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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Python = A-real-programming-language + Matlab\n",
      "\n",
      "### (i)Python = Matlab + A-real-programming-language (with unfortunate indexing)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab\n",
      "import cma"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using matplotlib backend: MacOSX\n",
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "WARNING: pylab import has clobbered these variables: ['f']\n",
        "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cma?\n",
      "cma.CMAEvolutionStrategy?\n",
      "cma.OOOptimizer??"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's write out the iterations of an optimization loop."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "import cma\n",
      "f = cma.fcts.elli\n",
      "es = cma.CMAEvolutionStrategy(ones(12), 1)\n",
      "while not es.stop():\n",
      "    X = es.ask()\n",
      "    fit = [f(x) for x in X]\n",
      "    es.tell(X, fit)\n",
      "    es.disp()\n",
      "    es.logger.add()\n",
      "    es.countiter % 200 or es.logger.plot()\n",
      "es.logger.plot()  # somewhere should be a window with the plot\n",
      "es.result_pretty();"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=538973, Tue Sep 23 23:41:51 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     11 1.555972958294088e+05 1.0e+00 9.40e-01  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     22 1.193626152008547e+05 1.1e+00 8.94e-01  9e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     33 7.739222284130834e+04 1.2e+00 8.33e-01  8e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1100 6.995455109263232e+02 1.4e+01 6.17e-02  8e-03  9e-02 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2200 2.710339118345073e+01 9.8e+01 2.94e-02  1e-03  7e-02 0:0.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3300 7.754992114095977e-01 2.6e+02 4.56e-03  7e-05  1e-02 0:2.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4400 3.723306581263208e-03 5.0e+02 2.01e-03  1e-05  6e-03 0:2.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5500 2.535537941653915e-08 9.3e+02 1.72e-05  5e-08  5e-05 0:4.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   6600 9.680792326573095e-14 1.2e+03 6.95e-08  1e-10  1e-07 0:4.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  604   6644 4.972402815295541e-14 1.2e+03 5.14e-08  7e-11  8e-08 0:6.7\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<cma.CMADataLogger at 0x108d44fd0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And pretty much the same can be expressed (much) shorter, if so desired. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "es = cma.CMAEvolutionStrategy(ones(12), 1, {'popsize': 33, 'bounds': [1, None]})\n",
      "es.optimize(cma.fcts.elli)\n",
      "es.result_pretty()\n",
      "es.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(16_w,33)-aCMA-ES (mu_w=9.4,w_1=19%) in dimension 12 (seed=803921, Fri Sep 26 10:13:50 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     33 1.731396165052827e+06 1.0e+00 1.05e+00  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     66 1.546139301741188e+06 1.3e+00 1.10e+00  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     99 1.690994719575509e+06 1.5e+00 1.16e+00  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   3300 1.398244833358657e+06 2.1e+02 4.27e-02  5e-04  8e-02 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   6600 1.398216904962991e+06 1.1e+03 1.47e-03  2e-06  2e-03 0:1.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   9900 1.398216904896172e+06 7.7e+02 2.00e-06  7e-10  5e-07 0:2.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  303   9999 1.398216904896172e+06 7.4e+02 1.83e-06  7e-10  4e-07 0:2.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on flat fitness: please (re)consider how to compute the fitness more elaborate=None\n",
        "termination on tolfun=1e-11\n",
        "termination on tolfunhist=1e-12\n",
        "final/bestever f-value = 1.398217e+06 1.398217e+06\n",
        "incumbent solution: [ 1.  1.  1.  1.  1.  1.  1.  1. ...]\n",
        "std deviations: [  4.45913746e-07   2.18206869e-07   1.13143996e-07   6.92526341e-08\n",
        "   3.08261927e-08   1.81542940e-08   1.00156125e-08   6.25777792e-09 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 63,
       "text": [
        "<cma.CMAEvolutionStrategy at 0x10e2d2450>"
       ]
      }
     ],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "res=cma.CMAEvolutionStrategy(ones(12), 1).optimize(f).result_pretty();\n",
      "cma.plot()  # caveat: assumes default logger name"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=796687, Sat Aug  9 22:17:50 2014)\n",
        "Iterat #Fevals   function value   axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1      11 1.550287065007986e+05 1.0e+00 9.89e-01  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2      22 1.008692477089747e+05 1.2e+00 9.98e-01  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3      33 7.025772056024326e+05 1.2e+00 1.06e+00  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100    1100 7.945946964317943e+02 1.2e+01 1.33e-01  2e-02  2e-01 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200    2200 3.769787024119492e+01 8.9e+01 2.73e-02  1e-03  6e-02 0:0.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300    3300 1.918610996629579e+00 4.1e+02 1.88e-02  3e-04  9e-02 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400    4400 6.327841773095008e-02 6.9e+02 1.12e-02  7e-05  4e-02 0:1.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500    5500 6.237018243272152e-08 1.0e+03 2.19e-05  7e-08  6e-05 0:1.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  597    6567 2.300617967608463e-14 1.1e+03 2.91e-08  4e-11  4e-08 0:1.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11\n",
        "final/bestever f-value = 2.300618e-14 1.853089e-14\n",
        "mean solution: [  1.26964983e-08   2.37614098e-08  -8.02974200e-09  -5.18487290e-09\n",
        "  -4.43153592e-09  -4.63756473e-09  -1.39852261e-10   2.92550505e-10 ...]\n",
        "std deviations: [  4.48479779e-08   2.39714183e-08   1.23662349e-08   6.45060338e-09\n",
        "   3.79159306e-09   1.92898640e-09   1.05001420e-09   5.37441495e-10 ...]\n"
       ]
      }
     ],
     "prompt_number": 177
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "res=cma.fmin(cma.fcts.elli, ones(12), 1)\n",
      "cma.plot(); gcf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=902626, Mon Aug 11 23:51:04 2014)\n",
        "Iterat #Fevals   function value   axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     11 1.296845503424673e+05 1.0e+00 9.50e-01  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     22 1.150969988503794e+05 1.1e+00 9.14e-01  9e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     33 5.948183136904862e+04 1.2e+00 9.13e-01  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1100 1.344315281022164e+03 1.5e+01 1.27e-01  2e-02  2e-01 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2200 4.532005431546528e+01 1.1e+02 5.40e-02  2e-03  1e-01 0:0.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3300 9.430538686593284e+00 2.5e+02 2.35e-02  3e-04  7e-02 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4400 4.208473624986115e-02 7.9e+02 1.22e-02  8e-05  6e-02 0:1.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5500 2.416001917636452e-08 9.8e+02 1.63e-05  5e-08  5e-05 0:1.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   6600 5.060455573958163e-14 9.1e+02 4.32e-08  8e-11  7e-08 0:1.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  605   6655 1.947054999411759e-14 9.4e+02 3.24e-08  6e-11  5e-08 0:1.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Mon Aug 11 23:51:06 2014)\n",
        "final/bestever f-value = 9.445587e-15 9.445587e-15\n",
        "incumbent solution: [  2.75315056e-10  -1.18132073e-09   5.28838745e-09  -3.16256059e-09\n",
        "   1.32683448e-09   1.61811447e-09  -4.98339119e-10  -2.86807271e-10 ...]\n",
        "std deviations: [  5.01770913e-08   2.37995239e-08   1.40423906e-08   8.36968745e-09\n",
        "   4.11561705e-09   2.03032302e-09   1.13235437e-09   6.63638547e-10 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "png": 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pUaOGFEEMMhbofvPNN2zbto3FixdTpkwZbGxs6NChA5ARZWrgwIF8//33bN26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\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jlOkZh27dSGShb1/Zd5qvbnwCAYku/fijiA6lrEzS2ZaWxJtfsEA+11ic8UmCXbtoHllZ\nlGVau5ZU4/h8moOBQd2MsaCA+jo9fEgUncBACtI3akTP3NOn1asJJieTyIa4aOgvYHnYUYZhEP5N\nOFKOpoCrw4XTfadP6mWEf7ckJgYrysgqr1FXx0/iFBoLBMBff5HhLS6mKMk//5DHKkMERwSjj38f\npOWnwVrfGsdGHIO9sX2t98cwJKQRGkp1jKNGUSDMVIxSHEmek0OHDsHb2xtZFWo3tLS08P3336Nf\nv35wdXWtdS1ETWNhGD4SEjbj1at5AAAWSwUMUwiADQODwWjSZCp0dT1kkgGRxsYxfAavF71G/LpP\nG07q9NSB7XHbT4QrZDWeDyUluJKejuuZmbjz4QNe5OZiookJjJWVsS4uDkVlnZz8fKI3ALiWmIie\nNQg6REyKQNJfScg0zcSg54PA1RKz8Z2c0NDtqAL1C4UjUw3mzKFMiYoK1Qt07Vr13xYXU6HnmjUi\nKoyZGS0Au3WjhVZ1EDpM27ZRZgGg/gTBwagV7UtcvHxJ7/6EBJJZnjOHJJ1l1fjxzh2qJ0lOps9G\nRkTBE8o9ywNv3lBW7cIFotkJoalJDqKODi0cRowA7OzkNw4hiotpsfLHH59KbqurA15elD0aPFim\nQWWZIzqaBAwqOgrm5nTvjxpVN3S+shAIqLC6USPRMxYYSIp79+9T6xEdHXK4EhMpmyPJ2qmhv4Dl\nZUeL04sR4hGCnCc50OyoCacAJ7C5ldOKInJz4RocjIwSKhjvqaODtRYWcBZHZeL5c0qDP3lCnMf5\n84GFC2uvcFLZIZKfo8/BPh+ba9789ia6mXer4VdVo2yAByBbtHIl2SdZC6XcvXsXo0ePRmwlPXha\ntmyJf/75B05OTrI7YAUUF6eBy9UBn5+PyMiJSEkRcY9VVS1gabkOhoZyfBmIieRjyYiaFoWS9JJy\n29XbqqPpD01hNNIIXA35OgMChgG71DilFRfjWHIyfBMTocflwhLAgVJxC2FDzKqQcioFz796DrAA\nx1uO0OmiU+Xf1hUauh1VoH6hcGSqQUkJLcJPnyblprNn6QVUHWJiSJ75wgWR5K2xMTlC9mIG8qKj\naVEbHk5O1PDhVGfRuzfRwmWN4GBg8mRREaqbGxXPC4tVpcWbNxTNP36cPrNYtKgfNowWmfJCcTHV\nHD17RsyTirLJSkq05lmypG7oXh8+EFVLVRWIjyfKVBn1VHA4JNe6ebOoMP9zg0BANMqff/60V4aq\nKo27d2+i9HG5FH2Wp4KdvNHQX8DytKMFCQUIbB0IQa4Auh66aHuiLTjqlT9ofIbBT69eYWNCAgCq\nHThua4uB4vBR8/MpM7NvH30WdmidMUNmBjPuQxwGHRmEZ8nEa/Tp5oOl3ZfWen+JifSOWL2aVA+F\nsLKiHl5eXmQPSkqknwLDMIiPj4eWlhYuXLiAEydO4HipMVZSUsKYMWPg5uaGAQMGwESOMosMwyAz\n8yaSk48gKelgaYYGMDIaBQODITAwGAI2u5506wHkRech9tdYqFqogqXEQszimHLfq7ZQhZGXEYxG\nGkHDQaNOx1ZWtaw6R6bofREetX2E4tRiNPupGSzXyDHdLwEauh1VoH6hcGRqQH4+dXG+fVtU8Lxw\nYc0vl4wMWryfOUOqYjo6VPQubvuDyEhqDFlKIQdAUfu9e6mZoawhEFBGaNIkog9xucCff1KwU1bI\nzaX9C/ubACR1vXs3OXvyRFoaNQzdsQMICSHHtFQFFs7OgKsrXV9nZ3Im6mLxzedTS4wLF0jpTNjb\nRVeXMh8uLkRprMuaGnERFkY9ddq1Iwrkhg2VNyfV1iYnfO1a2WX56hIN/QUsbzuafCwZEd9GQJAv\ngGoLVdiesIWmY9U9Wq5nZOD7qChE5ueDBWCZuTkWNW/+MVJdJRiGjO1PP4kaTXl4kMQhjyeThygq\nLQpD/h6CF6kvAACt9FvhyLAjaGdS+/OWnEwCMRcu0LtGiD59KFNz+DBljvfulW1vqvj4eIwbNw43\ny6RX1dXVsWDBAsydOxeNaqIQSImioveIj9+A+PiNAGgJYmw8Bq1b75eLIEBt8OHeByTtRmYoIAAA\nIABJREFUT0LGlQwUvCko953RaCNYrLKAiqkKWGwZ85UrgTiODMMwCOOFIe1sGtQd1NH+YXuwVT6P\nc9nQ7agC9YvP4y7/jNGoEWVihFLJS5ZQ0XBBQfW/09UFWrZcixcvqMA4M5Ocgl69KBpfE1q1ooX2\nP/9QdkZLixbg7u7kTNVU8CwuhDKPbDZlfq5dAzp1okjg+PEUUd+9+1PlqNpAXZ2cowkTiMYGkDCA\nuTk5h2Vf5BXHJy309clBuXKFFg9RUTQWFRXqseLrS47m2LFUs3LggHj7lWZ8HA4p5B07RjUfT57Q\n+c7IANatowWMiwuNt2zNjySQ1fmriLZtSR1OS4sc9qQkOqd+fjQHFRVyDD98ILqkvT2piW3ZQjXa\nZfvIyWuMCtQ/jEYYweGKA1TMVFDwpgDBrsHIuP6pepMQj3bvRrCzM74xMgIDYHFMDCwePMCq2FgI\nqjNCLBY5LKGhpJ4CUBp86FC6UStRjBIHZe9Na31rhHuHY7LTZABAZFok2u9uj3NR56r6eY0wMgL+\n/Zeek/fvgWXL6Nm5coWcl6Iicmb69gUmTFiLnJya9ykOmjVrhmvXrmHTpk1QVVUFQIvlxYsXw8bG\nBk+ePKn299I+s8rKxrC0XA8npwBoaXUCALx/fwi3bnEQFjYc+fmva9iD7MZSFbRdtdFqVyu4PHNB\n01lNodNTB0rG5E0mH07Gg+YPcItzCzfZNxE+KhwFCQVyHU9NePfnO6SdTQNLmYU2h9qArcJW2FYF\n/hNQODJiQFOTIue7d1MNwMmTVHeXnV397/Ly8qCrS3z9adNo2/XrVDszfz5lKKqDigotZk+dogh4\nr16kCubjQwvD//0PUr/Y8vLyyn12dia6k7MzfQ4JoSLqESOo3kBaaGhQjW5iIknruriQU7hmDWVB\nDAwACwtyKoqLPx2frMBmU3YoKIhoHE5O1LBOV5cW5d9+S3S7ypyrspDl+Nq1I6fKzw/w9KRtwcGU\nrdLWJqbMjRsiyqI4kNf5qwg2m2gxI0fSmAsK6NwdPEg1Xq9fE51w1ixqcmllRRQ1hqm7MSpQP9B2\n04bzU2dodtSEIF+AsK/CkPey8muel5eHRhwOjtjY4K9WrdCIzUZsYSF+fvMGrQIDEVXTvaKkROnB\noCCRFn5AAOm/CxtbSYDK7s1dnrtw0uskjNSNAAC8v3mYeX4m8otrMBY1DNvIiBQrAwKI1ivM+nO5\n9Nzv25cHAwMKyowdSz6bNGCz2ZgzZw7S0tJQVFSEI0eOwMTEBDExMXB2dsby5csRLVQpqQBZPbPa\n2q5o1+4+rKy2fdyWmvovHj60RFjYVygoqPmlI2/7wVHnwOp3Kzhec4TrO1c4XHWAskmZYkAGSPZL\nxmPHx8h/nV8v9iwvOg/Rc+haWay2gEZbihQqbKsC/wUoqGUS4sYNypBkZ9Ni88QJ8TnM585RNkdo\nW4yMyDkaPFi83xcV0cLw4EGiSQEUEZ87V/Zd5LOzKTuzciUtrgGa56hRpFLVpo1sjsMw1Ij0hx8+\nDZqyWLTwXbCAFvOyVhyrDDk5tMBevpzGZm9PUdJBg+qe4nXrFgWU09PLb2/cmJTZtm6lbI2R0edJ\nPxMiI4OC43fvUjYmO1uU0VyyhBZv8qj9kgUaOiWiLu1oSXYJHrV9hMK4Qmh21ES7e+1qpOV8KCnB\nwaQkzI6OhrAk62G7duggjhAAQFGkiRNJ6xig1O+qVbWfRBkU84sxyX8SDoYeBACoKamhj0UfrO+z\nHlb6VlLtWyCgQI6KCtGMN22iWs3378v/3axZVFMnK9v47t079O/fHyEhIQDI2Vm1ahXmzJkDZTkr\neaSnX0Ve3gukpPyLDx/oBcdiKUNffyCKipKhp9cHzZsv/myoZ4VvC/HmlzfIf5mPouQi5EflQ6O9\nBtqeagtVU1WZHqs6apmgRICnXZ8i634WdHrowOGqg1h0t/Hjx8PPz6/cdb169So6duwo07EDDd+O\nKlC/+DwsghSQtiO1pJ1qAwPXQigRf+YMMG2a+B3Ye/TIQ69ePKxYEQBDQ1qEDhkCTJ0qXidnZWWg\nWbPL0NDgYflyWtBmZZFiVIsW3li9Wvx51NTJWVOTxjZu3BaMHDkfvXoR3ezAAcDGJg/Kyjz06xfw\nUXkHEL8jNSC6HiwWRRfj48nR8/T0hofHHnA45Ej8/jtgYhIEVVUeBg5M/dgZXtx5CFHZ9aisk7OG\nBtC6tR/69JkAQ0OKeg4ZQgIIffrI776qbB4bN/Jw4UIEHj4UnhtAVXULkpLmY+dOymA1aQI0bZqH\nDh1q3yFc3vP49lseHBwi4OtL93xeHtCnzxYA87FsGfVMCg0FHjzIg50dD5cv1/88/msdqevCjnI1\nuXC85Yj9Svux++FuxPwaA4ZPcbSqntsDO3Yg9vffcd7eHqqlTR2nhobCU9wO7J06wcvGBqd696bP\nq1cD/v4yuU9WLFsB2yhbXBx9EWbaZsgrzsPph6fRxr0Nlv27DMV8ER9UXPsjnMekSRM+9vhs1YrU\nL7t29cIvv5zChAlEV2axAF/fy2jShPdJEKi2z62JiQkeP34MHx8faGhoQCAQYMGCBWjfvj0CAwMl\nnockz+348b4wNZ0JJ6ebsLbeCVVVc/z2WxH27z+JrKy7iInxwYMHFggI+LvW7zUhZDGPcXPGIYIX\nAac7TrA9bguOFgc3ntxAb8veeL3wNYLcghDcLRgFsQVS29H4KvjoW7ZswfQe05F1PwscLQ5a72uN\n/IJ8sebBYrHg7e2NAQMG4ODBg8jOzv7oxCjsqAJfEhQZmVpi1y4RXezQIaLLSNI8+c0bqks9dozq\ncB48EF/VTIiSEopwr1hBUbuWLYmi1b+/fIrVHz2iDM3p06JtqqrUuXrUKNkeKzeXHEUfH5pbWZib\nU5ZkzBj5ZmmSkijauWOHqCv30KFU8yFPSezqkJtL12DTpk9V2Dw9yaktVen8rMEwJDL1ww+fUjQ7\ndSJWkJeXVA3bZYKGHkmsDzsavzEer+aR0obRKCO0OdAGLE7ND/L7oiK0evgQH/h8fGtsjBlNm4on\n0SzEzJmUxgQofb1kCfFLZVBFX8QvwvZH27H5wWbEfiA6FK8VD3t4e2CgJkWTpWqwYQNRlAGazpkz\nsn32GYbB5s2bsXTpUmSXPqSLFi3CihUrZNL/RZzjp6aeQEbGdRQWxiEt7ezH77hcPSgpGaB1673Q\n1naV+1jEQV50HsJHhCPnaXm+N0uFBdPZpmixrAXYyrWLHVeVkcl+ko2gTkFgShi0PtgajceI/2Ia\nP348dHV18dtvv9VqTJKgodtRBeoXX3xGpr4wdaqIgj1mDPUjqbjgrhihKIsWLcgJ6duXagk6daJ9\nCpW0xAGXS8e+dIkW1tHRVLCvrk5R7osXa95HdWOsCBcXqtd5/ZoaT9rbE0Vo9GiiXl24IP7Ya4K6\nOtVb3LmTiuxsauC5ciU1kYyJIfW3YcOoSF4WQgSVoXFjcgzDw0XqbSdOUI2TkNonyfmTBdTViRkT\nF0eUv4wMum84HFrIODuTQ9u9O4lU1PX4xAWLRaIPkZGAq2v5MT54QOfb2pruKXldXwXqB6ZzTGGx\n3gIsLgvJR6i2IC+a+LbV3a/Gysr43coKLAD737+HS1AQZkRFgRH3Btm4kSJOAPDuHRnwNm2Iq1tF\nLYG4z48yRxmzO81G1MworOy5EsocZfhH+sPsNzOcjTor/hirQcWxzJ1LgTBTU5qOl1fNIjSSgMVi\nYc6cOYiIiED37t0BAKtWrULXrl1xpGyDLjmBxWLB0HAYrK23oW1bf1haboCWlhsAoKQkHfn5UQgJ\n6Y1Hj7yRkyMj9RspoNZSDU73naA2TQ0sJRaUDJTA0eKAKWQQvzYeof1Dkf+m9nVUFcHP5+PFmBdg\nShgYjjCE8ehPpT+ru39ZLBYOHDgAfX19tG3bFps2bZLJfaqAAnUNhSMjBTZupIJ7HR1a7HbqJGpm\nCQATJ06s9vdsNinSdO5Mzszu3VTwXV1n8srQvDmpmE2fLpK4jYykzEzv3pRRqNjzQ9wxVoYWLWjf\nwcGiTMy5c+TMWFpSC4faqmxVxKRJE6GhQedo0SLqfzdjBn138iSdc2FmTF5o2pSyB/v30+fiYjqv\nkycDQ4ZIfv5kASMjir7q6JD88f37VH/FZpMzfOsWZWhatZqIRYtIKrksPpf3lYkJoK8/EY8ekchB\nUBCVMZiYkLM2YABga0uNTSs0KVfgCwWLzYLZPDO08aNCu9ywXEROjgTDZ2q0R982boxzdnbw0NUF\nC8C2t29xpCy/tTooK5PBvXyZ6maMjOhhGTeObrjFiylKUgaS2kdljjIWdVmEC6MvoKVeS+SX5MPT\nzxMmG01wPPy4RPuqiIpjYbEocBUcTJTYV68ou29mRln6qmy+pGjSpAmuX7+On376CQAQEBCA0aNH\nY968eXW28GWxWGjWbC7atQuAo+NtmJv/Ci5XHwJBPmbP3o7Hj+0RFjYMRUXvkZi4DeHh3yA3N7xO\nxlYWHFUOViSugPsHd7gmu8ItzY3ucxaQeT0TDy0fImx4GHKe5XykVdYWrxe8Rl5EHpRNlGG9w7rS\nLFl19++sWbMQFRWF1NRU7NmzB7///jt+//13qcakgAL1AQW1TAZ4/54oR/fu0eeQEMpWBAUFiTU2\nhqE+NQsX0oJUQ4OyNQMHSj4WPh94+pSi9GUVNLlcinAfPUrSuUKIO8bqxn7nDjkXZSWhNTSotmTm\nTFpwM0ztCrorGx/DULZpxw7KQgDAnDkkmmBrS/U98qIkJSWRE/f06ccRYsKEdti69fNo/JiaSkX1\nmzbRPQUEAWj3USZ5wQIqED55khyzPn3qecCo/Brn55NjLnQeAbp/Wremf717U+8fGxv5Ch00dEpE\nfdvR90fe48VoKsQ3+c4EWROy4NLZRazfzouO/thAc6SREXZaW0NbEiOTk0Pc0cWLRdt0dMgIt24N\nQDr7mFWYhaFHh+Lam2sft9kb26OJZhO8Sn+F79p9h/lu86vZQ3lUN5azZ0kuPy1NtK1rV3qPyFIE\n5tGjR5g4cSLCwsIAAOPGjYOjoyPCw8PRq1cvODg4wNjYGJqamlCSZeObSsAwAqSlncO1a2tgbPwA\nQHk5RyUlAzg63oS6uq1cx1ERlV2n9EvpePPLG2Q/FvFoWcosaLpoQn+QPkwmm0DZoGoxhYrUssJ7\nhQj1INk6+4v20OurJ/ZYqsLOnTuxf/9+3L9/X6y/lwQN3Y4qUL9QODIyQkEBScomJJDC1qZN1MxQ\nkr5iBQXUw+3OHfo8YwbVgujq1m5Mjx7RQnDvXhFzokkTencPGSLbBmsMQ4HOBQvKLvJF0NGheZV1\nomSB6dMpI1EW6urkQPn4yMehyc+nDI2/v4i+5+FB2bSAAFpwOziQ4/j+PX3n5ib7cVQHgYCkvo8d\nIxpg6XqvHDQ0SBJ52DDZ3guyRGoqPUtbt1Yud25lRQ5tr17yOX5DfwF/DnY0YUsComeRdKxub13Y\nnbUTq5FfoUCAWS9fYve7dwCANmpq2NOqFTpra0s2gKdPKa378CF91tGhKFK3bsR/lFJSLz0/HXMv\nz8X+p/vBoPzr1refL2Z2nCnV/oV4+5Zs8JMnwPbtZAOsrYmCqll1D1KJUVRUhJEjR+LkyZNV/o2h\noSHu3buHli1byu7A1SAr6zGePx+GwsK4cts5HE1oajrD2Hg0jI3Hgc2uP0PHMAw+3P2AuNVxSL+Y\nXs7v4upy0da/LbTdtAEBPqkZK+vIZMRlILxTOIreFqGJdxNYb5WNXdqxYwcOHDigcGQU+OKgcGRk\niFu3qDZBCHt7yhiYmYm/j+JiWpQJnRkTEyou/+qr2o8rN5fGNn68qPu6nh71a1m4kLJJskReHtU2\nrFxJtAchlJSIIjR0qGTCCNWBYSi7sHz5pw6Upydw/DgxSuQBgYAcxWnTSBq7OgwaRE03W7SQz1iq\nA58P/PabqDC4MgwcCMybV/7+/ZzAMCSQ8eQJPRt371IDTmEfJRaL6tRatiTxCR0d2Ry3ob+APxc7\nmnY+Dc+HP4cgXwBtd23YX7EHR7XmVBvDMLiUno4JkZFIKn0IPXR1sdTcHK6SOjTv3tGDUNZoOTtT\nNMDcXLJ9VYLUvFRM8p8E/0j/ctvdzdyxf8h+WOhaSH0MIUJDiZaZmEjvnylTqMbR0JA+h4XR+6m2\nQTI+n4+hQ4fC398fBgYGyMrKgpGREZKTk1FUxhjOmTMHCxYsgJGRkYxmVjUEgiIUFr4Fl0sCECEh\nvZGTI7qWWlpucHS8DjZbvjLS4oCfz0fO0xy83fEWGdczUJQoOmdKhkpo+XtLGH8jqnkp68g8Gv4I\nOcdz0Mi6EZyDncFRq/45ycy8BS0tN7DZ5R3yf/75B/369YOmpiaePHmCESNGYMaMGZgrbCgrQzR0\nO6pA/ULhyMgYCQmUCRAqFDZtSpQzSZyZ5GRSRdu+nahMANCzJ3V7l0aV5v17imzv3o1yssn79xNN\nXNZ4945qiJSUqHu1MCvUvTtlMmSdLXn9mrJQiYm0aBcIaEE7dSqpeUmSHZMEP/5IvWfYbOKsFxXR\n3DkcEd0QoMDumjV0TuqiJ05FpKVRO43Hj0lIYd06uh+E9UwsFvUM7Nmz7sdWG2RlkRNZRjH4I8zN\nqRja21u6c93QX8Cfkx1Nv5KO5yOeg/+BD7NFZrBYKf7CPq6gAFMiI3GpjA6xpaoq9rZujS6SeLXF\nxfRQXLhA3nJeHhXiBQTIhMPIF/Dx6O0j2BvbY8HVBdgSuAUAwGVzsX/Ifoyyk5384/37FMwpSzcr\nCzabtA+mTaOMsaTPCcMwKCoqgkoZQ15cXIzAwEB89913eFHau8fU1BQPHjxA06ZNazuVWkEgKEJm\n5i1kZFxFQsJmMEwRlJSM0KLFSjRpMrlOx1IdijOL8fyr58i8mVluO1efC8u1ljCZZFLOkTmP82jE\naYR299tBy6V61b7MzAA8fdoN2tqusLe/BA5HxH/u1q0bQkNDUVJSgqZNm2Ly5MmYO3euXBTpGrod\nVaB+oSj2lzFMTYE//6S+KCYme5CYSC8LSYrfhR2eQ0Ioi8LlEk3I2ZloU926UZZFUhgbU+YiLo5Y\nFH37AsAezJ1Lx5I1TExokXngAL1UhXS2mzfp/xVV3ipDRc366mBhQco9//sfHdfQEMjMBNaupf8b\nGtI57NyZ/t+3L41LGuzZswerV9P5zM6mGqSTJ0l56+5dyiQ8fw44OZFc9rx5NPeKfR/khbLnT18f\ncHcHZs8mRbZNm6jZ5t9/U80Jw1A20MyMaqIFgmp2LKcxSgItLXLCV6ygBdu8eSKxi5gYohd6eFQp\nSKXAZwa9Pnp4/A11341bFYeMm+I/JGaqqrjo4IDnLi4YpK8PDoBXBQUY9OwZNsfHo0Tcm1lJiQru\nLl8Gnj3DHmVlepg1NIg3K2VxO4fNQSfTTlBTUoNvf18ETQmCupI6SgQlGH1iNL4+9jUyCzIr/a2k\nz0nnzhTcWbiQPjdqJKKQstn0fB8+DHTpQiqBkryj9uzZAxaLVc6JAQAlJSW4ubkhLCwMx44dg46O\nDhISEuDm5oYHDx4gPDwcxbJSgikzlsrAZitDT68PLC3XwsbmKAAOiouTERX1HZ49G4zs7CC5iBVI\nep2UdJTgcNUBdhfs4HjTEcZjKRNTklaCyMmRiJgY8YkwgPkS8xqdmOLiTKxbNxiAAKqqLco5MQBw\n69YtZGRkIDs7GxEREZg3b16dyGoroICs8dk5Mnw+HzNmzICnpyduCTVuv0CYmgK9egVBS4ui8tOn\nS64iY2RE9S1hYbTQBGhRdvs2KVQJF8qSQkUF6NCBaG/6+kFITQUcHWmBm1n5O1Rq2NvTAn/bNvp8\n8SLV07q70xyrmkdQUFCtjvf115QVOXECaNaMHL/UVKImPXhA/798mQrGx44FXr6s3byCgoLA4dD5\nrKrY38ZGxFtXVqbaGjs7Wi/5+FCh7tOn8lESq+n8aWiQ83f8OM0BICd8zBiiwa1YQTVB8kRtrzFA\nC7Off6Zzun49LdzWrqVCZ2VlyjCZm5PC3Pr1shvz544v1Y5Gs6Nh9A3RkMKGhCH7abZEi00bdXWc\nsbNDmrs7bNTUkMXnY86rVzC4exeZki6gLSwQ5OZGzbIKCujGcnYWaa/LAE4mTrg45iIsdS0BAMfC\nj8Fmmw2mnpmKnY93IrtQVBhWm+dES4vk2pOTiVYcGwtcuULP9M2bouzrwYOUKT94UDw7VNNY2Gw2\nhg8fjsePH6N58+aIjY1F586dYWtrCz09PdjZ2eHu3bsSz6c2YwEAQ8Mh6NTpNYyMRgMA0tL88eRJ\nezx7NghFRWKq3slwPBXB4rCg308fOt100Hp/a7iEu8BoND0HSXuTEGAoam6p2V4TZouqp3gwDIOo\nqKkID0+HqqoFrKy2STwmBRT4UvBZUsvS09Nx5swZmJubo1u3bpX+zedEiagOJ04AI0ZQ9KtxY+Iq\nL1xI70ZJwDCUwfDzIwEAIdzdSYVqxIjajS8hgWpWHj2izzo6tP/p06Wuca0UJSXUXNvPj2hOQjg7\nUx1Jhw5Av36ypV4VFVHGRChNDBDlr2wmisul8/jjj5S5kheCguhavX796Xc8HmUWeveWCSVfYggE\n5HAtXgxcu0bXCgB69KCsTR3Q3GWKe/dIlU2YkeFyyWG0lUDE6EumRHypdrQkuwRPuz9FThAVQDX5\nvgmst0l+7lOLirAsNhZbEhMBAA7q6njQrh1UJaWIFRYSD9PHhx4SFouUWFasIE9BBigsKYTvQ19s\nf7wdMZkxH7d3aNoB18Zdg5qSGtgs+cQd//6bAhfCQFvz5hTcGT6cREukxatXrzBx4kQEBARAUCEz\n1r17d1haWmLt2rXQ19eX/mA1gJTOziMhYRMyM0W9EhwcrkNXt4fcjy8p3u17h8gJkchHPgZgAAAg\nOTgZho6G1f/u3V5ERk4Ei8WFk9NdaGl1qIvhVokv2Y4q8Pnjs8vIAICeXuVSgl8ihg4lupGSEtW7\nLFtG70BJo+8sFmUwfv2V6Ns9e1LEOSCAsg+VKYWJA1NTIDCQ9mllRRmZWbNo3LXNUlQHLpcWys+e\nURZA2Ifm8WNaJwwYQNH00rWHTKCsTPQJNzeqBRo3jihU166J1iIlJUS1atyYFr8rVwKnT1NWR5Zo\n146u1R9/EBVq6FDKGAGUVfjuOypYd3amOqvoaNkevzqw2VQQfPEi1Z/s3k0Zmxs3yLHasKHu6Gay\ngKsrnVNjYypvWLCA6If/FXypdpSryYXNURuomBFt6e32t3jv917i/RgoK8PXygrLS6MCIbm52FyZ\nfF9NUFEhoxURQaorDANs2UIPs4y6AKtwVTDfbT5CpoVgWvtpUFcijmRgYiA0V2tCY5UGTkWcksmx\nKmLkSKK/zpxJ76nYWLKLjo5E1dy5k+jB69dThlPSd5elpSVu3bqFwsJCpKam4urVq3BycgIA3Lx5\nE3v27IGNjQ3mzJmDv//+G4WFhXKYJYHFYsPAYBAcHa/D2TkUwiVQWNhgZGRcl9txawuT8Saw3GgJ\nDXuNj9vUrKrX+c/Li8LLl6SEZ26+vN6dGAUUkDc+y4wMAOzfv/+LiyRWhxs3yhdRjx1LEr7SqHfF\nxtLCMyWF6lFv35ZORrewkBbzP/8selm5uxM1oUuX2u+3JgQFUebKz698pkJXl6R1vbzkd2yAMjZj\nx5IzVTFTwuXSd+7uVOtUUECKQFZWJGUtKwQG0lwvXhQJPJTFvHmUyZJHlqymcXl707kBqBH6+fP1\nkzGqD3zpkcQv2Y4yfAaRkyORtC8J4ABtDrWB8cjapUsPJSVhbEQE1Nls3HJyQvva6hEzDK3q//c/\nKjDjcIgbO3Zs7fZXDR4mPESfg32QXUT0Mg1lDQRPDUZLPflJGqekEOX44MGqGzP36UO2ytKy9sdh\nGAYRERHYs2cPNm7cWO47DQ0NzJw5E8OHD5f7PVlQEI+goI4oKnoHFksFZmbzoaPTC2y2CtTVbcDl\nipTviovTIBAUQUVFho15xETFPjLqwmLAChAIihAU1Bk5OUHQ0ekBB4crYLHk2GhLTHzpdlSBzxsy\ny8icPHkSU6dOhYeHBxaXbTAGoKSkBL///jt4PB4GDx4MX19f8Evz2P/++y/mzJmDnRWbgTQw9OhB\n78BVq+jzwYNUkyJNXUTz5kQJ09amuo9u3apWqBEHKipEe7t5k+hdHA5lfLp2BeTZ8LddO4oAvnpF\ndCChjc7IIOfh0CH5HRugjM3Ro3T8Z89I8WzgQHpRl5TQOmXSJKqB0dMjLnmLFpQxkVVdS4cOdJy3\nb4HwcHIm7e1F32/YQE5qixYk41xHDbXRoQM5M6tX0+cXL8iZmTyZaHgzZlCWsGwz1IwMuo6yzKr9\nV6CwoyKwOCxYbbOCrocuwAeipkQh+2klzYTEwChjY3TT1kauQAD34GBsio+vXaE3i0WV8TExxAPl\n8ynF6+0tWbW8GOho2hHRs6JxYMgB6DXSQ05RDjz9PPE6oxJeqoxgaAhMnEiBt7Nn6flv0oRsUceO\nNP0rVyhrvHgxBXZqAxaLhTZt2mDDhg1ITEzErl27MHXqVGhqaiInJwerV69G+/bt8eOPPyJHqLEu\nB6iqNkOHDlFQV7cHwxQiNnYFQkJ6IDjYFQEBOkhI8EVhYSKCglxx964B7t9vgps3WXj40Apv3/4J\nhvm8UtRv3vyMnJwgcLl6aNPm4GfhxCiggLwhM0fGwMAA48aNw6BBgz757uDBg3j+/Dn27duHvXv3\n4tmzZzh8+DAAYNiwYfjtt98wbdq0cr+Rh5pIXYPH432ybeFCCugBxE6YNUu6YzRvTpkMLS1S4Orf\nnwKF0oyxa1diTMTFkeoTQE6Xl5d0jpI46NyZxh8dTS9PhuFh7Fjgp5+ADx/ke2yAGnauW0cv8Zcv\nycH5+muRcwWQg1dURIt5DQ0eNmyonYpcZWCxyFFYsYLqd54+peshREwM8MMPpAhe/brRAAAgAElE\nQVS3YAFdo+pQ2fWtzZgWLKA+Li4utHjZs4eoJtu2ESXQ3p7u5WvXyNlzc6OsDY8HDB5MGbeqFj2y\nGGNDwX/djla8FzhqHNids4N6W3Xws/kI6hSE7GDJnRk2iwV/Ozt019FBgUCAua9eoX9oKIpq4EpW\neW9qatJNPWYMfd6+nbhZMj7fRupGGOswFiHTQqB0VAkRqRFw2OmA7Y+2y/Q4lWHgQKotTEwkW/Tg\nAdFtCTysWEEOTUyMdMdp0qQJpkyZgp07d+L69etwdHT8+N369ethYWGBm6XpIYZhPqmzkdZ+cLka\naN/+EZo3X/rJd9HRP+D+fVNkZZWXt8zPj0ZU1HcIDu6K1NTTYBiRkk992bP09MuIj98AAGjd+i+o\nqDRV2FYF/hOQmSPTpUsXuLm5QauS4seLFy9izJgx0NPTg56eHsaMGYPz589XuS8fHx9cuXIFBw4c\nwO7du2U1xDrHjBkzKt0+dizVHwDUsmDwYOkkYvv3pyaBenqUoWnZkjIp0owRoEjc+fNUt8FiAf/8\nQ5Sq7dvlmxFQVqZsSHAw0KkTjW/dOpIF9vev4ccyBItFTszRo5RliIigaGRBAdXQqKkBeXkzMH8+\niQdcuSL7MTg4kEhSaKhIjQugnkBr15Ij27EjSUn36UPXqCyqu76SwtycnOWdOyn716sXOVVubvT9\nli0idT2AsllnztA1GzaMxrpjx6dOnyzH+KXjv25HK7sX2Fw2HG87opFVIzCFDEJ6hiDnmeRRei0u\nF1cdHD7WzFzKyID3y5fVOnvV3ptcLqXWhenqXbso9X7mDPF0hWoZMoCplim2+myFazNX5BTlwPu8\nN7zPeeNNxhu8THsJvkBCScxawtOT6uS8vGaAwyEnZ8gQysr27k2JKWmCXc7OzggODkZxcTEWLlyI\nxo0bIyUlBT169ACLxQKbzYa2tnY5xTNZ2A82WxktWvjA3f0DunTJQbdufLRosRJstrAehYU2bQ6h\nXbtHaNlyM/T0+gNgIyvrLsLChuD+fTOkpvqDYZh6sWdFRcl48YKawTVpMh0GBoMBKGyrAv8NyL3Y\nPzs7GykpKWjZUsTrbdmyJZKTk5FXxerdx8cHhw8fxp49ezBlypRq9z9gwADweLxy/zp37oxTp8oX\nRl6+fLnS6IS3t/cnuu9BQUHg8XhITU0tt33p0qVYu3ZtuW1xcXHg8XiIiIgot33Lli24UmFlm5eX\nBx6Ph4CAAHz3HaXm2WzA398PLVtOKNekEgC8vLzEnseuXd7w9t6DJk1ElKytW4MwaFD18/AoTblU\nNY/t27dAW3s+AgMpU5CRAXh756FRIx5mzAgox6bw8/PDhAkTPhmbJPMoez3YbODOHQ94egaBw+Eh\nKysVgwcDo0dTfZGr61J8881aBAeLHKvqrsf8Cq3ty16PsqhsHkpKwJIlXsjJOQUuF1i0iCRN58wB\nVFV5+PCBGCeBgaQE99133ti2TXb3lZ0dUbmGDduCqVPn49AhUeF6YGAeLl/m4erVAHh50fmJjwd8\nff1w5Min3SJrez0Ayka5uARBS4uHv/9OxebNJGP966+Ajs5SAGtLx0SFwVOnxkFfnwctrQgkJwPf\nf0+1T3Z2WzBjBl0P4T0oyfWQdh7Ap9fDz88PPB4PrVq1go2NDXg8HmbPnv3JvuoD/xU7alahc7Dw\nuVXSVYLjLUdoOmsiJzMHfZ364tyGc+X+Vpz7hMNi4Rdzc/ikpAA//4w/371D56AgHEtOBp9hPpmH\nh4dHzfOYNYsiU6qqiLt1i55bVVVSmShVyJDW/gDAtX+vYa7OXCzpugQAsP3xdljMsoC1qzU0Vmtg\n/d31SMsjL0Ke77Uff5yPv//2wMOHpL4ZEpIHHx8erl0LwPbtJBJw5Qpw5Ejtn1sul4tVq1bB09MT\nXbt2BbdMcWBOTg66du2KVatW4fnz5zAyMkJxcTG8vb3x008/iT2Pyq7H0KFjcP9+MFgsNpo3XwR3\n9w949epX/PXXMBgbj4aWljNMTX+Avf15bN06ABERX4HL1UFR0VuEhQ3Gtm0tsWHDfAgEReX2Le31\niI+P/+Q8Cucxb948RERMRHHxe6ip2cDEZPnH+0poWwGFHVWg4ULmxf779u3Dq1evsHz5cgBAcnIy\nRo4ciVOnTn2MMmZmZmLo0KH4559/YGBgUKvjfM5FqpLgzh2ibxUUUMYhIECkYlUbpKdT80Uh5cjE\nhOQ1y9KTags+n6hEP/0kogk1b07/7O0pSyEjNdJPUFxMBe++vpV/7+ZGzT67dKn7gvi8PJq/UNpZ\nCDabOOcDB1LdTevWsj0uw5DDcP8+RUZ37aKmnGVhZESZFCMjosd5eZHwkjyQkUEZPB6PmDdlUVhI\nin1HjoioKJqa1KTT3JwYOq6u5CyXRW5ueVpfXaO+ilQVdrRyFL0vQkjfEOSG5IKlwoLLMxc0atmo\nVo38DiQlYXxEBIQvwOYqKjhuawvn2hqx2Fi6yf39qVGVEF27UkdjSWWfq8HV11fhfd4bUWlR5bbr\nqOrgn+H/oLt5dyhxpFB+ERP37tE7ISODBEFSUkTfzZxJWeNGjaQ/TlJSEgICAlBYWIhly5YhKqr8\nvDU1NZGdnQ0ul4tly5ZhypQpdSLnDACFhe8QGtofubmirtIqKqZo1MgKpqZzoKHhhPfvDyEn5ynM\nzZdAXd1G4mNUV+yfkLAF0dGzwGKpoH37R9DQsBN7v/7+/liyZAmio6Ohra2NJUuWYOrUqRKPryYo\niv0VkCfknpFpVGrFcsvwSYTFe2pVdRD8D6FLF1qIWlqS8/HVV0TdEvZ1kRR6etQL5LvvaKH47h3R\ngMzN6YUjTXNDDoeCj+/eAb/9Rk5LbCyppW3dSg7Ymze13391UFIiBsfNm3TO2rQhmkPbtvT93buk\nCqejQy/QM2fqpqYGIIqZvz85U2XXUwIBUcD++ouoX1u2UCZJVueIxSJa2ezZVK+SlUX3jZDqBVDW\nKDCQan6OHiW5Zz09YMkSklyVJUVQV5eyQZUJQqmokKP7+jWt6Zo1I6crJoau6eTJ1Di0QwdylH/8\nkRw/DQ0as7watX4pUNhRgrKxMtoHtoearRqYQgaB1oF4aPkQ6VclKAwsxbjGjXHL0RE2pecvtrAQ\n3Z8+RURtC96aN6fisYQEilAtXEjbb9+maEZgYO32Wwl6W/RG5IxIFP5SiEtjLmGA1QCocFSQWZAJ\nj0MeMNtshi57u2DjvY3IKsyS2XErwtUVOHyYAhjJyRTM6diRvtuyhYIQDg4kYCINGjdujOHDh2P0\n6NF4+vQpli9fDjs7u4/PRXZpBKekpASLFi2CtbU1Zs+ejcQ6UBxRUTGBi8tTuLmlwtJyE5SUjFBY\nmIDMzBsIC+PhwYNmePNmIVJSjiIoqDNyc6U8GWWQkxOKV68os2RpuUEiJ+bixYvw9vaGr68vsrOz\nER4eju7du8tsbAooUFeQuSNTMTKmqakJQ0NDvCzTlCQ6OhpGRkYyeQELKRF+fiIKjaxTpUJImoIf\nMmRIuW1VUQlevPBD27YToKpKToi3Ny3o2rWr3TwMDIjpsHdvEHR0eABSERtLClP9+gGLF4vmIdy/\nJCl4ZeU8XL/Ow5EjAbh6FVhaWiOZleWHNm0moEcPohsJF8nSXI9Tp06Vux7dutG6IDwccHJaijFj\n1iIhAZg6lWgOublx2LqVBx4vAqamtHimtg/SUzsqm4ePjw94PB5sbCibVlJCWYQJE7wxZcoeCFt5\nxMUBs2YFYcIEHiwsUrF+vagBnaT3VXXzcHamcaSkALt2+aFt216YMoWCwgMGULYqI8MLy5efQtu2\npMAWGlp3zweLRWUEc+ZswciR83HrFsDjnUL37gCXm4dHj3hYty4A69dTA1gAOHnSD0ZGE7B3b3lx\nA3k+59988029UiL+q3Z069at5bZXdr8XlBRgqe5SRBjSPVXwpgDhI8NxYMcBiakzXXR08LxDB0R3\n7IhWjRohd9MmtFu2DPtKG0hVtD9izWPECEQYGJBE5Z9/0jwuXcL8jh1J374Uktofd3f3T+Zx89pN\nbJ2zFedGncPbuW8xwmYE2Cw2ko4mIeBUAOZdmQfHnY4ITwmHj58POvbsiMvPLiO3SOSs1cb+lB1H\n2XlYWFBQ6ZdfAA0NPzDMBISGAu3bk8NT0/WoiMruqxcvXiAwMBDXr19HTk4O9u/fj+XLl2PgwIEY\nNGgQrKyskJ6ejt9//x1OTk5wcnLCi7LdlyGf94GSkj5evLDF7NmmsLM7DyOjUQDoOd68GTh3DuDz\ns/DokS2Cg7vj/v1zUlHL+Pw8+Pj0xY4dhdDXH4SmTb0/mUfZ8VWcx+LFi7F06VJs27YNp0+fhra2\nNlq1agWg4dhRBf4bkBm1jM/ng8/n4+DBg3j9+jWWLl0KFosFJSUl7N27F/fv38eaNWvAMAwWLFiA\nrl27YqwU2vtfAiXCy8sLR48eFfvvnz8nqeEbN0gtBgAuXRIph9UWqamUjVmxghbaHA69Y6dMAaZO\nlWyMVSE6mnqtvC/Tt27gQHp5aWtX/buaIMk55PMpMrh7N1EehOptM2cCc+dSs8v0dHIWs7Mpmti8\nee3HJu74XrwQZdmePweEaqK9e1PUUtaUs+rGl5sL/PsvOZ9l1YZcXMjJHTuW7pGWLaXrSVSbMSYn\n0/nw9ydKZO/elPVbsICoK0Ls308UORUV+Y+trikR/3U7KqnNLE4vRlDHIORH50PFTAV25+yg0Vaj\n5h9WgqTCQrgEBSGhtCHjZBMTpP7yC04eO1ar/X1EYCAV0927R5+3bQOmTy+fvhUD4p6btLw07Ane\ng7/D/kZwUnClf6PKVUVfy77Qa6QHB2MHzOw4E2yW+HFNccZSUkKCLcOGUc0eQLZ40ybZ0n8rjqWo\nqAj//vsvfv31V0SWRkO6deuGgQMHQl9fH127di1XayZrlB1PcXEGSkrS0aiRZSkFrS9yc0Va9SYm\nk6Gt7Q4dnV5QVTWtcp+VUcuioqbj7dudUFZuDGfnUCgrG1Y7lor709LSwuLFi+Hn54esrCx06dIF\nvr6+aNy4sbSn4BMoqGUKyBMyc2T27duHA0Jd4VI4Ojpi06ZN4PP52Lp1K65duwYA6NOnD7y9vcGW\nohvk5/YCliUYhuhgd+7Q5/HjqRO8tMb/yBGi/gihr0/1DNraFCX39JT43VoOOTkk0XngAIn5AEQB\n27aN9l+XEAgoKijsf1IVLCxo0f7tt1Sb6+BAGS15ITGRhAKOHKEXvbIyOXuennWzMBeipIQcuvXr\ngVOnRNkhIays6BoKaSL1iZwcuj4nToi2KStTXVKnTuToNG0qn2PX9QtYYUclR/aTbIR9FYbC+EJw\nNDkkCuBUu4aXH0pKsOD1a+x8+xYAoMpmo626OoYZGOBHMzOwa2sgGYZu1HXr6HOvXmTYvbzkGjGI\nSI2Ap58notOjq/27jk07wt3MHbM7zYapVtUL6tqgsJDeO//+S59bt6ZAmrxq9YTIy8uDr68vfHx8\nUFjqnAoxePBgTJ06FcnJyWjdujU61pGh4/MLkJ5+DpGR36GkRBSdYbPVYWW1FcbGY8Bmf/qir+jI\n5OVdwfPndALt7S9DT6+PRONISEiAmZkZHBwc4O/vDz09PUybNg3v3r3D1atXpZhh5VA4MgrIEzKj\nlo0fPx7Xr18v929TaRqdw+Hghx9+gL+/P/z9/TFz5kypXr5l8blQImSpksViUV2FtrYXgFPYt48k\nLgUC6eYxahQQFAS0a7cUmpprkZZGTRg3bwYGD45Dy5Y8hIfXfh5nzvjh8OEJOHCAqGUaGpSN6NnT\nC+bmp/DNN9SfBpD/9YiKisDKlTQ/cky2AKB5KClRET6Qh9evebh8OQCjR1MGwNAQMDPzg43NhE8o\n7bK4r6ZP52HjxlRcv050i6IiYMQIuh6bN9PnsvOQtfqacB5nz55Cx47A8ePUhHPSpMtQUhLN4+VL\nchJYLG906rQH27dTbZRwHnX5fJw54wctrQl4946ELDQ16Tw9fuyFrVtPwcGB7uGAAODs2S+bEqGw\no5LfJ5rtNeEc7Iz7re5jVfYqPHF+gg/3RQVyksxj0Q8/wPnOHdxxdERbdXUUCAR4/OQJFo4ahRkV\nChclmsfWrZhfUkIcWBYLuHYNeWPHgqeqioAtW8r9rSzVpVobtEbAhACs670O57qfg+cTT7yd9hZB\nU4KwyH0RhtsMB24AD48+xMb7G2G73RZjT47FXzf/kpn9UVEhwZn162nqERFeGDr0FBYuJNsjzjzK\nQtz7Sk1NDaNGjULnzp0xatQoWFhYwMjICABw+vRpDBgwAOPHj0enTp3g6emJu3fvyl01kcNRhaHh\nMNjbX0Z6+lD4+BggJ0cLAkEuIiMn4PZtFUyf3gYrVvxY7vdlqWUFBYmIjJwEALhxoxdWr75c7m/F\neR8InaJZs2Zh3rx5uHLlCn799VfcuHED+fn5CmqZAl8UZK5aVldoCJFEcXD6NAXtCgspAj1+PNW6\nSBvEy8+nRpqvXwNRUYCQPTFiBL10ZLE+evOGalQq2D3Mn091sLq60h9DHBQXk8paWBhln2xKRWNS\nUsjR+usvoitVhokTiZZmI7nQTI3IzaVzcfy4SO1HV5ccCA8PKnJv1ky6LJmkSEkBkpKo4F7odArB\n4RA1ZNUq2SgR1RYMQ7S4hw9JFenpU9F3LVpQJm7gQMqwSYuGHklsSHa0OL0Yj+weoegtRQOMvzWG\n5QZLKBso12p/AoZBdH4+TqSkYGGpQscGS0vMlUZWEgCePSPDWJby06wZ3biTJ8vG+EqABwkP4B/p\nj5MRJxGRKnJcPK09sbjrYjg3ca6VKlylx3pAQYeyU+/aFZg0ibK/pSUacgPDMFi5ciX27duHpKSk\ncuIZ6urqOHz4MDp16gRDQ0OZBQlqgkBQgvj4DYiNXQaBgNR4OBxtGBoOLVU9syuXkbl3rysKC29D\nQ6M92rW7Bza7+vubYZhKr5+5uTmWLl360bl59eoVrK2tkZ2dLXMBkYZuRxWoXygcmS8Af/1Fhl4I\ne3uibzk4yO4YW7cSjbukhIrC//iDGmLKAqGh9G/fPur8LkTfvqR+VlFyt67BMOTQmJsTjenWLaLD\n3bol+puePalXSkVlMlkdf+dOko8WZj2EcHSkrFKZZtd1hnv3SFL15Us6F89Kqd2urtQI08mJaHl1\n6WhVRGEh1R9duUK1ZUJZcIAcwjFjgEGDal8L1dBfwA3NjmbeyUQYLwwlmdSMkqPJgdV2KzQeIx3v\nf31cHH58/RoAsLR5c/i0aCH1WBETQ92My2Y9+vQhYyBsElWHKOIX4U7sHZyNOovtj7ejiE8OYdfm\nXbHIfRH6tuwrk+MwDNnXvXtRrgcYi0UBrnbtKDsuTW2l+GNhEBgYiClTpiA0NPTjdiUlJVhaWmLs\n2LFYsGBBnTg1DMNHWtp5vHz5PQoLEz5u19R0hq7u97C0nAiA6kDV1dXh7BwMNTWraveZnZ2N/v37\nY/78+Rg8eHC571atWoXjx4/j7Nmz0NXVxbRp05CUlIRLly7JfG4N3Y4qUL+o29CPHPA5UyLaCrWB\nS1FbVZSJEyn6PHIkoKFxGaGhPLi4kNEXDrG28xAel8eLg709DxxOBM6fJzWrp09lQ2VaudILGhqn\ncOUKOUiqqgBwGZcu8dC+vciBqmweEyZMkDtF5e7dANjYkIyykRFQUuKHFi0m4No1knoGSDK4Sxcv\nWFqeKrfu8PDwkPq+8vFZiqystYiLIyni1asBe/s4ADw8fRqB9u3pxe7iAgwdKtn1sLL69EUn7vPh\n6gpERnrD0XEPQkLIYeBygXv3guDlxYO1dSrYbMDampzURYtqdz2E90xtno8LF05hzhx6ucfEACNH\nXoaWFs3jwQPKXlpbA507e2P3bgUloip8Lnb0qwqFE5Lanzl/zYFbuhva+reFur06+Nl8fDP2G2zz\n2IaCeJGXK+48hPbnzowZ+L60d8evsbGYFBGBnxcvls7+GBmBZ2mJgFmzRJ72lSvws7fHhKFDPxlb\nixYt5Ho9lDnK6GXRC7/1+w1H+xxF4zONgRTgduxt9D/cHytvr4Svry/mz59f7nmU9LkdOdILpqan\n8OQJiQD8/DOgonIZDMPDqlXA8OEUVLp+Xbx5CI9Rm/cBi8VCx44dcfnyZUyZMgWq9HJCcXExIiIi\n8PPPP6Nfv34YP378J/Oo6vmo2NQVEG8eLBYHBgaeOH9+LG7cGA9dXap7yc5+jDt3Jpb7rZXVVqip\nWVX7fNy8eROtW7fG3bt3MW3aNOzdu7fc9ViwYAF69uwJCwsLNG7cGAUFBThYWtyqoJYp8CVBkZGR\nI/z8/PDNN9/IdJ/v3wPTplGBNkCqTj4+taebVRxjcDAFCd+/J/rQ7duAs7Nsxi5Efj71nxkzhgrO\nARIdWLlS1BemqvHVB+7coRrds2fps4UF1Rppa8t3fAkJ5EiVVRcDiO62ahWJA+joVL8PWY/vxQtg\nzRpS0yurUAdQJPW33yhrJUnvP1mPUSAgquC5cyTXLCxtWLSI7jFJ0NAjiZ+bHZXlvcDwGUROiUTS\nX0kAAJYSCyaTTWCxxgJcLfGUUyqOZ3JEBPYk0f7mmJpikyzVry5epKZQQt3x+fNplV+amqgPWxiW\nHIaVd1bi77C/aQzD/DCy7UiZj6WggAI1YWGibSwWnYJ+/SiwVlXmV9ZjKS4uRmJiInbt2oU1a9YA\nAOzs7PD9999j5MiRyMnJgYmJCThVGDlZjqegIA6JiVsRFbUeAwbQtsDAYXB2PlYt3Y9hGEycOBH7\n9u2Dmpoabt68CRcXF5mMqTZo6HZUgfqFwpH5AsEwJFH7v/9RjQtAjce8vWmRKS3VJzqaFst37gC2\nttSws7Imh9KCzyep5O+/F21r0YIoQb/8Ip+6FGnw/DmNLSeHVLLGjqXGkvKsF/nwAbh6lZy/zZtF\njp8Qjo6keObtLZuaEEnw5g05d9eukWMjpHU1bgxMmEAsmVevyOFp146okLKiK4oLgYCKjBcsIKc/\nIUGye7mhv4D/C3Y0/VI6Xv/8GjlPSPdcpZkKbI7aQLuz5NwlhmGw6+1bTH/5EsosFoKdnWFTpsu6\n1EhNJR17oTMDkFb60qX1yuH84cIP8A30BZvFRoemHbChzwa4NnOVWe0MQO+DoiJq7OvlVZ7aCxC9\n98iRurVz+/fvx+zZs5FZoSMvh8NBx44dMWDAAFhYWODrr7+u0rGRBUJDZ8DBYRsAICMjATo61cs0\nLl26FMuWLQObzcbp06cxaNAguY1NHDR0O6pA/eKLp5b9F8FiAYMH08L6p59IlSs3l7IGbm7Sd7Rv\n2RI4eZKi/c+fUx8AIfVLluBwqJ3CnTukRgrQ4tjPj+Zx4YJsO89LC1tbUY+TxERyGu3tiQJRXCyf\nY2pr0/kfM4bqVfz9yzt4T59SbY2VFfUFqpglkSdatKDi/1OnKEPl5UXbk5KIHtezJ/Ddd+SUDhhA\nzp+GBs0nObluxshmU1S3dWtyQiuwHxT4D0Cvrx7aB7aH3Tk7qFqoojC+EMGuwYhdHQuGL5mBYbFY\nmNqkCVy1tFDEMBj94gWKBQLZDdbAgOT3XF1F2379lVLVly9X/Ts5Y03vNRhtNxoCRoAHCQ/gvtcd\nlr6WSM2T3QPF4VBQyNiYgjfz5wN2diL/7fp1siEzZgB5eTI7bLX49ttv8erVKyxcuBBaWloft/P5\nfNy7dw+//PILRo0ahbFjx6JIKDkpB7RoIUolKylVn4b/448/sGzZMgDAjh076t2JUUABeeOLd2Q+\nF263vGRyq5uHqiotpt++Bbp29QawB/fv06IxN1e6eejrkyOhpLQFV67Mx4wZFN2Wxzzc3enF9e4d\n0KuXN5SV9yAzk+YxZAjw+PHncz0+fDiFyEgSYGjcGIiOvoxevXgwMaGMifAFK6/7KiZmC/r2nY/g\nYLr2rq6AmloesrN5+OOPANjakhORmipb2dCa5tGmDdCq1VIsW7YWBw6Q1Le+PqClFQd9fR6aNKF5\n5OZSP5g2bbZg3Dj5Ph9CsNmAu7s3vv56D8rWaCu43SI0dDt62v809AfowznIGaqWqniERxi1aBSe\ndHiCkixRlEa8WgYW/rW1her+/Xj6xx/oFRKCyNIHXybzuHIFE6ytyeDOmkUbw8Ph1a8fTm3bVu5v\n6+p6NFJqhENDD+En7k/QuEnqWW8y38BwvSHGHxsPtz5uuCNsfCachxTPLZdLgbkuXbzx6697Pvac\n4fOBbduC0KQJD8uXpyI/X7J5CCHJ9bh06RLevXuHxMREHDp0CA8fPkRUVBTatWv3sQbRz88PHh4e\n2Lt3r1yuR2JiBRWYKuZx7tw5TJs2DQAwbtw4TJky5eN3dfk+EM7jv2ZHFagfKKhlckRAQADc3d3r\n7HgnTpB8skBAkpZHj9JiuzrUNMYTJyiCDpA85unT8k/tP3tGNSBHjwIME4A+fdxx8GDdU6dqQmoq\n4OQUgISE8udvzBiinFVSZy8X8Pmk2DV/vkiKWFub6PUuLgHo3r3u7sHqEB9P13baNFGn73HjgNGj\nA+Dh8XmMsSIaOiXic7OjdWEzS3JK8G73O7z5+Q0EBQLo8/Rhe8wWbOVP43rVjedCWhqGPn+OAoEA\n6mw2dlpbY4ysu6IzDKViv/4aATExcNfTI5UXb+9600BnGAZfb/waV0qu4EOhKP0/yHoQDgw5AN1G\n8tHV5/OJyjp6NAVEAMDSEli4MACTJtWf/Th//jyGDx+O/Px86OjoYOTIkfD29oaNjY3M1M4qNsRU\nr4TO+OjRI3Tv3h15eXkYP348/vrrL9y9e7dO1yBVoaHbUQXqF198RuZzxjphF+c6wtChlH7X1KQi\nfRcX0YKxKtQ0xqFDSZpZTY2U0xwcSBBAnrCzI3rZ9u0AsA5XrgCmphScrGk+dQkDA8DObh2Cg4ne\nJcShQ0RD27q1bqhxHA6pmj18CGzcSNmRDx+AH38EhgxZhwsXgAoU73pBs86QWtoAACAASURBVGaU\nZbt0CejRgygjBw4Anp7r0KsXOeGHDtGCRYH/JurCZnI1uGj2v2ZwuOEAljILaf5piPGJkXg8/fX1\nEdy+PXro6CBXIMDYiAi0DQzEkjdvIJDVg89ikSE/dw7rNDSA9HQRV1KoPlLHYLFYKLxdiLQf0/C/\nTv/7uP1s1Fl0+LMDDoQcwJO3T8DI2PhxOESpDg2lbE3TplSDN2XKOvzwA/VDqw8MGDAAgYGBMDMz\nQ2ZmJnbu3Ak7OzuYmppi3rx5SBE2CZMjXr16hYEDByIvLw8eHh7YvXs3WCxWna9BFFCgPqDIyMgR\neXl5Mm8sJQ6CgmhR+Po1LWrv3CGaT2UQd4xPngCdO4tqQbp2pfepvOm3gYF5mDJFDSEh9JnNJiGC\nLVuEMs71i7LnLySEnJdr16jWR4jmzalBo5cX0ejk3ZKguJjUudasAQoL8wCogcUi52HQIKLb9+hB\n9I36REAARVfj4miMQhgbU3H+rFl13hvwEzT0SOLnZkfr2mYmHUxCxDiiHdmdt4N+//KGUpzx8BkG\nK2JjsSwmBsJqmXYaGjhnZ4fGKioyG2teZibUtm2jdLWQw+rjQ+nfOhYCKHteYjJjkJiViFEnRiHu\nQ9zHv7E1tMXKnisxuPXgqnYjFT58oJYEFy+S/VBRAczMAGVlOiVffy2Xw1aJtLQ0TJw4Ef7+/lBS\nUkJx6cuSw+Hg8OHDsLW1ha2tba0EEqrLyKSkpMDV1RXR0dFwcnLCrVu3oFmqaFJfa5CKaOh2VIH6\nxRefkfmcud1Lly4tt01eNQAV59GuHVGNjIyC8OIFD99+W/U8hEauJi5x+/bkzHTqBAB5uH2bB0/P\nAEyfLso6yIOD26GDGnbsCELTpjzo6qZCIAD+/JPkOH/4of5rlgICAj7Ow8GB+uS8egV06OANFovm\nERtL2aVu3Yjb/f69fGsGlJRofbN5sx+srb2ho0PX6Pp1Urrz8PCCtfUpnDsnKn6vj+fj9On5eP4c\nOHdODb/9BkyenAcul4f37wMwZw5lb96/V3C76wKfix2Ni4srt13etYZGXxtBzZZsYNiQMEwaNKnc\nPNTU1GqcB4fFwlJzc0R37IjpXC7YP/+MoPBwOD95gozSxaws5jFh6lScsrWlh6L0+8s+PuDp6gI7\ndtDD/P49wDByr1kquzg2UjbC2hlrscNuB6a1n4b2Ju3BZXPx/PpzDPlmCHY82lFuH7K6r4qLU3Hu\nHODrqwZ1daCwcClevlyL588paMRiAa1bx0FZmYe2bSMwahSweDElsubO3YK5c+cjPl6k/CntfaWv\nrw9vb294enoiJycHf/75JwASBhg5ciTs7Ozg7u4OX19f+Pn5ITAwUOzrEV8FFWHjxo1wcHBAdHQ0\nmjdvjnPnzoHD4XycR9nrpLCjCjRUKDIyDRj37pH6F0ASx0uXUsNHaREZSQv2TZtogTxgANXSyDD4\nWCWuXaNsU0YGKWANGEBOzatXdPxFi0iK+nNAfDytLcLDqafJsWOk/vbbb9Quoq7AMMDLlyRd+vAh\nNYosSzXr0IEYK23akERx06Ykk2xrS8pjUVHUcNLCglTa1NXlV68UHQ189VX5fhLt29M4QkIou7Vh\nA42zLtDQI4kKOwoIigQIHxmO1JO0EGOrsmG2yAxNpjSBsrGyxPu7mp6OPqVd4i1VVfFz8+b4tnFj\nsGWZNWEYcl5mz/5UMrFfPyowrKuHpBKk5KZg2a1l2PpoKxpxG+Hh5IewM7aT2/EYBrh7l6a9dStl\nciURk7OxISn7b76h0yerbHVxcTEWV9I4FQA0NTUxcOBAzJ8/v8Znr7KMTElJCYYNGwZ/f3/o6uri\n7t27aNOmjdhj09DQKJcdKigogI2NDUKE9AcZoqHbUQXqFwpHpoFjwQJAaEO5XOocL3RupMX27VRz\niv+zd97xNd/fH3/em0R2QiSSmDFixUztGK0apRWlarVVo8Nu+yWoFVpVq6pGlV/R1kiHLtRIa5TY\nRBARKzSCkIEsmff+/jiuDEHGvblXfJ6PRx/lc697z/vz+dz3+3Pe55zXQYQA/v23ZJyZy5dFFevQ\noYdf8/CQtDNTVJxcvBg++ED+/MIL0mfl7bdLvrfKzZtyX3z33ZPfW6OG9F7JqyxatqzcRx99lC2d\nrU/OnJHUkLCwh18zN5fvXrkSDL0mlvYFWJlHBU2GhtCeocRvi39wzMzRjKZBTbFrYFfozzt49y59\nw8KISksDoLezM1/Xro1rmcI7Ro/l0CGZRC5ezP3k7ukpT/SdOxut/4xGq+GldS/xd8TfALzd+G1m\nvzibivaGn/AuXBCJ/KtXIS1NFDEvX5aNpdDQ3Km/eXF2ls2yWbPAyUk/9ty8eZN9+/Yxa9Ysbty4\nwa08+vOffvopH3/88SN70eR1ZGxsbBg5ciTffPMNlpaW7Ny5E59iLuyNGzdmwIABTJo0qVifkx+l\nfR5VMC5PfWqZKZM3lcAYzJnDA8WvzEyp0ejdW6I1Wm3xbBw5UnbAQHb63d1F+jcxUU/Gk7991atL\n3c8vv0gfms6doU4dESS4ckUaRPboIYXjv//+8EO4PinM+Rs9WvqugKT+TZ4sO4GTJxuuL0J+9rm6\nwpo10stl+nRJuV+9Wv78+eeyK/nCC/LeiIjs81e1avZn3LkjUaZOneCdd+ShQZ82enlJrdeOHXLe\nOneWZ7OyZeU+/vdfeU/nzuKox8fn88EKTx3GmjPVFmoa/tWQRoGNcBvshkUFC7LuZvFeq/e4E1R4\npYzWjo6ceO45RleSxoW/xcZS6/Bh6h85wuf//VekQvh8z02rVhIiz8qCmBgpPHN1lSf5rl3BxUUq\n5A8eLPT3FdqWPKhVatb1XkeHah0A+P7k91RaWIk1J9boVQggP1s8PSVS/9ZbMj9NmyZz3KZNMqf9\n/LOocS5YIKdv0iRRQFOrxdlZvhy6dYOzZ/Vjj6urK3369CEkJISbN29y8uRJpk2b9uD1adOmYW5u\nzqxZs0i77/w+jjlz5vDNN9+gUqlYv379I52Ygv6ejhw5QlhYGIMHDy7Q+xUUTAnFkTEgVXM++RmR\nN9+E7duzpZh//112tOvUgdu3i2dj374iyVy2rKR7TZ4su/i//KIfxa5HnUNzc+jTR6JCgYEQHi4P\n0+PGyWK0ZYssYr17S6+VCxeKb0th7MsPtVqiMqGh2e0h7t4V56FJE1GaK0n7XFyk197HH0vK/cyZ\nsqBv2CD1NKdPy0L/7bdyba9ckSyWnTvl/I4aJWNatSpbVa4Aa3CBbbS0hC5dJMIWGCgpbvHx4jR3\n6SIOzT//iM116kjjTaXh5dONMedMlUqFU2cn6q6pS4uzLbCuY41zsjMh7UKImBJB1r3Cyek5lynD\nEk9PdjVujKe1NUlZWZxNSWHy5cv0CwtjxfXrD/rPFIQnnhtnZ5nYQ0KkE62FBcTFydN727Yiaagn\nycmCXqcKthXY/fZuAt8MxNHSEYChm4Yy4NcB3EzST/feotwzr78OGzfKelG7tszBFy/CvXuipGhr\nC0eOyEZTmTLiE771lqhTnjlTfHsaNWrEJ598QlZWFkOHDn1wfNq0abi5ubFp06ZH/tuAgAAmT54M\nwKJFi3hN1x+hiLYArFq1iu7du+Omb/lwBYUS4Kl3ZEylSDW/osi8haslVeyf3ziaNJHwekgINGni\nj4XFXC5cgFWrxlC/PqxdW/Ticl9f2d0fMSIAe/shxMaKg1O9uqRw9+xZ9HGMGTOmwNejbFkYOzaS\nDh186dUrexzHj0Pt2kuws/Nj6lRxHvIbh47CXI86deoU+nq4usby1Vfy0D9mDJiZSZFqhw6yk/jD\nDxAWph/RguDg4AKNI7/r0aABRERIo9WyZSVDxdwcypYNZsUKX2bMiGXrVkkrFNv8sbefi5OT1C+1\nagWLFkXy8suPH8eY+2GqglwPlUpqenbsgBdf7Ef79jKO2FhRaqtYMZD69X0fyo9XilQfj6nMo507\nd851vCQaC+c3DgsnC7wPeTO8/3DOc563Zr/FFpstBLcNJulU0hPHkfN+f6FcOUYdPsxrv/5Kz/Ll\nUQO/xMQw/NQp6nXuzEvr1rH/bnY/lkeNIygoqGDjcHNjlIUFq/z95UdRqxZoNASPH4+vtzexb7+d\nS+O8KMX+ut8sPPl6qFQqOtfszMWxFxnQYAD8Aj9t/Ilqi6rR+6febL+4na3bthb5vtLZog/RlD59\nfKlePYjt26VWRqWCjIwAAgOHsG6dRK2bNJG0s96987+v/v777wKP49VXX2Xu3Lls27aNbt26AXDn\nzh169uzJrFmzHrw3Z7G/ruHl+PHjUalUj/195LxOj7qvXnvtNdatW8c777yTaxxKsb/C04JSI/OM\nkpgou1HffZddK9q8uaSLFSe6nJgoylgBAdlNy0AUvVQqqREpqeh1dLSkQI0ZIzv3Olxc5EG4adOS\nseNJXLsmktKBgbmP9+snjmDTpiVTe1Qc1q2TyEh+KWbW1hI9Gz9exAL0TWqqCFksWpSdBteypWxE\nm5lJc9CiFu+W9txuZR59MtHfR3Np4iUybspEqbZV03BLQ8o9X7TGj9vi4vg+Oprr6ensy+HAfOrh\nwVQPD32YnJurV+HVVyVXU8ewYbBihfxASpg9V/YwausowmKyC+AcLR1Z3G0xbnZudKzeEXO1kbXh\n77Nvn6xXKpXMwxs3Zr9Wrpycwtdfl+wDfZQinT9/nmnTpvHzzz8DMHLkSMaOHUulSpUeSCoD9O/f\nn/Xr1+ul4eZ3333HlClTuHr1qt4aeOaltM+jCsZFcWSece7eldSi5TkUMt9/Xx4M3d2L/rkJCZKH\nPGGCpCXl5KWXZFGYMqVkFMa0WkmLOnxYdtQuXBDH4L33oFkz6YljiOeHwnL1qpyvH3/MfVytFgfz\niy8kzcFUSU+XiJ+dnQgKbN8uaWpRUfJ6mTKyQVylivzZxkaEAvSlEKTRSHrZ55/nPu7jI3VAt26J\nQ1UYSvsCrMyjBUOTpuHKzCtELY5Ck6xBZanCY4YHlT+sjJlV0Z2BDTdv8sXVqwQnSZSnu5MT82vW\npL6hJsZffslusOLuLoUkw4fLJFiCaLVa1oSsYfmx5Ry7fizXa/0b9Gd97/WoVaaXMJKRIbU2CxZI\nKlpOvL1ljn7++eJ9h1arZfDgwfzwww/5vt62bVv++ecfLPW0u9W2bVvat2/P7Nmz9fJ5+VHa51EF\n42J6M0UpIm842xS5cSOcr7+W1OleveTYihXiaBQnndrBQYosr1yRwuwtWx60PmD7dnnYrFJF0tI2\nb5Zd9fzQxzlUqSTNrX9/OHpUcqLT0qT24u235bUlS4omCqDPa1ylikSybt2SYnwdGo0IEHl5yYP6\n0qXiKJa0fU+iTBlJ+6pfX8QC5s6FyEipqXnhBTm/fn5yHXr3Fof25Zfh1Cn92KhWi8Ny5oxcUx37\n90OHDhL1yutUK5gWpjZn6uxRW6qpMbsGPrE+OHV3Qpum5fLHl9lnvY+IqRFFLl4f6OrK8WbN+OC+\nKMDW+Hi8jh6l5fHj7LuTW2RAL+fm9dflKdzaWnKNAwLkx9GlC3z1VYEnluLaolKpGNp0KEffPUrI\n+yG8WvdVLNQWAPwY+iONv2nMB9s+YNflXQa3pTBYWMhG36lTD6t/BgeLQMC6dcU/N6tXr36ketiP\nP/5YYCcmPDycwEDJTsiPc+fOcfDgQYYNG1ZUcxUUjI7iyBiQCRMmGNuEJ6KzsUkTiQQsWiQPgTdv\nys7SpEmi8Jm3VUFBcXCQzb6XX5adrD17JKXN2loeKjdvFmfGw+PhSERO+/SFo6PUzPz6q6QMVK4s\nx8eOlUhC167y4F1QDHGNXVzEtowMcbh+/lmcsYsXJaIxZowUt7/3njykl7R9hUGlkh4w27eLvdWq\niTpQ3bryemAgvPyyfm2sX1+ibleuyLNZ3boS9enYseAOoIJxMPb9mpe89phZmdHgtwa4Dckuio78\nLJKEg8W7sRZ5erK3SRO870vsHklM5OXTp9l75w6hSUlsjYtjxLhx+lH7GjdOnmw3bIB27eTY339L\nHqu7uxx/wvfo8zo1dmvM7/1+J31aOgu7LAQg9FYoi48s5sUfXqTaomrM3jebpPQkg9tSUKytZS3b\ntk3Ss7/5RlKzU1Nh1KgJxVbKNDMz4/PPPyctLY2NGzfikSNloGzZsgX6DI0GXn11Ai+9JEG4/Nbw\n1atX0759e2rWrFk8gxUUjIiSWmZAIiMjTUa57FHkZ2NCgjSazPmQrFbDsWP6qyuJjZUdrD//lOL2\n+5kVzJkjgjspKaKudvRoJF26VOWNNwzTDuH6dUnb2rs392795MmShvakja+Susbbt4s9V68+vLvW\nv784g3XrSi1SzjRnU74Hd+yQHUytNpIPPqjKwIHioDk66v+7iprDXtpTIkxtHjW1+/Vx9qRGpnK4\n5mG0mVrU1mo8v/bEfXAx8nHvc+DuXXzyC4ffvMnrDRqwvl49LPRVy5CUJE/i0dHS5VjX38TbWxo1\neXvn+8Mx1HXSarX8+9+/HIo6xKGoQ2w5v4UsbbYwgaeTJ5+/+Dm96vV6kHpmKvdMXJwodiYkRAJV\nefFFmDdP6gKLmz6bX0PMx3H3rqisbd4stgwfLps6xkpNLu3zqIJxURwZhXzJzIT160Vad98+Oday\npaQ8FaJ5cIGIjRWBgLVrH/2eSZNEKcZQtalarcj7zp2bndZVo4YsBiNHQoUKhvneopCeLv17pk6V\n1K2clCsHrVuLI9amjdF64RWY4cMllTEnc+aI7a1aSSqHMSntC7AyjxaP5PBkTnU9RVpkGqjAa6MX\nLr1div25V1NTGXH+PIG3b5Oh1aICdAv1wAoVWObpSVl9/zjS02HGDPjyy+xc306dJBWtUiUJWVtZ\n6fc7n0BsSiybz21m2u5pXEvMVhLxdPJkSbcldKnZJVd3emOzbZusGXFx2cfKloX582HQIJnPimJu\nYRyZ0FBJ3dXVgi5fnp3WbSxK+zyqYFye+tQyU5ENLa5MrqHllws7DnNzqR95/fUlvPmmH2q1FMs3\nbAjz5ul3HM7Osik4dy7Y2YncL0hXZXEggpkzx5cmTWLZs6dw49DxpOuhUkk0YPVqGDs2ACurIURE\nSG+VRo2k+aOvr2ncV1Om+PHWW/Dff9LvpWrVFMAXCOL2bdi6VdpGqNUBNGo0hMWL5b06TOn3sWwZ\nfP+9OC4g45g0KYj27SUHfc0aGDAggGbNhhAamts2Q47jWZMNVebRoo1j6Z9LaXm+JS59XUALuwfs\nplOdTpw+dLpY45g+YgRbGjUipV07Mjt0QPP883gvXAhBQWy4dYsGR48ScPMmO3bs0N/1KFNGiswu\nXyaya1d8gfB//pG8YxcXqFyZJb17l+j18PfzRxOs4ei7R/m47cd0rtEZmxgbLiy9wEsrX8Lray/e\n3/w+s/fN5qNJHxn9vjIzC6RZM1+WLZM5GEQ58913R2FpuQp3d0mxjYoq3O8jp/zy48bx88/QsmUK\nFy74UqFCEPv3Zzsxxvh9PGvzqIJxUCIyCgXiwgWRz9X16fr4Y6nXMMRmWFSU1IbUrCl5vePGSTG+\nDl9fiRQ5O+v/u3XcvCnf+e238mcd5ctL3c/kySJmYApERMAff0hdzd698NtvD0e3ypQRm994Q+pU\njB3pyI/wcMk1P3NGxpE3z9zcXMQCPv4Y7O0laqgvxbNHUdp3EpV5VD9oMjWc6X2GuM2yFW9T14bG\nuxtj6aY/3XStVsuPt27xcUQE/93vPFvH2pp5NWvS1ckJS31L5/7zjzx1X76c+/jKlZL/ayTupN5h\nfOB41p9eT2pmbpWYIU2G0KlGJ172fBlHKwPkqBaS9HTxDWfOfPg1Dw8RDkhKkrYELo8J5D0pIpOZ\nKfPiggXy9xdflJpTQ66RhaG0z6MKxuWpj8iYMnl3VUyRgtro6SkPy7q3f/65pP7s2sVDzQeLS+XK\n4sQALFw4l8WLpdB94EA5tmmTTPr9++fft0QfuLpKKtvly1IDq3vwj4uTY+++K/U9n39u/Gtco4ak\n5jk5SbuIH36Q6zJqFHh6zqVu3eysEU9PyQ7p1UsWP1NAdw/WrStiE3//LU7N6NESlalSRcaWmSn3\nnYODjMHaGiZOVAr4SxOmNmcW1B61uRqvX7yo9VUtAFLCUzhc6zDR6x4hF1UE5s2bxwBXV862aMHU\natUAOHfvHj1DQ+lz5gzp+p6IO3WSXZKkJDh5UnJZAd57j7k1axZOFUWPlLUqy7e+3xI9Lpq1vdbS\n6Xon6rvUB2BNyBre+O0N3L5wY82JNfoRRygkOe+ZMmVk3o2OFuXrpUuzBWauXMneEKxeXdbXonDr\nlojO6ZyYiROlptLZ2fR+TwoKhkBxZAxISkqKsU14IoWxUaWSPieLF8uD5JEjsvNTqZLs9F+4YDj7\nataUmp3jx6FiRXntp5+kFvXoUf1/rw5ra0kZv3VL1vKNG6FHD3nt1Vdh5swU/P2fKPJT4rzwgiya\nAwakEBoqedLNmslrGo0smtWriwLa2bPGtTW/e1AniR0UJHVAN27Irqarq7yeliaOzbx5ksKRMydd\n4enF1ObMwtijtlRTeWxlmp1qhp23HZpkDeFvhXPxo4toNcWfIHS2WJuZ8Wn16izz9Hzw2pa4OF46\ndYrkrKxH/fOiY2sr+bWffPIgDJ0SESGOziuvyO5CHqnoksDRypE3G71JG7c27Hl7D0OaDKGesxRw\npmamMnTTUCourMiOiztK1K787hlXV+lhNWqUrCPjxslxBwf5f3KybNTterLadC6OHIHnnoPdu6WE\naeNGqTHURapN7fekoGAIlNQyhSJx44bk3u7IsUY4Ooqcsk7R01Bcvixr6tq1kJUFVavKDr61tWG/\nV0diohSpBwRkOzBubtKOoX9/6NnTdIvss7KkuH7MmOxImlotDsEHHxg+Vau4ZGbCuXPSmyg+XiI4\ncXESoVu8WIpc9anMU9pTIpR51DBkpWZxefJlor6UbrAWFSxouKkhDi0d9P5dO+Lj6R0aSsr9H3RN\nKytGVarEMHd3HAzxgz56VCa6iIjcx319ZWerQQOZDA2lzPIEYpJjaPltSy7fkZQ4c7U5U9pNwa+N\nH7ZlSqADcyG5d09Ol25Drk8fqQ28n0kG5J9a9u234hilp0t95++/61+IR1+U9nlUwbgoERmFIuHu\nLuHrO3ckMuLpKZKP7dvLg/zvvxvuu6tXl4k+Lk6iQZGR4kQNHiwPtufOGe67Qeoz1q+XBeizz+RY\ndLSch169xL5OnWTzcsgQiSzs2iVOREREdkqXMaI4ZmaiwnbmjHSh9vERh2b8eHEIFy4UFTlTxdxc\nGoOOHCmZLjt3Ss1PTAwMGCDPUffLBxQUjIaZlRk1v6hJxZESPs64lUFwq2Cuf3td7+lOXZ2c2Ojl\nhdN9p+VSair/u3QJx6AghoSHc0PfP4jmzSU0vnQpfPRRtsOyaZPshrz4ooTsvb1FQlGlkp2ehg1F\nH75iRejXT3KhDNCh1sXWhXOjzxExNoLa5WuTqclk5r8zsfvcjo7fd+RG4g29f2dxsLYWtTOdOMDG\njeITnjmT//vT0qR06d13xYl59VWJzJiqE6OgYGiUiIyCXoiPl0hMWFj2sf79ZfffQf+bkA8IDJRm\nX3fvZh9Tq2VnvlcvWVMrVDBchESrlYUnOBi+/rpg9RoqldgUHy/rO0gUITZW0gumTBEHrSRIT5ec\n6uXLsx2AsmVlYW3VqmRsKC6xsTKG774Tp6xCBWlwOnCgOJXFobTvJCrzqGHRarREzonkyswraNNl\nqS3fszwe0zyw87bTq3Twvawsgu7eJejuXb6KiuLu/TQzM2BkpUrMqVEDc5WKmIwMKpYpo7/v3rVL\ncpsSEmQB2LevcLsJnTtLOFXXJVePpGamMuHvCSw5kq0W07xicwLfCiQ9K50Ktqajq6/VygbZ229n\nR8ubNhUHp2/fZNq1k4iMt3cSwcG2qFSykTZxYu7eYaZIaZ9HFYyL4sgYkNjYWJxNRTbkEejTxrQ0\naZr522+ysw+SG+zvLztIRck0KIh9yckSHTp1Snbo83a7b9FCmoG1bKl/hyanfRoNrFsn0QF7ezh9\nWhaYixelgD2/zsr5YWUla3unTlJ7VL68fux7HNeuiXTn6tXSh6BCBXFCU1JkU9XZWRyvKlX0v2jq\n6x7880+5z3Q9/QC6dhWHbPjwbKexMJT2BdjU5lFTmzP1ZY8mU8PVuVe5MuMK2kxZctXWatwGu1Fj\nXg3M7Z6cAlYYWxIyM5lw6RI/xcRwJx9Vj45ly/JJ9er4FLH77GNtSUuTXYXFi+XP7dtDrVrypJ6Q\nIJNwTIxMOLpOyCARm/fek3ypQkzUBTkvKRkpLD+6nPF/j39wTIUK3zq+ONs4U7t8bYY3G46DZfF3\n3Yp7z+zfL+vnn39KFB/AwiKZjAxdrlkSTk62bNgg81tRbbl16xajR49m9+7dAHTs2JFly5YZ5PdX\n2udRBeOiODIGxNfXl006vWITxVA2BgXJzpIujdraWiIz8+fDm28WfJ0qin3794vUcFBQbkW1Vq3E\nmdFoROXLw6NQH1ss+6KiZLftuefEMdGN/9w5SYvTaCQzY9++3FEtkJSB5cslj9pQ9ulIShLHJW/P\nFh1ly0qk7c4dcUz79pV63+I4N/q8B9PTpS/NkiXiSOqwtYXu3UW4oTDRrtK+AJvaPGpqc6a+7bl7\n6C5Ri6KI/SMWbZosveblzCnXpRxVxlfBodmjH6SLYotGq2VyRARLr10jOR9VsxkeHkytVg2zQu7w\n6OW8pKVJTuuJE9KkTOdwDRwIw4YVuM6mMLb8Ef4HfX/pS4bm0btKzjbOfNTqIya3m1ygzyyOPY/j\n7FnJvlu9GiAZEEemYcMk/vzTtkDR5sfZ0r9/f9LT01m3bh0ajYY33ngDW1tbNmzYUGzb81La51EF\n46I4MgYkODjYZG3TYUgb09NlV3/SJNnZ19GypdQzvPsu2NgYzr7MGWtwnQAAIABJREFUTIkObdgg\nEZuc2Q4qlaSfrVtXvGbV+j5/WVmwZYuoiu3cCTn7oFWqBC+/LA/k3bsXrBdMUeyLiRHVszNnxAFN\nT8/eGcwPe3uRSvbzg3LlCvVVRbbxSWi1kjd+6JD0AgoNlfS9+HhxagpjW2legE1tHjW1OdNQ9mQl\nZxHzawwXP7pIZrw8wKvMVdReURv3oe56tyVTo+HPuDi+i46mf4UKrLh+nX3383FdLCzo6uTETA8P\nahRQMUXv5yU+Xn6okyZlFw/a2Yk+sZ/fYye7wtoSFBnEX+f/wt3enUNRh3CzcyMgNIDopNxS2VUd\nqzK/83z61O+DWlXwnRpDrAmzZiUzY4Y4MjExSTg7F2wSe5wtDRo0YOrUqfTv3x+A9evXM2fOHE6f\nPp3v+4tDaZ9HFYyLiWdWPhlT7kid0yYwrY7UunHoJjlDdEAuU0bUsbp06cfcuX/g5yc794cPw4cf\nBuLk5Mvx448fh7e3d5Gvh7m5RAz++AM++mgJdnYyjnLlZK389dcUypb1xdc3iIkTZWMwv3HoyO96\nxMbG6vV6mJmJWMLMmZE0aeLLoUPhD3rPXbsGK1cu4dVX/ShbVhw0ePz1WJKzk+hjxpHzvnJxkRTB\nf/+FQYNG8dVXq/jvP3FoFi2CLl2CqV7dlwEDYjEzExW3zz8Hd3d/GjeeyzffZDs+BbmvdPegPn8f\nKpU4zB98ACEh0Lv3KN54Y1UuJ0bpSJ2NqcyjNnl2NgzVgb2g4yjO/PO4cZjZmuHQx4G5reaSMD0B\nx7aOaDO1nBt2jpV+K/Mdx9y5c4s8DnO1mupXr6KaMoWuZmb807gx/6tcGVu1mpiVK1m3aBHPh4Rw\n/f5uz5PGkfPhWC/X49gxfIOC4K+/pLjR0RGSkhg1ZQqrXF1zNQzLez10thT0erSt2paKZytydeNV\nNry2gYVdF3Ls3WOMe24cLf5tQV+7vvJv70bSb2M/zF43w8XHhfDY3OfiUffVjBkzHhpzcX4fZmbQ\nr1/2jlZOX/NJv4+c1ynv9Xj55ZcJCAigd+/erF+/noCAgAf3kr5+58/aPKpgHJSIjEKJEhYmjSZ/\n+UUiJmq1FMm/957hJYszMqSepmxZ+PVXyV7IKxIwZYrU9BhJOfSRRESIA7hnj6Qa6LIwhgyRRtvG\nkk1OTZV0+GXLcqejjRwpokamKkNdUEr7TqIyj5oG2iwt4UPDufnDTVBBxfcrUml0JWy9DCsXnKbR\n8O+dO4w4f56I1FQAOpUrx4Z69XDRp455YUlIgKFDZaIGkVT86acSUyCJvBvJsiPLWHxkMamZcl4q\n2Vfi4LCDVHGsUiI25CQ/+eXikpCQwEsvvcThw4cBaNOmDVu3bsXe3r7Yn52X0j6PKhiXpz4io/B0\nUb++RBJu3BCJSY1GCrG9vWW33wBqnA+wsBAnBuC116SB56pVEjXS1al8+qnY+O+/hrOjKNSoIel4\nK1ZI6tf48eJ4rVkjiqbz54t4UHy8jEvfTb4fhZWVXL+QEPjnH7ERxDnt2hWuXy8ZOxQUnmZUZipq\nf10b51edQQvXv7nO0YZH+W/2f3pppvkoLNVqujg5sblhQ6rfz7H95/Ztxly4gMaYXX4dHEQO8uJF\nqFxZNPZbt5auvqNGyUTzww8G+/qqjlWZ23kuMX4xHBh6AGcbZ64lXqPO0jrsulzIrpUmSpcuXWjX\nrh3JyckkJSXRpk0bunTpYmyzFBQKjeLIGJC8IVhTxFg2OjtL/cqECVKzEBIiLQk8PKTRZUnY5+Ii\nm36LF0vx+ty58mB+/jx07Ci1Kk/CGOevbFlxXH7+WdL3wsLkPL74oggJ1K4t/WGuXSs5+8zM5PvX\nr5eIG4hSW6VKkqb2OJ6G34lCyWBq90JJ2mNma0aD3xvQeGdjHNs5ghYuT7lMcJtg0qLTDGpLfVtb\nLrRsyU/16wPwU0wMlnv38umVK/n2vSmx81KzpkwgAwZI2Pn4cdkl+fFHUZPx92fVypUG+3q7Mna0\nrtKaA0MP4Grryr3Me/T9pS9bL2wlPSvduOemAKxatYqMrIyH7IyNjeXIkSN88MEHWFlZYW1tzejR\nozl8+DDx8fFGslZBoWgojowBCQ4ONrYJT8SYNpqZifPw338we7asWbqMgh9+kLSvkrRvwgSJFPXt\nKxGNHj3EKWjTJrt+Ji/GPH+vvSZqaF99JTbmrIc9dEjaMgQGlqx9KpWk5+3cmZ2e17y5HH/1VVEU\ny7v2Pw2/E4WSwdTuBWPYU65jOZr82wSPTz0ASDycyJE6Rzi07RCxf8aSefdhOWV9YKZS0bdCBb6r\nWxdLlYpMrZbpV67gffw4V+7dy/XeEj0vrq4Sxo+MhHnz4PXXpWkZwCefEJxz58tAeJb35OLYi1S0\nr0jcvThe3vAylrMsqb20Nj+czB0ZMqV7eM/BPbRb046lR5bmOu7s7EzlypVZunQpaWlppKamsmzZ\nMqpUqYKTk5ORrFVQKBpKjYyCyZCVJQ2fdWnRDg6ixJmaKilnPj4im2zo+pWMDFE0yxuRefddEdFR\nq8XhatjQsHYUhfh4uHQJ3npLpJ29vaUeqUaNkrdl507ZPP3tt9zHmzQRtTgvr5K3qbCU9txuZR41\nXbRZWkJ7hRK3Oe6h18r3LE/tb2pj6WZpkO+OTE1l6uXLrL15EwArtZq6Nja4lSnDDA8PWhqyy3FB\nyMyUsPm+fRLeX7ECunQRpTMDEpUQxZcHv+TbE9+SkJbd/fiV2q8wpsUYXvB4AQuzAshJFpKi1Mis\nP7WeEX+NIDE9EVdbVyI+iMDGIltM48SJE4wfP56QkBC0Wi3e3t588cUXNG7cWO/2l/Z5VMG4KI6M\ngkkRHy99Sv7+O//XBw6UXX1DF7enpUmKVEgIHDggduVl0CApdDfFgvaoKInIJCfL36tXl03NEqqV\nzcW8ebBtmzTTzLl52ry59Elo377kbSoopX0BVuZR00ar1ZJ4PJFTL50iMy53JMa2oS1NDzQtUDPN\nonIyKYk3wsI4k0M/38HMjCPPPUedJ2nnG5qkJJnkdIpm7u6ycJTADklqZirRSdF8G/wtn+377MHx\n7p7dGdFsBJUdKtPErYnevq8wjkxCWgKjt45m7SmZbH2q+LC+93qqla2mN3sKS2mfRxWMi5JapmBS\nODlBYCDcuyeqVyNHShRk4kRxXjZsgM8+e/LnFBdLSyn837wZ4uKk+L9p09zv+eEHmDkz21kwJSpX\nhq1bRQgA4PJlST+bNOnxPWEMwYQJsHu3nK8tW6BFCzl+9Cg8/7xkiYwY8XAjUAWFZx2VSoVDMwd8\nYnxol9SODpkdaPhXQ8wczUg+ncyprqdIuZjy5A8qIo3t7DjZvDlbGjbEr0oVqllakpCVRYcTJ1h5\n/TqnkpIM9t1PxM5OFoshQySv9sYNEQNYtEgWEANiZW6FR1kPZnWcxY+v/YhHWQ8Atl7YSo+AHjRb\n2YwVx1aw7cI21pxYw+oTqxn460BORp80qF1Hrh2h6YqmrD21FrVKzYwOM9gzeI9RnRgFBUNjchGZ\nM2fOsHz5cszNzbG2tmbKlCkPdiJyouwkPnt8952sWSqV1NSMHCnpZyVJUhJcuSLpWp98kn1c17Ok\nf3/Ti9CcOSPnau9e+buzs9jep4+k0ZUrl7s3gaHRaiXt7bPPJMVMh42N2GltLbVJb7whx415Pp/W\nnURlHi3d3N1/l5NdTqJJEXlCh1YOOL3shEsvF4NKNkemptLl5EnO5XAUZnh40MbBgai0NN5wdaWM\n2gj7o2fPSrg+JET+7uQk6mYtW8rOiYuLwU345cwvLDi4gCPXjjz2fd1qdWNxt8XUcqpV4M9+UkRG\no9Uwb/88pu2eRqYmk6qOVdnQewM+VX0KPxAD8LTOowpPByYXkXFzc2PhwoUsWrSI1q1bP9Rw6mki\nv4ZSpoap25jTvrfflg7yWq1EaRwdRaWrXz+JNGzcmH8KmD6xs4MGDWDGDHEGzM3FvsOHZR3t1w9u\n3TKsDYXB19cXLy+JKH37rdT3xMaKw1ChgqiKubhImtySJVLXYmhUKskIWbtWFOIaNPClfXt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sLCIpfajlarZdKkSbRv35633nqryN+n7CQqGBKNBo4dk3TopUulliUvdnaiSPb++1Kgb2giI6W3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\nsX79ekJCQqhZs2aVrKPiem7ZI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       "prompt_number": 305,
       "text": [
        "<matplotlib.figure.Figure at 0x106f58050>"
       ]
      }
     ],
     "prompt_number": 305
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we investigate the relation between the eigenspectrum of the covariance matrix and the objective function."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "res=cma.fmin(cma.FF2.RotatedFitness(cma.fcts.elli), ones(12), 1)\n",
      "cma.plot(); gcf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=334979, Sat Aug 16 19:21:53 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     11 2.511758723256458e+05 1.0e+00 9.14e-01  9e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     22 1.725102759833351e+05 1.1e+00 9.00e-01  9e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     33 1.626259798120410e+05 1.2e+00 8.60e-01  8e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1100 9.494395695654875e+02 1.3e+01 4.73e-02  3e-02  5e-02 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2200 7.976617072950506e+00 8.4e+01 6.76e-03  4e-03  1e-02 0:0.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3300 3.886491722707244e-02 2.9e+02 1.99e-03  1e-03  4e-03 0:0.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4400 5.941216954216212e-05 9.3e+02 5.36e-04  3e-04  1e-03 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5500 4.267497418922512e-11 1.0e+03 8.45e-07  3e-07  1e-06 0:1.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  549   6039 4.237643567449056e-14 1.0e+03 3.26e-08  9e-09  3e-08 0:1.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Sat Aug 16 19:21:55 2014)\n",
        "final/bestever f-value = 1.740791e-14 1.740791e-14\n",
        "incumbent solution: [  1.73829757e-09  -1.82820382e-08  -1.91544883e-08   1.16836992e-08\n",
        "   8.51305280e-10  -2.91942135e-08   1.71064399e-08   7.23091167e-09 ...]\n",
        "std deviations: [  1.97910522e-08   1.73847321e-08   2.00828999e-08   1.43715603e-08\n",
