notebooks/220_chapter7_fig7.7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot fig. 7.7\n",
    "\n",
    "Temperature response to forcing 1750-2019\n",
    "\n",
    "Theme Song: Arguing With Thermometers<br>\n",
    "Artist: Enter Shikari<br>\n",
    "Album: A Flash flood of Colour<br>\n",
    "Released: 2012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.stats as st\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as pl\n",
    "import os\n",
    "from matplotlib import gridspec, rc\n",
    "from matplotlib.lines import Line2D\n",
    "import matplotlib.patches as mp\n",
    "from netCDF4 import Dataset\n",
    "import warnings\n",
    "\n",
    "from ar6.utils.h5 import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO - sort out figure sizing\n",
    "\n",
    "pl.rcParams['figure.figsize'] = (18/2.54, 11/2.54)\n",
    "pl.rcParams['font.size'] = 11\n",
    "pl.rcParams['font.family'] = 'Arial'\n",
    "pl.rcParams['xtick.direction'] = 'out'\n",
    "pl.rcParams['xtick.minor.visible'] = True\n",
    "pl.rcParams['ytick.major.left'] = True\n",
    "pl.rcParams['ytick.major.size'] = 0\n",
    "pl.rcParams['xtick.top'] = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = load_dict_from_hdf5('../data_output_large/twolayer_AR6-historical.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['AR6-historical', 'AR6-historical_climuncert', 'remove_aerosol', 'remove_aerosol-cloud_interactions', 'remove_aerosol-cloud_interactions_climuncert', 'remove_aerosol-radiation_interactions', 'remove_aerosol-radiation_interactions_climuncert', 'remove_aerosol_climuncert', 'remove_albedo', 'remove_albedo_climuncert', 'remove_anthro', 'remove_anthro_climuncert', 'remove_bc_on_snow', 'remove_bc_on_snow_climuncert', 'remove_ch4', 'remove_ch4_climuncert', 'remove_co2', 'remove_co2_climuncert', 'remove_contrails', 'remove_contrails_climuncert', 'remove_h2o_stratospheric', 'remove_h2o_stratospheric_climuncert', 'remove_land_use', 'remove_land_use_climuncert', 'remove_n2o', 'remove_n2o_climuncert', 'remove_natural', 'remove_natural_climuncert', 'remove_o3', 'remove_o3_climuncert', 'remove_other_wmghg', 'remove_other_wmghg_climuncert', 'remove_solar', 'remove_solar_climuncert', 'remove_volcanic', 'remove_volcanic_climuncert', 'remove_wmghgs', 'remove_wmghgs_climuncert'])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(270, 2237)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results['AR6-historical']['surface_temperature'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.08054363848259337"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results['AR6-historical']['surface_temperature'][0].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "co2 0.08054363848246111\n",
      "ch4 0.08054363848254584\n",
      "n2o 0.08054363848258647\n",
      "other_wmghg 0.08054363848259337\n",
      "o3 0.08054363848256528\n",
      "h2o_stratospheric 0.08054363848258903\n",
      "contrails 0.08054363848259337\n",
      "aerosol-radiation_interactions 0.08054363848255054\n",
      "aerosol-cloud_interactions 0.08054363848200013\n",
      "bc_on_snow 0.08054363848259163\n",
      "land_use 0.08054363848261459\n",
      "volcanic 0.011505463835003194\n",
      "solar 0.06903817464844718\n",
      "wmghgs 0.08054363848240666\n",
      "aerosol 0.08054363848195728\n",
      "albedo 0.08054363848261285\n",
      "anthro 0.08054363848175762\n",
      "natural 8.357452071934639e-13\n"
     ]
    }
   ],
   "source": [
    "# 1750 values\n",
    "\n",
    "forcings = ['co2', 'ch4', 'n2o', 'other_wmghg', 'o3', 'h2o_stratospheric',\n",
    "            'contrails', 'aerosol-radiation_interactions', 'aerosol-cloud_interactions', \n",
    "            'bc_on_snow', 'land_use', 'volcanic', 'solar', 'wmghgs', 'aerosol', 'albedo', 'anthro', 'natural']\n",
    "for forcing in forcings:\n",
    "    print(forcing, results['remove_%s' % forcing]['surface_temperature'][0,:].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4TGlaH+MN7ydbDfGbKhhzp3N38yCJnnaiLo19FV6u6nVyaEYNlza9D78tgGY9Ab7dHCjeNuHrkddmlCRJeg86tvl1dJKUOKtR1ThHzZnsLNlKphA81PtFrLqZpupfEXC3UeQaw7fmHlK6CX/4VTYt/TC3t4QY6X0FoabYMnOQiww6TckZLPGuJGALgeUkFXU7KRwZ5H1N5fDFiV2PDDNJkqT3GF3X6anbj9XgINtaTPfYIOvn/AaTIcZPu7+GLeWgedrPIO8kZr8F5fFbGDdX4Aq18b0br6YkkGRqx1rGx/w0locwpSfIbpuMI3AVIUuEsKuJ1Vu2kjCOUZ4TIVVUN+FrkmEmSZL0HtPXNEQi0sYU92yEgEOeEL1WH98dvZ7MaCHdM36KMJ0k9dgUpmir6NcdxK0mDtY4GXe5+fq+Qwx1thJ0qxyZPMrtwkDIfyOqotFR2M+HXtyEqo8x3R3G1+wkrNkomuA1yc/MJEmS3mNqN2wHVIod1fjHB1hT/WuuU0uZ7V3OaNGrGHY0UPLEB6iy3EKy9zDNlnwSwsdLS6dye9soQy2bUBWNTfMGuCwtSc+pW8mI5lE72ceS2gOkj41Q5Qnja7MzmJ/BpxZ+dcLXJMNMkiTpPaanbj8Oo4dMSwGH7SPYjXFuH7iJuHUI8dIWshOfRI+MEXn9ezR5qkma7Dx6SQlTx5MUHPs1xBJsmzNEsV2gdy+lwruAI6WDeCJelh2pJT0rRqDHTjjDxmfnfJGLW49O+JrkYUZJkqT3kP6WfuLhDso9i1FJ8FzNM9wTX4o1kk+w7Zc4M68hfvRRUnqc1xYtQbEto7bCQsSpcOeWh4iNRjhW6SeeJrjEaifacj39nhFC7ih3//4pTJ4EsTEzqk3hUwvuYbmxDXeOecLXJffMJEmS3kMOr98K6BQ7q2kON+GyhanqvYKY1ogpkUv86BMMuzTu+1AemuM2+tMN7K4284XNvyTWO0xrUZimkih35oYZOfBpNEWjoTTKlKYG8uJ+9KSCLuDLS+5mhjJIniVGlmnqhK9LhpkkSdJ7SPfJfbhNWaSZs1lf8Rofi83HmEhDb24k2bSJgTwn/33jdBYO/Ttxk8L+ijCffemHxPr6aSmJcLDaz20eaDlwJ+nhPF6rGSVstnLLtg0YzBpq3MAPltyCXdEpcgQ5OJrJ0cH2CV+XDDNJkqT3iJ7GTuLhHkqcNfjEGP2eTqb0Xk4i0UGqZTvRzBx+cN0iSsOfxBHqJ5R6gdVbHiIRjHCkJsz+6jGWG3Lxt6wmxzuT16u60C2CD7/0NM6MOImgkXWLltNqLWa6Z5RTXif17nLMDvuEr02GmSRJ0nvEgXUbAChxTuNEaiOrRAnmaA7qqb1gtPLg1VNJ2t7P5MbnSQWewj3WSTg7nW0XeDlZMkpNbBqZvjKyui/iSHE7wpTEGEzwvtAxIsMWOioLeDpjJUvcffR4DRzy1LA83MlXPa9P+NrkCSCSJEnvAZqm0d+wlxxrCXanh/WOVv7dezWq5ifVsZvai9/HaNoSLt3+CLoaxzjZSHNJkP2mTjTdwKTx5cxGw9F0Pc053fjS4FjZLF754ceJes0k04x8qfKzXG1qxB/Qec01h5pIH//pMLNPu4jSCV6fDDNJkqT3gPqdR0gmxyn1LKV1dCMFhSqe1pkkOl5lqKKGjVOmctHOdRg0M4mZOTw16RBxVFzBKRBYykWEcPQspzmnnfoyJz2ZWdzzyi+xJ2JEkha+fMFnWKZ3k9A1NptnUpD08b+2AgJFh/CEz+M/zilJkiSdOxo2bUPBwCR3JTu1o1yamINAIdq5h/WL51LWcAijbkTPuZSnCw7hjORibf80BUMf4JqxPJw9y6ktruNIpQc9GaUgOMYN/duIDFn5w4xVYLaRYQ+xVa3CoSX5uSmfYOkehqufwGh/csLXJ/fMJEmS/sVpmoa39zi5tlLaUg20F/i43buYpL+Zk1MriIR95AV9WBw3sLVkM3M7biTLN5uilBGDbiRgGeWFOfX400qZ3nCYXUsvZd8zN+M95aI3O5c1RRdzubWRndFSkoqVnypO4uWvEJ7yAkprAWObR+GzE7tGGWaSJEn/4ppeO0IsFaDQs4yTva9QXZOOpSmfYNd2Di0spezUITT7NAJOE4s7bsSdcuK3eKnPrac3K8bJ8gvIjJZwxabnef7aj7Nlw8cZO+IgYTLzlfl3sUxr5miyAK8hje8LO8bytYQnb8TYVcOmoQYyLjFN+BplmEmSJJ3nEtEI9a9vx9vdyfLbPobF7viz8cYN2xAoBIwJmrOi3Bpajq4nabH6MYwJVKMFp/FCiFsJmcd5tfIRunJdjORcjwE3rvFdXLFpMzsu+jhPHP466j6dVNLI55d/nsKkD68rnU49my9gIa/iSRIVO7D1LOTxgWM8KMYYSk78FUBkmEmSJJ3nNv/qZzTte+P090lTp1Fz4cV/Nj46dIos6yS6hncQvzhIbu9CkgMnOF5eRF5PA3H3YoRioyu9nm2Tn2O44DMIQyGOwAYsoc1ceMJNd9nFfGv49+RuHSISMPPg/NsJWF1MtveyPVXFZRiZX/44iYrdOHsv5KGBOr5vHMEc1zkkVlA2wT2QJ4BIkiSdx6LBAC0H9jDZNQeTYqHt9cN/Nj7U0EUgMYJBMTNmTnCRrRRj0s3YeD2ReIC4yYpLmUefu4XNVWsYKL4fY8qHw/tjKgOd3NbuYlI0l88pG6la00xk2MzG8hW8XjCdZZZWTqQqyBIK1xU+T2LKbtw9F/HLoW7udfSSG0myy3glW7rfP+F9kHtmkiRJ57GGrdvQNBWXfSaZKT/9rY1/Pr5uBwCj0W4GFgf44NhKtGSQ+jSVzOEBku6FqAbB9snPM1LwNcr9W4go1XzDFmX0dRtKyswVWQeJrVOIhUzU5s/jJzPfz2VqHSOUMSxM3OvZj3Hadux9i3l8NMRHs5qp7opy3LiY/9Y+TuTC+IT34Yz3zIQQbiFEnRCi9G3GZgshDgkhmoUQDwshZHhKkiS9g46/uol0cy4lGZPIthYSigwTDQb+ND7UUY9JmImJOPPLgziH5pDsOUynx4wmFFxiDoeKNjCQfxUXRbcwf2gqPzvZS/jpFNNjJ7nK10DoZRPJkIGmrOnct/BmFmntOE3Z7MfDFZZ+piz8A6ahKjZ4HSwvOMCF3UH6lDK+nfgqV/Tp3LkzNeF9OKMwE0IsAnYDlX9lkyeAz+m6XgkI4M4zqSdJkiT9n6HWFny+PpymLF5t+TmN4/sB6Dx4DICEL8pwuAMdCM8NMCMwG0U3MxjrwOIbJuGcQsysc7x4hCnCwMdOFHCz/zn0bc+zqLGLjP1xfPVOdB2OTlrIF5d+lClihCqjjZfUXKYqYa5e8iMM47nsH6ikrHQrV7X7CZPGt0PfZsUwmIgST2ye8F6c6Z7ZncDdQP9fDgghSgCbruv733zo98ANZ1hPkiRJetOxNS+jYKAn2kyf00JCTwCCltcOAlD35HaSWoyUniC/2ouzcylaeIQT+UZMyQRufSYn818jnPYBvtHXjSP6MK4nO8gYjmHPjmNJSxB2Wfn13I/yjfk3UaaMcoEieE7NJ0eJcdeS72JPWGhquwR98itc1+HHkFD4n8D9TA+4MBl9BGNPYxIdE96LMzrsp+v6HQBCiLcbLgAG3nJ/ACg8k3qSJEnSG5LxOM3H92IzumlOG2T3wjFSqQBX7s1nqKsBgJ6ThwGBmhOhUrHhDNYQHdzCqDuKYsnAYM7hSMk4H4gM4zi1FtdGAxZ3koyqEEe6JrO2/BJeKVqAUejMUPq5RHfwsObBrcT40tLvkoFOrPbjNM/8FXePhkgLpPhd6It4wqVYTV34xzfgtwRwma0T3o+J/Azr7RJOm8B6kiRJ7xmN67eQUGPEiXJ4phdHMoHfLOjNCuLpVPAeaac/2AToGJeNk9a8CCEUmjJUbOPjCPtyWrJrCaddynWH/wv3RgP23DgZVSEe617JzxfeSJoCC5VBpmFjtlbIt9AxiyhfXvI98jQDsb13sXX6E9xoClHaFeVI7EIGQxeQbjxOcHQnfkecVxd7yYhn85kJ7sdEhlkfkPeW+/m8zeFISZIk6Z+jaRq1G17CIEx0ZUW40B3h8oBKUtH5Q4EROj3seugRIqkAoFOc4cd1YAlqrIdGZRAUI3bTdI4XPseSsUlkr1Exp6XImhlhj//zlMxeyOOkMGLGo2XSJzQ+q4fRlAhfXfIDCpN2AntvoKP0CCtyu5laGyeielgf/BhZ7CQ0cpzxNHh14QhG3czqsWUT3pMJCzNd17uEEDEhxDJd1/cAHwY2TlQ9SZKk94rOrQcYC72xb9BbPc6/vQDO5lwM6aVMW12Lik578DggSJQnyRvLxmYppzN+BHxjCEsVA2k99ObN4j9f/DUiKcieGcdv/wU1jmzGidEKDBOmXoyxUbdhUmLcu+R/KYt6iBy4DD0rSW7VZio6NTzxKA+FP0NafCvRYA/jmVY2z+1C0U1cVTefzPzz8O+ZCSE2APfrun4YuA34jRDCBRwFfvJO15MkSXov0VWN/c8/DQj8aXamKy2khVZhvexGABb3/oT1Lj+ZQQugw7wg6QcXowuNWlMXBk3FbJzFkUkbKA7cRu7BcRx5MRJZX+SgnuLpVAOtugOvMR0wASaqXM3cMfcJykamMHZ0DqTbic7/IXlBqOjzsyd+IfHRJrSYn7H8dLZOb0FHYfXRWdi8nfjsb3texTvqHQkzXddL33J79VtuHwcWvhM1JEmSJGh+dgcD/jYATi6I8LXXjZirVjPIKLmqi+zgVLwlu8isN5NlT2BxjmCPzCNgGiE63otiymHMlaJ5Uh7f2bkOkQRbxWT+12dkrRPChkLSkj6uNG+mtLCf4kkdZIkEBc1X0tORhu5JI7rkBzhUA9XHdQJ4ODpgQY0H8BUX8FrlSVJC44ojC0jzt2Oc24fXaZ/wvsgvMUuSJJ0nkr4YOzc8BkCgYBqVqZfIGlqMUuBkh7GLa4I+zKYqXKUvow0X0Vhl4KrecUzOElq1OkyxCEb7UnaWbMRovIlFdfejWTV+Jt7H457JZMdHuNGzkQvmHgRrDHMoH0/3SrL7DRz052POSKIufRCjaqBsTzEZxv08P7CEWCxOsLSE3VNqiYoUVxx/H7nxk+Qt6+DCfhON4fP7bEZJkiTpNOi6jvd4G+17DzDn9uswu2wA1P7iWYKJUUwGB7uXJ7lvo4q5dAXjBAkbRug2uql0zmbesE5hehsHinTcO+eCBbqDLYCRgWxBa57GF443kRxMopXk8WjmbKZH67lr2VPYsgJYfZPJq5uBPqrTmzCzLz6dosrNGKa/RixuJ3v3EqosT7PXV03XuJHgpEL2VRwloCS5/OQVFLKXigs6UJrn8vT4HQw7O7n4by/5jMkwkyRJOsds+c6POdmwDYCeU3V88EcPEDo2yIET6wA4sexGpnnvI6+hHMMFpTQamzCi0+LRqUooTOur5L55JdxhW4cjPIeAOUjM34nRVM6u8hfQLB/k2qaHGdcFD+Rfhpsgd658AodFJafuZrraA+wIjpHuSOLKHaVs2osY3CG6R4pJO/B+lrj+H+2RXPYNZhLNKqBuSgfDpiiX1V9PmWUb5bP6aTr6CQgsZdjdgte1Dvj0hPZMhpkkSdI5pGnDTk42bEMXAk0Y6Bo6yfov/hcj/m5SehJTzmzaSg5w/4sq5uKLSeop2iONpA8PEtFiqEWzcPiquTX7KbIa3ZjSqmhS21DUBEO5dsYdSe5q10j0BEjZXezNncXtVU/jwUHO7g+xa2wDadP7WFQSQrHoAPgjLhqPX05x61IuybyXQNLCKz3lxHKKGStTabb3c3Hz9Uyx7yWjQuPY/m9jiWdxuHA91aHtXJXzpQnvmwwzSZKkc0Rk3M+Gx36EDjxxzSeJWux84rmf0jz8xuWprOYsfrr6Uq5tuYu8Qy6MqxbSrAxhHOgmjhldi+NNjZBln0aeX8N0fD4i10CPrxWEjV2Ve1DMi7lj4Dn6R8zsLarEosRZkFWP59ineGnmT5mXHiWpw7GAi9HhLIbGsynuuJrShInLMu7FpEd4rncOgYKpZKXn8XTmH6geXMJM0ULKPZm+/VeimgK8XP0TFnWneM38Sc8XduwAACAASURBVNr6Rlgywb2TYSZJknQO0HWdtfffh6anqK+cxz1Pr2W8oIj/+dDX+NiLj5AV0dl05Sep8T/AdZs1TJNXoChGmiJ1oEUZz52BZ6SF3mgvue4FBNbnUmpaQJAgwUADYU85AfspPtVSgNrfBnh4pvISFuQdIe/UbbTO+BUL3FH6O5cQOHoj9qQTO1AEaIYRVqd/jTRljGf75zFSMJO5lhruK/gl2aEilg9mEzCVY2ktoy2zln1Fa8hou5zHTQvI1P3kZZdPeP9kmEmSJJ0DTry8gaGhdmImK7dv30JdkY9e5QDXHVB58rq7menX6PQ0cs+GZpydDgyrL6WbMaLeNhRDFlurd3BleDZDwTpwL2Ba8EIMlVV0xlsBlfqSIIpSzIci+xltczDutNPuKuJSwyEixUdJdwbp23cHXX0LaDapBC1hJmm9LDXv5lr7qxiFyjNjy/Dnl7LAUM43in6NMWVjVfMKUqlK9IRgy5Tf0eboJdbxZUYNVm407CChpJPLCeDyCe2fDDNJkqR3mW+gn+1P/hqArLiJjmwflxwHRddZu3QdzvBl7M1w8KG932PhVoG26GJMipVjiX2IVJDhvHw0UxP9mQEsXcNEtTC2qitR9RSdvnp0g4fGgkMsH7oUo+9JEn4Pm5fMId08zhxhR80+RdfRm1gzOp2rLE9wvWEfxdZRHMYkAAMxNy+ol5CbGWOSIYd/K3wUU9LO+xtuwREvI2D1sWHqr/DGyoh33sM0pZMHjI+wVbkIW24zl16+csJ7KMNMkiTpXaSpKi9/77toukrK5KCo+xhlw9AxS8fjhdWHIOy6i1S6keu3q+iZGVhzrqRb+IiMtCEUF7urjtFT9O/YI/9LWZeF7mQfkw2l7LIfJBJtZiR3Krpyks/7Q4y3mlGNgmezLmOKpQNzxXaCQ1Pp7wzzO8dd5FpDRFQTXWQyrGbRkppMn7mIS8VegpZFfC3vJSwJF1c1fhRXvIgBVzubqn5DwLeM5OhyrlV280PTL3iGKzFnhbjh+k+Qk7N8wvsow0ySJOldtPfpPzAy2AG6zsy+AfLHoLsY/Ld7sMZGcT5g5AO7IOJO4hyB6DU3Y9cV9ieOIBKjjGVXMJzloNowQn+GQDNlc2xkD8PlUQYG/SjAock9ZCSKyB/bSk+Pjeb52YQNdha4B9BNMZRjJr6R8Sgh1cLBjBy85Wba65fhiKpMMni5wHqMBnEVD2RvxB5P46qGu7An0zmev4ODxesJD69CC87gEnGcH5l/wT7mMJTu5kO33kFm5ryz0scz/eOckiRJ0mlqPrCHAy89iy4M6CY39vAImgKWW/KZ2fARKo78itinp2Cz6OSO6YzdOpVcfQ71Si/6UCcIB7ur60jZVvHN7zyCPelmKMsIyWF69D6U0CBJSy4jngY+MJbOSC1oNsFvq67EpQRZNHkLhs5yLrfsZCiVw6HFHsYnG0nrNLOkZCMF1UfQ8zPYp97Mf+VswBnP5AMNn0MzRVk744fsK3mB8PBlqMEZlCf8/MT8M7rJ56B7GrffftdZCzKQe2aSJElnla7rjPX30rhrB4dfWovF4CKeCrC4o4GMAHReY2Vq5xdIxt2MIEjv/jQ9995HIhEh6/gdjBOnLlSPKellKL+YwUzBdx95gdzhUf7zMZ2HLhsif8CDsTOGrno5NWUGAKsaO4iPm2i+3kNduIalGScQ5gg17a2owkTLIhWT0GhpmUR7tJRkwoRQDHRa+mksfJKcYDGXn7qTU3m7OFywBaFDtPdWtFgJ9qTGby0PoguFjY4L+dBHPkNGxrSz2lcZZpIkSWdJeNzHmgfuZ6S7A4Egx1pMf7Ift2bBHknQWwQlubdhHEpjv7GJEAlWpGZiOfx1QmYf+SkPm8RRTCNt6IZ0tk0/iEP9GDOaHkLxFFM60E3xiELKVIwx0ULMms7hKf2kRV3Y64eJpRt5NmsVpoEEN9asIbMjnxxjHTtdc3kuOsAJvxtfmhfSvNhUC4pmwhHPYHHn1dSMzOOFmp8z5hjEEnEw2v8phG5GpAQ/039GoWGUZ62r+eDHvkRmZs1Z760MM0mSpL8hmYgz2NpMYGQYs81GxbxFKAbDP/068UiY57/9TXyD/czNXInHVsDmsU3oQmFuewNGFWzXVOHuWcRhQzsdyQ6Ih9jpMLIsWU1pMpeDohN/fzNoUQ7PUAk7ivn6+nqErtO3KJ/8HX1U9Wvsmp5DdaeVZ668GfP417ml3kMiaKR7tZv9gwuZa2vAZfdR0G2mWzi5L8dLKGphTqKCmuHp6N5KzDEPBoyoIklL7l5+O/9bIHSM3kq8Ix9CMY9B0shng2u5KLuR/YZZXHD7V8jKOvtBBjLMJEmS3lZobJR9a9dQ/9qrqMn4nx7PLCzh6q/+O+l5Bf/wayUTcdZ+51uMDvTgzJzNRq2VzP4dGDWNimAMVwQaLxHMGr0Nv4jQNrAbS3gAgOE0lccybUzSDAQDLRhjnXiz86kv2o8wfYEFJ36BpVBhRcY6ujMzqO6x87NrQ+xa8lks0XrMxFlc58Vg1/iq5UsUJAb56AVPkdlbQLZyghvzKwlrMR7s/CrRiIuDKR/ZsUwGnR2cKHiNzvSTaIpKQVSnb+Q6fOFFGOytWEIZ3DjyMp8oeR0vaWTf9A0mTTp7n5H9JRlmkiS9ZwRGozTuaSDsGwehYHM5sbmc2N0uzHYzairKcHsbbYd2MdRxBHSNPHsVUzKm4TJlMp4Y4kDfBnY+/CjXfPPr/1DN0NgoL//3/6O/swktZwbB4SOY3ZmcqFmAPSFYue4JBrOgdNbFWNrz2B15DcID6PY56HoE03gTDquLcbMby2gDKXMmm+YcJWGdwbdfPoVIRsifOsI3kx/j7sx1TKrXyPDVo7pjuMfWYYso2PvjjE11EMPKHcaXcNj95NS62WlxcMoa447wIsZUjVOJKJmxQppKXkbPf5VFsSSrRsz0DazkGdsyVM2BwXmSjNFMrh5+kY9OOY6NBIMr7qWycmK/FP33yDCTJOlfmq7rdJ4c4PU/rMHbvQ+0wN99jhBmJrlnMdu1AHt6Bj0ZR2hQ92Mmi7xwOT0NR9E0FUX524cbW/fsY9Mvf0wqmcBQsBR1cD8DeUV0Z5aweP8pVnUeICUgdKuD8s5r6dGHGBk6iGKewvp5R0kpIa7eU4ZlsAGEBR2d/TMCJI0qTnUVc04+gjET+jOy2KzP4fLMA2QyTvmAn5GSQYzJLq5tsIGW4MmcVcxLnKDq4jocoyVkq8f5N08paUqCZV3X8npYw6VohGauY//IAoZPveWLzhZQTAMYrXVM6U3j4tH1XDqlj0KGaZnxYSqXf+FM36YzJsNMkqR/WZ0n+9j68FP4h/aBHictv4opC68hLTsNNZ4kFoiQSqokYzFS0SSGhIE01UPmeDqa009H/rPE8mvRozqxdidBn5lEjpVEh43u2hOULpjzV2sfX7uerc/8Eo85m97yi1D6XsOpG/nYq6/96TtRqoCtt+lckbweNBO1w1sQwk5TuYHl3nnszd3Li8vaWHVkJpbYGCdrrLTmHiLmuppHnqxDj3jJmTPGt/UP88VFD7H79VlczetM7dURvu9wwpBi6ak4ikPjlbRFfM37e8z2MPnH5tJsPckxR4Ib9QIORHRMhhS7MgYZ6FmKMB3FkRkiKSwgVBTTGCl/DSu6BFW+7VSXxZhjaGGo4jKmfPCnZ+W9/HtkmEmS9C9noK2fLb95ipGOPUCC7JKZFBYU4+yxkd5gRLGOohli2A0JAIQu0IwxUnYfMethWsvrIKuP2JAZHkqjqDNAuRoCwGe3cKQ0j5MvbfurYdZz7ATbn/01mbZi1pTPYV7HdlyRCKvqWhHotE+FQ6UKJ2vgC+kleGqXcTxRRzzSRzBrPtkiBfZWELmM24+zf24QpzaDJtdGUsY8PrdNw9O6B0Ma9BVkkZoUIbDVwYm0Um7M2MbsdivPXaCSGTKQ0RujpyqbKaYOylY14RycS1p0Lw/nZmNGMKvlJnqSdl5PH+SYrQNr0TZQEhCugEgparQc5+gCbtVPIHxNZE0ys8q6h0j+HHJvffJsvaV/lwwzSZLOO96eAMe2Hqa/qYF42EciNo6WiqHrKTQ1jprwApBVPJvpyxYRO9iGw3EK/8X7CdpH/uZr67rA25NN5DclLGgMYCuYTXJxFXFPBpqWJOvEVmZ1N1JnP/q2z/cPDfHiDx7AanCzKyeLi+pfJOR0s7KhDUWHX69W2DrLQJE5k7tcAfKPfpgwMZoHtoG5jEBOhL6ccvZMvoaU0UhO73/Qaz+GVRtExUf56GpWt/tIxcaZtNTLV/U7mRfdRe7hJNH3gylfY3K9hisq+Pq+bND7ebRwNTW+NgyZKXJen4bJvIVXXaXMNkOft4igq5fWwmexOrsw+coZH7uGyVEL1VkWpudpaEMbCXmHMeZn80HPJoQrH/vta8Fw7kTIGc1ECHEr8E3ADPxI1/Wf/8X4/cAnAN+bD/3mL7eRJEn6R3n7gmz/3Sv01r+Crr3x34pisGC0eDCa7QhhQzG4yS5ZwqxLL6B/12ZS42uIrdhHVKQYGp3E0cHJDGsaEV0lhUBHIHQdkRTk9evMbIqx2JuOp2ApxlWLUAxmQkYfESWGQ83AsfAz5NY9RW28E3/3IJ7ivD/NLzzuY8237kNTU3RkF1PTdYSAO4cP7juAUdV57mJB3zwr9xszychqJ6f+E9jCRezwvYqmabSVGYh7CmnNKOHe558nKxTiG7fcjXX8P1HVASzicv5nS5RUx05spRptWQUkc6KkdpnJnjlEvjrEibxyyuv7uXPvZMqbWtBzVHY5Z/JdNuIcmY019hKvZKURVVQWDF2Cqhs4krcLrN2keq7FEJzFvXP7SOt8ncFGH4FoCsVuIF5cwW2eV3EA4rbnwJ7xLv0WvL3TDjMhxCTgAWAeEAf2CiF26Lre8JbNFgA367q+78ymKUnSe5lvMMxrf3iNjiMvoqf6sblzWXbDF5iyeCE2l5tkLEoyHkcoCqlkgo7ajXQf+zZqzXFi6NT1FzPUYOKDzeUssBZiNLtAGEBLgqai6ypCB8XkQCmchFKZQVJPsM9ZT6fqpCNWiI6VFRip1AfIKFxKblsdx59/leVf/ggA/pEhnv3GvYSDPtTMmRQMHSErrHPF8b0AbLhQcOoiwVeSNdgHZmCqq8aRTOdE4hTD48fwZ1VjtaSxu3QWP//vb5Lle2Pv8gnvKD+6ZDljrig/fqoFJTCE7rBTPK+Vz+ifY45/D+U9AbRVkynu6Ocl9wXcY3mKJSc6ScU1WmYWUWjoI2dpPznHl5Bt28Lv06ooMMRxda5kxOKjMfMAqd7ryPXnc63h1wTXGgkZBSLdSiy7CM3u5E7PDvICA3DDo5B7dq/u8Y84kz2zlcB2XdfHAIQQzwPXA995yzbzgX8TQpQDrwNf0XU9dgY1JUl6DxnpDrJ37WHaD7+ElmzBZHWz7NZPM33FxTQfeIVdz9yDmupHsSQxWJIolgTYImALohcaONRbiPGQg/ePzMCZtwilMgNVixNKedFQEcKAASOKMKKjExVRuqzttNj30hjLoMNv50JtCzXRMfQEDFl1MrIuJltcQFHCwKkTr7Ocj5CIRVn37W8RDfrJyl5G7+geKkcDVPeOoBrhNx8z0VKg8p3gCvJabyRIin4RY0Sro7t/M5jyGCmIc2TqQm5/ZQ2ZvlG+cdEdfLa9joLug3x9TT+2kB8yK9ASQXIvCXDEMIWsSZ0YXlVIq4igNX+acucPeDR8M/dPepRAh4KnOsr/5NzG9FADhlQuWZH1vODOotsc5SMim/GYnd7SHRT6Mngw/jxT7T0oAmJVJgZFDr22atw5ClNDWzGPNcOVP4Zp17zbvxZv60zCrAAYeMv9AWDhH+8IIZzAUeArQCfwe+A+4N/PoKYkSf/CVFXDPxzF2xvk6KZ99DftREu2oRhNLPjAzSy67jpajv2B3esvh8w+jBVgVE1oCSfJuIVIyoJvzEHrUB41dR6uU+diz52PKDfTm2rigNiPPzkJU8qKMRnGoI4TY4SE4kUzJEgZ7Yw7irFqKWaP72TaoIIwaMSzksRdGuYxM62tJ6kuuoBczywOh1vwdfSy9bcPMebtozhrCSeDR8mPxJnaO0zUAl/+vAMsMf4rvpC81hvp0HrZFd2NIaFjCAwjhIUTUzVGC5aQPjLMlbu2sKVmNuUzWllfVMQnn6nHGo+TzJ2Cqb8OpufhyejjEdvNzGo6xOS+IMar3sfj3XVcU1aBR/XTOTeXhdNaeCT7ffSM5XJnxu8pby0jaN3IzzMmUyRUpjZ8gk509qUf4PHhU5g1F4dC5YQdWRRn2ylRBikd3QrdQFoJ3PQHqL7y3f4V+avOJMzE2zym/fGGrushYPWfNhbiQeC3yDCTpPe0VDLJzifWcWrPNuJhL5nFsyisnkbXyRP4+upBVwEdSGG0OJi9+hoWfOBaxoN72L35MnD1ExdF9O+/jUn9LtJDcSwaGHQQmo5BGFjpmIQprxxNS1KvHaIp1YTTrmGP9qCPmtFSAoNZw+RM4nYkMTlTGMwqWlIhMtxPeMhO0qTTOdXP3kI/CZOOohtA07h6H/iSfbjz5pLZc5zf3nsXACXu2bSOHcIJXNjSSUoR3PNJA7PdCW6Iz6To1EcZSA5wuPdpLKiAgjBkc6Q6jtE1g/rcUp78j68y4Mpg7eSLWd7XSCVtPLf8Om7YtQ5Tfz3+ysUsqFnHo9oqZjpqMbUaSMuL0j/2PmyVL2D3L6OaZr6ifoaLbQfYm5pOoaGPvPlelENhPlqYT9SgcovdzuBYHpHMRhalBhlNlLGtvwL7zIVcdc21lJWVvfFmRcYgEQJXPhhM79JvzD/mTMKsD7jwLffzgf4/3hFCFAMrdV3/7R8fApJnUE+SpPOYrusc37qL15/4LcmYF4M5D0dGFd6uY3g7DwJGMovm4M72YHWYmVRVTvWFyxn3v86hA9ehmXuIJ0sRm75Mtc/GDHchwmkD55/X0bQU/kQPJ7WXCRhP4HDoGLo1xnssmOxGnMURDEYFPamRjCnE/RaCfQ60pAFh0NDTEnTVjLGnIExaooDVrbeQHSzHoJnRRIoe+zP0hTpJS19CdnOScLqLfE8Nzf6jxK02rj52HKHq/OQWI7fmOZnf8mGyx2cwmvKyr+9pNGsNDeVWvM5hRh2NzPIvYVPVUu559g+4/WP89qIP8oj1h1Qobxz42uMZ4ZnLbqZi1M5F+Q8xLNJpzXeQs9/P3O5BLJeuoM/WwjWhacQCRcxM28IO/UKGsxx09pdwZXIz+V3TeDjzMCNGF593WJl89HOc0AWtuXu4ezzEj8dvYtVFk7nhttsxGt8SC/aMc+5Ej7/mTMJsK/BtIUQ2EAY+CHzyLeNR4PtCiB28cZjxbmDdGdSTJOk8pOs6XScb2fzrhwmONKMY05lzxadZfttlKAaVZELQU9dBen4mnlwLyWSAVCqA17ud3bvvR1dGSYRKMRz+CtU+J8a0YvAk6Yoe4pjSjM8QIaSnUBJxrIkUTqNGrt2AbksQ7zARjpgwpccYqoE9eQEC1tCf5iZ0gVEzYtJN/H/23ju6jrvM/39Nu72pd8lWlyz3GtuJ4xTSewFCgNDLLrAsLLtLL0uAhIWFAAkkkBCSkGoTJ7EdO3bcu9xlW7ZVrS5d3V7mTvl8/3B+gSwsoeQAyc+vc3SOzp2ZZ57PzDPz/tRnbGyyShYk8GfzuLj7fVRHpiOwEPYkspECRabKvJqx3DrapCWUO6s4ZsY5HdmLJiSu2HsQxbRZM1/ikqkNLNj3z8hC4XBiH50TmzC8M9je2oFHmJQaIVrHlrJ+2lJau09z8Y71bG5q45+KX6BSHqe9LUhnVxu3sR1y5bgLslSpvXxZfRe1A0fIGxY4yyVi5kVsLf8aP3GZfGloFdOKi/H3xnlp6EJ8UoKldTsxIyFWVni5Mt1Mf/9VeGNF2FqCrHaAnZmL8Xm93PiO214rZG8y/mLPhRCDkiR9AXiZs1PzHxBC7JEkaTXwZSHEPkmSPgI898r2bcB/vxFOn+Mc5/jHxbYsDr64mqObthIbH8E2TcxcHCQn1TOu57KPXU84/gQ7dl6IYYwSDMwjr2A+XYO7SHS2v8ZWZnAO7hMfpCXqRwmUgz/Hqdg6dnn34Fcs7HEHPlPCa0kggayCpEiMjiiAG7U0S0ejYF/pGIXpKhb030RJYgoAOTVDVkmT1ZJktASWbOHTQxQna/Dl8pBeGUkRkg7KOLqWxnDmYxsZjLSBKQz8gUYKze30FUzhxp3bkRHsq5dwXF7BwqP/TMpIsX34aZJWCj04g33NR5kVn4ElKYwGfGyoaybs8XPfg19n3B8kryXLLLmL3XUlHD1ajrM+zFOd53OL92w74GfWlRSXd5Hb6KZxoB/32z7OutKnOeC2KDAF3yjP8KOJADPFMdrlmXzI8QjBUCGP2124bQcLLRVvvIqTpmC84UWuTyb5hnEVP337NJxO598yTN5w/ioZFkI8Bjz2v3678nf+fwZ45q85xznOcY43D9GRYVbedSeTgz1ISiGqoxTVJVHZ1sqSWy7Fcm7m4NGrMMwJzOFpOCcXEq7YSTS+FzueR+bodQjbD/ioGysmIHlRfCUIT4aeybW0B3cjZR04I07k/Cy+qiSKKmEqAtMGy5QxDZm0w2Z3Xpa+UJSqaAtvP3QHoWwJCBunHkG2LUw1gKmWIv5XfkXJNgnFOpH0kxyf6mBux1Hqz/QiC0HG4eSF5W/HpdYxkR0gr7SZmdueYN7JQSRbsKNJouumQj547DPkDJ0tQ78m5axid3MC07OPxvgFbGqZTXdBEYaioFmCn997P+7EJBuXLeJzrmfYV1BF++4S9KQLV0QmutjgP46+n2IRQzSP49xiM7dzFLu5jrCjitWFD9CWNZicuAWz8jd0EuGWGau4YvJFSpvCFO24mc0VfSyKFXF05GrqMxJCTbEvtJ2ZXc24hM28WdP/PgHzBvLmbVOe4xzn+Iei/+hhVt71X5g5G3/J9Vz6geuomV6IEFnGx9fT03sH6XQXxol5VHR8kIBShOwKYhxtI6fHcDrz0PJqf2vQD1ZqnK7wCo4V7CdnuLHPePCUZjgzDfaEDCbVFIZk/v50NAG14Zm8u/1f8RpBsA0kvZ2Ska0UxSaIef0MFxYwnp/PaEEZKU8+qi0jyDIaMChMWly5vZd3rulkpKCQjRdeju7No+7YPm5c9wjrl36a0UwfpfkXkpbyQIqweoGE98IWPnjqvWCobB75FWOhenbPPkBNLIiWvZRVsxeTcTi5qS/Lgqigfvda/B0vs7uxmQ+Vvki3VsT+3mKELdF8fTfZ4y4mD/qZs2gLScuLsU2hoieNywX5tZ/m55U/IqwKPjpUTqRwiCdMm2OuEa5LN+Gva8dzYCZnlFOkZJl5ZjWBTBlnLMFky0quTYR5yH4/i+oLkWWZNzvnxOwc5zjHX81g53Ge+dZXEbafqXPezeybBpiIfIzeLcew7RzCFqQONzP12CcI+RuQ/QGykU7GjCOUuFrwhmoxc3GOpleTk1IotkXKNUY8MEQq4cfs8eMqNjneYrOzeJyayAya+1spSlXhMbwIbGwph40JgD9XjIwDU7JJSkdYeuBx8hNRuiqr6KmqwZtO0XSmnyWHDyILAcBkIIiuOSiIRXCYJnGfj/GFt1Bfspx6WcEG5Lbz6Yp/FV9ykDPKGabnWXRccxUb9Me4teJ6Wk5cQdyKsWvkCSKuag617aBt9Dz6CuvYXTeDikiMz/7kW/hSUfxGGn82SVdtGZUzJvFIWTZIU0mPO2mpG6b0Kz4cepKOpU6Gni1EdVnkT2aZOhhHWfJZutVR1vi7uSiVZXj8wzgGi6mddoij7hQfOXEHNQPr2Db5TjbXfR2/KfBFFnNGF5hFR9gQ3MX/nHLzber492Uz/46R88ZxTszOcY5z/FVER4Z55s6vImwPjRdej1p8D9seHMc3WIo3uwhVdVMiKvDnNaMUFpGJd3HUeITedBQ7p6D5tqIqJnZKRY85XmNbkkOohQ4ON2U4UDpMfXgOtx66g1C2EBubnGpjySZCUgANTUjIQjDpE0RdQ1y46zEaB3roqqpmy/lLCAV8lGd9gMGQM023I4EjEsYzGsUZz6JZNhNlteQHllBeOJ8dmPy3rHMMC2EbLMbBB0pn0NK9mz2N0zidPMJieQlNgTKKBhs5nengwMgabFczW2YewKW+m6fnt5JxOFjaNcgn772TQDbBvraZOBUJT2iM9lAzd6oPsj1QR9/uILVzh6n8pYnqK4b8eqZtO0jg/CwZU6PhYJJE41IqChr5Xu2XyEk2V4w10pUrpsIhMZSYyt7ACSytm3h2JkE1xxavzfxIgFi0Hodssa7p59wQTrAmfglOr8XC+pK/S9y80ZwTs3Oc4/8HJCYznN53kkwixaxL5+IJvDGD/blshie/8VUM3SJ/RisDB39Ey0k3i0MXo5XNRC757Ysykx2hI/4oXeEBkARShYUZsvHHTLIRFc1tUzxdYBturKyTUUVjbfVxIk6dxol5vPPgBwjoBehKDiW5mfkdL+DPpF61b0sSY3kFDBcWUxoepyw8TtTvZ9vixahl07jabiGU8WDoEWTFhYr3bCI+Fah45e8VOowkawe24o8cpCFYhtNbRk52kLFMwvnNNB9dj9Au5NjkVmqDDQT1fA7Gt9AZ3g3exWycuYdI4e10l7YwdyzFzS++QGP7GpzCYNMlc0gWOHAqOttSl/Gwdhe9WiH7DhVR3DZJzQoZRfXSPWMZDaEFZA78gqqtBwGd0eI6pja/i9/kPc1OZ5h/mkzTPf5+ggpUui1OxRZAxQlOeto5OfZ5pKJHScky02NtJC3wTtlBTLe5btTm7coyZpW60ZQ3fxcjnBOzc5zjLUtsPMW2J1+iZ/929FQfiLMv/l3PFHDdZ79M3Zy617UxOTTASn1fpgAAIABJREFU3lUrmXvVtRRW1fze9hfvvY/ExCCO4lKk7Vu5MJmHa9a7Ud35DGZPEk10gmwwlhlgLDECLpP+OoOd1WEc5OPXCwiX9dOkV3LGMYaU0zDlKIaiE8qU0TJyObXhWXiNIEmniZrYwPL2laRdLjrr64kFgwhFQTMN3OkMgUSc0ugEutfN3tr5KFULWGTXsz2V5DNyhC7NwHYq+M0Iheluysw01aZBs2lRZeRQszFGMkN0uhwcKGzhWMW7yCouNNtAERZZxUUkO8ldLi9OM4Uu+VjZ9ws0