plot_Fig11_sb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from astropy import table\n",
    "from astropy.table import Table\n",
    "from astropy.io import ascii\n",
    "\n",
    "import matplotlib.ticker as ticker\n",
    "\n",
    "\n",
    "#from astroML.plotting import setup_text_plots\n",
    "#setup_text_plots(fontsize=9, usetex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from palettable.colorbrewer.qualitative import Dark2_8\n",
    "if 'plt' in locals() and hasattr(plt, 'rcParams'):\n",
    "    plt.rcParams['lines.linewidth'] = 2.0\n",
    "    plt.rcParams['font.size'] = 15.0\n",
    "    plt.rcParams['font.family'] = 'serif'\n",
    "    plt.rcParams['axes.prop_cycle'] = plt.cycler(color=Dark2_8.mpl_colors)\n",
    "    plt.rcParams['legend.fontsize'] = 'medium'\n",
    "    plt.rcParams['legend.frameon'] = False\n",
    "    plt.rcParams['figure.dpi'] = 100\n",
    "    plt.rcParams['figure.figsize'] = 7, 6\n",
    "    plt.rcParams['xtick.major.size'] = 6\n",
    "    plt.rcParams['xtick.minor.size'] = 4\n",
    "    plt.rcParams['ytick.major.size'] = 6\n",
    "    plt.rcParams['ytick.minor.size'] = 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SAGA_DIR   = os.environ['SAGA_DIR']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# READ SPECTRA\n",
    "file = SAGA_DIR +'/data/saga_spectra_clean.fits.gz'\n",
    "allspec = Table.read(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/marlageha/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py:12: RuntimeWarning: divide by zero encountered in log10\n",
      "/Users/marlageha/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py:12: RuntimeWarning: invalid value encountered in log10\n"
     ]
    }
   ],
   "source": [
    "msats = allspec['SATS'] ==1\n",
    "mlowz = (allspec['SPEC_Z'] > 0.005) & (allspec['SPEC_Z'] < 0.015)\n",
    "\n",
    "r = allspec['r'] - allspec['EXTINCTION_R']\n",
    "g = allspec['g'] - allspec['EXTINCTION_G']\n",
    "gr = g-r\n",
    "# SUPER HACK!!\n",
    "mm= gr > 0.75\n",
    "gr[mm]=0.35\n",
    "\n",
    "dmod1 = 5.* np.log10(allspec['HOST_DIST'] * 1e6) - 5.\n",
    "dmod = 5.*np.log10(1e6 * allspec['SPEC_Z']*3e5/70.) - 5.\n",
    "Mr = r - dmod\n",
    "\n",
    "reff = 1e3*allspec['HOST_DIST'] * np.sin((np.pi/180.)*allspec['PETROR50_R']/3600.)\n",
    "#print reff\n",
    "\n",
    "\n",
    "sb = allspec['r'] + 2.5*np.log10(2*np.pi*allspec['PETROR50_R']**2 + 1e-20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# FIND NAMED HOSTS\n",
    "complete_hosts =[147100,166313,165536,61945,149781,33446,150887,132339]\n",
    "incomplete_hosts = [85746,140594,161174,13927,137625,129237]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# FIND ONLY OBJECTS IN NAMED HOSTS\n",
    "imsk = np.in1d(allspec['HOST_NSAID'], incomplete_hosts)\n",
    "msk  = np.in1d(allspec['HOST_NSAID'], complete_hosts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  col1  \n",
      "--------\n",
      "Sculptor\n",
      "  Fornax\n",
      "    LeoI\n",
      "     LMC\n",
      "     SMC\n"
     ]
    }
   ],
   "source": [
    "# MCCONNACHIE DATA\n",
    "file = SAGA_DIR + 'data/cfht_MW_edited.txt'\n",
    "mw = ascii.read(file,data_start=1)#, guess='False',format='basic')\n",
    "mw.columns\n",
    "\n",
    "MW_gr = mw['col10'] - mw['col12']\n",
    "MW_r = mw['col12']\n",
    "MW_reff = mw['col8']/1e3\n",
    "MW_sb = mw['col14']\n",
    "print mw['col1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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MGTKE1NRUsrOzadOmDf/4xz8AGDNmDP369Stw3RNPPJF33303vwb1yCOPICJkZ2dzyy23\nMGXKFAYMGMDRo0f59ttvWbt2LbNmzWLWrFkAPProoyQmJjJ48OD8NEDqp3nzv//9L82bNwdcNbqt\nW7cybtw4tmzZwubNm+nXrx9TpkzhvvvuIy8vL/gfhD+BIlNF/sJqQMaEXLC/V961H32NMteCkpOT\ndffu3XrGGWfo/v37dfTo0Xr06FGtXbt2/jF9+vTRrVu3qmrBGlDv3r115syZunz58vxjmzdvrvv2\n7dPvv/9eX3rpJZ/7ffTRR9q9e3ddu3atLly4UIcPH66zZs3Sp556Svft26eqqu+//37+e73++utV\nVTUjI0PvuOMOVXXVlPbu3etz7fnz5+sVV1yhjRo10smTJ6uq6u7du/XTTz9VVdXp06frokWLVLVg\nDWjdunV63XXXqapqbm6uXnTRRaqqmpSUlH+Md03H+xl414y6deumK1euVFXVcePG6auvvupTxsI/\nZ4qoAcX6PCBjTDnjXfsBCtSC2t90S9EnBxAfH0/Xrl0ZM2YMTZo0oXLlygX2q5+aAMDKlSvZsGED\n48f/mTaye/fuzJ07l//973888MADPudcddVV9OnTh2XLltG/f39q1arF7NmzueCCC6hVyzXv/ciR\nI4wYMYL4+Hiys7MB+Nvf/sagQYPYvXs3Bw4cKJDV2vve3bt354cffuDvf/87l1xyCZdffjlvvfUW\nH374IWvWrCE+Pt7nvG+//ZZ9+/bx2GOPoaqcccYZHD16tMAxwaThWb9+PUuXLmXlypVkZ2dz2mmn\nFXtOUSwAGWMcQ1VZ+sYUpnY4UGB7+6YHGPL6ZNrd2LXE+co8weWBBx6gVatWfP/990EdD66gMGnS\nJDp27MiKFSuoU6cOvXr1okuXLlx//fXUrFnT5/xq1apx7rnnkpWVxeDBg/nb3/7GnXfemd+sBdCz\nZ0927txJ1apVSU1Nzd9+22230atXLx5+uHDqSkhPT2fnzp384x//4Oyzz+ayyy7jyJEjpKSkUKVK\nFYYPH86LL76Yf3zlypU5duwY69evp2nTppx00kk89NBDACxYsIAqVQp+/Hu/b8+/Pdc4fPgw27dv\n58ILL6RLly40b96cH374gX379lEWFoCMMY5RuPbjUdpaUFZWFhkZGbz++ut0796d7du3A67RaUeP\nHuWVV17hr3/9K+vWreOVV17hwgsvZNu2baSmprJu3TrWrVtHdnY28fHx9OjRgxkzZnDWWWdx8skn\nc8MNNwS873XXXcf+/a4kK9WrV+fss8+mRYs/pyL27t2bvn370qxZM3755ReWLl1K+/bt6dWrF3Pm\nzOGqq67yueapp57KjBkz8msztWrVol27dpx++ukMHDiQ5ORkvvnmG1SVW2+9lWuuuYYXX3yR+vXr\n88QTT5CQkMCoUaOoVq0aZ555Jps3byY9PZ3t27dz7Ngxtm3bxquvvsrxxx+f/wxuuOEGjjvuOB58\n8EFuvfVWHnvsMSZMmMDZZ5/Njh07SE5ODvpn4Y8jMyFEm2VCMCb0isuEoKoMuaMVUztk+QQg134Y\nsqQFU1/5OOJZmz2OHDlC1apVGTlyJI888kjIr717927mzZvHoEGDQnrtSKpIyUiNMeVEoNqPRyj6\ngsoqJSWFLVu2cOmll4b82n379qVu3bpB51ErD6wG5IfVgIwJveJqQJOTB7NvxxdF1m5UldonX8KD\nidPCUUQTAiWpAVkA8sMCkDGhZ8lIK4aKlIzUGGNMjLIAZIwxJipsEIIxJiIaN24ctdFrJnIaN24c\n9LHWB+SH9QEZY0xoWB+QMcZEmYhYDbAQa4IzxpgIsFYVX1YDMsYYExUWgIwxxkSFBSBjjIkA6wPy\nZQEoCIX/09hre22v7XVJX3sWYXNKeSL1uigWgIwxxkSFzQPyw+YBGWNMaNg8IGOMiTLrA/Jl84CM\nMSYCrFXFl9WAjDHGRIUFIGOMMVFhAcgYYyLA+oB8WR+QMcZEgPUB+bIakDHGmKiwAGSMMSYqHNME\nJyJNgelAdaAmsAQYq6p5RZyTCPQAdnhvBs4H3lPVPl7HdQZ2ex2jwFBVXRPit2KMMT68U/IYF0cE\nIBGpDywDklX1WRGpCazGFYgGF3GqAhNV9RWvawmwGZhT6NhBqpoe2pIbY0xwLPD4ckoT3CD39+cA\nVPUA8DgwUEQaFnHeM8DCQts6AodVdVnIS2mMMSZknBKAOgKfFUrAthpXDa1doJNUdZeq/lFoc3/g\nhdAX0RhjTCg5JQCdA/xSaNvP7u/nBnsRd23pOuBlP7t7i8hyEckQkf+KSIfSFdUYY0rO5gH5ckoA\nqg3kFtrmeV2rBNfpA6Sqanah7duAb4HrVLU1rhrS2yIyrDSFNcaYkvKsB2T+