        "   2.21410481e-08   2.09798162e-08   1.80938322e-08   1.28599957e-08 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "png": 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OjkIwNE3Gp3PnzoSEhPDzzz+TmpqKkZGRUgwgTcd54cKFuLu74+bmhqGhIfb2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E6/vz8zCiNHsmQqJ83eBcnz55yURkbSPW7q1OyfExzMLIVynZ5Kldiz4uzMnhltolCwLPCb\nbyi87t1jtkQbPH/Onp5TpzJ+XE+Pjne1a+fudWNjKTLXr6cQyooNG2gYIHXCw4Hz53mtv3gBHDhA\n6+uICGDxYmDMmMKOUJOi3mxbVD5HBYKPGWFaIBBkj85neAqC48eZKWjcGBgyBPjiCzaiZ2fFmzb7\nkJbISK5l4u8P6Otzwcf58wtW7GQXo5IpUxhvo0YUZDmhdm32qixeDJQoQQe077+nuYGjI3D4cHrn\nsg+NT0lCAs+RgQHFDgBMmKA9sePl5YUyZShIEhNpSjBhAlC+PB8vXhxYvjz3YgegUBs+HPjnH2aI\n1HtkLCxoc92xI38fNoyZJTs7luoVK8ZjbGrqhdGjpbM4rLU18NlngJMTReKaNcDo0V5YtUp6Ykcg\nHXL7OVDQiPjyhtTjA3QjRoFAkDli4dH3vHvHxvNy5TixP3OG242MgE6dVM336r0Uf/zB7Mzw4XQq\nO3KEPSvt23PCHZuN1dbWrexvUTaud+ignbFlRXYxAjwWv//On5cs0exFyQ6ZjBPZb75hFmLBAmZb\nLl/mJL5kSR5DNzfAyip9X0128cXHs7fIzY3CVKEAwsJUjzdvrtlHkt+ox2dgQGHl5cWvqCgKk7xi\nbs7rIzmZa+HEx9MJD+C2fv1oiKC+rk9iIo8xEItlyygs9u7l9Sk1UlJiMXJkYUchkDI5+ZwqTER8\neUPq8QG6EaNAIMicj76k7a+/OBE/cIDuY6VLs7wmOVlzv08+4d306Gh+nToFnDuX+eu2aMF1S9Tv\n7CckcEKfkkIhYG/Pkra5c4GJEz94CFpl82Zg0CAej1at2MCf1zVjDh4Eli3j8XvxQrXd3JwLrL57\nx8VWe/fOWDC8fs2Myvbt/Er7f6hkSZ5TJydmlrS1xo1UUCh4LO/f5wKxiYkUga9f0wnu4kXVvoMH\nAzNnMhskyJ6iXoohStoEAt1HlLQJBNnzUWd4fvtNVfakRDkBNzNTTaRLluQd8ipVVPulpPCO+fjx\nzFhUrsyJZ0gIHz99mhbIMhkduN684XZ9fT5X3a65f3+tDO+DSEqis9nBg8w+/fcft3fsyKb5/BAP\nn33Gr6QkHtexYzlJj45WZiU4Mf/uO5anVazI8wGw/O/gwfSC1MgI6N6dz/vkE5Z0SYmICF4bVapQ\nhOUnMhlNDZo1S/+YqyvFz4gRNDn4/Xd+1ajBBWO//JLrA1lZ5W9MAoFAIBAIBFLho+3hiYxkKRXA\nvof//qMoOX6cAiYmhr8HBLDhXF3sACxD69mTVrz37gEPHgAPHwLHjtFhzdGR+ykUKrEDcKKuLna+\n/Tb9axcWUVFAmzYUGVu2qMRO06YsqapUKX/fz8CAvVBXrzKT9OuvtGhu1UolOFesYM/QmDH82r+f\nx7BcOVp2b95MYRYRweb3nj2lJXZ272bPkrU1e8BKlqTYaNWK7m/Tp1PA5XW9nawwMWF/2F9/URTp\n6TGzeOAA7baVWTBzc6BPH/YhJSSkF5WCoktRcLssDDc/MQ4xDjEO4XYp0A0+2pI2ZXZHT4/ixsQk\nf+NLSQGOHQvHgQPWsLXl5L5SJa7L0rIlRVa5cvwqTMLDw2FtbQ2Ai4r+8AMnvgMGcAxPnrD8rFq1\ngo0rKYnlagEB4YiPt0ZsLCflMTFArVosA8xoocuCRv34pWXhQmYAc0K5chyvk1M+BoeM44uMZJZn\n3TpVRk0dY2OVmUTFisyc3bhB4wNzc2bkvv02//5msjqGhU1RL8XQlZI2KV8jgIgvr0g9PkDaMYqS\nNoEgeyQwZSx4jh1TNbKPHp3/YgfgZHzx4qGYP5/vNXo0IJezmb1XL7qdFbbYAYChQ4cCYHZq0SJu\nmz6dgtDHh1mAghY7AAWiiwvw5MlQrF9Pg4ctW1hGOG+eNMQOoDp+6qSkcMFSdbFTpw57al68oLnF\n0KFA/foqA4inT1ladv689uOztKRb3qVLwNu3NKJYupQiqGFDTee8sDBg1SpmOpVleePG0YVuzBj2\nW2kjRoFAHalfIyK+vCH1+ADdiFEgEGSO5Hp49u3bh4MHD8LQ0BATJkxAuTyqguhoTuxKlGCfzdOn\nQN++zBS0b8/yM23h6emZ+nN4OCe8xYtzfZiHD1le5OhIe+GsRFdsLHD2LFCzpsqdK6+kpHD9mClT\nPDFzJo9DQgJQqhSFhlRQP4ZSJG18e/cy+6RcN2fePIof9d6nDh00HfliY9l3dOoUMzwTJwJ169JY\noEGDvJXoZXf8LCwofpS4uPCGwNGjvOZKl2Z2p149ZtaePGGZXlgYRdKBA8z4tGqlKuPM7xgFAqlf\nIyK+vCH1+ADdiFEgEGSOpATP27dv8ffff2PZsmW4c+cO1qxZAw8Pjw9+vdev2Tfx4AF/l8lU/TMV\nKnBy+j4LnMq7dyw7e/uWjfVmZiqTAX19zX3j4mjZXL8++11OnuS+AQF0zLK2boTOnTk53L07fXxr\n1/K7qSnQuTOzQJ06aU6OZ8wApk3jzyYmbDJPSWFm4O1bToZdXDiBVmYLkpIYb3g4zRPatQNu32YZ\nXdmyvFM/cCANAABVGUvNmrQ3lkLmSYmUy2wAVXxJSTyHx46pHpsxA0hTXp0hZmbAnj08T8HBmiK8\nTBmWxnXqxKyWhQXPaXQ0ULVq9uv75Pb4GRpyHJ07Z77Pr7/yeh4+nL1Abm7c3rEjr9V27XL1lpI/\nx4LCR+rXiIgvb0g9PkA3YhQIBJkjKcFz8+ZNODo6Qk9PD/b29ghTX1Alh9y5A/z7L0WEr69K7FhY\nsCkfAD79lAs1btvGJv0aNbj9/HmKnIgI/q6vT5vf588pICpU4Ova2PDr2DH2Q2RGRARw65bqd3XB\n1b07+yciIiiy9uzhV7lyvFsOUDSpWwrHxbHvIi3r1zMzU68eTRQiI5mtySmWllxY9Pvv06+Do0uk\npDC7EhXFc7dpEzN5w4ezTM/QMP/fMyqK6+D884/m9rp1aciQU6ytaS3988+8rkxMeP6fPwe++irz\n5331FbOXlpYU93J5emGe3xgb01mwWjXgp59obnD8OEv1jhz5cOEjEAgEAoFAoA0kJXiioqJgobbw\nikKRcz+F6Gja7n73XfrHfHxUjlj79lHY+Pursja9e/Nu+bx53N/cnHfdX7wAnj1Tvc6jR/x+5076\n95DJKIIMDZlF+fxzurddvcrFL0ePpiiZOZPN36VL8+7906c0MyhXjouaPn0K7Nih+dqVKtFRrnx5\nTqwvXaLxgZkZHeB276ZwUs8uZEe1alyjpWlTltnlVuikpLCcKS6O2aWSJXP3fG2wciXX70nLnDk0\nBBg/nkI3r8InLIxCqmxZjv3SJdVj3boxS/YhwtHMjP00SuLjgV9+AWbP1txPT4/HH6CoU8famufU\nw4PXnTZp3JjufQAQGgp4elJ8K4UPQFvswYNZqpebBWsFAoFAIBAI8guttH7v2rULI0eORJcuXTB1\n6lSNx5KSkrBkyRLI5XL07NkTS5cuRfJ7/1sLCwtER0ergstBZ/p//7EXp0QJldgxMWE/QfHiFC/D\nhrEXYudOZj4iIlSZluRk2vUqxQ7ASdzTp8Dhw8Dff1O03LkD+PlReLRvT0GjbtiiUFAgPX4MXLhA\ncbVliw+Sk7nGzI0bfN8VKxjz+vXcLzmZjeCnT2eelQkJYWnUt99ygn3qFCf3CxZQzD17xp6L+fOZ\n3Tp+nE3xAwey5G7bNk5Ab96kCLt+nZmnrl2B3bt9cjw5VyiAxYtpuKCvz2PQty8n/i4ujCW/7ZXT\nWmBmRkICMGuW6vfBg5ntWbOG4vLuXV4fjo48PgB7Z3KhqZGUxHKzqlXZz1KiBHDpkg+srWn7/PIl\nbbPzK0tmbMwxPXvGWN+84bX5/DkFz5YtzCJ16kSRo6fHMsYDB7jwrYsL4O6es+OXV+zsmH28coXX\nnvJPd/16/r00aaLKnKYlp+dY8PEi9WtExJc3pB4foBsxCgSCzNHKPVdra2sMGjQIFy5cwMuXLzUe\n27hxI65fv44NGzYAACZOnIhNmzZh0KBBcHBwwB9//IGUlBTcvXsXFXKwHLzSbU2duDjNu+5KbG2B\nqVOZKUlO5mKLp07RncrampPiMmU4OdPTY2mOEmdnCgclpqYsRbOx4Vom58+zNO7ePVWmJSkpCNeu\nDcO1a5z4KZHJgNatKWTs7FiCZmPDEqaHDzVj1tcHHBz4um/fco2cIUNYwtSmDR20ypfnpNLUlBms\nFi04AT53jgJl715mwPT1ede/Vy/GaGoK7NwZhD59hmW6GOazZ5xAm5hQ+M2Zo/m4slRwyxZ+TZpE\nQdC5MyfmiYks34uPB7p04XFWKPh7TtzxgoKCMGzYMCgU7I1auJDjGzGC2Q0DA5aUffMNRSrA46i+\ntpGLC+OePZs9Mm3bqh6zsWEZWOvWFKuHDrGs0c2NYlnZo/LgAa+rx4814zMyCsK//w5DgwbZj+VD\nKVOG301NaW6gxNmZX0qePWOWcMoUlkJu2QIAQUhIGAYvL+24EaalXj0K3zlz+Pfi58cbB5cv85pY\nupTZHvU+NeU5FggyQ+rXiIgvb0g9PkA3YhQIBJmj1XV4NmzYgHv37mGGWhe2s7Mz3Nzc0Pb9rDMg\nIAArV67EFs7OsGfPHvj7+8PQ0BDu7u6wzcSWTLl+BHAB6o33OUFfP/NFFS0tmbX46isKivv3mf3J\n6OaOsTFLqJycKApu3eLkLjY2V+EAYNnarl18rdxY/ZqYcK2UOnU4ufwQTEwoBps0YbbA1ZXZiokT\nWV6XNp6vvmIfVKtWLI07f57HaPv27N+rdm2WBkZF8eemTZktGTECmYqulBSKFnXBmRFGRizT++ab\n9I8pFOzlyagHKjMyuk5KlaKgGDaMoqJuXWmU86mjUDCL5e3N7CVAYTdhAsv61MVGQRAcTEH5+jV/\nt7JiBq56dV47yck8N1Ls+Snq60foyjo8AoEgc7S1Ds+9e/cwatQonDlzBmZmZhgzZky6hU5zQlH/\nHBXoBgVaVR8VFYWXL1+ievXqqduqV6+OFy9eIDY2FmZmZpDL5Rmu8JufZLWCfGQkxU1GAsfcnJkS\nJfHxKge1jKhcGRg5klmCp08pLB4+5ES5VCnenX/7luVoISEsFVPSvz8nrU+f0oktJibj94iL4+ur\n9xXZ2CB1oc7atZnBGDOGr7VmDfstkpOZtQgK4mvcv8+vbdsYszqmpow9JYXZkd9+4zYlTZrweSEh\nfOzhQ5ZWBQez30XdrCE4WPW869f5BbBZ38mJoufePWZZ6tblY+vWqcrQlJk1QNUHdfUq36N5cy6S\nunMns2DOzjxfEyfyOcbGzPCdOsXn9u3LjM2KFcCrVzxfxYvTbS8mRnWdWFrSHc/BgWJQ2WamnimS\nEjIZY2vblkJ8yBCWW7q70xhj9mwKkIKidm0eUy8vZlPfvNHsVQIoloOCsnedEwgEAoH2SU5Ohlwu\nR58+fbBv3z7cu3cPnTt3RoUKFeAipbUrBIIcUqDLN757P1M1V/OCVt6JiP2QtAgAoBsAeZqvlgDS\npjv83z+miaGhGwCqG2XpEBD0ft9wjX2joz0AeAGgYGHooQDkMDS8iY4d2eOzeDHQu7c3unZ1x08/\nUTz9/Tfw55+xqFBBjnHjAjF0KLMjXboAcrkvzMxcNd5r2zbg6VNnAH5pxE7G4wBU43j5khP26Ogg\nnD0rx5o14fD0ZH9Pjx5A9eoeaNrUCxcucBJMV6/Q9697M/UVzcyAZs28MWiQOwIDKYj27AEUiljI\n5XIEBgZqRHDypC8eP3bFn38CBw9SWCkUQN++zti+3Q+nTzPr4OoKdO7sD3t7OWbMYHYrJYWiZs8e\nN1y/7oMFC7ifqytw/DjPx5Qp4YiNZSbMwwMYPNgDX37pheXLGevx48DVq6H45x85XFxuQk+PAmbl\nSmDDBm+sXu2OGTN4HDZvBlxcYuHjI8fixYF49ox9VP7+wOrVvujQwTXVvGLXLoqiEyeccfiw5nXl\n7++foUB3c3NLV/MdFBQEuVyO8HDN68rDwwNeXl4a20JDQyGXy3Hz5k2N7d7e3unusMXGZnw+fH19\nsW2bK65dY0bF2JjHqE0bZzRu7IfQ0IIbB3AT69fzupw/HzAz80aZMu6YPJllcPHxwM6dmY/D1VXz\n7wNgttjPL//Oh6+vL+RyOezt7VG7dm3I5XKMHTs23WsJBAJBUefWrVu4ffs2PDw8oK+vj5o1a2LY\nsGFYs2ZNYYcmEHwQBVrSFhUVhZ49e2LTpk2pC4o+evQIgwYNwr59+2BmZpbj185LSVtWGBqyz0TZ\nD5JbjI0pYj75hHer27dnn0lICCd627fzbntmWFmpMhNmZpwIVqzIyfiVKxQz6pibs08mPp6/q2dT\nMsPMjCJD2cME0NThwQNmnDLDyEhlzV2sGONKSWFmpUsXoGHDbA9Phjx4wL4iMzMaKVy4wB6qx4+Z\ncUtKYjZm5sz0Dmvx8RSOjx8zpkWLmClYtUq1T4kS7POxsGDjfEICS/WUx8zEhBmPMWNoxKAkOZnH\nsqi4iz16RNOFdet4TEuWpCmCqyuv24IkJUVlbPD4Ma/trl0LNoacUNRLMURJm0Cg+2ijpO3atWto\n2LAhYmJiYPTeicfDwwPLli1DRGYONJlQ1D9HBbqBVjM8sjTNAhYWFrCxscEdtfqru3fvonTp0rkS\nO5ooMzy+atuYGdEk+8wIQPHw9Kkqw1OqFLc3bAi4unrg+++9cPcuS4X+/Rf47bdQfPqpHB4eN1G5\nMifRe/cCY8Z4o3Pn6jA0ZJ9Kjx7A8uWxePFCDiAQ1atzwdIGDQBDQ18ArmjfnpPSVatosR0Z6Yze\nvf0wcybf6/lzYOZMf7RuLUdSEu2tX71i2VjlyhyHQsGJZI0agImJZqaqeHGKldhYD9y44fVe7Mgx\ncSKwe3co2rSRY8WKm+jencJJJgOMjb0BMKOQkMAsz/XrsTh7Vo4dOwKxaxfXYmnUCLC19UXr1q6p\nvRqpZyOLO/EvXtBi+8oVirolS9xgY+ODZcvoMGdvL8f27UG4cUOOyEhVRuH5c+CzzzxQubIXHj9m\nidqdO8Cnn4bi8eapK2MAACAASURBVGM5/v33Jry8gD/+4DGtW9cbMpk71q+n2cGJE8CIEbEwM5Mj\nLi4wNfs1YADw++/MKOjra4qdjMbRokULSWd47OzsUn+vUAFYvRro3NkZ5cv74dUrOtfZ2wM//OCP\n7t0LbhzLl6vG8d13cnTtmvU4CiLDoz4OFxeXjyrD061bN8jlcvj6qj5HtXl8c3u9q7+nlK4T5TiU\nr5Vff7f5PQ65XF4onz85HYfUP0ddXV3TxSelv4/cjCMtmY3jp59+QuXKlTFt2jQkJCTg+vXrWLBg\nASLTLD4oPkcFuoJWMjzJyclITk7Gxo0bcf/+fXh4eEAmk8HQ0BDr16/HqVOnMHfuXCgUCvz0009o\n27Ytvv7661y9h/LO5LJlFzB6dKMc2wvb2PCOflgYBUBUVOYZEUdHioeLF7lOTmQkJ8SdO3MNkthY\n2k0bGdGFbe/etK/gD6CLxpZp02glrCqf4x3uFy/YxH31KkvB9u5l30lcHIVG1650kVu7lpmQX39l\no7869++rytkePOCaMF5ezJicO6fKaGQUY+XKdKUrX57ZjkaNOPaTJ+l417EjX/Pvv5kdSEykWIuL\no/Dat0/1ijIZjQiqVWOsFSsyg1CvHl+3YkWOLTCQ/SWvXmV+vipX9kfv3l3QoQPfMySEPT7Ll2vu\nt3Bhxo592aFQUGzNm0dXM+X6Nt9/z6yVoyOPSWb4+/ujS5cume9QyGQW34sXwNixXNdJefyNjGhs\n4O7Ov43CjlEKFPU7k7qS4ZHyNQKI+PKK1OMDpB2jtkwLgoODMW7cOAQFBaFixYro0aMHVq9ejWfq\nCxTmgKL+OSrQDbQieDZs2IA//vhDY5ujoyMWLlyI5ORkLFu2DIcPHwYAdO7cGW5ubjlac0cd9X/U\nr141wqefqiarOaFqVdobf/UVS9imTKHDWm5eIzPatmXJ2MaNqm2Ghlx8dNgwCpvkZGZt7txhCdbl\ny2zoz+37W1nxDv25cxQSISGqx9q1Yy+NiQkzIu7umjFlhdJuWh1DQ7q59etHYwM17wncu0fRsW0b\nDQtyg0zGtYkcHOh6FxBAx7uc0Lw58OOPXDyWvUgfzrFjQJ8+0MhQGRuzB0suV5kVFCViY9njNGeO\n5jo5Tk4sM2zaVJruaQVFUf9HrSuCRyAQZI62BE9aJk6ciJCQkFRX3ZxS1D9HBbqBVkrahgwZgiNH\njmh8LVy4EACgr6+PMWPGYM+ePdizZw9Gjx6da7GjTrdu3bB0qRwTJ/qmTnhr1nSGjU3WJW3377Nx\nvXt3N/Ts6YOBAykKmHlhKZixcThatGCj/cyZQK1aHjAy8krzuqEwMJDDxuYmxo6l4AgIAJo29YaL\nizscHLhXYiKwcGEs6tSRw8oqEDVqcBI9fjywaZMvrl1z1RA7VasClSo5o0YNP3z+ObM1Li7A3Ln+\nsLNTjePNG5Z+paS4ISREM2UeEBAEU1M5ZLJwdOzIzNGwYYBczmb/mBiKmqgoYP36UFSqJEfnzjdR\nrJhK7FhYeKNkSffUMYSEAL/+GosaNeT45JNAbNnCvqTp04EVK3wRHp4+ZZ5ViaGpKYXSgwcs43v8\n2A1jx/rgv/9oFDBvHtC6dRAsLOSoXTscbdsCX3xBF7eePT3Qu7cX+vZViZ28pP7bt2fv1vjxvihf\n3hXGxsyKDRzIzGDlys5wd/fDnTsqYZpRCYNCAQwZ4oZ+/XwwaxbL5xQKaZYwmJnxGvzzT380bizH\n+9Y6nDhBgdy+vRscHX0wciRLLc+dA86dk944lIiSNkFRIyHhBV6+9ENychyePduI5899s3+SQJAb\nvvuOdxvTLDR39epVxMTEICEhATt37sT69esxZcqUQgpSIMgbWjUt0CYZ3ZlcuJCTtzZtaPXs5EQx\nANDiODKS/RwKBSfICoVmRsXAgL0vMTHQcLDKCdbWFCSdOzOrcvkyJ40Ay9+KFWN5WFKS5vPq1GHp\n2M2bFBQAS968vVVN3WFhQM+ezAa1a0ehtG8fx2hiwnI7mYwZEjs7WlrHxHC/tFkaJUZGLCf7+mvV\nQpCPH1N41K3LPpc7d2jjXLIkfz51ii5fDx4AR45k/Lp2dsy2fPIJx+/nx7EpMTVlz05mz1dSsSJL\n6ypUYClcy5aaGaWCICGBrnubNqVfW8nBgedVX5+9WL17U6QqFzZN29PZvTvPR/fuFE/ve0AlR0oK\nSydnzWL/U0a0bMlSuKKY8UpLUb8zKTI80iUy8hSuXeuJxMSX6R4rWbIbHBzWwcioTAbPFHxs5CnD\nExnJCUxSEj/8q1VLfWjq1KlYuXIl4uLi4OjoiPnz56Nly5a5jq+of44KdIMiJXhCQ1lKJpOxF6Z2\nbTpQ/f47y7Hc3Dgx/eILVdmVnh6/0gqRjDA0pCB6/ZoT8kaNKKAOHMhsbR8/AL0yfK3y5SmQ/v2X\nPTJpqVKFpWNNmgALFqiEW3ZYWTFTYW3NvqKs1hxSxtiqVS/UqgX4+nJi36oVJ/F6ejxeHTvyeC1b\nRkEzbBgF3Zw5FEHx8ewJqVePZWHqC3EqFOzxOXOGx69jRx678HA6hu3Yobqp1K4dS9k0y4NVx7B/\nf+CXX1jCV5AoF/Lcs4fH6OlT9b4vVXxVqzJzqKRmTQrdixc1X8/amq5zFhbAt99SlDo4aMcpzc/P\nD716ZXwNZsfZsxSuJia8JiIjKdoTEngOly6lEM/rQqZ5iVHbFPV/1LoieKR8jQDaie/mzaF49mx9\npo9bWXWEo+PhHL3Wx3j88hspx5gnwbN9O/+5OjiwKVkLFPXPUYFuUKDr8GgDdXchOzuKGYXCGc7O\nLHVZu5Z9OomJ/li8WI7PP2f/yZAhfH5KihuSknxQvrz6oocZr8OTmOiB4GAvPH3KyeBffwEdO4ai\nYUM5+ve/ifLlVXf8Gzf2hq3tTwgIYJaEbm+x7183EI8f03iAYscXFSq44tYt2iobGzOLMm+eM/r3\n98OZM5w4z50LNG3qDzMzOerX57iaNGGfReXKbpDJfPDmDbMqa9cCyckcR48e4RgyhCYHkyYBBgaq\n9YQAX5w8Cfj4hCI2luulnDzJ8qUVK4DOnb1hbu6OGjUoUEaMAPT0YtGlixxt2gQiNJQC5eVL4Oef\nfTF+vGbpkUwGzJzpDGtrP8TFURT07w+MHeuPv/6Sw8aGInXoUGasevd2w6xZPvjjD4qCsmV9UbMm\nx7FtWzgcHJghWbGCJW1ffOGF//7j+Th1Cjh9Ov9LqJQLeYaFOWP5cj9ERDD74e4OVKq0CNbWcujp\naYqd3r3dMGGCD4KCGNv48UCFChxHeHg4Vq2iTXm1aoCjowdMTLwwaxZNIID8KwUbl4GTQ05LwZo1\nAwYOdMOcOT7w8+P5OXwYKFUqCGFhcvTuHQ5bWy5m++oVz0enTl6pVuc5HYfSGUyUtAkyQ909Tork\nd3wKhQKvXzMNXrXqXLRuHYlatXxRpcpslC3Lv4U3b47g1q2RSEx8k+FrREVdwJs3/6XGp1AoEBNz\nEwpFPjSq5jNSP7+AbsT4Qezfz+/du6d7aNmyZWjSpAlMTEzQu3fvXD8uEEiJIpXhATjprFuXLmBr\n1zIboVDwzvyECapsgrExnbhq1uT6K7GxzI6MG8fn3rsHPHzIngUldesyw/HqFXtZ0q7VY2jIsqsb\nN5hZat6cmY8qVTixTUhgud2iRYwlJYWT6Y4dWcbWqxezKuHh7Gc5fJjZJCsrZjayuwGbkMByuitX\n6IBmY8P3nTxZc/2aqCiu8zNpEjMsacve6talS9fDh8CTJ1m/Z716qq+WLSkMMrrjP3s248iK1q0Z\nT+nSmtsVCk62Fy/OyAkvPd27U/QV5Po54eEUwKdPU6ipr+ejTmwsMyNPnrDX68oVzceLF+d1Ub8+\nsyqWlsyw9OpV8CV9mfHuHcX2rl2Z7+PoCAwa9GHOeVKiqN+Z1JUMz8dGePg+XLvWA3p6ZnByegF9\nfc079mFhC3Dv3o8AAJnMGPb2a2BgYImQkFmIjr4IA4MSqaVwtWr5okyZAbh9+3948mQlAKB48Zao\nV28fDA1LQqD7fHCGJzmZNfEvX/KfbPv2Gg/v2rUL+vr6OHToEB49eoRdaT70s3tcSVH/HBXoBkVO\n8AC0Yv7pJ0549++nvTDAv+1Nm2hpfPYstzk5sfdn4ED2qQDsrxg1iiLj8GFaUb97p/n+MhkbvmNj\ns1/oUx3lczKiVClV70e9esxEubnl/LU/BIWC4u3gQbrIqZf2OTnRAS0khBPxrl3Ze2NuDmzYkPGE\nd9AgCjr1srZTpzh5B4CyZVka9e4dP1s//ZRCbfp0TvQNDYHdu2lKkJFw2rsX+O03ZpUiI9kTdP8+\nBZy+vir+unWZ7fv8c2bBpEhcHIVpbCyF0saNLJHMCD09usUpM5OFjUJBMe/ry3P35g2vkVateC0p\nGTiQfW3durGUT9co6v+oheCRHklJUThzpgYSE5+jXLlvYG+/OsP9njxZi7CweXj37k6Gj6tTsaI7\nwsLma2yrVMkDVap45kfIgkLmgwXP6dO8U2lpSdGTdmXv93h6euLy5cuZCprsHi/qn6MC3UDnS9oy\n4ocf2P+SlMTvL9/3fOrrc0J++jSwcyfvnJ84QYMSX1/ua2bGCfjChfwcsLZmBuT6dZam9e7NGyIK\nBY0B0oqdkiVZCjtgACfzzs7M9Fha8nGl2KlZU2VJPWwYJ4vqje5Xr1J0jRrFyby2kMmAypXZSxIS\nQoE3ciS3nzjB8V69yv6VcuV4Z9/Hh8fr4UMKkNmzuWgnwFKvUqX4/EqVKDo6duRjgwczK/biBSf2\nR49SmE6bRhFTogSNG7p14889ejCrs2QJTRqCg3k+1qzhObx1iyWBr1/zeTExqvN67Ron4s2aMbN0\n6BDPlfJLCpiYsEdGLucxfPiQ4xo/nq6Azs68XkuVohh0daV4U4rKc+cKbywyGR0Nx45ln+vu3bx+\nDhzgNe3kxP3+/JPn3d6e5y0hoXDiFQh0hdev/0Vi4nMYG1dC9eqLM93P1nY4mjW7CVPTGqnbihd3\nQo0ayyCTabqiKMWOvr45LCyaAgCePl2DlJRELYxAoDMoy9k+/TRTsSMQFBV0XvBktEL4wIHO6NfP\nDw0bAm/fsldCvbZfJuNE/uhRwMjIDUFBPqnN+VFRwKxZQZDJ5Lh6NRxOTuwv0dcHZDIPNG/uhdBQ\nTsB/+w2YM4d2zo0bs0fh1Su6kt27540qVdyxZQsnsa9fA6GhsXBykmP58kBcucISpYYNgU6dfNGj\nhysCAigAvv8eGD4cANgzUro0F/wEtLuS87ffymFrexOrVrHRvk0bAPCGj4871Fsl9uyJRZkychw5\nEojPPwd+/pmCaOpUX1hZuaq9JgVIXBxtqZUlbebmwPXrmuMYOpRr8ZQv7wZ9fR9ERvIYjxsHjB0b\nhB495KhTJxytWlF4VasG9OnjgblzvaCvz/NjZAQ0bhyKtm3lmDHjJpo0oSCYPRvo0sUbenru0NOj\n81vnzkDr1rGoVk2O2bMDNfpvCmvFdn19iuNffwW+/po9VT//fBPPn1M0AMCFC97YuNEdP/xAMde6\nNRAcXLi9L6VKUbQtWsRxNGzIzFVAAODqGgpDQzlevbqJkSNZSurmBowaJWypBYKMiI6+DAAoUaIj\n9PVNs9xXJtNDrVobYW3dB9bWfVCv3j6UL++Gli3D0LjxBbRrl4Jy5b5J3b9Spalo2DAQhoZlkJDw\nFE+erEJCQi4XThMUHZQrhmdWgy0QFCGKZEmbkv37+Xesrw+sXs1MSvrX4c2Nhw/5e/36FCj37lEo\nqVvzurnxzruVVcYxvXnDcrq5c/m7np4rRo5cj0mTOMnOLatXM/OipG9fZgRsbVmmlx+uXq6urli/\nPmMnoJgY2mNfukRHMQcHZrDGjqWQBCheatbkti+/ZOnVrl0UGqdO0bXt8WNg4kTukxPCwylSIiOB\nLVtcYWW1HgkJzICZm2v2HBkZsb9l7lxmlNSXdEpJofnC4cPMQGTnWNejB0XEl1/SXCEnZHX88pt7\n95ipOnWK2a7gYM3yyM6dOYa+fZG6nk5BxpcZERH8W0qjsTFvHksmhw4t/Bgzo6iXYuhKSZsUruOs\nyM/4rlzphlevDqBatUWoWDHvgjs5OQ59+lTHTz8ZoHHjczAyssGDB54ICZmeuk+DBodRokTHvL1R\nUhL/oA8cADw8mKLO4WrQUj+/gLRj/KCStkePaLcpk7HsIouaY1HSJigK6HyGJyu6dWPmIDmZGRNP\nz/T71KzJ8qf//Y+/X7nCiXndurSz3r9fZRawfDknkl27srzo6FHN17KyolXzsWMs6UlJ6YKVK5Hq\ncJaSS3OckSM5oR01ip9Jf/1FASSX8/Xv3s3tEUlPF2WDUwYUK8aM05YtzGaNH89xnzxJ4QWw3C4o\niGVWBga0lo6MBPr0Yabi/HmWseXmRrm1NUsKfXyA337rgkePWJaYlEShFRlJ4Vm8OEuktm2jQJHL\nuZ+ybEpPj+d1xw6ek2XLWGK1ezetvn/8UVPY7N3LskV7e5pKLFpEIXz1Ks/rwoWaTmzZHb/8plo1\nnv/ff2c5W3AwzQGUHDrE7KCtLdChA4VemzYFF19mlCpFQfrkCYVs377cPmECrycbmy64ckW1DpVA\nkJaC/Dv7EPIrvsTECLx65Q8AKFny03x5TX19Ezg7z0OLFg9gZGQDALCzc0exYnVT97l1a0Smbm/q\nJCVF4t27+xk/6O7O+uPbt1n7XK0a73LEx/PxzZs1G/zU6NKlC5JjkvHc9zkeL3+MuEdxuRtkASD1\nazDXKMtGWrSAomSpLHeVZbP2QHaPCwRSoEhneABmGjw9aUAAcOLOcrH0+y1ZwhIqmYyTSQcHPvb8\nOSdnhw+nW4gY7u68U50Rhw/TCEBpbV+tGkuThgzhjZXccPkyMz5XrjADpcxWmJtTTLRty4bx3Njv\n5wWFgiJi506uJZTGdRgNGlAkdO2qvRji4ih2Jk3SPC9mZjwn//tf9mvEJCbSACEigssRnDqVXsiq\no6dH+/Lq1ZkxbN0684xfQZCUxGOwcSPH/fffKmtrgKJw8WJec1L6n7RoEQW0eg/SwoXSc3Ur6ncm\ndSXD87Hw+vVRXL7cESYm1dCiRT7c0cqC+PgnePx4BR49WoiUlHcwMakGe/u1sLBoiAcPpsDauhdK\nlOgEhSIZoaFz8erVIURGBgAAjIzKw8zMAaVL90O5ct8g4c09GFVyhCwqBskGRkg0NoFJDMsAFF27\nQjZlCuDkBAVkiNpyEWbd6sDAQtNGM/jLYLzwfZH6e40VNWD7rW3qZDp5zgLcn/caevbVEV+pIWTG\nRqg4viLMG5hr9TjpAh+U4ZHLeZdv1ixcOtwNBsUNUHVuVZjZm6XukpycjMTERMycORNXr17Ftm3b\nIJPJYPR+5ezsHldS1D9HBbqBzmd4MurhUa/tl8nYvN6njz8AOWbO1My0KGv7ZTIKB7kcUCiC0KqV\nHM+fs7a5TBneVR861APff++FlStV5XHz54fC0THjdUYOHnTH5cssq5LJgHv3YjFtmhx2doGoWpUZ\nqE2bgPXrs+9RaNCAa89Mm+aPVq3kaN6c+0RHM9vRpYsbbG19sGcPJ/DJybnv4cnNui89e8phaBgI\nb28KutevgUmTfNGggSsMDSnQevakwKtTxxmrVuV/r8WcOR54+pQ9VRs30gEOYO/LqFE3MWVK9uP4\n4gs5QkIC4egIzJqlNG3wRfnyqvOhLB00NnZGSoofrl2j7XWPHkCJEv4wMpJj6FD2LH3IOPJyPgwM\ngF69YmFoKMe4cYGIjmZWysUFMDDwxdu3rhg6lFmzmjVp0NGkiTO2bdNeL1JOxmFg4I0vvnBHgwaq\nbbVqiR4ewceLQqFAbGwwAMDMzEHr72dsbIuqVWeiYcMTMDauhLi4e7h8uQMCA63w+PEyXL78CaKj\nryAgwAAPHkxJFTsAkJDwGG/eHMbt298iIEAP9xbWgCwqBtFljXG8xiKcjt2J02Xn4yEGIeXAv1D0\n7YdQDMBZbEDQgNc4V/044kJUd2aSY5IR7qf5d3jnf3fw1Of92g9hYXg86Twev/kEYWcq48W213i+\n8TnONzqHK12vIGxRGIKcgnBMdgxBLYPw+uhrrR8/nebdO96pBPDO8TO8OfIG4bvDoW+uWYI4Y8YM\nmJmZYfbs2di7dy9MTU3x2Wef5fhxgUBKFPkMj5J371jq8+YNy9S6dct4v4cP2ccTFcWMyZIlmdsa\nf/cdxQzA/glvb5ZDZcTmzczyZ8b33/NOfG7uwp84wRKtiAj+rL5mTtmyzK6MHk1jhIIkNJRrG6nP\nRY2NKczatGEZVn70H2VEcjIzBRMm8Pfq1VkGV7w4jSocHdnzY2aW9esAQFgYTSjq1+d5UShY3nb+\nfMb9YMbGLOnr2ZMlZQ4OhZtViY6mA96aNezHUqfU+wqGYsV4fZcowTJEa2tmIktlXeGQbyQlsUdM\n+SesJ7FbMEX9zqTI8BQ+CkUy7t2bgEePFqZuq1DhB1SvvqDAYkhMfIVbt4YjPDzzxbWKF3dCiRId\nYWxcEbdvfwtAdeew5kLAdi9wouo0JN7voPG8CtiOMjiEC1iT7jXre5ui5KjmePHXCwT3C4ZJVRNU\nmloJt1xvAQD0zfXh8LsDrBOPInCAGZKRs2yOQUkD1N1dF1atCzH9XoDkOsNz4AAnQRUqIOS7QDyY\n/ABWHa3geNhRY7dly5Zhw4YNuHbtGrp27ZquRycxMRHjxo3D5s2bIZPJ8NVXX2HRokXQT9O7VdQ/\nRwW6gcSmF9rD1FTldPXtt+zRy4jKldmrA7BXpWPHzPddskS1mOahQ5xMz52rWgtG/U71l1+yV+ju\nXYqfP/9kX6etLR9fupRr78yfz3K67BrsAfbxrFzJkqa7dylulH2Hz54B69dzMrt1a+avkfZuen5g\nZ8e+mZ07VT0l8fEs/2vRgsfY0zP9JDw/4tPX5/t4elJs3L3L83f3Lo/tV18BTZvyXGRHxYrMrClF\ni0xG8aPsC4uKAg4eDMSRIxQ68fGAvz/NLWrXpqFCt27MDma29pI2MTcH+vQJRFgYS+kHDuT4LSwo\nkiMiVE56Pj5csLV5c5o/TJ/OXpvBg9OXceYnBgZAXFwg9PSkJ3YE0kEbn1P5SV7ie/x4mYbYAfRR\nuvSAvAelRnbxGRqWRJ06O1C79laUKNEZRkZl0zxujXr19qBKlV9gazsCTk4RaNcuGU5OEahbdzcs\n37XHb5/1Rsyj9gCAld8CG4fyuY/QB/fBOnJDGz00qrco9XWvjI5GaPPF2NqP/6RszINQTm4Mp9dO\nMLI1QnJ0Mq5/cR0nh1pS7MhS0NJlB1pgANqhA2oiY1GY9CoJVz67gpgbOfgnk0Okfg3mivfubIru\nn+P55ucAgDJflUm3W/ny5TFt2jSMGDEiw5eZOXMmTp48iRs3buD69es4fvw4Zs+erb24BYI88FFN\nMaZPZ1lPWBjQv7/mIpvqfP01b4CUKMFJ7aefAsePp9/PyIhZi+BgZnji4mjR3KABbZ3npWnuqVOH\nd89dXDjx9PRE6mTU0JBr/UyYwP0sLXM32TQ1pWh6+ZKTaz8/TrZTUrgm0BdfUASlJW2M+YWeHjMq\nS5Ywa/brr4zHyopxTJ/OCXm3blmvM/Sh8Xl4MBuzfTu/Nm1ig3ypUjxfTZvSjOFD0dNj/MuXz0OH\nDuz7CQhgr1izZnw8KYnX0ZAhFKLffZfe9ACgeMqtoUVOmTdvHkqU4HW1cSOF9p07/H/3558UOrNn\nM7tTvDifExPDa3PHDroUfvIJe8e0hbauQUHRQerXSF7ie/nyr9SfS5XqiUaNTqB48ab5EVYqOYlP\nJpOhdOn+aNDAHy1bPoaNDd1FatRYASenlzA0VK0mbWhoBZlMD4aGJWFdqgcW1qiNF2+/h1GCDI9t\ngW39gXUDgUsNAEAfr9EMAOD35Q1UWzIQ26echT5iAOjj/llHbMEWyGTv4NUuHN5r18LA0gBNLjWB\nkQ0zBYmxLAmo0OkNjP9cApOgA5BduQJb/QNoi09gYELHkypzqqB1ZGuYNzZHSkwKzjuex9N1Twvs\nGOoECkWq4Imp0wOx12MhM5bB5gubdLv27t0bcrkcpTJJ+a9fvx5TpkxBmTJlULZsWUyZMiVd6bBA\nIBU+mpI2JTducEIaHc3J3NdfZ77v2bNAp07cVyZjFqdTp4z3VTc9UNKqVSx8fMxSzQ+y4s4dGtjs\n3cs1TN694/Zy5ZjBad06x0NMJTFRZZyjpG1bTry7deMENzY2FmY5qe/KJ96943GfPFm10GqFCsCU\nKXR6M02z7ER+x/fiBQXIgQPMBsnlLLNzcVH2AOWOzOJ7+ZIl0seOUTgoxyqTUey+fs0SxFevKGqt\nrIC1a1kOl5/k9vglJtJs4uJFZl927VJlG3v14mKpiYkUs1mVaGozxoKkqJdi6EpJm5SvEeDD41Mo\nFAgMLIHk5Eg0aXIZ5ub1tRDdh8WnUCQjJuY6ihWrl7UL15Ej+OG3B5BvqYZEI6DmvjoIb2GCxY8e\nYf+N59jqrIBhEp8/chVw+33Zd4e3pzDje0MkhjRBHGKw+Zt32OjCEoXaERFYqa+PpkOn4MzrZQCA\nupgE6/PeQOPGqveePh3w9EQ8SiC89c8ou7Qb9BvWQVxoHK71uYboC9EwKGmAlqEtoV8sZxbZmSHl\nazBXJW3XrrGcxMQE9767hLBFT2Hdxxp1d9TN9CkZ2U6/fv0apUqVwt27d1H1vd3p3bt3UbNmTURG\nRsLCwiJ136L+OSrQDT6qDA8A1KrFNWEAmgBkRbNm7I1xcqKg+fJLWjBnhNL04Px51SrzJ0+aoUED\n9vYospGVNWqwJM3fn1mlkydpjf30KSfkffvS7TM3GBqyL2jvXpaZAVzc08UFKF+eWZekpIL9ADc1\npd12SAiwYQN7SB49Yplh6dLMRKiX8+X3P5jSpXlzS1mWtmsX8MMPFJadOzNTk925Uiez+GxseJxX\nr+ZYlUJYVjhILgAAIABJREFUoWBmZf9+ioqQEGaCwsMpKAYP5rb8IrfHz9CQfT+7djEzFhxMUQgw\na7hlCwXcwIHMHK5aBdy6lbtjltcYBR8fUr9GPjS++PhHSE6OhExmoFWjgg+JTybTh7l5/azFTkoK\nIufMgVEkbUdNR5RGpc42aGxhgVU1a6JsBTPMniRDeCngSj3gtb0MfUpZAgCOFm8J1w3FEX64H8K2\nr0sVOwAQXKoU2llZ4XwFPdTFZNTEAlhb3+E/RXWmTQM++wzGeI3ygROg37kdEBEBEzsTNDrdCIY2\nhkh6lYTAEoF4d/9dro+BOlK/BnOMspytYye8+OsVgIzL2bIj+n1phpWaTamlJc9tlPpieQKBRNB5\nwZOdS5sSdfem4cM5sTt9GqhRww1Ll2bu3lS/Pq1+GzQAXrzwQMuWXhplZmldqBo3ZmnTkCHeKFfO\nHQkJ7GOpWxc4ezYWnTtn70Klrw+0bAnUqOGMTp38IJNxktmsGeDllXsXqhYtwhESwn6NH38EAA9E\nR3vB3Z1xrVsH3L+fO5e2vLppnTjhjx075AgJofCqVImZtPnz3VCtmg8CAlRlXvntbqanx2zKX3/F\nokIFOWxtAyGTMSPTsSNgb++Lzz/PP1ewYsVopHDhAt3/Bg8Ox+jRLDE7eRIYNcoDtWtzHH/8wbWB\n/ve/UDg5yfHffwVzPjIbx5Ilbvj8cx+sWEFBPm8e0LdvEAA5tm4Nx3ff0ZyhWjWgVSsPTJ2aN/c/\n4dJWOHzI56g6BeVKCEjrOsnrOHr16oerVwFTU3vo6Rnp3DiS/P3h0qoV/E5Px1VchV2t4qmP7dm2\nDQ2WL8ftT43Q7y9gzFJgWe1aMJg5Fy63b8NQJsMd1MT/9JZj7IN6wOTJ6K7Yhza3VHcVu5Yrh2Xu\nTrA98TP/YRsba45DJuOH+fDh8ADgFRHB+mFLS+h1aIfi415hMiYjJDEE5+qcw+3/3Ubiq8Qif11l\nOY73gifSvi/iw+Lxi+EvOJ6kWbOfk3EoM0