Readme.md

Data experimental del laser rojo.

En el notebook de jupyter se muestran las graficas de la data obtenida del espectrometro. Cada punto de dato corresponde a un valor proporcional a la intensidad de la luz (valor medido por un ADC de 8 bits) en uno de los fotodiodos del CCD lineal.

espectrometro.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import serial\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import textwrap\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAAAAAAAAAgKH4P+la0NgbTui6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714ad73898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714ad73208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7179874160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n2h1R4QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d164f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAzMT/AwdEBSBoQt+/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d30e198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714ad7de48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM3\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAgIH4fxSsiWSC6V0eAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714ad7de10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmUZGV5P/Bv98yAgwwgbjDgCMQ9BhQCDP6O2BjUGEzM\nRjTRmLjGxGjimojbcDQLcYsYwUSNWxISJZhoEuLeuBAZEEFHBAWj6CCIE5YBYWaYqd8fb1/rdk1V\nd1V3dVff6c/nnDm1V71Tfavqre99nrcSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAJBlbzAc7\n6qijWpdffvliPiQAAADAnu7yJI+Y750sakiUpNVqtRb5IWmqDRs2ZMOGDaMeBg1gW2EQthf6ZVth\nELYX+mVbYRC2F/o1NjaWDCHjGZ//UAAAAABoOiERAAAAAEIilq6JiYlRD4GGsK0wCNsL/bKtMAjb\nC/2yrTAI2wuLzZpEAAAAAA1mTSIAAAAAhma2kGhVkg8m+VySi5L8YpJHJtmc5LNT/06duu5zk1yc\n5H+SnLIQgwUAAABgYcxWivS7SY5M8pIk90hyeZLTk+yf5C216x2U5BNJjkmyOskXkvxsku0d96fd\nDAAAAGCIFqvd7MNJXlu77o6UIOiUJBckeXeSfZMcl+SLU5ffmuTqlHAJAAAAgAaYLSS6PcltSdak\nBEavSrIxycuSPCbJt5O8buryW2q325pSbQQAAABAA6zs4zr3S3Jeknck+eeU8KcKhD6S5O0paxat\nqd1mTZKbut3Zhg0bfnJ8YmLCT/oBAAAADGBycjKTk5NDv9/Z+tXum2QyyR+kLFKdlIWpX5SySPUL\nkxyS5K1JPpnk2CR3S/KlJEfFmkQAAAAAC2pYaxLNdgdvS/n1sqtq5/1pkjenrD/0gyTPS2lJe87U\n8fEkf5ZSZdRJSAQAAAAwRIsVEg2bkAgAAABgiBbr180AAAAAWAaERAAAAAAIiQAAAAAQEgEAAAAQ\nIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAA\nABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEA\nAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECER\nAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAR\nEgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAA\nECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAA\nAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIB\nAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAh\nEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAA\nERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAA\nABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREA\nAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABES\nAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQ\nIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAACQ2UOiVUk+mORzSS5K8otJHpDk\nC1PnnZVkbOq6z01ycZL/SXLKQgwWAAAAgIUxNsvlv5vkyCQvSXKPJJcn+UqSN6eERGcn+XiSLyX5\nRJJjkqxOCZF+Nsn2jvtrtVqtIQ0dAAAAgLGxsWT2jGdWK2e5/MNJzp06Pp5kR5KjUwKiJDk/yeOT\n7EzyxanLdyS5OiVcumS+AwQAAABg4c3WbnZ7ktuSrEkJjF7dcZutSfZPsl+SW7qcDwAAAEADzFZJ\nlCT3S3JeknckOSfJX9Uu2y/JzUluTQmSKmuS3NTtzjZs2PCT4xMTE5mYmBhkvAAAAADL2uTkZCYn\nJ4d+v7P1q903yWSSP0jy2anzPpqyJtEFSd6Z5NMp7WefTHJskrulrFF0VKxJBAAAALCghrUm0Wx3\n8LYkpya5qnbeHyU5M8leSa5I+VWzVpLnJHleSjvanyX5SJf7ExIBAAAADNFihUTDJiQCAAAAGKJh\nhUSzLVwNAAAAwDIgJAIAAABASAQAAACAkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAI\niQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAA\niJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAA\nAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkA\nAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQ\nCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACA\nCIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAA\nAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgA\nAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJ\nAAAAAIiQCAAAAIAIiQAAAACIkAgAAACACIkAAAAAiJAIAAAAgAiJAAAAAIiQCAAAAIAIiQAAAACI\nkAgAAACACIkAAAAAyAhColZrsR8RAAAAgNkIiQAAAADQbgYAAACASiIAAAAAIiQCAAAAINrNAAAA\nAIhKIgAAAAAiJAIAAAAg2s0AAAAAiEoiAAAAACIkAgAAACDazQAAAACISiIAAAAAIiQCAAAAINrN\nAAAAAIhKIgAAAACikggAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAgQiIAAAAAot0MAAAA\ngKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAgQiIAAAAAot0M\nAAAAgKgkAgAAACBCIgAAAACi3QwAAACA9B8SHZ/ks1PHH5nk+1OnP5vk1Knzn5vk4iT/k+SUXnek\nkggAAABg6VnZx3VekeTpSW6bOn1MkrdM/asclOSFU5etTvKFJJ9Msr3zzoREAAAAAEtPP5VEVyf5\n1SRjU6ePSakUuiDJu5Psm+S4JF9MsiPJrVO3OXLYgwUAAABgYfRTSXReksNqpy9K8ndJvpLktCSv\nS3JZkltq19maZP9ud/amN23ImjXl+MTERCYmJgYcMgAAAMDyNTk5mcnJyaHf79jsV0lSQqJzkpyQ\nEv5UgdBDk7w9yduS/HySF0ydf16SNyS5tON+Wps3t7J27TxGDAAAAMBPjI2NJf1nPD3N5dfN/jvJ\nsVPHT05ySZKNSR6dZO+UEOmhSTZ1u7E1iQAAAACWnn7azSpVvPP8JO9IWX/oB0mel7Ko9ZlJPp8S\nPJ2WLotWJ0IiAAAAgKVo3qVIA2p973utHHroIj8qAAAAwB5qlO1m86KSCAAAAGDpERIBAAAAsPgh\nEQAAAABLj0oiAAAAAIREAAAAAGg3AwAAACAqiQAAAACIkAgAAACAaDcDAAAAICqJAAAAAIiQCAAA\nAIBoNwMAAAAgKokAAAAAiJAIAAAAgGg3AwAAACAqiQAAAACIkAgAAACAaDcDAAAAICqJAAAAAIhK\nIgAAAACikggAAACACIkAAAAAiHYzAAAAAKKSCAAAAIAIiQAAAACIdjMAAAAAopIIAAAAgAiJAAAA\nAIh2MwAAAACikggAAACACIkAAAAAiHYzAAAAAKKSCAAAAIAIiQAAAACIdjMAAAAAopIIAAAAgAiJ\nAAAAAIh2MwAAAACikggAAACACIkAAAAAiHYzAAAAAKKSCAAAAICoJAIAAAAgKokAAAAAiJAIAAAA\ngGg3AwAAACAqiQAAAACIkAgAAACAaDcDAAAAICqJAAAAAIiQCAAAAIBoNwMAAAAgQiIAAAAAot0M\nAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAgQiIAAAAA\not0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAgQiIA\nAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAg\nQiIAAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIA\nAAAgQiIAAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICo\nJAIAAAAgQiIAAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAA\nAICoJAIAAAAgQiIAAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLd\nDAAAAICoJAIAAAAgQiIAAAAAot0MAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAA\nAKLdDAAAAICoJAIAAAAg/YdExyf57NTxByT5QpLPJTkrydjU+c9NcnGS/0lyyhDHCAAAAMAC6yck\nekWSdyXZe+r0W5KcluTElIDoyUkOSvLCJI9K8oQkf5Fkr253pt0MAAAAYOnpJyS6Osmvpl0xdHRK\nFVGSnJ/k5CTHJvlikh1Jbp26zZFDHSkAAAAAC2ZlH9c5L8lhtdNjteNbk+yfZL8kt3Q5fzcf/vCG\nfOMb5fjExEQmJib6HiwAAADAcjc5OZnJycmh3+/Y7FdJUkKic5KckOR7Se43df6TUyqJPpHk55O8\nYOr885K8IcmlHffTOuecVp761HmMGAAAAICfGBsbS/rPeHqay6+bfSXJY6aOPzGl9WxjkkenrFu0\nf5KHJtk038EBAAAAsDj6aTerVEtOvzRlIeu9klyR5Nypy85M8vmU4Om0JNuHN0wAAAAAFtK8S5EG\n1Pqnf2rlN39zkR8VAAAAYA81ynYzAACWiNe/PjnwwFGPAgDYEwiJAAAabHIyuemmUY8CANgTLHpI\n1GrNfh0AAPqzbduoRwAA7ClUEgEANJiQCAAYFiERAECDCYkAgGHRbgYA0GBCIgBgWFQSAQA02J13\njnoEAMCeQkgEANBg9UqiViv58Y9HNxYAoNm0mwEANNhtt7WPv/Wtyd3vPrqxAADNppIIAKDBbr89\nWb26HL/wwtGOBQBoNiERAEDDHXxwObzhhtGOAwBoNu1mAAANt+++5dAi1gDAfKgkAgDYQ6xYMeoR\nAABNJiQCANhDCIkAgPnQbgYAsIcQEgEA86GSCABgDyEkAgDmQ0gEANBwVaX2uJkdADAP2s0AAPYQ\nKokAgPmwvwkAYA8hJAIA5kNIBACwhxASAQDzod0MAKDhrEkEAAyDqQQAwB5i5cpy+NGPjnYcAEAz\nCYkAAPYQVbvZN74x2nEAAM2k3QwAYA9RtZsdfPBoxwEANJNKIgCAhutck+iAA0Y3FgCguYREAAAN\nV4VE1eGuXaMbCwDQXNrNAAD2EFU4JCQCAOZCJREAQEP1qiASEgEAcyEkAgBoqG4h0fi4kAgAmBsh\nEQBAQ3VWDrVaycqVyVOekrzsZaMbFwDQTNYkAgBoqG5tZitXluMXXjiaMQEAzaWSCACgoTorieoh\n0YoVoxkTANBcQiIAgIbqXJOoajdLhEQAwOC0mwEANJRKIgBgmFQSAQA01ExrEgmJAIBBCYkAABqq\n16+bJUIiAGBw2s0AABpqpkqi6hAAoF8qiQAAGqpeQVSdVkkEAMyVkAgAoKGsSQQADJN2MwCAhrIm\nEQAwTCqJAAAayppEAMAwCYkAABqq1UrGx6eHRVUFkUoiAGBQ2s0AABqqCoW6tZuN2xUIAAzI9AEA\noKGqUKjebrZqVTmukggAGJSQCACgoToriaxJBADMh3YzAICGarVKSGRNIgBgGFQSAQA01ExrEgmJ\nAIBBCYkAABrKmkQAwDBpNwMAaKhuaxJV4ZBfNwMABmX6AADQUNWaRN3azQAABiUkAgBoqKpyqNVK\nHvCA5KtfbYdEY2OjHRsA0DzazQAAGqr+62bXXFPOU0kEAMyVSiIAgIbatausPVSvGhISAQBzJSQC\nAGioVktIBAAMj3YzAICG2rWrBET1XzJbtaocWpMIABiUSiIAgIZqtXYPiVQSAQBzJSQCAGioqt2s\nW0ikkggAGJR2MwCAhurWbqaSCACYK5VEAAANNdPC1SqJAIBBCYkAABpqpoWrAQAGpd0MAKChZlqT\nCABgUCqJAAAayppEAMAwCYkAABpqpjWJAAAGpd0MAKChZlqTyMLVAMCgVBIBADTUTGsSCYkAgEEJ\niQAAGmrQNYluv11VNwDQm3YzAICGGnRNon33Td73vgUfFgDQUCqJAAAaqlslUXW8V7vZtdcu/LgA\ngGYSEgEANFS3NYlmW4to3OwPAOhBuxkAQEN1qySaLSSyoDUA0It9SQAADdVq9W4360VIBAD0IiQC\nAGiobgtXV8d7hUHazQCAXrSbAQA01EztZkIiAGBQpgkAAA0108LVvXbMCYkAgF5MEwAAGqpbJVGl\nV0hkTSIAoBftZgAADTXTmkS9CIkAgF5UEgEANNRcKom0mwEAvZgmAAA0VOeaRB/72PTLuhESAQC9\naDcDAGiozkqiE09sXyYkAgAGZZoAANBQnZVE/QRA1iQCAHoREgEANFRVSVQFP6tWtS/z62YAwKC0\nmwEANFTnr5v1ExKNjyc7diRXXrnw4wMAmkUlEQBAQ1WVRLt2ldP1drOZQqKzz04e+tCFHx8A0CxC\nIgCAhqoqiXbubJ83WzvZ+Hhy660LOy4AoJm0mwEANFRVSXTXXbtfZk0iAGBQKokAABqq1eo/JKpa\n0rpdBgCQCIkAABqrajfrJySqWtK2bVv4cQEAzaTdDACgoap2s/qaRJVeIdEf/mFy880LPzYAoHlU\nEgEANNRMlUSd6u1md9yxcGMCAJpLSAQA0FCDLFxdP10PjAAAKtrNAAAaapA1iSxcDQDMRiURAEBD\nDbImUT0kUkkEAHQjJAIAaKhulURjY92vKyQCAGaj3QwAoKGqSqJu8yuVRADAoFQSAQA0VFVJJCQC\nAIZBSAQA0FAqiQCAYdJuBgDQUFUlUT/8uhkAMBuVRAAADaWSCAAYJiERAEBDWZMIABgm7WYAAA1V\nVRJ1IyQCAAY18kqiRzwi+fSnRz0KAIDmabV2bzerQiMhEQAwqJGHRJdfnnziE6MeBQBA81i4GgAY\npiXRbmaiAgAwOAtXAwDDNPJKoiTZuXPUIwAAaJ5BFq6unxYSAQDdLImQyEQFAGBwKokAgGHSbgYA\n0FBzXZNISAQAdLNy1ANITFQAAOZi0EqiAw4o1zf3AgC6ERIBADTUIGsS7dqV3O9+yV57qeIGALrT\nbgYA0FBVJVFddbpbSDQ+rpIIAOhtSSxc7dfNAAAGt3NnsmJFfzvcqpBofFxIBAB0tyRCIhMVAIDB\nVcFPNyqJAIBBaTcDAGioqpKobmIi2XdfIREAMDiVRAAADdUtJLr3vZOzz+4dEmk3AwB6ERIBADTU\nrl27h0RJqRaaqZJIFTcA0M2SaDcTEgEADG7nzvaaRPVfOev8xbOk/UtoKokAgF6WRCWRvVkAAIPr\n1m5WsSYRADCoJRES7dw5/fTYWPKe94xmLAAATVEPiToriTpDolbLmkQAwMyWbLvZpk0LPxYAgCar\nr0k0W0ikkggAmM2SqCTqFhx166WfzZe+lNxxx9zGcOmlya23zu22AACjUF+TqK7XmkQqiQCAmSyJ\nkKjbRKXbhGc2J5xQfvJ1Lo45JnnVq+Z2WwCAUejVbpaoJAIABrdysR+w33azuYREve6/X9u3z/22\nAACLbZA1iaqQqDoOANBpSVQSdQt2+gmJnvWs5OMfn37eqlXDGRMAwFJXrUn0gAckD3tY+3xrEgEA\nc7HolUTddJuo9LMm0Xvfm9x+e/KEJ7TPW7kk/kcAAAuvWpPoK1+ZPncaH+8dErVa86u8BgD2XPOJ\nVC5NcsvU8W8n+Ysk70uyK8mmJC9IstsUZNB2s507SxvY6tX9DUolEQCwXFTtZvvuO/38btVCVUi0\na5dKIgCgu7m2m91t6vCkqX/PTvKWJKclOTHJWJIn93tnM4VEL35xss8+vW/bGTrNp5LIXjUAoEmq\ndrNO3SqJduwo1/XrZgBAL3MNiY5Ksk+Sjyf5dJL1SY5O8rmpy89PcnK/dzZTSPT1rw82MO1mAMBy\nUbWbdepWSbR1a7LfftYkAgB6m2ukcnuSNyZ5T5IHJvnvjstvS7J/txt2q9bZuXP38/pZk6jb9ebT\nbtbvYwIALAX1Xzer61ZJtHVrsmZNcsstQiIAoLu5hkTfTHL11PFvJdmS5JG1y9ckubnbDS+4YEM2\nbCjHJyYmkkx0fYB+ft2sm24TJQCAPdFMIVFnEHTrraWSqFuABAA0y+TkZCYnJ4d+v3MNiZ6Z5MiU\nxanXpoRCn0jymCQXJHliShvabh7zmHZINJO5hkTazQCA5aLXmkTdWspuvTXZf3/tZgCwJ5iYmJgq\nvClOP/30odzvXCOV9yR5b9prED0zpZroXUn2SnJFknO73bDfPVdVSDRbC1jn/fl1MwBguei1JlG3\naqHbbksOOcTC1QBAb3MNie5K8ttdzp+Yy511C46qcKjfUKla12iuFUiDPBYAwFLQq92sW7XQjh1l\nZ5pKIgCgl3lEKsPTLZzpN+ypwqQdO3rfFwDAnmiQhaur66okAgB6WfSQqNsvmXUzaEXQXXeVw/mE\nRH7dDABokl5rEnULgqrrqiQCAHpZ9JCoqviZzaBrElWTHZVEAMBy0WtNom5BUHVdv24GAPSy6CHR\n9u3Jm96UbNky8/VmWpPoX/4lueyy6edV1xt00nP55ck55wx2GwCApWCQdjOVRADAbBb9B+O3b09e\n/vJkv/2S5z2vnDfomkRPfWpy4onTz5trSPTHf5xMTs7ttgAAo7Rr19wqiao2fQCAupFUEtUPe+m3\n3ayi3QwAWG5are5zpZkWrh4bm30eBgAsTyMLieprE9UnMR/7WDkc9NfNOtcmAgDY07Va3edMMy1c\nPT4uJAIAulsSIVHdlVeWw34riIa5cLVfNwMAmmTXru7zl5nazcbG+v8hEQBgeVkS7Wb1YGft2nJ4\nxRWDBT5zXZMIAKCpZqok6rVwdb/V2gDA8rPkKon2378cnnVWctFF/d/vMCqJBEwAQJPMtZIIAKCb\nJRcS1YOabdv6v1+VRADAcjOXSiIhEQDQy5ILiea68LSQCABYbnpVEnVbuLqqJNJuBgD0suTWJJpr\nyGPhagBguWm1Bms3U0kEAMxkyYVEKokAAPpj4WoAYJhWLvYDztRutmpVcvTRM9/+aU/rfn4VLs01\nZAIAaJq5tJvVr9+rEgkAWJ5GVknUzV13JRdfPP28zonLF77Q/bbDqCRShQQANEmvSqJu7WbdKonM\nfQCAuiUREg2yJtG113Y/fxhrEgEANMlMlUSdc6JelUQAAJWRhURzmZT8+Me9L7MmEQCw3Mxl4WqV\nRABAL0uikqhfM01khhES6ckHAJpkLgtXqyQCAHpZEpVEw5igaDcDAJabuSxcrZIIAOhl0UOibdt2\nP6/fCUq3Xy7rrCCycDUAsFzMZeFqlUQAQC+Najeb6eftVRIBAMtNPwtXb9uW7NjRu5LottsWZ6wA\nwNK3crEfcMWKMkmZi24hUTUxqiZCMwVJAAB7kn4qiR7+8OSII7pXEu3cmaxZYycbAFAseki0117J\nHXfMbTKikggAoK3Xr5vVK4muvjq55ZbknvfcvZKo2nHX634AgOVl0dvN9tqrHPazcHXnZGWmkGiu\naxLVr29yBAAsdTffnPzXf5XjM7Wbffe7yVe/2j5v587dK4nuuqt9PwAAix4SrVrV/3U792pZuBoA\nWO7e/ObklFPK8ZnazZLkqKPap7u1m+3YUQ7nuhQAALBnWfSQqNtEZqZwpn6ZdjMAYLnr3IHWq5Ko\n8zbdFq6+8872/QAALHpItGLF3G/bz8LVQiIAYE/W+etkM1US1U93qyQ67LByKCQCAJIRhkT9hDn9\ntJt1XiYkAgD2ZPVQaL6VRPX7AQAYWbtZPwtXd05YFnpNIgCApa4eCs3062adt+m2cHXFmkQAQLLE\n28127Rp8TaL57Anz62YAwFI333YzlUQAQC9LOiTqrAqaaQLj180AgOVgvgtXd7u+kAgASJZ4SNQ5\n8elWCl1dbk0iAGA56Gw3U0kEAAxL49ck6rwPIREAsCdbiEoiaxIBAMkSqSTqFez0025m4WoAYDnp\nZ02ibiGRSiIAYDYjC4n6CXMGqSTSbgYALAdz+XWzxJpEAMDs9piQSCURALAc1AOgXu1mK1dOP121\nm9UriTq+nghZAAAcjklEQVTvBwBgZGsSJcmmTeVwPu1mnZcJiQCAPVk/C1d3C4mqdrPq9qtWtS+3\nJhEAkIx4TaKf+ZmZr9u5d6yfSiJ7wgCAPVk/C1d3rgFZX7i6CpXqIZH5EwCQLJFfN+tl167p11NJ\nBAAsd/1UEnUGR2Nj7etWl9WrjYREAEAygpCompjUJyPDaDezJhEAsBx0/rpZt0qiTlXFUfUvUUkE\nAOxuSYdEMy1c3XmZkAgAWA462826VRJ1qtYjStrXr1cSWZMIAEhG2G7Wzx6rmdYk6pzMaDcDAJaT\nqi2/n0qiVqsdEqkkAgB6GVklUT9hTqvVe00ilUQAwHJU7SjbsaP3wtWd6hVHFq4GAHpZEu1mvQzS\nbqaSCABYDqo5z/btvReu7jQ+vvsvntVPC4kAgCRZOftVhqtbu1mrldx5Z/v03nsn27Yld9yRfPGL\n7fNVEi2+669PPvCB5P/9v+RRj0o+85nk535u1KNaWv7rv5Kf+Znk5puTW29NLrss2X//5HvfK5fv\nvXeyenXy/Of3t7d3T7dzZ/K5z5Vt6xd+IfnoR8vrdvPmZM2a9vUe97jkwQ8e3ThH7bvfLVUCa9cm\nX/5ycuWV5X3xzjuTQw5JtmzpfrtTT03ue9/FHetS8pnPJFddVV6Pa9YkW7e2t6utW8trcN99d7/d\nE5+Y/NRPLe5YR21yMlm/Ptm4MbnrrrJNHXRQstdeyfHHJ9dck3zoQ+W69edwzZqyls3v/E55b1uO\ntmwp29r11yc/+lFyj3uU1+Y++yS33162sc73+61by/P62MfO//GrSqJt2/qvJBof3z1MqodEC7km\n0UUXJT/902W7Ofvs5LbbynO0Y0d5zir112uS/PjH5T3t8MMXbmxL0QUXlL/rNdckJ52UnHdeeY3W\nn5uZjI0lv/Ebyb3vvbDj7OUb3yjzoLVrR/P4dZ/+dHve+pnPlOq5444rc7N//MfkppvKZU94QvLA\nB45unIvtuuvKZ8C6dWU727mzHN+5M/nWt/q7j1FvZ0l5D7nwwuQxj1m8x9y+PTnrrHI4Pp787u8m\n3/xmcuml/d3+hBOSY45Z0CEuOddeW+b783HKKcvvs2CUFj0kqiYynZOR97ynfXz16jLx+cAHygSh\nUr+NSqLF8bSnlQ/VpHyJP/nk8qZYL1Ff7k45JXnxi5O3vnXm6z3xiclhhy3KkJa0L36x/SXpzDOT\nF72ofdlJJyUPe1iyaVP5ov/2t49mjEvBox9dgsY3vjF5+cuTe90redKTkve9r1z+W79VvpjWff7z\nZcLyB3+w6MNdElqt6SH2wQcnP/hB2aYOPDD5whfK+S94wfTbXXZZea7POGPxxroUnHRSmdxW21Rd\nq5W86lXJv/xLOf2MZ5Qv9uedlzzlKWVS/qAHDSfwaKIXvSj5p3/qffl++yW//dvt061W+VJRHZ+v\nas6zbdvcKomqMSxWJdH69clrXpPc5z7JS14y/bLq9XjRRckll7RPV8/ZG95QdsAsJxMT3c+vPiNn\nMzmZ3O1uybOfPcxR9e9hD0uOPrrs4BilO+8s89b/+7/kgAPanw/velcJH5/97OQ5z0m++tXk299O\n3vKW0Y53Mb3rXcmGDdPPe8hDynvKox/dXyB5wQVlp8Jzn7sgQ+zLRz5SPpMW8/vfZZeVeX/loova\nOwtmC0b/93+Tz342+dd/XdgxLjUf+EAJiY47bm63v/TSMp/7sz8b7rjobWQh0fbt7fNaremTk9Wr\ny17genVR0l8lkXLp4brllvbxH/ygHF5/fXK/+41mPEvNjh3l8Pbb2+fd//6lCqTT5s1ComT6c7Vx\n4/TLnvWs5OlPTz784eSccxZ3XEtNtXezeh98xCOSd76z/YX+bW8rwVHd619ftrPlqv5+lZQ9i//8\nz8njH19ee1VI9Dd/M/16739/8slPLsoQl4zqM/jmm3tf57bb2sfPPrvsCTzvvORNb0r+5E+W97ZW\nf26SUoF1/fXldXrZZaXytnM7q0KiYah2mlXtZnOtJKqfXuj505137j6vS9rP04YNJSSqP29nnVWq\ni5aTu+5qHz/88PKlslJ9Rs7m1a8e/etzKfzdqudg8+bpIcL27eW8+9+/bG/nnJP827+NZoyj0vl5\nmSTf/36Z15599vQKv15e+9rRb2fbtpXDfn/lcRg6/8+3317OO+us5KEPnfm2F164e1C+HGzeXKqP\nO3fS9evv/750IbB4RtZuVg+Jkuk/w1qVr9cnLIcdNr2c8fLLy+G55yY33NB+8z/99PIYr3tdKTE9\n7bTSQlDt8asmcElpybjhhvZ9zpRCH398qQTZf//kxBPLHueqDL+Xf/zH5BWvKCWdf/d37aT9l34p\nednLyv1s2lQmk9WH6aZNpSR7EK1W+TL0jneUtqdHPKK8kJ72tOQ//qOkths3lklkq1WS7gMO6K88\ntL4X6GlPK4e/8Avlw2NsrJz35S+3v7h++MPlA/fLXy5vmh/6UNlbU9/Ted11ye//finNfM1ryhff\nz32uPA+tVvki8sMflg+qbonzxo3l/E2bygf83e9ePiR+9mdL+eaKFWWv4yteUfYQPfWppXXp9a8v\nt/3859utKI99bPLv/17u7447yv9p06YyMbvnPWd/fqrJ3Lnnts875pjpIdGqVeX/8sxnluf+wQ8u\nex2uvLI83pYt5ct+9X9asaJsD0ceWT7Eb7yxPF9vf3t53eyzT7m/Qw9tTx77Tea/+tUySX/wg8tt\nt29PXvnKctmnP10e76qryv3deWe5ftL+AlQ9Tj3cGXSvQL1N6iMfmX5ZtU2uW5d86lPldVf55jfL\n323LlvJ3/f73k4svbm/f1Vguvri8BurVbtXlhx8+/7LoG25o/32rx16xonxpO+KI8resf2nbuLFs\nEzt2lOt8/ev9PWfVl9B3vrMcHnJIKY+vdNs+160rVUef+lR5/7zkkjKmxz2ubEff/373x9q4sby3\n3XJLqbipHmfYYfDxx5c9j1dcUfYyV6/l6rCbO+8srQuPfOTs919NFitVKHvooaWqqJd168p7ZbW9\nVdv+IYeUf4vpssvK63P16unb9bBVAXevcOz448t7QWWffdrPxUEHlefs1a+e/oX+4IOTf/iHUl3Z\nLQxYDFddVcZx9NHlc7/+3F1xRfk/7L///B/nkkvK4RFHlAqEhz+87El+yEPK3/ABD+h92/r72ooV\nyQc/mPz1X7f/3uPj5bPg2mvLZ8yTnlQ+M+rqlUT9tpuNje1eSfTgB7ff5/sJiY45pnx2/fjHybHH\ntt+D+/G+95Xqlrp6NeRMr7XqOfv618vr+eUvL8/bHXf099gLYXy8PB8XXzzc+62HRMcfPz0k6twx\n0Mu6deUL/H/+Z/u86m++WG3v3/rW9G29snFj+7OyOn300dO/BwxL9Tl66qml4qVyxhnlvWvdunJ6\n3brkv/+7Pd4rrii3vcc9SpXpb/1WmQONykyfkXP17W9PP33YYWWecPe79xcQJe3PgfPPn35+fV62\n0H74w/Zj1isjF+I5q9x44/TT559ftq9DD539tuvWlc+IztfGC15Q5nsL2fY7m/HxMjfoXLtuGK6+\nunyPnqt168r3tfrzdtddZb466HP25CeXfICZLZlKovoXuiokqj7QTj21hA/dqjMOPLC8mdcnN697\nXTk844wysapPrvbbr328HhAlvfeotlrlzaZ6w3vlK8t4ZvPBD5ZApLrNc59bNuiPfawEIieeWCYX\n9b0t558/eEi0ZUsJPi65pExQL788+c53ypeepIRSGze2n8+bbioBTj+VGmNj7RCmeuOoXox//uft\nVqEqJDrjjOnB0hlnlL9f/bm99NLyQk/KJL5Khr/3vfIGW0/on//86aXV27aVQOxJTyr/p//93/aX\nka99rQQdW7aU/98rXlHaGKsJ1mteM/3/tnVrexydH2Y33lhCvn7c4x7tPTIrVpS/wV/9VXvdk333\nLdvajTeWCe1JJ5Xzb7qpbL9XXllOP/GJ08dRTdyT5M1vbh+vWjDrE8ejjy5tI7NZv74c1r/8/cVf\nlD0fr31t8pu/Wc5btWr6WKrJ0eMel/ziL7bvJynb8a//+uyPXbdyZfmitmVLCTv23rt8wN7nPuXy\nY48t5bjVZPm9722P5/LLy8T3V36lvH6e85z2ZU9/ejl+r3uVUDApwUg1vs2b51+hdOKJ7ePPeEZ5\nvOo1cf31pcLi934veelLy7a/fv3uJfePfnS5bCb19dtWrGj3YV97bdnmu030n/rU8rdstZK//Mvy\nnvDtbyd/+7fl+b3ggt1v993vllLtahv+v/9rX9YZ4s3He987vX3w1FPLc/fyl5fjv/Zr3dcUeOEL\ny3vPmWf29zgrV5b/69q15f3+JS8pr7Px8bIOQLf1iE48sQRr1d/xpS8th5s3l4nEYq4dsH59GeuZ\nZ7ZfZ3/0RwuzXlL1fr5iRdku7nOf8vevAs0VK8rzWE0Y16wpFaUrV5bPtF/+5en3NzFR3oevu66E\nRaOwfn3Zlqv31eOPb+/gWL++vO+///3Deay99y4hy403lvec7dtLCPKOd3Tfzq6/vnwW1j8P//RP\nyxeGc89N3v3ucj+nnVa+oF5zTfksqz6/66/d+ppEyeAhUeUDHyitSTfeOPtEe+vW6WtuVOFI/Tnu\npT53OPDA9mE9GHj2s8vkve6668rrsLrt+vXl8+vd7x7sc3ohnH56+Vu/8Y3lPX2YVqwoc69737u8\nHx1ySHlfqD4jZ/OMZyRHHTX9vOr95EtfGu5Yuxkf3/0XipPk4x8v2/Mtt7R33q5fX/5fna1Pw1Lf\n9qrtvzpd7Qg54YSytEI156ieq5tuKnOxT32qvfTCYvvEJ8pz9sY3Tt9RNF9jY+356wEHlPesW28d\nrBrn6U8vO6fr3v72EsC98pW7v54XSv1vnJT3qsc9rve8Yhjuc5/yXI2Nlc/Fffftr0Xv0EPL37Me\ncP/N35QqpNWry9xtVE4+uXz2LMR7xPh4fzv7ejnppLJTq/o7t1rldXvCCf3PDyujXEOrSRY9JKo+\nMOoh0Q9+MD0oqfY0XXNNOTzuuN6hzKMeVSYt9T0Eler2db32Jh97bKlUqH953muvMs7O8OhHPyqH\n9et2U2+rue22cv0q8b7qqvLva1+bfpsf/rB9v9Xjz+ab3yyHF1/c/iJR/1J65JG73+bAA7vv4RnE\nkUe2FyG76qoSLHSuG3DDDe3/a6Ue2tW/kN797uWDqu7kk7tXM1RB2gMfOP053Lat/bxXj9m5t6Sb\n1aunv2Hf857ze346v9AdcUT5V3fhhWX8mzaV07OVqM5k3br5jXfz5rJoY2ViYvqi8ZUHPWj3xzni\niLk/dq+97dUe2sqmTSXoSEp4tHZte49NfQ2aajKwdm17TA9/ePvyYWz3hx/e3rY6Jx8HHtheo+WE\nE3o/1uGHz30cM1X37L13e89ZZ1/8wQdPD/cqD3lI7/ub73NV97Wvtf+GSXssv/Ir5fC447o/XrUI\n91zHUp8M9HruVqwolYiV+ufEYx8783O0EO573+n/38c/vv8KgvmarXrsoIPK4X777f43Wbu27Oj4\nqZ8a7rYzH/e///Sx3Otewx9bVY1Q7X3vrJap3Pe+uy8q/7CHlTnMj35U3oNXrmxvs5dd1q74uvji\n8qVk9eryGVdVSFQ7SfoJia6/vnzOJu252N3uVt63bryxfH5fd115nO3by7/6zrTvfKf7/XY+x3PV\nLQQ5+ODu87ZLLilfGka5nT384WV7f8z/b+/+Y+2s6zuAv29dkS6jpOCUTGsgCMYS6ko7hOJGp6tY\nsEjRYRoDKakIGESzLIaFhf1h4h8iy2bCMFmZmz/5kcq9RkMlbu2UwpBmmoYYMhghbIOYZYG1EEIG\ndn98zpPz3NNzb89p7z3ntn29kps+595z73l6zud8n+95P9/v97m4+pDz5XDe+yeeOPNzM87nrLmg\nR2/NtI/Z49Db52jbsaNCunHtX3PitH2Car407fug+tXZww9XeLt27fies6Z9W7NmNPvQHAMG1fu5\nbPfumhr/6U+P932wZEkdWxbK8butt5/WWLZsYe7vsWDkIVHTQWlPC3jhhenzMzdsqJCjObO9enUd\nJJtwprF6dSXFd95Zt5ct667jkdQZ+M2baw2F5vE2b67O0LPPTg8PPv7xGgGwbl11fl97rc6wv/3t\n3X1uhrTt2lW3L7989v9r+4zd4sXd+59xRvLoo93b69Z1/+bUVH29/nrt32mnTR/9NJNTTqk5xHfd\nVbfbSfS553ZHYyU1ymEurhp1wQXdofbNh6jeDt7+/fX/bIKspBZCXb68Xqv267V1a40uefDBOjtx\n3339D1hnnlnTia69tg6aX/1qBSwPPFA1sH9/BT6Hen3abr21nvdXXqnX+5prBv/dYX3oQ3VmqBmt\n0DjvvBoVs21b3V66NLnpphqxtXx5t3PVuPnmGlFz6qkVpg1i69YaXfWBD0w/K3buuRXQNXVy2WV1\nwGqC1ttuq9ejCSCa99rKlcn73z/8czCs9tmHe+/tjmjas6c6l0uWVGflne+sfb/qqu79m/dvUqPL\njtTnP1/T/1asqMc7+eT6sLJ3b70m73hHdYCbcGrDhuosfelL1Y4tXjz3Z5372bSphvu/+GI9T+vX\n97/f0qX13F19dY3E27Rp8CvoDGPVqvr/33RThX5nnVXv72a0ykxt0jiuoPXJT3ankA7b+TtSmzd3\n264bb6w2fZCprwvB+vX1/hxkVON8+exn60z2xo0VeDQjN5PqgPfrZI7TRRfViJT167ujai69tJ7H\n22/v3u/yyw8e/ZxUSDTbmf+VK7ujUvft678AdBNq3XhjjVT8zGfqOPHBD9bvtqeenHBCHZ+/9a3q\nM33xi9Of4/l23XUVok1OjvZqRv1ceGGFfrNNLVxIbrll3HtQ/Zxk+sUVNmw49MjaUbv++hq18Mwz\n1RcatI81H1atOrquvLlmTR3rh50VMZcmJurz26hP8ByuNWvqNV67drz7cfPN3cEMR4Orrhrve/NY\nN+oLch/Yvv1APvaxGpHQDg6SGqr38svVibnhhhqKOsxq9b/6VX3oePLJ4UOQ116rjtLUVHXGnnuu\nPug9/viRdSonJuqDefPBf1Cvvlodsx/8oD70Dnr/pKYhjXqB5I0ba19ner0mJurD9GyLpAIAB7vn\nnu504LYdO6qP0F7HptfkZIW/H/5w3f/AgTq58rnP1fYll9SJi8aKFTWNf8WKetze6SQAwMI0UUOL\njzjjGdE68F3NsOF+Z8SagOGkkw7vEuvNEO3DmbPb/E5zRq3Zz2GHXvZzOAt4NmfOBz2D3r7foS6/\nOB8Geb3mci41ABwvZjrG3n33oaeaNdOV2gtDt3+nd8HoX/6y/n322dEv3A4AjN/Ip5udf34tcvz8\n87UezSmn1Fmqp56q0T/NlY++/OUagTOMRYtqatnhTg+YmuoOm168ONm+/cg7SLt3H7wWzaAmJ4eb\nljI5WSOi+q3PNN/uvPPg6VNte/cKiQDgcHzkI3WV1ImJ6itNTdWI4Zdemr4uWz8XXlj9g3PO6Q7N\nv/LK7lT2r3ylpoqfemr1V554oqb7n3HG9KuPAQDHh5FPNzswzPwxAAAAAGZ11E43AwAAAGDhERIB\nAAAAICQCAAAAQEgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIRE\nAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABE\nSAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAA\nQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAA\nAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgE\nAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECE\nRAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAA\nREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABA5j4kWpTka0keSbIzyZlz/Pc5juzatWvc\nu8BRQq0wDPXCoNQKw1AvDEqtMAz1wqjNdUh0RZITkqxNckuSO+b473Mc0SAyKLXCMNQLg1IrDEO9\nMCi1wjDUC6M21yHRRUl2dLYfS7Jmjv8+AAAAAPNgrkOipUn2tW6/MQ+PAQAAAMAcm5jjv3dHkn9J\ncn/n9n8kWd76+dOxThEAAADAXPr3JO8a9070ujLJ1zvbFyT54Rj3BQAAAIAxmUhyV5Ldna+zx7s7\nAAAAAAAAAAAAAAAAACwsi5J8LckjSXbG4tV0/WuqJnYmuTu10NbDSX6S5G/SXVz9uiSPJ3k0yWWj\n303G6H2p+kiGq48lSbZ37vvDJG8Z0f4yPu1aWZXkP9NtX/648321wuIk30y93o8l2RhtCzPrVy+r\nkvxXtC9M96Ykf5dqS36a5JxoW5hZv3rRtjCbt6YuDHZ2jpG25crUmyCpTvzkGPeFhePEVEjU9v0k\nf9DZvivJFUlOS7I31VFb2tk+YUT7yHh9IfV6P9K5PUx9/EmS2zr3/USSvxrNLjMmvbXyqVQNtKkV\nkmRLkr/sbC9L8lySqWhb6G9LDq6XrdG+cLCPJtnW2b441a5oW5hJb71MRtvCzBYneSDJk0nenXn+\nTLRoDnd8Nhcl2dHZfizJmhE9Lgvbe5P8ZpIfJfnH1BXxzkulnEnyYJI/SvJ7qYXQ/y/JviRPJ1k5\n6p1lLJ5OhcxNOj5MfbTbnR2d+3Ls6q2V1akzKP+c6oT9VpLzo1ZI7k+3s7QoVQ/aFmbSr160L/Qz\nleT6zvbpSV5M1Yq2hX566+WlaFuY2e2pMOiFzu157beMKiRamtrRxhsjfGwWrldSBX9JkhuSfLvn\n5/uTnJyqn//t832Ofd9L8nrr9kRr+1D10W531Myxr7dWHkvyp6mzc88k+YskJ0WtUMeel1P1cH+S\nP8/0Pom2hbbeerk1yc+ifaG/N5L8fZK/TvVr9VuYTW+9aFvoZ0uS/07yUOf2ROa5bRlVULMvVeDt\nx/31iB6bhevf0g2GnkryP0ne1vr50lSq3ls/J6XOznD8abcbs9VH7/eb73H8eCDJz1vbq6JW6Fqe\n5J+SfCPJd6NtYXbterkn2hdmtyU1HWRbammFhraFfrak6uVvUyGAtoVe1yZZn1qn6neT/EOS3279\nfM7bllGFRLuTXNrZviA1Pw6uTXJHZ/t3UkX7UCo9T5INqWF0P0vy+0nenEo+35PkiZHuKQvFzzN4\nfbTbnea+HD92pIbdJjWsdk/UCuVtqWPNF1JncBNtCzPrVy/aF/q5OsmfdbZfTY0S2RNtC/311suv\nU6OitS30ujjJuiR/mOQXSa5JHYeO+rZlIjWHbnfn6+zx7g4LxG+ke8WQn6QCxLOS7EotPrst3aF0\nn0oV/p4km0a9o4zV6ekuRjxMfSxJcl/qihE/Tl0RgGPb6enWyntTV33YmeQ7qXn9iVqhhvU/n+7V\nY3am5uzviraFg/Wrl/dF+8LBliS5N7WezCOpK+HptzCTfvWi78Kh7ExlKdoWAAAAAAAAAAAAAAAA\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgJP4f+HC6VrM8trEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d316eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d3169b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 115200)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAAAAAAMBS/B8WDBiomSV+AAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d2bcbe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 254)"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAAAAAAMBS/B8WDBiomSV+AAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f714d1c9320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f4b600e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)\n",
    "data_series.to_csv(\"./digital/data/laser_rojo.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAAAAAAAAAsBT/B02qCp/ph6G3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f1604efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f44319f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)\n",
    "data_series.to_csv(\"./digital/data/laser_rojo.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKIn/By9j3XbYl4q7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f15fa7c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAAAAAAAAAAAAAAAAUBD/C+oGXkTMogrmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f15fa7c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f15fd35c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(1):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 255)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfoAAAGCCAYAAAAIZAHlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0f1611d4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = pd.read_csv(\"./digital/data/laser_rojo_2.csv\", index_col=0, names=[\"I\"])\n",