5IhBCMA+oFqhbZ7X\n+0twnf5A78IbVfXlQq/fE5H5wGgRmaqqx0pwD2OMMSHglAD0PXBKoW2e15uCuYCIXA/kqmpGkPfc\nBNQBTgR+LbwzKSnJ54SEhAQSEhKCvLwxxlQcaWlppKWllegcRyxIJyLjgAHAyZ6BCCLSE0gBGqnq\nziCu8QawSlWn+9k3T1VvK7TteeD/gHhVPVJony1IZ4wJqYo6DygWFqR7EtecnrsA3POABgNPeYKP\niFQTkXUiMrPwySJyEq7RcrMDXL+7iHT1Ov4i4Dbg6cLBxxhjwsH6gHw5oglOVXeJyDXADBH5J66B\nB4uBRK/DBFeWhOp+LnEH8Laq7glwi3uA+0TkflxBtxowDPAJZsYYYyLDEU1wTmNNcMYYExqx0ARn\njDHlms0D8uWIJjhjjCnvrFXFl9WAjDHGRIXVgEopMz2dRdOmUXnPHvLi47lp8GBatmkT7WIZY0zM\nsEEIfhQ3COGJoUOpl5JCj5wcqgJHgPlxcWT368cDjz8esXIaY2KHzQPys6+iPYxgFBWAMtPT2dSp\nEz1zcnz2zYmLo0lqKi1atw53EY0xJiaEfRSciNwsIh+LyIcicksorulUi6ZNo4ef4APQIyeH1KlT\nI1wiY4zTrF69mmuuuYaGDRsyZcqUMl1LVbn77rupVKkSt99+Ozt3FpsYJmaEahBCQ+BKXIlAzxOR\nfiG6ruNU3rOHqgH2VQUqBwhOxpiK48orr6RXr16cddZZDBtWtqT7IsKzzz6LiJCcnEzDhkWt0Rlb\nQjUIoYq7zWo7MEFEuofouo6TFx/PEfAbhI4AeXFxES6RMSYWePqAvvzyS6ZOncqpp57Kli1bGDRo\nEFdccQWqyqhRo/jjjz8QEWrVqsXEiRML9B2Vty6TUAWgjSKyBHgV2AycHaLrOs5Ngwczf/lyv31A\n8+PiuHnIkCiUyhjjdKrK0aNHOf/880lLS+PUU0/lhx9+4Nprr2XLli28+OKLbNiwgQULFgBw++23\n8/zzz/Ovf/0ryiUPn5AEIFX9SES2AH2Bi4DnQ3FdJ2rZpg2Z/foxJ8AoOBuAYIwJZMOGDfz8889M\nmDAhvzbToEEDdu/ezdKlS7nqqqvyj73qqqtYvHixBaBgqOoPwKhQXc/JHnj8cbI6dyZ56lQq5+SQ\n5675WPAxxhRFVRERnnnmmfxtBw8epEaNGhUyTY9NRC2lFq1bW8AxxgTNE2DOOussVq5cyd/+9jcO\nHjxIhw4dWLFiBR06dGDx4sUMcTfjr1q1ihtuuCGaRQ67Us0DEpHjcPXzxAEHgN+CWTQuVlg2bGNM\nWWRmZjJmzBi++eYbunXrBrhqP8uWLWPevHmMGTOGc845hz179jBw4EAuueQSVJXRo0eTnZ2NiBAX\nF8fEiRMBuP/++3nmmWf45z//yeTJk2nQoEE0316JhGQiqoicAPwLuBnX8O3fgd3AcUBdXGv4/Ai8\npqrvhqDcUWMByBhjQqPMAUhE7gFaArOA1ap6KMBxpwCdgL8Bj6jq+tIWOposABljTGiUKQCJyAgg\nTVU/LsENBbgPyFLVrJIU1gksABljQs1ywfnZF0QAilPVUk3vL8u50WQByBhjQiPkyUjd+d5aAONU\ndV8Zy+c40Q5AJVnqYcCASWzc6LdFlCZNqvPCC8PDWdQSi7XyGmPKpqgAVNph2JfgCkDnAGtLWzDj\ny7PUQ6L3JNfly8kMsNTDxo2HWLEiKcDVAm2PnlgrrzEmfEqbjHS7ql6tqhZ8QigzPZ16KSn0dAcf\ncOWc65mTQ72UFLIyMqJZvJiSmZ7O6C5dSGzbltFdupCZnh7tIpkKTkQ4oZZUuD6gopQ2AH0kInNF\npK2I1AhpiSowW+ohNJ4YOpRNnTqRuHAhyWlpJC5cyKZOnXhi6NBoF81UYO+98ya9r63D++++Fe2i\nOEZpA9A4YD8wDcgWkdUiMklE/ha6olU8sbLUg5NrF1aLNE6kqix9YwpTu+9lyeuTrRbkVtoAtAZ4\nUlWbAScDEwABHghVwSoiz1IP/jhlqQen1y6sFmmcaOmiBXRotA4RaN9ondWC3EoVgFT1UeAEEemm\nqjmq+q6qPqyq3UJcvgrlpsGDmR8gyDhhqYdYqF3ESi3SVBye2k+7pgcAaN/0gNWC3EqdjFRVndPu\nUk6UZqmHJk2qE2j0mGtf6CyaNo3EImoXyVOnFpugNdTlLTxkfcfRo7ZgYDFKMszflJ137QcoUAtq\nf9Mt0S1clJVqHlB5F+15QFkZGaQ6cKmHxLZtSU5LK3r/smURK49nyLp3sH61dm0+PnyYFw4f9jl+\nTlwcTVJTHfEso8XfM/P8geNvmL8pG1VlyB2tmNohC+/VFlRhyJIWTH3l43K/DEM45gGZMHLqUg9O\nWo7cuznQoyrQZ98+jh53HMk1azLywAFbMNBLoGfWMyeHOSkpZHXuXKGfTzgUrv14WC3Ipcw1IBH5\nq6p+GaLyOEK0a0DhUtYsBJnp6Wzq1MnvcuSRrl2M7tKFxIULAwbDQa1bU7dePcfVIqOpuGeW3Lkz\n4//730gXq9wKVPv5c3/FqAWFuwZ0F3BPCK5jwqysWQictBx5cYMNTqxShWT7MC3ABmhEVqDaj4fV\ngkITgEISukWkKTAdqA7UBJYAY1U1r5jzduMaFu5tnaoOKnRcZ2AkrvlLtYHpqvpqKMpekThlOXIn\nNQfGCntmkbXui1Xsy76MjzMCf0SqKrU/X2kBqAzK3FYlIvWBZUCyqj4rIjWB1bgC0eBiTl+jqtcU\nc/22wFyglap+KSJNgM9FZJ+qLixr+aMpGsk9ndBHddPgwcxfvtxvc6AThqw7kT2zyHowcVq0i+B4\nThmE4KmtPAegqgdE5HEgRUQeDcFy38nAYk9flapuFJE3gPFATAegWEvuGaohwE5qDowV9syiq6Ku\nB1QUpwSgjsBnhXr+V+MqXzvglSLOLbIJUETqAFcBDxfatRroLSKNVHVbyYtsSqqkmb6L45TmwFhi\nzyx6YiHwvPvuu8yePZsTTzyRvXv3kp2dzaOPPsqFF17oc+yBAwcYMGAAq1atYvPmzaW6n1MC0DnA\nF4W2/ez+fm4x5zYUkTlAI+AY8AkwSVV3u/efjStI/VLE9S0AhVm4hgA7oTkw1tgzM/4cPnyYfv36\nsXXrVqpVqwbAyJEj2bhxo98AVLNmTSZMmEDbtm1LfU+nBKDaQG6hbZ7XtYo593tggqp+567tzAPW\nikgzdxCqXeh63teXIK5fbkQya0JhociiYIwJn0OHDrF37162b9/O2WefDcDYsWMByM7OZsiQITRo\n0IDffvuNqlWrMnPmzDLf0ymj4PYB1Qpt87zeX9SJqnqz17/3ish9wA9Af2Cy+9re1/O+vhZ3/fIk\nmquN2hBgU1qrV69m9OjRrF+/nq5duwKu5qzPPvuMBQsW0KhRoyiXMDhO7wM6/vjjGT58OM2aNaNd\nu3Z06NCBbt26ccIJJ9C/f39atGjBfffdB8BNN90UknuGIgB9HoJrfA+cUmib5/WmklxIVTeLSB5w\nlnvTD7gCTYmun5SU5LMtISGBhISEkhTHuNkQYFNaV155Jb169eL555/nmWeeyd/+3HPPcdxxx0Wx\nZCXj1MDjbcyYMdx1110sXLiQN998kwcffJC33nqLJUuWMMRrlOSiRYt8zk1LSyOtiFRd/pQ5AKnq\ni2W9BrAYGCAFUxBcBRwF3g90kojcBuxT1VSvbScDlYHt7vLtFZFVuJYQ93YV8F2gAQj+ApATRbNZ\nrSRsCLDpoTxOAAAgAElEQVQJpeTkZPr06UNcXBz33HMPNWrU4I8//uC8885j6NChfPzxx9x5552c\nd955xMXFsXLlSm688Uam2nIcRVq7di3NmjVjwIABDBgwgNGjRzN9+nQqVSp+4YRAf6AnJycHPMcp\nfUBPAnfiyqrwnHse0GDgKc8QbBGpBnwGZKrqne7zmgDXi8hyVd0nIpVwDa3eDczyuv5Y4F0RuVhV\nvxKRc4FuwB0ReG9hVZpmtWjMHbIhwKasNm3axO23346q8s0339CnTx8mTJhAjRo1eNw9ivKqq67i\nggsuoEOHDjz44IMkJyezfv16Dh48yIcffhjld+B8vXr14ssv/8yspqo0atSIuLg4Vq1axSWXXIKq\n0qNHD+bOnYuqlqlm54gApKq7ROQaYIaI/BPXwIDFQKLXYYIrS4L3n/WvAw2AZSKyz33ej0ALVfWM\nckNV09y1pRQR8WRCuFtV3w7n+3KqaM0dsiHApizOPfdc5s6dC8Crr75K9erVWbJkCSNHjsw/5sor\nr2Tx4sV06NABgFatWlG9enWqV6/Orbfe6ve6kVqewul9QOB6Xrfccgunnnoqe/fu5ciRI8yYMYNj\nx44xZMgQhg4dSk5ODv/85z/Jzc0lKSmJ3bt389hjj/HQQw+V+H6lCkAicjaQrap7SnO+P6r6LXBd\nEfsPUWhItqp+R5B56FT1HeCdspTRlJ0NATah8H//938AxSbx9AwnDiTUc9OK4uTA4/Hcc88F3Dd7\n9myfbbNmzSrT/Uq7JPdjwC4RWSMi00WkqzudjjHGREzHjh1ZtWpV/utVq1Zxww03BHVuLKzwW96V\nNgCtAZoBA3FN8OwL/CgiX4vI0yJycagKaIyp2DIzM3n11VfZsmUL999/P7m5f07pGzFiBIcOHWLQ\noEH07duXbt260aFDBzZu3Mirr75KVlYW06b5z8m2aNo0ehQxNy3VBiyEXWn7gPar6tfuf68GHhWR\n84HewP+A2SIyRFWXh6CMxpgKrGXLlnzwwQd+99WoUYOnn37aZ3uTJk0CnuMR6blpsdAHFGmlrQGd\nKSIFevTcfTgbVXUK0AroVNbCGWNMuHjmpvkTjrlpZR0xVh6VtgY0CnhbRJJxjVbzTEa9GkhR1UMi\n8l0oCmhCL1bmDhkTTjY3LfrKtCS3iHQH+gGnAV8CD6nqTyIyAjhdVWNypdTyuiR3eRXMMNpIDbU1\nscUzCs7f3LRQj4KLRarK5PEjeHD0xFIvG17UktxlCkBF3PBeIE5VJ4T84hFgASh2BPMBYh8ypihZ\nGRmkRmBuWiz2AS1J/Q9LZ/alw4CXS71qa5kCkIi0A3ar6qclvGldoJ+qTi7JeU4QzQAU7F/qFeUv\n+qKyNtSts4MuGa/7bUKZWb0aFy11ZXHa1KmT32PmxMXRJDW1zB820cgsYUy4qSpD7mjF1A5ZDFnS\ngqmvfFyqWlBRAajYPiBVfV9EbnNnEnjBPfmzqJvVxJVW5zRcfUUmSMFOiovk5LloKyprQ5t65wUc\nRtv7UC73PPwgVascx/QwLwPh5FVpy3NwDEXzkAls6aIFdGi0DhFo32gd77/7VqlrQYEENQhBVeeJ\nyHJgpHuOzyb3Vw6uhKEnACcBzYG9wOOqOj2kJS3ngl2wrSQLu0Xrw8ffqoqTJk3ipZdeIiUlhZ49\ne/oMnV26dCkdO3akR48eTJw4kcaNG7N79242bVoMbMG1esYvuNYufAg4mbijuUUOo93y1RrOzD1W\noZeBcHJwLKulixaw49NneP/dy0P+wVjRqSpL35jC1A4HAGjf9ABDXp9Muxu7hjbYe4YGBvuFKyfb\npbgSeQ7BtdR1P1xpdGqW9HpO/HI9lsga1bmzHgZVP1+HQUd17lyi41RVr7460d9hCq594ZCbm6sN\nGjTQQ4cO5W8bMWKELliwwF2mq7V27dr6888/FzivZ8+eWqlSJd24cWP+dZo3b64XX9zTq9x5Ctcr\nvK2g2qbeXwI+iwzQZwUd5X4uwTyv0orGcy4PZSuLY8eO6QP/10KPvYrr+7Fj0S5SsXAtCxPtYgTl\nvXfe1CUja6q+Rv7XeyNr6pLU/5T4Wu737PeztsTzgNzX/FxVX1HVqar6qKqmqOqHqnogNGGx4gl2\nUpzTF3bzXlXRY+zYsfnpUc4880y6du3KxIkT8/d/+OGH+cv6qrvv7fXXXyc+Pp4TTjjL6+qVgCcA\n1/LAB09rxfwAczVeqAT9FG4C5gcoaySG2h7Ys5XRXbqQ2LYto7t0ITM9Paz3qyj8NQ85nedD1+nU\nXftp17Tgx3n7pgdY8vrkkL6H0k5ENSEW7KS4SE+eKynvVRVvueUWZs6cycGDB6le3TW/SEQYPXo0\nL7/8Mjt37gRcmY3vuOOOAv+xs7KyaNq0qZ87NMWz1mDN+MZk9+vHnLi4/GdyBJhTE6rEuwJySyAb\nmOPe5zlmhAjv1q/P4rFjwxYYTmMovb+eR+LChSSnpZG4cCGbOnXiiaFDQ36viqTwB2RxH4wDBkwi\nISHJ79eAAZMiWfSY4B3cvYUj2FsAcoibBg8O+Ne891/qwR4XTWPGjOGHH36gffv2vPnmm5x55pks\nX/5nVqZzzz2Xzp07M2nSJJYvX07r1q2pXLlygWuISFBtzQ88/jhNUlNJ6tyZ2xvUIelSaDIUTjnz\nz4DzAK6Fo5Jxre/RA2hcqRJzfvghbIGhCuk8SAr35OVaossQK/wBWdwHo6cfzN9XoD7SiipQ7ccj\n1LUgR6wHZFwLto07/SL27vuUO90fWkeAmZWrMafO+Vw0ZxUtWreOiYXdCq+qOGrUKKZPn07btm3z\n/+OOHj2ayy+/nJ9//pn5830byVq0aMHLL79MkybX491Znpu7FxHhuONq52dtaNG6Nbv3/Eqbpu/T\n/gLXcaow/1vo6f49auH+ygROB/rn5eVfM9AgjmD5yyyhX8/n7uziR9+V51Fq4eD5gPR0jnuErZM8\nhGJhHlCg2o9HqEfEWQBykAP1rmVQ3iM8zVTqksPvxLExbwhHt7em2sak/OOcvrBb4VUVAU4//fQC\nr8877zz69evH5Zdf7lP7AejRowdPPvkkt93WIr9/aN++fbRp04ZZs2Zx8cV/Jlz396HU8nzITIA5\nadDjAPmB+pkqVUg5etRvuUs7LNtfkEhsu4KqaRv8Hu/dVxfuUWrlLe1SMM1DTh0R5+TA47Hui1Xs\ny76MjzMCB3FVpfbnKy0AlUdHac16iv8ADGZht2h9+ARaVXHs2LF88sknTJ8+nUGDBvHEE08Arv/Q\n999/PyLC+PHjefTRRzn55JNZtmwZSUlJzJkzh5o1a/Lrr78yadKkAsEHAn8oPfBPyLoUkt+DPf+r\nRO7Jl1E39whV16zxW+5QDuLw9NX5GzDi6avLTE9Hv57P31jB78SzkcEcJbSTicNZg4r0ZOhAtR+P\nWKgFRUNJfk4PJvpfuiJcLACVY9Fqvgm0quK4ceMYN26cz3YRYcaMGcyYMaPA9tq1azNlypRi71fc\nX21VLoN6qtQ++RJy1m7hyJo1RQaGkgj0y11cosuDxx3Hpk6d+DAnh6ps4AjwLMuZTD+24/zJxNGY\nDB3p5qHywOmT1i0AmZhXkr/aMtPTQ5YBubhf7kB9devat6fZ0qUFyvA58Bs5tGM6WXzCBpybRrEk\nk6FDKdLNQ6EW6T6gaP2cSsICkIkZoeiwD9UgjmB+uQP11W2YOrVACqEngHq4RuhVJY8jrORZOjHv\nh/NxYraCRdOmkRjm9Eb+lLZ5yCn9YJHuA4rWz6kkLACZmBGqDvtQDOII9pfbX1/d4rFj85sAM3EF\nn55e+6sC95NDlR1ryMrIKHC+E0bNOX0ydGEVdSRhLPycLAA5iFP+UqsIghnEUZSy/HJ7D1BYhKvm\n48+debk+f6U6IbdbMAMsTPTFws/JApCDOOUvNVXLMlycsvxyew9QqBzgGuCcv1ILs5VESyfSfUCx\n8HOyTAjGx59Zhp2cX2sSrr/4XV9r126JaHqVsmSkaNmmTYEUQk5OreRP4fKDOwWSgyZDO1Gkc8HF\nws/JakCmgPy5Ft33OnpORRU20IQ91GWPaw5NzmBWrPDMbUgK+/3LOpjB0w+VNnIkL3/8MQO8MjN4\nOOGv1MB9TnWo17o7G6r85sjJ0MbF6ZPWLQCZAiKxCFVZncZQHmQed/NnyqJozKEp6y93i9ataZGR\nwRNDhzo2tVJRfU5XX53E+LTnI1sgU2Jl7e8MJwtAJl/hmeZOm1nepEl1DuzpQ++v53FPXm7+ds+o\nMUhhKJ0jWqZQ/HJH86/UirK0uxPEQi64SLMAZPIVlWXYCbWgF14YzuguXbjzy1y/++8mh+eZCvw1\nsgULgWADWShHSjp9lnx5Y4HHlwUgA8ROluHihj/XxXmjxkIpVCMlY2GWvCn/bBScASK7CFVZFLcg\n3+84b9SYEy2aNq1ANgZvPXJySJ06NcIlMhWRY2pAItIUmA5UB2oCS4Cxquo7POjPcy4A7sW1RnMe\nUAf4EBivqnu9jksEOgO7PZtwrc8+VFX9p0auQGIpy3BRcxtmVq5GrQvjbdJuEJwwS94JWR0iyfqA\nfDkiAIlIfWAZkKyqz4pITWA1rkA0uIhTk9zf26rqUfd1VuEKSDcWOnaQqoZ+3eVyIBpZhkv74VPU\n8OfD/frxifVdBCXYibThzM7hhKwOkWSBx5cjAhAwyP39OQBVPSAijwMpIvKoqu4McN73wBuqetR9\n3i4ReRGYJCInqepvYS95ORCNLMNl+fBx+tyGWFDcLPlvj55EQkKS33PLY+3ERIdTAlBH4DMt+CfC\nalzlawe84u8kVR3hZ/NB9/fjQlrCcizSi1CFgpPnNpSVZ2j0pqyv2Hm4KgdPa0XN+MYFjtm58zsa\nNjzP7/nBBIjiJtJmf16nQtVOTHQ4JQCdA3xRaNvP7u/nlvBabYB0Vd1eaHtvEUnG9Z53Ac+r6pIS\nl9SYMPI3NPrZ7J0+k2zj4nqzYUNSgKsE2l5QUTXJhQFqP6b0rA/Il1MCUG2g8OQOz+tawV5ERK4A\nrgNaFNq1DTgA3KmqeSLSEXhbREapavFLbhrHKk8d2YGGRntPsj0axHLtwSj43NzzpnbDyjEf0aTJ\nqpDcwxRkgceXUwLQPqBaoW2e1/uDuYCINAbmAreo6ibvfar6cqHX74nIfGC0iExV1WOlK3Z0rV69\nmtGjR7N+/XqGDRvGsGHDAPjpp58YMWIEc+fO5fXXX+fWW28tcN6IESN48skn6d+/P9OnTwfg66+/\n5rHHHqNq1apUrlyZbdu20aZNG4YPH06lSs4drV+eOrKLWmPIM8l2fYgCUKSfm7+MC8Y4JQB9D5xS\naJvn9SaKISJn4Fpa5S5VXR7kPTfhGrZ9IvBr4Z1JSUk+JyQkJJCQkBDk5cPvyiuvpFevXjz//PP5\nwQfg9NNPZ8KECWRmZjJ+/PgCAej3339nyZIlxMXF5QefTZs20a1bNz766CNOPfVUAH777TeaN2/O\nvffey/HHHx/ZN1ZBlddJtoEyLtQ8/SKuvtr/OTaUPvakpaWRlpZWonOcEoAWAwNERLwGIlwFHAXe\nL+pEETkLSAXuUdUV7m3XArtV9Qv363mqeluhU08HDgG/+7uuvwAUa2677TbmzZvHW2+9RdeuXQF4\n8sknuffeexkzZkz+cZMmTeL222/PDz4AJ510Ei+99BI1atQIS9ls8T1fxQ2NjsVJtkVlXIB1NHnm\nkXI7mKSw8t4HFOgP9OTk5IDnOCUAPQncCdwFPOeeBzQYeMozBFtEqgGfAZmqeqd727m4Jp5OA/aJ\nyKW4Jpn+A9d8IM/Ahu4i8qaqvuU+7yLgNuBpVQ00sT7mValShZEjRzJu3Di6du3Knj17yM7Opm3b\ntgWOy8rKomPHjj7nt2/fPmxli6W+mUgpamj0s8SxkcgtzRCqPxCCXbq8PPM0P45NSCAvPp7M9HRL\n+OrmiADknr9zDTBDRP6Ja+DBYgquViy4siR4/+9/CjgN/Obg9+5JvQe4T0Tux5V+qBowDJgZsjfh\nQCLCHXfcwfjx41m4cCFfffUV999/P7/88ovPcdHOcGACD42eWbka804+n6vO/gj4CICdOw/RrFmS\n3+uEogYZqj8QnJBxIZos4WvRHBGAAFT1W1wj2ALtP0ShIdmqGtSf6Kr6HO5JrhVNlSpVGD58OGPH\njqVNmzace+65PgGoZcuWrF+/nltuKTjJdMOGDTRq1ChszXDGV6Ch0ffEaC2hLEuXxzpL+Fo8xwQg\nEzp9+vQhKSkpv625T58+zJ8/n/vuuw/wbYMeMWIEN998M/379+fkk08G4LvvvqNz58589dVXJb5/\nJNeYKY99SZGYZBup51ZcxoVor/gaTsU1P/bo0oXzW7eu0GswSXntECuLgmMhnCszM5MxY8bwzTff\n0K1bN8AVXJYtW8YVV1zBt99+y9ixY7nhhhvyz9m4cSPDhw/ngw8+YODAgUyaNAmAH3/8kfHjx1O5\ncmUqV67MH3/8wb///W/OPvvsEpXJ0+Tgb3a9NTlUTMH8nyhP87k8Etu2JbmIUWGJwGjK/++HiKCq\nftv4LQD5ESsByGky09PZ1KmT379258TF0SQ1tcI3OVRUWRkZpBaRuy8hIanIpb/T0vzvc7LRXbqQ\nuHBhwObHZGC8+3V5/v0oKgBZE5wJGRvxZAIJR7Oi05cTL7L5EbjZ63VF/f2wAGRCpqKPeDKRU5LR\nZdFq3guY8BXIpmC+sIr6+2EByIRMRR7xZCKnpKPLopmuyXtU49aVKzl91y7+jm+yyor6+2EByIRM\nRR7xZCJX04i1pl5P86Onj7SF/X7kswBkQqa4NWac9KFgQi9SNY1Ybeq13w9fFoBMSNlqpaY0SjIv\nKVabej3ZRjLT0+33w80CkAm58rxaqQmPkjTPxWpTr/fUDvv9cHHuQi/GGONHyzZtyO7XjzlxcXgy\nCR/BNZemojZlxSqrARljYk5JmnrLY7qm8sICkDEmJgXb1OuUND7lfT2g0rAAZIwJCatpFM0Cjy/L\nBeeH5YIzxpjQsFxwxlRA5THDtClfLAAZU05FMwWN8WV9QL4sABljTARY4PFl84CMMcZEhQUgY4wx\nUWEByBhjIkBE8vuBjIv1ARljTARYH5AvC0DGlFM2MTQ8nL4UeCyxiah+2ERUY4w/nqXA/a3nU3gp\ncONS1ERUC0B+WAAyxhTmWdHU3zIQc+LiaJKaWmRuuoo6D6ioAGSDEIwxJgiLpk2jRxFLgadOnVrk\n+apa4YJPcSwAGWNMEGJ1KXAnswBkjDFB8CwF7o+TlwJ3MgtAxhgThJsGD2Z+gCATzFLgNg/IlwUg\nY4wJQlmXArc+IF+OGQUnIk2B6UB1oCawBBirqnnFnBcHTAMuBvKAH4FBqvpboeM6AyOB/UBtYLqq\nvhrgmjYKzhjjV1ZGBqlBLAVuXBw/DFtE6gNfA8mq+qyI1ARWA8tVdXAx534E/E9Ve7hfvwBcClzm\niSIi0hZ4F2ilql+KSBPgc6Cnqi70c00LQMYYEwKxEID+DdwJnOwVNHoCKUAjVd0Z4LxrgfeBi1X1\nG/e204GtwD9U9T/ubenAb6razevcFKCFql7o57oWgIwxIWXzgHw5pQ+oI/BZoU/91bhSBbUr5rz9\nnuADoKo/AT8DNwCISB3gKiCz0LmrgfNFpFHZi2+MMUWzPiBfTglA5wC/FNr2s/v7ucWc56929LPX\neWcDUsrrG2OMCROnBKDaQG6hbZ7XtUp4nufcWl7H4Oe4XFyBqajrG2OMCROnBKB9QLVC2zyv95fw\nPM+5+72Owc9x1QAt5vrGGBMSNg/Il1OWY/geOKXQNs/rTcWcd42f7acAH7r//QOuQFOi6yclJfls\nS0hIICEhoYjiGGOMf+W9/yctLY20tLQSneOUUXDjgAGUfBTcNcAHBDcK7ldVvdXr3BSgpape4Oe6\nNgrOGGNCIBZGwT2Jq5ZyF4B7HtBg4ClP8BGRaiKyTkRmek5S1WXAcmCU17VG45rjs8Br21jgBhG5\n