onTpxIHcebN1zLycLC4qP8HBVIm4+upE2JtzczMikp\nwGef8Y57Vk3TL17QeSuYrqG4dYv9QFmRlMSejhkzNLd36EBhNHFilosbp3LuHCebZ86wb2jjRvYg\nfSgJCWyknzMHePCA2+RylnpdvcoFsjNzm9MWCgUzbqNGqba1b8/jV7MmrcG1SUgITQ3WrlWtkyeX\ns6yxXz+aUWjzBp9CwYzKwoU8z0r09GgkULw4ReHkyapsXWFy+DAzdA8f8hgpF3utWpXCsUqVwowu\n/yjqpRi6UtKWn8QkxGDf7X3oYd8DZoaFe9c+NHQe7t+fCBsbZ9Spo9lUqFAocO7JOdwMv4mt17di\nZOORKF2sNAz0DNDENhPr0AJm/erVGGpvj5XfKuBwS4a6fnVh3VPzn9r2Fy/QPzgYdsbGuNGsGcze\nO3idjIxEm4sXU73eiskSEFjPDtVePcaZVVPQtdsMJOkZoLShAW41aw5LAwOcj4qCDECT4sWRjhMn\n0td+m5jg+UR/3JiRnGoqV6xuMTj+5wjDEob5ezAKkRyXtEVEsMwhJQW3vjyPp5ujUHZoWTj4ZJ1d\nnD59Oi5dupTOpc3Ozg6LFy9Gnz59AADbt2+Hu7s7Hj58qLFfUf8cFegGOp/h+VBGj2b5kokJe2fm\nzs26LKd0aU7wlNn9vn0zNz1Q8vPP7vjlF/YNqS/AefQosxpdu6p6dbKiaVNmjTp25MTSxYViRTnJ\nzC1GRsCIESypatbMHXp6wJ49bFz38OAd+3HjGGdBZaZlMrqbnTnD8QLsf2nb1h1lywLffKPdWCpV\nApYtowBU2ngr1zTy9qZt8uXL6Z+X9u7ahyKTUcSePk13PRsbnqeUFC6G+s8/tJfu1Cl3xyG/4ktL\np04U3seP83/o0qXcfv8+RU///lkv4FoQMQqKDvl1jSgUCgzfOxwDdgxAsdnFMO9E/jSif2h8r175\nAwAsLNKLzeXnlqP52uYY7DcYf9/5Gz239ERLn5Zova41Qt7kru5VW39jv70XHlVeUE0Y2Rql26df\n6dJ42aoVbjdvnip2AKCVpSX+rFULFY2NYe3jgwMNmsGxpAMsqndC29l+mGswCwDwIjEJ1c+cQfer\nV9EsKAhNg4LQ99o1LH30SPONnJxYxtC0qcqBJS4OZS4tQJvoNqi9vTaMbI0Qcy0G1+TXEH05GkmR\n2fwTV6NIfE4dPAikpCClbkO8PMDJR5mvyuB5QgIUGUyAkpOTERcXh8TERKSkpCA+Ph4JahMPV1dX\nzJo1C8+fP8fTp08xe/ZsDM9oZXeBQAJ8tIIHYAP/gveulpMnsy8hKzvopk05CTc2ZiZk27asX9/u\n/a14BweWxT14QOGyZAlQsiT7fRYtyvo1lBgbMws1ZAgnwZMm0clt06acPT8jLC2BgQPtcPAgsynq\nTfuLF1NgWVvTxUtbLmJpadaMouf4cTbGW1jwGP72GwXih4q8nFKuHMvMli+ngUC5ctx+6xbLDJUZ\nPiV2Wki3DBlCQ4PYWF4vvr508jMxob32119z7ZqMHN/Soo340mJuzhsInp68rgFmqzp2ZPloZGTh\nxyjQbfLrGpl3Yh62XFNlUib+OxGexzyRosjbB9yHxJeY+AZv3hwBgFRHNCVPop5gyZklGT0N8cnx\nqLykMp5EPcnw8fyKLzuCoqJwqlw5lH+UDOM3nEqY2JlkuK+1kRGMMyihcClTBqEtW2Jas2Zoo9YL\nYmRUBoNrj8ePmA8AiEhKwoFXr1If3xEejjF376LX1atIev/Pae2TJ2j+4gUGbtiAoLAwlkYAwO7d\n0A++hNJ9S6P+wfrQt9BHZGAkzjuex6WOl5CSlLNzXyQ+p96Xs72y/xpJr5NgZGsEy7aW6HTpEmqc\nOYOgNHfTsltYdOrUqWjZsiVq1aqFOnXqoG3btpg0aVKBDkkgyCkfbUmbEoWCWQ1l2Vn37szkZFVq\n5ulJcxhjY06Mhw7N/QKT69Zx8cqaNTnBtrJi7052pKTQSvj772mDDdBw5YsvmIXo1i1nr5MZBw+y\nDzQ0lHfulVmsL75gg3pOSvDyG39/io+4OB6vwYNZ+pZRVYM2uHeP73niBEvMvLyYjUrrKKdtAgMp\nIhITVdu6d2fmx9aW13JhLnSq5OhRivo9exhTxYo0/ChWjOWSulTRUNRLMT6mkraXMS9RaXElvEt6\nh0ENBuHg3YN4EcNF1qzNrNHHoQ8qFK+ApuWboqltU1iaWMJAz0Br8UREHMTVq11hYlINLVrcTd3+\nPPo56q6si/DYcBjoGWD3gN34rPpnuPHyBn757xdsu847ba6OrljXc53W4suK27Gx6HT5Mh7Fx2OZ\nexjqnK+IEl1KoME/DfLtPRQKBc5eaIXvo3shTFYdfYo9RW39MLhFdtXYr7e1NdpbWWHMXdUxNJQB\npxo4onHFiqp1D775Bpg/H482vMXdMap9TaqaoMqsKrD5wgZ6hrp5DzhHJW1JSSwdePMG1zsG4OWR\nFFT4oQKiPcug4YULMJbJ8KxVK1gZ5n+pX1H/HBXoBrr5152PyGTsE1mxgja8+/czM57VXWl3d040\n4+N5B3vhwsz3zYy+fbnOz+3bFBEmJhQxt29nXbKkp8dytOBgCi2A2SZPT/acVKtGMZDZYqnZ8dln\n7Ml49owT6yVLWFq1Ywed3WbMyJsj14fQpQszBsrjNXkyzRaOHSuY969Wjdm8ihUpON3d2c9TrRot\nvgvqeLRuTfc0ZdYJ4PVaoQJd/szMmAVL0wNb4HToQEe3gAAeI+VaU9OmMds5eDDd3pSCXSAoCKYe\nnYp3Se/QtGxjbIhoi+c1f8OvnX9FMcNiCI8Nx5qgNZh2bBq6buoK6/nWqLS4Ev69/2+GpT75wdu3\nJwEAlpatNLbvv7Mf4bHhsDazxqlhp9CtRjfoyfRQp3QdbO279f/snXdYVNfzxj+7Sy+igKDYEFCw\nI3aNsaBGo8Eau7GniEk09hhLEjWWqLFGjcbeYy9fS+wdAQUsWEAEKyIgve3u749ZqqCoaGJ+vM/j\nI9vunXv27jlnZt55h5kthIa38vJKfjn1y1ux7WUYf+cO95KTqeWbQBVvUWgrPaw0UUej8G/rT9Co\nIFKjUl9ylBdDoVBQonh7pjOW9doudIn7msrPZjKF8TTnCANYgQINO3TZnqxI1cKn1/2IWbpUukCD\nRIbGjaP0N6VpFNGISusrAZAUnMT1Htfxb+1P0t3/8KR09ixER5NWrDRP5dbDtpct6x5L49FPrK3z\ndHYSExNxcnKiWLFi78raQhSiwPHeOzwFpS701VcSQbexgZs3fbGz88DPL3f1FFNTiV6PHw8QysiR\nHvzww6uppxQpIjQtycZsJC2tPwsWiFiApaVkcV50HeXLy3seP5YNeOnSnpiYrODuXck6NWsGu3e/\nuQqMQrGATp1GUbOm0MkmToQqVRKoU8eDU6fenZrNsmUenDgRQRcd8yMsDFq0mESfPu9G7cnODurU\n6Yan507KlZPngoNhyZJDmJp6MH260M1edh1v+n0EBy+gZ89RhIYKY8PJCbTaBG7f9iAp6TQHDkjG\nb9Ys+PXXf1ZdqHFj2Ls3lAoVPPjgg0AMDMQ5XLMGevRYQJkyozLqfMLD/10qSYXqQv89nL6yn90b\nwOtLHxSDBkH79ox4VhnfL3xxL+9OCbMSlLUoSxFDSR0/iH1Ay7UtqfZ7Nc7fO1/g9jx7JrvOIkUa\nEJMck/G8130vAAa4DshVnGBUo1G0cZIsx/dHv8dznyf3Y/LZofoNkazRMO3uXf568gSA2dNEYcWy\nrSXmdc251v0akfsjCfs1jDOWZ/Du5o06Xo0mTUPgoECCxga9kgNZsmR/9PWsUAAmJlUwN69LI84y\ngSn0YR0T+BkLMjtXN+E4O2mPLY+4k6ylnUtFHvv6ZnLHFy+Gli3Rv34B29tLcWzsh2UrC5QmSqKP\nRuNVxYv4wPgCG69/FXR0tgiXQWiSNJi4mGDsasoGXXS09wuUgSZOnIi9vf2LJcoLUYh/Of7fU9py\n4sIFUeUKC5Pia29vySzkBq1WnI3ZsyVT5OUFtbOsT4GBgbi8pOvo2bPyuYgIidZfvizPm5mJA1bj\nFRgCcXGwebM4YrqgDdWrSwYrr4aW+bExHTNnyrHidetBxYowdSoZTsjbQG72xceLcMOePfL400/F\nNnv7t2dHViQni5DA8uWwdWsgKSmZ9g0eLLZkoaO/VWi1maIGKSmSAbpxI/P1Zs0CmT/f5bn2Ff8E\n1GrYtUuyPzt2ZDJN7O0DiY524fRpqFLln7UxJ/7rVIz3hdL2KvNUbohJjmHuRxZMOpHjhY4dYfv2\nbE+lqlMJjw9n5OGRbLu2jVSNZCoG1hzIco/lBWKfRpPG6dNF0WjiOZXan8nnVjOjxQxGNBiB0wIn\ngqOC2dltJ+1dcp+4tVotTVc35eTdkwC4WLtwdchVlIrcY5hvOn4ASWo1NX18CExIAKCkWs3uFreJ\nw5nKmysTsTOC8I2yeVaQhBap51E2VeAypBLXukoBpJFbEGW+TKJU244SYdTTE/uuXJHmXmq18Mr7\n9pXzJoWSlhaDmVlV3dglExV1lEeP/uTJkx2Amr/ozP9owwR+xt3xG/4XupehqWNJxYCPLYuxr1p1\nmVyuX3/+wsaNI67791ztcpXEW4lYtrWkyl9VUBll54YXxBi+LeSL0lalCly7hl/1A0T5G2L/sz23\nhxShpb8/lnp6PGzYEINc6qx8fHzo378/s2fPpmvXrkRFRb2yff/1ebQQ7wfe+wxPQaNePaFKlSol\nEfxatSQinRsUComkd+okG8/WrYVelo7Ro0e/9HwNG4o89pQpopqWkCBOSlyc2NKqlTg++YGZmdQF\nHT8u9TwA/v7S0LJePaEY5UR+bMx8r8g3p0ti37wpzsaAAUKBexvIzT5TU6G4jR4tGbKtW0UGuVw5\nyZq9bRgaisjDunXg7j6aZcsym83+8YfQuHJTdHsbUCjkHvrxR1Huu3xZ7qUKFeT1Y8dGU6+e9F+6\neFGavOr2K+8cKpX8VtaskWbfn3wiz4eEjCY6Gv73v3/GrkL8+/Eq81RuuPbkGp3S97pFisiECOJ5\nnzyZ7b36Kn1KFSnFxs4bufn1TdpWaAvAiksrMrIvb2pffHwAGk08SpU5k8+uRKPVMOrwKD7d+inB\nUcEYqAxwd3AHxLnJmRVRKBQc73ucnd0kwxkYEUjHzR3p9lc3PvjzA0YeGsk6/3Vsvbo1w76zYWdp\nv6k9ih8VjDg44pWFGlY9epTh7AAsCLxBAlLIH28Rw+NNsgi48jUf0B4n5gFqNMe1Gc4OQJKvIxGf\nx6MpVZY0t5oQE8PoYcOI6LUIf/UUnlFZlFtmzQKtFiOjshnODoBSaYiVVRuqVNlK7dq+WFq2oQvb\nWMEgWjiNpEyZ7/BwHMBsRgCwPzKK49HR4kTZ2T1/Yb/8gtm4blT+vSQKfQWR+yLxqe1DnH9ctre9\n6T34jyI4GK5dI1lpTdQVQwBse2TS2bra2OTq7KSlpfH555+zePFi9N9CbU8hCvEuUejw5AIHB6kx\nMDAQZbW+fUV2N7dMvEIhEtMODlLk37Ch1LsALFy48JXPbWycLscsmYTDh4UaNH169mL1F8HFRTJV\n585JjRFIFqlpU3B1FUnhw4dfz0YrK8kieXtnblhXrpS6kvr1JcPxyy/5UxDLD/Kyz9BQ6kK8vITC\nBSK08PnnkmUbPFiU8d42lixZyODB4pTu2CGOV2QkfPSROLL5lWYuKBgZSYbv5k3w9YXatReSkCBZ\nyLp1pQ6peHFxzOL/QeZGuXJSF9WxIzRosJCNG9Ob4haiEM/jdebSrLgedolKT3QPrl4V/feBA+Vx\n9+55Tlj2Re3Z23MvHs5Ck6y3vB4jD40kOS052/u+nPAluwJ3odFq0Gq1TD05lQ9XfsiAXQNITH2+\n90B6/c75J7FkdTu2XZfFo7ZdbSLUKmp7e6M8cQLliRNMvHMHTZZFSKFQ0N6lPd/V/w6A3Td2s+Xq\nFs6EnWH2udn02dGHrn91xWyaGZ1GdKLV2lbsvrEbgDnn57ArcFe+x2/1o0cMuXULgL62tiR/+CFt\n1x1AgzEKpYbrv8xDoVVixi1M9K6ibdcSO+MDlCL7OUqxHSWJRFGX64xHEXCT0G/7s6BqNa6njCCS\n+lxiEbfwJHb0Utiw4YV2mZlVp3r1/TRqFEXlypspVeorAGxte9C2bHvqIA5q54CL/GVvT2pYmHz/\nZmaS8XAXp5L9+zHv14iqGx3Qt9En4WoCPrV9eLr/aca5st6DWq0Wrfo9Isfs2wfAk/IDQANF6hdB\na2/ANh2dNy8626xZs3Bzc+ODnP2NClGI9xCFDk8e+OADEQbo2FEef/sttGiRScPJivLlJXr+4Yfy\net++sp6WKfN6MpbFiknzxo0bxYECGDdOsk353aTq6YkD8scfkjlKd3z8/ODoUclGzZgBtravZ2Ot\nWlLHtGtXJuXvwgWheX3/vdQiDR0q+4gXSX2/DC+TAnVzkyxWZCR88YU85+MjdrRtK5mOQYMKzgF7\nkX0dOogjWL68UArnzRNVtbp1hcb1rlGzJpw9W5aNG8W2dJpdQoI4hqVLSx1vYqLIgD/Iv8ptgcDI\nSNhEZ8+WpXv3d3vuQrxfeFNJ4Cc+p9DTQoKZoaTvQeQ5y5WDhw8lLduyZZ5KKKvar6KqjWQZZp+b\nTeOVjQmJDuFK+BXc17jTdn9bOmzuQJXFVXCc78gPx37gVOgpVl5eSY0lNYhOis52vPT6nau60p3f\n2/5OB5cO8sCqIZal29P48mV8siw4P9+9S2t/fx7n0Oaf1WoWO7rtoL9rfwbVHETnSp1RKTLpWPGp\n8fQ/3p/41HgoUgXMpVj/r+t/5WvsolNTGXLzJlqgk7U1CytUwOD6dWLPi0y0kb2SCiektqMol+ii\nWIfF0b3MGxZKKYtVWHIOAAUpmJtvwHmtA1qlhic04xQHiVtVmajZJVBjlnHO+3TBh+WEfXsG7cOH\nACRci+VO83U8/fRXGDaMhLGLSHksY6GvXxQbm64otAo4cwZFXAIODlNY41CU8gQTqTHg02vXKHr6\nNNNNTYm/c0cWrMOHM1PL9+5hdXsDda7UwcjeCG2qloC2ATz8U86f9R68/c1tThU5xbPzL9Hc/7dA\n5/A8TmkMgE0vG3ZFRBCnVlPeyIiGuUie3r59m6VLlzJzZsH0qipEIf5pFNbwvARarUTH0+vdPT2l\nEWVutXtpaZJdSKczNWoEf/2Vvb/Nq0Kjkc378OGyUa1aVbIaryqJrNXKWn7kiNRvpjMTHBzketq0\neX1J44QEWTsOSQ89zp7NzhJxdJRan/r1ySj4f1sICRFnc98+oZylo0wZkdxOF+x5m3j6VL6zU6cy\n1hlAHLBhw6BJE/gn2AFarTg306cLreyurnehUpnZZ6l5c6hUSZxVZ+d/h8z1P4n/Ovf8fanheROo\nNWoGflmSVX88IbKSPZbX7mS+eO+eTKpZZTlLlJBIyg8/SPMtHR7EPsBzvyc7A3XRCy0YpsGASzDh\nJJSMg78qQa/OkKIHxnrGJKZJdse9vDurOqyidJHSAJw+W4a0lHuM8IORzTfQo1oPNlzbRa9Dk8H1\n+eZsSkCpUJCmy/Bsq1KFjtbWeRaRxybHcjbsLGqtml7be4nDVfpTcByiu+5tELSITyt3Yc5HczLs\nyg0rHz5kwI0bVDExIaBOHTnnd99xe24i9+hGUaN9KJOsiKQ+Kw30WJOSmQ1obHODvzXNiIsojYoE\nGN4EizmLeLLjCVc7XX3uXNvqbaH1pbaYpmTWoFgXC8A56EsCqu0n5r5F9nFRJFNze2nMPSpJVDB9\nc+7gIGn3kiU5f7kd46JrcZxmGZ9rZ2XF7qpVM8dvwAChKlSqBAEBxPon4N/Gn9THQqswrWaKJlFD\nxWUV0aZo8W/tD4DKTIXrKVdMXExQKBQoDf+ZGPILa3ji4sDKioSU4nixDlTQ8EFDOj4KZH9kJBPK\nleOn8uWfO+aqVav46quvMo6bmppKbGwslpaW7N+/nzrpHcLzgf/6PFqI9wOFGZ6XQKEQqk06TW3R\nIqFL5QY9PYnkd+gg0eszZ6BXL6GmvS6USonGp9fVXrkiWfhJk6Q/zKtcR7NmUt8RGyvXYWIimY+2\nbaV/jy6Q9sowMZFj//KL/DtxQjIHzs7yelCQsEbs7cWOBg2yOwIFCXt7OdfatULpWrJEnKywMBGA\n+O23ty8jbWUFY8aIKM6xY3JehUKuuWVLGZc5czJ7HL0rKBTyXf30k3wnojKYvans0aNyb1SqJBmg\nXr0kAPrDD0LZK0Qh3jccCzkG4cJnsyjjlP3F0qUlOtOtW+Zzjx4JH7ZhQ/nRKBTQpAl2dyLY0Xkr\nT40mMSW4PJu3QtJUWLxfnB2ALtdh3CmwjocHIx4wu5V0tj5y5wiuS1x5HPeYU8E7SUu5h1oLMdjR\noVJnvr11i17hFtmcnUoJCWz4+We0zZqh/vhj/HfsoKyuyVrnq1czKGa5wdzQnBaOrWjh2JqdvQ5h\noDIGq0znjdKdoWxPtl7bSpm5ZTKobrnBR9cnoY2VFQq1WrT4587lGcIlLpl0mRilOEx+KVVwcZE1\nC+BUuDNf22yhqOk1NEbhTH82CbUaincsjuspV2JqxnCr1AUSDKO5bxlG6jcahg4cyslKJ/ErfxIF\naUREVeOM5ZnnnB0AjdaQoI6H0KgMMp0dkIVNV1xb1ekXpugvYyGe9GENCrTsffqUmt7e/Jm+6M2e\nLZ24r18HR0fMF3xLwz9jsXSXzX58QDyJtxPxa+6X4ewAqOPU+NT04ZTxKU4XPU34ltfsB/E28fff\nkJJCeLFPAbBsaUl0UTioa+Tay9aWmIsxz8mId+vWjaCgIPz8/PDz82P58uWYm5vj5+eHq6vrO7+M\nQhTiTVHo8OQTnToJBQxEDnr9+tw3rPb2WetgZ3D0qGR6rl17/r2vgo8+ko2nnp7U5vz0k6ikjR+f\n/9qedCiVMGQIBAZCo0YzMDAgQ8745MmC6Y8yeLAc/+lTcRizqpadPw/t2oly3JYtEBOT93FyyjW/\nCmrWFJrb339LHVRammTKWrSQ9W3DBrj/hmquL7OvaVMREkjvm2RoKHVhI0ZI36QX9XsqCORln0qV\nKZSxbZvQ2Q4flgxUuqLbgwcyRh9/LBm6Tp1k3CZMkM+9bRsLUYh0vMk9stpvNcV1GW2VTS7p9urV\npWhTq5UU+Pz5MkFlxcmTkr7X18dy7I+MX3OHLHX4zMhSAzH5BDyep0/RDdv54ngcgwMMME6Bp4lP\nKTG7BCP2Ck86LAF+av4rR6JjmJ9jIvoZuNa1Kz2OHpUnEhOpNG8eOwYOpI2X1KUsvX+fy3lMIGka\nDbW9vTE8eZKmt+NR3fsMitYEwFNXuG9Yvh+oJBPQc1tP/B9nbuTTRRIux8aySMd1raFWE1/CCpYs\nQY0hcUik/optFGkacXhSbU24cgWWLpWaSpUKll37gEYOjymfdJPpf9owcaKco+gHRWnn0w7LQ078\n77sjtA76mCU9l7Bj4g4mdZvEsL6TeOg2Ptt12ZS/g91X0ojM3DEFBalEU5NT7MeXhQQzEK1bLanR\nOX8ehgzBLKoo9eoFUssogQGspBeS+veLj2fgjRs0u3iIk9qEzD4Rd+/CypUo2rah0hF3TEzFWd5I\nZuuLYi2KUWZMGUyrmqLQlyyRJknDjcE3iL38gkZ6/wT27UMLPNY2B4TOtjk8HDVQx9yciobGXO1y\nlXN253h2JvN+MjY2xs7OLuOftbU1SqUSOzu7QgGDQryXKHR4XgGjR2eug717S1Yjt5oegDp1oFu3\nBCwspKakShXZ8KbLRb8OWreWANSsWbJGazQwbZpkTF7HoSpTBtzdE/D3l6zD06dCt7K1lexUQcDS\nUuyNipIN9OnTUg8FUgPUrZsI56xfn/vnEwpAUszJSbJOc+ZIsPboUXHCevWS7yU09PWPnV/7XFzE\nUb5hw+O3AAAgAElEQVR9W5rEGhuLA1u69NtVJ3uZfa6u4siULCmO4Ny5UhOVLpP+ySfpvaIEI0eK\no+TmJvS3LVveXPWtIL7jQvy38br3SHJaMtuvb8cmvfbRxubFH2jeHL7+WooT05ut9eoFZcvmHllq\n2BAOHiRh0CBpJqXTxlempMLAgZh+P4ll21JImAbRM5QcXwmex6H4CXBUuNGjWg+OZOH/jl+7ll3j\nxzPO3V0KNp2chHa3axc4O+N26xb7x4yhy/HjaBUKuh08SKxuAnuWlsa5Z8/4LSwMg5MnuZyl4DMx\nUah11cLDmb9mDZWNjEhGj2m9A3Av7058ajyN/mxEk1VNGLR7EMoZJfnmwHA8dVkkU1KIG/4Rpk8l\nOhWDC1r0SNV/QnS1sQCcxJq6bQwz5osyZWRuATgfYMozJOo1bZoE7DQaUCqUdK7cGUt9S04cteKD\nD0DzwJU7397BSM+IsY29qK5TWzMormbLr3f5scVPHNx4kH3Lz1N2uiMAWgyIoQqh9Oay6TI034qQ\nA0uWQIcO6KmKULfuLSpX3sQg5TaGsiBjbI7HG9DMP5DOdsGcOfkD2iw9v/SJoU58V5rSDFOOYckF\nalRbRY2JMTg6HqXOZTcaPW1E1V1VMa5gjDpGzaVGl4jxekEU711Co4F9+4ilIonR5iiNlVi3t85Q\nZ+tta0vk4UiSQ5NRGisxq2WW56GaNm1KpC4rVIhCvI8orOF5RTx7JpvCuXMlM9GqlayLhoa5v//O\nHald0fX2omRJ6ZmSriz2ukhMlDqL9euFMmdmJvVCH330eseLixMl0HTqnpOTSGwbGb2ZnXnhwgU5\n186dkM7MGDFCsgcWzzMXCgyXLwtb5eJF2dCnpkoGbs4ccVLfVc2Kl5c4z7r+fZiYCBWvcmURvbC2\nfjd25AdxcSLG0KKFCFBYW4tDlA4bG1i4UH4DVapIzdZ/Bf917vl/vYbnRMgJmq5uyqY9RnTzSZIC\ntjFjXv1AqamiQrJihUzi69fLAuDklD0iEB8v723VSiaZFyDZyRLDdfupceUK/o6ObP7xR7rmFE24\nfl2iJSA0rY8/huRkIho1wrV9e+4XL07Z8HCG29oyVU+PiJek+9dPmULPI0dY1acP/QcMAKCOmQmR\nvsMIeuwLRiXA0RMs60DCPTCRzE2tXf05Nz8EfQ0kqeCxuhd3GIRRfUjS9WT9Cjc8FxRh6NDM88XG\nSkDuqq5cp3fvzNrKoUMlmRYUJErhOYXCXD3OcKVWczr7p9BQ48TYSvdINMhOPyhh4MRJh/086huC\nOjkz65DYJIEPGl/FfIpOSvrrryXyZmjI/fuLuHVrKFrAh1r8wWBuIvzrIjzjtLOSatatxThDQ/jz\nT3Ec2rSR+ycrfvtNoo8PHpBctQmXu90n8UYiKnMVbhfcMK2USz+ct4A8a3h8fKB2bW7rfcu9tA7Y\ndLdBb4U9zl5eqID7DRvypMdNIrZHUOqbUlSYVyHbcfv168fGjRsxMDDIeO7vv/+mXrqsez7xX59H\nC/F+4L3P8Hz88cd4eHiwcWNmuvltdmBfsmQGkycL/cfEBA4dCsXe3oOAgMBs712wYAGjRo2ifHnZ\n3HfuDHZ2CTx86EG9eqc5cCDzva/TSd7YWNbe4GBZUOLiPGndegXm5hKBv34dli715ZNPcr+OnBSR\nyMhQUlI82LYtEEtLyUQ4OkLTpgtwdR2VTWUsISEBDw8PTudoEPQq1/Hs2SECAz0IDBQaFQhdytLS\nk5kz8/995LyO0NBQPDw8CAzM/ftwdRUVuR074PTpBJRKD86cOU29euLwBAS83veREy+7r+rWlboi\niYBOIiFhBn/+KRmURo3gxIkXX0dWFMT38aLr2Lx5BU2bihLes2dw8KAvTZp48NlnERgbizPftSu0\nbz+JihVnMHt25udf9n28y+t4ld95jx498PDwYFj6zVmI9xLHQkQX3i1GtwF8XdUUfX35cV6/Lini\nkiUlLZ7V2QFpEla0qDQHc3cX6c5jxzK1+7PA8HYkT1u1wl8XIWia3nU6K7I2gXNwEJ7wnTtYr1vH\ntqpVKRUdTaiNDcO12uecnaKxsdzt1g1Ns2YcHjGC+fPn0/3oUbCxoefGjVTR0RMuxiUQVHEaND4A\ndVaJswMZzg5xd9i9XJwdACM1xCNF7kZmkrW5ZGpNIEWeE4UxN5e1sl8/YUisWSN+B0iQRKkUJc3c\nVJEv725E2vkv2FwNvq1xO9PZSQFuAXfhUcptKgZWpNV3Hozp8wXPjIWSZXzCBK9pbgS13YIGpSjz\nGBnBxImUshtC48ZxNGzwkEGuc/Bv4MFeJyVllJHEYMGvt0+Soo2WCNzQoVIMevmyFKjm7HUwbJhk\nBXv3xrBFTVx/eIp5DUPUsWruTr37/EW9a+zbhxYl4aqWgNDZ1uuyO60sLSkaqeXpbpHeLjm45HMf\nVygUeHp6Ehsbm/HvVZ2dQhTi34LCDM8b4MgRKfhPTpYN3x9/SKQqL0RFCUUonS42ezZ8+aU4Tm+C\n6GgpKl+27HnWRd++4hjlXJdfhMOHJRIXnqP+cvx4OU9BZ320WgmY9ukjj42MJKjWo0fBnic3BAQI\nxWLnTqld0teX+qaxY99MXS+/0GqlTqZfP6GJ+fpm1oY1bCgCCDVrwjffyN//Nvj4yFjdvZuZqQPJ\n0jVvLo5+69b/Ttvzg/96ZPLfMI++TTRZ1YSzwSdJnKlPmgZmnj3LKX19xpYti3u6nv67QkICxMXh\nE9oWi5XeOC2Gc5Ur03DRIso8fkxo9+7C8Z02TahY6Z7BvHkyAeSCxNhYui1Zwp46dSj76BF7v/+e\nMuHhmCcmktayJYabN8uPcft22bR/+63IdXbpgtrcnKuXLtHpyROCchRuNjGM50SyOIlux+fg8+Oe\nbK9ftNhK/DNrTKubEu8fz2wqsl9px6NH0ufrZZg6VdaSnFi4UFROMxpIFw2BYToFscAPYVcqJJ7T\nvaiCLuWh6u3MA2hh7KmxVPGvQukIcdhKNo/B2atXJv98+HBZfHOk89eHedM7KA4DkllovoNBbotR\nKHKJCf/+u8i2JiZmV3zRIZaK+LAUgGp7q2HV9u1PfnlmeOrWJfKiGn9mo2elR4MHDajoe5HgpCTW\nV6pEo5VJ3Bl3hyL1i+B27vnff79+/ShWrBhz5z6vHPgq+K/Po4V4P/DeZ3j+Sbi7yzqiry+1DPb2\nkl1JVwHLGTkuVkykm3v2lMcjRmRkw98IRYvKQhESIgpxWbF6tQgddO6cuzhAThtBlMTCwqTB6JAh\nUqsEskh99tmb2ZobFApxsNauFXWwpCQZoz594I8/It5qYX+1atLvKCRErjuduVKypNTX9O8v4gKT\nJkGO9hdA7uP3KlAopEQgNVUygf7+0gMKRN57zx7hu5csKXTFX355schDQdv3MtSqJQ7yzZviqKXX\nZz17Jlm03r2FAqdQSLB7woTnhSLeto2FeP/xOveIVqvF75Ef3a+AKjmVQePHMykujr+jovj8xg1i\nC1AmMV/2mZiAjQ1JyXe51wUSDv7J3WXLALB/9EjoUitXSiZn5szMXgjffptnF2Vjc3O2Jyfzv9Gj\n8RoyhGoKBUW/+gpVSgqGBw5k8IMjPvxQJhIrK2ku16gRqthYqg8fzonKleluY0O34sW54OaGpkkT\njtX/mOqRe1FdncHRGXszT1i/Plq/ABKSxKtJ0ck2B2HKgAH5c3ZAgmcXL4pjs24dODpG4Owsda5L\nlsjcl5QEU0fZw9ZNcGAObPowi7MDoMZ4fzE4OyLjGevr4/lh9y8ojiiY5SEO48OjRUjcckrGFYSP\nPn/+czb1LF2LFqaxpGDIl7GfMtRvE+FZJv2M7/irr8R5SkiQRapDB4kOfv01AObcxALpTXGt1zUS\nbiSg1Wi5M/EOV7tfJSU8l4XkbeDRI7h4kXBaAGDzqQ0XEuMITkrCTKWivaUVD5eLSl3Jz5/P7oBk\neNasWYOVlRVVq1Zlzpw5GYIWhSjE+4ZCh+cN8fHHUnResaJkcCZMEIUyrRYG6DjSWWFiIhv78eMl\n3R8UJI5S8+b5byqaF+zsZJMZEiK1Idu2CcMCxDH74IPnRRNysxHAwECyVosWSSZr0yZ5futWybzs\n3fvmynM50bu3LILpjKR16+DzzwdQpow4W1nlvRMTC1Ze2tZWaqs2b87s1XP/Pqxalel0WFrK31mR\n1/i9LipVkv49gYFSatCvnwgLpKaKs/z997KHqVNHNgUvQ0Hb9yKoVEJpv3VLvrt+/bL3PTp1SgIC\npUtDly4SJNBo3q2NhXg/8Tr3SGRiJM+Sn/GZH5yoUYP1TZpkvBaclMQnp6dw/rwLcXFX3pl9anU8\nqalPQAH6zTpy19ISgHKPH8PAgdkbrE2dmtl5uk+fPCMdeuPG0frLL7HdulUWlFmznkvpZ7NPqYTF\ni+U9e/ZQys2NjUZGbPL1pe6uXSj8/VH064fP9BOkfHsIiyTdRNu9O5w7R6KJA9pkLUpjJam6xp/x\nRU346ad8DUEGateWptC9ekGlSgO4dk0uX6kUmrahocx368Z1g/ODAHFSBg4cyIULF9DX1ycx4SJ6\nR11gThgcmknE9vGYmUGrkj358LsPiTKJAuDCx9Fca7CHtKm6TMWwYVK4maUXg0KhYG+ttrQxjUKD\nisXRdtiePcup6OjnxnDD48d43LzJ4+XLZdEtXlycqBs3QKGgKhMxJhT1MzWXm1zCp7YPd3++y5PN\nT/Bt4EtazDvoSfC//6HGgCdKiVja9LLJECvoZG1NyqlYkoKSUBVRYdM1dzGPb775hps3bxIREcGK\nFSuYN28e8+bNe/u2F6IQbwGFDk8BwN1d+uOkB+RWrJDMyuTJk3N9v1IpG7/Ll4UGnpoqNO8ffywY\ne8qVk6h6p04S5DlwQOhZAQGZ/RHSkZeNWaFQCNMinXK2aZNQ86pVExpdQToepqYiSHT8uND9Spee\nTGys0B9KlxYp6yZNJKvVtm1m88yCgEIhTt6VK5Kx+PNP2ZinIz5enLHatUVtDvI3fq8DZ+fMgO+l\nS6KwOmlSJs3O21vuuyVLXjz+b8u+F8HJSTYxK1fKWO7cKZnCGTMkMADijHfrJhLYdeu+exsL8X7h\nde7joKggiiRB0xBY30Ki3INKlmSbXSAq0jhBU1Ym1eTSpUbcuzcfjeb1G6blx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TPeCFqt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\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17X90dgBUZCrYLLWhcVRjrJdaY7teqIslP03msvZlAiYEkBadhjztw42jcrHv6+tL+fLl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       "prompt_number": 81,
       "text": [
        "<matplotlib.figure.Figure at 0x10805dd10>"
       ]
      }
     ],
     "prompt_number": 81
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "res=cma.fmin(cma.fcts.cigar, ones(12), 1); cma.plot(); gcf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "res=cma.fmin(cma.fcts.tablet, ones(12), 1); cma.plot(); gcf()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=911960, Mon Aug 11 21:10:33 2014)\n",
        "Iterat #Fevals   function value   axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     11 6.035763723609656e+04 1.0e+00 9.40e-01  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     22 6.997761557523916e+03 1.1e+00 9.94e-01  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     33 1.702129541396765e+02 1.2e+00 1.03e+00  1e+00  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1100 3.036207425561787e+01 3.0e+01 1.51e-01  1e-02  2e-01 0:0.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2200 2.428637272374357e+00 4.9e+02 4.01e-01  2e-03  6e-01 0:0.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3300 7.043024076772539e-05 1.0e+03 5.08e-03  4e-06  3e-03 0:0.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4400 1.640012468451166e-11 1.2e+03 6.64e-06  2e-09  2e-06 0:1.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  447   4917 1.758247323071426e-14 1.3e+03 2.17e-07  4e-11  5e-08 0:1.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Mon Aug 11 21:10:34 2014)\n",
        "final/bestever f-value = 8.341604e-15 8.341604e-15\n",
        "incumbent solution: [  2.82382657e-11   3.55566222e-08   5.48256511e-10  -1.16399251e-08\n",
        "   5.47506463e-08  -1.54368983e-09  -3.33869085e-08  -3.79454784e-09 ...]\n",
        "std deviations: [  4.48821051e-11   4.49286901e-08   4.63785583e-08   4.59364439e-08\n",