WUXPJbCCy1k9ew3Z4PX0lrbwmdUbmLbpeaYmRkh4PPz0vGtZ756PlBbMlU7yfe0+ZMViW7gCR8CgvFPGHU0xPvta2ktyJPQhFs/7OO2hFcjZUSobP8SgNsojxZuYputMHb6U01YebT6F7f7DVI3NQBWCDs8JbnO6+XHgKH7LJi9yHQlZcLDuSb7YE+ZQfz1jlYV8ZO7rx8CbhXNido5zvMUwDYu1967i5K4VCCuConkprWulZsYMFFVhx5MPsOWxJ6mb859/1E77C6vZ/MjPELbJ8W1bufXL36C8senV7Z07d3Fy1wYkp4e8k93MURrwLHonKTPOvomHSBedxHBJiJRKtsDm6FSbw6Vxpk7O5uqTd1CQPtsUMiWDqHuM2Xo+Tsv9Gh8syWYsIHBMbOXKzU9gahr75szhzJQplCulVNtB3DiwsTGwMCSTCDZB4WGO7mFHZJAPuScYceXhtgQ+LY3wKpi6gwG9jG5bY7v0h5IZgSIs6jyDLA/t40JtJ05D53hvPd92foD+omZaT+/gYNt7sWJPYsseCFzBmtnPksm7mb6ShXxl5fOcv/4xUi4PRy9s5CHvJfRopTzgupul0lFcwiQny7yQbWNiwsuUlghl62NQcx77Fm9nMk8QkZxkD32euinXMWpAngO+MuWHSMLi6yMaaxM3UaZJnHTGuK/q53wx8h1akwob/DHePjrCVp/O3IjGWM5Dft4oXTGZYH8B+6JNUAnnNxb9ldH2j8M5MTvHOf4ByCYNHG4F+a/s8pkcivLE1+4mHT2Ey1fC/Os/jaQ4iHeNkT1qIwmLwoqZTAy0Ex1NECrx/54NIQTrfvoLjr68ElmroWrWeZw5uJoV3/4WH/vZAyiqSjoWZe1P/gcklcLxCWapTQSm38ZIppvdrvtZNVNFtkswZYOYaxy34ac+PId3HViE2/Sjywl06yC+9Cix/CZUy0PcGSerDKA7nJiqi0ByjJknNnFx9wlsWeZUUxMnm5opl0pxx012WiliUgZJkgnYBoWWTrmRoyJnsMshsz4whb5gNZrQaS4Z5P3FK2jjCJ6shSdjoZoC01bJGF4yppucpSILG1WyKJDi5NsJFCF++wErYE5wguvFAR4qvJqmMwMcKn+OOeIOkh54sek+hksvIx5cwCe3H+K8DU9i5qusXbyQJ5Tl6Gg84rmThfYJOuQauimlt8eBlRFUnj9G1S8kZE8Bz58X5Vf+OMKE9VKcTM2D3Nj/YUKqzP3FP6fHEee7o2FeCn8ZBZmZLoXPFa+gNNFEONBPw1grh+uO8u2qr5CUVRrGG8/e17q1XBfRye32sHvODEp8DhqKfb93/9+snBOzc5zjb4yZsxjojDDSHWPgxDAT/UPksmlKa8u55fOXIv0fLYXXIzwY4dEvfAkj00vdvBsIWVUom1SKVEGZVIwQAhDUa5eyyeNg6+NrueZTt7zGRjadYcW3vs/wyR24gg34ys5w5uCjeAqdpMbi7Hh6FUtuuY6nvvkdzFwSf0Zntl1NcMY7Gcmc5oHgy5QlP8y1HZW/55/AZsKbxBN7icv3/gZLUUi7vQSSq7Ak6axw/C+iefkca22lr7aeoFLKYDzDk658Jn2vpFgSAgmBkF5bCShhkvPlw3ze9xQXWgdwxiyInd1mS5BxKRiahMs2cMsRZDUCKtgyCEki65QZcLtIOVUmrXzCVgFp202Jc5jZfcPMKzsKB6AgOsxTc39K0jFByjcbRVvIfRt6KF59H7Js8y+zP0e3UoCMxf3+uzjPOMGGsVoOTpaDkFA9JtWXjuN9rhBPsp/9y5fwyJQ9tGWd/Gisi0+UlPKU+yQNZQ8SzQRYlb+fy5NpCiKLOK03Ue+WOKmlGfUd58LBtxHN30tpxy0Ephxmp1dlXtTCE74KrwOGi3ZTf7QCRybK0dBU3j2z4i+OtX9EzonZOc7xBtK5e4j21SfwFQRoXFBBdWsBmWSOdDzHaHecrv2DjPcPI4SCJPuQJAUoRNFgrC/BjpXHWHLjn/+tKNOweOJr38HI9NI0/Q6mjhURkCWyVgKhuEHSEMLEsnQ0zcecwGw27l+NZdyEoskIW7D5sXUcWP1LbCuOv7gGI3yalr15FGhTGe0aYWdgkr3PPkrnzi3ERk6jWhYLkgEC895LODfIC9Ik08fuYNI9zmDgNLKRwFIcJD0lWIrFnGMv8/ZNW8lpTo61zaCzsRZD0ygaH6dkdIycQ2OgshJJCBy5HFmnC5+zlFTOzb6szX5XBWZAZZrSyzvyttHgGqHUnMBrZ3CbWTTTxGkZeOwsQZEGQEcmXKgR9XiZsAsIG0WkcoXkJIGlWEiqQJZtZNlAVXLIkk0u6yGtB8jEAqSiQbzpHGWyG5DZaSsEpz7GQquTA54W5ncHeXH2AIaziaB8Mz/cOkHvnsfIy0S5Z/776fPl8faq1XxMXsmU0RQ741XEF1g0h0awLYmMESC5uZVpx/cx2TSLuxbuoTnr5mejnQzRwn9O9PGuCoWfensIBxMUm/DZiRzPRt+H5ovQqhTxHwVrWBwr5hp5G2u8Maqdt3PBuMTBfJO2zlZ0qZK8vBESERdVmyfYOGUBhqRwzcyyNzb4/86cE7NznOMNIB7OsuLul0lGFCRJJTIap78jBiILyCCd/R1AlgKElChObRynpuBRPFRJfob1APvXHGDxDa1/do35+XueIRM7SlPFO5keKySa7EIEatEcbvpSxzmT6mQ8248tTC6v+CAukcNtCw6/3EHbslYe+/K9TPSuRXMV4ivNJ3Amzsx0Na7Wa1FVD2V6lGWdz7A5GCE2chqEYHHExjvrDrJWio16jJBooz+/i6W7n6Z+sP/3fNSdbo60TaezoZ5hu4gzKQVLqFzkyidX34Rt2ZjJBMhOLNVDV87BTpGPUCUu9u3nh86VnCcfI89KQRL0nEzWKWMpEpYLbFnCliUSisSIx8uEy8upWD3jkQYCQxUsNNuoFYHX+JQVKYakfgbFOGEyZDCRhMAloF7xMZs6ZK3q1f0vUAx2iEPMZoRUscr0nkGmZj9Oy0CGD0cE3XsfYtZoJzumXsLqila+UfVDbo7sxW1atOfKCC9W6e1bTKy3GICi0XEu2LoVO1TOf1zVSWXOz/2jHZxKXc62+IeY6Xme72u/5hv5bhCC+0YHORD5OFm3zsVKEfvlFF2BXfxkqIugMNih1yG5MpQcvYwrRAcEbsKvSLibVhIYKMCdGWLvjIupDLqZVRX6M6P8H5tzYvY3xMjprL13Jem4ydu/dPvf1RchBJl4DKfXh/ImTi7690YIwb7VXex+9giqHKTOEaXI5SNt66RySRKGhYJAlSWcqkrA4aNM8aNJZ2vFthAIbBRJodYFcaucyGiS/NLfH8v6vzix8zRde56kuehWqnWbhDpGQbCBnsQhtjqe41DVBGcCNkkXeLMatYf2My/vUqYHzmfXiuc4uH43k/1rcYfyMBNxmvrLKVIK8U2/mInsIF3R55gRupJQ3dVUjT/IGQfMMyN46z+AQ/OxLnYISWkkJbZyx4pnmAyG2LlwISPlZci2TSgaJedwEPHlcyoX4rBRSoUWocF7Bgl4wJ6PT0+QVH2IoIyHLB505son+YHjMc7nCA4scqrEZEhjv6+AHrOScaMS03JgmRpCSEimhWTmkC2D5FghWauAoK2y1Gyj2pZxSCfp80QYVhNU5wTFhouQCOEXJdRyHvDKJ05erUdYaFIvEoexhQ9JMgAHvtFr6HQdo7RkHKNX5tMvJ6mrmkls5z1UhE/R3nATd7bO587Avdw2vouw7OJQU5BhahjcMZW5e47hzhwC28aTjSF5C/nOjQJdgx8M9pPNTeW55Hs5HExx2ljC56I7WJM5QVaS6E9dQIexhPqiSbxZmXvLHuWGhAeXZXMgUs5s3ygTRUfwRS8iLeag2KWUem1SRQcJHFpAe1mQ3XaQT8+tekt1McI5MfubMTk0xFN3Podv3MahT5KKJvCG/vQX1htFKhph/+pn6diykVRkkrbll3LZRz/1N/fjH5m+o2H2PN/NjOVVNC0s/T/3M3IWz3xnMxMDBiWahzaPjV8pQpcSBIWCU61A/p0XhiVsTEnnlVwSZ224xomLAcyEQplzJm1ulY6txzj/loV/kq+pmM66++6h3DeXImMA1TsNl+rjV9qj7Kp1UJhZTnHaRU1Uw2E50NUM272HmWUbhEQaI9pOOqKjOh00ZWuonBzFrpqOv6CVnkQ7j+fvAX8Ticl1XOK/iWkD9TSwBU1cQyCvkZ3xPSSlVqzsem7YvobjDY2sb5rLKbOQqB4CSabEFcZExbThJvc2vq9uooj4q2WISW5edsymRh5lNl2vKZ/ukBkqdHEoUMPpWDXmRCmZ8TzybTd1VgV+4UZGIiXpJKRJ4nKMOAbFQqPKrqXZCpFRBvl+2Xq2uPsoyFQiC4WcP0NaS5BxJEBkmaaHuDxWQ30uhMt2YaLS44Ad3gn6XKMMaeMopoP3j17DvFQ9PXkFXFFzhEPH2ijvfIb04Ba08AnWzrqUX9RP5+PKs9yW20pXKEi762KGOhopP7Gf5R1bMFWNTKAAkKB0Gr+8UGd/yUHuHg5QY2T5efxTnA4Y3I2fnqrt/OL0V7jS8zgeZYKX4x+jvH4fc8eX8bg2QMrTzScGj/FsbD4vps/jzvQ9bGt6idqBhXTknLQ6ZBKlhwmnNaoODPKNeR9jSoGHjyyr5a3GW07MUpEk255qZ+BEGtOQcfmgaWE5C69r+7vVRHoPHeGFH+2lYOQ4PdOqcSt+unYcZsaVS/5mPgghOLjuBbY8/iS6uw2v4yYcBS5OdI5y2d/Mi78PfUdHef7n27B1Jw6nxsKrW2lcUEwqqmObUFTjR5YlkpEsz/3wAJPDGRRg/UMHmDrrUhzO339MouNpnvzmRtA9zPUIqpxeDM6O00iWilNyvEbIABRJxsCgP32U0VgXQ5lBctLZ9EsSEstLQxS4KuhuP/gniZmwBSvvegTVjNFSmI9it+JUvTwruvGP38zbxuWz6Z1ECtlKIds5bLUawVT6tePUeJtoUpbSk93NBZnZYBu4Z96OwOZQYi0H5Dpaxz+IjU3UnmQs209+/TWokRa8hdM4lTzKqNVGXNvMrdvXsK+pjR/WX8O4WkCjNszt2lZC0iRpy8FC+Rhz5dPYwES+g5cKG9kfaKU6O8DykcNcGduJocp0FgVIKi4MSWFYCnFssg67qwDLdTaLfZWdT5tVQ7ltMeaIMamN4xSCKYaK1/IjW6UIEUQiSUQd41+rHyVuOPEYPrxqHsOBLhRbxa8XUJKcQn66jGCmCIfp5pBisN0ZIaMlyagJbMnEzknowo/PUFBtjY2OXs5LO4moNUjyEfpnu2jYMoRpRNkxdwYP1S7iRrbxGekZevwhDnQsItA/RMPIAVy6TqyoCnnxe8i4z8bG43kb2RA6yHvD9Vye3cjGxAdZ4Q7xU0KoSDSMLsOq384v+27Bl3HSMO/XzD31XjoweHjKD/jPsEku5+Ru5XbGiwoxzUfId50i5DG5weUkhclA05Nwxs8RtZZBxccj10/HpSl/PLjehLxlxEwIwbYn1nFyzTCFE6epSXVhaBrhYDPtkwrpeI6L3jP3NceYhsW6+7eR002u//TFb7xPts2eVS+w97kYmn6AbP0y8sIJZHWSdc+99DcTMzOXY+UPfkDPYCVu57vxWCZKrg+3nSRjef8mPvw9ELbgse/+hkiXlyLFh4sIWd3H9qdOsf2pU7+7Jy6fRjaZwy3BbGeMSlch3bqbNffu57p/WfAau6N9cZ7+1ibyFD9zfTYuyYlBDsnWOBR9mcO5wzh0gwpXLT4tD91Kk7XSJIwwKTOGqUiMF+STLJ2CkN0EMgZThgfpy5yiyF2DJ/36j6WZs3j5kb2Mdq1iSf1S0pNOqgOl7EjEEKIEb2Q907r240sOYssSSbeXrMtNIB7nyIxP0eWaoNY/g5qcRq2xBEJFuH0V9CbbOSz1YZtXobgibG7spGwiQn62ir2xEWZ5dMoLWulM7uN4rpaBQDvvfX4lR6oa+GrT7dRIY9yT/1UWpE/y6vxCFeI+haOhAn5RchOrvNdSMzpGW0cP6cxUOp3TUQsj2IaGfTp09gBJRmhnU1t5nSoNViXNZgmGkuDpgo2syt+MKVkEsoU4LDemnCOrJckqaSQh47Cd1ETayOpehvKPIQmZajNIs+pESBbj6iQjnjFOSft+NwzQbCea5cSWbLLa2e+eeSwXhcJNVjI4FOrkX/M6uHnkWk5J7VSXhXngPTcxM3mclY7z+Lr1S65TdnHGFWT02VKmjR1Gd2iMe10YdTM5sriMRwvvQki/nbl5W3gBn449S19uNl+TlvMD2QPAR0hxAxqXjp7Hted/nZiWoHL/v2Mjc3fxUzTpPt6R3sujkUWMBwp554wiDh+vRaR6oHwb8vACwrPvwvSO4hmbx6P1S5lWHmBJfcGf+yi9KXhLiFk6HuM333oYX/txaO0jvciFEkpjOSOEJvsIHtnFsW0fIVDYybwrzy76HO6e4Pkf7saKjaLaGQZOtFDZXP6G+XNsyxYObegkm5qKXX4ce3gBeWYnMwNzQBTzqLL5L7KdNUy6e2N4bYnK+hDK66xLMnI6d331fgLh6RRZQxRp7RQ6Sihy1eOUnZzSO/8iP/7RGeuf5NFvP0OhVMcFPot8zQ2cfUnEjBgTuQTaKw2nqCWIp5xM0QR17gIkOQ9b0ql1OtlyMkY6rr+a/mmsN87T397MVIefNrdMRiRR5BCR7ADbYhuo7u6nNVCHf3KIuOMgp8vyEJIEQsarmzSGU5RPxsm4UvSU5xguKiPhzSde3EwgfbaLrUj9v2vNlmVzcH0f7c9vIDGxhoaK2cSGTjKt+D2cSEUYNLq4eMejJJ0ymxtmky1qptgfpVBOUiDFieshSvet52TdtUzqw/i9U7GdWVRXPjujqxhkKRozOFG8g9Kxbr78wG4U2+Z0VR2n6z/GRtGPN74C2bqYwVAv121YyWggny/Mej//5F/BJ3gWJS04QRHPakvYWzwT1WVzpHAWEVchNZPDXNa5j9q4TpNVgUY5nXYfk8MhJCGoUD24hIoiFAJGPlV2EQ7JYLv/GB8pvJ8UFk7LjWxroFrE3RMotoY/m09JYgqBbCFuw0fEM8LpwnZkJJaLELfJPbRNDuBNm0iAJUnoTokxt8oJt5MOl5sRTUOX0+ikEJJGiW1xQTrB9LCObMgI20+7H74YjNMeOkpxsowrcwfw9w2wpqKNr5m/Zp7SSbcaJPl4EI+ZZm9LA3qoCGfpFNZVHeKQ9wUWm0WcZ9QhmU6mhttYYN2HgYvP5z7Cx/xJCrNBfkqWoJlhtSPJQruImoP/Sto9Rn62mLu0XuLBPfxicJDBdICVuUsIYvCFm+bw06/XMCPSg93yK9LVD2J7VWJZlfFRD72hEr69qOYtN1b2//GWELPdD68nrbfTtLyForFrmdgfYYIwsuREcxioZe04xHrWr9PIJg2ioxFOdGYpsbsZn2piyDrbHt7IO+786yZlDJ06wdbHNzLeZeOTNeyKIVwCtBGJxYEALscFZLITuF2FVMb0P8u2EIIf3LuPhjW/Ykp8F/Gk4DdTruXiez9DqNjzB485MjTO83e/RGmqgFLtCE2h2bikBnQ9SiR6nIC3mlI7H8syUZS/TShkciZ9sSzNRW/MYk1LCHoyOlUuB05ZxrYF6x/eSOf2YaZ5GqhzGIwYvXiUalyyh6xIY7pMarQibMkCJKrF2awTQthk5DQe4cOyJQyRZZbXyQv37+WWzyxluDvKM3dtp83lo86pkBTj+OViDsd2khjdgT//Ys603HbWsQqQ7QyB7BmQbAQShtdHf2GQfum3ZfcCvrSJU4+S0eoBcDGOrudwOh38b57//tMcObASt5mgqKwKl/4yU/P/naiR4kTqOG/b+TB7aprxzMrxEecqAtLZrs+s0BgnRMidZDi/m5H02zhs9zA90IKiqhyKvExEvozB/BP0+tbxsTUTlE1EODW1ls78Si47uJ3JwFOES29FEU2cLtzPnI51+DJpvrLsffwk+D0uNQ8xZJfxkHM5P5/3HlION+5cFo+hUxKJsHi8k+nhNLPMGiwtxyNl6/BaDj45ej2WcKAIiaSaIC3nsGVBv2OYe/IfJS5khJImqcVBAsmAKdEGqnMKTleUpCvNhGwy5j/DYOgEpmzhtjUWaCofzg0xp78XRdgYdjkJezG2CKBKwzisk9Rk+pgiJbicBELIWLYLEwVJ1nFKubPXzp6CKYqQ5WGujA7wvEPjiPc4rWYdmdwxbirdj2keZobcTe/hfHLHnKSCXrYvruVkU5b2wAFy8h40W+WjsQu4ZaQepDimrOCXfolD6uPu1L9RVBRmYXQGBzA5RZI5pXvo1Eb58vCNfMnwkW/U8T0pzoaa+/jsBJSbGR4eWMTByibePa0An1NlTFSyIDzJPvJI+1QkQB1zcixRja9Q4tpZb0yF/R+Rt4SYRSYPMGViLlbPYYodOcr85cjucoQkY1gZ+ntqSBROIIr3saJrKZqVwe8bZaDkIKHjDXgli7BjDD1t4PRof9a5LdNm1S+2sHZ7O2XFXmo1N3l5HuLxMJ6hADMDxRQWLCSbDbN5+ElSVowrKz/ElFQhlmGh/Il91/fc/Rz1yfs51tyKa5+LYjtMxfhG1rx7iFtX//g1LbSUZfFvT26mZdMkFXI/s/PayJMWMZI8TUd8FxP6IJIQzNeuotRVTWdHD60zGv6scv8lPPjEJuo2foOQHubYvz9Ha0vV6x/0RzgzEueZHz/MlNG9PKoVE/fJFEwqlCmLWRKsJKNvJ2JUUuNqJpLtYSR1DKe7mTLPK/nofmeNromJKqlIhmBXeAXkxllY+WGyYgKrx8WqB3ZyZm+MuR4vZZpF1k7ilvLYO/osSa2aePEn0XIJioeeo7vkOP50gML0LNKeCnilJuyOxXFne3Bmw9jKJChJNCmJU9Ox5SxnlFvJ5WUxbSedR04zY17ra8q78f7naT+9ksXLenAVCMyOXnzj/4JD8bIl0c3ynQ8z3FjAe2ZtwJYlhvK9nPRVkXCaCCxUIei0pnNV+hS121ZysO1drMnswEEATV7CvsqnmHm6g9vbY1iKwoPnXUFnaTXXKrvYbM3kkoO7+WZbBz3lXi485mde5xmenH4hPyq9h0ZziJ2ppXxm/kfpLqqiLBbhg4f7mBbNkZDTuISDUruUA4EO/rPoe2TkHJZsIAmJw1ofecJDTjJISQYCgS1ZZLQEhqqDkChOVtESnsIV9igLPScoMDpx52yEARlDJeOSSXoVoh6VCVWhNpqlqsfEYZlkrIUkzFvJiGpsZDScCCxkUoCMKo2jyV04pE5UaRiQMK0C0qKBrLUAi9+mfMrIL3Nl6j62ehUmstWsdczgZmMPSclJ3+58xsbzODm/lf5yH9vrDjOhZZmdaqZAGeOa6JXMSu3B53jkVXu2kPmf7Ed4MZTPj2INZBD8lCTG1B/zK+cYklAIOYb5Vt/HyQC9U7/HvIzG+zJHWRdp5ky6DktWuP2yGWcNFk0jGLMxDAnNAZGMg6K+Eg4WNLC0qQSP4y3xyv+DSOIPrLr/WzJv3jyxb9++19/xj7DzHf9KmbcZtagFIWwm9WFSuRhuwyKk5aEFKhlLDLPLtYWjjTohbZjKfdNptqZQH2hECIsV2ZeY07KUZf909Z983lRS53vv/xKLQwLHiV60ogKCnik4fRWovgpkRcM005yK7KEj1Y7QWlAcDVyVX8l4opuRFifXf+p9r3ueh360Cit7lNCBreR7u/l1aRvJVC1luQgXnBnjQN55fPXBs3n2tgyGWfXj56iNuKgsyDDbqCVjJtgbfpHxbBw8s1DVWpB8NCpdNPub+G5mHT/84Tf/4uv/egghePJrn+b87CrSDi9HrDZSkza33/vEX2Sr/aWXCO/8KbOMvZQoUQDiIkh74j2k1UsJsZH+6CDzAjfhkJ10TxzjhFKPkBU88eMUSFuQnQEsEcewJSStjpCjhFhuFGEcwuICxpzTmekYoMrbSMwW7EtJzPJIBGUdGwMZJ/uj2xiVl+HMxSkbWseOyl6eKrkN0w4hlAzTvSuoTfTiNGWclgSKn5hWTadzBiNWASnDjSnOVp5kbL7Z9QwtFZdjSRLHK8a4/bOfeLXcuXiET33lK3x8xgtI+2WOjFdTFLqC5tBCDmSjVG74GnJplhmLz3DaO5Vd4XeRS47g8htYihMJkCSBmcuhBXuo3Xacbv8/E82fgY2gK/g073hpK/60TVdFNfe3Xca7fS9zq3q2O3zS9HF6TQmSrNHXUEvLgUN0F5cxfVk/FfIkz8Ru4vOXvQ+LOAv6N2NbRzjjHEFgU5UrJy2nGdHCWLKFYqvURKZRmqwk7B7lZFH7q2NIDtOFJxfEYbnw5QI0ZhUuc52m1dlDXlzHrdvYkkTCWY5lNKPmXDgYQZX7UKWJ18SKYVcQNT+Mbs/FRjBOllEpxZCUxiFcVAgPNWi4+P0vCAgEkEbIp0HeSVg2mLDm0mAtxOv8EpdOjbAkspCiaAWL4ltQ+01GpKmcnlaLOzfB3pq9dDsNPjF2PYuMKYSSfvIc/41LPspLmet4UJyHJOt0imI8wRjftr1UJafyVZHCKn+c/cH9/NeESZ9dzc8KJ5AkEwEU5fw8Ndz2Oi4rAAAgAElEQVRJOBOgb3spX5n5AUpqyljxucsB+Mnao1yx40b21OXjLI6zfH+YZyPL+bL6bv7r+jZuX/T7yaLfTEiS1C6EmPeHtr0lZPpQQKIoUMXRyZfpSRxGFzZgI4mzM8XmZObTUHIRS/RrCe09RZ5yAQ3+clyqg3Csk4JgE0vSVTw1sJNl/Glils0aPPCxj3LRyCCuYSeeluvx55/NgZbUJxiMH2JY72M424cpeXB4byRS7iSZd5xwr0zQU8ZDw1u4/nXOc2BnP0aqm4HEDvoq3fQYX2Pe8WMo8ghCZAjbHpqSJ/nWR7/DpC9EWbaYKSW9XG7ORjPKOR3fT0fsGMJzIenifPpKJaTCME7nEDU7DGRJZopl/hVX//V59Asf4gbtOZ7l/ciTM4kap7G9J/5sO/1dER755Q9YGNzG26y9rOdKTo5OR00ewRRJUPeDvZd693KW5r2HlJlicwKSSj3jjsNEXAaNVisp9eOoZhrJtlDIUpQ5imm3Y4o2xjz/hpZL4MkMcQqY4tewrSO8LTidlBXGFiqy5GRHrIeEfD41ZzbQ593AF+feSlGghfflbaFejXJS1VjVdxlHRDEonP0DHOQoVUeZ5u2kSI7gRccndKJKgJGxFBVminJ3FbnRvteU/XNfe4DbZmxhbHMhOee1zK2cg0f10Z3LIR/6HrKWpmX+MC/l3seJiQs5WbaZZFEUWUhokkbCVUTEX0pKDTAz4mB57V68m3/FkxfNpb+gn8882UfK4+d/ll+JEVK53/E/FBNlf6qJ42Efl9R0UTIvRmSnl2n7DzJclEfT4iFK5SgPJe7gvy67Ak/056j6bk44QbE08jJVSAh63IOotkZ5rJH6idkszKZZVLwKV+E6TFVi/1gdm7NTCZLj8sJOXL7TSE6TUNKkJKfjjr8iYI4qYupScsmrkTOvXfxsYKEyiVvuRZHCGPYUcqKBIXT2KHsY1jcxWDDByYI0CaeNy5AI6Q68uotgLh+/XUaV4aE5l6NCHiQgdSEQTAo/kiSYLnUzW3uR41IjIXMxC7Iv0OU9TXG0hu2uG/BO9ZP19eNJDDNWs49Od45/G3oX1ySjuJXv4XL1YgoH301/gg3BcpoLO8kZbpa7O7jaCFDRex2ryOHL28OGUDufCWeYkdS4hp2UDC7kVyEXpmzyH2NxfMLk8fAiQq4cg/5iPn3RbzPGTKstYdW2Jfxz90o2d03HIY8z3OuDelhaX/hnP3NvJt4SYpYMGDw/+GtwteItWoTHLZG1/FhJPyI7QHt6K4nhBLNLruKCwrPN8Uysl03JHYzmznCech0VBU0Uxo4jhHjdAVIhBD//l4/SNN6LWbGMwqplmMLgcGQHfelBsrYA2YkkBZA9VxAP1dE3d4g5ziepSk8QPnkT5Z46psdzf/Q8pm6w59kVbJq6nfkTReyyb+SC8RPo8iG8jmIagxeByDKS7qMycpCqvHxmm80EUxcTN8NsC68kqjQRLrmaM9PTNGjrmZXqQc/lMNMaGftsBafUsN+YG/EH+P43/ov3OF9kXfJOUpaPZHgltp3Edrb8WXYmwmm+9vDz3Fa4idljFjuzjzI4sRE9swNDDlHhWUSe5qba24hXC9Kvm5yIJun1rGPNgm0oqhMJi008zdyTy2ker0OSbdy2kyHPQix1OQ49ihZfx9Pz1mMLmXce/ASjmX4CWg3dzg1UpBeCpLAtNoqd8dLQ+01+schFtOBm3iPH0HWLo6k0uxxZytJBbg9txVOaRTJlbFtGzjmxkvkkdT+ZnIJJHkKCHOCQDGL5JolkDpfiplT3k81mcblcbH5+Nd7QQRxHDUzP+5gemMOoYfMbxyTK0He5cniCygvDbNQ/xEFzHitm3XV2/dQfQFg+Xqy8msvGphEKDnL1tq2oFiQ8bl66cD6f8zxBgzREGD/P9LXRWJFkdPZCVvX5+VDZJvZd10ByQGJG2QhTHaM8En8v37xoGv6xL6LaWQqyxTQNX8ycsTb8yiiqlGbEqkGVY8z2rKW2+B4C2TSOtOCVjFOUq8eYW9aFL2WRP2bA2Cu+IpOWmggbl5C1lmBnvIRFikh2kNzkWibFIJbTjdNdTsDVjF8rJWjPREVmiAz7lZ10Wc+ye2qKnAahpGDhkJ8i20s8Ps64J8Nons7hkjim3AOAZkJx3IFqFpFV/eQwkUQaW24kpFrcrA9y8cQUlqcy3Fk4Sch0EHFGyDojkJjkeM129gUl3jl+OTend+DRNnPGrGO9/i5WizlMrz/IZ6qfxTk2C9lnQrwSf9+VDGBzxNHDjtKnuSThIBhrZOWgj6tDW7nae4A1I1+gkgEu0O7nV67Luej0EJ9suoVSj8LVM387DtZS6udL1vl8Sl3BRdJhTo9VcNDXSGWem5qCPzy2/lbhrxIzSZJuA74IOIDvCyF+/L+2zwLuB4LAFuCjQog3vBmQblDIliyjp94g6BiiNBcB4WZSKSEcaWTOjjxOxV9grO9n1Kc0xlyCM0oESSmBvOs5kThBta+ZBfFq1j73LFdc+8fbS/d+9p8pHB1GrbqBuoLZDGcHaFe34KxSGfZPY1yqQDU0UAROd5Ka3PNUxA4QN6aRSI2j2mfTcFfG/vgkiH+750X6Wvuo77KZlN7J0ske9NxWSgMNXFBwLZaUw7Jlav2v9JcLMBw6HdG9nMxKxIJLGGvIUipe4LroesrIQzNkXJaOB50N0llB8Uquv/4m/AHW7TjCMvVJdke+QI/Dg9yzFts++00tTzb1Okf/FiEEn/z+JlqrdlF7ppGxzC3sHn0a2xik1HMBi/Jm4XScncQRz+XoGDrJbm0rzy5ux6n4adYrySWclCfqiZV3sK9xE3ua179qXzEkpvWWMFg8yoTXQ2NqEZJkEpOepjNzFUtcFdTqF5Owo+xKxvCGx7FTv+Ir1zZyfuICinODrCjdQsx5NpOtYjvo8ffSqefRFG9EFjIWNpZkkgkNktB00kqGtJLGkA0sycKUEpw3Nh994pXrIyfo7e0F4P5163j/eUc489K1LCqaw041xrcbf0xbdz//sccm0JBiU/BmTibPZ33rj2m1F7CjaBYZtZhQMkvFWJjCaBxfNkV3/gGGxeO8HDqPT0/roO9EKRFHPkXTw3zV+wgj+HlppI4BuZg1y65iTz7IZh/UfYiGfZPcxE70ag0keDp2I99cVoU//H0q9DLqx5Zx2Vg+M7yrqSq+G1k6W0kyFQlbAocpsFMQ9ZaSTd+Anb4MVeolaD1C5eABbNzEjFsxRRWWyMMQ1aTRGDGHSYY3MpzZQ29ggo4aiVOzJMSrw8SHkew1lMQlyicVCuIKUa/FwakWliy4oMfDJQUXUpTXRMSaRE8l8ZblEZRV3APDyC/uYFAfoa9CY3BGKX1Bg3FXEiHFCFoKbsmBW3YxZsf4bmGQU/JuPhwPQSEkfMP8P/bOOzqO6uzDz8zszva+6r3LlmVZstwrGGy66cEQegkQEggJIR1IJSEJ6YFACC30mgAGbLDBBffeJVm9ayVtb1O+P2QgBBNCC1+In3P2HO2MZvfu7N753XvnfX+vHvRgHRlkZ/kadjgFruw7i/PDrVgNr/F0+jR61M9TIOpcNul3hFEJrroVi2omKShU6mYU4G5hkP1Ff6YwZWVioJQDXRIeo053rJ5S23JuUW/HJ8fYbS4lY0WQVcYsDngK+dkJNe/IGctwmIjK2eyP51Fp7ia9SWXH/EpOLvd/ZqMY3+RDi5kgCHnAj4DJjNVrXSsIwgpd1/f8w789CFym6/o6QRD+DFwO/PGjNPhwZA+1UeVYjdhk4WCqgKikk7SPUKO8SFnUw4rG80luXUxw9EU224ZBsCCZ57O7upLcktcJv6EQSY/idufw/Z33UzKjCr89A7/l3dPym358E0V9ATKzF1PhGk9T6gCJ/N+SZSrEpXZQqK9E1kHWzKTEFEOaAyHmYkV4Lu1CJuMTwwjmAACa1fuen6lly2bEbo2QYw1TE99m90iQdHwZXnMWc30nEBD6+UNlH5PiS2mL1zK7YzzJlEaflqLNbcNcaqcgtpVjoveTowj8JX0yf1TGEZadCOjIqSQnG3cDYDR8/GUghkMJNiz9I7OUYxl0WDAc3EVaHaQuWYi9oJHNofVomo4ovn8H++rPltFsSHHjQD/JxDU8P/gcpLupTBZTWzCRETnK3Zn30ZdoRdOgdUIIQZCxJH3EDKOE4naOaj4Poyaj985nsjFKIHszctJGwBRjj6uZ/QWjuFKTOKq3lGbXBkLWQf5WZ+bKtRGWKvuxySoRLZei9vX0ml/m7pNLOKpzFsvLHiRujOCPZlGtNFBviDAl3sE9vlJ2WJsJmNa/47PoSGiSE01yo4l56KIVUZcwp2O0uoZIRfoBUNUUyx+9i97BOBPL2wmtyKPWM5t+LcrDlm9z7dI0U3bqyK40a8fPpS94GruLnuUMpjIusZZfb34ClxpG00USmoeE5ieq++nsyeEbVg8rfQNcmJ1FTW4/MX0UjxDh6WAt+4az6G6YwLK8BIbYA9hH4mPtjm7livpvcMPa+ykzDrFjqJA7FtRhDt5FWbyMo1vncqr4DIXe7SRw0efLJ5A5gjGt4R1No+sySb0MbfhihMEigsEDSMPLMPvGobhuRkvHEDES1hWCygDBVB+dyfvp0fawP19lX7VIygiCLpKf8jBzxIMvKGORrYhuCyFthIF0Dz2uUbYVK3jDMLPFzFRhMsGuYTYc7GGTO4c2WwUikDk4RH64leJ4O/5MJ/7MKgrSGtWvt2LtDWBNpt/Kk9MZc7gy5OSwbW4lvyzczQ2BemoSG9nubmH2diP78ofYnqlywcDJnBMUccpPsZmpTBDOQK94mCFPM6HWE1g0OB0QaEHBrsvsQmUZ/YwWPYAipDhxsJhAi0JY9jKg5GCM9FLSlYO7MYSORM9aDzmCge/WnEyl38Lp9Xnv+H0JgsD08kx+uPXz3LrjTtZbaoiKRhZNeG8nm88KH2Vmdgzwqq7rwwCCIDwBnAl8/9DzIsCi6/q6Q/9/L3ALn4CYrZLncIdeTB79eNNBYjGZ5mAeFUIniy3Pc1z/X2gtuYIVI6djjYtEbAI5ecNcNHoLnfvt7Kv207OjjTL7BGbuzeSyRy8lbTRgNuVw2ZRTOb9mCQBX//R2KtrDVHgWUWIvZ5uylWT+39i/fxFDxiRN7gUIqkCuEKBU6CWNxF69iILSDK6/7HMUem3c8t1WosZB0EB+j3yiWErh208PEi95mQvaF7JWkShMbgNdYU7OIsJims/NqyArLiEqx3DywDp68kFO+ykbmoAnPcCExO24pH5+GzqddfaJ3HfVXG7OfjtiUddVbv76lai6ikU8/PJDIJLEIIm4LO8d4amoGsv29LO5Y4QzGvIZl+NE13XO+fHfuMeymlbT9XT1BTHHdpKZsJBXdRwO0cOB8F6effRBTlty/r/8blcfGCTan+bK8fdhabqGv49uheQ+ikYlKmvmEzGp/DDnHlpsnageFXSBMWPfNEk5wrTO85jYMxnZ3EeycBOPenswRkOIusSIpY+UlCAz4aM4kseItZuVBVsxaHY0yUGW1UdIeBL/6MmIZpHitgfZl7WPPy3yUzZcwNLKv1A3Ws1EzcMibT01sftQEBkQvDw8spEOKYe7Mo4nIVjQdImCRIzq2BAFSg8+rQ2TnkTUwUAasxjgtJyJpLVu4koEA/lM5CWas53Myewmtft0bAYnLybv4kcPpBBEnUSlzIrq6ejB82nJfoWvCtuoGdxJr5RNX3Q6AcGEX+rHJA7jkEI4xF4KWMP5o3n8JmOE+23zWBzZgllKcT9z+NukWfTbW5DjK5CjI9TEJ1E2XIiatPFS8eMo0Qf5Xf0FTNuyitULGpAiPycjlc0VzfOZa/kVFjFKh2cKzePaEXRwtZ2NubeOqOZCSjhJpkcJ7XyE/cZdLK830FIrkpKeY35bJnNH6xnR+lhn38aBXIFen452SE08YTNlXSZyA2ayhs24bV58+YVYXA4S0TADW9swhaNk4KJW8uJ2e0grCuHgKCPGQYZqT+CJUA6SJLJ4Yi6SKLKpzcOagRzWMJNx9hRTEgcYbF2H7jKBqxBBEJBlmaSi0S5nEzO58aeizHp1I+NPNbBb9nF0LMZvve2Mq65lXVGQhsg4Lhi245Z/Sa+UzfPKhTyrpTiq6RymIrEQI82kaBZexW/uIigG2B07Flv2NtZbOrl8II/Ibg1NsvC0az5Ro4Un/ZNQBuzMWfoyipakqq6cW4MZBMxO/nR2PYbD5JnOqMjgO7vr2DtQyMYzzsOZMjCr7LN9vww+mpjlAr3/8LwXmPo++99d5Ohj4O6vXseLg0FOyXS/NZUejiR56PVt/H5tFtM9j7Ek9ivOlS9AlQ0I0mYS4U08GlhA5sJ6KnfcR7vSR6U4iXHG8YysiyGhEZMkHuy6k2UHNqMPeZjU18o0eR6FtmI2KKsIeloJHCjmifPP59bqAm7zORGBtqEwm9s6yHSY+EpJMVbT22Jw2uKFPP/SPRABWTi8SNyzdCPOkEqwaAOZ6k3kBkdQk9up80/DTBbX1Zs4u/tZ/FsaMSj1tFEPgC6NknI9w3jTCh4PHctfDSdQVyWy8vxF7xJOQZBIOVQSwQhmwUYsFcMqvy1qiqpxxh/XMj7XyR/Oe6dzypvous4NT+xg5aYeFmhmvvtaFxMaMli9q5+rMn9Jx8C3eMraQ+FoG7oO5ZmTcIgeAJwGG4/vW8Fp/Gsxu+Mvm2lzRDitbwKb4nGIrMOWEinPn4FFzqDdeC83t7fSknKxIsdNwK4SsUuYEg2ctLuYUKqESvNKpnn+jDUU48oQ3FjyOf7uzCItWhC0KD3GrQxYdoDgxWE6huuGDlIV3sxFWX6emK5z3d8fIyei8twEmSfnWsiI+Im5O7hmcDqnpp/HpwTZZS7nR4YLGPQHKMveiy/gZF73CD/ou+cdnyeBgX7RQZ9sJSWaQBfQBQsOUeKcyEEiJhhJj+A1eHlCncN0bysdr+VytHsa3Wo/C17aSCRH5tH6fBTjBCqCi+jybOcb0mO4UqPc4bgWd88cJosirZ7d7Mh9FZM3gNGmIAgyvmEnZ+/p4Q6tkGfzU6wd+DL5qRE2VQ5hCd2JNaJTlCzj3L7PEekrIdOwF7+8D2vvQh7Pe4GQt4e/H7sYT9+PkFWN77YfxWzbj9GxsW18IaP+NmydszE92IvYvZRWz3KMKvR6RNZXi2w8QyVslTClBHKHTKiizvNV/TwnvgiAMS2QMWqitsVEvuJjnKuKwpxyfNWFePML8OUVYHE4GYok2dsbIpJQyLMYKbYqRLtb6Ws+wEDbQUxWG96yah4L5fLMjn5mlvn41TmTyHS8vaTePRrn79t7uH9tG/crE8gc30BjtolcKY4QHWV3WGdD2EZYfVswXvRMY1HvAyzPTXNVKMHzNjNPl+zEl3bxnd7xZJp+Rp/JzZWhmzDrXh7BhAUDQyRYK/STJ+5hgTaekdR4OuRRwjkbWenazGmjPhLbLNiUNEvds1BFiWVXTeHKP7/Bg+YKTr1iHAaHjWV3PMILjYu5dHYJ9YWew/aZmWVjDh9NV36T17slFo7PRjZ8tKKv/w18FDE73PqQ9gH2f2yYRJHFWe/8Yr12E9ecMI1LFkzmuFtSDPqeJ8/4J1yaRJO5AH3/55h+7cVcUZTLNRvvQsrcx6zELKq8lShRKxkGG0nSjG9p5bXONkpcQzSm5lPoKGZDYiUdLol0KMmj597A81MqyfmHBNeSDCclGRMO29aaSUex9JU7SapxTIIZRVMwiG9/DcF4mqXrQ4j2fhoGJ7KKBBnJXZhEB1X22fw9V2J8z2tk7Z2NXRQxu1T2KU30SgkkaRhSebyg/BKTXeMrx4/n2mnvbShqNaSIqzHMoo1nlz3EkhMve2vf37b3kOpP0BkKM7aS/G7uW9vG6k09fD5mYr+UIqbDK5t6sfm3Uhaspq1gB6Xbc0mlDzIuJJFfMotg5DWs1um4ZS8NxvbDvu6bbGobxp2Mc+y4ZRTtPI+9wTWgR5kUs+CvmoVufJxj9KdIWQ3U2jo5Ju5gX7IGZ0+cXeFsetMlZGasZPu4HkL+bNypADWtMX7R+jA/Fg2Iuk5clFnunM1LGedy9PBWzhz6C3HRSMpgYEE8xmpHGV+/aAAt5UcyDWBNeMgwwk9HmylIrWaNrZ475eMoyF3HrKwXMUka4gDoeTr7ikWa4l40VcAsqKiySMooHMo7Sx56jBFWdTI3m+lwK4STEbLNeUxKZZOMb6VcnIYsWkhs/QWiHR6dciY50UmYYzYGHS1cbHsQpxbkZs/PmNlRSE/uE2ysWkmWNYWsQVNSpDsk0ZsWUZH5tSPFqeEEj7nW01pzBl2pYZyBx6iN1PClns8xHLViE1ZS7/85LnEYgJx4CauTfoYH/4SIg4Q4xI3dZzBd/COaaGXTZBlF0nAtO5u+tS/yxCwDe86SiZvf7PIqgq5SFHZzujqV4yecTG5xBZqqsnP7alY0L8eoSxxVeDSFMyeQUVSC2fbu5e/u0Ti/enw7z27rIaW+fTmRRIEZpT7OajyGo07J4OBghG89vZOmgX6uXVDBlxdUIP3Tknae28KV88q4bHYJL+3u54Wdvaw7GCAQVQA7skHk2JosTq/PoybXxZaOEW54bCsrw2dQbX4cx8g4ftvXxV+tZzIlkkue4VZ2aCWcHfweEySNn+oyUSFIRHgVs5BiltLITrmUy3P/SL8cfKsdpwU92LZ4sCSSJHyT2eUs5PvTfVQUZfLlxfVc+/hOnn74IaYlevnVpIspdMp8bWHVe/abEr+NLKeJ33UqRFPKZ65u2XvxUcSsG5jzD89zgJ5/2p/9L/b/R7CaDDxx41ksuTVNk2kaatJFlRjhsm9eyPzMsWRIOeFHyImxcuMLLMg4hUZ3FWkthSQYKLbk4hTd+MIOypxl7Ilsoj0nhBRq4s5Z32H5PwnZ+2EwyqhpiZSWxCia2N7TxOT8tyP7HlzXTmEqTbT0byzsPJNVQRE1tYca7yw0QWS93MbU3VVYRIGebIGJc8pYJHezct0qtmg1BKx5LCwv5BdH1eB4nwRJezRGXI3jlr2seeOFt8RM03R+/8oBFidNDL1HcIiu6/xhZQtHKzJtYoKXrWBXNZxygl/ZHiatXseavjS50d0YVIHM4vnomsLroa1MM5bgkbMg8K+XPu5c3kyrrLFg0MwaNYyW3IY/nMY0cQkpYYiWgU284mqkJ/4lEq5WTpCfw5lOsyp0FXHVzZ7GTqTSjUzu0vDcGsOVkLCcrLAh34c3nURDwK6kWTyyjNNHlqGK0JNr5kC+HVNM4yv7hng5x46omRClGJoukG3wcGfPaqKSnS87r6GkYD0X+u5CUwUsm0XE9S4OLvwigZ1rOVF4iVQBpFMS2qiINiRhHRGRAgKGYQEhydiQTwPNrzO00ECv10O6fQjRPY642Er0QC0zffW0pjaS2dHJa1PnUhieQsLRSsAQYbH1OSqVZr6d8z0qO6xsa/gWs7OGCKUEmrfZKXAex9zqaRi9PjSLiZVrHmeN9SWuGujmGUcRRR0/ImYIURYv5pqWixhkDROdz1MsthATC9mXn4Vm7mT8gVZu7C3n7gw3nXIfV/Yt4Zj40xjlOJsmWxFSxTiXNvIn5ytsuEBBMaSpEyuoz5iEpmvk2HOYUTaP0rzqd33P8/PPZT7n/svfQstghAfeaOfhDWN10pZMLeCE2hwcZiOBaJI3WgI8u62Hax/Z9tYxPpvM/ZdMZU5Fxnu9LAAGSeTEiTmcOHHsoj8aSxFOKLitRhzmt1dPTqjNwWwUueRenRnJISJMo1DbTlfIzLH8FQSNp8QlnJS5lWtGpqHqCRyKBZGzUNF40P8Mf/W/AoIf0X4WBbEw5QNhbFv6sCSSTMkfz2XSRBpsCucvHjOaPqm+gDteO8jtk86iIDpIn83LXz/XgEV+b7MFQRCYU5HBk1u6uGFRFfMq//Xn/6zwUcRsOXCzIAgZQBQ4A7jizZ26rrcLgpAQBGGWrutrgAuApR+ptR+STJeTl39wKb+7+9fUVmdw9Pwr37H/+AwLTaMp/jj7daQ3ojh1P2u8u8kLZ3Cy/UxmSA3ghLbIHrblLScVUrmj/Js8PLuKYsu7Ey7fj3QiQkpLIosyP1u2jEcvflvMnt/cgVURMcoaLTI44vuQRDPFzik8l2NgamsMXfXTmW/k3EvrKc9yAKXMmHXRB25HKh0gocSwWArwhN5ehtjRHSQ2kGRYMyCnYsRT6rs6z+6eEMnRFDlxI3c5NXIEgXENBzhfeYjQvqvZVbmSwtULSSltVEdEsssbaY28xs7sIgq1TmrEqZiGk4RiSZzWd5/DlKIxvHcAQ1UP2c1H0T7SDnqCCnMRGVIhu4Iv0ypb2Oq5jDcWmEko82jdP5WpTUkSZhVp7lMsSYZwPjcT+YWHGfbl8ucFc7lu/71MiQcQREiqBhKSgSGXTIvDgySqBBU/2d8KosyXEfNinB6P8KQjDYBXrOYvXWsIGPwsL81iceYjpBNGkq/7KHwuRGDSPBy3f4emtIgkHMeP2k7Dt28VqaQZRTeR8JtRCyxYs7NwZGRgsVoxSiKibKRrcIBF+2+gLcOJvOEA5M/BHSyhwVVCnCSmtQ/RlS0Rt56C2/MKpcYuJgnt5Cu7+WXu5bj6PQxMuYXZziShJpEpwQvIu+5GwqLEsqEg64NR1g9GCZZcwknrXuNEdM4cNfOYJ8SsUB0X99ZQ5LyamQRQsNOcV0p7aRBDwoI1cAw9mS8yf+AVLM13kGfMIcwj+C372V3pQIhORnu5ihsmPM+AV6XWPJ5bFv6QCs97u8oMhpO8uq+fQDTFedOKDntftj0Q5bkdvTy/o5c9vSEM4pgd0/XHVpLveed93jkVGXxtYRVbOkbY0DZMvsfK3Ao/buu/P9B8E7dVfs/jjq7OosIGQriEzeYCFqQ9/E78NdHHyEgAACAASURBVAKwLrecWmkLkzs/h6gZkFQzT1r38nfXBoZtB1CNQXJHKzit1UusfxO6Njaz9EYSzMwv46cBF4k8Mz+9Yv5bt0skUeDey6Zz1h1raTXI/G5JPTPK3t8o+LsnjucLc0upyPrPl5n6tPjQYqbrercgCN8GVjAWmn+3rusbBEF4AfieruubgPOAuwRBcABbgd98HI3+MEgGI9de+bXD7ht/7Jd44skvMUFw8au5Y24khSkDJFq5vaebeUN1pKU0m0s34IqV86L5BL67cBxzvB/uhxJXY6TUBGbJht554K3tncMxkr1JMIWZM1jI/piNrNQexlvHIwpGBmPN+IOlmH0SM48vOyRkH56o2UwimMAgGnGk3k5CXXcwwATgCXsKs27gopHYuzrFin0DTEpJLDcrJEyjmCp+Qyookx44A7m4ib17jiMvsRNR08nIm4auplmpdPH8wgupXf0IdQkjDtXK9558hNs/fwF3rTrICbU5b12k3mgLUKkEcbia6RTL0JLbsaQ0rGXzCBFkb2gTXbMXsLSylMkdIRZsDCBoAunMJlz+dhbuPAml/SDJjXcyVHcC+354PZFEgtMG5/KVLb9h6qY9JMI2TH0JPP4oBeUpYm0yzpYQKxum49UCKLY41w8NsM+xkCbXfB7bfRvoEs21aXJN/fSvrWDcU93ogo7hmz/h5dpG7m0LICGQ1nV0KZ+KxoswigIaOmFFYyCZJv3mSVQOPZIKmL0ckzZiMo0SUnqJqzEmOurRdI29Q7dRGIyxrO406jxPcYr8BAABg5tbcy/H1NeIvf5mqqxphBUik+1XYf7Kl/lWWx8P9wZIaDpOg8hkp41Kq5mCWAn77DFuCO5j5tCP0DSNSaabUY1GtlW4CfgkDEkR447j2b73AAG5ibPLziNb+DM5RV/jxUQjl8dfZcAnE5Tq6NlSw8+mPYMmiNwy/WecXnX8e/7mIkmFP71+kD+93kLiUH7jvWva+PKCCqJJhed39tIXTJBWNUZiY2eqvtDNd04cx8l1uWQ53zuNRBQFGou9NBa/d5Twx8GUiiy2bJmLK7uZusiPcTu+TGeGCYHpTGs6G80QJ6GnuTbnIbrdWzAoMoUBH0U9dop6k0iJDkqDUWzJNPZEioJjjmXNvn5erWngmtmF7+prWU4zz3xxNsPRJOWZ/16fd1mNuD6gNd9/Ox8pz0zX9YeAh/5p2wn/8Pd23hkU8v+SvOoZxK1OTt0Wo6FEo8coIfWYGLJXMMHZy+v5L5ObdJIVHkc6oFC2pIErCj/81N1odJDSkjhlL6X9g29tX7ann0pdYyR3HQ3BMnaPJtG1EQrdE9nmBH+3B8ESoik3k0v/KST3wxAVnSQPZa5K5rdLqL/RPER2UiOdYQBVZ1Pz0Ls62Kv7B5imwv1WhfKSZ3FHcrip62pURzfLTNspHJlHKrWHkmCKzOJpdMZ38djCxchimk5PEHrBITnpbd7Jxu5RfvzCPp5pGuC5S6YjCgJ/3tJJr1vkK50SOyMRDGof49Me/IZCtg+/hjbTzuMVRzO7dYjZGy1EDBotOQkWDUpMS55Iumcr4R2Pox3/Tf6yuIFlS/cj6Tppr4lvNXwPffLYyNecTHDJxhUseP0lOr05PPzFhWyf2IA1OMCabeczIsrcffAVVF7DJChsm2ynW8jHe6dE/e52AtNm0H3917klnGa0a4jpIdD7Ykwt8SIU2tirplH1MUPkGruBHJORbJORLNmITRIxCgIWScQkCrS8ZqbW0ElnloB7x+MMjp+Ky7eSrBda2FZuxOhxcYrp9/yy8EKezDoGMezn4oO9KLXfp8yaxvikAXdgPh1/uIwrNuwlqKgsyfZxbo6XSU7rW/XVLhq8lsj2y6lBpzrjVuyxNJqusaXWhyEwi1ifjRdHt7E+5zWSs8aOORA6wC/chZSMdPAFXiVskziYVUfrgZncOu4RskYt/PDsB5meM+aCE4yl2dY1SjSpMKvcj9ko8siGTn7zShOBaIqTJubwxaPKSasaN/1tN995ZhcAk4s8HFWVidEgUOS1cXxt9rtmYZ82U6qyeWhbGTWGB4mIJxGUfkiM/eS2nEpSHmUL7dyW9xIJawfjmn1MbrZike1kymbyWnaRX1GN76qvIhgkBIuF7nsf4FfFx1DoMHDNovGHfU+vTcZr++CzzP8lPhMOIB8VQRSZFRzg1loj525yEXVKeM0KdTti7J9YwkgqhS9UgiW+m/um3siGxrKPlIBoTENKSyCLJiy6663ty/b0k62pKN4hWiPjEFNNeE0F2IwZ9CpDoLiI5hr55kWHD8j4oMhJhYQwlkdkk8ZGvIqqcaB5hGFJIq9uK+aUwobNKktmlbx13Ggsxd62UWp0E5IhAdogP+n8Lv0ZmxipvZuupT8jN7kVdI08z3hEycTDuQYGPTmc33c36fSYP5zVYMFnSnLLyp0A7GkKcNGmZv7SWE7TrgG0YgHT3imYI50ogKNwOgkSNNs38qfyr5AXiTJri4SqRDh5/c+w1J6FMbeBdNdGDvYeQD75Jr6UJzPy4kHMBpFMm4nu3aOUqRK9JVZkg8SIKPCH2cfzh9lvzybm2K0oqWz60l6CmToZ4T7ido19hXZeFI6h4Tc9FHd10nr91/l1/Qy2B+JURXRce0fZMhKnxG/jrtdacFqMfG1hFeNynFiMErJBQNF0hqMpRobjxAHNIBLVdHb3BMm0FlKe7mV7hptjtq2hvyaMa+0WBM3Ay+Pn8AvLL3k8ayHPWj7P1ft3EzJswFC7lCJbBHW1G98aEx2PfIsvbGkmoz/FvJTI/p3t/EDqINtpJt9jYWK+m8/X1uJYqdBhzadotIu0QWB3Th0/7DfSKb8BLpCtOlNaLewsP5eE7KSHX/FG5ALqPWsxyNsJCccyvK+eW4t+z4Q2E1df+XemZ2URSSr8fkUz961tI5ZSgbF4lzctYGeU+rjx+GomFbw9eHrqqplsbh9BNohMzH97+/9XGou8gIAnJnNfxrN8oW8JtpEaBk3d3OV8lNWufjQpztSd4ziPSrKjOxB27EFQVZynnAyCQGTFCoyFBcTWref3iVx6y3w8uqTxM1k08z/FETE7RK5cTsLUyj2zwrgVmL9hFr8//lyuePHnFJosyPo+ni06k1sXVJMhf7Tpu0NRSehxjKJM2lpAVFWREdjVOkJQNDAuZKA57iM3tYpyVyNxQUMZMCI5O4j6x+OyffD7dIej1GIgJow5TthUgWhwlJYweJMqXb409vBDmCQzycF3Bmoc6I+QqYpskdPkFK1ieqgeLCOMTryb1bsWUxC1kUpuJSsYxVcxjeFUL09Oncrk8DqsWybjimWQsESxSiZynAIvtQ+iGy2Y1Thbl29lUSJNXaSTdFY/bS21qOmDuNIG/I4JdMVaeOWYRYQlO1/esBdNzaK2ZynmY7+PQZToGW5ls6GArul1PKQn0duSHDMph5+eVIPXKvOjF/by59Wt5PRGKc+0k+k0U1WTwcp0ggKzEW9/iidebGMwnOTP5pO5LXAHq8gj2xKkf7Ca3OUpSro6eeIrN3JneS3+oRgTWqI0d4WozLLz44umML8qg5bBKF95dNtbM45/h2PFKi40beOZTC8QYur2TSS6ZZ6YaaIsYye2mMqz9gu5OvlHBgp6cNpbyZVVYh3FlD3cTe8VN3D1jl5MO0cYTWv0+m0Ueq2oms6B/jCv7hsgqbRyVFUGM0xzeMb6BlmGRgbMdl6QWinrg3OaVTLiJg5Un8pDxyzm4jw/C/0uln9/GT+vfZLvd15NVeIrdFiaubH4dmbugQnnPcicrCw2t4/w5Ye30j0a55S6XM6ZUoBsEFnVNGYA3FjsYfZhnCgEQfjElwY/TvI9FjJliA40sKf6VZ73ZKMqaR7KfI6grCBESpnb0shVvZ0Ytj6JeeJErJdeCqpK4PHHeSF7EprZQt7al9iZVcXfyudw0cxippV+Notm/qc4ImaHKJ56MZfuuY40EoY9+RhPPYMllWXcrV9L3sFB9vkzKWvI4uycj97pyrx+ktExETELNlZ19lIoO/GndCK+EBPDXroCgDZKtqOSvXIKTbES9fi47ozDh/x/GMYVl7NtYMyNxKpJ7GhtZXfYRbUQRSxq5dSOc0kaRtkopUlrOsZDoc2tQxFyVJ2dsk6Go4tju0+ndfKv2dMxHff+45DS69B1jSLFhtlewKO+ISQ05nZuwR4+Bx2dmDqE1eBAj9lJqzbS8zJRB+MI+7s4uKMDq0/isoEO9kTqMSqdVBhLkQQDazLb2eA4g0taVkNgPLnD2ymqXUK3oHEjUUJuHwkRFDWBM8vKnWfWMaPg7e/suyeN5+jqTO54rYVwQmFTWy9Pbu7i6OpMdoUS7O4JMbnIQ12+myf3zeGbxr8yV+wm0WPk2Ugxi3at4farv8rSohrqO5Mc2BdgyGzgB6dOYMmUgreSWMsz7TzzxVkcHIzQNRInqaikVR1JFPBYZTw2I6IgkExraLpOMJ7mxnuGEFNG2rMNRMxAt8y+PHhyUj5vDK/hsexTOX54F5Zxb1Co69iNKvGBcgp+PUQ4awJXZRQgbglQlevkp6fXvmuWo2k6965t4/vP7SHZ+AV+unUpj2bF2C9kc/0TChXRXG665Bp25BczwW7hhaoCJjnHlvgiX72d4V8t5CsTb8Of9jFkDDB1n4a3/Eaurh0LvLjwng347DJPXjWDyUVvn/P/JqH6dxAEgYYiDy/umM4J/X38vuAxdEFAT2SS03wmJw5UcFT8OQxbV2E/aj56WiH8/PP0BsL8fP4X2G7OGnuhQ1kzZzfm850TP5hX6RHezRExO0TRpJnkPZxPMG1G8JRwyXELEEQRWRR5vGqYOpORO2uKPxZ/s9yKWpq6xkarrrTAU3sOcLS/nEoxTWtuCD3owZ7oxmPOR5bsxCIhTI4BmqwVuD9Gs9DcqkZWb30aAJNmZNmWtQSsM9AEAzZXN8XyIEpKZnk4m654ghLbmP/hwaEoxXqK7UaR3JhKhj3KXmOEyOYL8elJ0sk1uKIKzuwZaLrK/ROLmNP7EjQfTURUMRmiRNQR3IZshKCFzHFJpgpPsDFrGj1KPsaDQ+wuKcTR2o010ksaDZ+/lhARHpwyk8JkNwU7CkELUVxSR0oU2BBSmG420OwQ2J9t4rJphdxQV4gkvjtZdFa5n1mHHMSHoynuXdvGQ+vbyXaZufX0Ws5uLKB7NM6K/QO8kazmJMtGhvY4OWr/Bm66+ga2ltSQuSHA/miKc6cV8tVjq/Ac5n6GJApUZDn+7Yiy+ppqDrbqVGpD3PR5CVQjHRkwP5FAEkTSwyeSO+XbSKJKrK+GdOds/CvakOOd/O7cc0jtHqWx1Mv9F005bN0qURS4ZHYJj23qJDqgsCU0mSv6NnLi2iAt+cWc9/WbObE4h+v8Lo71ud4avACckJ9NX2Q2xctfY834IU7arWEVZ3DqzefQNRzjkns34rPLPHrFDLJdn4zX5/8n6sqyeLFphKaDM8hVq2nXcsmMF/HFXB+T1BeJP/UShuxs9m3czbK6RYQmT2O1IRtVMvDL0yYwq9xP61AUXYfppd7PvG/if4IjYnYIZ0Ym6bzpZHn9LLjsaoRDF8FvlubwzdKPN+kwq3QyO1Y9Ofa+GmxNRoi1DpFpsJL2DrC7r5xcZROFtkrSaASiFixlBzi1Yt7H2g5Xbg1B86Ogg4yBA8Q5sLOZTJfI9P5+HlQuwGSM4vQ3sa+7h5LKsaKWBwej+HUD+Zn9TBytIpy1kdVrr6NElag1/IaNikzJ0DCe8mlsscVJCCbmjOxFi09jaYWRowI7GY3GyTVUYg0p1Lt3c8LBjZxjf57L824n3m2lKruNnW0T0dIbsAgWXPZyVlv6GJCruHHHMrTUZDKsQTIFI6tDChPsMsZTcplb7mOR34XlMDY/h8Nrk7n+2EquP7byHdsLvFaOm5DNN/ZcRdDmZldxNa+eMp1YZh7+DQF0HZ754qyP9R5PY0kmUm+UU1L93OzLBgR01c73AztokhdQWPEnEBWG13yB2tEG0rYYUsd9dFTMZlnISp7Pwr0XHl7I/pGT63K57aX9/OW0H/LYhlX4soJsnXs0f5s1kQmOtwdLibTKy3v62dg6zBfmlTLrl7/k6R/8lJv/+hQr5hxDw09+iEsQWXzfJnQd7r9k6v+EkAFMzB+71z2/cxN/8J5JsWznFncXrodvIR4KIXk8LDfl8bPpSzBKIhkOEw2Zdr5/Sg3FfhvAv4zMPMIH54iYHUIQBM794S/+I+9lySgmJIcAsKoCvtgIr2TkcZR5mPGDu5ACjejpNvKs8+hGQTPEaDNM5YwZH2/Jc5snj5TZQDqaQsZEXqKHjTUzEcK92Chg0k4TMZNEeHI/r+/bwPGHxKytJ4SAEdXfx4TmYg7k76FwqACfvI5tQyK2RBKbpwDR7OKxcpkp/auItS9CERUsOXbyg0GGjQoG0YglAWXDAzweupmktYNvhW7jxsYfcerovQzELsSRaqZCzEcQRB6syWJibC+mphqMYoBp5mxakyoGWWDeN6exyP3x3Et8kyVTCnl+Ry835F0PjVbqDTIja/qIqRoPXz6dcTnO93+RD0Cx34oxnqIQA7rbgiAmOV7KxqNuoyU9HcH7e9oGZ1KiNpB3eTGtF1+BJhq4aepxiHG47/xG7Kb379InTczhtpf2s1Cyk3HReRyMJfl6ro9889jsUtd1ntjcxc9f3k9/aMylZEfXKI9fOZMv/+i7PP3lL/F5v5MM2cjNf9tN00CEBy+dRpHP9rGej//PTMgdE7NBi5u/Lr0J95TJxNavx1Baimax0J6S+E3jEibne/jj5yeT4fh4f5tHeDeffcOu/4fY3H7C5rEoQpMuUbx3G+6+BHtzrOQkMskJBrEbrFhkNyMxcGRsJKFkYvd8vCM52WJFEmVSWgKjYCSv/QB5KQVvfohOvQZJieKIpnDG4WDvfmAs2jEynKTToKFaeig26+xuW4SEgDH2MilVor59AF/GLGKCwqpMA/MHt2OO5rA+x8i1TSkmKXYGjWPLKlbNwr6Bs5jalKRuUzZ7YtPwCgFqugx4AkF0PUqOtYyQGGez18VxB7rRFRMFTg9pYH9CY/aSKswfs5DBmMddntvC0XGJrZOria7rJxxP88Al0z52IQMo8tlwJGxIySwWpIeYkszjRx2vEldnEZ/8NJoO4oYZeHf8lc7TT0WIhrjvjOvpj5q4aHbxv72cWeSzUZfvYumOPs7K9nJjaQ75ZpmkorJ8Tz+X37+JG57YQZ7bwoOXTuOP5zWwvSvI7csPYJMkPp/rI0M2sqltmPveaOPCGUXMrvjsG9n+Iy6rkQKXiSZfESajRKqrC1N1FamDB1HsTm475euYTUZ+e279ESH7D3FEzD4FzDY7IdvYxdyEjCEUpezAOqL5LkaFBkh3km0ZC4UfUgSs3t0syD68qehHQZQkbCmNlJpEFk20x+2c2fkXcqVWpH4PqfBTpGPLGUlX4hgZa2/3aByXotFn18kPjaL4DiD2lSOzn9awjfyRUQySiCmrjpeyDZQN70KKVqOgYSyyUhzXcWpeRqSxWYBV0GhsiiOnl2KPDhFtPZrf9d7MKmUReroNARG7p5INXo38VA+W1ipMtn4mYKIpppKTbSFn6ifjPSeKAmc05LG6aYgFv3iNwXCS+y6dSm2+6/0P/hDkeywENDctuoPfDPTy655dmEjSoTWQsvfQFJpG+fb1GPZvJlR/Ai9873YeM2bhdZr4+jHv7dV3OE6amMvO7iBth+qnbekY4YRfr+Ky+zextiXAd04cxxNXzmR2hZ/ja3M4uS6XB95oJ5IcK0eoajrfeWYXuS4LXz/u3RZV/wtMLPLSkluJnkohms0k9+3Hd801PHDJD9kfVPjF2XXkuCyfdjP/ZzgiZp8CoiShiGbSWgpZMGLRFZw2nanJbSRHctHSbeSZihjVEyQMg3SYxlHZkPWJtMWSiJBWkxgFI5rRzYPu48kf7COvN4GuBdCUPoh4MIqHgj8GoxTqUURPgvKggwF5kKyEjJR8FQGdqu5RnP5GREnm2UIrc3tWovQ10G5SOa9HIabp9Og2UofuSVqEFHrydUKRvRhij1DZmWRXso7RaDZaupkCIQuDZOHFPB8nNrWgpWwUGxxEBWhLaUw795ONArtwZjHnTy/i5LocHrxsGg3v4VT+cWAySPQJHvYcWil0GgaJqkfRV7thzJt4czX+rg3sOuVKvnbNhfyuV0GMKvz8tNp/6dV3ON70IXxuRw97e0Ocd9d6EmmNO8+fzNbvHctlc0rfUWvu0tklRJIKT27uAuDhDR3s6wvzrRPGYfs3ljY/i9TmuejVZEKZeQiiiOO22/mGfSoPbezkirmlHF39yfTZIxyeI2L2KWFKyqTUOCZRJm1zsD6jnomjr5HXLyAo3fgshQRSBky+7RzsO5rcik8mmTSphsYSuCUZ1SARyC2kk6kI8Tdr18dwDqkgj2W9tg5FcWoKLnuSymgBbww2ghZlJBajaCiELmlIxbPoMmkMSb2MFxVE1URHuY2GUY3+tMaQ4sKgqqhqEpvkIBXfgkHQiKWT6IntrAufR3Z/Ck3poUguREVli1cjqy0Lg7OHasFNR0wlM9NCxid0Xt7EZzfxg1Mn8JPTJ75nyY2PkxF7HqqvD1V3kNLK2KE2kPa00Jkso+GlNbQXTuGGvHEMLOvC0BPjmqPKOXrcB79o5rotNBZ5uHdtOxf/ZSNOi4GnvziTRTXZmA5TZ29SgZtJBW7uXn2Ql3b38eMX9jKtxMsJtZ/9oo/vxZsGvuu+/Vtyn3qKr/a4WNU0yC2n1PDN4/83Z6ufJkfE7FPCEldJKFFMkkzYkYWe7aRZn48t3o/XnI1BMjGUBl/GWqaa7Bg+4Mj73yVoTJA+5EaiyF4szkGSoVI0pYPJvoWMd8/EHoxgNiWIpNLsD0QQBIm0L02JaCE+WI6u7AME8gJhTJYCZE8Zfy8wM7XtdUKDM4iKKWYKEoquY8qyocl2rLpCVBvGp41FzzU09+FIp9GT65m5N4Eh2QrouB0l7LOFmTqyDz2aQbYlQkyE5qTGpJNK/uVn+29EypnAUfIQz/bM44HealIN9yAadWI7qnGEu/hx/SLk3jgLSv08cOlUvrbogy0v/iNfmFeG3y6T5TJz5/mN76j1dTi+vqiK4UiKLzywGa9N5rdL6v+nQ8rH5Tg5Zlwm97zRweX3b2Z96zA/P6uOC2d+PCk8R/hgHBGzTwk9GSOhRrCIJhRzPnNDm0hGxqGlO8gyF6PpGkFLK7oxSUX1J+cMkDBLJLUYsmgm7Mpm3ugmKjsSSEoXpfZaCmzVkIzgMAXZ3NXNvkCUqGhAtASw2kbxha0I2h6MigpCCmPxbABWZqSYo20jNVhFp1nnpF6F3rROxaIi7HkOFC3CfnsvHlshU9uGyC06gaqQjKrF0dV+LNKrmHUDFnsB630idU0pBEOC8WoBQ2kNoyxSPDnzEzsvnxb2wkaKwmmWj9tP//TtKGYzg0omjY9tYX3JdDoENz85vZY7zp/8vqVN3o9jx2fx4nVzefaLs95hL/VezCz38+J1c7l4VjEPXjqNzCOh5Xzp6AqC8TQbWoe59fRaFk/66J6pR/hwHBGzTwmVUWJaELPBho6L2bFVZPcbId1EnqmQPoJg28EBbQa55Z/cUprBYCSpRxEFEdHsZLs6Dk8gSIYpC1E04DR60dUh9JSRjZ3dtI/E6HcJFEd76DLHsCoCqWQAfziGVfJhLJrFsiyJgvBqjGI1AgIUObCqENTBXZdBRpWXiGGU5/wbEE1OCmovx1SxiILys0DXKXT9HiUcoowcBEFkh9eGpbcAe+5OTIqT/VGVyqnZSP9mLtl/E1m5xYQjds6oG2Z+dhSsaUY2lyMno/x2/EKOrcni7MaCT619BV4rN538dq7U/zp1BW7+dP5kll47h3OmFn7azfmf5rN3NfgvQZU0QkIAWTThDSd42L6YgqEEohbCZcmlT9MxuvegH5xDduknEz0HYJUE4oQByA/GEVKl6EoX2daxJTxRkLAJSTTFwcb2LmLBFEGbSn44wvZE0ZjQaTreaBxL5UkYRZl7SiWmNK8j2DaLISnKvJRIWNfxV3kQRIGMag+Co48Dhn4CwiAGfyUjUgjZXUKVoZSDXS7impE8OZ+EkCIn3o6gyeRYYnTJENNg3LzP5gi4PNPOzmQxGYEUiiTQHS9m7v2beGTKYkaMdq49+r1rhB3h02FhTTalGe+uin2E/yxHxOxTQjHDsGEEgPxIFHegEE3pJsNSiCCI6PIwbkOAAksmsuWTixZzaVEi4lg7igdVprSEQWkm11xCRB0FwCkZEZIWDphN2BMqcYdIflAiFMhHV1sAkEgi5k9mRaaBovQySgpVlFgGIzJMDah0JzUqFo655buyreS5erGnXPzNtxKVFN8q/A19Qi8VnuloiGSH4lh9lWx3jlDamUYyhSiKlhKMqLg8Jvz5n82LR5HPxqt6PRP3hGlYG6Xk5mGac338vWAaR1VlMCHvkxvYHOEI/80cEbNPCdEgEDCNuYDkRKLMaBlBUnaSZS4ipSeJZ6zCoicoGPfJljx3K3FChgQAjoREYZ+CRY9hk73s0NvRdR2n7EWKiww4sslwSkQ9VjI1M45RB4J2EHNKweGvwyyaeTknyeRNG4n2z0AV03jy3YhASBBwHZphGowSeQmB2v7JPOZfwbkV3yAhwavebVjt+WSOmKkfTGOyZLPRrSD35WPP24IYLaI9plE6Jesze4NdEgW2+KYDMBKyYEkleOS0LxJNaVx7TOX7HH2EI/zvckTMPiWsgk6fbUxEzLoZS8yMmDhIrqmINmmAtNDGkFjwiYXkv4kpITJiGkuENelRdKWHLEsxAHFbgqgygsvox5DQyAv3I/sd6G4Bg9GEOyGgpAO44glcuUczYBLwGZ6lOG+I2s62DQAAGsNJREFUcNdk+sQw05IiA+j4/2mp1BJ2kjdsxhvPIWRIMLe7nk6LgCCITE8b/6+9O4+SK6sPO/79vVevXu1V3V3VVd1d3VJLai0jCQlmBMzCzCQzwMHgBfAYD3GAg2MW29jOCbF9SOIQjmOf2CYQIAQcSGAwDjljHLBhWGccM5kDNgJmBs0iabTOtHpfq2uv927+qNZII7XUPS11Vy+/zzl1TtXrV3Vv//pKv7r33Xcvds9+ALxGDfwgqewxzgZtPGD7SzfexI+L5Xt6+WT9NXw87/C77+nlifF27t7TuaRJGkptVprMWiQmNUYjzXu3olIi2vXXGDtCNJRmNDCL+BbF6VvoWsHJHwCWlWDMreB5Ndpsj7j5Hl3hbRRro+S7jjDtjZAMpgmWGvRMDtJZHaM9MM5QIIOYGr5XJ1W3iSa38Z2cz8CTR/GDAxgvSB3DvlmfsbLPtttfeI2rNp1mJPIIN5/+BXJzvcRGb8eZdKlRxc7tYvSGGznrjtE/VQenSEZcpkse0bhD55alLdu0Xr1iS44/8d7B19s6uTH3AWYrDf7lq7VXptTVaDJrkWi9St1y8PwGcVMiPPU4ufkeUSB6knCgjF3ZQySxslulh8JpKuEI5blnaQtmKJTGyIZ6OckxqsFpZrxJYk47wWqDtolZ3No5euqDDHvt+I3mjdWxRB4LoZ76PqFCkOkzt1F3p8nmmzfzjjR8uve98PaCmXqC7w2cJD/h8As/fT9BqZGZ2MPj0Weo9t9M3vRzOD4CI90k8j8iOnwTE0WfLQfSiLUxhxjP29vV/ALz5vzv8o1Hq7xuX4693XqtTKmr0WTWIuGaR7juUG0UsO0EsyNBep08BWaJtR2lqzBG95aVn7mWSPXjBFxmSydIuVk6QtuwbZfTsUmenXUo+lVssXEbwqzdxelIgv6pc8zOJTHeEADR1DaqFnQUv0fn1jkqk9sYNkVe4tmMWpDojGBdMo3eiuYIx2oM7vhrfP8wDyZPkvIdjoTOEPcjHAuf4VhgAuO5JPOHGZ+9gZoP+d0ba6PHhezKNXuef/sPEYo17ZUptRTLTmYi0ici3xORp0XkqyJy2fSy+XMKIvLo/ONb11bdjSPYcAjWHCqNWRwnwZyJkolu5+nIWaa9Oep2kL69K7+2W0d+L4l6lWPuM9hic7DtTnyvxmykTkg8SvMTKV3fYjie45l0D1snpwnMRBHvDOFanXBygOMxD+ucx2zxVpAG4brhhoLPSMkjv//yFdWT6e102h7fyY7xmZ427j74TUptJ/ipGef3+z7Kf8rfzyvO9eHbFaJtzzIuDgD53Su/pFSrZeIuWzsiBGyLP3rjfnYucTV8pTaza+mZfRL4pDFmN3AY+HcLnHMI+EtjzMH5x2uvobwNRSROolKh4k+SIMyhWg8BJ8qZ4FkacyHOhbav+PUygLbeHVh1m/+XOw1Aws3wQ+87pH2h2zlO1W5e13OMYNo9Cu1JhDDtcxZ+Y4xU1RB3exiPP4ddTzF9+lamI0Pkcs0be4drPr0vu3xGZkfvDt4TKPF72SJvH/gbdnWcYCY6Tt/UPk64g3zg1FsozGWh82lCxTzlQoNMb4xwbGWHXdeKr//Wq3jk9/4p9+qNuEotybKSmYg4wO3AX80f+hxwzwKnHgL2ichhEXlIRPYvq5YbUDiSJlKrcDo2ScjtIN99FyPWCPjTBByhVN1DIr3yywVFU2litQo/7CvglSbwK9N8fMd3yDQgU5mF+WQWwKI9OA42jAT7iNU8PL9CNpDFFotA6jCOvQ8EinNFdlgOowGoW0Km9/KeRbqvm9yoR07KHMg9ifiGRNfTbJvezQce/SPGGs9hfIeePQ9gxvZQqG6OIcbzom6AYECvAii1VMv915IGZo0xjfnXQ0B+gfMqwH3GmJuAPwO+IiKb46v1ImLJXuqez3/b8SCnnCKBWCdfST9Mt1UmXXiWpPuSVbmXKhgK41YC1Bzh8OiX+e70/yToJKlTw2uDgF0DICA2PY1B2plg0u/G+DMAROLNWYoy9wTFsZvwM0/TE9jCrqJhvOyR60tcdr0MIJXrIDhkUQtaYAzGEvbEjhPoOMpzfoFCvR8/OkKy/SRTwwcwhhW/TUEptX4tmsxE5B4Ree7iB/DFBU71Lz1gjPmgMebT888fAOaAld2Aap1IdA1QcKtMW3N8oeOjfCz1ID+IPYZlT5IpzdC/+9Cq1MMJhalRob+S50/vfJb/cvspDs7tYtovc87ehtjN7ytBEdxKnb2lk5RqHRhvEgA33s1I0GP23EGMF2SyNEs021y377mST++BhXcgTmYSPHJuK/URF0SYPXsjcafIbHIE34tTL2aZajsJxmK63EyY2W3Xf3dnpdTGsGgyM8bcb4zJX/wAXgskROT8viRdwLlL3ysi7xORi+dkC1C/HhVf72L57UyHSwQaKR52sjyc/jZbyzlqZYdyOMyWvauzT1QwHGbGLXLDbC/F8AS+3WD7TAcpf5rBya14fvPGbkcEajavG/4BZi6K8ZvT8iORPBOhKepTh3DbTtIxlme3H+A5Vygb6LnChA03EuB0PcXQ0Xb8hsXgkZ+lJFlOuwUid/4ZD205zMDBv0EqGRw/QLIzvGmulymlXrxlDTMaY+rAw8Bb5g+9DfjGAqfeAfwqgIjcAdjA08spc6OJdGSoOFU6vQip8FnmnAL5QoJw1eJ0Jkt79+qsPRgMhSlbJbaONMsTI2QLhh7nLNPFHjxTwRgfx7KYsrpIeM+RnLaw/UEiDSHqpKlHhjGNNNL1U+xMjnzFMFNtbtOSXuB6GYCIYFsRJp9OcfSr/5qjXT+mOLaLXV3H+NSPf4lfOvEtOiPj1MZ3MFf3yfXrfVZKqSu7livMvw68S0SeBF4F/FsAEXmPiHxo/pzfBl4tIkdoXjO71xhz2XDkZhSOxnBti1TDoehME/FC9M8GcEJTDAW6XrBl/UqybBvLsQiNlYg3omyr5ilWZ+jwJwiZvRgMdb+CIzZzJsvxUD+Zgg+NCbLSjojglcsAzNSr5GNhKjaMFTy6d7Zd9feIhXoYTzX44oG/4Ma7XsLsUIK90WN8JPkf2XrDafANk4M7qdZ8cjrEqJS6imUvx26MOQPcucDxT130fBB49XLL2MiCoTDt+EghTDjq8t5jr6FeO87W40OM71vdkAXEZqo6xO8M3UuwFqAw+ffU9/sc6n0pTz7yTRq1Co5lE6iEOR66kZc2DHWvTDrQnH4/M5XCTT5L9LkBXupaPBOzmJkw7N119XvCdt/2Dh4Z+gRz7vc5lH85D/sncYyPv89QDQfBahCYuQGA7Apug6OUWv907m+LOK7L1kaJLUeqvO/HNzFx6jESYyGimRluvunnVrUuoaBHOVCnc0gIDk+RLo0y5nRw8NZ+JFCm7pdxLJfuqQqnzH4wJXwMsXCWkuUzW8gTzTxBf+AgJRuCU81JIz07rz77cMeNPbxk8DX8cvrtHL2vjJPZTdkNUI1b+HaDRiVO0O0i4Np0dOtmkEqpK9Nk1iJOKER3rYrYFhPjwwDEi6eZ3eGyvWd1N2BMe3We6ZnjR+Pf5qmZH9AbiHLEtBNNukTsIjVTJmi5pKfKZKbB9yYACEVzzNgVMAHc9FG22kGOZRymEIIh+4rXy87L72yj3cqQ/vYhho7Nwlwb5bkuZsodeMUwpdEBKhZkt8QXnN6vlFLn6f8QLRIIBknUfMquj2ca1Nw6VbePp+IxAtbKbca5kGxjkuO9cwCUg3Uy+SHOBCMAxIIT1EwFxwoRL9TZNlzHktMAhMNZqqYM0sCPTyBAarbBpCV0D6QWve5nOxZ9N3TQqHoEwwFKzwSpTeRIBKewY2XmpvNMjVd1iFEptShNZi1iWTb2XIhz0eYuz2W3RJcUeCy4+msPBjyL6XidwXSZcL1Eedsoia4DAISsGlVTIWi5WH6V/IRH0DtDhDCOHaHcMNjRQUKz/TyWsshVhdlCne6dS/s9bri1i7ZchDf85gEsYzFeSiK2z9SpW/Bn78T3DTlNZkqpRaxuF0C9QKEUp9Lu4VmGtrkCfTtOQPqXV70ettdsBsd7R3jnww6Tr3cYyO8DoGbCGKniWC7GVAFwGqN00AXAVDFBpPdH9I3fyE9ci0IyChNV8otM/jivb28Hb93bvBWxa3uS708OEPy7GxkpJ7j9pt08em6QXL/OZFRKXZ32zFqo4EcZzhT5+s3D7PBqlHphT+6mVa9HtOxya6XMex+EaMpn2OumZ36ZqqlGOyVp4FguYgogDSr1Oh12M1kVGkK8/SliMzvJlzyGah7hRJCO/Iu/Ty63LcmszPHVtkc49Os5ZqdrJDJhwnG9WVopdXWazFqo6iTJ1qtMJmvsTU0x4XawI7V11etRtmJ8YmSMVx4YJXrHEI9W0/TEmsmsKGnKtgdA2Axjx05QMkESgXZqeFQMxOLHOWPF2R6NcPaZGXa8rHNZ98ml+2IMjB7i5255Nf9ky50MHp/S9RiVUkuiyayF3I4etpUMqTnD1J0BfmgG6E/0r3o9Zqx2Aj6cfqXL6f1hvk+ZrmhzGNFKZKlZzfvc28xJIomvN+seSVOghgTHELvGyYgwmw7j1X0GbupcVj0yvXHCjRi3+K9h8lyJarGx5OFKpdTmpsmshbrz23iXP8r9Q0NUT8T4STFENrryG3JeqhDt5+hsmvrJEKce68ZLOYQCze1nYh1d1APNZNYwYWKzzVmPbqSTYkOw3EHqEmXOtTg7XiHW5i57wkayM0IgaDH+bIHBo82JMT1LnEiilNrcdAJIC2W3b6d+NkiXO8fRZ7OcGahiyep/v+hs6+ZrR/fgTlqEwkG2Z7qe/1kynWfaGYY61CRGR6GAY1KEgu3MlRtYqSGodZHzPQbPzLDn5i5kmUtxWZaQzscYe7bAzHiZVDZCrM29Xr+mUmoD055ZC6V68hQbzckN56SNG7JbW1KPnbubS0ZVyz4Vq4Ptye3P/yyd6cZ3mj0zxwpzbKaDbq85uWPOBzd9Fmt6F3nLplHz6dvXcXkBL0K6N87Y2WbPTIcYlVJLpcmshRKZTuYaQXwDj7QX2d6CyR8A0fSFSRYPbH2U7akLySyVyBIwJQBcO0LZD5KlOVV+zm+Q6DzNdGkbFTuEFZBrHhbs2dlGo+aTzETYf+dC+70qpdTldJixheIdGX4y2cNgKcnZbTO8NrG1JfUIhsIAeJZhqL3MjtSOC3WMxmF+G5iI3Vyeqt1ux8enHn2OmD/Lk14ab7ZKz0AKx7UXLGOptr8sw6999HaCIW2aSqml055ZCwUchyET4enZTmohOJRbnd2lLxUMN5PZaFsV3xH6kxdmVMajUSzjUfSnidlxLGNww2mmpAShQVyvRrnextRImd491zbECM19zjSRKaVeLE1mLea5zT/BHQN3kYuuzu7SlwqGm+swDqer5GP552cyAkRCLrZnmLImSVhx2gplvFSOSWrgjOJhk2wYALK655hSqkU0mbVYpL05dPfOV72vZXVo785zx6+8E/fGfg5kDrzgZ3bAxmkEGHEmSUiMG8+OEgplmfN9jD1CzQrT0WjeVJ1exqofSil1Peh4Tou96s4388TfP0g22bX4yStERLjpZ9/EJxqvw5bLr3kVxVBzS1jhdoLhDLYEqNYF256lZGUwEiSZCevwoFKqZfR/nxZ7+evfxMtf/6ZWVwOAcCC84PGqmaPieIhlQ+cuAAJOEaIes+U+/HKAroGr712mlFIrSYcZ1aIsr4RvmkOJ3paXNY+lThFOVKgWOykVfNK9OsSolGodTWZqUXHjYTeaN04nkns4ERjG6niCmF+EYnPpqswiu0orpdRKuuZkJiIfEpEPXuFnQRH5gog8JSI/FpHd11qeWn1pW7Drtedfn7AmqQZPEm8UsOeaMyG1Z6aUaqVlJzMRSYrIZ4H3X+W03wKKxpg9wO8An19ueap1ooES0YbPrN1cZNixCpTLDkGvgVVO4UYCRBK655hSqnWupWf288Bx4MNXOef1wBcBjDHfA9Ii0ncNZaoWiHsFYp7PYHCUI+Fn6KRCvRTFWOB57bTloogsb3FhpZS6HpY9m9EYcx/AlYYY53UDQxe9HgLywNnllqtWX8AtEaxU+XDXfQB8YPwgpu5ScVwajTBtXZEW11Aptdkt2jMTkXtE5LlLHt9d4ucv9HXdf3FVVK1WNR5lq4xjAqS8OLXEWQKWxbTbgVe3aMtGW11FpdQmt2jPzBhzP3D/Mj9/EMgBz8y/7gLOLfOzVItUQhEq9TLvG76XoB+kvPsjyEwH1XoaQHtmSqmWW+mp+Q8AbwMQkduAijFGhxjXmYKdQOo+/YUs3cUk9UCZULCEKTZnMLbltGemlGqt674CiIi8B+g2xvwB8HHg0yLyBFAF/vn1Lk+tvKIJk6jDlBmmTom5iTbSfoGhchw7YBHvCC3+IUoptYKuOZkZYz54yetPXfS8Arz9WstQrTVlkmw1Df6x9CUCIZ/UaCfxxDDnSp2kshEsS2cyKqVaS9dmVIsq2yEkOE4qP40TbuCd24ITbeBXc6T69HqZUqr1NJmpRZlIDDd4msRACTBMN2YQDLVCjmTnwosTK6XUatK1GdWiQtkcKSlQfqyHyo/7CeeHMK7gVeMkM5rMlFKtp8lMLaojv5OINc3Akb1se2oHifA4hUgEsEhpz0wptQboMKNaVLo9gwSqVEYeoRZyiJ2qM9bZAUAyo9fMlFKtp8lMLSoei+K7FhPv8CFYYutPfU63xwk4FpGkLjCslGo9HWZUi4q5UeqJMLGOaSJd08TKDcrVMMnOsC4wrJRaEzSZqUW5tkvBjRMY8wmeFOj2qFbiOsSolFozNJmpRYWdMBNWhMyXIP0FodwnVMttOpNRKbVmaDJTi2pz2xi2HBJOnbZklbmYjVdMk9BkppRaI3QCiFpUxInwnHhkb57GMvBUpAMpdtGW02FGpdTaoMlMLcmEeNSCFhiHCg72XI5UVpOZUmpt0GSmlqRshZhNBKjbwmAlQNSJEUnotHyl1NqgyUwtSdDJcGRPAoDBCYe9uZhOy1dKrRk6AUQtSTLS+/zzyWJar5cppdYUTWZqSTpiXVT95vPZqR5SmsyUUmuIJjO1JNl4JwVfmPEEmcvRlou2ukpKKfU8vWamliSXyvD4kEXZh3i1XYcZlVJriiYztSTZeCefn3AB+MWA3jCtlFpbdJhRLUk6kn7++S237Me2tekopdaOa+6ZiciHAN8Y88EFftYHPAGcmD80Yox57bWWqVZfR6i5fxlGuO32l7S2MkopdYllf70WkaSIfBZ4/1VOOwT8pTHm4PxDE9k6FQqEiNpR2kPthEOhVldHKaVe4FrGin4eOA58+CrnHAL2ichhEXlIRPZfQ3mqxTLRDD3x7lZXQymlLrPsYUZjzH0AIvLBq5xWAe4zxnxaRH4G+IqI7DHG1JZbrmqdN2x7A7FgrNXVUEqpyyyazETkHuAjlxx+2hhz92Lvvfg6mjHmARH5Y2AP8NiLrKdaA9594N2troJSSi1o0WRmjLkfuH85Hy4i76N5zWzi/CGgvpzPUkoppa5kpedX3wH8KoCI3AHYwNMrXKZSSqlN5rrfNC0i7wG6jTF/APw28DkReRtQBu41xvjXu0yllFKb2zUns0vvLzPGfOqi54PAq6+1DKWUUupqdBkHpZRS654mM6WUUuueJjOllFLrniYzpZRS654mM6WUUuueGGNaWwGRMeDMJYeTwMyL/Kg0ML6MKiynrOW8ZzXLWuuxWM34LScWa/3vu9z3bcRYLLd+qxWLtR4/WF+x2GKMySx4ljFmzT2AP1/Gew6vYlkv+j2rWdZaj8Uqx+9Fx2Kt/301FtelfqsSi7Uev40Ui7U6zPi3a7ys5dZvNctajtWq32rGbzXL0Vhc2/v030drylqONReLlg8zXi8ictgYc1Or67EWaCwu0FhcoLG4QGNxwUaJxVrtmS3Hn7e6AmuIxuICjcUFGosLNBYXbIhYbJiemVJKqc1rI/XMlFJKbVIbIpmJyFtF5EkReUZEfqPV9VltIvKQiDwhIo/OP16xmWIiIgkROSIiW+df3y0ij4vIcRH5w4vOOygiPxSRYyLyGRG57rtGtNoCsfgf83E43zbeOH98wRhtFCLy7+f/TTwhIn8yf2xTtosrxGLjtYvlTJVcSw+gBzgFtANRmrtY39Dqeq3i7y/AOSCwGWMCvAJ4HKgBW4EwcBbop7krxLeA182fewR45fzzzwLvbXX9VzIW88d+CnRdct4VY7QRHsDdwCNAEHCAB4F7N2O7uEIs3rgR28VG6JndDTxkjJk0xhSBvwJ+scV1Wk27AAN8Q0QeE5HfZHPF5NeA36CZ0AFeDhw3xpwyxjSAvwDuEZEtQNgY84P58z4H3LPalV1hL4iFiESBPuC/z3/b/g8iYnGFGLWq0itgCPhXxpiaMaYOPAXsZHO2i4Vi0ccGbBcboTvdTfMPdt4QzT/KZtFG89vWe2l+s/q/wP9mk8TEGPMvAETk/KGF2kP+Ksc3jAVikQUeAt4NzAFfo7nz+xwbOBbGmCfOPxeRAeAtwMfYhO3iCrG4DbiTDdYuNkLPTBY4tml2szbGfN8Y8zZjTNEYM05zmORDC5y6WWJypfaw6dqJMeakMeaNxphRY0wJ+DjwM2ySWIjIXuA7wPuBEwucsmnaxcWxMMYc3YjtYiMks0Egd9HrLi4MOW14InKbiNx18SHgNJs3JldqD5uunYjIfhF588WHgDqbIBYicivNEYvfN8Z8nk3cLi6NxUZtFxshmX0XuEtEMiISAd4MfLPFdVpNKeBPRSQkInHg7cCvsHlj8g/ALhHZISI28FbgG8aYM0Bl/h82wNuAb7SqkqtEgI+KSJuIOMC7gP/DFWLUwnpeVyLSC3wFeKsx5kvzhzdlu7hCLDZku1j318yMMYMi8m+Av6M5Y+czxph/bHG1Vo0x5msi8grgJ4AN/FdjzCObNSbGmIqIvAP4MhACHqA5AQbgn9G86B2nGa+PtaSSq8QY87iI/DHN2WwO8GVjzP8CuEqMNoL30/y9/vNF1w8/BbyDzdcurhSLDdcudAUQpZRS695GGGZUSim1yWkyU0opte5pMlNKKbXuaTJTSim17mkyU0opte5pMlNKKbXuaTJTSim17mkyU0opte79f8zusxwgowqFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 510.236x311.811 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl.plot(results['AR6-historical_climuncert']['surface_temperature']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "AR6_forc = {}\n",
    "AR6_ecsforc = {}\n",
    "forcings = ['co2', 'ch4', 'n2o', 'other_wmghg', 'o3', 'h2o_stratospheric',\n",
    "            'contrails', 'aerosol-radiation_interactions', 'aerosol-cloud_interactions', \n",
    "            'bc_on_snow', 'land_use', 'volcanic', 'solar', 'wmghgs', 'aerosol', 'albedo', 'anthro', 'natural']\n",
    "\n",
    "for forcing in forcings:\n",
    "    AR6_forc[forcing] = np.zeros(5)\n",
    "    AR6_forc[forcing] = np.percentile(\n",
    "        (results['AR6-historical']['surface_temperature'][-1,:] - results['AR6-historical']['surface_temperature'][0,:])-\n",
    "        (results['remove_%s' % forcing]['surface_temperature'][-1,:] - results['remove_%s' % forcing]['surface_temperature'][0,:]), (5,16,50,84,95)\n",
