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Last active December 18, 2015 03:08
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Generating and plotting synthetic gravity gradient tensor data with Fatiando a Terra
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{
"metadata": {
"name": "fatiando-maps-and-prisms"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generating and plotting synthetic gravity gradient tensor data with Fatiando a Terra\n",
"\n",
"This notebook demonstrates how to use ![Fatiando a Terra](http://fatiando.org/) to generate and plot gravity gradient data with right rectangular prisms.\n",
"\n",
"First, we load the required modules from Fatiando:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline\n",
"from fatiando import mesher, gridder, gravmag\n",
"from fatiando.vis import mpl, myv"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
"For more information, type 'help(pylab)'.\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can make a prism model and forward model some data:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"prisms = [mesher.Prism(-2500, -1500, -2500, -1500, 800, 1200, {'density':-270}),\n",
" mesher.Prism(1500, 2500, 1500, 2500, 500, 800, {'density':270})]\n",
"shape = (100, 100)\n",
"area = [-5000, 5000, -5000, 5000]\n",
"xp, yp, zp = gridder.regular(area, shape, z=-150)\n",
"fields = [gravmag.prism.gxx(xp, yp, zp, prisms),\n",
" gravmag.prism.gxy(xp, yp, zp, prisms),\n",
" gravmag.prism.gxz(xp, yp, zp, prisms),\n",
" gravmag.prism.gyy(xp, yp, zp, prisms),\n",
" gravmag.prism.gyz(xp, yp, zp, prisms),\n",
" gravmag.prism.gzz(xp, yp, zp, prisms)]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have our data vectors we can plot the generated data:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"titles = ['gxx', 'gxy', 'gxz', 'gyy', 'gyz', 'gzz']\n",
"levels = numpy.linspace(-7, 12, 20) # If you want to put everyone in the same color scale\n",
"mpl.figure(figsize=(10, 8))\n",
"mpl.suptitle(\"Potential fields produced by a prism model\")\n",
"for i, field in enumerate(fields):\n",
" mpl.subplot(2, 3, i + 1)\n",
" mpl.axis('scaled')\n",
" mpl.title(titles[i])\n",
" mpl.contourf(yp, xp, field, shape, levels)\n",
" cb = mpl.colorbar(orientation='horizontal', shrink=0.8)\n",
" cb.set_label(r'$E\\\"otv\\\"os$')\n",
" for prism in prisms:\n",
" mpl.square(prism.get_bounds()[:4], 'k', linewidth=2)\n",
" mpl.m2km() # Convert the plot axis from meters to kilometers. Has to be the last plot function called!\n",
" mpl.xlabel('Horizontal coordinate y (km)')\n",
" mpl.ylabel('Horizontal coordinate x (km)')\n",
"mpl.savefig('figure.png')\n",
"mpl.savefig('figure.pdf')\n",
"mpl.savefig('figure.eps')\n",
"mpl.savefig('figure.svg')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"png": 