2H2tc4FuuCamGmOMiQJHNMGp6i53bWaGiPwT18CAxUCi12GCK0tC4aUcbwGmichn/JkJ4QbvKoyq\nponIbUCKiHgyIdytqm+H7U0ZY4yXijoPqCiOaIJzGmuCM8aY0IiFJjhjjDEVjAUgY4wxUWEByBhj\nIsDmAflyxCAEY4wp76xf2ZfVgIwxxkSFBaAwKemM4PLOnkdB9jwKsudRUEV5HhaAwqSi/AcKlj2P\ngux5FFQRnkdJ+oAqwvMA6wMyxpiIsD4gX1YDMsYYExUWgIwxxkSFpeLxQ0TsoRhjTIhYKp4S8qzf\nXtqvxMTEMl+jPH3Z87DnYc+jYj6PolgAMsYYExUWgIwxxkSFBSBjjIkAywXny+YBGWNMBBTXH1IR\nWQ0oTBISEqJdBEex51GQPY+C7HkUVFGehw3D9sNWRDXGmNCwFVGNMSbKrA/Il/UBGWNMBFirii+r\nARljjIkKC0DGGGOiwgKQMcZEgPUB+bI+IGOMiQDrA/JlNSBjjDFRYQHIGGNMVFgAMsaYCLA+IF/W\nB2SMMRFgfUC+rAZkjDEmKmK6BiQiHYA7gRNwvZcawIuq+ryfY1sDo9zHnQgcASap6n8iV2JjjDEe\nMR2AgDnABFV9AkBELgcyROR4VZ3sOUhE2gEzgbaq+qN722zgCsACkDEm7Dz9P9YU96eYzoYtIu8C\nnVQ1r9C2M1W1qde274HHVfVZr20NgHhV3eDnupYN2xhjQqCobNgxXQNS1Rv9bD4IHOd5ISItgTOB\nDwud+yvwa1gLaIwxJqByNQhBRCoBrXA1zXn81f29kYi8IyIZIrJERP4v8iU0xhjjEdM1ID8GA7uA\niV7b6gECTAFuUNUd7lrRRyJyiqo+FoVyGmMqGOsD8lVuApCIdAQGAAmqethr11FAgRmqugNAVTNF\nZD4wHPAbgJKSkny2JSQkVJilco0xoVXeA09aWhppaWklOiemByF4iEh7XDWcjqq6vdC+HsBrQAdV\n/cBr+yhgHNBAVXcVOscGIRhjTAiU6yW5ReRGXLWYdp7gIyJ3ikic+5A0XDWgUwudegpwCMiJUFGN\nMcZ4iekAJCJ/B1KAkcApInKpiFwG3AXEAajqTuA5YKCI1HGfdybQA3hSVY9EpfDGmArFcsH5iukm\nOBHJxX8/lgJnqeo293GVgGTg78BuXMO0Z/nLmOA+3prgjDEmBIpqgovpABQuFoCMMSY0ynUfkDHG\nmNhkAcgYYyLA+oB8lZt5QMYY42TWrO/LakDGGGOiwgKQMcaYqLAAZIwxEWB9QL6sD8gYYyLA+oB8\nWQ3IGGNMVFgAMsYYExUWgIwxJgKsD8iX9QEZY0wEWB+QLwtAxjhMZno6i6ZNo/KePeTFx3PT4MG0\nbNMm2sUyJuQsGakflozURMsTQ4dSLyWFHjk5VAWOAPPj4sju148HHn882sUrwAKlCYZlwy4hC0Am\nGjLT09nUqRM9c3zXSJwTF0eT1FRatG4dhZL5iqVA6RSe/p+K9tli2bCNiQGLpk2jh5/gA9AjJ4fU\nqVMjXCL/MtPTqZeSQk938AGoCvTMyaFeSgpZGRnRLJ5jqWqFCz7FsQBkjENU3rMn/wO9sKpA5QDB\nKdJiJVAa57MAZIxD5MXHE2h9+CNAXlxcJIsTUKwESuN8FoCMcYibBg9mfoAgMz8ujpuHDIlwifyL\nlUDpNDYPyFfIByGIyE1A3VKe/ruqLgpleUrDBiGYaImFzv1YGixhoi+io+BE5E1gBlCaUD9QVf8R\n0gKVggUgE01ZGRmkTp1K5Zwc8tw1H6d9oMdCoDTOEOkANEhVp0f63FCyAGRM8WIhUJros3lAJWQB\nyBgTajYPyFdIByGISE0RmS4ib4vIIBGp4t7eVUSSQ3kvY4yJJTYPyFdIa0AiMgv4DPgRaAFcCPRW\n1b0i8puqnhSym4WR1YCMMSY0iqoBhToZ6WpVfcH978UiciIwQkSmhPg+xhhjYlyo5wHlicilIjJD\nRI5X1f8Bo4G/A9VDfC9jjIkZNg/IVzhGwbUBzgRe8W7HEpHrVPXDkN4sTKwJzhhjQsNGwZWQBSBj\njAmNqGbDFpGYGHhgjDEmsiKxImoP4MkI3McYE0UDBkxi48ZDfvc1aVKdF14YHuEShUdpF+KrqPOA\nihKJAGS9bsZUABs3HmLFiqQAewNtjy2eFESJ3imIli8nM4gURBZ4fEUiG7Y9dWNMzLOF+ELPlmMw\npgLLTE9ndJcuJLZty+guXchMT492kRzLFuILvUg0wRljHKgszUlOUNq+mNIq60J81gfkywKQMRWQ\nd3OSh6c5aU5KClmdOzs6s3U0gqdnIT5/QSiYhfgs8PiKRBPc8xG4hzGmBGK5OSlafTGxsmJtLAl7\nDUhVc8N9D2NMyZS1OcmfJk2qE2i0m2tfaCyaNo3EIoJn8tSpYam9tWzThsx+/ZgTYCE+J9cYnSrs\nAUhEmgAdgPWeVDzuZbv3qWpauO9vjPFV1uYkfyI1zyccwTNYDzz+OFmdO5NcioX4rA/IVyT6gEYC\n57u/e/wBPCkij6rqvAiUwRjj5abBg5m/fHmBPiAPpzcnhSN4lkSL1q1LVduxwOMrEn1AFwFXq+pH\nng2qmg60AQaW5cIi0kFEFojIMhFJF5FPReSuYs55UkSOuZOmGlMhtWzThux+/ZgTF8cR97YjwJwY\naE6Ktb4YG+oeWNiTkYpIuqr6/bAval+Q1/4fMEFVn3C/vhzIAMao6mQ/x18N/AeoC7R1B0J/17Vk\npCYokR4KHGpZGRmklqI5Kdo8o+D89cU4aQh5rJQznKKaDVtEvgQ6quovhbafCrynqheX4drvAp1U\nNa/QtjNVtWmhY2sCWcB0XCPzLACZMrEPl+hyevDMTE9nU6dOfps558TF0SQ11VHlDZdoB6ChwGDg\nJeB79+YmQG9gqqqGdLyniPwHaKaq5xTa/hSwCVgLLAcSLACZ0orEh0tFSe5ZXo3u0oXEhQsD9lUl\nd8NHLPwAACAASURBVO7M+P/+N9LFirhILsntQ1UfF5ETgGH8uSrqIWBKGIJPJaAV8EKh7dcAF6nq\nve5mOIsupkwiMRS4IiT3LM+iOVovVkRiGPbFwDxgIuBpFluvqvvDcLvBwC73vTz3rwXMADqF4X6m\ngrIPF1OcaI/WiwWRGAW3FhilqvtV9VP3V8iDj4h0BAYAHVT1sNeuKcBMVf3Bc2io720qHs+Hiz/2\n4WIg9kbrRUMk5gFlqert4byBiLQHHgOuVdUdhXa3B84XkU64gk+8e/sTIrIHGOdvQmxSUpLPfRIS\nEkhISAhdwU3MiuV5NCYyKlrmhLS0NNLS0kp0TiQGIcwD+qiqT2+qiDyrqneX8fo3Ao/gqvnscG+7\nE3hDVX0+Hdx9QMtwDULwmzTKBiE4k9M65cM9Ci4hISlgH9DVVyeRluZ/n3EWp4/WC7eoDkIAlgDv\niMirwE9Ante+FmW5sIj8HdeQ6n7AKSJyCq5azl3AUsBfQ7x4fZkY4rRO+bKkZTEVR2kzJ1QEkQhA\nL7u/X+dnX1mrGW/geg/vBHNdEVkOxLn3e5rgrrXqjimtcH64RCq5p4kMywXnKyJ9QEAPP9sF1+i4\nUlPVaiU8vm1Z7mdMJIWrSTHWszfEKgs8viIRgB5R1a3+dojISH/bTXg5rS/FRI6TVkG1/4cmEhNR\nU4vYfSGurAQmgpzWl2IiUytx2iqo9v/QRGRJbhGpjWvAgWeQgMfduCaJGlNhRapWEq2F3IyL9QH5\nilQmhPeAk3F1/nsHIPtJmKCVx075SNZKLHtDdFng8RWJGtBkYAzwGrBEVduKyHHAbbhqRMYEpTz2\nCUSyVhLN1DD+mhjLSlWZPH4ED46emF+7MLElEgGopqq+BAWqoIeB2SKyIAL3L5dsJFP5EMlaSbSy\nNwRqYsytcz5l6etZumgBOz59hvffvZz2N90SotKaSIpEAPJOmVVVRKqpaq779V8icP9yx0kjmUzZ\nlLZWUpoRZNFIDVNUE+PefWv4jAyOUrrlrZe+MYWp3fcy5PXJtLuxq+NrQdYH5CtSgxDuwrUe0HfA\n6+41e9oBh4s80fgIRZ9BeexLiVWlrZWUdgRZpLM3FNXEeGdeLq/XG4Bc2N1nX3H/D5cuWkCHRusQ\ngfaN1vH+u285vhbkCTzWevGnSASgx4FuuLIVTATScS2NsA/oGoH7lysl6TOweRbOF41aSSRTwxTX\nxJhw8ckkL0sq0TXzaz8dDgDQvumBmKkFWetFQZGYB/Qu8K7ntYicA5wP/OAvWagpWkn6DGyeRWwo\nSa3E80fF2rVb8P0ZVgec9UdFOAY+eNd+gJipBTltHlYwwj3QIyJNcN5U9SDwRaTvW17YIlflU7C1\nklj7oyLUAx8K1348YqEW1O/qq1kbYJ9T52GFe6BHJBakMyFki1yZWNKyTRuy+/VjTlxc/mikI8Cc\nUjYxFq79eHjXgpyqW0JCTM3D8h7oseT1yWEZPBHxGpApm4q2yFWssw7n0A18CFT78QhUC3JKX2is\ntV5EYqCHBaAYZOvQFM0pExQj3eEcF7eFZs2SHDmSMRQDHwLVfjwCfVA6pdkyllbRjdRAj0ik4mkc\nKBu2KT1b5CowJ0xQjEaHc7NmZ5TrVVLXfbGKfdmX8XFG4A9AVaX25ysdORih1dVXcxpAXJzjWy8i\nNdAjUgvSXROB+5hCKuJ8H6dMULTEn6H3YOK0aBehTDx9KFkZGY5uvYjkQI9IBKBWIvJjgH1HgB+B\nmarq3N7DGFUR5/k4ZYJiuFLsVMQ/Ksobp7deBDPQI1S/U5EIQM8DvXHNBdrs3nYWrlrRK0A88IKI\n1FbVVyJQHlMO+OtYVlWq70thyZDoT1AMV4dzRfyjwkROaQd6lFYkAlAc0FJVv/PeKCLnAfep6gAR\neQTX8twWgBzAKZ34RfHuWK5COk2YRo1qGxn0rx0Rn6DoLxge2BPPKZWrcU9ers/xTutwNpERC7ng\nSjvQo7QiEYDOKBx8AFT1O3cQQlW3iIjlhSuFcAwxdUInfrBOYygPksK/yOHh06HL5QX3R6IWFGiU\n1Q7qQuWnuTMv19EdzuWdU5otnRx4PCI90CMSAegsETlRVf/nvVFETgLO8dpkk2JLIdRDTJ3SiR+M\nKqTzICncTw5LqkGHG4lIu3WwtvM4sy78nV/O3OPYDmenCOdcHWu2DF6kB3pEIgAtAj4VkVnAD+5t\n5wC9gHdEpCowCvBtqzAR55RO/GA0YRp3k4MCS0+HqZf7P85fLShSE0Rrxjdm/H9fDvl1yxunzNUx\nkRWJADQYOAQ8DFRzb8sFnsIVeGriWpr73xEoS7mzYcO2Uu3zJ9ayDNfFNdIsUO3Ho3AwtYzEwXNK\nFoHyIFp9QE7OxhGJbNiHgaEiMpo/m9y+dyclBdeaQMnhLkd5dfDgsVLt8yfWsgz/jmuk2boasG8p\nfLz0z33HgK3163HmhRcCf7Zbxx1/YsxlJI4mq5mETjT6gJz+x1bEUvG4A846720icp+qzohUGUxg\nsZZluEmT6hzYE8/Mr6vx4J5c2FNw/5y4uP9v797j5Krr+4+/PgSIIDJRvDQoiBYTi5em3ALWJBtQ\nEkhIEy81XuIPmqK9qL9cfvanguzGG9aQ3WiLiiVgif4MqBDZgCEKWTYqGxSNpSgQ2gZaCFVDMxDA\nkGw+vz9mJszuXHZm98z3nDPn/Xw89rHsOWdmvpzdzGe+38/n+/0y52s3VgSTSxYs0ARRyYQ0bP8Q\nakfUo4CpwLFA+bvYXwMKQAkQcvJZFEpDP6uXv6iphVlbMUE0KVVWIuXSsBpHiLXg3gh8H5hIIddT\n/haX/LrEhDviiKfI57tqnmtE6MlnUWp2YdZWTBBVHkQaEToH1KrVOKIUoge0Evgk8E1go7vPNLPD\ngXdT6BFJmWYThpMnv47HHuuqca768eFCTz6LWjNLm6RpReIsyUIvMnQOKA3bP4QIQEe6+9Uw5BPA\ns8A/m9l3A7x+asSVMEz7KsPN0H5KyaReZPTS8GErRADaV/bfh5nZeHcvzfmZHOD1U2G0CcMoPjmm\nfZXhZmk/pcZloWfSrtLwYcta3S00s9uB64Crga8ALwa+A5wDvN7dT25pA0bBzDx0d/mSBQvoXL++\nZnd5xfz5fObGG4O2SUSiE9c8oK1bttAb44ctM8Pdqw6vhOgBrQLeAdwEXAb0A/OAPUC6x3MilIaE\noYiM3oEDB1j5mY/j7kGLeZK8/UPL119z95vd/UJ33+nu/0ZhMuqpwHHu/oNWv35alBKG1SQlYSgi\no/fcIr/a+qyk5UNwdV/cbKO7z46tATXEMQQ30N/P9nnzqiYM1+ZyTOrtTeynGJEkS8JyQu7Osvef\nSffsrSzbOJXua+9M3JSGVol1CM7Mng98GDiNwuZz5Q2Z0urXT4s0JAwlO5Lwph2VJCwndOuG7/Lm\nY7YmfkpDaCFyQP8MnA5sBYavjvnaAK+fGqrOik6SF2BMgyS8abeL5yZ6F35O8sTu0EIEoNcDk8sW\nHz3IzL4a4PVTJckJw7RI+gKMki1pW+Q3pBCbwP2yWvApuizA60uCDPT3F0rOZ87kkgULGOjvj/z5\nS/OpSlWFpflUx6xZw9YtWyJ9PZF6Sr2fc06qXOR343UrU7FLaiuF6AGtNrMlFOb+PDIsu38NcFaA\nNkgChOiZpGEBxpDaKZeTRmlb5De0EAHoCeD9FOYDRTrmaWazgYuAF1L4fzkCuMrdryy75iUUVt1+\nC4W9h3LAg8AlxbJwCSDU0vCaTzWUcjnxSfMiv6GECEBfp/CGfxVQvjyzUdgldSzWAp9199UAZnYa\nsMXMjnb3lcVr/hxYBJzh7rvMbBzwLaDPzN7o7v8zxjZIA0bbM2n2E3waFmCUsOJaTijti/yGECIA\nmbv/edUTZmP97d9F2X5C7v5TM7sNuJDCKtwAvwH+3t13Fa8ZNLOVFKry3gpcP8Y2SANG2zNp9hN8\nGhZgTIN2WgMurmHGLC3yO1ohAtD9Znaou++vcm7nWJ7Y3edUOfwMcHjZNd+ucQ3l10lrheqZaD5V\nNJQbGrvhi/zGtRZckoUIQJuAG8zsOuBRYLDsXCfwvaheyMwOAc4EvjbCpdOBPIX16SSAkD0Tzadq\nzLZtO+jo6Ko4ruKE1lDgqRQiAF1T/D63yrmofyNLgd9Rp7zbzHLAx4C/cfcnIn59qSF0z2T4fKpS\n+bcmpj4nnz+hxvBmtWMi0QsRgLYCC6scNwrFAJEws3OBDwAdxQ3vql1zOIVy8K+6e2SvLY2Jq2eS\n5YmptXI527btIJ/XQiSgVTPiFCIAfc7dH6p2wsw+EcULmNks4AvA2e5eNa9kZuOBG4DN7v65kZ6z\nq6ur4lhHRwcdHR1jams7GOkfbL3zoVd6CFX+nVS1htI6Orq44w4Ns4X8cNLuOaC+vj76+vqaekys\nq2FHwczmAJ8DZpeCj5ldBFzv7vniz8+jkGv6gbtfXjz2KuAUd/9OlecMvhp2WpT+wVYbRluyatWI\n55s11omUSd/oL66JooUA1FX13IwZXfT1VT/XTrQCfRjBV8M2s4+7e8PL7DR7fdnj/gy4ElgMHGtm\nx1IY2vsgcCuQN7MjgJuB/wQ2m9kpxYefCkylMCQnDRipN7HmhBMi722M9Q04yRNTB/r7uf+Gr3Ng\n10QeZwIPsJT9lA/9dMXVtEzQqhnxa9VacG9t8fUl1wMvoVDNdlfxaytDt3lYAswA3ld2zV3Al4m+\nCKKtbejpYWGdf7A3X3ZZ3fO93d2tbF5VSd3ob/Xy5WyfN48f7rqfLfSxjfWsYh6vYHks7cmiJH84\nyYpW5YD+yMyubuL6F4/mRdx9fAPXXIYWPY3ESP9gj3rmmWD/oBtNHCdxYmqtnuRHyANrWM589tPa\nT97tNNF0tEKvmtHuOaDRaFUAuh94VRPX39uidkiERvoHu+eII9hXI0hF+Q+6mcRxEiem1hv6+Wvy\nXEk3v2pxANI8n/AfThR4qnB3fQ37KtwWGe7OO+7wa3M5d6j4ujaX86u+9KW65wf6+1vehlqvMdDf\n7xfPn++XzpzpF8+fH0lbRuvSjo6q7S99vZmZDu4zZnTG1sas6Fm2zK/N5fzZ4r1/tvh31LNsWdxN\naxvF99Oq77UhyrClSUmdlzBSb2LJhz/M6h07WtrbGG3iOEkb/Y3Uk3wcLZgailbNiFfqy7BbIc4y\n7KjLmFth65Yt9Nb5BzvS+bHonDmTFXXmGnTOnMmK22+P5LVapV7575fHjefrr383R0545ZjLsLUX\nULJkNQcUvAxbRictkyZH6k20srfRDtst1OtJPrt4MXdF9EFDewElS9YCTyNCbMktDRqpzDmOMuak\nmbt0KetqBJk0bbewZNUqJvX2smL+/EKvbf58JvX2JqaXKxKCekAJonkJI0tiVdtoJSkvJRKHoAHI\nzFZR2DL712Z2iLsfCPn6SdcOw0shKHEsaZTVHFA9oXtAj1OYIwRwAXBwsqqZXeju11R7UFYkcdJk\nUqn3IGmjwFMpdAC6B9hkZuOAiWb2vuJxA17Lc3sHZVKrh5dUFSUiSRI6AM0APuLuvzKzc9x9U+mE\nmVXbsC5zWjm8pKqobNFyO5J0cQzB3Vf871cMO/eSwG1JnKE9lD8ufPsf+NEnb2PSpB+rhyJN0d9L\nsigHVElDcAmiHopI+1LgqRQ0ALn7TRS2TsDMznL3g1PWNQQnIpItsc0DcvfbzexEYDzwW2DTCA8R\nEZE2ElsAMrOPU8j7PARcASwEvhFXeyQsVeRJ1igHVCnOlRB+5e7fM7NZ7r7fzGptXCkRSVJVVFT5\nrqSuHC4ynAJPpTgD0OnFTwQTzew84DUxtiUT2q1X0czGdCKSPHEGoBVAJ3AycBfw6RjbkghJ6qEk\nXb2Vw7/8xSs4/bbHmXL65LYLuiLtJM4ihGeBi+N6/STKwptlKfezbduOMT1PvY3pLhrcyxW/3M0D\nE6rnmETioBxQJW3HIEGVcj/5/Aljep6RVg5/EVo5XJKltA21PCcxAcjMjjIzjTNJQ0orh1ejba1F\n0iER+wGZ2auBLcDbzOxlwCZ31/hJW6vMd+VyO5gy5YSG8l31Vg7/CjkeYBkv4baI2ioirRDnPKCF\n7r4OwN3/3cxOdPdn4mqPhFaZ75oypYu+vq6GHl1aOfzLX7yCiwb3HqyC+wo5VrKY/UwDBSBJEOWA\nKsXZAzrbzG4oFiOg4CPNWrJqFaff9jhX/HI3LyLP48WeTyH4iCSLAk+luIfg3mJmPywFIZFmTTl9\n8sFqt5dAcdit0PNR6bpIssUZgHYDpwMfMrNDgB+5+2dibI8EEPVcpyyUrou0K4urW2hmZwGPuvt9\nZnYoMNnd742lMcOYmau7LCJRymoOyMxwd6t2LpYekJl1AIcDDwC4+34gEcFHRKQVshZ4GhFkHpCZ\n/T8z+6yZnWtmR7t7H7ADrYQgIpJZQYbgij2eOcCbgSnA/cDdwAvd/W0tb0CTNAQnIhKNekNwwXNA\nxdUOzgAWA19x958EbUADFIBEJGrKAVUKvhSPu//e3fvcfREwNfTri4jEQWvBVQqVA/qimV1Y3IK7\n3GCI1xcRkeQJlQN6FzAfmA4Y8AvgKWCCu5/T8gY0SUNwIiLRSFoO6ERgRtnX0UA/sN7drwnamBoU\ngEQkasoBVTkX980wsxMo9IxOcvdETGtXABIRiUaiA1ASKQC1j4H+fjb09DBu924GJ0xg7tKlnDF9\netzNEskMBaAmKQC1h9XLl3PMmjUszOcPbtewLpdj1+LFLFm1Ku7miWRC2wYgM5sNXAS8kMKyQkcA\nV7n7lVWuvRh4O7AHcGCZu99d43kVgFJuoL+f7fPmVd2wbm0ux6TeXqZO07YNEo5yQJUSsyX3KK0F\ntrj7We4+Hfgb4Itm9tHyi8zsUuD9wIzidV8DbjOz44O3WILY0NPDwirBB2BhPk9vd3fgFknWaR5Q\npbQHoLuAfyj94O4/pbAZzIWlY2Z2FPB3wJfc/cnidd8Eflc8PioD/f1csmABnTNncsmCBQz094/2\nqaQFxu3ezWE1zh0GjKsRnEQknLg3pBsTd59T5fAzFFbaLumgMDS3ddh1dwLnjeZ1S7mFzvLcwubN\nDCi3kBiDEyawD6oGoX3AYC4XuEUiMlzae0BDFDe2O5PC0FxJafWFR4dd/gjwyuJeRA0b6O/nmDVr\nWFQMPlB4k1uUz3PMmjVs3bJlNE2XiM1dupR1NYLMulyO85ctC9wiyTozO5gHkoK2CkDAUgpDa5eV\nHTuq+H3vsGtLPx/ZzAsot5AOZ0yfzq7Fi1mby7GveGwfhQKEXYsXqwBBglMOqFKqh+DKmdm5wAeA\nDnd/tuzUnuL38cMeUvr56WZeR7mF9FiyahVb589nRXc34/J5Bos9HwUfkWRoiwBkZrOALwBnu/vO\nYacfLH4/lqHDcMcCDxV3Y63Q1dVVcayjo0O5hZSZOm2aAo5IAH19ffT19TX1mFTPAwIwsznA54DZ\npeBjZhcB17t7vlgF99/A37n7FWWP2w7c6u4fqvKcNecBaX6JiIyG5gFVSnUOyMz+DFgDfAI41sxO\nMbNTgQ8COQB33wN8HviwmR1dfNx7gBdT6DU1RbkFERkN5YAqpboHZGZ7qT6M6MCr3f3hsms/AbwT\neLJ4fqm7/7zG8464EsLWLVvoVW5BRKSutl2Kp1W0FI+ISDTadghORCQtNA+oUltUwYmIJJ1GVSqp\nByQiIrFQABIRkVgoAImIBKAcUCXlgEREAlAOqJJ6QCIiEgsFIBERiYUCkIhIAMoBVVIOSEQkAOWA\nKqkHJCIisVAAEhGRWCgAiYgEoBxQJeWAREQCUA6oknpAIiISCwUgERGJhQKQiEgAygFVUg5IRCQA\n5YAqqQckIiKxUAASEZFYKACJiASgHFAl5YBERAJQDqiSekAiIhILBSAREYmFApCISADKAVVSDkhE\nJADlgCqpByQiIrFQAGqRvr6+uJuQKLofQ+l+DKX7MVRW7ocCUItk5Q+oUbofQ+l+DJWF+9FMDigL\n9wOUAxIRCUI5oErqAYmISCwUgEREJBambmElM9NNERGJiLtXTX6pB1SDu4/pq7Ozc8zP0U5fuh+6\nH7of2bwf9SgAiYhILBSAREQkFgpAIiIBaC24SpoHJCISwEj5kCxSD6hFOjo64m5Couh+DKX7MZTu\nx1BZuR8qw67CzFz3RURk7MwMVxm2iEh8lAOq1DYByMwuNLPfmdmlNc5fbGY/N7N+M7vDzE4J3UYR\nya5G5sVkTeqLEMxsArAOuA94YY1rLgXeC5zq7k+a2XuB28zsje7+cLjWiohISTv0gJ4PdLr7EqCi\nf2tmRwF/B3zJ3Z8EcPdvAr8rHhcRkRikvgfk7o8Aj9S5pAM4Atg67PidwHktapaIyBCl/I+G4Z7T\nDj2gkZxY/P7osOOPAK80s9QHYRFJPuWAKmUhAB1V/L532PHSz0cGbIuIiBRl4dP/nuL38cOOl35+\nutqDurq6Ko51dHRkZoKYiEgz+vr6mt5KvK0moprZAaDL3T9Vdmwu8D1gqrv/rOz4tcCb3f3VVZ5H\nE1FFJFJZzQFlfSJqH/B7YOqw42cCtwRvjYhkknJAldo+ALn7HuDzwIfN7GgAM3sP8GLgC3G2TUQk\ny9oiB2Rm1wMvARy4wMw6gG533wDg7p82s0HgDjN7snjd2fUmoZbngJT7ERFpTDO5oLbKAUVFOSAR\niZpyQJXaogckIpJ0WQs8jWj7HJCIiCSTApCIiMRCQ3A1qAhBRKKUlRyQihDGSEUIIiLRyPpEVBER\nSSAFIBERiYUCkIhIAGZ2MA8kBSpCqEFFCCISpazklVWEMEYqQhARiYaKEEREJHE0BJdSA/39bOjp\nYdzu3QxOmMDcpUs5Y/r0uJslIjVkZR5QMzQEV0XSh+BWL1/OMWvWsDCf5zBgH7Aul2PX4sUsWbUq\n7uaJiBxUbwhOAaiKJAeggf5+ts+bx6J8vuLc2lyOSb29TJ02LYaWiYhU0mrYo5DUKrgNPT10Vgk+\nAAvzeVZ0dysAiUhsVAU3RknuAXXOnMmKOr/czpkzWXH77eEaJCINyWoOSFVwbWRwwgT21Ti3DxjM\n5UI2R0Qa5O6ZCz4jUQBKmblLl7KuRpBZl8tx/rJlgVskIjI6CkApc8b06exavJi1udzBntA+CgUI\nuxYvVv5HRFJDOaAqkpwDKtm6ZQu93d2My+cZLPZ8FHxEkks5oCrnsnYzGhFnANIEUxFpJyrDHoU4\nyrBLE0w7yyeYbt7MgCaYikhKqAx7jOLoAWmCqYi0I5Vhp8CGnh4W1plg2tvdHbhFIhIl7QdUSUNw\nCTFu924Oq3HuMGBcjeAkIumg0aZK6gElhCaYikjWKAAlhCaYikjWKAAlhCaYirQ35YAqqQquijjn\nAWmCqYi0E80DGoW4tmOYOm2aAo6IpJbmAY1RGpbiGYsPfODzPPDA76uemzTpeXztax8L3CIRaVfq\nAWVUrUCzbdsO8vnXAtUCTVermyWSSVldC64eBaA29sADv+eOO7pqnK11XERaQYGnkqrgREQkFgpA\nIiISCwUgEZEANA+oknJAIiIBKAdUSQEoo3K5HUyZ0lVxfNKk54VvTINUPi7SXhSA2lghmHTVOPfa\n1L1hq6pPpL0oALWxtAUYkXameUCVFIBqiGspHijsjrqhp4dxu3czOGECc5cu5Yzp04O9vohELyuB\nR0vxjFGcS/GsXr6cY9asYWE+z2EUVsReV1wRe8mqVbG0KSk6OrpqDsHNmNFFX1/1cyISH23JnRID\n/f0cs2YNi4rBBwq7oS7K5zlmzRq2btkSZ/NERCKlIbgE2dDTQ2eNrbcX5vOs6O6uWClblWEi6aAc\nUCUFoAQZt3v3wZ7PcIcB46oEp1ZUhrk7Kz/zcT56yWWJmjhXv6ovueXjIqDAU40CUIIMTpjAPqga\nhPYBg1W27L7//odrPl+9c/XcuuG77Pzpl9l082nMmvv2UT1HK6g3J9JelANKkLlLl7KuSpCBQiHC\n+cuWVRx/5pkDNZ+v3rla3J1br7+c7nc9ycbrVupT2wgG+vu5ZMECOmfO5JIFCxjo74+7SSKpoQCU\nIGdMn86uxYtZm8uxr3hsH7C2WAUXYqfUWzd8l9nH34MZzDr+HjbdfEPLXzOtVi9fzvZ58+hcv54V\nfX10rl/P9nnzWL18edxNkwTSWnCVVIZdRdw7om7dsoXe7m7G5fMMFns+tYLPhAkXkM9/veq5XO4C\ndu+ufq4ad2fZ+8+ke/ZWzMAdlm2cSve1d+ofzjAD/f1snzePRVXycmtzOSb19mprdRG0I2rqTJ02\nLZY3r/LeDzCkF5SkXFASjKZiUUSGUgBKuSOOeIp8vqvmuUYdzP3MfnrI8VknPc2y61Zyzpy3qRdU\nZjQViyIylAJQyk2e/Doee6yrxrnqx6sZ3vspUS+outFULEq2aR5QJQWglItibkyt3k+JekGV5i5d\nyrrNm6vmgGpVLEq2KfBUUhFCFY0UIbTTgqEbe7+DDfwvZr2uegAC2HjvkdiZ1465F9RO903r9omM\nrF4RggJQFSMFoHZ741m5Yil7dv68bu/G3Tlq4sl8tLNn1K/TqvsWZ1BrpmJRJIsUgJpULwCp/HZ0\nWnXf2u3DgLSvrOaAVIY9CrX2A1L57ei04r6Vrx5eUlo9fO2aNWydP1+/C0mMrASeZvYDUgCqoTwA\nlVP57eiGvFpx3/RhQCR5hm/guWLFiprXBg1AZvYGYAYwEXgRsAvYCdzm7veFbMtoZb38tjTk1Vk+\n5LV5MwMjDHm14r7pw4BIugVZC87MzjSzfwF+CVwOXAicB/wF0A3ca2Y/M7OTQ7RnLEazYGi7GMuG\nea24b6WgVk0WPgxIumgtuEotD0Bm9l7gWuDLwKvc/Xnufqy7v7L4fTzwmuI13zGzea1u01gkYcHQ\nuGzo6WFhnSGv3u7umo9txX3L8ocBSR93z0weqFEtrYIzs1cAVwLvdPfak0yeuz4HrAMWufvvqJsG\ngAAAGw5JREFUWtawkdsx4jygNJbfjnX31M6ZM1lRJ7nYOXMmK26/ve5zRH3fRlsFl4b5SNrtVtpB\nbFVw7v5fwJwmrs8D57auRdGJa8HQsRjr7qlR5HGivm9LVq1i6/z5rGgiqI02jxVaK3a7FUmS0EUI\nk4DZwK/c/YfFY3OBPe7eF7It0rykLj/TTFBT6bbEJavzgOoJvSHdJ4D3AuW/gSeA1Wb27sBtkSa1\nQ/5rLHkskbFQDqhS6HlAbwD+1N0PDmy7e7+ZTQduAb4VuD3SpNEMeSWJSrdFkiN0AHqqPPiUuPsT\nZnYgcFtklNKY/ypJwzyuUoHE0du2cRK/5AGWsp9kFUiIRCH0EFzOzI4dftDMXg5MCNwWyaCklm4P\n9PdzyYIFvPO44/iXt7yFzvXruSm/g22sZxXzeAXLY2mXREfzgCqF7gFdC9xlZlcDDxaPTQIuoDAh\nVVooir2DGpHkEuczpk9nYPFi1tYo3R5Nz26s5dKlqrzZ+TyTgUVl5w4DPkKeQ8ddwddf/zhHTnjl\nweeVdFH+p1Lw1bDN7DPAMqD0L+j3wOXufmnQhtTRyDwgqS7U6tRjfdOPcj5SR0dXzXLpGTO66Our\nfg6GrhJ+CdBJ7eHBFfPn85kbbxxVG0XikqjVsN39EjO7DDipeOhX7v5U6HZI9EKWONebI+PeyRc+\n/TE+esllNYc8kpLHKl9QdRzVgw+oQELaU+gcEADu/pS7/7T4peDTJkKWOD+9+yFOYgFvZiYnsYBD\n6T947pknf83On36ZTTffENnrtUp5Vd4gaG27NqYcUKXgPaDiitjLgdcXD90DrHL3fw3dlqRJ+9Ir\noUqcVy9fzgX/+i0uYu/BYb6vsJmVLOa/uJwX2k/ofteTLLtuJefMeRtmlti8VHlV3lyK61BVuU5r\n26WfhvUrhV4JYQHwbeBR4N+Kh88G3mdm73T39SHbkzRpX3olRInzwWG+wb0Hj5US9bCGS8bn+OuO\n32AGs46/h00338CvN/8ksUvvlK8ucQYwAKwFFkIkBRIiSRa6B/Q54AJ3/0b5QTNbBFwGZDoApV0z\nS/WMtrdXbxO6vyLP+uNW82cnFwayZp30NBf906VM7/svFj3xxMHrkrT0zvCqvCXAj4HFhx7KoRMn\ncuwpp6Rqoq9IM0IHoD3Dgw+Au681s4+EaICZXQisBL7k7p8K8ZpZ0UyJ82h7e/WG+W4fDx+ek6c0\nzG4G5594H4feWn2Oc1S7po61vL3a6hJ/q6DTdrQWXKXQAWiXmR3q7vvLD5rZocBjZT+f6+7fj/KF\nzWwChSH2+4AXRvnc8pxWL9VTa5jPge8fB6tPGxps5p18gGXHwXkPwvD0b1R5qShyc0mpypPWUeCp\nFDoArQNuNLMe4KHisROADwBXm9nxxWOfBCINQMDzgU533xqqt5VVrXwzrTXMd+t4eOscGF5kZAbn\nnAebroRZe4eeS3NlWdoLVkQgfAC6uvh9Ds+tiF16y3hH2c+Rf1Rw90eAR6J+Xgmr2jDfs8A3ThjH\n2tMGqz5m9umw7BY4Z1gvKM2VZWkvWBGB8AHol8CSEa4xoCdAWxIn1FI5aTd8mG/H/j285033YFY9\nAJnBWXPglq/CnL2qLJN4KAdUKXQAutLd76h2wsxe5+73Fv/7yrDNSgYNmzSufJhv5YqlbN15BHdt\nqT3JL797N//x+ie56+hXpm4LiagldU5Uu1PgqRQ6AJ1c59wVQAeAu381SGskNlH29j7amckO86hE\nuR25ApmMVegA9CYzG+fuB8dKzOwIYDWQqI+jXV1dFcc6Ojro6OgI3pZ2pN5eeFGu1RdlIJP20NfX\nR19fX3MPKm0TG+IL2EWhEu6Q4s+nAw8A/w08HLAdB4BL65x3kSSbMaPTwat+zZjRWfUxF8+f78/W\neNCz4BfPn9/Qa995xx1+bS5X9XmuzeV8oL8/wv/T9kGhuCruZgRX/H+u+l4bugd0FYV5ONeY2Q7g\nExTKrf8SeG/gtkgbS8rwUKvaMZohzKjW6qu3GkVUk3vbkSsHVCFoAHL3/wtgZkcCXwT+xt2/Vjz2\ni1a/vpldD7yEwieRC8ysA+h29w2tfm0JJynDQ61sx2iGMEdaq++e++5joL9/xAAZatFZaX8tD0Bl\nk0vL9QKTgdeZ2XEUSq8/B7yplW1x9z9v9NryHJByP+kRck+iNLSjXN21+oDlO3eyfd68EQNkiEVn\nG+HurPzMx+vu+yThNZULqjU2F9UXhXzLYJWvA2XnDgCDrW5LE20ew4inxCmqPEe7tGO4nmXL/Npc\n7mDbngW/FryniTxOUnJA37/p277k/Bf4xt7vBHm9sUI5oFhyQJp8Kge1egmZpAwPJaUdw5Um8b7r\nXe/idTt34sD5wNSya0bK4zSz6GyruDu3Xn95xb5PSebKAVUIEYBqTj4tZ2ZfCNAWiVmrl5BJyvBQ\nUtpRzdRp03jD5Mms2Lmz6vlGAmSrF50dya0bvsvs4+8Zsu/TrLlvD/LaEp2WByBvcFKpu3+r1W2R\n9tfMnkRZaEctUQTIuFbwPtj7mf00UNj3KS29IBmqpQGoWGDwF+6+oonHfBZY7e6/bV3LRqYihHSo\nVua8K+bhIUjGMFU9SQ+Q9ZT3foDU9IKyshZcM0UI1uqbUdx64WXAJe7+73Wuey2FSrh73L2zpY0a\ngZl5u/+RxKWjo6vmENyMGV309Q09Vy9ndOSu23j3f95T9Q3+zPnz6Y1peKjc1i1bEtGOakpl4tXu\nX1JXM3B3lr3/TLpnbx2y9YY7LNs4le5r71QvKGHMDHev+ksJMQS31MwuBu4vTj7dTmFFhP0URgBe\nDLwGeDnwMXdf3eo2SXrUyhkdSj9fHPd5Fg0+t8lPeZkz8+fzmRtvDNfQGpK80VzceZzRGN77KUlL\nL0iGCjIR1d0/a2bXAAsprPn2Ggq7ku4CdlKogLve3X8Toj2SfpPo4aLBvVXPaTZ+46IMkK2ucBye\n+xlOuaD0CbYSgrs/CnQXvySjoloF+0Uks8w5y1pd4Vir91OS9F5QVnJAzQi9FlxqqAihNaJaBftx\nklvmLK1xz89/zJ5dp3JnnX2f3J2j7v5RIgNQVgJPM0UICkA1VNuOQZLjAZbyT+O+z99UGYZLehWX\njI72fUqH4R/YV6yoXQStACSptJ/prJ34J7zgyV8nssy5Ua3Om4gkmQKQJFr9nNGfMWnRF1JVxTVc\nq/MmkhzKAVVSAJJEa6QHkKaAI9mlwFMplgBkZquAq9z912Z2iLsfiKMdIhKdZiscNfwocfWAHgfu\nL/73BcDVpRNmdqG7XxNHo8qpCi4d9CbWWs3c32bvtYYf21MaquDuATaZ2Thgopm9r3jcgNcCiQpA\nklx6E2utqO5vtTX7siYrOaA0VMHNAD7i7r8ys3PcfVPphJnNjalN0oaqvfGNtOW0PNfz2bZtB5WB\n5nlA472dWluT733BH1V57sal7Xfb7oFnNOIcgruv+N+vGHbuJYHbIm1q77/dyvZ5qyve+Ebacjqk\nqFaGiFqUPZ9aW5M/uecX/Iwt7Kf5IpJaQS1Jv1sZmYbgpC0dSj+Ldv6i5mKlW+fPj716bqC/n5f+\ndisTLR2f4EdjQ08PnTWWRbpocC9X0M2vmgxA9YJaUn630phYApC73wTcBGBmZ7n77aVzGoKTKCR9\nsdKsfIIfaWvyF9H8mn31gloSfre1