    "    )\n",
    "    AR6_ecsforc[forcing] = np.zeros(5)\n",
    "    AR6_ecsforc[forcing] = np.percentile(\n",
    "        (results['AR6-historical_climuncert']['surface_temperature'][-1,:] - results['AR6-historical_climuncert']['surface_temperature'][0,:])-\n",
    "        (results['remove_%s_climuncert' % forcing]['surface_temperature'][-1,:] - results['remove_%s_climuncert' % forcing]['surface_temperature'][0,:]), (5,16,50,84,95)\n",
    "    )\n",
    "\n",
    "# create some new aggregated categories\n",
    "non_co2_ghgs = (\n",
    "    (\n",
    "        (results['AR6-historical']['surface_temperature'][-1] - results['AR6-historical']['surface_temperature'][0]) -\n",
    "        (results['remove_ch4']['surface_temperature'][-1] - results['remove_ch4']['surface_temperature'][0])\n",
    "    ) +\n",
    "    (\n",
    "        (results['AR6-historical']['surface_temperature'][-1] - results['AR6-historical']['surface_temperature'][0]) -\n",
    "        (results['remove_n2o']['surface_temperature'][-1] - results['remove_n2o']['surface_temperature'][0])\n",
    "    ) +\n",
    "    (\n",
    "        (results['AR6-historical']['surface_temperature'][-1] - results['AR6-historical']['surface_temperature'][0]) -\n",
    "        (results['remove_other_wmghg']['surface_temperature'][-1] - results['remove_other_wmghg']['surface_temperature'][0])\n",
    "    )\n",
    ")\n",
    "AR6_forc['ch4+n2o+cfc'] = np.percentile(non_co2_ghgs, (5,16,50,84,95))\n",
    "non_co2_ghgs = (\n",
    "    (\n",
    "        (results['AR6-historical_climuncert']['surface_temperature'][-1] - results['AR6-historical_climuncert']['surface_temperature'][0]) -\n",
    "        (results['remove_ch4_climuncert']['surface_temperature'][-1] - results['remove_ch4_climuncert']['surface_temperature'][0])\n",
    "    ) +\n",
    "    (\n",
    "        (results['AR6-historical_climuncert']['surface_temperature'][-1] - results['AR6-historical_climuncert']['surface_temperature'][0]) -\n",
    "        (results['remove_n2o_climuncert']['surface_temperature'][-1] - results['remove_n2o_climuncert']['surface_temperature'][0])\n",
    "    ) +\n",
    "    (\n",
    "        (results['AR6-historical_climuncert']['surface_temperature'][-1] - results['AR6-historical_climuncert']['surface_temperature'][0]) -\n",
    "        (results['remove_other_wmghg_climuncert']['surface_temperature'][-1] - results['remove_other_wmghg_climuncert']['surface_temperature'][0])\n",
    "    )\n",
    ")\n",
    "AR6_ecsforc['ch4+n2o+cfc'] = np.percentile(non_co2_ghgs, (5,16,50,84,95))\n",
    "\n",
    "AR6_forc['total'] = np.percentile(results['AR6-historical']['surface_temperature'][-1] - results['AR6-historical']['surface_temperature'][0], (5,16,50,84,95))\n",
    "AR6_ecsforc['total'] = np.percentile(results['AR6-historical_climuncert']['surface_temperature'][-1] - results['AR6-historical_climuncert']['surface_temperature'][0], (5,16,50,84,95))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5,)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_forc['total'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.06310326 -0.04653063 -0.02300891  0.00172144  0.01976024]\n",
      "[0.98611954 1.10798124 1.29365315 1.50668911 1.64848345]\n",
      "[0.96053118 1.0811771  1.2704868  1.48955094 1.64020591]\n"
     ]
    }
   ],
   "source": [
    "print(AR6_ecsforc['natural'])\n",
    "print(AR6_ecsforc['anthro'])\n",
    "print(AR6_ecsforc['total'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 510.236x311.811 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = pl.subplots()\n",
    "\n",
    "gs = gridspec.GridSpec(1,2, width_ratios=[5,1])\n",
    "ax = pl.subplot(gs[0,0])\n",
    "# errorbar for owmghg is going to be a mess so pre-calculate it\n",
    "\n",
    "#hot = ['#f03b20','#feb24c','#feeda0']\n",
    "#hot = ['#de2d26','#fc9274','#fee0d2']\n",
    "#cool=['#3182bd','#9ecae1']\n",
    "\n",
    "hot = ['#cc404a','#ed8037','#ecd151']\n",
    "cool=['#304fbf','#369ce8']\n",
    "\n",
    "ax.barh(0, AR6_ecsforc['co2'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['co2'][2], 0.18, xerr=np.array([AR6_forc['co2'][2]-AR6_forc['co2'][0],AR6_forc['co2'][4]-AR6_forc['co2'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['co2'][2], -0.18, xerr=np.array([AR6_ecsforc['co2'][2]-AR6_ecsforc['co2'][0],AR6_ecsforc['co2'][4]-AR6_ecsforc['co2'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-1, AR6_ecsforc['ch4'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "ax.barh(-1, AR6_ecsforc['n2o'][2], color=hot[1], left=AR6_ecsforc['ch4'][2], lw=1, edgecolor='k')\n",
    "ax.barh(-1, AR6_ecsforc['other_wmghg'][2], color=hot[2], left=AR6_ecsforc['ch4'][2]+AR6_ecsforc['n2o'][2], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['ch4+n2o+cfc'][2], -0.82, xerr=np.array([AR6_forc['ch4+n2o+cfc'][2]-AR6_forc['ch4+n2o+cfc'][0],AR6_forc['ch4+n2o+cfc'][4]-AR6_forc['ch4+n2o+cfc'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['ch4+n2o+cfc'][2], -1.18, xerr=np.array([AR6_ecsforc['ch4+n2o+cfc'][2]-AR6_ecsforc['ch4+n2o+cfc'][0],AR6_ecsforc['ch4+n2o+cfc'][4]-AR6_ecsforc['ch4+n2o+cfc'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-2, AR6_ecsforc['o3'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['o3'][2], -1.82, xerr=np.array([AR6_forc['o3'][2]-AR6_forc['o3'][0],AR6_forc['o3'][4]-AR6_forc['o3'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['o3'][2], -2.18, xerr=np.array([AR6_ecsforc['o3'][2]-AR6_ecsforc['o3'][0],AR6_ecsforc['o3'][4]-AR6_ecsforc['o3'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-3, AR6_ecsforc['h2o_stratospheric'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['h2o_stratospheric'][2], -2.82, xerr=np.array([AR6_forc['h2o_stratospheric'][2]-AR6_forc['h2o_stratospheric'][0],AR6_forc['h2o_stratospheric'][4]-AR6_forc['h2o_stratospheric'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['h2o_stratospheric'][2], -3.18, xerr=np.array([AR6_ecsforc['h2o_stratospheric'][2]-AR6_ecsforc['h2o_stratospheric'][0],AR6_ecsforc['h2o_stratospheric'][4]-AR6_ecsforc['h2o_stratospheric'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-4, AR6_ecsforc['land_use'][2], color=cool[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['land_use'][2], -3.82, xerr=np.array([AR6_forc['land_use'][2]-AR6_forc['land_use'][0],AR6_forc['land_use'][4]-AR6_forc['land_use'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['land_use'][2], -4.18, xerr=np.array([AR6_ecsforc['land_use'][2]-AR6_ecsforc['land_use'][0],AR6_ecsforc['land_use'][4]-AR6_ecsforc['land_use'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-4, AR6_ecsforc['bc_on_snow'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['bc_on_snow'][2], -3.82, xerr=np.array([AR6_forc['bc_on_snow'][2]-AR6_forc['bc_on_snow'][0],AR6_forc['bc_on_snow'][4]-AR6_forc['bc_on_snow'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['bc_on_snow'][2], -4.18, xerr=np.array([AR6_ecsforc['bc_on_snow'][2]-AR6_ecsforc['bc_on_snow'][0],AR6_ecsforc['bc_on_snow'][4]-AR6_ecsforc['bc_on_snow'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-5, AR6_ecsforc['contrails'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['contrails'][2], -4.82, xerr=np.array([AR6_forc['contrails'][2]-AR6_forc['contrails'][0],AR6_forc['contrails'][4]-AR6_forc['contrails'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['contrails'][2], -5.18, xerr=np.array([AR6_ecsforc['contrails'][2]-AR6_ecsforc['contrails'][0],AR6_ecsforc['contrails'][4]-AR6_ecsforc['contrails'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-6, AR6_ecsforc['aerosol-radiation_interactions'][2], color=cool[0], lw=1, edgecolor='k')\n",
    "ax.barh(-6, AR6_ecsforc['aerosol-cloud_interactions'][2], color=cool[1], left=AR6_ecsforc['aerosol-radiation_interactions'][2], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['aerosol'][2], -5.82, xerr=np.array([AR6_forc['aerosol'][2]-AR6_forc['aerosol'][0],AR6_forc['aerosol'][4]-AR6_forc['aerosol'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['aerosol'][2], -6.18, xerr=np.array([AR6_ecsforc['aerosol'][2]-AR6_ecsforc['aerosol'][0],AR6_ecsforc['aerosol'][4]-AR6_ecsforc['aerosol'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-7, AR6_ecsforc['solar'][2], color=cool[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['solar'][2], -6.82, xerr=np.array([AR6_forc['solar'][2]-AR6_forc['solar'][0],AR6_forc['solar'][4]-AR6_forc['solar'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['solar'][2], -7.18, xerr=np.array([AR6_ecsforc['solar'][2]-AR6_ecsforc['solar'][0],AR6_ecsforc['solar'][4]-AR6_ecsforc['solar'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "ax.barh(-8, AR6_ecsforc['volcanic'][2], color=cool[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['volcanic'][2], -7.82, xerr=np.array([AR6_forc['volcanic'][2]-AR6_forc['volcanic'][0],AR6_forc['volcanic'][4]-AR6_forc['volcanic'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['volcanic'][2], -8.18, xerr=np.array([AR6_ecsforc['volcanic'][2]-AR6_ecsforc['volcanic'][0],AR6_ecsforc['volcanic'][4]-AR6_ecsforc['volcanic'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "#ax.barh(-9, AR6_ecsforc['anthro'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "#ax.barh(-9, AR6_ecsforc['natural'][2], color=cool[0], lw=1, edgecolor='k')\n",
    "ax.barh(-9, AR6_ecsforc['total'][2], color=hot[0], lw=1, edgecolor='k')\n",
    "eb = ax.errorbar(AR6_forc['total'][2], -8.82, xerr=np.array([AR6_forc['total'][2]-AR6_forc['total'][0],AR6_forc['total'][4]-AR6_forc['total'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(AR6_ecsforc['total'][2], -9.18, xerr=np.array([AR6_ecsforc['total'][2]-AR6_ecsforc['total'][0],AR6_ecsforc['total'][4]-AR6_ecsforc['total'][2]]).reshape((2,1)), capsize=3, color='k')\n",
    "\n",
    "# labels and prettiness\n",
    "ax.text(1.0, -1, 'CH$_4$',ha='center',va='center', color=hot[0], size=9)\n",
    "ax.text(1.28, -1,'N$_2$O',ha='center',va='center', color=hot[1], size=9)\n",
    "ax.text(1.45, -1, 'Halogens', va='center', color=hot[2], size=9)\n",
    "#ax.text(1.1, -2, 'Stratospheric', va='center', ha='left', color=hot[1])\n",
    "#ax.text(0.5, -2, 'Tropospheric', va='center', ha='left', color=hot[0])\n",
    "ax.text(-0.23,-4, 'Land use', va='center', ha='right', color=cool[0], size=9)\n",
    "ax.text(0.16, -4, 'Light absorbing particles\\non snow and ice', va='center', ha='left', color=hot[0], size=9)\n",
    "ax.text(0.05, -6, 'Aerosol-cloud', va='center', ha='left', color=cool[1], size=9)\n",
    "ax.text(0.7, -6, 'Aerosol-radiation', va='center', ha='left', color=cool[0], size=9)\n",
    "#ax.text(-0.75, -9, 'Anthropogenic', va='center', ha='center', color=hot[0], size=9)\n",
