.38\n",
+       "28    1960-9                               314.23  1960      9         317.46\n",
+       "29   1960-10                               313.88  1960     10         317.22\n",
+       "..       ...                                  ...   ...    ...            ...\n",
+       "712  2017-12                               406.76  2017     12         407.10\n",
+       "713   2018-1                               408.09  2018      1         407.51\n",
+       "714   2018-2                               408.30  2018      2         407.17\n",
+       "715   2018-3                               409.30  2018      3         407.43\n",
+       "716   2018-4                               410.36  2018      4         407.56\n",
+       "717   2018-5                               411.15  2018      5         407.95\n",
+       "718   2018-6                               410.79  2018      6         408.48\n",
+       "719   2018-7                               408.73  2018      7         408.60\n",
+       "720   2018-8                               407.08  2018      8         409.37\n",
+       "721   2018-9                               405.69  2018      9         409.36\n",
+       "722  2018-10                               406.10  2018     10         409.52\n",
+       "723  2018-11                               408.02  2018     11         410.09\n",
+       "724  2018-12                               409.21  2018     12         409.84\n",
+       "725   2019-1                               410.82  2019      1         410.53\n",
+       "726   2019-2                               411.58  2019      2         410.70\n",
+       "727   2019-3                               412.06  2019      3         410.37\n",
+       "728   2019-4                               413.55  2019      4         410.80\n",
+       "729   2019-5                               414.78  2019      5         411.39\n",
+       "730   2019-6                               413.91  2019      6         411.16\n",
+       "731   2019-7                               411.77  2019      7         411.05\n",
+       "732   2019-8                               409.97  2019      8         411.76\n",
+       "733   2019-9                               408.55  2019      9         411.99\n",
+       "734  2019-10                               408.51  2019     10         412.02\n",
+       "735  2019-11                               410.33  2019     11         412.70\n",
+       "736  2019-12                               411.96  2019     12         412.99\n",
+       "737   2020-1                               413.31  2020      1         413.47\n",
+       "738   2020-2                               414.14  2020      2         413.78\n",
+       "739   2020-3                               414.62  2020      3         413.46\n",
+       "740   2020-4                               416.14  2020      4         413.72\n",
+       "741   2020-5                               417.08  2020      5         413.58\n",
+       "\n",
+       "[742 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "filtered_data = np.fft.ifft(fft_data_filtree)\n",
+    "Monthly_data['filtered_data'] = np.around(np.abs(filtered_data[0:len(filtered_data)]),decimals=2)\n",
+    "Monthly_data"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 102,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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47xeN5ciRIyoqKmryf34RjAKs0Yt7E724N9GJ+xK9msO9+eMfpXvvlT77TOrZs6lHE8zzvOXOufCzPwH4N1m0CC+88ILGjBmjBx54gAAHAADQQr3/vjRoUPQFuLpiY5MzZP/+/Zo8eXK187NmzYq48UlLNGbMmGq7JL744osaPnz4aV/z5ptv1s0331zfodXZs88+W20p7IQJE/TEE0+c8bEAAAC0ZEeOSHPnSj/+cVOPpP6iOsTVdufG5qB79+713uiipViyZElTD6HB3HbbbUHP4LUE0bBEGwAAoKrZs6WSEunSS5t6JPUXtevK2rVrp/379/MvhEAz4pzToUOH1K5du6YeCgAAQJC5c6V27aQJE5p6JPUXtTNx/fv3V1FRkfbt29dkYzhx4gT/MhqluDfR6+jRo8rIyGjqYQAAAARZs0ZKS5PatGnqkdRf1Ia42NhYJSQkNOkYcnJylJWV1aRjQGjcm+iVk5Oj2NjYph4GAABAkLVrz46llFIUL6cEAAAAgIawd6+0Z4+Unt7UI2kYhDgAAAAAzdKuXVJtnr5au9baemx2HlWidjklAAAAAERy5ZVS167SrFmR+61ebS0hDgAAAACayOHD0sqVkudJX3wh9egRut+pU9KTT0rDhkm9e5/ZMTYWllMCAAAAaHZycyXnpPJy6b33wvd7+mlp82bpoYfO3NgaGyEOAAAAQLOzeLG1vXpJ774bvt8LL0gjRkjTpp2ZcZ0JhDgAAAAAzc7ixdLgwVa8e8OG0H127JCWLZNuuMGWXZ4tCHEAAAAAmp3ly6XRo6X4eGnbNltaWdXbb1t73XVncmSNj41NAAAAADQrX3xh5QUyMqTWraWjR6X9+6tvbvLpp1JyspSS0jTjbCzMxAEAAABoVtassTY93WbiJGnr1ur9cnOl7OwzNqwzhhAHAAAAoFkJFeK2bQvus2+ftHPn2RniWE4JAAAAoFlZvdpqvvXqJbVrZ+eqhrjly60dOfKMDu2MYCYOAAAAQLPhnLR0qc3CSVLnztK554YPcVlZZ3R4ZwQhDgAAAECz8Y9/SOvXS1/9qv9cfHz1Z+LWrJESE6UuXc7o8M4IQhwAAACAZsE56Re/kIYPl267zX8+KUnatCm4b36+NGTImR3fmUKIAwAAANDknLNZtkOHwvdZskQqLJTuuktq1cp/PjVV2rJFKimx47Iy6zd4cOOOuakQ4gAAAAA0ucWLpRtukG66SSovD93n5Zeltm2la64JPp+aasHNt6Ryxw7pxAlCHAAAAAA0mldftfaf/5TeeCN0n7ffli6/vPpzbqmp1hYUWJufby0hDgAAAAAaQVmZBbfp06XWra2EQFUHDkhFRdK4cdXf84W4wkJrCXEAAAAA0Ihyc6XPP5e+9jVpwAB7vq2qvDxr09Kqv3fuuVKPHsEhrnt3O3c2IsQBAAAAaHC7d0vPPmsbltRk1ixrL7nEygJULRcgRQ5xks3G+Wbg8vPP3lk4iRAHAAAAoBE89pj0rW9ZYe6azJplxbt79pQSEsLPxHXqJMXFhb7GsGHS2rUWGgsKCHEAAAAAUCc5OdY+91zkfsePSwsWSJMn23FiovTFF1JxcXC/9euloUMlzwt9ncxM6csvrcj3nj2EOAAAAACoteJiadkyq+X26qvSyZPh+y5caO/7QlxCgrWBSyqdk9atC7+UUpKysqx95RVrCXEAAAAAUEsLFtiOkzffLB08KG3aFL7vrFm2I+WFF9pxYqK1gUsqt22T9u6VRo0Kf53hw22WzleqgBAHAAAAALW0aJEUE2MhTqo5xI0eLZ1zjh37Qtzmzf4+CxdaO358+Ot07CgNGiRt325hLj7+tIcf9QhxAAAAABpUfr6FqPR0Ow4MZIF277byAr6llJK/NIBvp0nJQmGnTrZ5SSTTp1s7dqzN7p2tCHEAAAAAGpRvi/9zz5W6dQs9E7d/vz9sXXdd8HtDh9pGJj4LF0pjxtgzdpE8+KB06JA0Z079f0M0I8QBAAAAaDDl5VZ02/dMWlJS6Jm4jz+2pY8zZ0oZGcHv+UKcc1JJiZUOiPQ8XKDOnaW2bev3G6IdIQ4AAABARPfea/XZfvKTmvvu3GllA3whLjk59Excbq6FrUmTqr83ZIiVC9izR9qxQyottefdYAhxAAAAACJ6802pqMgKeBcVRe7re5bNF7qSkmzGraQkuF9urtV2i42tfo2hQ63dsMEfAJOTT3/8ZxtCHAAAAICwnJN27ZKuucZeP/lk5P5r11obOBNXVmZBzqe8XFq+XMrODn0NX4jLy/OHuKSk0/8NZxtCHAAAAICwjhyRjh617f0nTpQ+/DBy30cesefXeva0c77wFfhcXGGhFQQPF+LOO892qVy92kJchw5Snz4N8nPOCoQ4AAAAAGHt2mVt375SQoL/OJTf/tbe//OfrVab5F8GGfhc3OrV1mZmhr6O50kjRkgrVtjnkpP91wMhDgAAAEAEgSGuXz/bbKTq822StGNHez3yiHTbbVYOwKdPH5tJC5yJy8uzYuC+JZehZGVJ69bZLpU8DxeMEAcAAAAgLF+IO+88C3HOWZHuqt55p59at5Z+97vg855nSyoDZ+LWrbNg1q5d+O8dMUI6dUrasoWdKasixAEAAAAIK3Amrm9fe/3ZZ9X7bdrUSZmZUu/e1d+rGuLy8qRhwyJ/74gR/tff+17dxny2I8QBAAAACOvzz6VOnaRzzrGZOKn6c3HOSVu3dtTw4aGvkZxsM2rl5dKJExbo0tIif29SkjR1qvTyy1ajDn6tm3oAAAAAAKLXrl3+GThfiKs6E7drl3TkSGzYEJeUJJ08aZ/bv9/CXE0hLiZG+uCD+o39bEWIAwAAABDWZ5/5Q1yPHlacu2qIW7PG2vT00NfwbUyyebO0Y4e9Dhf4UDOWUwIAAAAI6eBBKTfXH7hiYmyDk6rLKX0FviPNxEm2jHLlSql9ezYrqQ9CHAAAAICQ/vEPWwb5zW/6z/XrV30mbtEiqU+f4+rWLfR14uJsBm/zZqv9lpEhtWrVeOM+2xHiAAAAgBYoPz90vbdAM2ZYLbfsbP+5/v2lnTv9xyUl0qxZ0qhRX4a9TuvWUny8tHGjtGqV1YDD6SPEAQAAAC1MXp5tLPL00+H7lJdLS5dK06ZZrTefgQPtuTbn7HjRIunIEWn06AMRvzM5Wfr4Y+nwYUJcfRHiAAAAgBbmsccspM2bF77P1q3SsWPVn3MbMMCWWO7da8cffmgzbVlZ4WfiJHsu7vBhez1qVD0GD0IcAAAA0JIcPiy99JK9Xrw4fD/fZiVVi3IPHGitb5fJdetsk5KOHcsifm+fPtaOGSNlZtZx0AhCiAMAAABakHXrpOPHpcmTpe3brZh3uH5S9XpuAwZYu327tVu3SomJNX/vFVdYCQJfgMTpI8QBAAAALUh+vrW33mptuNm4tWstnHXsGHw+cCbOOQtxCQk1f29GhrR6tb9mHE4fIQ4AAABoQQoKpDZtpGuusTZUiHPO6rlVXUopSV27Sp062Uzc/v1ScXHtQhwaDiEOAAAAaEHy86WUFJthy8oKHeJWr7ZyAFOnVn/P8/w7VG7daucIcWcWIQ4AAABoQfLzrfabJI0dKy1bJpWWBvd54QWbpbvxxtDXGDjQCncT4poGIQ4AAABo5pYts8B1/HjkfqdOWfgKDHHHj/t3ovR54w3p8sulc88NfZ0xY2zjk9xcOybEnVmEOAAAAKAZKy+Xvvc96bXXpFdfjdy3sFAqKwsOcVLwksovvpCKiqQJE8Jf5ytfsefmXnhB6t5dOuec+v0G1A0hDgAAAGjG3nlHWr5c6tBB+stfLFyFs2yZtdnZ1g4cKLVtK23Z4u/jm5WrWuQ70KhRtrnJnj3SDTfUb/yoO0IcAAAA0IwtWmRB7Le/lVas8D+nFsqyZVLnzlJqqh17ntSvn/TZZ/4+tQlxsbFWZ65bN+k3v6n/b0DdtG7qAQAAAAA4fYWFVnstK8uOIxXfXrrUZuFiAqZy+vaVdu3yH69da0sk+/SJ/L1PPy0dOSL16FG/8aPuaj0T53leK8/zVnqe927F8bme533sed7GirZbQN97Pc/b5Hleged5ITYmBQAAANAQNm60mbX4eDveti10v5MnpTVrbClkoFAzccOH2yxdJL16SUlJpztq1EddllP+SNKGgOOfSZrlnEuRNKviWJ7nDZV0o6Q0SdMkPel5XquGGS4AAAAAn7IyadMmC3H9+0utWoUPcS+/LJWUSBdcEHy+b18Lcc7Zn/XrpbS0Rh866qFWIc7zvP6SLpf0PwGnr5L0fMXr5yVdHXD+VefcSefcVkmbJI1umOECAAAAZ7+PP5befbfmfjt2WNmAlBSpdWsLcqFC3OHD0j33SOPHS5deGvxev35WZuDQIWnfPlsimZLSID8DjaS2z8Q9KumnkgI3D+3tnPtckpxzn3ue16vifD9JgXXfiyrOBfE873ZJt0tS7969lZOTU7eRnwHFxcVROS5wb6IZ9yY6cV+iF/cmenFvolNLuS/f//5IHT4cq1dfXRyx39Kl3SRl6OjRlcrJOaSuXTO1erWUk7MqqN+8eT20b98w/cd/rNLcuQeD3jt0qJekoXr77aU6dqy1pBE6dmyNcnIO1GnMLeXeRIMaQ5zneVdI2uucW+553sRaXDPU6tlqG506556W9LQkZWdnu4kTa3PpMysnJ0fROC5wb6IZ9yY6cV+iF/cmenFvolNLuC+lpTbDdvKklJAwUQMHhu+7Zo21X/1qlvr0kTIzpVmzVO1/o3fekdq1k+64I1Nt2gRfIybGdpjs33+0du+2c9dck15ZS662WsK9iRa1WU45QdJ0z/O2SXpV0iTP816StMfzvPMkqaLdW9G/SFJcwOf7SwrY7wYAAABAOJs2WYCTpLlzI/f17STZu7cdx8fb822nTgX3mzfPCntXDXCSLaeU7HObN9uGJgkJ9foJaGQ1hjjn3L3Ouf7OuXjZhiWznXPfkDRT0i0V3W6R9E7F65mSbvQ8r63neQmSUiQtbfCRAwAAAGchX502qeYQt2aNlJ7u30kyPt42J9mxw9/n8GFp5crqG5r49O1r7c6dFuLi4qzuHKJXfYp9/17SJZ7nbZR0ScWxnHN5kl6XtF7SB5K+75wrq+9AAQAAgJZg7Vpb4jhpkhXyDqesTFq3TsrI8J9LTrZ20yb/udxcqbxcmjAh9HXat5cGDpTy8uxzlA2IfnUKcc65HOfcFRWv9zvnJjvnUiraAwH9HnDOJTnnBjnn3m/oQQMAAABnq7VrbXfI0aOlgoLqSyN9Nm+Wjh2zmTgfX4jbuNF/bt06awPDXlVZWTZbt3EjIa45qM9MHAAAAIAG5Jy0cKGUnW212kpLgwNZoBUrrA0MZ717S506Bc/ErVsnnXuu/7m5ULKypMJCaf9+K0OA6EaIAwAAAKJEfr60d6908cX+gtt5edX7vfWW9M1vWjgbOtR/3vNsFi8w+OXlScOG+Z+bCyUz09qYGOmKK+r/O9C4CHEAAABAlJgzx9qLL5YGD7ZQFSrEPf20bUCydKmVDgiUnOwPcc7ZTNywYZG/NyvL2vHjpZ496/cb0PgIcQAAAECUmDPHwllCgm04kpRUPcQdPy59+qk0fXro59dSUqStW6WSEqmoyHanrCnE9e8vXXml9MMfNtxvQeOpsdg3AAAAgMb32WfSzJnSv/6rf+ljWpq0fn1wv/nzpRMnpKlTQ18nOdl2rty2zTY/8V0nEs+z70bzwEwcAAAA0IiKi6W77rLn3SL54x8tfP3kJ/5zKSnSli1WIsBn9mwpNla68MLQ1xkyxNr8fP/OlDWFODQvzMQBAAAAjaS8XLr6amnWLNuw5KWXQvdzTnrlFemaa2wppU9ysnTypM3SxcXZuXXrpEGDpI4dQ1/LF+Ly8izInXee1L17w/0mND1m4gAAAIBGsnWrBTjJlkE6F77f7t3S5MnB50MV796wwR/UQunSRerXz5Zh1mZTEzQ/hDgAAACgkWzZYu3XviZt3x4cxgLNn2/thAnB56uGuBMnLPBFCnGSlR1Yt86CHCHu7EOIAwAAABqJL8T9279Z+/HHofstWGAzaFWfXevfX2rb1h/iCgttiWZNIS4tTVq50nay5Hlmgl9vAAAgAElEQVS4sw8hDgAAAGgkW7dKbdrYJiQ9e0q5uaH7LVwojRtndeECxcRIiYn+ELdhg7W1mYnzGTfu9MaO6EWIAwAAABrJli1SfLzUqpWUkSGtXl29z/HjtuwxOzv0NZKTg0Oc50mpqZG/98orpa9/XZo3LzjQ4exAiAMAAAAayZYt/t0mMzNtx8jS0uA+a9faEsmsrNDX8IU45+w5t6QkKwQeSZ8+0ssvS+efX//fgOhDiAMAAAAayZYtthxSspm4kyelgoLgPitXWhspxB07ZrtXrl5t10HLRogDAAAAGsGXX9of30ycL3xVXVK5cqXUtastuwzFt0PlqlXS5s2EOBDiAAAAgDrJy5Ouv146dChyv6VLrfWFrsGDpdhYWz4ZaOVKW2rpeaGvk5Rk7f/+ry2pTE8//bHj7ECIAwAAAOrgySelN9+UHn44cr9582xDk/Hj7Tg21gJZ4HLK0lJpzZrwSyklaeBAqXVr6a237JiZOBDiAAAAgFoqL5feftte/+lP0v794fvOnSuNHCl16uQ/N2hQcIgrKLAC3pFCXOvWFuS++MJqyQ0cWL/fgOaPEAcAAADU0pIl0uefS3fcYaUB5s0L3W//fut74YXB5wcNsp0my8rsuKZNTXyKi6392c/CL7tEy0GIAwAAQIv2+uvSX/9au75vvWXLIu+7z9pFi6r3KS72F9i+/vrg9wYNkk6dkrZts+OVK6V27ex5uUgefFC65Rbp7rtrN06c3QhxAAAAaLHKy6Wf/ET66U+lkpLIfZ2zEPeVr0i9ekkjRoQOcfPmSRs3Wp22MWOC3xs0yFrfksqVK6Xhw23JZCS33CI995w9YwcQ4gAAANBiLVkiFRVJhw/b60hWr7a6b9dea8fjxkm5udXD39KlUkyMNHVq9WsEhjjnLMTVtJQSqIoQBwAAgBbrjTdsWWSrVtIHH0Tu+8ILNmM2fbodjxljz8Vt2BDcb+lSaciQ4A1NfHr0kHr2tDID27dLBw8S4lB3hDgAAAC0WLNmSRMnWiD75JPw/Y4ckZ55xp5x69XLziUmWrt9u7+fcxbiRo8Of62sLJuBq+2mJkBVhDgAAAC0SMeOWeHuMWOsFMD69RbCQnn+eVty+aMf+c/FxVm7c6f/3LZtVgpg1Kjw3ztihLRunS3fjImxZ+KAuiDEAQAAoEVaudK2+h81SkpOttm2ffuq9ysvlx5/3GbXxo71n+/d25Zi7tjhP7dmjbWRZtdGjLAi3y++aLtSdujQML8HLUcN++AAAAAAZ6dly6wdNcq/O+SmTf7lkj4ffmi7Tc6YEXw+Jkbq3z94Ji4vz9qhQ8N/74gR1u7aJU2adPrjR8vFTBwAAABapGXLpH79pPPOs5k4yUJcVR98IHXsWL3mm2RLKquGuLg4qXPn8N+bmCgNGGDf+8tf1u83oGViJg4AAAAtTmmp9NFHVvNNkuLjbWYtVIhbs8aeW2vTpvp7cXHSggX+47w8KS0t8nd7nj1/164ddd9wepiJAwAAQIsze7ZtQPK1r9lxmzbSwIHVQ5xzFuLS00NfJy7O6syVldmf/PyaQ5xkM3sEOJwuZuIAAABwVjlxQmrb1ma8wnntNVvyOG2a/1xycvUQt2uXdOBA+BA3YIDN6u3ZIxUXSydP1i7EAfXBTBwAAADOGvv22XNuDz0Uud+8edLkybak0SdUiPPtNpmREfo68fHWFhZKubn2OjOzzsMG6oQQBwAAgLPGn/5kM2cPPywdPRq6z4kT0ubN1euzJSdLX35pn/dZtcraYcNCX2vsWHuWLifH6r61b0/dNzQ+QhwAAADOCsXF0hNP2KzZ/v1WoDuUwkKr/TZkSPD5UDtUzp1r/bp2DX2tbt2sZMCsWRbisrP95QqAxkKIAwAAwFnhgw+sYPejj9omJfPmhe63YYO1VWu5VQ1xJSV2jYsvjvy9kyZJ8+dbiBsz5vTHD9QWIQ4AAABnhbfeknr0kM4/X8rKklasCN1v/XpbApmaGnw+MdE2Q/GFuNxcW5JZU4i76ir/67FjT3/8QG0R4gAAANDsnTolvfuuBarWrS3EbdxoSyyrWr/eAlvgpiaSHcfF+UNcTo61F10U+bvHj7fA+PTT0vTp9f4pQI0IcQAAAIhax4/bDFt5eeR+69fbUkpf8e4RI6zG2+rV1fuuWhV+o5LAHSqXL7fjnj1rHmdWlvSv/yrFxtbcF6gvQhwAAACi1t/+Jl13ne06GUnVUgBZWdZWXVK5a5eFtPPPD32dlBR7Zs4XAMOVFgCaEiEOAAAAUWvjRmt/+1vb/j+cNWuswHdKih337Sude67N0AX69FNrwy2RzMiQDh60z23eTM03RCdCHAAAAKKWb4bt0CFp6dLI/YYN82/v73lSUpIFsUCffip17hw+nPnOv/SSzcYxE4doRIgDAABAVPItabzuOjv2lQYIZfVqKT09+FxSUnDNN8lKBkyYEL6W2/DhFgB9NeYIcYhGhDgAAABEpR07bAZu8mRbGhkuxOXnS3v3Vg9cSUl2jZISOz5yxK4RqQxAp05WY+7zz6U+fWy3SiDaEOIAAAAQlXw7S2ZkSEOGhA9x990ndewo3Xhj8PnkZKmsTNq+3Y5XrLDZvezsyN/bvbu1Tzxhs3JAtCHEAQAAICrNnSu1aWPPqYULcUVF0uuvSz/6kdS7d/B7SUnW+p6LW7bM2lGjIn/vM8/Ycsprr63f+IHGQogDAADAGTFzpjR1qnT33bXrP2uWPb/WoYOFuC++kA4dCi7EtnKltZdfXv3zVUNcbq4tlayp7ltGhnTzzbUbI9AUCHEAAAA4I/7wB+mjj6xdtSpy3337rM/kyXY8ZIi1O3a0D+q3bp21oYp3n3eeBUBfmYIVK6SRI+vxA4AoQYgDAADAGVFQYDtNdu4s/e534fudPCn953/a6698xdr4eGt3724X1HfdOmnAALtmVZ4npaVZ+YGTJ21GLlTYA5qbMJurAgAAAA3n4EHbQXL0aFvO+NJLUnm5FBNiSuG//kt66inp3/7N//zawIHW7tkTHOLWrrWyAOFkZkpvvmmzceXl0qBBDfSDgCbETBwAAAAanW9JY2qqlJUlFRf7d40MdOyY7Qp51VUW5Hwhr0MHqVev4Jm4khIrLxBpdi0jQzpwwJ6vk6TBgxvoBwFNiBAHAACA03b8uM1w1aSgwNpBg/wzZ2vXVu/3+uvS/v3ST35S/b2BA4Nn4jZssCBX00ycJL36qrWpqTWPFYh2hDgAAACclgMHLFg9+GDNfQsLbVYtMdE/cxYqxC1ebIW9zz+/+nvx8cEhbsECayMV705P9183Ls6KeQPNHSEOAAAAp+WPf7RdJP/+dyuiHUlBgYWwtm2lc86REhJCh7jVqy14hSqybTNxbSu/a8ECqw2XmBj+e885R5o0yf8aOBsQ4gAAAFBnJSXS449L3btLmzb567WFUlpqz6SNGeM/N3y47RoZqLzcgp1v9qyq+Hjp1KlW2rPHjhcssBm7UIEv0JtvSlOmSN//fo0/C2gWCHEAAACos82bbXOSX/xCatVK+t//Dd937lx7zu266/znUlKkrVuDZ/C2bpWOHo0c4iQLjbt2Sdu2WTHwmnTtKn34oXTHHTX3BZoDSgwAAACgznwblYwbZ8sZ8/PD933rLal9e2naNP+5uDjpxAkLdz162LnVq60NF+LGjJE8z2n2bE+ff27nahPigLMNIQ4AAAB1FrjbZFKSzcyFM2eOdPHFUseO/nNxcdbu3OkPcatW2eYnaWmhr9OjhzRkyGG9914X7d9vwTArq/6/BWhuWE4JAACAOisosLptXbvaTNzmzaE3Nzl2zGbpsrODzweGOJ/cXGnoUKsJF86YMQe0bJn09ttWODw2tv6/BWhuCHEAAACos4ICf+HspCTp0CErOVDVmjW2YUnVGbOqIc45C3GjRkX+3gsu2Cfn7HPjx9fvNwDNFSEOAAAAdVZQYEspJQtxUugllb5dK6uGuF69bBbNF+J27rRyBVVn7KpKSDimv/7VXgc+Ywe0JIQ4AAAA1MnatdIXX1iZAClyiFuxwop3DxgQfD4mRurXzx/ili2ztqaZOEm6/XbbGfPCC09v/EBzR4gDAACASkule+6xgtp33SWVlYXv++ijtqnITTfZsa/YdtUQV1Zm9eFGjQpdyy0uzh/icnNtZi7czpRVBW6SArQ0hDgAAADo9delhx6SevaUHnlE+uST0P127ZJmzJBuvtkKfUu2EUm/flJhYXDft96y2m+33x76WnFx0o4d9jo312b22rZtmN8DnM0IcQAAAFBurtSunfT++3a8Zk3ofv/1XzbDdvfdweeHDpXy8oLPPfmklJwsXXVV6GtlZUnbt9uf2mxqAsAQ4gAAAKDVq20mrGdPqX9/f+HtQF9+KT39tPStb/mfg/MZNkzasMF2opSsXbpUuuwyqVWr0N95xRXWPv64dPBgzZuaADCEOAAAgBbOOQttGRl2nJ4eeiZu+XKppES64Ybq76WlSceP2/JJyZ6PO3Ys8jNuvkLhjz1mx8zEAbVDiAMAAGjhPvtM2r/fH+IyMmxW7dSp4H7hygVIFuIkad06a30zeb5rhuJ50vXX2/LMLl1sSSaAmtUY4jzPa+d53lLP81Z7npfned6vKs5nep632PO8VZ7n5XqeNzrgM/d6nrfJ87wCz/OmNuYPAAAAQHX79tlza7/9bc19fYErM9Pa9HTbrXLDhuB+K1ZYqQDfhiaBfAHM91zc6tVWRsAX7sJ54AH7zNq1tjslgJq1rkWfk5ImOeeKPc+LlTTf87z3Jf1a0q+cc+97nneZpIckTfQ8b6ikGyWlSeor6RPP81KdcxE2qgUAAEBDuusu6aWX7PWPfyx16hS+7/z5UuvW/hA3ZIi1GzcGz6StXBl6Fk6SOne23SZ9IW7NGlsu2b595HG2asUMHFBXNc7EOVNccRhb8cdV/Olccb6LpF0Vr6+S9Kpz7qRzbqukTZJGCwAAAGfM6tX+7foXLIjcd9YsaexYf9ALVfft6FErIRAuxEk265aXZ8/YLV0qjRhx+uMHEF5tZuLkeV4rScslJUt6wjm3xPO8H0v60PO8P8jC4PiK7v0kLQ74eFHFuarXvF3S7ZLUu3dv5eTknO5vaDTFxcVROS5wb6IZ9yY6cV+iF/cmejXne1NeLhUWXqApU/bon//so+efL1LbtltC9i0ubq3lyyfoG9/YrpycbZXnu3Ydr/nzv9CYMVb8LT//HDk3UjEx65ST80XIa3XpkqhZs/rrueeWa/fuUTrvvHzl5Oxu0N/WnO/L2Y57c+bUKsRVLIXM9Dyvq6S3Pc8bJgtg/+6ce9PzvK9KekbSVyR5oS4R4ppPS3pakrKzs93EiRNP7xc0opycHEXjuMC9iWbcm+jEfYle3Jvo1Zzvzc6d0smT0mWX9dX+/dLmzQM0ceKAkH1nzrTQ961vxeuii+Irzw8aJJ040VcTJ/aV5C/KfcMNwzR4cOjv3bZNeu01adUq22byjjsGKyEhTOfT1Jzvy9mOe3Pm1Gl3SufcQUk5kqZJukXSWxVvvSH/kskiSXEBH+sv/1JLAAAANLKNG61NTZXGjbOllb76bVXNn28biowZE3w+MTF4OWV+vj03V7U+XCDfJiaPPy7Fx0sJCaf9EwBEUJvdKXtWzMDJ87z2stm2fFkwu6ii2yRJFf93oZmSbvQ8r63neQmSUiQtbeiBAwAAILRCWwGplBSbUTt50mbnQlm0SBo5UmrXLvh8UpLNvpWU2PGGDXa9SDtI+jZEkaSrrz798QOIrDbLKc+T9HzFc3Exkl53zr3red5BSY95ntda0glVPN/mnMvzPO91SesllUr6PjtTAgAAnDkbN9qukP362WycJBUUSAMHBvc7dUpatky6447q10hMtPptO3fa6w0bai4X0KmTlSdwTvrd7xrmtwCorsYQ55xbI6naPkTOufmSRob5zAOSHqj36AAAAFCpvNxqr9Vk/XqbNYuJ8Ye4wkJpypTgfqtW2Szd+PHVr+HboXLLFql/f2nTJum662r+7iVLpDZtajdOAKeHf7wAAACagRMnpOHDpV/8InI/3/b+o2xvEfXpYzNkviWWgebNs3bcuOrvBZYZ2LjRZuUCl0uG064dAQ5obLXanRIAAABN65VXbIZtwwbpyiurb0Tis2mTdOCA1X2TJM+z2bhQIe6996Rhw2zZZVX9+tmM2pYt0jnn2LnAwt8Amg7/nQQAAKAZeOwxaehQqVs36cknw/dbXFGt1xfipNAh7tAhm4m7/PLQ14mJsd0lt2yxZZdt2ihsaQEAZxYhDgAAIMrt22dlAm65xZ5fW7YsfN9Fi2zmLHDp46BBVsPt5En/uU8+kUpLw4c4yZZUbtli352WFnlnSgBnDiEOAAAgyq1da21mpj3rlp8vHTlSvV9xsfT669KkSVKrVv7zqan2rFxg3bclS6S2bYNn7KpKSrLPrFxp3w0gOhDiAAAAopwvxKWnS9nZFshWrqze74knpP37pXvvDT4fuENl4DWHDIk8u5aYaMsu9+3jeTggmhDiAAAAotzatVKPHlLv3hbipNBLKp9/Xpo4sfqmJykp1gaGuHXrbLfLSBIS/K8jLbsEcGYR4gAAAKLcmjUWuDxP6tXLdo5csya4z+7dtnPlZZdV/3yXLhYACwrs+MsvpaIi25kykuxsqWdPacYMKTm5YX4LgPqjxAAAAEAUO3VKysuTvvMd/7nERGnr1uB+c+ZYe/HFoa8zaJB/Jm7dOmtrmonr31/au7fuYwbQuJiJAwAAiGIffigdOyZ95Sv+cwkJoUNcly5SVlbo6wSWGfCFuJpm4gBEJ0IcAABAEygvtzptJSWR+82YIZ17rjR1qv9cfLz02Wc2S+ezcKE0YULwrpSBUlNtVu3gQXvGrksXm2kD0PwQ4gAAAJrAM89IF15oM2cHDoTuc+SINHOm9LWvWbFtn4QE26Fyxw47PnHCyg6MGBH++3w7VG7c6N/UxPMa5rcAOLMIcQAAAGdYaan04INSnz72vNv774fu9/bb0vHj0r/8S/B5366RviWVeXlSWVnkMgC+EFdQYDNxLKUEmi9CHAAAwBn28cdWRPvRR63gdqiab5ItpYyPl8aPDz4fH2/ttm3WrlplbaSC3ImJUkyMlJNjSypr2tQEQPQixAEAAJxhixZZoLrySgtToULc7t3SJ59IN91Ufdljv35S69b+mbhVq6ROnSyohdO2rc3gvfmmHTMTBzRfhDgAAIAzbNkyKS1N6tDBnolbudKecQv02mu2+UnVpZSSBbiBA+35NslC3PDhFgwjSU62WTiJEAc0Z4Q4AACABrBunX+WKxLnpNxcadQoO87KsuLbvk1KfGbMsOWRQ4eGvk56urR6tT1ft3y5NHp0zd/tW4b54x/bjpcAmidCHAAAQAP42c+kG2+suTj29u3SF19I2dl27NuMxFe7TbKllMuW2fXCycyUNm2y0gLHj0tjx9Y8xl//Wnr3XelPf6q5L4DoRYgDAACop5IS2zCktFR66aXIfWfPttY3czZggLWffebvk59v7ciR4a+TmWmzen/7mx3XJsT16iVdfjmlBYDmjhAHAABQT0uWSEePSu3aSc8/H76fczYLNmyYv6Zbnz4WqgJDXEGBtb6yAKH4dqJ86SWpd297Rg5Ay0CIAwAAqKePP7ZNRb73PavBduxY6H7vv2813e6+2z8b1rq1hbDAEFdYKLVvL/XvH/474+L8rydPZnYNaEkIcQAAAPXgnPTGG1bLbdw4O/btGlnVww9bMKv6rFu/ftVn4lJSIu826Xm2+cmjj0pPPVX/3wGg+Wjd1AMAAABozpYvlzZskP76V2nwYDuXn+/fsMQnN9eem/vjH6U2bYLf69fPX/NNspm4SIW7fW66qV5DB9BMMRMHAABQDy++aIW0b7jBZs88z78xSaD/+z+bWfv2t6u/FzgTd+qUtGVL5OfhALRshDgAAIAQdu5sr4KC6kW4A5WUSC+/LE2fLnXrZhubxMeHDnGLFllB7i5dqr/Xr5904ICVCti6VSorkwYNarCfAuAsQ4gDAACo4tvflm6+eYwGD5Z+8Yvw/T74wGq+ffOb/nODB1cPceXltoPluHGhr9Ovn7Wff167nSkBtGyEOAAAgAC7dkl//7s0ZcpuDRsmLVgQvu8rr0g9ekjTpvnPDR5sQay83H9u/Xrp8OGaQ9xnnxHiANSMEAcAAM5q5eVWAuDw4dr1//RTa6+99jONGWObloTinPW95BIpNtZ/fvBgWxa5c6f/3JIl1oYryD10qD0v989/2qYmPXva8kwACIUQBwAAzmrvvy9NmWLPoq1bV3P/Tz+VOneWkpOLNXSotHevtH9/9X5bt9qs3QUXBJ8P3KHSJy9P6tBBSk4O/Z39+knXXGOlAlas4Hk4AJER4gAAwFnNNwvWqpX0+9/X3D8nRzr/fKlVK6chQ+xcqNm4efOsPf/84POhQtyGDRbMItV9+3//Tzp40EIcSykBREKIAwAAZ7UVK6S0NOnOO6XXXpOKisL33b3bnkmbONGOhw61dv366n3nzZO6drVrB/IthQwMcevXqzIQhjN2rDR1qr3u0ydyXwAtGyEOAACc1ZYvl0aMkP71X6XSUttRMhzf83AXXWRtXJwtg6wa4kpLre7b5MnVZ9c8L3iHyuJiaceOmkOcJD3zjDRhgnT99bX7bQBaJkIcAAA4a+3aZbNrI0dasOrWzb+8MpScHKlTJwt9kgW01FRp48bgfnPm2LNyX/966OsEhjjfbpO1CXH9+knz50tZWTX3BdByEeIAAMBZa+FCa7OzbYZs9OjwIc45//NwrVv7zyclSZs3B/d99VXb/OSyy0Jfa9AgC4+HDvmfp/MtzQSA+iLEAQCAZufYMWnLlpr7vfyy1Lu3NGaMHY8ZYztFHjlSve9//7fNnl1xRfD5pCTbibKszH9u7lxbStm+fejv9W1uUlAgrVoltW0bfmdKAKgrQhwAAGh2brvNlieuXh2+z4ED0nvvSTfd5J9ZGzPG6sYtXx7c9/Bh6d//3WbWvvvd4PeSkqRTp2xppmSza5s22exeOIE7VC5fLmVkBNeSA4D6IMQBAIBmZfNm6R//sGD1jW/YMshQ3njD38fHt5Pkpk3BfZcutb4/+pGVIgiUmOj/Xsl2u5TsObtwEhMtOK5fbyEuUl8AqCtCHAAAaFaeesqC1s9/bsW7t24N3e/FF+05tMBNQvr2tc1KduwI7rtokbWjR1e/TlKStb4Q55vFixTMYmNt+eS779rSzUizdgBQV4Q4AADQrMyebZuP3HijHfuKbgfaskVasMBm4TzPfz421oJcqBA3dKjVfasqLs5m1XwhLjdXGjBA6tEj8jgHDbLn7yRm4gA0LEIcAABoNoqL7Tm4CRMsdHXrZlvyV/Xee9b6gl6gAQOCQ1x5ubR4sTRuXOjvbN1aSkjwlxmo7fJI39LNrCx2pgTQsAhxAACg2ViyxHaJnDDBlkVOmBA6xC1aZDXXEhKqv1c1xBUWSl9+GT7ESdLw4RYefZua1CbE3XWX9M47NmY2NQHQkAhxAACg2Zg/35ZH+gLX2LG2A+TRo8H9Fi4MH8oGDJB27rQZOMn/PFykEJeZaTNxn35qx7V5xq17d2n6dAIcgIZHiAMAAM3GggU2K9alix2nplobuNvk559L27dL48eHvsaAAbYT5b59drxokT0L5ysLEIpvc5Rnn7WWZ9wANCVCHAAAaBZKSy1wnX++/1xKirW+59WkmmfWBgyw1rekctEiqx8XE+Hfinwh7n//t3abmgBAYyLEAQCAJnXsmDR1qvTnP0fut3atbWwyYYL/XHKytYEhbvly24wkMzP0dXwhbvt2K/Kdlxd5KaVkO1r6TJsWuS8ANLbWTT0AAADQst1xh/TRR1Zw+4c/DN9vwQJrA0Ncp07SeefZ5iQ+K1bYbpDt2oW+Tny8tVu3WjB0rublkZ4nPfmkhb677qrxJwFAoyLEAQCAJlNaKr38sr0+csRm2jp1Ct03J0fq398/k+aTkuKfiXPOQtxll4X/zi5dbNORLVv835WeXvNYv/e9mvsAwJnAckoAANBktm2TSkqkr37VSgcsWRK634kT0ocfWjgLLN4tBYe4zz+X9u71P8MWTmKihbg1a2xTk7i4ev8UADhjCHEAAKDJFBRYe+utFs5C1XyTpNmzbZbu6qurv5eaasHt8GGbhZOkESMif29iorR5s9V+S0+vHgwBIJoR4gAAQIPat0+6/vrgbf/D8YW40aMtTIULcTNn2tLHSZOqvxe4Q+WyZbbLZLhNTXwSE+2ZuJUra7eUEgCiCSEOAAA0qCeekN58U/q3f7Nn1CIpKLDn07p3ly64wLb7Ly2t3u+TTyzAtW1b/b3AELdokdWRC/dcnU9iohX7PnGi5lk7AIg2hDgAANBgTp2SnnrKQtns2Ra+Iiks9BfsPv986ehRadWq4D47d9rSx4svDn2NpCRr8/PtmbqaygVIUkKC//WNN9bcHwCiCSEOAAA0mDfekPbskf76V3vObOHC8H2dk9avlwYNsmNf6YCqSyo//dTaiRNDX6d9e9uYZOZMey5u7Niaxzl8uLWPPWafB4DmhBAHAAAazJ//bDNr11wjDR7s32gklPnzbUMS33Nu/ftLAwfakshAOTlSt26Rn11LSbHn26TazcT16mWzhnfeWXNfAIg2hDgAANAgVqyw5Yw/+IFtLjJiROQQ9/zz9uzatdf6zw0d6i8X4LN2rRXjjonwby0dO1o7ebL/GbmaxMbWrh8ARBtCHAAAiGjZMumRR2repOStt6RWraSbbrLjESOkoiLbrbKqY8ek11+XbrjBH8AkKTnZdrUM/K6NG2sOZtdcY+1TT1EuAMDZjxAHAADC2r5duvRS6a677JmzSP7v/+y5tu7d7di362Oo2bi335aOHJFuuSX4fHKynfcFv131F/sAACAASURBVAMHpC+/tPOR3Hab7TRZUz8AOBsQ4gAAQFh//KPtGJmSYkEu3Gzc9u3SmjXS9On+c0OGWFt1eaRkSynj462sQCBfCPPVmPO1tQlnocoPAMDZiBAHAADC2rDBdnL8yU+kLVukbdtC95s929pLL/Wf69VLateu+meKiqz0wC23VH/OrT4hDgBaCkIcAAAIq6DAdpvMyrLjqjXcfBYtkrp2tR0pfTzPdpvcvj2474sv2ozezTdXv058vAW7wBDneVacGwBgCHEAACCkY8es0PagQTYbFxPj38a/qsWLpTFjqs+sxccHz8Q5Z0spL7ggdDBr08aCn28J5saNVgOuXbuG+EUAcHYgxAEAgJB8s2GpqVYQe/Dg0DNxR45I69aFrs9WNcTt3m2ze4FlBapKSPDP3hUU1L5kAAC0FIQ4AAAQUmGhtYMGWZuVFXombtkym2EbO7b6e/Hx0hdfSMXFdrxhg7XDh4f/3gEDpB07pPJyaf16KS3ttH8CAJyVCHEAALQw998vvfFGzf0KCqz1bSoybJhtSnLkSHC/RYusHT26+jUGDrTWN7PmC3G+nStDGTBA2rVL2rzZdsYkxAFAMEIcAAAtyJtvSr/6lXTPPTUX7/7oIwtwnTrZ8YAB1hYVBfdbvNhCWbdu1a8RH2+tL8StXy916SKdd1747x0wwMb20Ud2TIgDgGCEOAAAWpB77pE6dpS2bpUWLAjfb8UKae5c6bvf9Z/r39/awBDnnIW4UEspJXu+TbJZNclm4oYMsR0nw/GFxffft3bo0PB9AaAlIsQBANBC7N5tYeqee6QOHaSXXw7f96mnLOx95zv+c3Fx1gaGuM2b7Zm3cCGud2+7ji/ErV9fcyjzhbgPPrAZu1AzfADQktUY4jzPa+d53lLP81Z7npfned6vAt77oed5BRXnHwo4f6/neZsq3pvaWIMHAAC1t2yZtZMm2Rb/ixeH7uec9N57Vri7Sxf/+b59rQ0Mcb5rhNqZUrIZt6QkC3F790p79tQc4nxhsaxMGjEicl8AaIla16LPSUmTnHPFnufFSprved77ktpLukpSunPupOd5vSTJ87yhkm6UlCapr6RPPM9Ldc6VNc5PAACgZTt61Ga7arJ0qdSqle0ymZEhPfqoVFIixcYG91u71jYWufTS4PNt20q9elUPcZ06RQ5myck2Azdvnh1PmBB5nB06+F8HLucEAJgaZ+KcqdgYWLEVf5yk70n6vXPuZEW/vRV9rpL0qnPupHNuq6RNkkLsVwUAAOqroMCWG86cWXPfpUtth8kOHSzEnTrl34Ey0AcfWDttWvX3+vcPDnGLFtmulK1ahf/e5GRpyxZpzhz77rrMrl12We37AkBLUZuZOHme10rScknJkp5wzi3xPC9V0gWe5z0g6YSk/+ecWyapn6TABRpFFeeqXvN2SbdLUu/evZWTk1Of39EoiouLo3Jc4N5EM+5NdOK+RK/63psXXxyokpIE3X//l+rceXXYfmVl0oIF52vixL3KySnUyZMdJY3SK6+s1yWX7A3q+8orGUpMjFVhYW5lrTifdu2GKT+/nXJycnXiRIxWrbpAN920Qzk5WyN893k6dWqQXnihRIMHF2vhwvDj9HnhhfZq3dpp7twTNfZtLPxzE524L9GLe3MGOedq/UdSV0lzJA2TtE7S45I82Uzb1orXT0j6RsBnnpF0XaTrjhw50kWjOXPmNPUQEAb3Jnpxb6IT9yV6Vb03CxY4d9ddzpWU1O7z2dnOeZ5zknP5+eH75eZanxkz7PjUKefatHHu7ruD+x065Fzr1s7dc0/o69xxh3PdutnruXPtmv/3f5HHOHu29ZOc+9Wvave7ogH/3EQn7kv04t7Uj6RcV8tcVqfdKZ1zByXlSJomm2F7q+I7l0oql9Sj4nxcwMf6S9p1WgkTAIBm7pVXpFmzatf36FHp61+X/vQn6aGHau5fVCTl5kq3327Hkf4D+OzZ1l58sbWxsfYc27p11fuVloZeSinZpiNffmkFv1essHPZ2ZHH6Svs3bev9P3vR+4LAKhZbXan7Ol5XteK1+0lfUVSvvT/27vvOCvqe//j76GjoPRedtnCAgssvSpIsSvWaNREozGxxOSa+IupDxNzU+7Vm3hjjN5EoyEmMUogoCKdValLXZqLgLCgFOmwtKXM748PkzllZs4hEdjyej4ePGZn9nvmzMmJ5e33+/189A9JI05fz5VUR9IuSZMk3e44Tl3HcTIl5UgqOjuPDwBAxbV7t3TvvdJ3v5ve+N/8Rtq82ULRk09KR45Ej/f2wT3yiIWyjeErGjVrlpSXF99kOyvL9qrFmjpVatgwvPhIfr4dV6ywnm9NmlgbgSitWtn7bNwoNW0aPRYAkFo6M3GtJc12HGeFpEWSpruu+5akP0jq5DjOKkmvSbr79KzcakmvS1ojaYqkh10qUwIAqqFXXpGOHpWWLJEOHEg9fuZMqUcP6RvfkI4ds0AXZeJEKSfHZtQ6dgwPcbt3S+++K40aFX+9Uydp0