    "plt.figure(figsize=[8,6])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "# ---- Style Stuff ---------\n",
    "\n",
    "# Ticks solo abajo y a la izquierda\n",
    "plt.gca().get_xaxis().tick_bottom()    \n",
    "plt.gca().get_yaxis().tick_left()\n",
    "\n",
    "# Elimina los bordes superior y derecho del marco\n",
    "plt.gca().spines[\"top\"].set_visible(False)\n",
    "plt.gca().spines[\"right\"].set_visible(False)\n",
    "\n",
    "# Indica los ticks\n",
    "l_y_ticks = np.arange(0, 254, 50)\n",
    "plt.yticks(l_y_ticks, [int(y) for y in l_y_ticks], fontsize=14) \n",
    "\n",
    "l_x_ticks = np.arange(0, 4000, 500)\n",
    "plt.xticks(l_x_ticks, [\"{:d}\".format(x) for x in l_x_ticks], fontsize=14)\n",
    "\n",
    "# Etiqueta de ejes\n",
    "plt.xlabel(r\"Pixel\", fontsize=14)\n",
    "plt.ylabel(\"Intensidad\", fontsize=14)\n",
    "\n",
    "# Rangos\n",
    "plt.xlim(0, 4000)\n",
    "plt.ylim(0, 255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data[data[\"I\"]>50])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIkAAAK4CAYAAADwRK1qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmUZHV9N+BPD8MwLMOMcWFEURYVVwZZXIhoxyXGYCRK\nNHGJG0sSl7xqiCdHjRlcowGjuCTGBZcIERWXgLgBzSYuOIASRETAAQQFZZkZYJaefv/49bWqa6qq\nq7qru2/PPM85c7qq7lK37tyquvWp7/dXCQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQJIMzead\nrVixYuyyyy6bzbsEAAAA2NpdlmT/6a5kVkOiJGNjY2OzfJfMVytXrszKlSvnejOYBxwr9MPxQq8c\nK/TD8UKvHCv0w/FCr4aGhpIBZDwLpr8pAAAAAMx3QiIAAAAAhETU1/Dw8FxvAvOEY4V+OF7olWOF\nfjhe6JVjhX44XphtxiQCAAAAmMeMSQQAAADAwEwWEm2f5LNJzkvy/SR/luSxSW5Mcs74v+ePz3t0\nkh8muSjJYTOxsQAAAADMjMlKkV6eZL8kb0hyrySXJTkuydIk72uab3mSbyU5MMmOSS5IclCSDS3r\n024GAAAAMECz1W72hSRvbZp3Y0oQdFiSc5N8PMkuSR6X5MLx6XcmuTolXAIAAABgHpgsJFqXZG2S\nJSmB0ZuT/CDJsUmekuSaJP8yPv2OpuXWpFQbAQAAADAPLOxhnj2SnJbkw0n+JyX8qQKhLyf5YMqY\nRUuallmS5LZ2K1u5cuXvLw8PD/tJPwAAAIA+jIyMZGRkZODrnaxfbbckI0lelTJIdVIGpv77lEGq\nX5vkAUn+Pcm3kxycZHGS7yVZEWMSAQAAAMyoQY1JNNkKPpDy62U/a7rtn5KckDL+0E1JjklpSTtq\n/PKCJO9MqTJqJSQCAAAAGKDZCokGTUgEAAAAMECz9etmAAAAAGwDhEQAAAAACIkAAAAAEBIBAAAA\nECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAA\nAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIB\nAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAh\nEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAA\nERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAA\nABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREA\nAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABES\nAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQ\nIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAA\nABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEA\nAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECER\nAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAR\nEgEAAAAQIREAAAAAERIBAAAAECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAA\nECERAAAAABESAQAAABAhEQAAAAAREgEAAAAQIREAAAAAERIBAAAAkMlDou2TfDbJeUm+n+TPkjwk\nyQXjt30kydD4vEcn+WGSi5IcNhMbCwAAAMDMGJpk+suT7JfkDUnuleSyJJckOSElJPqPJN9M8r0k\n30pyYJIdU0Kkg5JsaFnf2NjY2IA2HQAAAIChoaFk8oxnUgsnmf6FJF8cv7wgycYkB6QERElyZpI/\nTjKa5MLx6RuTXJ0SLl083Q0EAAAAYOZN1m62LsnaJEtSAqO3tCyzJsnSJLsmuaPN7QAAAADMA5NV\nEiXJHklOS/LhJKckeW/TtF2T3J7kzpQgqbIkyW3tVrZy5crfXx4eHs7w8HA/2wsAAACwTRsZGcnI\nyMjA1ztZv9puSUaSvCrJOeO3fS1lTKJzk/xnkrNS2s++neTgJItTxihaEWMSAQAAAMyoQY1JNNkK\nPpDk+Ul+1nTb/0tyYpJFSa5I+VWzsSRHJTkmpR3tnUm+3GZ9QiIAAACAAZqtkGjQhEQAAAAAAzSo\nkGiygasBAAAA2AYIiQAAAAAQEgEAAAAgJAIAAAAgQiIAAAAAIiQCAAAAIEIiAAAAACIkAgAAACBC\nIgAAAAAiJAIAAAAgQiIAAAAAIiQCAAAAIEIiAAAAACIkAgAAACBCIgAAAAAiJAIAAAAgQiIAAAAA\nIiQCAAAAIEIiAAAAACIkAgAAACBCIgAAAAAiJAIAAAAgQiIAAAAAIiQCAAAAIEIiAAAAACIkAgAA\nACBCIgAAAAAiJAIAAAAgQiIAAAAAIiQCAAAAIEIiAAAAACIkAgAAACBCIgAAAAAiJAIAAAAgQiIA\nAAAAIiQCAAAAIEIiAAAAACIkAgAAACBCIgAAAAAyByHR2Nhs3yMAAAAAkxESAQAAACAkAgAAAEBI\nBAAAAEDmICTavHm27xEAAACAyagkAgAAAEBIBAAAAIB2MwAAAACikggAAACACIkAAAAAiHYzAAAA\nAKKSCAAAAIAIiQAAAACIdjMAAAAAopIIAAAAgKgkAgAAACAqiQAAAACIkAgAAACAaDcDAAAAICqJ\nAAAAAIiQCAAAAIBoNwMAAAAgKokAAAAAiJAIAAAAgGg3AwAAACAqiQAAAACIkAgAAACAaDcDAAAA\nICqJAAAAAIiQCAAAAIBoNwMAAAAgKokAAAAAiJAIAAAAgGg3AwAAACAqiQAAAACIkAgAAACAaDcD\nAAAAICqJAAAAAIiQCAAAAIBoNwMAAAAgKokAAAAAiEoiAAAAAKKSCAAAAIAIiQAAAACIdjMAAAAA\nopIIAAAAgAiJAAAAAMgchEQAAAAA1I9KIgAAAABUEgEAAAAgJAIAAAAg2s0AAAAAiEoiAAAAACIk\nAgAAACDazQAAAACISiIAAAAAopIIAAAAgKgkAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAA\nAKLdDAAAAICoJAIAAAAgKokAAAAAiEoiAAAAACIkAgAAACDazQAAAACISiIAAAAAopIIAAAAgKgk\nAgAAACBCIgAAAACi3QwAAACAqCQCAAAAIEIiAAAAAKLdDAAAAICoJAIAAAAgKokAAAAAiEoiAAAA\nACIkAgAAACDazQAAAACISiIAAAAAIiQCAAAAINrNAAAAAIhKIgAAAADSe0j0+CTnjF9+bJIbxq+f\nk+T547cfneSHSS5KclinFakkAgAAAKifhT3M88YkL0mydvz6gUneN/6vsjzJa8en7ZjkgiTfTrJh\nYFsKAAAAwIzppZLo6iTPSzI0fv3AlEqhc5N8PMkuSR6X5MIkG5PcOb7MfoPeWAAAAABmRi+VRKcl\n2bPp+veT/FeSS5K8Kcm/JLk0yR1N86xJsrTdyk4+eWV+9KNyeXh4OMPDw31uMgAAAMC2a2RkJCMj\nIwNf79DksyQpIdEpSZ6YEv5UgdAjknwwyQeS/EmSV4/fflqSdyRZ1bKesa9+dSzPec40thgAAACA\n3xsaGkp6z3g6msqvm30jycHjl5+e5OIkP0hyaJIdUkKkRyS5fLobBwAAAMDs6KXdrFL9LtnfJvlw\nyvhDNyU5JmVQ6xOTnJ8SPL0pHQat9utmAAAAAPUz7VKkPo195StjOfzwWb5XAAAAgK3UXLabTYtK\nIgAAAID6mfWQCAAAAID6ERIBAAAAoN0MAAAAAJVEAAAAAEQlEQAAAABRSQQAAABAhEQAAAAARLsZ\nAAAAAFFJBAAAAECERAAAAABEuxkAAAAAUUkEAAAAQFQSAQAAABCVRAAAAABESAQAAABAtJsBAAAA\nEJVEAAAAAERIBAAAAEC0mwEAAAAQlUQAAAAARCURAAAAAFFJBAAAAECERAAAAABEuxkAAAAAUUkE\nAAAAQIREAAAAAES7GQAAAABRSQQAAABAVBIBAAAAEJVEAAAAAERIBAAAAEC0mwEAAAAQlUQAAAAA\nRCURAAAAAFFJBAAAAECERAAAAABEuxkAAAAAUUkEAAAAQIREAAAAAES7GQAAAABRSQQAAABAVBIB\nAAAAEJVEAAAAAERIBAAAAEC0mwEAAAAQlUQAAAAAREgEAAAAQLSbAQAAABCVRAAAAABEJREAAAAA\nUUkEAAAAQIREAAAAAES