ZCUH1IzY5wG5++1mdiIwHvgtsGmEhwShKrh0S/JipVn6BD/S\nzquHHLOTGa/vqjhXb/hxpKCW1IVosxJ40lAFd5CZfZxC3uch4AoKWzZ8I9ZGoSq4tKiVQ/F/3cm+\nXclcrHQsn+CTUHaey+1gypSuhnJUI+28+oUbv9Z0sI1iO3FpnTRUwZX7lbt/z8xmuft+M9sXd4Mk\nPWq94Q70n8W6efMSueX0WD7BJ6HsfMqUEyp2rq2lFVuTx72deNqq75IsCQHo9OLY6EQzO4/CZnUi\nY9KKN76ohPoEP5beUpTVeVHvvBrn73YsuTvlgCpZyJthZm8EBt393rJjhwOdwMnAXcCn3X1/sEZV\nYWauP5L2sHXLFnoTtljpQH8/22v0ztbmckzq7a3Zxo6Orpo9oBkzuob0TJq5Nm6jCZahf7dj+b1l\nmZnh7lU3cQrdA9oGrAPeUzrg7s8CFwduh2RElFtORyXJvbO4jGZoMfTvNq3Vd0kWOgBtdff3jHyZ\nSHuLelhKWi+t1XdJFjoA7TCz57l7RV/bzL7i7n8duD0isUli70xqG2vuTjmgSqED0EbgJjP7BvCf\nwGDZuamB2yKSOklduicLxlp9p8BTKXQAKi2x85Yq5xL129FEVEkibS8RH+XuGpPkiahbKUw0Hc6A\nbwVuS12aiCppp95S9JS7G1kzE1FDl2Gf7+69Nc7NdPfNwRpTh8qwRcJKwgoPrZbVHFC9MuygASgt\nFIBERKJRLwAdEroxIiIioAAkIiIxUQASEQnAzA7mgaQgCYuRioi0PeWVK6kHJCIisVAAEhGRWCgA\niYgEoBxQJeWAatBSPCISpazkgJpZikcTUavQRFQRkWhoIqqIiCSOApCISABmxgufb5kZimuEApCI\nSADfv+nbXHD2C9h08w1xNyUxFIBERFrM3bn1+svpfteTbLxupXpBRQpAIiItNNDfzwUzpjLzpT/F\nDM6a+AsumDGVzpkzuWTBAgb6++NuYmxUBVeFquBEJAqrly/nRVddxd0vfYLVXWAG7rCwC9Y9CPt5\nbkfVJatWxdza1lAVnIhIYAP9/RyzZg0v3fsE580pBB8ofH/fefCP4+EwYFE+zzFr1rB1y5ZY21uN\nu/OFT3+sZUOGmogqkkFZ2IE0bht6erg0n+f/ngjdpw09N/d0eOct8KEHwYCF+TwrursTt7X3rRu+\ny86ffplNN5/GrLlvj/z5FYBEMuiBB37PHXd01Thb63h7GujvZ0NPD+N272ZwwgTmLl3KGdOnj/l5\nx+3eze3jYXZZ76fEDBadB5uuhFl7Cz2hcfn8mF8zSuWFE8uuW8k5c94W+VJCGoITkcxavXw52+fN\no3P9elb09dG5fj3b581j9fLlY37u/bkc3z8Ozjmt+vl5p8PG48CBfcBgLjfm14zSrRu+y+zj78EM\nZh1/T0vKxxWARCSTSjmaRfk8hxWPRZmTedmbTuatVXo/JWYw6zzYNL5QiHD+smVjer0olXo/55z0\nNACzTnq6JeXjGoITkUza0NNDZ41hryhyMnuf+R9uvPflbLjtMV66f5BDgAPAf1OofjsOGAQemXA4\nb3zv4kTlf8p7P8CQXlCUuSAFIBHJpHG7dx/s+QwXRU7mo509QA9bt2yht7sby+c5kMsx9eyz+ffb\nbsPzeTyX44PLliUq+BzM/cx+esjxWSc9HXkuSAGoBm3HIO2gVrXbtm07gM8D2a12G5wwgX1QNQhF\nmZOZOm0aU6dNO/im7TfeCB/6UCTP3QrDez8ljfaCtB3DGGkiqrSLjo6umtVuudwFTJlyQsXxdivD\nrhWEn979EH/x63X81bOV59bmckzq7U1UzyQEd2fZ+8+ke/bWqrkrd1i2cSrd197ZcC+o3kRU9YBE\nMmrKlBPo6+uKuxkt19v7AI89dnXVc08c+VOef8R/sbBYiLCP51YmyFrwgdq9n5Koc0EKQCLS1p55\n5kDNc48ddiqTer/Ciu5uxuXzDBar0bIYfADu+fmP2bPrVO7cUrt34+4cdfePFIBERMaqlKNptYM5\noAQP7xcKJ8JRABIRCSDJgScumogqIiKxUA9IpI1NmvQ8aq3tVjgnEh+VYVehMmyR9jFx4jt57LHX\nVT33B39wLzt3fjtIO+LKAbVqsdVGqQxbRDLr/PNPqbP1xCnB2hHHh9rVy5dzzJo1dJaXmW/ezEBC\nNsBTD6gK9YBEJO0G+vvZPm8ei6osKRRyoq12RBURyZgNPT0srLPYam93d+AWVVIAEhEJwMwi39Ct\nnlYvthoFBSARkQDcPWgeqLTYajVJ2QBPAUhEpA3NXbqUdTWCTFI2wFMAEhFpQ2dMn86uxYtZm8sd\n7Anto1CAkJTFVlUFV4Wq4EQkanHNAyptiBfXYqv1quAUgKpQABIRiYbKsEVEJHEUgEREJBaZCUBm\ndpKZ/cDMtpjZ3Wb2WTMbF3e7RCQbQs8DSoNMBCAzezFwO3CDu08DpgFzgMtjbZiIZEboeUBpkIkA\nBPzv4vevArj708Aq4G/N7A9ia5WISIZlJQCdC/xsWGnbTyisBn5OPE0SEcm2rASgE4FHhx17pPj9\nNYHbIiIZpBxQpazsB3QUsHfYsdLPzw/cFhHJIOV/KmWlB7QHGD/sWOnnpwK3RUREyE4P6EHg2GHH\nSj9vr/aArq6uimMdHR10dHRE2S4RkbbQ19dHX19fU4/JxFI8ZvYp4APAxFIhgpktAtYAx7v7Y8Ou\n11I8IhKpuNaCi5uW4oEvAQ58EMDMjgSWAv84PPiIiLSC5gFVykQPCMDM/gj4Bwq5n+cDtwCd7j5Y\n5Vr1gEREIlCvB5SVHBDu/mvgLY1eX54DUu5HRKQxzeSCMtMDaoZ6QCISNeWAKmWmByQiEqesBZ5G\nZKUIQUREEkY9oBqUAxIRaZ5yQGOkHJCIRE05oErqAYmIBJC1wNMI5YBERCQWCkAiIhILDcHVoCIE\nEYlSVnJAKkIYIxUhiIhEQ4uRiohI4igAiYhILBSAREQCMLODeSApUBGCiEgAyitXUgCqQVVwIiLN\nUxXcGEVRBdfX16egVUb3Yyjdj6F0P4Zqp/uhKrgYNPoJICt0P4bS/RgqC/ejmRxQFu4HaAhORCQI\njTZVUg9IRERioQAkIiKxUAASEQlA84AqqQquCjPTTRERiUitKjgFIBERiYWG4EREJBYKQCIiEgsF\nIBERiYUCUITM7CgzW2pmd5jZD81sq5n1mtmfVLn25WZ2g5ndaWY/M7OvmNnz42h3q5nZBDO72swO\nmNnxNa5ZaGZ3mVmfmf3YzL5rZn8Yuq0hNHg/xpnZ35lZf/GePGBmt5jZy0K3t9UauR9l1x5tZg+b\n2b+Hal9oI90PMzvTzNYW/y7uMLO7zexjZnZYHO0dCwWgaM0ALgYudPe3uPtUYDvQZ2avLl1kZocD\nPwC2u/uZwOnACcA3wze5tczsbGAz8DygasWLmU2n8P9+mbt3uPufAo8At5pZW63W0cj9KLoGeCNw\nlrt3ANOBU4BjWt3GkJq4HyWrgSNb2qgYNXg/vgT8rvhvZQbwTuD/ULg3qaIAFK3dwJfcvfzT2WXA\nC4B3lB1bBJxYPIe7HwA+B8wzs1MDtTUUBzqAW+tcU/p/3lh2bCPwKuCk1jQrNiPeDzMrvan8rbvv\nB3D3x4A5wEMB2hhSI38fAJjZucDLgZta3KY4NXI/7gX+/uADCu831wHvt5RNNFIAipC7/9jdPzXs\n8DPF74eXHTsXeMDdd5cdGwAOAOe1sInBufvt7p4f4bKbgSeBv4CDPcT3AYPAb1vbwrAavB8LgZ8P\nv87df+buT7WudeE1eD8wswnAKuAvgVS9yTajkfvh7hcUP5CUe4bC2p6pek9PVWNTajqwH1hXduxE\n4NHyi9x9H/A74DXhmpYM7n4/heHLDxbH9h8F5gIfdvedsTYuHlOAR4v5xM3FnNg3zGxy3A2L0Wqg\n293/M+6GJNQ0YJ27D8bdkGa01fh6K5jZ0cDEka4rvokOf+w44FNAp7s/WHbqKKDaP6S9QKILEcZy\nP+o85xso5MQuc/ee4n17B4WAnGituB8U8jwnU/gbOcvd3cwuB+42sze4+3+MrrWt16K/j7nAse5+\n1VjaFocW/X0Mf423URiaTN3oiQLQyN4J/BO1E4JWPDeuyrmrgbvd/bJhx/cA46tcPx5I+hDLWO5H\nLSuAJ9y9B8DdB83sFmCXmc1y981jaXCLteJ+7C9+/3jZzogXA38FfARYOop2hhLp/SgOvV0OvDWS\n1oXXir+P5x5sdjKF+zPL3XeNqoUx0hDcCNx9jbsf4u7janwd4u5D/nis4Crg9+7+wSpP+yBw7LDH\nHAa8mELVXGKN5n40YDIwpKzW3Z8EdlEo2EisFt2PhylUOe0te529wE4SPkTbgvtxFoWA/M9mdruZ\nbQZmA39Q/Hlj/YfHq0V/HwAUp3d8E5jv7vdG2/IwFIAiVqxCuQZ4phR8inX9F5VddgswycxyZcfO\noPBp6JZgjU2Oh6kMyIdTGIp6OpYWxes24MXl8zrM7BDgpRSCUGa4+w3u/np3P6v4NZNCheRjxZ9n\nx93GOJjZaRSCz9vd/V+Kx95hZifE2a5mKQBFqPgm8Q0Kb6ZfN7NTzOwUCgnC95Rd+g0KPZ2PFx83\nDvgY8D13/1nYVgdTr3LpCuCPzKy8VP2Txe9tNzeqqN79+BrwGwpzO0o+DBwG/EMrGxWjZirb2rYK\nrkzN/0czOwPopTB144ji+8ypwPuBuhN5k0arYUfIzN5NIbhU0+fuZ5ddeyyFN5NjKZRo3wUsd/e2\n+sRfHKNeBbyMwlDbVuD3wDmlOS7F6+YDH6VQin44hZ7PZ939h8Eb3UJN3I8/pFD5NZFCXvAp4BPu\nvi14o1uo0ftRvHYWhQ9qk4EJFKYu/KBKjjW1GrkfZnY/hUraama6e3+ItkZBAUhERGKhITgREYmF\nApCIiMRCAUhERGKhACQiIrFQABIRkVgoAImISCwUgEREJBYKQCIiEgsFIJGEM7MVZnavmT1rZlWX\n9jezJWZ2oLhv0LtDt1FkNLQdg0jCuXtncaflC4A/ZNiCpGZ2PPDHwH3u/r7gDRQZJfWARNLhALAD\neFWVc2+hsF7Yj0I2SGSsFIBEEs7MTqSwevpDwAnDzr0Z6Af+FPhx8MaJjIECkEjy/SmF3s0OynpA\nxW08TgB+C7wO9YAkZRSARJLveHd/mEIAOqHs+NuAG4A3A79x938L3zSR0VMAEkmPHRR7QGb2UmBP\ncf+oN6HhN0khBSCRBDOzFwK/K/64A3h5cefdOe7+/eLxN6PhN0khlWGLJNubgJ8U//thCh8a305h\nB13M7DDgNGBZ8eezgHMp7BgKcJu7rwvZYJFGKQCJJNubgE8CuPt+M3sUeKO7f7t4/lRgEPhF8edH\nKWzfvRn4obs/G7i9Ig3TEJxIApnZG8zseuCjwLeKOR+AO4DLraAH+AfAgS+a2UR3vw84HQUfSQFz\n97jbICIRMbNDgQ3uPjvutoiMRD0gkfYyGRUkSEqoByQiIrFQD0hERGKhACQiIrFQABIRkVgoAImI\nSCwUgEREJBYKQCIiEgsFIBERiYUCkIiIxEIBSEREYvH/AVaU34r2wiDnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b0af590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = 6, 10\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(3, 1)\n",
    "\n",
    "# g-r\n",
    "ax1.axhline(0.85, c='w')\n",
    "ax1.axhline(0.85, c='k', ls=':')\n",