        "   4.13387835e-08   4.62000742e-08   5.08839495e-08   4.13995678e-08 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "png": 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16tUJCQlh//796OnpYWNjI0T+gvxNtsuXL2fbtm0sWbIEHR0dmjRpQpcuXYD8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GAAAg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iz0+g9V/ar5lqLDj0/9YP7F7ADk/ovTPfLmpl7ch0RgQIpiQJpplYpgibEM8tUnla9RUvzA1J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\nq6+WS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xajXKnoOlZ0/aBi63j58mVGjBhBXFyc0Xx0pR3NwZTrnpT96WAKsqenp9O1a1cA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\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FWbZ51PQgifeBsZS/pu7MnA9xJoUUhmwdclsekZGR9O3bl7S0NDIzM7l58yapqamWPDIy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\nQmCC\n",
       "prompt_number": 233,
       "text": [
        "<matplotlib.figure.Figure at 0x11544d7d0>"
       ]
      }
     ],
     "prompt_number": 233
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import scipy.optimize as so\n",
      "f = cma.fcts.tablet\n",
      "so.fmin_bfgs(f, ones(12))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Warning: Desired error not necessarily achieved due to precision loss.\n",
        "         Current function value: 0.000000\n",
        "         Iterations: 8\n",
        "         Function evaluations: 250\n",
        "         Gradient evaluations: 17\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 64,
       "text": [
        "array([ -7.43837935e-09,  -3.07782618e-08,  -3.07782615e-08,\n",
        "         1.05679413e-08,   1.05679418e-08,   1.05679418e-08,\n",
        "        -3.07786743e-08,  -3.07782615e-08,  -3.07786745e-08,\n",
        "         1.05679420e-08,   1.05679422e-08,   1.05679424e-08])"
       ]
      }
     ],
     "prompt_number": 64
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "is about 20 times faster. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "import scipy.optimize as so\n",
      "f = cma.fcts.tablet\n",
      "f = cma.FF2.NoisyFitness(f)\n",
      "xout = so.fmin_bfgs(f, ones(12))\n",
      "# cma.fmin(f, ones(12), 1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Warning: Desired error not necessarily achieved due to precision loss.\n",
        "         Current function value: 981024.068224\n",
        "         Iterations: 0\n",
        "         Function evaluations: 68\n",
        "         Gradient evaluations: 4\n",
        "(5_w,11)-aCMA-ES (mu_w=3.4,w_1=42%) in dimension 12 (seed=569133, Wed Sep 24 08:10:34 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     11 8.842933426921109e+04 1.0e+00 9.42e-01  9e-01  1e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     22 1.298629867561645e+03 1.1e+00 9.08e-01  9e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     33 3.766368527355514e+03 1.2e+00 8.69e-01  8e-01  9e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1100 1.551565504918144e+02 3.7e+01 4.51e-01  3e-02  7e-01 0:0.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2200 2.363417099759745e+00 4.2e+02 2.84e-01  1e-03  4e-01 0:0.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3300 -1.037009341186836e+00 9.9e+02 1.15e-01  2e-04  1e-01 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4400 -5.009998232831460e-01 1.7e+03 8.67e-02  1e-04  8e-02 0:1.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5500 -1.247887137849521e+00 1.9e+03 5.67e-02  8e-05  6e-02 0:1.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   6600 -4.885450082234257e-01 2.0e+03 3.69e-02  5e-05  3e-02 0:1.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  700   7700 -1.098211574752266e+00 3.1e+03 2.63e-02  4e-05  2e-02 0:1.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  755   8305 -3.785499278564515e-01 3.2e+03 2.67e-02  4e-05  2e-02 0:2.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolstagnation=477 (Wed Sep 24 08:10:36 2014)\n",
        "final/bestever f-value = 1.013568e+00 -3.677627e+00\n",
        "incumbent solution: [ 0.00060342 -0.12258507  0.44149079  0.08756842 -0.20518501 -0.19268802\n",
        "  0.27850432  0.10334738 ...]\n",
        "std deviations: [  4.21263002e-05   2.32334590e-02   1.07158126e-02   1.75851095e-02\n",
        "   1.22148415e-02   1.39697132e-02   1.70607414e-02   1.83109489e-02 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "(array([  3.94434707e-04,   8.56366556e-03,   4.87267467e-01,\n",
        "        -4.59770402e-02,  -1.82192369e-01,  -1.93554164e-01,\n",
        "         3.36274553e-01,   2.13565778e-01,  -6.69622366e-02,\n",
        "         1.85525443e-01,  -1.23332216e-01,  -1.06502707e-01]),\n",
        " -3.677626546623503,\n",
        " 7532,\n",
        " 8306,\n",
        " 755,\n",
        " array([ 0.00060342, -0.12258507,  0.44149079,  0.08756842, -0.20518501,\n",
        "       -0.19268802,  0.27850432,  0.10334738, -0.09756165,  0.14648287,\n",
        "       -0.10122917, -0.13359587]),\n",
        " array([  4.21263002e-05,   2.32334590e-02,   1.07158126e-02,\n",
        "         1.75851095e-02,   1.22148415e-02,   1.39697132e-02,\n",
        "         1.70607414e-02,   1.83109489e-02,   1.62046350e-02,\n",
        "         8.63676062e-03,   1.51483511e-02,   9.11568066e-03]),\n",
        " {u'tolstagnation': 477},\n",
        " <cma.CMAEvolutionStrategy at 0x10e27ac10>,\n",
        " <cma.CMADataLogger at 0x10e27d1d0>)"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import scipy.optimize as so\n",
      "# import bbobbenchmarks as bb\n",
      "# f = bb.F6(0, zerof=True)\n",
      "f = cma.FF2.NoisyFitness(cma.FF.sphere, \n",
      "                         abs_noise=lambda: 0, \n",
      "                         rel_noise=lambda dim: 1.1 * np.random.randn() / dim)\n",
      "# so.fmin_slsqp?\n",
      "# so.fmin?\n",
      "x0 = ones(30)\n",
      "restarts = 3\n",
      "for irun in range(restarts + 1):\n",
      "    x0=so.fmin_slsqp(f, x0, iter=1e3, acc=1e-9)\n",
      "f(x0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 75429198442.9\n",
        "            Iterations: 2\n",
        "            Function evaluations: 74\n",
        "            Gradient evaluations: 2\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 79302101518.7\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 75810291308.3\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 77174074565.6\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 72724911441.9\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 69813497305.8\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 79715839257.8\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 76773173723.6\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 75969204876.2\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 74661889769.4\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n",
        "Inequality constraints incompatible    (Exit mode 4)\n",
        "            Current function value: 78336730588.5\n",
        "            Iterations: 1\n",
        "            Function evaluations: 32\n",
        "            Gradient evaluations: 1\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 66,
       "text": [
        "78499579452.589066"
       ]
      }
     ],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cma.NoiseHandler?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x0 = ones(30)\n",
      "res=cma.fmin(f, x0, 15, \n",
      "             {'popsize': None}, \n",
      "             # noise_handler=cma.NoiseHandler(len(x0)),\n",
      "             #{'verb_disp':0, 'verb_log':0}, \n",
      "             restarts=0) \n",
      "es= res[-2]\n",
      "es.result()[0:3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(7_w,14)-aCMA-ES (mu_w=4.3,w_1=36%) in dimension 30 (seed=737881, Fri Sep 26 10:45:01 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     14 3.698740991917695e+03 1.0e+00 1.39e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     28 4.270071138365895e+03 1.1e+00 1.29e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     42 4.102335705735133e+03 1.1e+00 1.21e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1400 1.743419414786245e+00 1.6e+00 2.22e-01  2e-01  2e-01 0:0.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2800 5.219427157094039e-04 1.7e+00 4.62e-03  3e-03  4e-03 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   4200 1.164382664631448e-07 1.8e+00 8.19e-05  5e-05  6e-05 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   5600 3.601763147666719e-11 1.8e+00 1.57e-06  9e-07  1e-06 0:1.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  487   6818 4.015915635862842e-14 1.8e+00 5.97e-08  3e-08  4e-08 0:2.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Fri Sep 26 10:45:03 2014)\n",
        "final/bestever f-value = 2.109147e-14 2.109147e-14\n",
        "incumbent solution: [ -6.93304861e-08  -1.51790262e-08  -5.26548740e-08  -2.19338456e-08\n",
        "   9.72401733e-09   1.91913696e-09   2.17217270e-08   3.37705657e-08 ...]\n",
        "std deviations: [  3.42825070e-08   3.38642523e-08   3.17482689e-08   3.61136209e-08\n",
        "   3.30437598e-08   3.32195416e-08   3.37823612e-08   3.33660402e-08 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 67,
       "text": [
        "(array([ -6.93304861e-08,  -1.51790262e-08,  -5.26548740e-08,\n",
        "        -2.19338456e-08,   9.72401733e-09,   1.91913696e-09,\n",
        "         2.17217270e-08,   3.37705657e-08,   2.44226182e-09,\n",
        "         9.20720999e-09,   1.04765680e-08,   3.26617110e-08,\n",
        "         7.65138724e-10,  -1.77670838e-08,  -2.81484266e-08,\n",
        "        -1.27108708e-08,   3.38073280e-08,  -4.05847994e-08,\n",
        "        -1.97145154e-08,  -1.05852604e-08,  -2.73345864e-08,\n",
        "         1.13591015e-08,  -1.95504515e-08,   2.53926259e-08,\n",
        "         1.01883885e-08,   3.11303338e-08,  -1.55288164e-08,\n",
        "         8.11959333e-09,   1.31404832e-08,   5.30934867e-08]),\n",
        " 2.1091467601043082e-14,\n",
        " 6819)"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "reload(cma)\n",
      "f = cma.FF2.NoisyFitness(cma.FF.tablet)\n",
      "x0 = ones(22)\n",
      "res=cma.fmin(f, x0, 15, noise_handler=cma.NoiseHandler(len(x0))) \n",
      "es = res[-2]\n",
      "es.result()[0:3]\n",
      "cma.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(6_w,13)-aCMA-ES (mu_w=4.0,w_1=38%) in dimension 22 (seed=751736, Fri Sep 26 10:50:57 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     16 3.207015399566928e+04 1.1e+00 1.38e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     31 1.249702342417075e+04 1.1e+00 1.33e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     47 2.319128359534327e+05 1.1e+00 1.26e+01  1e+01  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1565 3.428575818919457e+05 8.1e+00 1.60e+01  4e+00  2e+01 0:0.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   3128 8.991243785926607e+04 3.6e+01 1.64e+01  9e-01  2e+01 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   4691 1.591432481429884e+04 1.5e+02 1.02e+01  2e-01  2e+01 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   6252 4.767814439789204e+02 3.8e+02 2.26e+00  1e-02  3e+00 0:1.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   7819 2.751265908555007e+00 7.3e+02 4.08e-01  7e-04  4e-01 0:2.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   9384 2.878370307330673e+00 9.3e+02 6.26e-01  7e-04  5e-01 0:2.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  700  10941 5.642142834392939e+00 1.1e+03 6.88e-01  5e-04  5e-01 0:2.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  800  12509 1.164245556280017e+00 1.1e+03 9.57e-01  6e-04  5e-01 0:3.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  900  14069 1.736326598632572e+00 1.2e+03 1.17e+00  5e-04  5e-01 0:3.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1000  15633 2.416777450624867e+00 1.3e+03 1.06e+00  4e-04  4e-01 0:4.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1100  17199 3.207367059799500e+00 1.3e+03 1.62e+00  5e-04  5e-01 0:4.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1200  18764 3.639442159968485e+00 1.4e+03 2.01e+00  5e-04  5e-01 0:4.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1300  20331 2.938319799053689e+00 1.4e+03 2.14e+00  4e-04  4e-01 0:5.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1400  21901 2.873576679734283e+00 1.3e+03 2.53e+00  4e-04  4e-01 0:5.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1500  23468 9.517947747990458e-01 1.3e+03 2.95e+00  4e-04  4e-01 0:6.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1600  25026 3.800514257422423e+00 1.4e+03 4.39e+00  5e-04  5e-01 0:6.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1670  26131 4.124747164925942e+00 1.3e+03 4.80e+00  4e-04  5e-01 0:7.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolstagnation=893 (Fri Sep 26 10:51:04 2014)\n",
        "final/bestever f-value = 9.072503e-02 -1.138169e+00\n",
        "incumbent solution: [-0.00067371 -0.18272607  0.19993807 -0.3425643  -0.35112928 -0.27006578\n",
        "  0.37523121  0.04651746 ...]\n",
        "std deviations: [  4.36595696e-04   4.04463170e-01   4.19373852e-01   4.12466053e-01\n",
        "   4.45566863e-01   4.35759090e-01   4.06417974e-01   4.14376580e-01 ...]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 70,
       "text": [
        "(array([  5.58290162e-04,   9.77246489e-02,   6.15561061e-01,\n",
        "         4.82270348e-01,  -1.61232622e-01,  -1.23469002e-01,\n",
        "         4.36320576e-01,   2.81166168e-01,   2.92380223e-01,\n",
        "        -1.56446490e-01,  -7.28331582e-02,  -4.36664205e-02,\n",
        "        -7.07247890e-01,   2.87591184e-01,  -1.83934954e-01,\n",
        "         7.77793999e-02,   1.14913110e-01,  -8.53370163e-02,\n",
        "         5.86768357e-01,   2.82506480e-01,  -4.85478951e-01,\n",
        "         4.24318736e-01]),\n",
        " -1.1381693102349439,\n",
        " 24703)"
       ]
      }
     ],
     "prompt_number": 70
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's check some of the available options."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "cma.CMAOptions()\n",
      "cma.CMAOptions('boun')\n",
      "cma.CMAOptions('max')\n",
      "cma.CMAOptions('tol')\n",
      "cma.CMAOptions('scal')\n",
      "cma.CMAOptions('fixe')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "{'fixed_variables': 'None  # dictionary with index-value pairs like {0:1.1, 2:0.1} that are not optimized'}"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f = cma.FF2.UnknownFF()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 73
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cma.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 75
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "x0 = f.typical_x(10)\n",
      "print(f(x0))\n",
      "res=cma.fmin(f, x0, 1e-2)  # small step-size\n",
      "es = res[-2]\n",
      "print(f(x0), f(res[0]))\n",
      "cma.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "7.97428576741\n",
        "(5_w,10)-aCMA-ES (mu_w=3.2,w_1=45%) in dimension 10 (seed=824080, Fri Sep 26 10:59:26 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     10 3.409177334010695e+04 1.0e+00 9.18e-03  9e-03  9e-03 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     20 6.407906759348757e+04 1.1e+00 9.05e-03  9e-03  9e-03 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     30 2.054111250492007e+05 1.2e+00 9.13e-03  9e-03  1e-02 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1000 1.010506300754184e+02 5.4e+01 2.46e-03  9e-05  4e-03 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2000 2.218652621748019e+01 1.3e+03 3.25e-04  8e-07  6e-04 0:0.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  300   3000 1.359260018546915e+01 2.1e+01 1.06e-03  3e-07  7e-03 0:0.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4000 8.749193455779661e+00 1.2e+01 1.39e-03  1e-07  3e-03 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5000 8.362820575051998e+00 4.1e+01 9.91e-04  4e-08  2e-03 0:1.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   6000 4.930389571262566e+00 9.0e+02 2.79e-02  6e-07  5e-01 0:1.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  700   7000 4.550442806285886e+00 1.1e+03 4.60e-05  4e-10  4e-04 0:2.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  800   8000 4.550442510550710e+00 1.5e+03 2.43e-08  8e-14  1e-07 0:2.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  807   8070 4.550442510550710e+00 1.5e+03 1.77e-08  6e-14  8e-08 0:2.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Fri Sep 26 10:59:29 2014)\n",
        "final/bestever f-value = 4.550443e+00 4.550443e+00\n",
        "incumbent solution: [ -1.01784466e-04   1.04751683e-01   7.39160556e-06   3.50394251e-01\n",
        "   2.85151243e-01   1.30833366e-01  -1.55287106e-01   4.21730279e-03 ...]\n",
        "std deviations: [  6.56841865e-13   1.08811630e-09   5.66237473e-14   9.34224146e-10\n",
        "   1.21611720e-09   8.75543650e-10   5.59407498e-10   1.01176582e-09 ...]\n",
        "7.97428576741 4.55044251055\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 74,
       "text": [
        "<cma.CMADataLogger at 0x112025490>"
       ]
      }
     ],
     "prompt_number": 74
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "x0 = f.typical_x(10)\n",
      "# x0 = best[min(best)].x\n",
      "# x0 = res[0]\n",
      "print(f(x0))\n",
      "res=cma.fmin(f, x0, 5, \n",
      "             # restarts=1, incpopsize=2, \n",
      "             options={'scaling': r_[.5e-3, 1, .5e-4, 6*[1], 1e2]\n",
      "     }\n",