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TrqhxUab3m5lwrdE64c5n1ni9LGdfw9X5POV2xj4UZDzY4V2zM73VQqigoAC3\nb9/GlStXkJOTY3r+5s2buHjxokuNu3fvHgYOHIhhw4ahX79+5Sd4aZpLr0sysHX2gDe1SzAvkGdP\ntzalx8mRiRqpE1xur9TkLobc3eja23ifOBNuc/1kW3dmgiTg6G1llHCIuHJCG7MC+dr0z2xOb7UQ\n+vzzz5GWlobs7GzExMSYnq9atSomTpzodMOEEBg7dixCQ0MxefJkp+cnK2wNbit7PYjWsN4r5PuY\n7cNjtsYJSdUbJDNmwj6piiEl9czoGTOhTcai50SZxwAQDuvZO4pwhOJ3i/MpoUCyxu4YodmzZ+Mv\nf/mL2wv66aef0KlTJ0RERNwfDwTgww8/RI8ePe43hGOEXOeJMUKllS6IyhZA7owR8sagORnGCEmZ\nCbWOh/B0MSRF4ePIWB+L66Wy8RDewEyon6UeH+PFQt8Wf7U7belC5z3DBwCAfuJfNqeTir1xcw4N\nlj527Bh+//133Llzx/TciBEjPNNCY0NYCLnOldPnd5YpaJy9YmhHYbknSMqB0oBsg6WlyoRaN/qe\nKoS8VQDZ2uj3E/+yurG2WQhZuSK15JgJclLZPBh7fYwFzb+EhaEsNjxr+BbAgwLqKMrnRsqCyF4h\n5NDp89u3b8dvv/2G3r17Y9OmTejQoYPHP+DkBnvXfrB0iGxnmWmcHfOjhCJIJsyEfe4eIpOyALI2\nncsb6rJZ1NBn3xpmQr2sFUGOTGuJpdyE42i5YsitjHmY3UJozZo1OHz4MFq1aoUlS5bg0qVLGDp0\nqBRtI2c4UgwB5XuHdnrgqs/2rjGhsR0BM+EYV4shuYsgZ+8dZpeG77tnxEyok60iqPTvjD08jjlh\n+ql0sWOpGFIKu7fYePjhh+Hj4wNfX1/cuHEDtWrVwvnz56VoGznLkdsHxML9Cx5G93rwOjorggBm\nwpvkLoJcFt3L/jQau9VMacwElRXVqzYA2wOtvZ5LB9ntEWrTpg1yc3Px3HPPoXXr1qhSpQrat28v\nRdvIVcbiw9aGd6UXCxQNFj+lMROOc6ZXSO4zwRwZ2Gm2Lq4UNhq61UxpzIT6OFKE/Ev0My9kck7Y\nmPq+o9Wbm35WRpljn0ODpY0yMzORl5eHiIgIzzeEg6XJFTINDDXydia0MDDUkULIm0WQu986SxdD\nbhdCgPcLIWaCHGApF8Yem9K/c68QCjX7Hyg/cFqKcUL2BkvbPTQGABcvXsTu3btx/vx55ObmYseO\nHR5rIJFMwk21AAAgAElEQVQaMRPkMo0eImMmSK3sHhpLSUnB119/jdDQUPj4+Jie79Spk1cbRt7n\n1qXXNX47BVuYCf1QylktSsdMaMvvCLXYY3S0enObvUKWeoPsUcLZY3YLoW+++QbHjx9HpUqVpGgP\neZmnDkGUfR09FUbMBJE5ZkK7yhZFxmLHWBCVLn5cfX252S2EgoODUVhYyA+4ijla/NgaS2Hvw2pc\nhh4KImaCANi/ZIWOMBPaU7oAstRDZKsAKr2/UEKhY4/dQujhhx9GVFQUunTpYvqQGwwGzJ492+uN\nI/d4ogAqO42jBRGg3aKImSAyx0xow1GEW72gonHb78wX5rKPlXodIbuFUJ8+fdCnTx+z54z3gCFl\n8mQBZG0eR6p8rfYSMROed+JMuNfOHLM23sGR+exirxAAZkKNHMmFpeLH0R4etRRBgJOnz3sTT5/3\nDGd2Jp48rdgRXimIZD5V2Ju0cKqws39zpVxQ0al7jTlbCGn89Hlv0kImlMRaLiz1CjmaIWvZsVYI\nKeH0eas9QoMHD8bq1asRHl6+8QaDAUeOHPFMC8ljpCyCXOHu/afkxkyolzO9Qk5vmJ3pFdLYxRSZ\nCW2ydIjMnYJFziLIEVZ7hLKzs1GvXj1kZWVZnDEoKMizDWGPkMtc+RbtiULInQ+xxwoiCb/9ypEJ\ntX/7VdK9xozcOSnA5vrYK4akKoKYCXKCrTzYugGrI2wdDlPS3ed5aEzlXN1pyF0IGbldEPEwgGIp\n8e7z7nB4fSwVRFL2BDET5CR7+wNnCyJHxgMpqRCyemjM39/f6mA3g8GAmzdvut86cosSdxbOUtOA\namZCOt4cPO11Gjv8ZQszoQ32Dh1bKmxKF0fODoRWyiExI6uFUH5+PgBg6tSpqFevHoYNGwYASE9P\nR3Z2tjStI6tUu5OwQg0FETMhLVUXQzrBTGiHs2dXunoWmNKKIMCBQ2MRERHlBrxZes7thvDQmMM8\nsXNQyqExaxwuiGQ4DCBlJtR6GMCTBa1SiiElF+lmmAlygzdPpJGrCHL7pqtVqlTB8uXLUVxcjOLi\nYqSnp8Pf39+jjSQqSyk7P0uYCSJzzIR2eKNY+R2hiuwJMrJbCK1YsQKrVq1C7dq1Ubt2baxatQor\nVqyQom1kgacKBHc/lFJ8qJs3ParIgoiZkJZqemJ0jJnQFk8VLkovgIxsXlm6uLgY8+bNw/r16z2y\nsM2bN2Py5MkoLi7GuHHjkJKS4pHX1QtPFwVeveKuBylp/BAzIQ+OF1IuT2aCeVCWstt6R/YXaih8\nyrJZCPn4+OCnn36CEMLty6UXFxdj4sSJ+PHHH1G/fn20adMGffr0QUhIiFuvS+5xthiS80OuhIKI\nmbDPW38fFkPK5KlMaDUPWqLGIscRdu81FhUVhb59+2Lw4MGoXLkygPsD1gYMGODUgvbu3YtmzZqZ\nLrD1zDPPYN26dWYfcrVfedibvLkDKP3htlYUKSkAchdEUmaCzLEYUiZPZIJ5ILnYLYTu3LmD6tWr\nY+vWrWbPO7vRv3jxIho2bGh63KBBA/zyyy9m01xLXYAaxp+bDwHaJTi1DK2ScsOvpILHktsZ+1CQ\nsR8AUAPANRnaIHUmjB5OaI3KCW1caLG2yFEMKfoL2p4M4JftsjbBE5lwJA8AM0H2ld5POMJuIfTl\nl1+60x4TR7pMa6ROePAzAIA9RGSuckIbsw3ftemfSd4GuTJBD7BnqJR2CeZfGmdPl7wJnsiEo4fV\nmAmyx9n9hN2zxs6fP4/+/fsjMDAQgYGBGDhwIC5cuOB0w+rXr4/z58+bvW6DBg3szqfUM4ekoud1\nVyq5M0H38UuScngiE8wDycVuITR69Gj06dMH2dnZyM7ORlJSEkaPHu30glq3bo2TJ08iKysLhYWF\n+Prrr9GnTx+H59djQaS39VULpWSCWAwphScyofY8hJpOFrf+j5TJbiF05coVjB49Gn5+fvDz88Oo\nUaNw+fJlpxfk6+uLuXPnonv37ggNDcXTTz/t0iA4vRREelhHtVJaJpREjsLE28tksWWfJzKhxjw4\nW+SwKFImu2OEatSogWXLliE5ORlCCKxcuRI1a9Z0aWE9e/ZEz549XZq3LLnPHCL9Umom9IxjhuTl\nqUyoJQ+eKGRKv4bST1LROrs9QosXL8aqVatQp04d1K1bF6tXr8aSJUukaJtDtNhDpLX10RqlZ0Kv\n+KVIPnrJhLd6c9hDJC+7N12Viqdupqf2jSGLIOfYu5memqnxBpNKyZ+ncqSU9XGKDDddlYqcmZCi\nWGHPkHe4fdNVT50hIxU19xCptd16o7ZM6JEqCxgV03ompOqxYc+QPCQ7a0xqaiqI1NRWUm8m9Mbd\nYojFlOO0nAmpixMWQ9KT7KwxuSi9yFBy28gytWdCT1jMSIOZ8CwWQ9KS9KwxOSntLDMWQOqllUzo\nhStnlCllO6EWWs2EowVJOBz/fB0FP1tKY3ewdFZWFiZNmoQ9e/YAANq3b485c+agUaNGnm2IxIPg\n5NrQsQDyLDkGS2s1E56g9ALCkfwpfR3skmGwtBYz4Y0iqDRHCiIOnvYMe/sJzZ015gopNnwsgLyD\nZ40pixqKCFtZVEP77eJZYx7hSCHkahFkZK8YYiHkGW6fNTZixAhcv37d9Dg3NxdjxozxTOsUwjiO\nyNPFirdel+Sl5Uzo4bYAJ86EW/1HrtFyJqxxtwhy5DW0mD8lsjtG6MiRI6hWrZrpcUBAAA4cOODV\nRsmpbNHizMaRBY8+aDUT1ja6ofid30zJJq1mwhpPFEGkHHYLISEEcnJyUL16dQBATk4OiouLvd4w\npWBxQ2XpMRMshsgWPWbCU8JxlAOoZWa3EHr11VcRFxeHIUOGQAiB1atX46233pKibUSKxEwQmdNa\nJmwdkrLVG2RrPn6RUC6HBkv/9ttv2Lp1KwwGAzp37ozQUM//QdU4MJTkJ9dgaS1mwt54BHsbco6x\nUQiZBktrLRPW8uCNQshWjxALKPfZ20/Y7RECgJYtW6Jly5Yea5RauDpQjR9c7dNrJoisYSZs4+Fl\n5XKoENIyqe8kzCCQUv2OUJ6lQuQlrmz7ub+Qhi4LIXsb+597z8SljYdceu3avaIQ932KQ8vmh5yU\nxlox9H+95+PWxp2uvWhCL2DRBjdbRqQMRxGOcBzFv3p/jVMbTzsx57emn5r1Csaz3z/t+caRS3RV\nCDn6bdfVIsjZeY3tYUFESmLp8+hyEQQAGRvdaA2RPOz1kDpXBFmfl2eMyc9qIeTv7w+DwWDxdwaD\nATdv3vRao7zBlS7/t8VfnZr+PcMHAB4MpnP0A85jx+qgtUy4wt5A1XIDpoPtXrNVcpq/srSE9JqJ\n0tt2V/cTZV+nLO4TpGO1EMrPz5eyHV7l7D1jvrUznaOcKYhYDCmfljKhN45eD0xpN2dWOq1nwpvj\n5lgEKYfDX9cuX76Mc+fOmf45Iz09HZGRkYiIiEB8fDyOHDnidEO9zZErhbp6+wFHr0LKgarqovVM\nqJ07t7jhhVRdo8VMGLf21hxFuEcPb7EIkp7dMULr16/Hq6++iuzsbNSqVQtnz55FSEgIfvvtN4cX\n0rRpU+zYsQOPPvooNm/ejPHjx5vuUuxt7t44z978zhRDPBasDWrPhJZ5soBh75Dj9JAJe71D7m7f\nWQDJx24hNHXqVPz888/o1q0bDh48iG3btmHZsmVOLSQuLs70c2xsLC5cuOB8S73EnSKI9EnrmVAL\nqXptmjc9ymLIDr1kwtPFCosfZbBbCPn5+aFmzZooKSlBcXExEhMT8dJLL7m8wEWLFqFXr14uz69m\njvQKcayQ8jET1nmqF0Vph6ZYDNmm50y4ur3mdl457BZCAQEByMvLQ8eOHTF06FDUqlUL/v7+Li1s\n27ZtWLx4MXbt2mXx99dSF5h+fjihNSontHFpOaRdtzP2oSBjv6xtYCbsMxVEZR6rmWKLoT0ZwC/b\nZW0CM0FK4ux+wu69xm7duoWHHnoIJSUlSE9Px82bNzF06FDUqFHD5gvPnz8fCxcuhMFgwMaNG3H5\n8mUMGDAAmzdvRrNmzco3xEv3kLF3eMvSoTHj6Y3/Ev2cWtazhvvnm9k6ndKR48j8puA4Oe41puZM\nuLwjN54Gf7rEqaLmhCESgP3T7tVEkcVQaTLca0zKTOB0ibdWwzmlMiHJfP+jhS8VUrO3n7BbCKWk\npGDmzJl2n7Pl3Llz6Ny5M5YvX4527dpZbogOCiEWQZ4nRyEkZSbUsNG3eV0eDRZCRootiGQohJgJ\nCeZzEAul8uztJ+yePr9ly5Zyz23c6NyVYt99913k5uZiwoQJiI6ORtu2bZ2a35t4LQdyltYzQY7h\nDucBZgLAPoP9fxI4cSa83D+yzeoYoQULFmD+/Pk4ffo0wsMfvJF5eXmIj493aiFffPEFvvjiC9db\nKSNjMWSvZ+n+dNYvxchT59WPmbDsxJlw3RYFih03JBHdZqJ0UeNMgWNpvjbe770zfkb1mlN7rBZC\nycnJ6NmzJ9544w3MnDnT1K1UtWpVu8d9lcSRK4Mab6Jn73Vc5WgRxB4oZdNKJsiz9FwM6S4TjhY9\nv5T6OdbB15SwIAJYFJVmd4wQABQXF+PSpUsoKioyPdeoUSPPNsRLY4SMnLnwYel7wbii9BghFkHe\nJccYIUC6TChuPISLtDhGqCzFFEMyjBECdJCJskXQM24e6lpp4W8kQTFUlh4KInv7Cbunz8+ZMwfT\np09HrVq14OPjY3r+6FF1vXmO3jPG3UNYzXoFO/0aLILURSuZkEqVXh3lboIk9NwzpPlMeHp8TxMr\n10jaZ5C8GOJhMwd6hIKDg7F3716vd3N6u0fISGlXi2YR5B45eoSkzIRieoTscGQjail7Wv38y1oQ\nydAjpOlMWCuCfrH8tFOsHTaToWcI0G4x5PZZY40aNcIjjzzi0UbJyd4N9PTWDnKe1jIhBWtfQJT2\nxcRTtLpDsUazmXC1J2h/qX9SLtdNej3LzO6hsSZNmiAxMRG9e/dGxYoVAdyvyl955RWvN86byhYh\n3t4gs+jRDq1mQi5ava2Mng6V6S4TtnqDyhY/+wG0tvE69gZTy0Bvh8vsFkKNGjVCo0aNUFhYiMLC\nQggh7ndPaowWN8TkHbrIROlvpDJ102uBXoohXWRCh/RyaQyHzhoD7l8XArh/WqRXGiLRGCHSFrnO\nGgOkyYTsZ8g4WATZ21g6dh0u7ZK0GJLprDFAg5lwZ3yQrZ6g0hQ2TsgStRdDbo8ROnr0KKKjo9Gy\nZUu0bNkSMTExOHbsmEcbSaQmushEG6GoDbHaqX1HYo8uMlGaI4ez3CmCFEbrY4fsFkLjx4/HP/7x\nD5w7dw7nzp3DrFmzMH78eCnaRqRIzITztN7j4wgtF0PMhD5otRiyO0bo9u3bSExMND1OSEjArVu3\nvNooJXDnD67lDR7pNxPusnYtLz0VScZtg9Z2KLrMRCzcO4VeJb1BZWlxILVDZ4299957GD58OIQQ\nSE9PR9OmTaVom6Q8uWEq+1pa+sCQfjLhDXoqemzR2iBq3WbC1WJIpUVQaVoaSG330NjixYtx+fJl\nDBgwAAMHDsSVK1ewePFiKdomCSmOfWr9+KreaD0TJA2t7EQADWfCkXFysXC8sHF0WpWMz9PKfs1u\nj9Bvv/2GTz75BL6+DyY9cOAAAgICvNowb5Lrj6fFLkU90mImSB5a6RliJmBe4Dhz01WV00LPkN0e\noe7du6NLly64dOmS6bmxY8d6tVHeopSeGaW0g1yjpUyQ/NS+EwE0nglXemdi4VxPkbvLk5na92l2\nC6HHH38cr732GhISErBr1y4p2uRxSv0jKbVdZJsWMkHKovZiSPOZkKo4UWERVJpa92d2D40BQFJS\nElq0aIGnn34ao0eP9nabPEYtfxQeMlMftWaClEvtZ5RpPhNthHfvAabyIshIjYfK7PYIGa/G+Nhj\nj2HHjh3YuXMnjhw54vWGuUuNGxM1tlmP1JoJUge17UQAHWXCW8WKRoogI7Xtyxy+xUZp586dQ6NG\njTzbEA/dYkNtfwBL1LghlIuct9gozVuZkO0WG07iZ9bzXN6WyXiLjdI0nwlP9Q5prAgqSwnbBnv7\nCauHxmbOnImUlBRMmjSp3O8MBgNmz57tmRZ6iBYKICMeKlMmtWWC1E0NZ5TpOhPuHirTeAFkpIZD\nZVYLodDQ+xc+a93a/IYp7txVeN++fYiLi8OqVaswYMAAl17DEqVvLFylhg+QnqgpE6QNSi+GdJ+J\n0sWMI0WRToqfspS+L7NaCCUlJaG4uBhHjhzBrFmz3F5QcXExUlJS0KNHD4912yp5A+EpSv8A6Yka\nMkHao+RiiJkoRadFjqOUvC+zOVjax8cHu3bt8sgHcs6cORg0aBACAwPdfi29nXaup3VVOqVmgrSt\nedOjit2JMBPkKKXuy+yePh8VFYW+ffti8ODBqFy5MoD7x36d6bK8ePEi1q1bh61bt2Lfvn1Wu0yv\npS4w/fxwQmtUTmhTbhqlvpHexnFD993O2IeCjP2ytkHKTCBt+oOfY58A2iW40XJSO4u9Q3sygF+2\ny9IeI2aCHCXFvszZ/YTdQujOnTuoXr06tm7dava8Mx/wyZMnY8aMGTAYDBBCWP3mUCN1gtXX0GsB\nVJaSuxelUDmhjVmBfG36Z5K3QcpM4KVp7jSVNKhcMdQuwbwYmD297Cxex0yQs7y5L3N2P+HS6fOO\nmD9/PhYuXAgAuHHjhulDffXqVVSuXBkLFy5Enz59HjTExunzLILK03MxVJpSTp93hCuZUMypwnbw\n8yg9q9tFhZw+7wgtZ4IcI8W2w95+wm4hdP78efzlL3/BTz/9BADo1KkT0tLS0KBBA5caNHr0aCQl\nJZX7pmCpEGIBZBt3PvIUQlJmQi0bfX4W5WFxGylDIcRMkDu8vf2wt5+we2Xp0aNHo0+fPsjOzkZ2\ndjaSkpIkuXw6iyD7+B7JQ65MEJWllEHUzAS5Q+4ToOz2CEVGRuLw4cN2n3O7If/rEeLO3XlK2BDK\nRY4eISkzoZZvv3r+DCqFadspQ48QM0Ge4o1tids9QjVq1MCyZctQXFyMoqIiLF++HDVr1vRoI41Y\nBJEaSJkJIkfJWYwyE+QpctQBdguhxYsXY9WqVahTpw7q1q2L1atXY8mSJVK0jRzEAlJazIQ59gYp\nh1x/C2aCPEnqfZrXzhpzFrs83afHHZKazhpzlloyocfPnZIxE6Qlnti+uHzT1dI30TNe16H0Y03f\nTE+l9H6NIW9jJojMMRPkbVLs16weGouJiUHr1q0RExODdevWmX42/lOMPRnaX6YTy/NUl+LtjH0e\neR2lLs8VzIR1Wv+8yPH5ZCY8iPsJVS/PuF/zVias9giNGjXK9HNaWhpGjhzplQa47Zft0l9iXepl\nOrk8T1TQBRn7Ld7ixFukXp4rmAnrtP55kePzyUx4EPcTql/eiTPhqJGxwCuZsDtYmtSJA6iJiEhL\nruXW9sq+jYUQERERqYaniyGrZ435+/ub7v5bUFCAhx9++MFMBgNu3rzp2YZYu9MwkR1SnSHDTJBa\nMBNE5ty61xgRERGRVvHQGBEREekWCyEiIiLSLRZCREREpFuaKIT27dsHX19frF271uvLSk9PR2Rk\nJCIiIhAfH48jR454dXmbN29GixYt8Nhjj2HmzJleXRYAnD9/HomJiWjZsiXCwsIkuzJscXExoqOj\nkZSUJMnytI6Z8BxmQhuYCc/RXCaEyhUVFYnExETRu3dvsWbNGq8vb/fu3eL69etCCCE2bdokYmNj\nvbasoqIiERwcLDIzM0VhYaGIjIwUv//+u9eWJ4QQf/zxhzh48KAQQoi8vDzRvHlzry9TCCFmzZol\nkpOTRVJSkteXpXXMhGcxE+rHTHiW1jKh+h6hOXPmYNCgQQgMDJRkeXFxcXj00UcBALGxsbhw4YLX\nlrV37140a9YMQUFB8PPzwzPPPIN169Z5bXkAUKdOHURFRQG4f2psSEgIsrOzvbrMCxcuYOPGjRg3\nbpxmbxYpJWbCs5gJ9WMmPEtrmVB1IXTx4kWsW7cOEyZMACD9NSYWLVqEXr16ee31L168iIYNG5oe\nN2jQABcvXvTa8srKysrCwYMHERsb69XlvPzyy/joo49QoYKqP46KwEx4FzOhPsyEd2khE6pO2eTJ\nkzFjxgzTXY+l/Oa0bds2LF682KvHY+W8eFh+fj4GDRqEtLQ0+Pv7e205GzZsQK1atRAdHc1vvh7A\nTHgPM6FOzIT3aCUTVm+6qlTz58/HwoULAQA3btzAM888AwC4evUqNm3aBD8/P/Tp08cryzQYDNi4\ncSMuX76M5557Dps3b0ZAQIBHl1Va/fr1cf78edPj8+fPo0GDBl5bntG9e/cwcOBADBs2DP369fPq\nsnbv3o3169dj48aNuHPnDm7evIkRI0bgq6++8upytYSZYCbIHDPBTDjFoyOOZDRq1Cjx73//2+vL\nOXv2rAgODhY///yz15d179490bRpU5GZmSnu3r0rySC4kpISMXz4cDF58mSvLseSjIwM8dRTT0m+\nXK1iJjyDmdAOZsIztJYJ1fUIye3dd99Fbm6u6Xizn58f9u7d65Vl+fr6Yu7cuejevTuKi4sxduxY\nhISEeGVZRrt27cLy5csRERGB6OhoAMCHH36IHj16eHW5RryXkPowE97FTKgPM+Fdns4E7zVGRERE\nuqXqwdJERERE7mAhRERERLrFQoiIiIh0i4UQERER6ZbiCqGyF2X68ssvMWnSJKde47vvvvPoBaxu\n3LiBBQsWODStNy8q5eiys7OzMXjwYJdf59NPP0VBQYGnmmXmtddew/bt2wEAQUFByMnJcel11q9f\nj/fee8+TTVMsZsJ1zIQ2MROuYyYs8OjJ+B7g7+9v9vjLL78UEydOdHj+oqIiTzdJZGZmirCwMIem\nLdt+b7G0np5adlBQkLh69apHXqu0mzdvijZt2pgt59q1ay69VklJiYiMjBSFhYWeap5iMROOYSaY\nCUcxE+7TUiYU1yNUlih1dn9WVhY6d+6MyMhIdO3a1XQ1zVGjRuH5559Hu3bt8Prrr2Pp0qWmbwdR\nUVGIjo5GdHQ0KleujJ07dyInJwf9+vVDZGQk4uLicPToUQBAamoqxowZg8TERAQHB2POnDkAgDfe\neAOnT59GdHQ0UlJScOvWLXTt2hUxMTGIiIjA+vXr7a7HV199hcjISERFRWHEiBE218eR9UxJSUFm\nZibi4uIQERGBqVOnmr1P4eHhAO5/UxowYAB69uyJ5s2bIyUlxTTdCy+8gDZt2iAsLAypqakAgNmz\nZyM7OxuJiYno0qULAGDLli1o3749YmJiMGTIENy6dcts3U6fPo2YmBjT45MnT5o9Nlq3bh26du1a\n7vmCggL07NkTixYtwtmzZ9GiRQuMHj0ajz/+OIYOHYotW7YgPj4ezZs3x759+wDcv45EXFwctmzZ\nYve91xpmgplgJswxE8yEW5lwqczyIh8fHxEVFWX616hRIzFp0iQhhBBPPfWU+Oqrr4QQQixevFj0\n69dPCCHEyJEjRVJSkigpKRFCWP52sH79etGpUydx7949MXHiRPHuu+8KIYTYunWriIqKEkIIMW3a\nNBEfHy8KCwvF1atXRY0aNURRUZHIysoyq/SLiorEzZs3hRBCXLlyRTRr1sz0O0vV9rFjx0Tz5s1N\nVW1ubq7N9XF0PZOSksSyZcuEEELMmzfPtOzS30yWLFkimjZtKm7evCnu3LkjGjduLC5cuCCEECIn\nJ8e0PgkJCeLo0aNCCPMK/MqVK6JTp07i9u3bQgghZsyYYXrvSktMTBSHDh0SQgjx5ptvirlz55ab\n5vnnnze7qmtQUJDIysoSXbt2Na1HZmam8PX1FceOHRMlJSUiJiZGjBkzRgghxLp160zvhfG9ef31\n18stR2uYCWaCmTDHTDATnsyE4gohW12eNWvWNHX1FRYWipo1awoh7l823fiBKDuPEEKcOHFCtGjR\nQvz5559CCCGio6NFZmam6fcNGzYUN2/eFKmpqeKDDz4wPR8SEiIuXrxYrsuzsLBQvPjiiyIiIkJE\nRUWJypUri0uXLllsvxBCzJ49W0ydOrXc89bWx9H1NAZQCCFu3Lhh9QP+3HPPmebp2bOn2LVrlxBC\niAULFohWrVqJiIgIERgYKL7++mshhPkH/LvvvhM1a9Y0bXBCQ0PFuHHjyq1Lenq6eOmll0RxcbEI\nDg42hae0nj17it27d5seN27cWERGRooVK1aYnsvMzBSPPfaY6fGIESNMvz99+rRpYySEEJs3bxZD\nhgwptxytYSaYCWbCHDPBTHgyE4q/xYYoc+Hrso+NKleubPH5/Px8PP300/jiiy9Qu3Ztu69TsWJF\n088+Pj4oKioqN016ejquXr2KAwcOwMfHB02aNMGdO3esroPxrseWOPu8tfW0pVKlSqafjeuUmZmJ\nWbNmYf/+/Xj00UcxevRoq+vQrVs3rFixwuYyBg4ciOnTp6Nz585o3bq11ZsMlpSUmH42GAzo0KED\nNm3ahGeffdZieytUqGD6m1SoUMHs71FSUqLL2w8wE+aYCWaCmTDHTDiXCcWPESqtffv2WLlyJYD7\nH7JOnTpZnK70h2PMmDEYPXo04uPjTc917NgR6enpAICMjAwEBgaiatWqVj9UVatWRV5enunxzZs3\nUatWLfj4+GDbtm04e/aszXZ37twZq1evNo18z83Ntbk+jq5nfHy82XSOEkIgLy8PVapUwSOPPIJL\nly5h06ZNZut78+ZNAEBsbCx27dqF06dPAwBu3bqFkydPlnvNSpUqoXv37pgwYQJGjx5tcbmNGzfG\nn3/+afbcu+++i4CAALz44osOt9/ojz/+QOPGjZ2eT0uYCXPMBDPBTJhjJuxnQnGFUNnKzWAwmJ6b\nM2cOlixZgsjISKSnpyMtLc3ifMZ5zp07h3//+99YvHixaSDcgQMHkJqail9//RWRkZH461//iqVL\nlwybiy0AACAASURBVJZbVmk1atRAfHw8wsPDkZKSgqFDh2L//v2IiIjAsmXLzG5wZ2n+0NBQvPXW\nW3jiiScQFRWFV1991eb6OLqeaWlpmDdvHiIiIpCdnV3uPbC2TgaDwXSzvBYtWmDo0KHo0KGD6ffj\nx49Hjx490KVLFwQGBuLLL7/Es88+i8jISLRv3x7Hjx8vt44AkJycjAoVKuDJJ5+0+PsOHTpg//79\n5dqYlpaGgoICvPHGG1bba+nnvXv3Wg2/ljATzAQzYY6ZYCY8mQnedJU85uOPP0ZeXh6mT59u8ff5\n+flITEw0jeh3R0lJCVq1aoX9+/fD11fxR3hJp5gJInNKzATTQh7Rv39/ZGZmYuvWrVan8ff3R2Ji\nIrZt24bExES3lrdhwwYMGjSIG3xSLGaCyJxSM8EeISIiItItxY0RIiIiIpIKCyEiIiLSLUUfTK5e\nvbrpFEIif39/s9NT9YiZoNKYCWaCzLmSCUWPEbp/CtxCK79dD2CW9Zl9H7P8fEkqEJ9qfb7WVp4/\nnwoMsjJfG+tvYY2vXkCN1AkWfxeK363Ol5M6H0+kdnRqvjWp/w/vpJZY/B0AhOecsPj89JlAaner\nswH7LT+d+n9AaqDz8/3lJGDtPtHbbbzcc7B+ATG9YCZUnAkr8wDMhDskz4S1PADMhAWpy4DUcOfm\nAaTNhIoPjV1zbTaR5dp8V1yb715WtkvzXc+67vQ8V7Juu7SsrHMuzYYsF7+EXXBtNrKLmSiLmdA7\nZqIsyTNxy/40lkiZCRUXQlddnC/Ltdkk/oDfyLrh9Dwuf8DPuzSbyxv9i67NRnYxE2UxE3rHTJQl\neSZcLISkzISKC6EaLs4X5Npsga7N5xdUz6X5Hg161Ol5AoOcv78MAAQ1dGk2BFm+TYxd9V2bjexi\nJspiJvSOmShL8kxUcW0+KTOh4kKopmuzGYJcm0/iD3i1oGpOz+PyB7yRS7O5vNFv4NpsZBczURYz\noXfMRFmSZ8LFQkjKTKhgsDTRfTxDhpkgc8wEM0HmNHfWGBEREZE3qfjQGBEREZF7WAgRERGRbrEQ\nIiIiIt1SfSE0Z84chISEICwsDCkpKU7NO2vWLFSoUAE5OTkOTT9lyhSEhIQgMjISAwYMwI0btq/h\nsHnzZrRo0QKPPfYYZs6c6dAyzp8/j8TERLRs2RJhYWGYPXu2Q/MBQHFxMaKjo5GUlOTwPNevX8eg\nQYMQEhKC0NBQ7Nmzx6H5PvzwQ7Rs2RLh4eFITk7G3bt3LU43ZswY1K5dG+HhDy4tmpOTg27duqF5\n8+Z48skncf16+YuCWZrP2fdfr5iJB5gJApiJ0pgJC4SKbd26VXTt2lUUFhYKIYS4fPmyw/OeO3dO\ndO/eXQQFBYlr1645NM+WLVtEcXGxEEKIlJQUkZKSYnXaoqIiERwcLDIzM0VhYaGIjIwUv//+u91l\n/PHHH+LgwYNCCCHy8vJE8+bNHZpPCCFmzZolkpOTRVJSkkPTCyHEiBEjxKJFi4QQQty7d09cv37d\n7jyZmZmiSZMm4s6dO0IIIYYMGSK+/PJLi9Pu2LFDHDhwQISFhZmemzJlipg5c6YQQogZM2ZYfB8t\nzefM+69XzIQ5ZoKYCXPMRHmq7hFasGAB3nzzTfj5+QEAAgNt3fjK3CuvvIK///3vTi2vW7duqFDh\n/lsWGxuLCxesXwR87969aNasGYKCguDn54dnnnkG69ats7uMOnXqICoqCsD90wBDQkKQnW3/qqMX\nLlzAxo0bMW7cOIfvs3Ljxg3s3LkTY8aMAQD4+vri0UftX6DrkUcegZ+fH27fvo2ioiLcvn0b9etb\nvvxVx44dERBgfnGV9evXY+TIkQCAkSNH4ttvv3VoPmfef71iJh5gJghgJkpjJixTdSF08uRJ7Nix\nA+3atUNCQgL277dxB7dS1q1bhwYNGiAiIsLlZS9evBi9evWy+vuLFy+iYcMHl+Js0KABLl507qLh\nWVlZOHjwIGJjY+1O+/LLL+Ojjz4yfQAckZmZicDAQIwePRqtWrXCc889h9u37V9+vXr16nj11VfR\nqFEj1KtXD9WqVUPXrl0dXu6lS5dQu3ZtAEDt2rVx6dIlh+c1svf+6xUz8QAzQQAzURozYZmv068s\nsW7duuHPP/8s9/z777+PoqIi5ObmYs+ePdi3bx+GDBmCM2fO2J3vww8/xJYtW0zPla6Mrc33wQcf\nmI6pvv/++6hYsSKSk5Otttvdi3zl5+dj0KBBSEtLg7+/v81pN2zYgFq1aiE6OhoZGRkOL6OoqAgH\nDhzA3Llz0aZNG0yePBkzZszAu+++a3O+06dP49NPP0VWVhYeffRRDB48GOnp6Rg6dKjDyzYyGAxO\nv1eOvP9axkwwE2UxE8wEM2HOqUzYPXimYD169BAZGRmmx8HBweLq1as25zl69KioVauWCAoKEkFB\nQcLX11c0btxYXLp0yaFlLlmyRLRv314UFBTYnO7nn38W3bt3Nz3+4IMPxIwZMxxaRmFhoXjyySfF\nJ5984tD0b775pmjQoIEICgoSderUEZUrVxbDhw+3O98ff/whgoKCTI937twpevfubXe+lStXirFj\nx5oef/XVV+KFF16wOn1mZqbZMdzHH39c/PHHH0IIIbKzs8Xjjz/u0HxCOP7+6xUzcR8zQUbMxH3M\nhHWqLoQ+++wz8c477wghhDh+/Lho2LCh06/hzCC4TZs2idDQUHHlyhW70967d080bdpUZGZmirt3\n7zo8CK6kpEQMHz5cTJ482aE2lZWRkSGeeuoph6fv2LGjOH78uBBCiGnTponXX3/d7jyHDh0SLVu2\nFLdv3xYlJSVixIgRYu7cuVanL/tBnTJliinsH374odXBbGXnc+b91ytmojxmQt+YifKYCXOqLoQK\nCwvFsGHDRFhYmGjVqpXYtm2b06/RpEkThz/gzZo1E40aNRJRUVEiKipKTJgwweb0GzduFM2bNxfB\nwcHigw8+cGgZO3fuFAaDQURGRpqWs2nTJofmFeL+B9yZswEOHTokWrduLSIiIkT//v0dOhtACCFm\nzpwpQkNDRVhYmBgxYoTpjIyynnnmGVG3bl3h5+cnGjRoIBYvXiyuXbsmunTpIh577DHRrVs3kZub\na3e+RYsWOf3+6xEzUR4zoW/MRHnMhDnea4yIiIh0S9VnjRERERG5g4UQERER6RYLISIiItItFkJE\nRESkWyyEiIiISLdYCBEREZFusRCSweeff47AwEAsXLgQX3zxBd566y2MGTMGcXFxKC4uRtu2bR1+\nrXbt2jk9D5HSMBNEDzAPEnPoqkjkUQcPHhTJyclmz33zzTciPz9fCCFM/wshxO+//y7ef/99q69l\naR4itWEmiB5gHqTFHiEZ7NmzB/Hx8QCA77//HgAQGxuLKlWqAIDpfwDYtm0boqOjrb6WpXmI1IaZ\nIHqAeZCWT2pqaqrcjdCbBQsWoFKlSvjuu+9QUFCA+Ph4VK1aFRs2bMDPP/+MH3/8EQEBAfj111/x\n8ccfo3nz5igoKMDatWtx4cIFVK5cGS+99BL69+9fbp7AwEAcO3YMmzdvxp49exASEoKKFSvKvcpE\nNjETRA8wD9Jij5AMjhw5grfeeguvvfYa2rZti7t37+Lw4cNYvnw5Ro4ciV69emH+/Pno0aMH6tWr\nh+eeew4+Pj6oVasW7ty5g6CgIAQHB+PEiRPl5gGAxYsXo0WLFqhUqRLy8/NlXlsi+5gJogeYB2mx\nEJJYXl4efHx8UKFCBdSoUQPx8fHYunUrVq1ahaFDhwIAzp49i4CAAFy6dAl16tQBAMTFxeHbb79F\nz549AQAtW7bE0qVLy80DAMOGDcMrr7yCtWvXonbt2jKsJZHjmAmiB5gH6bEQkti+ffsQGRkJAPDz\n80OFChVw6tQp3L17F40aNQIArFmzBsOHD8fevXvRtm1b7Nu3D7du3cKlS5dQo0YN7N+/H+3atbM4\nz//93//hyJEj+Omnn1CzZk3Z1pPIUcwE0QPMg/Q4RkhC+/btw0cffYTCwkLk5eVh9+7dSElJQZ8+\nfdC1a1ds3LgRp06dQps2bRAbG4v8/Hzs378f9erVQ/PmzXHmzBnk5ORACIGoqCg0btzY4jw5OTn4\n73//i1atWqFZs2ZyrzaRVcwE0QPMgzwMQgghdyOIiIiI5MBDY0RERKRbLISIiIhIt1gIERERkW6x\nECIiIiLdYiFEREREusVCiIiIiHSLhRARERHpFgshIiIi0i0WQkRERKRbLISIiIhIt1gIERERkW6