7GQAAAABRSQQAAABAVBIBAAAAEJVEAAAAAERIBAAAAEC0mwEAAAAQlUQA\nAAAAREgEAAAAQLSbAQAAABCVRAAAAABEJREAAAAAUUkEAAAAQIREAAAAAES7GQAAAABRSQQAAABA\nhEQAAAAARLsZAAAAAFFJBAAAAEBUEgEAAAAQlUQAAAAAREgEAAAAQLSbAQAAABCVRAAAAABESAQA\nAABAtJsBAAAAEJVEAAAAAEQlEQAAAABRSQQAAABAhEQAAAAARLsZAAAAAFFJBAAAAEBUEgEAAAAQ\nlUQAAAAAREgEAAAAQLSbAQAAABCVRAAAAABESAQAAABAtJsBAAAAEJVEAAAAAEQlEQAAAABRSQQA\nAABAhEQAAAAARLsZAAAAAFFJBAAAAECERAAAAABEuxkAAAAAUUkEAAAAQFQSAQAAABCVRAAAAABE\nSAQAAABAtJsBAAAAEJVEAAAAAERIBAAAAEC0mwEAAAAQlUQAAAAARCURAAAAAFFJBAAAAECERAAA\nAABEuxkAAAAAUUkEAAAAQFQSAQAAABCVRAAAAABESAQAAABAtJsBAAAAEJVEAAAAAERIBAAAAEC0\nmwEAAAAQlUQAAAAARCURAAAAAFFJBAAAAECERAAAAACk95Do8UnOGb/8kCQXJDkvyUeSDI3ffnSS\nHya5KMlhnVak3QwAAACgfnoJid6Y5GNJdhi//r4kb0ry5JSA6PAky5O8NskhSZ6Z5N1JFg16YwEA\nAACYGb2ERFcneV4aFUMHpFQRJcmZSZ6e5OAkFybZmOTO8WX2G8QGrlmTrF49iDUBAAAA0MnCHuY5\nLcmeTdeHmi6vSbI0ya5J7mhz+xbOOWfl71vOhoeHMzw83PXOjzwy+cIXtKkBAAAAJMnIyEhGRkYG\nvt5eQqJWm5su75rk9pTqoSVNty9Jclu7hYeHV2blyt7v7Le/7Xv7AAAAALZarUU3xx133EDWO5Vf\nN7skyVPGLz8rpfXsB0kOTRm3aGmSRyS5vN3CKoIAAAAA6qefSqIq3vmHlIGsFyW5IskXx6edmOT8\nlODpTUk2DG4zAQAAAJhJvYZE16X8clmS/DzJcJt5Pj7+DwAAAIB5ZirtZtPS2m42NJR87nOzvRUA\nAAAANJv1kKidyy6b6y0AAAAA2LbVIiQaHe08zUDXAAAAADNvztvNku4hEQAAAAAzr/aVRENDs7cd\nAAAAANuqWlQSbd7c3/wAAAAADFbtK4kAAAAAmHlCIgAAAADq0W4mJAIAAACYW7UPiQxcDQAAADDz\nZj0kajdIdbeQyMDVAAAAADOvFpVE3X7dDAAAAICZV4uQyJhEAAAAAHOr9u1mAAAAAMy8WlQSaTcD\nAAAAmFsqiQAAAACoRyWRkAgAAABgbgmJAAAAANBuBgAAAIBKIgAAAAAiJAIAAAAgNWk3a3cbAAAA\nALOnFpVE7W4DAAAAYPbUopIIAAAAgLlVi0oiAAAAAOaWkAgAAACAerSbCY4AAAAA5lbtK4kESAAA\nAAAzrxYhkSAIAAAAYG7Vot2sm6GhmdkOAAAAABpqUUkEAAAAwNzaqkKi738/ueeemVs/AAAAwNaq\n9u1m/YRKT3hC8qEP9bd+AAAAAGpSSTTI6qLR0cGtCwAAAGBbUftKon4tmPVHBAAAADD/bXWVRH4N\nDQAAAKB/tQiJBklIBAAAANA/7WYAAAAAqCQCAAAAoMYh0WmnJZs29b9+IREAAABA/2rRbtYuODri\niOTCC/tfv5AIAAAAoH+1rSTqd96KMYkAAAAA+lfrkGgqVBIBAAAA9K8W7WaDpJIIAAAAoH+1qCQa\nZHWRkAgAAACgf1tdJZF2MwAAAID+bXWVREIiAAAAgP7VIiQaJO1mAAAAAP3TbgYAAABA/SuJ+p1f\nSAQAAADQv9qHRO0cfHDy3ve2n6bdDAAAAKB/tWg36xQcjY21rwy6+OLkjDPaL6OSCAAAAKB/87KS\nqBshEQAAAED/ahESDTI40m4GAAAA0L9atJt1060VrR0hEQAAAED/alFJlCTXXJO89rXTX792MwAA\nAID+1aaS6EtfSj70oS1v7zf0UUkEAAAA0L/aVBJ1CoP6Ha9IJREAAABA/2oREg1y4GohEQAAAED/\natNuNqhwR7sZAAAAQP/mpJLowguTjRtnZv1TDZtWrUruvHOw2wIAAAAwX8x6SLRxY/KkJyWf+tTk\n8/bThjbdlrUDD0ze/ObprQMAAABgvpr1kOjuu8vf229v3DY21n8FUGso1KmNrR8bNkx/HQAAAADz\n0ZyFRGvXdp7nr/6q//WOjpa/gxwEGwAAAGBbUYuQqLWS6POf73+9VSWRkAgAAACgf3MWEq1ZM7Xl\n161rf/sg2s0AAAAAtlVzFhLdddfE29uNSdRaFbR+fbLLLu3Xq5IIAAAAYOpmPSRauHDqy27aNPk8\nQiIAAACA/s16SLTjjoNb17nnJjfdVC4LhwAAAACmbtZDou233/K21oGrO2mdZ3g4ed3rGuto/gsA\nAABA72Y9JKrMVJgjJAIAAADo36yHRJ0GqG53+yWXlJay5vnaXW53HQAAAIDezVklUat2IdFFF028\n3ksQJCwCAAAA6F8tKol61S4Aah2LSEgEAAAA0L85qyRqDYuq6+vXd15GAAQAAAAwM2pXSfSrXzUu\n9xIKVetTSQQAAAAwdbUIiZoHrr7xxsbtmzdvOV+7ZSebBwAAAIDuajNwdWXdus7TugVAwiEAAACA\nqatFJVHz7VMNgrSbAQAAAExd7SqJmnVrJesUBgmJAAAAAPo3Z5VEnQKf6VYSAQAAANC/hbN9h/20\nm01lUOp+w6I770xuu62/ZQAAAAC2NvO23azTvP2GRK98ZbLnnv0tAwAAALC1qcXA1WNj0x+4eqp+\n+9vBrxMAAABgvpnTSqKXvrT79NmoJAIAAABgjiuJPvvZLaf3W0nUGg4JiQAAAAD6N2chUWvb2aAG\nrgYAAACgf7UYuLrX8KfdfK3hkiAJAAAAoH+1GLi6+fZeK4k6hUJCIgAAAID+1a6SqFtI1Os6AAAA\nAOhPbSqJ2plKlZCwCAAAAKB/cxYSNYc5Q0PTH7jamEQAAAAAU1ebdrNeKoxmopJIqAQAAABQo3az\ndpVEraY6DQAAAIDualNJNNnldtfbTes3LOpnjCQAAACArVXtKom6MXA1AAAAwMyoTUhUaQ55Nm/u\nPG0qv3wGAAAAQHtz1m527bX9L9MuCBIWAQAAAEzfnFUSXXRR47bmXzeb7sDVQiIAAACA/tVi4Opm\n/baUGXgaAAAAYPpqMybRVAeurm578IM7zwMAAABAd7UIiTpVD01lvCEhEQAAAED/atdu1syg1AAA\nAACzoxaVRM23d6sk6kW/ywieAAAAAGpYSdTrr5t1mk/oAwAAANC/WlQSjY1NfeDqmdgeAAAAgG1N\nrSuJNm/uPK2X5fu9PwAAAIBtVe0qiXptN5vOPAAAAABMNOshUT8hzlQqifql3QwAAACgJiFRc1DT\nbXBq7WYAAAAAM6MWIVGngatnIyQCAAAAoOYDV/cSEk03FNJuBgAAAFCTkKjTL5ppNwMAAACYHbVo\nN2u+vdeQqLo8NNR9GQAAAAAmV4tKomZTaTdr/RW0fmg3AwAAAKh5JVFr+NNp2dHRyecBAAAAoLNa\nVBJ1qh7qdUyi1nazoaHk/PMHt30AAAAAW7tahERJb2MStZs/mVhJVLnmmv7uFwAAAGBbVpt2s0q3\nkOjKK9vP13x5ZGTKmwYAAACwzapFJdHYWCMQ6hYivfSljcvNwVBzJdGZZ06+nmYGrgYAAACoUSXR\ndNrNpvPrZtrNAAAAAGoSEq1bl7zylVtO7xb+dKokavWLXySHHtrfNlZOOSU59tipLQsAAAAwn9Si\n3ew3v2lc7rWSqNOYRK0uuKD866Rbu9nxxycnnNB5OgAAAMDWYuE0ll2V5I7xy9ckeXeSTyXZnOTy\nJK9OskXMM52Bq9vNNzbWvZJoMs33sXbt1NcDAAAAMJ9NtZJo8fjfPxr/d2SS9yV5U5InJxlKcvhU\nVjyoMYmmMtbQySf3vwwAAADA1mCqIdGKJDsl+WaSs5I8IckBSc4bn35mkqe3W3Cy8Gbjxt7mrYKh\noaHpVRL5dTMAAACAqbebrUvyb0k+keShSb7RMn1tkqVTWfGmTY3LvbabTaeSyK+bAQAAAEw9JLoq\nydXjl3+e5LdJHts0fUmS29stePvtK5uuDY//a2iuJOo2IHWvv4IGAAAAsDUZGRnJyMjIwNc71ZDo\nFUn2SxmceveUUOhbSZ6S5Nwkz0ppQ9vC0qUrc8cd7aYU/VYSJdrNAAAAgG3H8PBwhoeHf3/9uOOO\nG8h6pxoSfSLJSWmMQfSKlGqijyVZlOSKJF+cyoo3bSrBzdjY9Aau7pV2MwAAAICph0Sbkvx1m9uH\nJ1uwl4GrFywo1UHd5m2uHtJuBgAAADA9U/11sxkzlXYz1UAAAAAA0zPrIVEvlUTVOEHd5t1rr97X\nCQAAAEB3tQuJqjGJus37ta8lu+7a+zoBAAAA6K6W7WZVSHTdde3nqQa2rrQLiQRHAAAAAL2rXSVR\nc7tZJ80h0diYgasBAAAApqvWlUSd9FJJBAAAAEDv5n0lUWtgBAAAAED/aldJ1G9IlBiTCAAAAGC6\nahcSzXa72WT3BQAAALAtmPftZmNj0wuJVBwBAAAA1LSSaDLazQAAAAAGq3aVRP22m0134OrW+xIu\nAQAAANuihXO9Aa02bUoWdIiunv3s5MlP3rLdbPPmqd9fayg0OposrN1eAQAAAJhZ86qSaNGiZK+9\nBjtwdavpBE4AAAAA81XtQqLR0e7LDg0Jiabi1lv9khsAAADQWe0Grh4d7RxmCImmbs2aud4CAAAA\noM5qWUk0EyHRLbf0tn3NIdGqVb0tAwAAADDf1a6SqNuYRP2ERK23/fVf93b/W2slEQAAAEA3tQuJ\nZqqSaP363u5fSAQAAABsi7aZdrNeCYkAAACAbVHtKok2beo8TUgEAAAAMDPmfSXR2Fj7YKfd/dx1\nV1l/N5OFRHffndx442CDKQAAAIC5VrtKotHRZEGHrWoOib73vYm392LnnZO3va37PJOFRDvtlDzw\ngcmVV/Z2nwAAAADzQe1Col5/3az19l5ddVX36b22m91zT+/3CQAAAFB3tWw3a2fjxuQb3+g9JJpq\nO1h1/5Mtr90MAAAA2JrULiTqVEk0MlL+TreSaDJVJdFk65xvA1w3j+EEAAAA0Kp2IVG3gasrsxES\nTRYCzbeQqNfHBQAAAGybajcm0WQhkUqiqakez3zbbgAAAGB2CIlabO2VRNrNAAAAgHbmXbtZu5Bo\nkIFNryFRr2HLLbck69dPb5sGQbsZAAAA0E3tKomqn7nvZL61m93vfsk//MP0tmkQDFwNAAAAdFO7\nSqKkHiHRINvNbrhh6tszKCqJAAAAgG5qV0mUDCYkmmpwZOBqAAAAYFs070OisbH6VxLVgYGrAQAA\ngG5q2W7WzXTbzboFUMngB66uC5VEAAAAQDe1rCRa0GWrpttu1msb2XxsN7v77s4hmEoiAAAAoJta\nVhLN5cDVo6Pl73xsN7vrrs7TDFwNAAAAdLNVhETtgo/Wn3zvNUjaWsck0m4GAAAAdFOrkGj58smX\n67fdbKoh0SDbzerQ4qXdDAAAAOimVmMSPfrR5e8g2s1aK2eaQ6Zu5vPA1d22XSURAAAA0E2tQqLt\ntit/BxEStYZDvVYUzeeBq7uFRCqJAAAAgG5q1W42yJBoWxyTqBp0u/rbTCURAAAA0E2tKokWjG/N\n1hYSzVb1TreQyK+bAQAAAN3Mm0qi5uWmGxINDSUnndR+G7SbAQAAANuiWlUSdQuJmkOOqYRE1fLV\nsj/+cfttmM8DV2s3AwAAAKZqqwiJuv2aV79hznyuJOql3ayO4RYAAAAw9+ZNu1mnkGh0tL92s17D\nn/k8cHW30KyO2w0AAADMvVpVEi1a1Hlac8jTHBJt3Ng++GmtnOm1gqZb0NJu/XVSbZOBqwEAAIB+\n1aqSaOHCzvN0qiTatKlzJdHISPKa10x+v53up5f56kS7GQAAADBVtQqJqnaz5gBm5cpk9907h0Sd\nKok2bkxOPnnL+23XytZsJgaunq1gRrsZAAAAMFW1ajdrFxItX14Cjn5DovXrJ84305VEa9fOfZVO\nL+1mc72NAAAAQD3VqpJowfjWNAcwVdDT7rakc7vZ+vWN9TXf70wNXL1kSfK//9t9mZnWrd1MJREA\nAADQTS0riZpDjtaQqNdKog0bulcSdWo7m86vm914Y/dlZlovYxIJiQAAAIB2Fs72HfY7JlG1TLeQ\nqF3wsX59YyDsye632XweuLpbENTvr7wBsHW46qrkjjuSgw/uPt+73pU8+cnJk55Url9+efnS4Zpr\nkmc+s7RVX3ZZsu++ycc+Vt5PrrkmedCDkje8Ibnf/Wb+scy0U05J/vIvJ1Yi/8//JM9/fvL5zydP\nf3py3HFAWeCiAAAccElEQVTJgx9czlmuvjp585uTBz6w7I8TTkie8Yzkox9Nli4t+/Qb3yj7/mMf\nS9atS+68M3niE8svuh5xxNw9VgCAdmY9JOqmXUjUOhhzP2MSbb994/pcDlw9W1QSAdDqWc8qYU63\n962NG0vYkTTmO/jg5J57yuWTTkq++90SdPzHfyTf/nay114lQEmSAw5IXvCCmXsMs2HTpuRFL0qe\n8ITy2JLynvnCFyYPe1jy4hcnz3tectppE5fbf//kb/4mufnm5B//ceK0170u+dM/Lct+/eslTHvn\nO5MPfrBMr+O5BACwbatlu1lzkFGNOdQpJNqwYWoDV3c6MZuJSqLZ/nUzA1cDUNm0afJ5brqp+3Kb\nNzfeW264oQRPRx/dmD7X7daDcPPN5e+vf9247dZby9+f/KT8Xb2683I33LDltF/9qrHcvvsmb3nL\nxOm9/N8AAMym2rebVSdQ3UKiV796y3Vt2NB+4OrJTGdMornWWnXVrNPA1StXlvL3f/u3xm3velc5\n6T3xxBnZzNrbtKlUoY2OJh/+cHLWWaWV4Nxzkx13TH74w+TP/zz5ylfK/DvumPz3fyennlraLj7x\nieT665Mvfzl5yUvKN9Knn5488pFz+7gq//zP5fnxnvcMZn3PeEbyqlclz31uqSa45JLGtCc8obRj\nbNhQWiySZOedSzvHJz/ZmO/YY5Pjjy/f4m+3XWnPuOWWxvS7704WLx7M9k7m+99PXvGK5IorBr/u\nz32utKz85jflfpJyzKxeXVpPNmyYOP/SpaVN6EEPKsfjjTeWy0ny29+W526zalpS1nnCCaVyYT46\n8shyjLznPcnvflcuNx8Tleoxr17d2Jettz/wgRM/wDfvp2bVPv7bvy3VMu0ccUTynOckb31r8pnP\nJMPDZbkFs/CVy803J/e/f7Lnno3X8tWrk2OOSf7rv8r1do+t2icPfnDndTcfe9V8zQHGscc2nsMf\n+EDyoQ+VbamsXJm8//1lnttvL7ftvnsjJKm268Ybk8c9rlQlDdKFFyZ/93fJj3+85bQXvKDxfKuO\nk5e/vBxXH/pQY9uqffCc55TX9aRUWCXJ3/99+XvxxVuu//jjy/F5991bTvuTP2lsX1Vptc8+yS9+\nUS7vtdfEY2f16vL/+9Wvltfqr32t3F6XL3huvTW5730b1zs9l3pV/X8k5TFef33ndd5yS9nH97pX\n8ulPJ3/xF+ULwSc9qZwHvvCF5X3oK19JvvCFMn2uvP3t5TXipJPKsbZ8+cTwcTr7rXmf9Tr/MceU\nFsjKfe9bnhN7712O3SOPLLdfeWUJM2fTr39dngcnn1zOrZLy/rbXXsmaNeX6kiXl8r3vXaZN97jr\nRfW6ecwx5bVu5crGtKuuauynujw3zzyzvHf1e3wMUvP78AteUM53ktKqvGRJee17yUsm7svZdNRR\nyaMelbz+9eX6PvuU46p6vZ9tzV86XHFFcthhybXXNm5bsiT5gz9IPvWpcq4xV668MnnEI0ol8VFH\nJWefnTztaeW964EPnL3tuPXW5K67Jt52r3slt91WjrsDD9yy0pepm7N2s3vuKR8smz8otvt1s8na\nzdavb7/+2f51szqotqmfdrN3v7ucGDeHRMcfX55w22pIVH0rfOut5QT9O9/Zcp4qIErKSevFFzfe\nDJNyonveeeXyjTeWsT3qEhK9613lOBhUSPSd75SxSA4/fGJAlCTf+96W869bN/F5n5Q2jKScJLZz\n002N9o+Zds45yU9/OjPr/tznyolccyvsCSeU8U5aA6KkBERJeVO+6qoSRp53XtlPb3rTlvNXx9z6\n9eUE9sQT529IVB0jn/98smpV5/n+9V9Lu88jH1k+8FQnXdW+2HPPMo7Mpz7VWOY1r2nfGvWWt5R9\n/J//2TkkOu20ch+rVyff+la57ZZbkt126+fRTU0VLKxYUYKam28uQWwVECWNx91swYISvlaBRyc7\n7VTmqebbbrvyfrvddo332h12KJf32KOs9447ym3V6+Zzn9t4HagCoiR5xzvKtj7sYclFF/X/2Cdz\n1lmNap9WZ59d2uN++cuyfUcfnYyMNKqf3vjG5NnPnvj4mlW3VX/vc59GG97ixY1qoyRZtqzsk/vc\np7w3rF3bWK4KV3760/JBN5l4X2eeWYKuhzykvGdUAVFSXrNnI4iczM9/PvH6ypXJU586tXWdfnp5\nLn7rW2U//vu/l+O63TH80Y+W85WknJ+cdFJ5zdy4sQRwj31sCYmq9+ZTT53bkKg6p/rMZ0pI1BwQ\nJeV1Ziof5NeuTR796NIa+sxnTj7/mjXJYx5TXiOaQ6Jbby3H2N57T3yfXrVq9kOiq65qnEdVIdHV\nVzcCoqQEzj/7WeN50+4YGaT3v7/8S8q+W7x4YrDxf//XuDw62viSey5dfHF5fV29uryHzfY556WX\nlv+/o48uAfeppzbOi6vX2l/8ojxf58onPlGCode/vpyLXnNNuf2SS0rYMNv23LNxuXo+NodED3hA\ncsghZfvmMiT60Y/K309+spyPVufsmzc3Xr9nw5OfvGU17223lb9HHlneQxicOask2mGHLU942lUS\nVWMOdQqJfve79vezevXED5VVcHLZZeXvqlVlnksvnbhcdT/XX7/lOqtvUZPOpfXXXlvexB/zmMYT\n/YorygnCmjXlje6668ob9H77lTfHTZvKtyO3315OIm+9Ndlll1JZUB38zQOOjo2V+9999/Lheaed\nGveRlBPhAw4o35xXL4BVVcSqVWVfbNpUHmv1wfSCCxqPvbrPXt+Et9++bPfQUFn30qXlMY6Nleub\nN5cT57VryzyPelRjQNRlyxofMKr/26GhcnmyQK86Dqr5FiyYeOzss0/5u25dqdxYtqzx2JqXGxoq\n+zIp+/VnPyuXzzij8Y34ZFrDkW9+s/FC9vCHlzfF5csbj631MSxa1Piw0DpPZdGi8viqf+0ecy+q\n+Zv/fzvdZ/P6q8vt7vOGG8oJ/1RdeWX36WeeWU6Mp2uHHRofgDvtt+p52+n4r/7PFixoVJB0+z9o\nnl619Oy1V3nuJyXgmMy9712eV0mp8ui0L1orRX75y8GdTLc+zqGhicdtp/mSsv1r1pT9NTZWXjM6\nBfytml9329lvv/INVzKxwqF5X1T7rrLbbu2raprn67bfqteIs88uf884o3ywH4ROz8WkUX2zbFnZ\n/up1q1m3aqGZsOuuE+93l10a05ofy6MelTz0oY1pg/6Q98tftl/vpk3l2Fuxonwjm5Tqx49/vBH0\n7LFH//tt553bX04ax9FOO5Vjv9X225f3g1bVB4b99ivvyc3OOKOx3m7HSCcLF5btaX0+Ve9/O+5Y\nzhcmez85//yJ1x/+8Kkfcw94QPlbhRLLlpW/7dbX+oH36qvL31NPLX+vuaZU+1ZuuKHzMTaV983m\nLzF32KG81uy9d3nv+s1vtpy/CjhuvrkElK0OOmhq1QvV//vee/e235uPk2p/VMf9qlVlnzcHHpdf\n3v252c++a563Os52262Euc2B9chI+XvppY37bj3+m19Xkpl/naveUyr33DNxvzQ/D04/vbeAofWc\ntXVa6+3bbVcqI0ZHS4XkZCH/qlXJoYeWL+4OPHD2f0igeo489aklJFq4sLHPqs9eSTnH6uX1v9v+\n6mTnnctzY/36xjlWq1tuKfff/CXGihWTj1k70847r7zOnXVW47YlS8rr4w9+MPPBaHV/K1aU+2v+\n4rJ6jbjuurIdzUHNbIbKre+1zfbdtzxPv/Odcm7azfLlJVClu1kPiZpbKjqFRAcdVD7Yn3PO5O1m\nnfz4xxPLzqsPoVWFwHnntX+TGR0tAVG7b6CqX3xJkve+t1GJUW3j6Gh5cUrKgXrggeXytdc2TggP\nP7y8IS5bVtLhU06Z/LEk5YSnOqE688xSkvjpTycve1mjJWWPPcr05z2vnDC9+tVluerEa5ddyjcj\n1b449NBy0r5+fbncXAK/xx5bjp3QTusJYy+WLZsYvlTb3+rQQ3u770MPLSdkl15aTq6XLi3fNrVr\nF9ptt0aYduihZZk1a8qH7qGhcvK3444lFT/ppLLP/vAPyzdto6OlrPLmm8s81Ung619f3pzvfe9y\nTO2yS/LFL5bj+wEPKNM/+clGZVb1uC66aGI7x0Mf2viWtvWx33NPaXOrLF5c/o9+/vPyKzkL+3gm\nP+Qh5bFU/7/N+7HZ+vXljeLhDy8frr773fL4fvnL8mJcnYDsskt5Th9/fCnL/tKXyvauW1eWve66\ncn3nncs3IWecUZZZu7Z8KLr++vKhbWysBKTXX1+Ojw0bymP81a8ag+NOx513TjxRedCDOp9oLl7c\n+fhvd8wfeGD5ANZp/mXLSnC8aFE5Pp///FK2e9BBE0t1n/70ctxWJy8f+UipuPzjPy7zVq+d++9f\nWnZ+8pPyDexhh038Riop1xct6u153Ivzz5+4z6r9sP/+5cQiaTwPV6xohAdr124Zoibd91lSnqs7\n7liOgdHRErDdc0+jqurOO8vJXvW4n/nM0hL19a+XaozKUUeV8vbvfrfsq332SZ7ylPb3+bKXlRbT\npUs777d73ausY6edyjG7ePHEKqXp6vR8rCxY0Hh/2n778n/86EeX16C3vnVw2zFV//RPZdtvu60x\noHPSCO2PPrrsr0Edl806PW9f/OKy3+5///KFy2MeU16bFi4sz6nJfvVtthxwQDmOn/a0UiH3ohc1\nqiubq33PP7+cLx1ySO/rvvjicvy3Hletr2eTve8mjXOF4eGyH6fq8Y8vg3pXjjii8cVWq4MPLsf5\n5ZeX68uWlf/vj360nJutW1c+mFb7bNOm9sfCxo3l/fxhD+u9+u+OOxrnk/vv3/hycWys7IO9997y\nPXjffUuYvPPOpfVs8eLy+vX2t5f3wKm2twwNlffLFSt6n/+P/qi0aDTvj8WLS8h99tnlNeRpTysf\nTs8/