ybp1Cn/2uLFVqgksWKlxytKsnSp3/MtqnG3JzNTqlMn9TgAQGrpVKdc4bpuL9d1e7ium++67pOnr5e7rnvX6Wu9XdedFfOan7qum+W6bmfXdd85mx8AAICK6pVXrHLkqVPSnDnRY0+elBYulAYPljIy7NqmTeHj9++3ao833GAhKjMzPMQ995zN6iWW68/MtLC4bZv/DKtWWZAM07q1tRnwQpy3VBIAcO6c0Z44AACQnsOHLeTcf7/NQKUq2LZmjc3WDRpk4UqKXh753nvW4+2aa+w8LMS5roW4a66RunWL/13i+2zYYDOHUSHOcWw2bupUm+FL1bgbAPDZI8QBAHAWrFljM3ADBlhz7cWLo8fPn2/HwYNttqt27eiZuAULrDdbv352npkp7dollZXFj9uyRfr0U+naa5Pv0amTHb19cStW2LF79+hn7d3bn71jJg4Azj1CHAAAZ0Hx6VZoPXpYAZGoQCZZiGvWzMbWqGF73KJeU1Rk977gAjsPm71budKOXkGSWB072sya95qVK+29U82u3Xuv/75Rs3YAgLODEAcAwFmwYoV04YU225WRYTNiJ06Ej583z2bhvCIhGRnhIe7UKQtxAwb41/6VEFe3rpX9j52Jy8mR6teP/mxZWdKePbb8MrbaJQDg3CDEAQBwBmbNksrLU48rLrZliTVqWCA7cULaGtI1ddcu6cMPbT+cJ6pQyQcf2P65oBCXGPxWrrTebo0aBd8rO9ve2xub7sxa3br+ckwAwLlFiAMAIE1FRdLIkdJLL0WPc12b1erZ085TVZtcsMCOgwf71zIybC/b4cPJ4596yoqljB7tX2vWzGb+gmbiova49expYw4csJm1VPvhAADnHyEOAIA0ec21p06NHvfJJ9Levf6sVqoQN3euVKuWNfn2eK8pLY0f+8EH0tix0te/LrVt6193HHtNbIgrL5dKSlKHuEOHrOecxB43AKgMCHEAAKTpzTftOHt29P622KImktShgx2DQpzrSuPGSZdc4hcLkcKXR86YYa955JHkeyUuwVy1ytoQ9OoV/qwFBXb805/syEwcAFR8hDgAANKwaZMtkRwwwJYeFhWFj00s1e8VEAkKcSUlDbV+vXTnnfHXvZm4xOWRixdLLVvaPrdEXohzXTtfutSOffqEP2vXrtaqYPp0qUED/30BABUXIQ4AgDSMHWtLFn/zGzufMyd8bHGxhaGLL/avhVWbnDWrherUkW6+Of56y5YW/hJfs3ix9YbzqljGysyUDh60ypGStGSJdNFF0QVI6tWzVgOSNHSoFWIBAFRs/K0aAFBtTZtme8uilkZKVtL/5ZetqEnfvjYL5i2ZDFJc7Bc18QSFONeV5s1rppEjk6tHBvWKKyuzPXGxe+diJbYZWLLEGnOnCmYvvCD9+tfSX/8aPQ4AUDEQ4gAA1dK770rXXis9+2zqapNz5liY+tKX7LygQFq+PHjstm1WTGTgwPjrQb3i1q2Ttm6tr2uuCb5XZmZ8iFu61IJfOiHu+HFb1hm1lNIzerTtsQtrQwAAqFgIcQCAaun1120p4aBB0hNPRPd+GzfOxl5/vZ0XFFhQO3IkeeyUKXa86qr460G94t5+245hIS6x2uT8+Xbs3z94fFaWHdeuldaskY4ds5k4AEDVQogDAFRLJSVSly7So49KO3aEz6ydOiWNHy9dcYUV/pAsxJ06ZdUfE02ebEVMEkv1BxUqmTlTat/+cGgxkYwMawReVmbnc+ZInTtLzZsHj/cKk6xebUsppfRm4gAAlQshDgBQLa1dK+Xl+csew6pNLllifd9iC494ZfkTg9/evTYTd/XVyYVHEnvFua69Z7du+0Of0ZtZ27DBQuPcuVZ8JEp+voXLpUst1OXkRI8HAFQ+hDgAQJVRVmZLCFM5eNCCWV6e1K6d1Lq1tHBh8FivsfeVV/rXMjKscuSHH8aPfeYZe4agHm6JveI2bZJ27pS6dDkY+py5uXb88EMraLJ3b3ohrqREWrDA+sNRbRIAqh7+1g4AqBJOnbKAM2hQ9P42yWbhJAtxjmN7zMJm4qZPtzAUu4SxRg2bJVu3Lv79f/Mb6cYbk5dSSsm94rzQmJd3IPQ5s7Pt+OGHVklTki69NPqz5efb3rslS1hKCQBVFSEOAFAlTJpkpf2XLZN+8YvosSUldszLs+OAARaU9iesbCwrs2Iio0cn3yM3N34mbuNG688WVqREii9UUlRkxVI6dToUOv7CC6W2be19Xn/dwmRUzzfJQpwnsYE4AKBqIMQBAKqEX//aQtLw4dIbb0SPXbRIqlXL33PmLVuMLToiWSGR48elUaOS75GTY3vVTp60c29/XGJ/uFixwW/pUhtbq5Yb+ay5udKMGbY88nOfi/5cktS1q1XRnDQpvBUBAKByI8QBACq9kyct5Nxwgy2nLCkJX1J56JA0dqx0001SnTp2zduvtnlz/Ng5c6SaNaXBg5Pvk5Nj77Fli50XF9syy27dwp8zL8/6yO3fL61cGbzsMlFurrUlqFEjvRBXu7Y0caJ03XWpxwIAKidCHACg0lu3znq2FRRI3bvbnjBvyWQs15V+/nNp3z7pG9/wr0eFuN69bVljIq/qo7cvbvlyC2n164c/p7d8c9YsW3qZTohr1cqO3/xm6qWUAIDqgRAHAKj0li2zoxfiJJvpSvTMM9JPfyrddpvN2HmaN7fCI7Ehrrzcio8MGRL8nokhrrg4eiml5Ie4cePs6D1rlAcekJ56SvrZz1KPBQBUD4Q4AEClt3y5LY3s0sWaYdeuLa1YkTxuyhQr/PGXv8T3catRQ2rfPj7ELV0qHT0aXtK/TRvpggssxO3ZY69NFeI6dbK9eN6evXRCXKtW0mOP2WcCAEAixAEAqoBly2wvWp06Fna6dAmeiSsutmIfQb3TOnSID3FeywGvGXgix7EWAOvW+YHRawIepnZtC4vHj1vVySZNUn82AAASEeIAAJXaggXSzJlWldKTl5fciHv7dmnHjvCglRjiFi2yJuBt24a/d26uhbjiYjtPNRMnWfGVDh1siSQAAP8KQhwAoELat8/6os2YET3u4Yeldu2kJ57wr2VnW1Pt48f9a6laAHToYFUgvaqWixZJ/fpFv3dOjvTRR9LixVKLFn4Rkii//KVUWip9/vOpxwIAEIQQBwCokN5804LX979vVSWDlJXZUsp775Uuvti/npVlbQdiZ9ZSzZZ17Gjvs3mztQBYuza9EHfihJX0T7WUEgCAzwohDgBQIY0fb8eiIun994PHrFhhwatXr/jr2dl2XL/ev7Z0qQW1xo2D79W5sx3XrrWZNSm9ECdJBw8S4gAA5w4hDgBQ4Rw+LE2dKn3pS1ZAZNas4HFea4GwELdhg39t0SIrahLGK/9fUiLNm2fvO2BA9HPm5vo/P/xw9FgAAD4rhDgAQIWzeLE1777pJikzM7hxt2TLLZs2tT1xsVq3tqbb3kzcrl3Sxo1S//7h79m0qfWLKymxJt/du0uNGkU/Z4sW0v/9nxU38RqGAwBwttU63w8AAEAib4atTx+bIfvgg/BxBQXxPd8kO8/K8mfi0l0e2aWLtGqV/fniF9N71q98Jb1xAAB8VpiJAwCcE2vWSP/v/1nBkVSWLbNKj61bW7Bauzb5dcePWy+4xKWUnpwcfwZv0SILdn36RL9vXp61LCgrC2/yDQDA+UaIAwCcE489Jj39tDR9euqxS5f64SwvTzp2zMryxyopsXYAYSEuP9+WUx45Ynvc8vKkiy6Kfl9vX1zNmtLIkamfEwCA84EQBwA461askN55x35++eXosUeP2qxd79523qWLHROXVIYVNfF07y6dOmWzde+/H98MPMxtt0kPPWR73Fq0SD0eAIDzgRAHADjrxo+XatSQ7rpL+sc/rCR/mMWLbemkt/TRmx1bvTp+3LJlVrwktkJkrO7d7fjyy9KhQ9Jll6V+zjZtpOees2IqAABUVIQ4AMBZV1IiZWTYTFd5uc2OhZk+3QKfN3PWtKnUvr1Vooy1fLnUo4ctfQySnS3Vqye98IKdpzMTBwBAZUCIAwD8S+6/X/ra19Ibu3atNdP2ZsdShbh+/eKbcvfubfvkPCdO2Lm35DJIrVoWACVp8GBrHwAAQFVAiAMAnLGFC6UXX7RZrk8+iR576pT04YcW4jp0kBo2tBL+QfbutXtffnn89d697R5lZXa+aJF04EDqJZLf/750553SpEnpfS4AACoDQhwA4Iz95CfWCPvkSemll6LHfvKJdPiw7W1zHKsaGTYT9+tfW+i74Yb46717S64rFRfb+bRpdq8RI6Lf+8EHpVdf9WfkAACoCghxAIAzsm+fNHWqNbkeNswKlURZu9aOnTvb0Qtxrhs/budO6amnpFtvTV4m6Z17SyqnT5f69iWcAQCqJ0IcAOCMTJlie9LGjLHy/mvX2uxZGK/hthfiuneX9uyRtm+PHzd1qlWRfPzx5Hu0bi01aWIVKsvLbcllOtUmAQCoighxAFDNua70299Kf/yjdPx46vGTJlmRkAEDLJgdPhy9L+699yyEtWpl5zk5dtywIXlco0ZSQUHyPRxH6trV+seVlFiIDOsPBwBAVUeIA4BqbsMG6eGHpXvukX7609Tj58yRRo2y0v7e7Jo325bo+HHbv3b11RbEJCkry3/fWO+9Jw0dGt4ywAtxK1bYeY8eqZ8VAICqiBAHANXcpk12rFdP+sMfrFhJmP37pS1b/ADlNeL29r0lmj/fXnP11f61jh2tD9xHH/nXtm+3e1x6afh7d+0q7d4tzZwp1akT3uQbAICqjhAHANVcaakdf/ITC2gzZoSPXbPGjvn5dmzVyloGhM3EvfaaVLu2zdx56tSx5t2xM3Hz59tx6NDw9+7Sxb9nt27WBw4AgOqIEAcA1Vxpqc2MPfigBayZM8PHev3dvBDnODYbFxTitm2zmb2775Yuuij+d506xc/EFRVZKIva59a1qx2PHmUpJQCgeiPEAUA1V1oqtW0rXXihBSWvF1uQVaukBg2sabcnOzs+kHmeecYKkHz3u8m/y8qKn4krKpJ69rQlnWHatpVuuUUaMsSCIQAA1RUhDgCqudJSP5QVFEjLl4ePXbXKljLWiPmnR0aGLcM8ccK/duyYzcJdf73NuiXq1En69FOprMzaEyxaJPXvH/2cjiO98YYVVqG9AACgOiPEAUAVtHy59LnPWVGRVEpLrdiIZLNhn36a3MNNsv5sRUXJjbgzMy3Abd3qX5s4Udq1yxqCB/GqWq5caQVNDh5MHeIAAIAhxAFAFfQ//2OzVg89FD3u5Enp44/jQ5wUvKRy7lybObvyyvjrGRl23LjRv/bWW1KLFtLo0cHve8kldpw9W1q2zH7u0yf6WQEAgCHEAUAVU1YmjR8vNW4s/eUv0rp14WM3bbJZtMQQ5/Vii/XOO1ZpMnEpoxfivFYFkrR0qdS3b3jPt+bNrTjJrFn2XrVr++0KAABANEIcAFQxb70lHT4s/ehHdu7NdAWZMMGOI0fasUkTC1hBwW/yZJtBa9gw/nqHDrZfzQtxR45YtcqoSpOSNGKEze4VFVlBldq1U30yAAAgEeIAoMpZssRaBXz5y1a2P6ra5J//bHvRsrP9a9nZ0vr18eNWr7Y/N96YfI+6daU2bfwQt3KlLdNMFeKuuMLaBcyeTcsAAADOBCEOAKqYtWul3FzpggtsiWJYtcnVq+13d9wRfz0oxP3tb1aR8pZbgu+VkeGHOG/mL7EASqJRo6R27exnQhwAAOkjxAFAJbB9u/TJJ+mNLSnx95cVFITPxP3xjzZT9/nPx1/PzraWAUeO+NfeeMP2wrVqFXyv3FwLha5rwbBRI3+vXJhataT77rOfu3dP+bEAAMBphDgAqOBOnLD9YyNHWk+1KOXl1njbK+Hfs6eFv/374zecnTghvfqqdPXVVkUylre00qs2uXevBcNRo8Lft18/aedOafNmm4krKLB9cqn8x39ITz5J3zcAAM4EIQ4AKriXXpI++MCWSc6eHT12wwbbj+bNxHkzXBs3XhA3bvp0ads26Z57ku/hhThvSeWSJXaMagHQr58d58+3apOp9sN5GjWSfvhD28MHAADSQ4gDgArMdaWnn7aQ1KSJ9MIL0eNLSuzozcR5YW7z5vgQ98orUtOm0jXXJN/DC3Fehcp0QlyPHhbE/vQnW4aZbogDAABnjhAHABXYsmU2I3b//dKYMTYT57rh4xcssAIkXohr394KnGzefOE/x+zbJ02caAVNgmbAmjSRLr7YX065eLHUqZNdD1OnjgW3yZPtnBAHAMDZQ4gDgHNs1y7bi5ZqaaRkVSFr1ZJuuslmwnbvlj7+OHjs8eNWrOSaa6SLLrJrNWrYbFxpqT8Tt3ChdOxYcLsAT0aGVFpqPy9ZEj0L5/niF/2fadwNAMDZU+t8PwAAVCeua9UgZ8yQDh1KXdDjzTetqEnTpv7s1rJlNsOW6K23pB07bNYuVpcu0owZfojzlklGBa2OHa1Ayu7dNiP3wAOpP9tDD1l43LPHgicAADg7mIkDgHOouNgCXH6+9N57/h62IJ9+agVNRoyw8x49rOKj14ct0eTJVijkqqvir3fpIu3YUU9lZXa+bp3UoEF4uwDJn4lLZz9crLvukr7+9fTGAgCAfw0hDgDOoRkz7Dh2rAWyN94IHztnjh0vvdSODRpYP7awEDdnjjRkSPIsmLc/zpuBW7fOipdEtQDIyJAOHrQqllLqxt0AAODcIcQBwDk0Y4bNjPXqZUFpzZrwse+/L9WvHz8L1rOntGpV8tidO21Wb+jQ5N9lZtrR2+O2bp2UkxP9nB072nHcOCkrS2rcOHo8AAA4dwhxAPBvcl0/IEU5dsyWUI4ebed5ebZcMsysWdLAgfEVJDMypC1bkpt+z5tnx6AQ5wWy0lIrfrJxo99GIExGhh03bZL69o0eCwAAzi1CHAD8m379aws948ZFj5s3z3qojRpl5126WAPvkyeTx370kTXNTuzj1qGDVF5u++ViFRZKdesGB66mTaV69U6qtNSC3MmTqWfivBAnxVedBAAA5x8hDgD+DeXl0lNP2c/33WeVGcPMmCHVrCkNG2bnXbpIR48Gz+JNmGDHxDYAHTrYcfPm+OuTJ0vDh0v16iXfy3Gkli2PqrTUCqtIUteukR9LjRvb0s1vfcvaIQAAgIojZYhzHKee4zhFjuMUO46z2nGcHyf8/jHHcVzHcZrFXPuu4zjrHcdZ6zjOFWfjwQGgIvjb36RPPpG+/W3pwAG/mmOQGTNseaTXw61LFzsGVaicMEEqKLAm27G8pZGxIW79eunDD5Nn7WJ5Ie7dd635d6pm3I4jLV8uPf109DgAAHDupTMTd0zSCNd1e0oqkHSl4zgDJclxnPaSRkv6579OOI7TVdLtkrpJulLSbx3HqflZPzgAVAQvvWRLEx991M7D9rjt2yctXuwvpZT8Pm2Jrzl82BpyXxHwn8C8mbjY2bvJk+0YHeKOqbTU9uQNGhS/zw4AAFQuKUOca053F1Lt03/c0+e/kvTtmHNJGiPpNdd1j7muu1HSekn9P7tHBoCK4aOPbGbrnnukli1tCWJYiJs/34qReEspJdur1qSJzaTFKiqSTpyQLrkk+T4XXyw1bBg/Ezd7tlWQTJy1i9WixVHt2mXLKWOfAQAAVD5p7YlzHKem4zjLJX0qabrrugsdx7le0ieu6xYnDG8raUvM+cenrwFAlTJpkh3vusuWH3bpEh3iatSQ+vWLv56VZWEwltcfbvDg5Ps4js3GeSHOdW18UOCL1bLl0X/+HDTDBwAAKo9aqYdIruuelFTgOE4jSRMcx+kh6fuSLg8YHtQ+1k0a5DhfkfQVSWrZsqUKCwvTfeZzpqysrEI+F/huKrLq9N3MmpWriy5qro8+mquPPpIaNeqsefOaqrBwXtLYyZN7qFOn2lq8OH7TXIMGXbV6dQMVFhb989qkST2UmVlHxcWLA9+3QYPuWr26jgoLl2jz5gu0a1d/NWtWosLC7aHPmp9/TNde20jDhu3U4cN7VU2+okqhOv01U9nw3VRMfC8VF9/NueO4blK+in6B4zwh6ZSkRyQdPn25naStsmWTX5Ik13V/fnr8VEk/cl13ftg9+/bt6y5eHPwvK+dTYWGhhg8ffr4fAwH4biquqvDd/OpXVqDkpz/1C4kEuewy6/3m9Wj7n/+RHntM2rXLlkp6Tp60pZZ33ik9/3z8Pb73PatuefSoVa6MGuv5+tell1+2QiovvSTdf7+1KsjNDX/WqvC9VFV8NxUX303FxPdScfHd/Hscx1nium5a3VnTqU7Z/PQMnBzHqS9plKRlruu2cF03w3XdDNmSyd6u626XNEnS7Y7j1HUcJ1NSjqSikNsDQIWycaP0+OPSn/8s3Xxz9NgPP4wPTl7Z/sQllatXSwcPwc62KgAAIABJREFUWkGRRJ062f63jz+285UrbWxQ0+7Y9ykrsyWV8+dLzZql7vsGAACqjnT2xLWWNNtxnBWSFsn2xL0VNth13dWSXpe0RtIUSQ+fXo4JABXef/6nzYjdfbcVATl+PHhcWZm0davUubN/zWsZkBjivJUlQQVFvGIkGzbY0dsPF7XHrVs3O65eLS1dKvXubXvlAABA9ZBOdcoVruv2cl23h+u6+a7rPhkwJsN13V0x5z91XTfLdd3Oruu+81k/NACcDcePS3//u3T77dLIkTZDllg50rNunR1jZ+I6dLAebIkhbvZsKTMzeGmmF+K84iZz5kjt2/utBIJ4IW7ZMgtyvXun/mwAAKDqSKs6JQBUB3PmSPv3S2PGhM+qedautWNsiKtRw2bmYl9z6pS1IQjbItCunVSrlj8TN2+eNGRI9HM2aSK1amWNxo8fJ8QBAFDdEOIAVHnLl0uvvy7t2RM9btIkqW5dafRovxH3mjXJ47Zvl37wAwtTiXvREtsMrFwp7d1rRVCC1KolZWdbKNyzR9qyJb1Q1q2b3VuSevVKPR4AAFQdhDgAVdqLL1oouu026b/+K3rsrFnSpZdKF14oNWhgyxqDZuKefVYqLZXefluqVy/+d1262O/Kyux89mw7RjXYzsuTSkr8UNajR+rPdccddqxfP7rJNwAAqHoIcQCqrJ07pQcekC6/3IJRVCeTQ4ekVaukgQP9a2HNuxcutPvFjo19jeQvtywstJAVtcctL8/23i053UIunRB37732moULbRknAACoPvhHP4Aq6913re/aj34kDRhgyyrDWmMuW2b71/r186/l51uIO3HCv3bqlIXB/v2D7xMb4k6etGcIW0rpycuzvW0TJ1q7gFat0vt8WVlS9+7pjQUAAFUHIQ5AlTV7ti2N7NPH9o15e86CFJ3uZhkb4nr0sCbcsRUq162z4iex42JlZVmLgpISacUKad++8KImHm//3Xvv2XvSLgAAAEQhxAGoVMrKpD/8IX52LExhofVbq11bKiiwa8uXB48tKrI9cLGzYN6yxhUr/GuLFtkxbCaubl1bPllS4veHSxXiYnvNpRoLAABAiANQqTz9tHTffdLzz0eP27XLKkt6BUW8Ga5ly5LHfvSR9I9/2N65WF272qxacbF/bckSKybiLZsM0rmzhbjZs63yZLt20c/aqJF0443So49K3/te9FgAAIBa5/sBACBd5eXSCy/Yzz/4gXTnnVbmP4i3PHLwYDteeKE12/YKjsT6/vet1P+Pfxx/vW5dW+oYOxO3YoXtQ6tZM/w58/KkKVOkTZusKmY6xo9PbxwAAAAzcQAqjTfflHbssNB14IA0d2742KIiq9oY23MtJ8f2tMU6eVKaPFm66y6pbdvk+3Tv7pf+d12blUtVPTIvz5Z7HjyYuqgJAADAmSLEAag05s2zvmyPPRa+NNJTVGQNsRs08K95IS62QuWaNRYIhwwJvk9OjrR5s80Cbtsm7d6dOsRdeqkFwq9+VbrllvQ/HwAAQDpYTgmg0li0yAqUNGpk4SqsSInrWoi74Yb469nZVlly924r5S9ZMJT8ZZeJMjPtfps3+1Uqe/aMfs6cHOnjj9P7TAAAAGeKmTgAlcLJk9LSpVLfvnZeUBAe4n72MwtqXlETT06OHWOXVM6fLzVvbhUlg3jXN270C5zQmw0AAJxPhDgA59WJE9KhQ6nHlZTYOK8/W0GBBat9++LHffSRFT254w4rfBIrKMTNm2ezcGG92TIz7bhxozX5zsiQGjdO/bwAAABnCyEOwHlTVmZ70bp2lXbujB67eLEdvZk4b0njqlXx4957z47f+54VNomVmWnXvBC3a5f9PGhQ+Pu2bWt95jZulBYsiB4LAABwLhDiAJw33/ymhbMdO6T7748eu2iRFSnxGmPn5trR26fmmTfP9swF9XGrU8faDHivmT/fjmH74SRrJdChgzRnju1zGzgw9ecCAAA4myhsAuC8OHXKGmzffrvUooU17z5xwvq1BVm8WOrTx+/P1rGj/ZwY4ubOtdmyxFk4T2ybgXnz7P282b0wmZnSjBn2MyEOAACcb8zEAfjMnDolPfdclmbOTD125UpbQnn55VKvXtKxY8k93Dzl5VbEJDZs1a5t4So2xO3day0DombWYtsMzJ9v712/fvSzerN/9eunrkwJAABwthHiAHxmJk+Wxo1rrzvukPbsiR7rzWyNGuVXe/SaaidatcpCnlfUxJOdHR/ivGqVieNi5eRYX7ht26wNQVTg8zz5pPTaa9K0aVLduqnHAwAAnE2EOACfmf/6L6lx43Lt2iX97/9Gj5061fattW1rx5o1w0Pc7Nl2DAtxXvPuFSvsGDVblp1tx7//XTpyJL1CJU2aSLfdJg0dmnosAADA2UaIAxDq4EHppZesR1sqO3ZY8Y+bb/5Y3bpJS5aEj923z4LZ9dfbeb16NkMWFOKOHpV++Uvpkkv8cv+e2ObdkoW45s2lli3D39trM/DHP9oxnZk4AACAioTCJgACua50773SuHFS06bSDTdEj1+40I49euzXwYO2VDHMW29ZEZMbb/Svde8eHPz++ldp61Zp7NjkXm7erNqHH0rNmlkI7NEjvOebZEGwZk17rxYtpPbtoz8XAABARcNMHFCNHDmSeq+a5513LMBJ0oQJqccXFVk4ysk5qK5dpU2bwpt4jx9vyyhjl0fm5kqlpRbuYhUWWtgaMSL5Pj162HHpUpstXLXKvxamdm1bGikF3xMAAKCiI8QB1chDD0n5+bacMZWZM22Z4+23S5MmScePR49fuNACVL16p9S1q83klZQkjzt8WJoyxWb2YtsAZGRYEPv44/jxRUXSgAHBs2vt2tnSycWLbW/ckSN+kZQor75q9021bw8AAKAiIsQB1cSxY1bMY9s26YknUo+fM0fq399C3L59dh7m5Elrxj1ggJ1362bHNWuSx06damHrppvir3v73TZt8q/t22dBsH//4Pd1HGs7sGiR9XyT/GeI4jg2C9iiReqxAAAAFQ0hDqgmZs2yQiXZ2amLlRw6ZEsUhw6Vhg+3GbPCwuh7798vjRxp59nZtmxx9erksePHW7XHSy+Nv56RYceNG/1rixbZMSqY9esnffCBze41aSLl5YWPBQAAqAoIcUA18Y9/SA0bSo8/biEtaKmjp6jI9qYNHSpdfLHUp49f5j/IK69IjRtL111n57VrS1lZVnAk1smTttfu6qulWgllldq3t7AYOxPnFUeJ6vvWr58t3Xz9das0WYO/qwEAgCqOf90Bqon33pOGDfN7nXmzXEHeeceC2JAhdj58uLRgge1nS3TokM2u3X57fCPs3Fxp3br4sUuXWjuAq65Kvk+dOlbsJDbELVxoM2uNGoU/68iRUocO9nM6SykBAAAqO0IcUA3s3m0zb0OGWLhq2DA6xE2cKF12mXTRRXY+bJgVNgl6zZw51ssttl2AZP3Y1q2TTp3yr02davvRRo8Oft/MTH85petaiAvbD+epW9fuO2CAdOut0WMBAACqAkIcUA3Mn29Hb7lhnz5W0TFISYktgxwzxr+Wn2/HtWuTx8+aFT9r58nNtWIqW7b416ZNs/du3jz4vTMy/BC3ebP06afpza7l5dlMYefOqccCAABUdoQ4oBqYN8/2oPXta+f9+knLl0vl5cljp06147XX+tfat7cZr8TlkZKFuIEDpQsuiL+em2tH7zUnT1qD7cSwF6trV2sxsHev3zycJZIAAADxCHFANTBzpgU4L2j17WsBbtWq5LGLFklt2vj7zCSbvcvKSg5xn35q+9wuuyz5Pl6I84qblJTYnro+fcKfs1cvOy5fbiGubt30+r4BAABUJ4Q4oJLavduWOaZqWL1jh1V5vOYa/5pX7TFoj9uiRcHVIHNykqtNPvus7V27447k8a1bSxde6L9myRI7phPili61Z+7d2wqeAAAAwEeIAyqpe+6xPmxjx0aPe/ttO3rl/yXbe9a0aXKI27fPQldYiNuwwe8vd/iw9Nxz0g03BO9Fcxxr+r1ypZ0vWWKhLmrfWvPmUrt2FuCWLGEpJQAAQBBCHFAJlZVJb70lNWtms1bbtoWPfestC0Y9evjXHMeWVCYWN/Fmy8JCXHm5X6ikqMj2rt17b/h7FxRIy5bZbN3ixXZes2b0Z+vd23q+HTlCiAMAAAhCiAMqoQ0b7PjVr9pxypTgcceP2364q66y4Bard2+byTt+3L82ZYoVQAkKcYmFSrzCIwMHhj9nQYEFvXXrLMRFjfVcf73/c6r2AgAAANURIQ6oIA4fln71K5tlS2X9ejvedJPtPQsLcQsXSgcOSFdckfy73FzpxAm/uXZ5uS3NvO46qXHj5PE5OXaMDXFZWTYbGKagwI6//73d/9JLU3403Xef9NRT0i23WN84AAAAxCPEARXEuHHSN79pIcp1o8d6QSonRxo5Upo9O/g1U6daZcmRI5N/lzizNmmSVZv88peD37NNG6tuGRviUi137N7dZgB/9Ss7Hzo0erznscekN95Inj0EAAAAIQ6oMLyG3IWFFsqirF8vtWwpNWwojRgh7dxpSyMTTZtmQatRo+Tfxc6sua7NfmVmBs/aSRaosrNt/JYt0tatqUNcgwa2hPLkSXveJk2ixwMAACA1QhxwFrz/vvTEE34RkHTMmWOBx3GkuXOjx65fb4FKshAn2d63WLt3W/XJsFDWrJl08cVWjbKw0AqVfPvb0YVHvDYDXsgcNizlx9Kbb0q33Sb9+MepxwIAACA1QhxwFnz/+9KTT1rfs61bU4/fu9dm0q65RsrLs0AVprxcWrvWD3EdO1pj7gUL4sfNmGEzbFEzazk5NrP28su2D+6ee6KfMydH2rjRlmk2a5ZeI+6mTaXXXvOLsAAAAODfQ4gDPmNHj9oM2OjRVqzkgQdSv+bNNy1wDR1qSxQXLgze41Zebs2yt2+P31/WtasFu1jTptkyyr59w983J0das8b2w91wg1SvXvRz5uRYMZS//EW67DLbbwcAAIBzi38FA9L0/PP+vrUoCxdakHvkEenRR61P2/794eMPHJAef9zC2SWXWFn9nTul0tLkse++K61aZU2277vPv965sy1zjA1+s2ZZ0KpVK/y9BwyQPvnEnu+WW1J/tthG3aNGpR4PAACAzx4hDkjDhg3SQw9Z9chUCgtthuqSS6Thwy1YLVoUPv7pp21m7YUXbD+aN3O2bFny2DfftNmye+6Jr9zYubN06JAFMknavNlaB6Tas/a1r0nf+pYFyKAKlokGDbJ2Ab/7nfSFL6QeDwAAgM9exH+jB+B58UU7LlhgyxZjZ6QSzZhhjbQbNbJZNcexGbygmas9e6RnnrFZMC+8eVUjvV5wHte1EDdqlJX6j+U9T0mJ1K6dFVaRUvdlq1nTQmS6atQIb0EAAACAc4OZOCCFU6ekV16RBg+2EDN2bPjYffsssF15pZ1ffLHtV0ssOuL55S+tufcTT/jXGjWyoiGJIW7ZMptdGzMm+T5eiPP2xb3/vnTRRVKPHul8QgAAAFQmhDggheXLbbnjgw9Kl18u/elPFuyCzJxpPdG8ECeFFyrZvVv63/+Vbr1Vys+P/112dnKIe+012992003J79umjfVkKymx8/fes8InUe0CAAAAUDkR4oAUpk614+jR0t13W++3sGbcU6bY7FtsE+xevSywbdsWP/Yvf7FZuB/8IPk+iSHu1CkLcVdcEdww23Fsxm/lSunTT6UPPrA9eQAAAKh6CHFACtOmSQUFUsuWtpTxooukv/0teZzrWogbPTq+IqQ3y7ZqVfz4mTOlrKzgXmvZ2RYWjx6189Wr7fzmm8Ofs1cvmzVMdz8cAAAAKidCHKqlzZutL1phYfS4Y8ekuXP9oiT161voWrcueeyaNdLHH8cvpZSkbt3sGBviTp60dgEjRgS/b3a2hcKNG+38vffsOHx4+LP26mWtAsaOtQqWUf3hAAAAUHkR4lAtfec70sSJFs6WLw8ft2KFdPx4/PLIDh0sBCaaMsWOV1wRf715c5vFiw1xy5dbEZSoECf5Syrff9+qTmZkhD9rr152nDTJWgHUqRM+FgAAAJUXIQ5VwtixttQwsXhIkNWrpb/+Vbr/fpsR8/a8BVmyxI6xs1odOtjSxsTiJlOm2NLJdu2S75Ofb+/rmTXLjmEza7EhznVtJu6SS+J7wyWKXZaZTj87AAAAVE6EOFR6riv95CfS+PF+dcYob79txyeftD1pRUXhYxcvlpo2lTp29K916GCzczt2+NcOHbKglbiU0uOFOC/4zZplhUhatQoe36SJtRpYv96WVG7blrpQSf36FjYHD5auvTZ6LAAAACovQhwqvblz/WWHXkCLMnu21KWLBagBA1KHuD594mfAOnSwY+ySysJCqbw8OsQdOiSVltq4998PX0op2ft5FSq95xs4MPVnmz/f3z8HAACAqokQhwrp2LH0lkZKVnr/gguk3NzUIe74cQtQl11m5/37WzGSrVuTx86ZYyX7E8OTNysXG+KmTLFnGDo0+H1ji5ssWmSBLirESVJOjh/i6tVL7iUXpFYtesMBAABUdYQ4VDjbtlkgu+IKv8R+lPnzrZDHmDE2K1deHj7WC1BeiOvXz46LF8ePKy+XbrvNlls++mj877yZuNJS/5q3Z61u3eD3jQ1x06ZJNWpIw4ZFf67sbGnTJvtMvXtLtWtHjwcAAED1QIhDhXPXXdawevp0qyIZ5cgRqyDZv7/1cjt+PLj8v2fSJJutGjnSzjt3tuOGDfHjFi602bmf/9z2psW6+GLrFefNxB0+bPvd+vcPf9+LLrLwt2qVzRYOHBjctDtWdrbtoSsqir43AAAAqhdCHCqU/fut6Mfjj0u33mpLJROrQMZavlw6ccJCTlA/tliuK02YYBUhGze2a02aWMD66KP4sTNn2mxZ2JLHTp38IirLllmVy1R92fLzLZguWSJdc030WMmvUClJl1+eejwAAACqB0IcKhRvWeOQIdaMe8eO6MIj3u/697dZtZo140v5x/rgA+nDD6WbbvKvOY6Umek31fbMmGEFTbywl2jQIFvGeeKE/8ze0sww3btLO3faz+mEuL59pW99y/bbXXVV6vEAAACoHmqd7wcAYnmhzJvVqlnTlkCGVWZ8+21bptimjZ1nZ4fPxP3yl7Zn7cYb46/HzqpJtjxy4ULpscfCn/OSS6Tnn5eKi22fXdu2UuvW0Z/tkUdsKWetWlKPHtFjJWvW/fTTqccBAACgeiHEoUIpKrKqjN4MWM+e0tKlwWMXLLDlib/4hX+tW7fgELdhg/TKK9LDDyf3ZuvUSXrnHVtu6TjSmjU2wxa1PNLr2fb++/ZnwIDUn61tW+k//zP1OAAAACAKyylRYbiuBbPYZYnt2lm1ykQvvpipQYMs7D34oH89P9/K8idWtfzVr2xW7/HHk++VmWnjt2+3c285prfHLki7dva6P/zBCpykahcAAAAAfFYIcYhzxx3S3XdHj1m2THrySasEmUpZmfTQQ9LVV9sSxSgLFliQuuIK/1rbttInnySPnTOnmfr0kebNs8Iknm7drBBK7PLIfftsFu722/1ll7E6dbKjV9xk9WpbyhhbWCTI5z9vfeQkv9olAAAAcLYR4vBPe/ZIr78u/elP1p8szDPPSE88IX3uc6nv+fbbtnds/nxp1CgrLhLm9dctPI0Z419r00bavduaf3vKyqTNmy/QdddJeXnx9/AaYscuqRw/3nrDPfJI8Pt6Ic5rM7B6tRVJqZVisfEDD1gFy9at/VYFAAAAwNlGiMM/vfmmlcp3XemFF8LHlZXZ8R//8JcghikslBo2tFYAx49boAviutK4cdKVV1ofNo83cxa7pHLZMsl1ncA9azk51hQ7tkLlvHnWSqBPn+D37tTJApsXMNesiV5K6Wnf3pZn/sd/2F46AAAA4FwgxOGfJkywYDJypDR1avi4Tz7xZ6mKi6PvWVhoRUA6dpSuv976vgUtw1yzRvr4Y+m66+Kvt23rv6fHK+kfFOJq15Zyc+ND3Pz5Vt0yLGh5r/ngA+ngQZuFTCfESdLPfiZ9+9vpjQUAAAA+C4S4Ksx1bXZt//70xs6bJ40eLXXtaksLXTd47Natft+yqBC3fbvtTRs+3M6/8AXrkzZrVvLY6dPtOHp0/HVvJm7rVv/aokVS8+ZH1bJl8Pvm5/vLKffts4AY1qLA06WLjZszx85TjQcAAADOF0JcFfbcczb7df/9qcdu3WoBq1cvKSvLZqR27Uoed+qULW3Mz7cKjVEh7ne/s6NXqGTwYDsG7YubMcOWQnbsGH89KMTNmyd17Xog9H27dbPm3YcO+X3nBg0Kf07JD67vvGP78rxnBQAAACqalCHOcZx6juMUOY5T7DjOasdxfnz6+lOO45Q4jrPCcZwJjuM0innNdx3HWe84zlrHca4IvzvOxJo1Vk6/vDz12K1bpW99S2rRQnrjDX+mK8zy5XYsKPCrMq5fnzxu507roda2rfVwCwtxn34q/fd/Szff7De2btJEuuACacuW+LEnTkjvvhtc4bFJE2vQ7S2n3LJFKi2VuncPn170ipusWWMVLx0nvm1BkC5dLKD+3/9Z4LvggujxAAAAwPmSzkzcMUkjXNftKalA0pWO4wyUNF1Svuu6PSR9KOm7kuQ4TldJt0vqJulKSb91HKfm2Xj46ub3v7eCI5Mnpx47caKFvalTrQT/3/8ePd4LcT162Eyc5FdrjOWFqTZtLMSVlMRXjvR4FSF/9CP/muPYnrvEELdypRVL8Rpox3Icey/vfefOtWNUiPP2s61ebSGua9f4YilBuna1Y3m5dNll0WMBAACA8ylliHPN6XqEqn36