      "    )\n",
      "es = res[-2]\n",
      "print(f(x0), f(res[0]))\n",
      "cma.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "7.97428576741\n",
        "(5_w,10)-aCMA-ES (mu_w=3.2,w_1=45%) in dimension 10 (seed=825813, Fri Sep 26 11:05:17 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     10 1.628314822515112e+03 1.0e+00 3.21e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     20 6.333563205771474e+02 1.1e+00 2.96e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     30 4.112879614172572e+02 1.2e+00 2.72e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1000 2.459225201774954e+01 4.3e+00 1.33e-02  6e-03  1e-02 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2000 2.345456153748471e+01 8.9e+00 7.64e-05  2e-05  4e-05 0:0.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300   3000 2.345455843647335e+01 9.5e+00 5.35e-08  5e-09  1e-08 0:0.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  322   3220 2.345455843647302e+01 1.1e+01 1.05e-08  8e-10  2e-09 0:0.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Fri Sep 26 11:05:18 2014)\n",
        "final/bestever f-value = 2.345456e+01 2.345456e+01\n",
        "incumbent solution: [ -4.66242817e-04   9.38653347e-01   2.59966607e-05  -1.76590560e+00\n",
        "   1.05819040e+00  -1.62653455e-01  -7.33848633e-01  -4.60478228e-01 ...]\n",
        "std deviations: [  8.48679128e-13   1.66638934e-09   7.78812504e-14   1.59497562e-09\n",
        "   1.26792628e-09   1.04323327e-09   7.69944395e-10   1.29098380e-09 ...]\n",
        "(10_w,20)-aCMA-ES (mu_w=5.9,w_1=27%) in dimension 10 (seed=825814, Fri Sep 26 11:05:18 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1   3241 4.823665812708348e+02 1.0e+00 3.28e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2   3261 5.278819257791532e+02 1.2e+00 2.87e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3   3281 5.909786583239293e+02 1.2e+00 2.40e+00  2e+00  2e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   5221 5.389253120900150e+00 3.8e+00 6.06e-02  2e-02  3e-02 0:0.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   7221 -1.419301749764557e+00 1.1e+01 1.74e-05  1e-06  2e-06 0:0.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  261   8441 -1.419301756370672e+00 1.1e+01 2.11e-07  4e-09  1e-08 0:1.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 1 restart (Fri Sep 26 11:05:19 2014)\n",
        "final/bestever f-value = -1.419302e+00 -1.419302e+00\n",
        "incumbent solution: [ -2.07373266e-04  -4.24279442e-01   2.67291461e-05  -2.86467833e-01\n",
        "   4.76413218e-01   6.62010518e-01   1.55700630e-01  -7.06401086e-02 ...]\n",
        "std deviations: [  4.62065629e-12   9.54495166e-09   3.85011446e-13   7.84817375e-09\n",
        "   7.93290303e-09   6.08893598e-09   4.08319476e-09   7.58973911e-09 ...]\n",
        "(20_w,40)-aCMA-ES (mu_w=11.3,w_1=16%) in dimension 10 (seed=825815, Fri Sep 26 11:05:19 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1   8482 5.176197250044970e+02 1.0e+00 3.07e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2   8522 3.177603906919926e+02 1.2e+00 2.59e+00  2e+00  2e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3   8562 3.478275956079751e+02 1.3e+00 2.58e+00  2e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100  12442 -2.408429666711172e+00 8.7e+00 8.00e-03  6e-04  1e-03 0:0.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  187  15922 -2.414260813464097e+00 9.8e+00 7.43e-07  2e-09  6e-09 0:1.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 2 restarts (Fri Sep 26 11:05:21 2014)\n",
        "final/bestever f-value = -2.414261e+00 -2.414261e+00\n",
        "incumbent solution: [ -3.56642887e-04  -5.56009737e-01   9.00798695e-06   1.48260185e-01\n",
        "  -5.76482642e-02   8.62015037e-02   2.33714280e-01  -2.40288918e-01 ...]\n",
        "std deviations: [  2.90033459e-12   5.73903824e-09   2.81653823e-13   5.03622470e-09\n",
        "   4.97144050e-09   3.46439820e-09   2.47022958e-09   4.47349656e-09 ...]\n",
        "(40_w,80)-aCMA-ES (mu_w=21.8,w_1=9%) in dimension 10 (seed=825816, Fri Sep 26 11:05:21 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  16003 5.294129795928528e+02 1.0e+00 3.41e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2  16083 3.516744409489680e+02 1.4e+00 3.50e+00  3e+00  4e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  16163 5.892527074171256e+02 1.8e+00 3.58e+00  3e+00  4e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100  23923 4.467784332280940e+01 2.6e+01 1.09e+00  1e-01  3e-01 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200  31923 -1.419301755743234e+00 1.2e+01 1.94e-03  2e-07  6e-07 0:2.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  225  33923 -1.419301756370686e+00 1.1e+01 2.36e-04  5e-09  1e-08 0:2.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 3 restarts (Fri Sep 26 11:05:23 2014)\n",
        "final/bestever f-value = -1.419302e+00 -2.414261e+00\n",
        "incumbent solution: [ -1.96707445e-04   1.06252580e-02  -9.26159191e-06   4.72277053e-02\n",
        "  -8.30128141e-01  -2.14603826e-01   8.21767126e-02  -6.80198617e-01 ...]\n",
        "std deviations: [  6.38042296e-12   1.17739718e-08   3.75163780e-13   1.04195454e-08\n",
        "   1.02951288e-08   7.88299021e-09   5.41462887e-09   9.51921038e-09 ...]\n",
        "(80_w,160)-aCMA-ES (mu_w=42.4,w_1=5%) in dimension 10 (seed=825817, Fri Sep 26 11:05:23 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  34084 4.438181683138968e+02 1.0e+00 3.72e+00  3e+00  4e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2  34244 2.805304224053467e+02 1.6e+00 3.55e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  34404 3.154543825010660e+02 2.3e+00 3.36e+00  2e+00  3e+00 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100  49924 -5.399032273839950e+00 1.0e+01 2.82e-01  1e-04  2e-04 0:2.7\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  153  58404 -5.399137984743831e+00 1.1e+01 1.44e-02  5e-09  1e-08 0:4.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 4 restarts (Fri Sep 26 11:05:28 2014)\n",
        "final/bestever f-value = -5.399138e+00 -5.399138e+00\n",
        "incumbent solution: [ -3.32114075e-04  -6.57260679e-01   1.24814643e-05  -9.52831422e-02\n",
        "  -6.66799225e-02   1.80176221e-01  -2.01197211e-01  -5.03151125e-01 ...]\n",
        "std deviations: [  6.55185449e-12   1.15363482e-08   6.01686005e-13   1.05059260e-08\n",
        "   1.01019508e-08   8.03718651e-09   5.41995948e-09   1.03322562e-08 ...]\n",
        "(160_w,320)-aCMA-ES (mu_w=83.1,w_1=3%) in dimension 10 (seed=825818, Fri Sep 26 11:05:28 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  58725 3.502768314092597e+02 1.0e+00 3.60e+00  3e+00  3e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=1):  clipped learning rate for negative weights, maximal eigenvalue = 2.889851, maxeig * ccov = 0.652873 > 0.600000\n",
        "new min eigenval = 1.562992e-01, old = 3.863606e-01\n",
        "new cond = 7.665301e+00, old = 2.982227e+00\n",
        "    2  59045 2.092622389500033e+02 2.8e+00 3.34e+00  2e+00  3e+00 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  59365 1.953991915097024e+02 4.3e+00 3.13e+00  2e+00  2e+00 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100  90405 -6.394097041821453e+00 9.6e+00 6.61e-01  5e-08  1e-07 0:6.4\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  110  93605 -6.394097041837313e+00 9.8e+00 4.96e-01  3e-09  8e-09 0:7.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 5 restarts (Fri Sep 26 11:05:35 2014)\n",
        "final/bestever f-value = -6.394097e+00 -6.394097e+00\n",
        "incumbent solution: [ -2.12257584e-04  -5.89875347e-02   6.64943554e-06  -2.90769726e-01\n",
        "  -3.22726067e-02  -2.65541995e-02  -1.76193413e-01  -2.69101173e-01 ...]\n",
        "std deviations: [  3.90380324e-12   7.39449123e-09   3.71036472e-13   6.38040920e-09\n",
        "   6.19921812e-09   5.13403149e-09   3.44111135e-09   5.45732097e-09 ...]\n",
        "(320_w,640)-aCMA-ES (mu_w=164.0,w_1=1%) in dimension 10 (seed=825819, Fri Sep 26 11:05:35 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  94246 2.820858111979802e+02 1.0e+00 3.52e+00  2e+00  3e+00 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=1):  clipped learning rate for negative weights, maximal eigenvalue = 5.765172, maxeig * ccov = 1.485939 > 0.600000\n",
        "new min eigenval = 6.120715e-02, old = 1.523567e-01\n",
        "new cond = 1.923430e+01, old = 7.537982e+00\n",
        "    2  94886 2.071426324972180e+02 4.4e+00 3.39e+00  2e+00  3e+00 0:0.1"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  95526 1.061292181794744e+02 6.7e+00 3.27e+00  1e+00  2e+00 0:0.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=52):  clipped learning rate for negative weights, maximal eigenvalue = 3.593793, maxeig * ccov = 0.926279 > 0.600000\n",
        "new min eigenval = 2.711333e-06, old = 2.781527e-06\n",
        "new cond = 2.459895e+03, old = 2.371392e+03\n",
        "WARNING (module=cma, iteration=61): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.779153, maxeig * ccov = 0.974054 > 0.600000\n",
        "new min eigenval = 1.857547e-07, old = 1.826002e-07\n",
        "new cond = 1.183733e+03, old = 2.674914e+03\n",
        "WARNING (module=cma, iteration=63): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.462762, maxeig * ccov = 0.634762 > 0.600000\n",
        "new min eigenval = 8.283250e-08, old = 8.140629e-08\n",
        "new cond = 3.356571e+02, old = 7.137568e+02\n",
        "  100 157606 -6.394097041836673e+00 1.2e+01 5.43e+00  1e-08  3e-08 0:17.3"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  107 162086 -6.394097041837355e+00 1.2e+01 4.96e+00  1e-09  2e-09 0:19.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 6 restarts (Fri Sep 26 11:05:54 2014)\n",
        "final/bestever f-value = -6.394097e+00 -6.394097e+00\n",
        "incumbent solution: [ -1.34816747e-04   2.71016680e-02   2.31772582e-07   9.57570896e-03\n",
        "  -1.20117304e-02   2.73937428e-03  -2.07799795e-02   5.53736027e-02 ...]\n",
        "std deviations: [  9.57245058e-13   2.09608734e-09   9.46097520e-14   1.63892276e-09\n",
        "   1.57566075e-09   1.36536924e-09   1.00242172e-09   1.43711298e-09 ...]\n",
        "7.97428576741 -6.39409704184\n"
       ]
      }
     ],
     "prompt_number": 76
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "# best = {}\n",
      "# best[res[1]] = res[-2].best\n",
      "if res[1] < min(best):\n",
      "    best[res[1]] = res[-2].best\n",
      "best"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 582,
       "text": [
        "{-6.3940970418373553: <cma.BestSolution at 0x10ae90490>,\n",
        " -5.3991379847440584: <cma.BestSolution at 0x123971d90>,\n",
        " -0.42434269927757384: <cma.BestSolution at 0x121660e50>,\n",
        " 5.5453813709295474: <cma.BestSolution at 0x120d2d950>,\n",
        " 7.5353146440114784: <cma.BestSolution at 0x11624af10>,\n",
        " 7.5353146440115069: <cma.BestSolution at 0x1189a0b10>,\n",
        " 7.5353146440115211: <cma.BestSolution at 0x116b3ae50>,\n",
        " 22.459599379379753: <cma.BestSolution at 0x114d9f1d0>}"
       ]
      }
     ],
     "prompt_number": 582
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "cma.Sections?\n",
      "# s = cma.Sections(f, x0).do(plot=False, \n",
      "#            locations=arange(-0.01, 0.01, 0.001))\n",
      "# s = cma.Sections(f, x0, basis=cma.Rotation()(np.eye(10))).do(plot=False)\n",
      "s = cma.Sections(f, x0, \n",
      "                 basis=diag(r_[2e-3, 1, 1e-4, 6*[1], 1e2]),\n",
      "                 ).do(plot=False, \n",
      "                    locations=arange(-0.2, 0.2, 0.01)\n",
      ")\n",
      "figure(1)\n",
      "hold(False)\n",
      "s.plot(plot)"
     ],
     "language": "python",
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 77,
       "text": [
        "<cma.Sections at 0x11056bbd0>"
       ]
      }
     ],
     "prompt_number": 77
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "f = cma.FF2.UnknownFF()\n",
      "x0 = f.typical_x(10)\n",
      "# x0 = res[0]  # 2.781408742568728e+02\n",
      "res=cma.fmin(f, x0, 1e1, restarts=7, options={'CMA_elitist': False, \n",
      "                           #'scaling': r_[.5e-3, 1, 1e-4, 6*[1], 1e2], \n",
      "                           'popsize': 10}, \n",
      "             eval_initial_x=False)\n",
      "# res=cma.fmin(f, res[-2], None, {'tolfacupx': 1e5})\n",
      "es = res[-2]\n",
      "if 1 < 3:\n",
      "    es.logger.plot(fig=1)\n",
      "    figure(2)\n",
      "    es.logger.plot_mean()\n",
      "    figure(3)\n",
      "    es.logger.plot_mean(x_opt=zeros(10))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(5_w,10)-aCMA-ES (mu_w=3.2,w_1=45%) in dimension 10 (seed=170269, Thu Aug 14 18:16:48 2014)\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1     10 2.114572800352607e+09 1.0e+00 8.55e+00  8e+00  9e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     20 9.993596192248468e+09 1.1e+00 7.74e+00  7e+00  8e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     30 2.984559525592937e+10 1.2e+00 7.98e+00  7e+00  8e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100   1000 3.725919941496404e+07 5.3e+01 3.02e+00  1e-01  4e+00 0:0.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200   2000 8.586338645554262e+05 9.7e+02 2.79e-01  8e-04  5e-01 0:0.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  300   3000 1.178251154413742e+05 1.9e+01 1.94e+00  7e-04  2e+01 0:0.9"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400   4000 8.249545001119819e+03 3.7e+01 1.81e+00  1e-04  4e+00 0:1.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500   5000 1.118127206055699e+02 5.3e+01 1.37e+00  4e-05  2e+00 0:1.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  600   6000 1.296515249927134e+01 6.7e+01 7.29e-03  1e-07  8e-03 0:1.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  700   7000 1.279360842074040e+01 3.1e+02 9.60e-03  8e-08  3e-02 0:2.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  800   8000 1.251008532906548e+01 1.6e+03 2.31e-04  1e-09  1e-03 0:2.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  900   9000 1.251008469494589e+01 1.8e+03 3.83e-07  9e-13  1e-06 0:2.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  923   9230 1.251008469494445e+01 1.7e+03 1.11e-07  2e-13  2e-07 0:2.9\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 (Thu Aug 14 18:16:51 2014)\n",
        "final/bestever f-value = 1.251008e+01 1.251008e+01\n",
        "incumbent solution: [ -9.28065583e-04  -6.68560598e-01   2.69673641e-05  -4.96809055e-01\n",
        "  -2.73722201e-01   4.12597293e-02  -8.90469255e-01  -9.46815106e-01 ...]\n",
        "std deviations: [  2.40159883e-12   4.24169676e-09   2.12914849e-13   3.63186279e-09\n",
        "   3.66535986e-09   3.04246091e-09   1.80340342e-09   3.76646489e-09 ...]\n",
        "(10_w,20)-aCMA-ES (mu_w=5.9,w_1=27%) in dimension 10 (seed=170270, Thu Aug 14 18:16:51 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1   9251 1.868220136971357e+10 1.0e+00 8.64e+00  8e+00  9e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2   9271 3.813143348761700e+08 1.2e+00 7.92e+00  7e+00  8e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3   9291 1.238260203705370e+09 1.3e+00 7.00e+00  6e+00  7e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  100  11231 1.110565625010712e+04 8.7e+02 2.75e-01  7e-04  4e-01 0:0.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  200  13231 9.110605696251567e+02 8.5e+00 2.24e+00  2e-04  3e+00 0:0.9"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300  15231 1.628188257700930e+01 2.7e+01 1.32e-01  2e-06  1e-01 0:1.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  400  17231 1.580262185071348e+00 7.8e+02 2.80e-02  1e-07  1e-01 0:1.8\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  500  19231 1.565570377096265e+00 8.6e+02 3.31e-06  3e-12  3e-06 0:2.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  523  19691 1.565570377089955e+00 7.9e+02 3.49e-07  2e-13  2e-07 0:2.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 1 restart (Thu Aug 14 18:16:53 2014)\n",
        "final/bestever f-value = 1.565570e+00 1.565570e+00\n",
        "incumbent solution: [ -8.44152561e-05   4.70740289e-01   9.97868931e-07  -7.72172981e-01\n",
        "  -2.85666209e-01  -5.81488289e-02   2.02646685e-01   5.77355552e-02 ...]\n",
        "std deviations: [  2.06465371e-12   3.63665537e-09   1.89364931e-13   3.85223988e-09\n",
        "   3.64946741e-09   2.96941081e-09   1.96366492e-09   3.33378340e-09 ...]\n",
        "(20_w,40)-aCMA-ES (mu_w=11.3,w_1=16%) in dimension 10 (seed=170271, Thu Aug 14 18:16:53 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  19732 1.233642234589675e+09 1.0e+00 9.19e+00  9e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "    2  19772 1.061928361254877e+09 1.4e+00 8.97e+00  7e+00  9e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  19812 4.444947038187292e+09 1.6e+00 8.65e+00  6e+00  9e+00 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  100  23692 1.610068809974724e+02 9.1e+00 1.68e+00  1e-04  3e+00 0:0.7"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200  27692 -2.254167431331865e+00 5.4e+02 1.04e-01  4e-07  4e-01 0:1.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  300  31692 -2.414265851283147e+00 5.8e+02 4.05e-06  4e-13  5e-07 0:2.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  301  31732 -2.414265851283233e+00 6.1e+02 3.85e-06  4e-13  5e-07 0:2.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 2 restarts (Thu Aug 14 18:16:56 2014)\n",