    "ax1.axvline(-12.3, c='w')\n",
    "ax1.axvline(-12.3, c='k', ls=':')\n",
    "\n",
    "ax1.plot(Mr[msats&msk],gr[msats&msk],'ro',label='SAGA Satellite',ms=8,zorder=4)\n",
    "ax1.plot(Mr[mlowz&msk&~msats],gr[mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7,zorder=3)\n",
    "ax1.yaxis.set_major_locator(ticker.MultipleLocator(0.25))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax1.plot(MW_r,MW_gr,'^',color='#ffa500',ms=10,label='Milky Way Satellite')\n",
    "\n",
    "#ax1.plot(MW_r,MW_gr,'v',color='#ba55d3',ms=10,label='M31 Satellite')\n",
    "\n",
    "\n",
    "ax1.set_ylabel('$(g-r)_o$')\n",
    "ax1.set_xlim(-20.5,-10.5)\n",
    "ax1.set_ylim(-0.1,1.2)\n",
    "ax1.legend(loc=1,fontsize=9,frameon=True,numpoints = 1)\n",
    "\n",
    "# MW LABELS\n",
    "ax1.text(MW_r[0]-0.2,MW_gr[0]+0.07,'Scl',fontsize=11)\n",
    "ax1.text(MW_r[1]-0.2,MW_gr[1]+0.07,'For',fontsize=11)\n",
    "ax1.text(MW_r[2]-0.2,MW_gr[2]+0.07,'LeoI',fontsize=11)\n",
    "ax1.text(MW_r[3]-0.7,MW_gr[3]-0.1,'LMC',fontsize=11)\n",
    "ax1.text(MW_r[4]-1.0,MW_gr[4]-0.03,'SMC',fontsize=11)\n",
    "ax1.get_xaxis().set_ticklabels([])\n",
    "\n",
    "\n",
    "# SB\n",
    "ax2.axvline(-12.3, c='w')\n",
    "ax2.axvline(-12.3, c='k', ls=':')\n",
    "ax2.plot(Mr[mlowz&msk&~msats],allspec['SB_EXP_R'][mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7)\n",
    "ax2.plot(Mr[msats&msk],allspec['SB_EXP_R'][msats&msk],'ro',label='SAGA Satellites',ms=8)\n",
    "ax2.set_ylabel('$\\mu_{r, \\mathrm{eff}}$ [mag arc$^{-2}]$')\n",
    "ax2.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax2.yaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax2.plot(MW_r,MW_sb,'^',color='#ffa500',ms=10,label='Milky Way')\n",
    "ax2.get_xaxis().set_ticklabels([])\n",
    "\n",
    "\n",
    "ax2.set_ylim(18.5,27)\n",
    "ax2.set_xlim(-20.5,-10.5)\n",
    "\n",
    "# SIZE AND MAGNITUDE\n",
    "ax3.axvline(-12.3, c='w')\n",
    "ax3.axvline(-12.3, c='k', ls=':')\n",
    "\n",
    "ax3.plot(Mr[mlowz&msk&~msats],reff[mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7)\n",
    "ax3.plot(Mr[msats&msk],reff[msats&msk],'ro',label='SAGA Satellite',ms=8)\n",
    "ax3.set_xlabel('$M_r$')\n",
    "ax3.set_ylabel('r$_{\\mathrm{eff}}$ (kpc)')\n",
    "ax3.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax3.set_yscale('log')\n",
    "ax3.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.0f'))\n",
    "\n",
    "ax3.set_xlim(-20.5,-10.5)\n",
    "ax3.set_ylim(0.05,15)\n",
    "\n",
    "ax3.plot(MW_r,MW_reff,'^',color='#ffa500',ms=10,label='Milky Way Satellite')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.tight_layout(w_pad=0,h_pad=-0.1)\n",
    "plt.savefig('fig_sb.pdf')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NV40al5PrKUTyUaHmgDK6Dshid/EY4HBgb2Bn4EtgObDI3SufpJ8nCj0AzX76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\nVAsTkCSpFiYgSVIt/g9YAPJjm81iiAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1286eb890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = 6, 10\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(3, 1)\n",
    "\n",
    "# g-r\n",
    "ax1.axhline(0.85, c='w')\n",
    "ax1.axhline(0.85, c='k', ls=':')\n",
    "ax1.axvline(-12.3, c='w')\n",
    "ax1.axvline(-12.3, c='k', ls=':')\n",
    "\n",
    "#ax1.plot(Mr[msats&msk],gr[msats&msk],'ro',label='SAGA Satellite',ms=8,zorder=4)\n",
    "#ax1.plot(Mr[mlowz&msk&~msats],gr[mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7,zorder=3)\n",
    "ax1.yaxis.set_major_locator(ticker.MultipleLocator(0.25))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax1.plot(MW_r,MW_gr,'^',color='#ffa500',ms=10,label='Milky Way Satellite')\n",
    "\n",
    "#ax1.plot(MW_r,MW_gr,'v',color='#ba55d3',ms=10,label='M31 Satellite')\n",
    "\n",
    "\n",
    "ax1.set_ylabel('$(g-r)_o$')\n",
    "ax1.set_xlim(-20.5,-10.5)\n",
    "ax1.set_ylim(-0.1,1.0)\n",
    "ax1.legend(loc=1,fontsize=9,frameon=True,numpoints = 1)\n",
    "\n",
    "# MW LABELS\n",
    "ax1.text(MW_r[0]-0.2,MW_gr[0]+0.07,'Scl',fontsize=11)\n",
    "ax1.text(MW_r[1]-0.2,MW_gr[1]+0.07,'For',fontsize=11)\n",
    "ax1.text(MW_r[2]-0.2,MW_gr[2]+0.07,'LeoI',fontsize=11)\n",
    "ax1.text(MW_r[3]-0.7,MW_gr[3]-0.1,'LMC',fontsize=11)\n",
    "ax1.text(MW_r[4]-1.0,MW_gr[4]-0.03,'SMC',fontsize=11)\n",
    "ax1.get_xaxis().set_ticklabels([])\n",
    "\n",
    "\n",
    "# SB\n",
    "ax2.axvline(-12.3, c='w')\n",
    "ax2.axvline(-12.3, c='k', ls=':')\n",
    "#ax2.plot(Mr[mlowz&msk&~msats],allspec['SB_EXP_R'][mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7)\n",
    "#ax2.plot(Mr[msats&msk],allspec['SB_EXP_R'][msats&msk],'ro',label='SAGA Satellites',ms=8)\n",
    "ax2.set_ylabel('$\\mu_{r, \\mathrm{eff}}$ [mag arc$^{-2}]$')\n",
    "ax2.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax2.yaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax2.plot(MW_r,MW_sb,'^',color='#ffa500',ms=10,label='Milky Way')\n",
    "ax2.get_xaxis().set_ticklabels([])\n",
    "\n",
    "\n",
    "ax2.set_ylim(18.5,27)\n",
    "ax2.set_xlim(-20.5,-10.5)\n",
    "\n",
    "# SIZE AND MAGNITUDE\n",
    "ax3.axvline(-12.3, c='w')\n",
    "ax3.axvline(-12.3, c='k', ls=':')\n",
    "\n",
    "#ax3.plot(Mr[mlowz&msk&~msats],reff[mlowz&msk&~msats],'bs',label='0.005$<$z$<$0.015',ms=7)\n",
    "#ax3.plot(Mr[msats&msk],reff[msats&msk],'ro',label='SAGA Satellite',ms=8)\n",
    "ax3.set_xlabel('$M_r$')\n",
    "ax3.set_ylabel('r$_{\\mathrm{eff}}$ (kpc)')\n",
    "ax3.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "ax3.set_yscale('log')\n",
    "ax3.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.0f'))\n",
    "\n",
    "ax3.set_xlim(-20.5,-10.5)\n",
    "ax3.set_ylim(0.05,15)\n",
    "\n",
    "ax3.plot(MW_r,MW_reff,'^',color='#ffa500',ms=10,label='Milky Way Satellite')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.tight_layout(w_pad=0,h_pad=-0.1)\n",
    "plt.savefig('fig_sb_talk.pdf')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
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