j+u67jTXdU+cvr5AUrvTP4+R9Jrrusdc190oab2k/p/xc1cJEydKf/tb+uMLC+34yiupx06YYMU6evaUhg61ma4oy5fbDNxFF1kTa8cJnonzljW2aWPl/U+etKWLiWbOtOWWiQVC2re35tixFiywY9iSx4wMP1DOmSM1aCBlZR0K/SxZWTZ7t3Kl3TvVUkrJwut//7f0ve9JX/1q6vEAAADA+ZKiE5Y5PZO2RFK2pOdc101s23yvJC+OtJWFOs/Hp68l3vMrkr4iSS1btlShl1AqkLKysrP2XKdOSffdN0gHDtTWiRNFatv2aOT4Awdqqbh4iC688KTeequG3nxznho2PBE4tqyspmbNGqJbb/1Y7777kdq1a6/Jk7M0fvw8NWmSvBbTdaXCwkHKz9+vwsI1kqQWLQZq3rx9KiwsiRs7a1ZrSZ21efN8HTxYR1If/f3vKzVkyO64zzZt2hANGrRb774b//patTprw4YmKiyc/89rEybkqXHjJtq0aZ5KS5M/T5Mm2Zo/v7VmzXpfs2f3Unb2KR05cjDyu2nfvo/++tda2ru3vho1KlFhYYpeCPKXXJaUxDcLx5k5m3/d4F/H91Jx8d1UXHw3FRPfS8XFd3MOua6b9h9JjSTNli2j9K59X9IESc7p8+ck3RXz+5ck3Rx13z59+rgV0ezZs8/avefMcV2LT677uc+lHj9hgo390Y/sOH16+NiJE21MYaGdL1hg53/7W/D4RYvs96+84l+77DLXHTgweewPf+i6juO65eWuu3u3ve7pp+PHLF1q18eOTX79E0/4r/fk5LjumDHhn+fFF+1+69a5bqNGrvvgg6m/m89/3v/fd9WqyKH4jJ3Nv27wr+N7qbj4biouvpuKie+l4uK7+fdIWuymmcvOqDql67r7JBXK9rrJcZy7JV0r6c7TbyzZzFv7mJe1kxRTWxCS7VGrU0e69VZbehhWzt8zZYotI/QqTS5bFj529mypXj1pwAA7793b3mvJkuDxEydKNWpI117rX8vODt4Tt2yZ/a52bSs60qSJtG5d/Jjx4+1+l1+e/Pr27e2zenvc3n/fXj9sWPjn8QqjzJxpLQM6dw4f6/E++5e/7O93AwAAAKqCdKpTNvcqTzqOU1/SKEkljuNcKelxSde7rns45iWTJN3uOE5dx3EyJeVIKvrsH71ymzHD+qcNGybt3m2NrsOcOiVNmiRdeaXtRWvfPjrEFRbaPrB69ey8dm0r3x9U2n/7dumPf7SiIk2b+tezsqwS5YGYSv5eFckRI/xrubnShx/6564rvfqqNGqUAvu4tT8d77dssbHf+IZdi9qH1q2b7dF74w07TyfEPfSQtHatFYMJa/INAAAAVEbpzMS1ljTbcZwVkhZJmu667luSfiOpoaTpjuMsdxznBUlyXXe1pNclrZE0RdLDruuePCtPX0mVl1ug6t3b+rJJfnXIIEuWWG+266+38169wkPcnj1W9j+xwqLXzDrRrbfaa37xi/jrXpuB2Nm4JUusf1xsiMvJiZ+Jmz9f2rRJuuuu4Ofr0MGOH31k45Ytk7797eiS/hdcYM8zc6adpxPiate2gAkAAABUNelUp1zhum4v13V7uK6b77ruk6evZ7uu29513YLTfx6Iec1PXdfNcl23s+u675zND1BRuK704osWTlJZu9ZmtXr0sD+OEz2zNmmSVLOmdPXVdt6rl93jUECBxtdft2e56qr46127WhXJozH1U/bssWqP3/mONHBg/PigNgOzZ9tx+HD/Wk6OzSIePuw/a61a0pgxwZ8lJ0dq3lyaNk1atcqu9ekT+tH/6cYb/Z+9IAgAAABUR2e0Jw7h5syx/WqXXWazZlFWrLBj9+62zy0nJzrETZxobQK85Y49e1pQC5pZe/FFC4aJwchrZh279HHePDteemnyfbwQF9tmYMECm91q0cK/5s12eeOmTJGGDLFWBUFq1rS9d2+/LS1datcS2xAE+X//L/4eAAAAQHVFiPuM/O53Fsg+/tgackdZscKW+3nLArt3t8bUQTZutH5n3lJKyS/UkbjHbfVqW/J4333J+8C6dEl+zZw59hxeaf34fi6DAAAJoUlEQVRYDRtaWIudiVu6NDkc5uTYcd066yFXXJw8C5hozBhp/37p2Weljh3DA1+sZs2sGMzEianHAgAAAFVZWn3iqjPXtcIjzZqFjzlwQBo3TvrSl2zf1sqV0fcsLrYgVru2nWdk2MyU6yaHLy+0xIa4rCx7beJM3OTJdrz55uT3zM21e8eGuLlzLZTVrx/8nFlZ/gzbzp1WjKR37/gxsSFu9+lWcalC3OWX25LKnTuTl3FGuemm9McCAAAAVRUzcRFOnHB01VUWOILK7XtmzLC9ZrffLuXn+3u9gmzdakEvtvBIhw72+l27kse/+qrtgfMKjUi256xz5+QQN2WKzeq1TWqtbkEtM9MPcYcOSUVFVpUyTF6eze65rr/cMzHENWwotWplyzT/8hcLi927h9/Te5bvfMd/PQAAAID0EeIizJjRUlOn2s9R1SOnTLElgYMGWYjbsEE6ciR47HPPSSdPSl/7mn/NK9SxeXP82FWrbHnk3Xcn3yex2mRZmfVcu/LK8Ofs2tUPce++a1Uyg3q5eQoKbLZs+3Y/xHnVNGPl5EizZtk977wzvZL+Dz8s3Xuv9PjjqccCAAAA8BHiIixZ0lgXXmg/xxYEibVypS1jHDXKljh262YFREpKkscePmz75caM8QuHSH6IKy2NH//HP9qs2x13JN/LqzbphcXZs6Xjx6NDXJcufmXMadOsj9zQoeHjCwrsWFxs++eys6XGjZPH5eTYsztO8LMGqVtXeukl/z0AAAAApIcQF8J1peXLG+naa63BdlCI27DBKkF+8ol0ww12LT/fjkGFSl591cr6P/po/PWgmbgTJ2z81Vfbcs5EXbvGV5ucMsX6qQ0ZEv6ZunSx2beNGy3EDRvmNwQP0qOHHRcssJm2sIDYpo0df/jD+GWfAAAAAD57FDYJsWGDtGtXXQ0fLu3YERzi3n3XjtOm2UycZLNStWsH74t77jnbU5a4D61pU9snFhvipk+3ZYz33BP8fF6FyjVrrOXA1KnWhLtu3fDP5FWonD3bllV+6UvhYyWpUSMruvLsszaL6PWpS/T1r9vM4he/GH0/AAAAAP8+ZuJCeI2tL7vMinUEhbh586QmTaSRI/19YF7rgMQQt3attRa4557kPWOOY7NxsSFuwgTp4oula64Jfr6cHKlGDQtx69ZZ6IxaSin5Ie755+04bFj0eEnq29dmD+vVi2/yHat5c/tcNfh/EwAAAHDWMRMX4oYbpE8+Wa3c3G7KzbXKkXv2WGjzzJ1rxUwSw0t+vi1BjDVhgn/fIB06xO+JmzvXlkbWqRM8vm5dW7r4wQfS2LEWBK+7LvozXXyxNGCAtHChdOGFwUVKEv3mN/YZW7YMb0UAAAAA4Nxh7iRE8+bS8OE75Tj+0sWiIv/3u3db8ZKgPWj5+dKmTVYx0jNunNS/v9S+ffD7ZWXZjJrrSnv32gzb4MHRz9i1qxUdeekl683m7a2L8s1v2nHwYL9PXZSWLe01d96ZeiwAAACAs48Ql4YRI2wG7pVX/Gtvv+3/LlG3bnb0WgCsWGGtAj7/+fD3yM+X9u+3IineLF5UkRLJQtz69dK2bdIDD6T1UXTTTbZ/7wtfSG88AAAAgIqFEJeGunWlu+6yJZG7d9u111+3ma/+/ZPHexUqvX1xv/+93SMqOMW+Zu5cqWZNqV+/6OfKy7PjFVdI116b3mepVcuKphDiAAAAgMqJEJem226z8vxz5thyx2nTpM99LrixdWam7TlbutSWR77+uu2Fa9o0/P7e7N2qVVYwpaBA/+xRF+bmm6UXX5QmTkyvwTYAAACAyo/CJmnq2dOC0vLlVsjk+PHwQiI1a1oT7dmzbanjp5+mXhrZrJnUqpXdf+FC6ctfTv1MF1wg3XffmX8WAAAAAJUXM3FpuvBCK+tfXGwhq2ZNqU+f8PEjRtieuGnT7Lxnz9TvkZ8v/fnP1pMtVVETAAAAANUTIe4MFBTYTFlRkQWuqOWOXsGTZ56xY48eqe8f234g1cwdAAAAgOqJEHcGevaUNm6UZsywfmtRevWyJZLFxVYApVGj1Pd/6CFrHJ6XJ7Vr99k8MwAAAICqhRB3Brzm2K4bXJUyVs2a0s9+dmb3dxxbfllc/K89HwAAAICqj8ImZ2D0aOm3v7WQdeONqcffd58tv7zyyvTfo0YNqU6df/0ZAQAAAFRthLgzUKuW9OCD6Y+vUUN67rmz9zwAAAAAqh+WUwIAAABAJUKIAwAAAIBKhBAHAAAAAJUIIQ4AAAAAKhFCHAAAAABUIoQ4AAAAAKhECHEAAAAAUIkQ4gAAAACgEiHEAQAAAEAlQogDAAAAgEqEEAcAAAAAlQghDgAAAAAqEUIcAAAAAFQihDgAAAAAqEQIcQAAAABQiRDiAAAAAKASIcQBAAAAQCVCiAMAAACASsRxXfd8P4Mcx9kpqfR8P0eAZpJ2ne+HQCC+m4qL76Zi4nupuPhuKi6+m4qJ76Xi4rv593R0Xbd5OgMrRIirqBzHWey6bt/z/RxIxndTcfHdVEx8LxUX303FxXdTMfG9VFx8N+cOyykBAAAAoBIhxAEAAABAJUKIi/a78/0ACMV3U3Hx3VRMfC8VF99NxcV3UzHxvVRcfDfnCHviAAAAAKASYSYOAAAAACoRQhwAAAAAVCKEOAAAAACoRAhxAAAAAFCJEOIAAAAAoBIhxAEAAABAJUKIAwBUG47j/MhxnMcifn+D4zhdz+UzAQBwpghxAAD4bpBEiAMAVGg0+wYAVGmO43xf0hclbZG0U9ISSfslfUVSHUnrJX1BUoGkt07/br+km0/f4jlJzSUdlnS/67ol5/L5AQBIRIgDAFRZjuP0kfSKpAGSaklaKukFSS+7rrv79Jj/lLTDdd1nHcd5RdJbruuOO/27mZIecF13neM4AyT93HXdEef+kwAA4Kt1vh8AAICz6BJJE1zXPSxJjuNMOn09/3R4aySpgaSpiS90HKeBpMGS3nAcx7tc96w/MQAAKRDiAABVXdCSk1ck3eC6brHjOPdIGh4wpoakfa7rFpy9RwMA4MxR2AQAUJW9J+lGx3HqO47TUNJ1p683lLTNcZzaku6MGX/w9O/kuu4BSRsdx7lVkhzT89w9OgAAwdgTBwCo0mIKm5RK+ljSGkmHJH379LWVkhq6rnuP4zhDJP1e0jFJt0g6Jel5Sa0l1Zb0muu6T57zDwEAQAxCHAAAAABUIiynBAAAAIBKhBAHAAAAAJUIIQ4AAAAAKhFCHAAAAABUIoQ4AAAAAKhECHEAAAAAUIkQ4gAAAACgEvn/a1Dvyu6BTW4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "trace=['CO2_concentration_moyenne_mensuelle','filtered_data']\n",
+    "couleur = ['blue','red']\n",
+    "j=0\n",
+    "for i in trace:\n",
+    "    Monthly_data.plot(x = 'date',y = i, figsize=(15,8), color=couleur[j])\n",
+    "    j=j+1\n",
+    "    plt.grid()"
+   ]
   }
  ],
  "metadata": {
-- 
2.18.1