        "final/bestever f-value = -2.414266e+00 -2.414266e+00\n",
        "incumbent solution: [ -2.66848764e-04  -1.25137755e+00   1.03764366e-05   3.00846868e-01\n",
        "  -5.15778220e-02   4.20688729e-01   1.24820839e-01  -4.45399052e-01 ...]\n",
        "std deviations: [  3.63179366e-12   7.42381751e-09   4.06281728e-13   7.46969289e-09\n",
        "   7.34719379e-09   5.09605007e-09   3.80788817e-09   6.00808343e-09 ...]\n",
        "(40_w,80)-aCMA-ES (mu_w=21.8,w_1=9%) in dimension 10 (seed=170272, Thu Aug 14 18:16:56 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  31813 4.569120550233187e+09 1.0e+00 9.51e+00  8e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "    2  31893 7.915905791091508e+09 1.6e+00 1.05e+01  7e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  31973 1.376750628537953e+09 2.4e+00 1.04e+01  5e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  100  39733 3.897175371756912e+01 1.2e+02 1.73e+00  1e-05  2e+00 0:1.3"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  200  47733 -6.394050057005757e+00 1.3e+03 1.76e-01  1e-08  1e-02 0:2.6\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  271  53413 -6.394097041837099e+00 1.2e+03 1.10e-03  6e-13  6e-07 0:3.5\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 3 restarts (Thu Aug 14 18:16:59 2014)\n",
        "final/bestever f-value = -6.394097e+00 -6.394097e+00\n",
        "incumbent solution: [ -2.12257585e-04  -5.89875344e-02   6.64943532e-06  -2.90769723e-01\n",
        "  -3.22726080e-02  -2.65542027e-02  -1.76193412e-01  -2.69101175e-01 ...]\n",
        "std deviations: [  6.57137837e-12   1.25554790e-08   5.92128951e-13   1.12907570e-08\n",
        "   9.83301996e-09   8.15947937e-09   5.49378449e-09   9.64842358e-09 ...]\n",
        "(80_w,160)-aCMA-ES (mu_w=42.4,w_1=5%) in dimension 10 (seed=170273, Thu Aug 14 18:16:59 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  53574 1.493094415473587e+09 1.0e+00 9.96e+00  8e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "    2  53734 9.488080958808970e+08 2.0e+00 1.02e+01  5e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3  53894 4.191288927924591e+07 3.9e+00 9.91e+00  2e+00  1e+01 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "  100  69414 -4.740445070327823e+00 3.1e+02 1.79e+00  6e-07  7e-01 0:2.9"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  178  81894 -5.399137984743859e+00 6.1e+02 2.73e-02  7e-13  8e-07 0:5.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 4 restarts (Thu Aug 14 18:17:04 2014)\n",
        "final/bestever f-value = -5.399138e+00 -6.394097e+00\n",
        "incumbent solution: [ -1.29462310e-04   6.04657476e-02   2.18229631e-06   2.39562113e-02\n",
        "   1.05039568e-02  -1.60630118e-02   2.92767313e-03  -9.16741234e-04 ...]\n",
        "std deviations: [  7.18300657e-12   1.31284763e-08   7.19325262e-13   1.20361525e-08\n",
        "   1.20840152e-08   9.05948203e-09   6.39263705e-09   1.12973348e-08 ...]\n",
        "(160_w,320)-aCMA-ES (mu_w=83.1,w_1=3%) in dimension 10 (seed=170274, Thu Aug 14 18:17:05 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1  82215 1.412160146958559e+09 1.0e+00 1.01e+01  6e+00  1e+01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "WARNING (module=cma, iteration=1):  clipped learning rate for negative weights, maximal eigenvalue = 3.522838, maxeig * ccov = 0.795877 > 0.600000\n",
        "new min eigenval = 1.297723e-01, old = 3.227626e-01\n",
        "new cond = 1.153180e+01, old = 4.545350e+00\n",
        "    2  82535 5.696429465662079e+08 3.4e+00 9.67e+00  2e+00  1e+01 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=2):  clipped learning rate for negative weights, maximal eigenvalue = 3.541480, maxeig * ccov = 0.800089 > 0.600000\n",
        "new min eigenval = 1.738888e-02, old = 4.192105e-02\n",
        "new cond = 9.952869e+01, old = 4.109000e+01\n",
        "    3  82855 7.993623540371940e+06 1.0e+01 9.45e+00  7e-01  1e+01 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=3):  clipped learning rate for negative weights, maximal eigenvalue = 3.412817, maxeig * ccov = 0.771021 > 0.600000\n",
        "new min eigenval = 2.469829e-03, old = 5.942988e-03\n",
        "new cond = 7.690398e+02, old = 3.095869e+02\n",
        "WARNING (module=cma): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "WARNING (module=cma, iteration=17):  clipped learning rate for negative weights, maximal eigenvalue = 3.321066, maxeig * ccov = 0.750293 > 0.600000\n",
        "new min eigenval = 1.240124e-01, old = 1.356219e-01\n",
        "new cond = 1.321267e+01, old = 1.170474e+01\n",
        "WARNING (module=cma, iteration=87): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.711096, maxeig * ccov = 0.612489 > 0.600000\n",
        "new min eigenval = 3.424532e-08, old = 3.516429e-08\n",
        "new cond = 8.810240e+04, old = 8.730169e+04\n",
        "  100 113895 -7.383938446935616e+00 3.4e+02 1.73e+01  8e-08  1e-01 0:7.0"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  155 131495 -7.389056098930467e+00 3.8e+02 1.15e+01  5e-13  6e-07 0:11.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 5 restarts (Thu Aug 14 18:17:16 2014)\n",
        "final/bestever f-value = -7.389056e+00 -7.389056e+00\n",
        "incumbent solution: [ -2.82887961e-12  -2.93490947e-09   1.41863213e-13  -1.18873948e-09\n",
        "   2.88066964e-10   1.97910947e-09  -1.20717223e-09  -2.76452745e-09 ...]\n",
        "std deviations: [  4.18319206e-12   1.01516763e-08   4.71052695e-13   8.10858929e-09\n",
        "   9.12044614e-09   7.11299316e-09   4.94479557e-09   8.09421847e-09 ...]\n",
        "(320_w,640)-aCMA-ES (mu_w=164.0,w_1=1%) in dimension 10 (seed=170275, Thu Aug 14 18:17:16 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1 132136 2.814911761794240e+08 1.0e+00 9.68e+00  2e+00  1e+01 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "WARNING (module=cma, iteration=1):  clipped learning rate for negative weights, maximal eigenvalue = 22.376923, maxeig * ccov = 5.767518 > 0.600000\n",
        "new min eigenval = 2.087831e-02, old = 5.213282e-02\n",
        "new cond = 6.147547e+01, old = 2.455263e+01\n",
        "    2 132776 6.927377870428429e+06 7.8e+00 1.03e+01  6e-01  1e+01 0:0.2"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=2):  clipped learning rate for negative weights, maximal eigenvalue = 8.492280, maxeig * ccov = 2.188834 > 0.600000\n",
        "new min eigenval = 1.174076e-03, old = 2.918970e-03\n",
        "new cond = 1.344308e+03, old = 5.355596e+02\n",
        "    3 133416 5.820114549560329e+05 3.7e+01 1.13e+01  2e-01  1e+01 0:0.2"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=3):  clipped learning rate for negative weights, maximal eigenvalue = 5.957531, maxeig * ccov = 1.535518 > 0.600000\n",
        "new min eigenval = 1.516998e-04, old = 2.692929e-04\n",
        "new cond = 1.193473e+04, old = 6.705478e+03\n",
        "WARNING (module=cma, iteration=4): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.911051, maxeig * ccov = 1.008050 > 0.600000\n",
        "new min eigenval = 1.896141e-05, old = 4.292363e-05\n",
        "new cond = 1.124678e+05, old = 4.881851e+04\n",
        "WARNING (module=cma, iteration=5): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.772191, maxeig * ccov = 0.972260 > 0.600000\n",
        "new min eigenval = 3.687686e-06, old = 6.096772e-06\n",
        "new cond = 5.681423e+05, old = 3.334639e+05\n",
        "WARNING (module=cma, iteration=6): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.705854, maxeig * ccov = 0.697418 > 0.600000\n",
        "new min eigenval = 5.134896e-07, old = 1.250345e-06\n",
        "new cond = 4.943321e+06, old = 1.961524e+06\n",
        "WARNING (module=cma, iteration=7): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.017727, maxeig * ccov = 0.777801 > 0.600000\n",
        "new min eigenval = 1.102959e-07, old = 1.855507e-07\n",
        "new cond = 2.676739e+07, old = 1.524562e+07\n",
        "WARNING (module=cma, iteration=8): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.010757, maxeig * ccov = 0.776005 > 0.600000\n",
        "new min eigenval = 2.422549e-08, old = 4.216844e-08\n",
        "new cond = 1.188849e+08, old = 6.651969e+07\n",
        "WARNING (module=cma): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "WARNING (module=cma, iteration=11): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 9.063165, maxeig * ccov = 2.335976 > 0.600000\n",
        "new min eigenval = 5.354053e-02, old = 1.232710e-01\n",
        "new cond = 3.553478e+01, old = 1.531510e+01\n",
        "WARNING (module=cma, iteration=75): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 6.525911, maxeig * ccov = 1.682014 > 0.600000\n",
        "new min eigenval = 2.045476e-09, old = 2.084220e-09\n",
        "new cond = 1.020133e+05, old = 1.123477e+05\n",
        "  100 195496 -7.389055797037472e+00 3.2e+02 1.07e+02  6e-10  8e-04 0:19.1"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  127 212776 -7.389056098930624e+00 4.0e+02 2.16e+02  2e-13  3e-07 0:25.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 6 restarts (Thu Aug 14 18:17:41 2014)\n",
        "final/bestever f-value = -7.389056e+00 -7.389056e+00\n",
        "incumbent solution: [ -1.39237526e-12  -2.25074421e-09   1.18611423e-13  -6.28215391e-10\n",
        "   7.79064077e-10   7.11466951e-10  -9.45158574e-10  -6.39564473e-10 ...]\n",
        "std deviations: [  2.95557703e-12   5.19360090e-09   2.04533055e-13   4.52112301e-09\n",
        "   4.14237327e-09   3.33008202e-09   2.37508221e-09   4.75338606e-09 ...]\n",
        "(640_w,1280)-aCMA-ES (mu_w=324.9,w_1=1%) in dimension 10 (seed=170276, Thu Aug 14 18:17:41 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1 214057 5.569802148714306e+07 1.0e+00 1.02e+01  3e+00  1e+01 0:0.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAEvolutionStrategy, method=updateBD):  doing two additional eigendecompositions to guarantee pos.def.\n",
        "WARNING (module=cma, method=updateBD):  further warnings are surpressed\n",
        "WARNING (module=cma, iteration=1):  clipped learning rate for negative weights, maximal eigenvalue = 17.623541, maxeig * ccov = 4.886512 > 0.600000\n",
        "new min eigenval = 2.461447e-02, old = 6.145886e-02\n",
        "new cond = 4.776496e+01, old = 1.903551e+01\n",
        "    2 215337 1.233361067252273e+07 6.9e+00 1.14e+01  8e-01  1e+01 0:0.3"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=2):  clipped learning rate for negative weights, maximal eigenvalue = 5.676426, maxeig * ccov = 1.573913 > 0.600000\n",
        "new min eigenval = 2.111636e-03, old = 5.254519e-03\n",
        "new cond = 6.505767e+02, old = 2.575964e+02\n",
        "    3 216617 1.259767256567473e+06 2.6e+01 1.17e+01  2e-01  1e+01 0:0.5"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, iteration=3):  clipped learning rate for negative weights, maximal eigenvalue = 5.704654, maxeig * ccov = 1.581740 > 0.600000\n",
        "new min eigenval = 1.692225e-04, old = 4.175788e-04\n",
        "new cond = 8.879611e+03, old = 3.544226e+03\n",
        "WARNING (module=cma, iteration=4): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.453311, maxeig * ccov = 0.957506 > 0.600000\n",
        "new min eigenval = 4.824134e-05, old = 6.841192e-05\n",
        "new cond = 3.227091e+04, old = 2.211611e+04\n",
        "WARNING (module=cma, iteration=5): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.767723, maxeig * ccov = 1.044684 > 0.600000\n",
        "new min eigenval = 6.976919e-06, old = 1.597819e-05\n",
        "new cond = 2.314260e+05, old = 9.765246e+04\n",
        "WARNING (module=cma, iteration=6): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.592551, maxeig * ccov = 0.718841 > 0.600000\n",
        "new min eigenval = 2.428122e-06, old = 3.919205e-06\n",
        "new cond = 7.406002e+05, old = 4.409920e+05\n",
        "WARNING (module=cma, iteration=7): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.746628, maxeig * ccov = 0.761563 > 0.600000\n",
        "new min eigenval = 4.435979e-07, old = 1.084714e-06\n",
        "new cond = 4.329917e+06, old = 1.717392e+06\n",
        "WARNING (module=cma, iteration=8): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.765327, maxeig * ccov = 0.766747 > 0.600000\n",
        "new min eigenval = 2.141345e-07, old = 3.029474e-07\n",
        "new cond = 9.845818e+06, old = 6.716550e+06\n",
        "WARNING (module=cma, iteration=9): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 3.139071, maxeig * ccov = 0.870376 > 0.600000\n",
        "new min eigenval = 3.529620e-08, old = 8.704273e-08\n",
        "new cond = 5.927247e+07, old = 2.376720e+07\n",
        "WARNING (module=cma, iteration=11): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.688571, maxeig * ccov = 0.745465 > 0.600000\n",
        "new min eigenval = 3.048118e-09, old = 7.584489e-09\n",
        "new cond = 5.117286e+08, old = 1.998270e+08\n",
        "WARNING (module=cma):  condition in coordinate system exceeded 1e8, rescaled to 1\n",
        "WARNING (module=cma, iteration=12): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 5.872553, maxeig * ccov = 1.628294 > 0.600000\n",
        "new min eigenval = 3.570613e-02, old = 8.002084e-02\n",
        "new cond = 4.625066e+01, old = 2.020624e+01\n",
        "WARNING (module=cma, iteration=63): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 4.085380, maxeig * ccov = 1.132761 > 0.600000\n",
        "new min eigenval = 3.138484e-09, old = 3.034488e-09\n",
        "new cond = 1.420398e+05, old = 1.576426e+05\n",
        "WARNING (module=cma, iteration=64): "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " clipped learning rate for negative weights, maximal eigenvalue = 2.276228, maxeig * ccov = 0.631134 > 0.600000\n",
        "new min eigenval = 2.284244e-09, old = 2.159665e-09\n",
        "new cond = 1.429817e+05, old = 1.432711e+05\n",
        "  100 340777 -6.394097041834598e+00 3.8e+02 5.15e+01  2e-12  2e-06 1:6.3"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  108 351017 -6.394097041837355e+00 3.2e+02 4.51e+01  1e-13  1e-07 1:13.2\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on tolfun=1e-11 after 7 restarts (Thu Aug 14 18:18:54 2014)\n",
        "final/bestever f-value = -6.394097e+00 -7.389056e+00\n",
        "incumbent solution: [ -2.12257584e-04  -5.89875343e-02   6.64943553e-06  -2.90769726e-01\n",
        "  -3.22726065e-02  -2.65542003e-02  -1.76193413e-01  -2.69101172e-01 ...]\n",
        "std deviations: [  1.20838272e-12   2.27967657e-09   1.14088312e-13   2.06823189e-09\n",
        "   1.97177152e-09   1.50689769e-09   1.00982561e-09   1.82914435e-09 ...]\n"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "reload(cma)\n",
      "o = cma.CMAOptions()\n",
      "o.set('ftarg', 3)\n",
      "o.ftarget = 4\n",
      "o.tolfun = 33\n",
      "# o['gftarge'] = 4\n",
      "# o.gtarg = 55\n",
      "# cma.CMAEvolutionStrategy(ones(2), 1, o)\n",
      "# cma.fmin(cma.felli, ones(3), 1, o)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "WARNING (module=cma, class=CMAOptions, method=check):  \n",
        "        An option attribute has been merged into the dictionary,\n",
        "        thereby possibly overwriting the dictionary value, and the\n",
        "        attribute has been removed. Assign options with\n",
        "\n",
        "            ``opts['tolfun'] = value``  # dictionary assignment\n",
        "\n",
        "        or use\n",
        "\n",
        "            ``opts.set('tolfun', value)  # here isinstance(opts, CMAOptions)\n",
        "\n",
        "        instead of\n",
        "\n",
        "            ``opts.tolfun = value``  # attribute assignment\n",
        "                        \n",
        "WARNING (module=cma, class=CMAOptions, method=check):  \n",
        "        An option attribute has been merged into the dictionary,\n",
        "        thereby possibly overwriting the dictionary value, and the\n",
        "        attribute has been removed. Assign options with\n",
        "\n",
        "            ``opts['ftarget'] = value``  # dictionary assignment\n",
        "\n",
        "        or use\n",
        "\n",
        "            ``opts.set('ftarget', value)  # here isinstance(opts, CMAOptions)\n",
        "\n",
        "        instead of\n",
        "\n",
        "            ``opts.ftarget = value``  # attribute assignment\n",
        "                        \n",
        "(3_w,7)-aCMA-ES (mu_w=2.3,w_1=58%) in dimension 3 (seed=843640, Fri Sep 26 11:12:44 2014)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Iterat #Fevals   function value  axis ratio  sigma  min&max std  t[m:s]\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    1      7 5.372838545343574e+04 1.0e+00 8.68e-01  8e-01  8e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    2     14 5.001763229693996e+03 1.1e+00 7.56e-01  7e-01  7e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "    3     21 4.123893937142180e+04 1.1e+00 6.86e-01  6e-01  6e-01 0:0.0\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "   36    252 1.327905409364908e+00 2.5e+01 1.65e-01  5e-03  1e-01 0:0.1\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "termination on ftarget=4 (Fri Sep 26 11:12:44 2014)\n",
        "final/bestever f-value = 2.535088e+00 1.327905e+00\n",
        "incumbent solution: [-0.85740518 -0.01692421 -0.00123025]\n",
        "std deviation: [ 0.13365414  0.08169331  0.00479633]\n"
       ]
      },
      {
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}