    "#ax.text(-0.2, -9, 'Natural', va='center', ha='center', color=hot[1], size=9)\n",
    "\n",
    "ax.text(1.91, -3, 'Anthropogenic', va='center', ha='center', rotation=270)\n",
    "ax.text(1.91, -7.5, 'Natural', va='center', ha='center', rotation=270)\n",
    "\n",
    "ax.set_ylim(-9.5,0.5)\n",
    "ax.set_xlim(-1.2,2.0)\n",
    "ax.axvline(0, color='k', lw=0.6)\n",
    "ax.axhline(-6.5, color='k', lw=0.6)\n",
    "ax.axhline(-8.5, color='k', lw=0.6)\n",
    "ax.set_yticks(np.arange(-9,1));\n",
    "ax.set_xlabel('$^{\\circ}$C')\n",
    "ax.set_title('')\n",
    "ax.set_yticklabels(['Carbon dioxide','Other well-mixed\\ngreenhouse gases','Ozone','Stratospheric\\nwater vapour', 'Albedo', 'Contrails & aviation-\\ninduced cirrus', 'Aerosol', 'Solar', 'Volcanic', 'Total'][::-1]);\n",
    "ax.set_title('Simulated temperature contributions in 2019 relative to 1750', size=11)\n",
    "\n",
    "# legend\n",
    "eb = ax.errorbar(0.5, -7.2, xerr=0.1, color='k', capsize=2, lw=0.8)\n",
    "eb[-1][0].set_linestyle(':')\n",
    "eb = ax.errorbar(0.5, -7.75, xerr=0.1, color='k', capsize=2, lw=0.8)\n",
    "ax.text(0.68, -7.185, 'Forcing uncertainty', va='center', fontsize=8);\n",
    "ax.text(0.68, -7.735, 'Forcing + climate \\nsensitivity uncertainty', va='center', fontsize=8);\n",
    "\n",
    "rect = mp.Rectangle((0.35, -8.17), 1.3, 1.28, facecolor='None', edgecolor='k', lw=0.5)\n",
    "ax.add_patch(rect)\n",
    "\n",
    "# values\n",
    "ax_values = pl.subplot(gs[0,1])\n",
    "ax_values.text(0.5,0,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['co2'][2], AR6_ecsforc['co2'][0], AR6_ecsforc['co2'][4]), ha='center', va='center', size=9)\n",
    "ax_values.text(0.5,-0.6,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['ch4'][2], AR6_ecsforc['ch4'][0], AR6_ecsforc['ch4'][4]), ha='center', va='center', size=9, color=hot[0])\n",
    "ax_values.text(0.5,-1.0,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['n2o'][2], AR6_ecsforc['n2o'][0], AR6_ecsforc['n2o'][4]), ha='center', va='center', size=9, color=hot[1])\n",
    "ax_values.text(0.5,-1.4,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['other_wmghg'][2], AR6_ecsforc['other_wmghg'][0], AR6_ecsforc['other_wmghg'][4]), ha='center', va='center', size=9, color=hot[2])\n",
    "ax_values.text(0.5,-2,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['o3'][2], AR6_ecsforc['o3'][0], AR6_ecsforc['o3'][4]), ha='center', va='center', size=9)\n",
    "ax_values.text(\n",
    "    0.5,-3,'{:.2f} [{:.2f} to {:.2f}]'.format(\n",
    "        AR6_ecsforc['h2o_stratospheric'][2],\n",
    "        AR6_ecsforc['h2o_stratospheric'][0] if abs(AR6_ecsforc['h2o_stratospheric'][0]) >= 0.005 else abs(AR6_ecsforc['h2o_stratospheric'][0]),\n",
    "        AR6_ecsforc['h2o_stratospheric'][4]), ha='center', va='center', size=9\n",
    ")\n",
    "ax_values.text(0.5,-3.8,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['land_use'][2], AR6_ecsforc['land_use'][0], AR6_ecsforc['land_use'][4]), ha='center', va='center', size=9, color=cool[0])\n",
    "ax_values.text(\n",
    "    0.5,-4.2,'{:.2f} [{:.2f} to {:.2f}]'.format(\n",
    "        AR6_ecsforc['bc_on_snow'][2], \n",
    "        AR6_ecsforc['bc_on_snow'][0] if abs(AR6_ecsforc['bc_on_snow'][0]) >= 0.005 else abs(AR6_ecsforc['bc_on_snow'][0]), \n",
    "        AR6_ecsforc['bc_on_snow'][4]), ha='center', va='center', size=9, color=hot[0]\n",
    ")\n",
    "ax_values.text(0.5,-5,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['contrails'][2], AR6_ecsforc['contrails'][0], AR6_ecsforc['contrails'][4]), ha='center', va='center', size=9)\n",
    "ax_values.text(0.5,-5.8,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['aerosol-radiation_interactions'][2], AR6_ecsforc['aerosol-radiation_interactions'][0], AR6_ecsforc['aerosol-radiation_interactions'][4]), ha='center', va='center', size=9, color=cool[0])\n",
    "ax_values.text(0.5,-6.2,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['aerosol-cloud_interactions'][2], AR6_ecsforc['aerosol-cloud_interactions'][0], AR6_ecsforc['aerosol-cloud_interactions'][4]), ha='center', va='center', size=9, color=cool[1])\n",
    "ax_values.text(\n",
    "    0.5,-7,'{:.2f} [{:.2f} to {:.2f}]'.format(\n",
    "        AR6_ecsforc['solar'][2] if abs(AR6_ecsforc['solar'][2]) >= 0.005 else abs(AR6_ecsforc['solar'][2]),\n",
    "        AR6_ecsforc['solar'][0] if abs(AR6_ecsforc['solar'][0]) >= 0.005 else abs(AR6_ecsforc['solar'][0]), \n",
    "        AR6_ecsforc['solar'][4] if abs(AR6_ecsforc['solar'][4]) >= 0.005 else abs(AR6_ecsforc['solar'][4]),\n",
    "    ), ha='center', va='center', size=9)\n",
    "ax_values.text(0.5,-8,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['volcanic'][2], AR6_ecsforc['volcanic'][0], AR6_ecsforc['volcanic'][4]), ha='center', va='center', size=9)\n",
    "ax_values.text(0.5,-9,'{:.2f} [{:.2f} to {:.2f}]'.format(AR6_ecsforc['total'][2], AR6_ecsforc['total'][0], AR6_ecsforc['total'][4]), ha='center', va='center', size=9)\n",
    "ax_values.set_title('$^{\\circ}$C', size=9)\n",
    "\n",
    "ax_values.set_xlim(0,1)\n",
    "ax_values.set_ylim(-9.5, 0.5)\n",
    "ax_values.spines['left'].set_visible(False)\n",
    "ax_values.spines['right'].set_visible(False)\n",
    "ax_values.spines['bottom'].set_visible(False)\n",
    "ax_values.spines['top'].set_visible(False)\n",
    "ax_values.set_yticklabels([])\n",
    "ax_values.set_xticks([])\n",
    "\n",
    "# Create the figure\n",
    "fig.subplots_adjust(left=0.2)\n",
    "pl.tight_layout()\n",
    "pl.savefig('../figures/fig7.7.png', dpi=300)\n",
    "pl.savefig('../figures/fig7.7.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2563235294117647"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 510.236x311.811 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rebased_climuncert = results['AR6-historical_climuncert']['surface_temperature'] - np.mean(results['AR6-historical_climuncert']['surface_temperature'][100:151,:], axis=0)\n",
    "rebased = results['AR6-historical']['surface_temperature'] - np.mean(results['AR6-historical']['surface_temperature'][100:151,:], axis=0)\n",
    "\n",
    "\n",
    "pl.fill_between(np.arange(1750,2020),\n",
    "                np.percentile(rebased_climuncert, 5, axis=1),\n",
    "                np.percentile(rebased_climuncert, 95, axis=1),\n",
    "                alpha=0.3)\n",
    "pl.plot(np.arange(1750,2020),np.median(rebased_climuncert, axis=1), label='emulated - climuncert');\n",
    "\n",
    "pl.fill_between(np.arange(1750,2020),\n",
    "                np.percentile(rebased, 5, axis=1),\n",
    "                np.percentile(rebased, 95, axis=1),\n",
    "                alpha=0.3)\n",
    "pl.plot(np.arange(1750,2020),np.median(rebased, axis=1), label='emulated - forcing only');\n",
    "\n",
    "xl = pd.read_excel('../data_input/observations/AR6 FGD assessment time series - GMST and GSAT.xlsx', skiprows=1, skipfooter=28)\n",
    "temp_gmst=xl['4-set mean'].values\n",
    "temp_year=xl['Unnamed: 0'].values\n",
    "pl.plot(temp_year, temp_gmst, label='chapter 2 GMST')\n",
    "pl.legend()\n",
    "\n",
    "temp_gmst[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7ff21ff53290>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 510.236x311.811 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rebased_climuncert = results['AR6-historical_climuncert']['surface_temperature'] - results['remove_volcanic_climuncert']['surface_temperature']\n",
    "rebased = results['AR6-historical']['surface_temperature'] - results['remove_volcanic']['surface_temperature']\n",
    "\n",
    "\n",
    "pl.fill_between(np.arange(1750,2020),\n",
    "                np.percentile(rebased_climuncert-rebased_climuncert[0,:], 5, axis=1),\n",
    "                np.percentile(rebased_climuncert-rebased_climuncert[0,:], 95, axis=1),\n",
    "                alpha=0.3)\n",
    "pl.plot(np.arange(1750,2020),np.median(rebased_climuncert-rebased_climuncert[0,:], axis=1), label='emulated - climuncert');\n",
    "\n",
    "pl.fill_between(np.arange(1750,2020),\n",
    "                np.percentile(rebased-rebased[0,:], 5, axis=1),\n",
    "                np.percentile(rebased-rebased[0,:], 95, axis=1),\n",
    "                alpha=0.3)\n",
    "pl.plot(np.arange(1750,2020),np.median(rebased-rebased[0,:], axis=1), label='emulated - climuncert');\n",
    "\n",
    "np.median(rebased_climuncert[-1,:]-rebased_climuncert[0,:])\n",
    "pl.axhline(0, ls=':', color='k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.98543102, 1.10032594, 1.27065688, 1.44459347, 1.56650939]),\n",
       " array([0.96053118, 1.0811771 , 1.2704868 , 1.48955094, 1.64020591]))"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_forc['total'], AR6_ecsforc['total']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## numbers for ES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.98611954, 1.29365315, 1.64848345])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['anthro'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.96053118, 1.2704868 , 1.64020591])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['total'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.17309026, 1.58459535, 2.16831149])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['wmghgs'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.10988042, 0.23275264, 0.39297216])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['o3'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.96113552, -0.50488861, -0.21932192])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['aerosol'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.14664167, -0.06076764,  0.01232843])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['albedo'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.06310326, -0.02300891,  0.01976024])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AR6_ecsforc['natural'][[0,2,4]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## numbers for chapter 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.04053168, 0.06514436, 0.0946551 , 0.121197  , 0.13683193])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.percentile(\n",
    "    (results['AR6-historical_climuncert']['surface_temperature'][100:151].mean(axis=0) - results['AR6-historical_climuncert']['surface_temperature'][0])-\n",
    "    (results['remove_anthro_climuncert']['surface_temperature'][100:151].mean(axis=0) - results['remove_anthro_climuncert']['surface_temperature'][0]), (5,16,50,84,95)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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