v/N53U03lXDukEMmr5y5/PLyGlAdT1ddNbGaqvW85Q1vKMdo8zY+8YnlNf6mm8rt1ZdtnSoG\nB+nxjy9/99238UM4rcfTK19Zzu1OOKG3dXZ7bW+ddv315dzp059OPvvZ8sF3snO9oaFSEfm1r5VK\nxtm2fHl5nu63X3lO7r77xH223Xal2uPaa/v7fNHLa1KlCjfGxsq5Q+t50fLlZd9U93/IIeX5O1cB\n0TveUT4LnHFGOT899tjyGrh8eQmX3/zmcq59+ukz857Z7Ne/Ls/TE09stFe37vtq31XBXdWmOlve\n9rZyjvwv/1KuV8/BpHxWe8lLyjyTefaz/3979xojV3neAfy/BgMmxg4yYFQnMaLUBZEApi44kDat\n4oJKKU0jFfIF4ggjmg+RElSiVq1q5SJFgoDaL3UEtCUlhVJSEldE0ITWbgoGXEQQIg6wXCLu5iKK\noVSkrE8/PHs6s7Oz6117Pbu2fz9pNGfO3N45+8w7Z5/zvO+pCmLmlmb58qoRaZqmufzytl6kLl/7\nWl2vW1f3J02zfn3THHNM02zYULfvvLNpXntt7PMmu3zjG02zZcvUH79hQ9Ns3Tp2XWtoqP/6t9+u\n21df3bnv6af7v/6HPtQ0hx/eNNdd1/z/tui9LF06ft1993Xe76abxr9f7+X++5vmwx9umocfbsa4\n++66/4gjOut27qx1119f1yec0EzZVLfrri5HHlnX8+aN376TvfcZZ9Tyk0/W7Ucfrdv33NP/fa68\nsmnOOqvz+pdcUsuLF9fl9df7v9fwcD1u27apb5t+7V24sHP7ggtq3apVdX3zzXW9cuX457755tjP\nceGFTXPrrbX83nu736a2XSedNH59G9c//GEnRq67rq7vuGPP3nM2PPHE+P5md5x44vi4euWViR/f\n3afty5Km+cpXxt5O6rvXarfxT3/aWffMM/2/i9u3D6zp+5Skac45Z7ZbwVyWNM3550/vOStX9v9d\n/chH+u/X7K9+/vP6nBs3Tv05jzzS2T7PPddZ3rGjaebPb5qRkb3X3rnkxhvrc+/cuevHrls3Np6u\nuGJsnO3pfsu+aPXqib9jJ5889r6rrqrbX/960xx77IG5zXanTzrllM7zrr1277Rrf3X77bXdLr20\nrtesme0WsbuSNDORtBl4JdGKFZ2y8N6jyO2Rie4ysZGROorTTjJ20EHTG5c/f36nAmcqPve58eO8\nP/GJGh7S9Gzyyy6rjG9bCfDtb3fu++IXK+Pfe+aSZ5+tipFlyzrboddpp9VwpW7r13fGr7dDHSar\nrli/vo709X729uh+d/VCm0Fvx5S2JfmDtGxZHXU66qj+pdsTaauk2s/Ze91r8eKxZcFtBcS779bf\nd6KS4V297lTMnz926EH7t2i3d7v928/UrX1sa+HCzpHImRgL3+8927LORYs6MdK2Y7IKkLmq92+3\nu0dy+8XIro7aTVYiuy/pt826hzz1+570GxKVzM6Rzn1F2y/BRKYbIxP9rvcbDrc/a+eDm07/392f\ndQ8T/MxnqjptLswVNQjtNptK1UVvfPYO+Z0Lc/gMWu826Na7X9Fu65tv7sz3dqBtsyVLpj8sdNmy\nTtXfnuyvH4ja/fp2vqHJ4pUDw6AL7JrXX2/y8ss17vLttyuR8eKLVXJ81VU1BGHFikpiDA0l115b\nY78vvrjKPrdtq/XtMK0zz6yAXr68SvLmzavEzAsv1JCV88+vH/VbbunMS7NgQad8dOHCKun82Mdq\naNYFF9Spfc89t5JVIyPJ5z9fwxMuvLCed+KJ1e5DD63hNeedV49fsKDKHJct60xkumRJlXg/9VQl\nu97//vp8Z5xRSZ4lS+rxW7fWP1Pz5lVC6vHHq12LF1fpZu8ZW955p77Q77xTn+PUU6sM+M03K9lx\n+OH1D/1FF/X8AZoqXV2zZuw/b/ffX9v+Zz+rH/d+8yX0MzxcY1WfeqqSYgcfXO9x9NH1Oh/4QP2w\nPf54tXPp0hp60s7fMTxc5aCnnFLbaf78GnK0YMH4MeG9Hnustl87D8k993SGBDZN/bi+9lq14fjj\nq5Ty9NNrG7/6ar3+jh1V+vr88/WcdvLSfrpff3c880x9vjZB98YbFadLl1Yp6cUX13Y88sj+Y8nv\nuKMzZ9NZZ9X23bq1SpD3xPBwxUq/0vt77633GhqqGFm1qs6I8tGP7ps7xt/5TiVh33ijhpzszmR7\n27fX3+3ll6svePHFyePi4YdreMa+/o//gw/WcI92mw0PV3l079Dcft+TjRur7zzhhPpuP/FEDb1l\nvG3bqv+djWQ9+4af/KR+v6cz0erwcP3u9Q5Re+WV6hdHRmpfph0WuD/bsqUmUZ/Ob9jmzdX3rV5d\nZy596aX6PT/++DqQeCB4770a9j6VfY633qr9mXbOve3baxLjww6rfb5zztmrTZ2TXn21pkLoN0Rz\n+/baf2/nSXn33Rpu9NJLtW+6fPnUJirfnzz7bOezT9VDD9X3+5BDkk9/evwBViY2MlLTbDRN7YOc\nfbb9kH3VUGXy9zjHM/AkUdNbjtM2ZGj86ZqHhipxdOWVtbx2bQXw3jQ0VOMtv/rVseu+8IX+s6YP\nDdU8EF/+8t5tFwAAAEA/M5UkmlO1ACefPH5dW03yvvftecXEVK1cOX7dZBNbTuXsRAAAAABz2Zyp\nJAIAAABg+vbLSiIAAAAAZockEQAAAACSRAAAAABIEgEAAAAQSSIAAAAAIkkEAAAAQCSJAAAAAIgk\nEQAAAACRJAIAAAAgkkQAAAAARJIIAAAAgEgSAQAAABBJIgAAAAAiSQQAAABAJIkAAAAAiCQRAAAA\nAJEkAgAAACCSRAAAAABEkggAAACASBIBAAAAEEkiAAAAACJJBAAAAEAkiQAAAACIJBEAAAAAkSQC\nAAAAIJJEAAAAAESSCAAAAIBIEgEAAAAQSSIAAAAAIkkEAAAAQCSJAAAAAIgkEQAAAACRJAIAAAAg\nkkQAAAAARJIIAAAAgEgSAQAAABBJIgAAAAAiSQQAAABAJIkAAAAAiCQRAAAAAJEkAgAAACCSRAAA\nAABEkggAAACASBIBAAAAEEkiAAAAACJJBAAAAEAkiQAAAACIJBEAAAAAkSQCAAAAIJJEAAAAAESS\nCAAAAIBIEgEAAAAQSSIAAAAAIkkEAAAAQCSJAAAAAIgkEQAAAACRJAIAAAAgkkQAAAAAZOaTRPOS\nfDPJliSbkvziDL8+B5DNmzfPdhPYR4gVpkO8MFVihekQL0yVWGE6xAuDNtNJok8mOSTJWUn+OMk1\nM/z6HEB0iEyVWGE6xAtTJVaYDvHCVIkVpkO8MGgznSQ6O8ldo8sPJFk1w68PAAAAwF4w00miRUl2\ndN0e2QvvAQAAAMAMG5rh17smyf1Jbhu9/VySD3bd/2TMUwQAAAAwk55KcsJsN6LXp5L87ejy6iTf\nn8W2AAAAADBLhpJsSHLv6GXF7DYHAAAAAAAAAAAAAAAAgLllXpJvJtmSZFNMXk3HQ6mY2JTkr1MT\nbd2T5EdJ/iqdydUvS/KfSe5L8juDbyaz6MxUfCTTi48FSf5p9LHfT3LUgNrL7OmOlZVJnk+nf/mD\n0fVihflJbkr9vR9I8rvRtzCxfvGyMskL0b8w1kFJ/ibVl/xHkpOjb2Fi/eJF38JkjkmdGGxF9pO+\n5VOpL0FSO/Hfm8W2MHcclkoSdfvnJL8+urwhySeTHJvkkdSO2qLR5UMG1EZm15dSf+8to7enEx9X\nJPnz0cdelOQvBtNkZklvrKxLxUA3sUKSrE1y7ejykUmeTbIx+hb6W5vx8XJp9C+M93tJbhhd/niq\nX9G3MJHeePle9C1MbH6S7yZ5LMkvZy//TzRvBhs+mbOT3DW6/ECSVQN6X+a2U5McnuRfkvxr6ox4\np6eynElyZ5I1SX41NRH6/ybZkeTJJKcMurHMiidTSeY2Oz6d+Ojud+4afSz7r95Y+ZXUEZR/T+2E\nLUxyRsQKyW3p7CzNS8WDvoWJ9IsX/Qv9bExy+ejycUneSMWKvoV+euPlv6JvYWJXp5JBL43e3qv7\nLYNKEi1KNbQ1MsD3Zu7671TAn5vkD5P8fc/9byVZnIqfN/usZ/93e5L3um4PdS3vKj66+x0xs//r\njZUHkvxR6ujc00nWJzkiYoX67Xk7FQ+3JfmzjN0n0bfQrTde/jTJ1uhf6G8kyY1J/jK1X2u/hcn0\nxou+hX7WJnk1yQ9Gbw9lL/ctg0rU7EgFePf77hzQezN3PZFOYmg4yetJlnbdvyiVVe+NnyNSR2c4\n8HT3G5PFR+/6dh0Hju8m+XHX8sqIFTo+mOTfkvxdkluib2Fy3fHyD9G/MLm1qeEgN6SmVmjpW+hn\nbSperk8lAfQt9Ppskt9KzVN1WpJvJTm66/4Z71sGlSS6N8l5o8urU+Pj4LNJrhld/oVU0P4glT1P\nkt9OldFtTfJrSQ5NZT5PSvLoQFvKXPHjTD0+uvud9rEcOO5Kld0mVVb7YMQKZWnqt+ZLqSO4ib6F\nifWLF/0L/Vyc5E9Gl/8nVSXyYPQt9NcbLztTVdH6Fnp9PMlvJPnNJA8nuST1O7TP9y1DqTF0945e\nVsxuc5gjDk7njCE/SiUQfynJ5tTkszekU0q3LhX4Dyb5/UE3lFl1XDqTEU8nPhYk+cfUGSPuTp0R\ngP3bcenEyqmpsz5sSnJzalx/Ilaosv4X0zl7zKbUmP3N0bcwXr94OTP6F8ZbkOTW1HwyW1JnwrPf\nwkT6xYt9F3ZlUyqXom8BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAG4v8A/9PM\nfyj+w0cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3406596da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser = serial.Serial(\"/dev/ttyACM0\", 1000000)\n",
    "for i in range(5):\n",
    "    l = -1\n",
    "    l2 = -1\n",
    "    s = b\"\"\n",
    "    #ser.write(b\"1\")\n",
    "    while(l2 == -1 or  l==-1 or l2<=l):\n",
    "        s += ser.read()\n",
    "        l = s.find(b\"BEGIN\\n\")\n",
    "        l2 = s.find(b\"END\\n\")\n",
    "        if (l > l2):\n",
    "            s = s[l:]\n",
    "    l1 = l + len(\"BEGIN\\n\")\n",
    "\n",
    "    data = list(map(lambda x: int(chr(x[0])+chr(x[1]),16) ,list(zip(*[iter(s[l1:l2])]*2))))\n",
    "    \n",
    "plt.figure(figsize=[20,12])\n",
    "plt.plot(data, \"b\")\n",
    "\n",
    "plt.ylim( (0, 254))\n",
    "\n",
    "data_series = pd.Series(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}

laser_rojo_1.csv

laser_rojo_2.csv