x\nECIiIiLdYiFEREREusVCiIiIiHSLhRARERHpFgshIiIi0i0WQkRERKRbLISIiIhIt1gIERERkW6x\nECIiIiLdYiFEREREusVCiIiIiHSLhRARERHpFgshIiIi0i0WQjI7cOAAoqOj8cgjj2DIkCF4+umn\nMXXqVISHh2PDhg2m6e7du4eaNWvi0KFD6N27N+bOnWv2OhEREVi3bp3UzSfyCldyMXHiRFStWtX0\nz8/PD9OnT5dxLYg8x1Im3n77bfTp08fsc+/j44OlS5fio48+KpeH0aNHy70aisRCSEaFhYXo378/\nxowZg9zcXDz77LP49ttvUaFCBYwYMQLLly83Tbtx40bUr18fUVFRGDVqlNnvDh8+jOzsbPTu3VuO\n1SDyKFdzMXfuXOTl5SEvLw87d+5EQEAA+vXrJ+OaEHmGtUwYDAasX7/e9LlftWoV6tati65du2LK\nlCmm5//73/+iVq1aeOaZZ+ReFUViISSjPXv2oLi4GJMmTYKPjw/69++Ptm3bAgCGDRuG77//Hvn5\n+QCAZcuWYfjw4QCApKQknDhxAqdPnzb97plnnoGvr688K0LkQa7mwujKlSvo168f5s6di8jISMnb\nT+RptjJhdOLECYwaNQqrVq1C/fr1Tc8XFBSgb9++mDx5Mrp37y5101WBhZCMsrOzzT6wANCwYUMA\nQN26dREfH481a9bg+vXr2Lx5M4YOHQoAeOihhzBkyBAsW7YMQgisXLmy3M6ASK1czQVw/1DZoEGD\nMGzYMAwZMkTSdhN5i7VMCCEAADdu3EDfvn3x/vvvo3379mbTjR07FiEhIZgyZYpk7VUbdiHIqG7d\nurh48aLZc+fOnUOzZs0AACNHjsSiRYtw7949tG/fHnXr1jVNN3LkSIwYMQLx8fGoXLkyYmNjJW07\nkbe4k4tJkyahWrVq+Nvf/iZpm4m8yVYmhBBITk5Gly5dMG7cOLNpZsyYgVOnTmHnzp1SNld12CMk\no/bt28PHxwdz585FUVER1q1bh3379pl+379/fxw4cACzZ8/GiBEjzOaNi4uDwWDAa6+9Vu53RGrm\nai4+//xz7Nixw2wMEZEWWMuEEAJ//etfcfv2bXz66adm82zatAlz5szB2rVrUalSJZlarg4shGTk\n5+eHtWvXYtGiRQgICEB6ejqeeuopVKxYEcD9Q2ADBgxAVlYWBgwYUG7+ESNG4OjRoxg2bJjUTSfy\nGldzsXLlSmRmZqJevXqmM2VmzJgh12oQeYy1TFSqVAkrV67Enj17EBAQYPrcr1ixAqtWrcKVK1cQ\nEhJiev6FF16Qe1UUiYfGZBYTE4ODBw+aHsfGxqJPnz6mx40bN0b//v1RuXLlcvM2btwYHTp0QFBQ\nkBRNJZKMK7nYtm2bpG0kkpK1TGRmZlqcPjk5GUuWLJGqearGHiGZ7dixA3/++SeKioqwdOlSHDt2\nDD169AAA5OTkYPHixRg/fny5+W7fvo158+ZZ/B2R2rmaCyKtspUJcg8LIZkdP34cUVFRCAgIwCef\nfII1a9agdu3aWLhwIRo1aoSePXuiQ4cOZvP88MMPqFWrFurWrYvk5GSZWk7kPa7kguj/t3fm0VFU\n+R7/dhZ4xiBGCCAGCIREErJCYghhSQBlM7jhMoBoongGF8Q1OjKPgE8kozwNKMwcNSiLo+g4BhB4\njANBZJFkQALGAQYTzKIIBEiAYEhy3x+xO92drq6la6/f55ycdFfXrXur6n5vfet3760yM1yaIHzH\nxuzz7wiCIAiCICwGRYQIgiAIgrAsuhksbbPZtC4CYVDMGtQkTRBSIU0QhCveNOHVCF25cgVbt27F\nV199hcrKSthsNvTr1w+jRo3C+PHjZX+lQxQ7KDrNmbwV6JY3W9Zy6C1Pe35Hf4hTLU8ULACenK9J\nflEDDglOdtSm7isUSBP6yFPL/FTToVQNRqgb6DeSJqzShpoyP1/y5NEE568vv/wyUlJSsHHjRgwa\nNAg5OTl44IEHcOONN2LDhg1ITk6mp7eqjBiDYFT0vI+kCYJwxWia0HP7QmgHp1VPSEjAvHnzPIYi\nc3Jy0Nraio0bNypaOMJa6L2RIk0QhCukCcIMcEaEpkyZ4rU/1s/Pz+UBZ1pxVUay6fN0zk81s5A6\nWp18tMpPAqQJ/eRp9vwAkCZkhNpQE+SnYJ680+dLSkqwaNEiVFZWorm5uS2RzYaysjJ5C2KzSer7\ntSKq9nOrhNTG6agtQfWBoaQJa6N7/UX4kSYEoPvzSMgHjyZ4R7FNnz4dr7/+OmJjY+HnR7Pt9UDU\ngEOmErHeu8TcIU1YFzPpTk5IE4SR4TVCoaGhughtEoReIE0QhCtG1ITZbigJ6fB2jW3duhUff/wx\nxo0b53j7s81m8/g2dJ8KQt0AojGDiH2NBmnRNUaasC6G0JwGXWNG1oQhzinhG752jX3wwQc4cuQI\nmpubXUKecldwwnoYrUvMDmmCIFwhTRBGhtcIlZaW4t///rcsT/RsaWlBcnIywsLCsGHDBp+3Z3Uo\ntKsNpAmCcMXImqB2lOAd1TZ8+HCUl5fLkllBQQFiYmLoMemEYaNBgLqaoAaaMAJGv04YuT0ifIfX\nCO3ZsweJiYmIiopCXFwc4uLiEB8fLzqj6upqbNq0CQ8//LBp34OjBUYUsBHL7IzamiAzROgduk4Q\nRoa3a+z//u//OlRIKU79qaeewmuvvYb6+nrRaQnvUGhXXUgTBOGKGTRB7ah14TVCX375JR566CGX\nZS+88AIWL14sOJONGzeiR48eSEpKQnFxMed6Z/JWOD5flZGMoIwUwXkQxsDXaNCl4hI0FpfKVBpp\nqKkJFCwAABwFEHZHH9IE0ZG9xcA3OzQtglmuE2SGTIJITfBOn584cSKmT5+OGTNmAAAee+wxNDY2\norCwUHAmf/jDH7B69WoEBATg8uXLqK+vx1133YVVq1a1F4SmCvuM3gWsRJeYFtPn1dQEjre6pDN6\nt6LR0bvGAGgyfd5M1wlDnGNCHDya4DVCjY2NmDJlCnJycrB582aEhISgoKBAcnl27NiB119/vcNs\nADJCvqN3AZvFCKmpCXcjBJAZ0hK9awyAJkbIbNcJQ5xnQjg8muAcLF1XV4e6ujo0Njbi3XffRX5+\nPq655hrMnz8fdXV1PpWJZo0pg54vkHoum1BIEwThilk1YYb2ihAOZ0QoPDzcpSIyxhzfbTYbfvjh\nB3kLQhEhWdDjnYySjYqaESEtNOEpIgRQQ60VetRXB1SMCJn5OmGIc00Iw9euMbUgIyQfehOwWYyQ\n2ngzQgCZIS3Qm7Y8okHXmFqofZ0wxPkm+JHaNbZjB/+I6+3bt0srFGEZzHSx1psmqJEmtEZvmpAb\nM7VfBDec0+c3bNiA5557DuPGjUNycjKuv/56tLa24ueff0ZpaSm+/PJLZGZmIjMzU83yEgLQyxRQ\nszUietTE0R/iTHecCeOgR03IjV7aU0I5vHaNNTQ0oKioCLt27cKJEycAAP369cOIESNw2223ITg4\nWL6CUNeYrEgWbomHAYop0sLsalyg1e4aU1sT3rrG7JARUg9DXBBV7hqzwnXCEOed4IbGCFkXUeL1\nZIDcEWGI1Lo4W3mMkDNkhtTBEBdEGiOkCIY494RnpI4RIiyEEBMkZj1CdaiRJghloZsN88L7ig3C\nuAjq2xZrbkpsvJEhajC0gcYLEQShBGLbFaPdmJERMjk00M9akBkSRgzKPS4vR4zKJSGMhJXaU1/a\nEee0RjhevF1j8+bNQ3Nzs+P7+fPn8eCDDypZJkItpHZ1eUlnhYuw3jVhhIZHC2JQ7vjjW8cnSmyW\n60bWuybkxAptnJz7GDXgkO6PGa8RamlpwU033YSDBw9i69atuOmmmzB06FA1ykZoyTdaF0C/kCaM\nh1hzI9oM2c2PswHytMykWE0Ter+wS0VJ06LnYyZo1tiXX36JrKwshISEYMeOHYiMjJS/IDRrTFE8\nRgncG2hv5ifV7buHcUJaVHStZo2ppQmhs8Y8oeeGRy18je64d5UJ0pE3JD6KQhQazRqz2nXCbJFX\nb+2FWB3xdTGrfux8nTW2Y8cOzJkzB3/84x8xevRozJkzBzU1NbKWkdAAMSbI0+8WuMvlwiiaMFtD\nLRafu7iEbEPKZAMTYhRNyImZbjS49kVqVzFfOr0dO97B0s899xw+/fRTxMS0ObzPPvsMY8aMwZEj\nRxQvHCEfSg/y01vFVhIjacKqg6f5Gu84eD8mhyBAK76MsVMjMqQiRtKEnJhh8LQ3E+QMn2acsevH\nvg29T0Lg7Rprbm5GQICrXzp9+jS6d+8ub0F0FPI0Ky6CdW7E3aM9pU6fk91+c+4ic2rMtbrYatE1\npqYmfOkac8ZqZsibERLaoDubIXtDLlhDdty7lJ1Rygxp0DVm9euEkc2Qp7bBWT/OehESHXI2PZ40\n5Ixqx41HE7wRIffKDUD2yk3oiFIP393NkMUhTegbrsZazB2tfX3OyJAQE2T/jcsMmSgyRJowJt5M\nkCcDxGeEyhHjEgVy1lAMyjuYIb1E1Og5QibBuYJyhSE9VjrnRtzdBDkvt5shDw271aINRsQqXWRi\nxjN4W1dwKF/I7EqLmCEro5cLuhiEmCBPBiiu7ij3Rq9z/SrEDOkBMkIGhqshF9Qvmz8ZOLBJeGY7\nnT4nTQJyv5BUNt5yEYphFTPkCfdokKf6mT95D77ddPK3b5+LyyBkEhDrpgnnSKo3M0SYAiOaIWfc\nNRGDcjdNCKHdJI2cVINHv+hohtzRw3HjnTV28eJFvPzyy5g1axYA4NixY9i4caPiBSO8I+TO1+s6\nYkyQyLR8ZZNjNo+WGFkTWjc4WsBnguwzXMQ1+G6c9aAJ9wgrV/TIBDPJjKwJOTHDjYazXnzRxM5N\nF11mj7lHmfQEb0QoOzsbQ4cOxe7duwEAvXv3xtSpU3HrrbcqXjjCM2LD/14jME+x9gZ7j5cNpf32\nf6f3Rlto2fQaIhWC0TVh1siQ2JsDrvUPsihH3SxHjONOthwxbUbSbly+QZt27Jqw6yfNaWPuY+xM\nGhkyuibkRA8RDj7c9c91c2CH/RPt14lvvWw4se2fLdd1sd7be96I0PHjx5Gbm4tOnToBAK6++mrF\nC0VYAz3eGQjBDJrQe0MtF2IHSNvhmjXjwNvYIPcbCq6xdybCDJogvOilFG0G6NvfPnP9uZmkuLqj\nHrXk3vZrfWPGa4Q6d+6MxsZGx/fjx4+jc+fOojOqqqpCZmYmBg8ejNjYWCxdulT0Nghp5kF0muZj\n7X9K5mNQSBPGhCsaFFd3lHMAqOQ67S266gmDd4+RJlzR+sLuC14fhvibqT92rOOf43dvESOdwmuE\n8vLyMGHCBFRXV2PatGkYM2YM8vPzRWcUGBiIN954A9999x327t2Lt99+G99//72kQhMKYG+43c2P\n/bvYhl0gRjRPZtGEVaJC3vBkgLzOinHGPdLjfvPApRkTvsfPLJqQEyObIcBNB/ZIENpNzw6nP+fl\nzticTJGe23reMUK33HILhgwZgr179wIACgoKEBoaKjqjXr16oVevXgCA4OBgREdHo7a2FtHR0aK3\nRRBaYiZNmGW8kFzT5t3X4x3XIPQGweTP4zKTJuTECOOFxOBsgpzZAWD0b7+7v2Euru4ocJ2+Zwvz\nGqGxY8fin//8p8ugN/syqVRWVuLAgQNITXUdNXgmb4Xj81UZyQjKSJGcB+EZowvzUnEJGou1HXSh\npiZQsKD9c+poYFiG5Dy4MIsZ0g3Nx4AA+V84ysneYuAb90uTutB1wjpoW9MEIlITnEaosbERly5d\nwqlTp1BXV+dYXl9f79PL9C5cuICpU6eioKAAwcHBLr91y5stebuENQjKSHFp+M4s+LNqeWuhCTw5\nX/J2CYswLMPVIC9dwLWm7NB1gh+j3HxKnVigS0RqgtMI/eUvf0FBQQFqa2sxdOhQx/IuXbrg8ccf\nl1S2K1eu4K677sKMGTNw++23S9oGQWiFmTVBUSFCCmbWhJwYwQwdQpy5zJAIOI3Q3LlzMXfuXCxd\nuhRz5szxOSPGGB566CHExMRg7ty5Pm+PkIbexahnzK4JMkMSSIPrU9cBdbvFNMbsmpATI5ghIYyG\nQbrHRMA7RmjOnDk4fPgwysvLcfnyZcfymTNnispo165dWLNmDeLj45GUlAQAePXVVzFhwgSRRSbM\nhJ4H0HFhZk0Y1Qw5v+zR13UPXRflWE8U3gyQiQdKA+bWhJwY3QxFRrYNiB7t5XckA/htUDVLbNOT\n3tt5XiOUl5eHHTt24LvvvsPkyZOxefNmjBgxQnQFHzFiBFpbWyUXlFCYNLTNgAmIdJ0CbG/c0zwl\nsiZm14RRzZAU7KZH8JR5Z5Lh/WGJXJox4ZOlza4Jq1GOmN9eoPqbLn57YjRK282QO5E8gVA9myHe\n5wh9+umn+PLLL3H99ddj5cqVOHjwIM6dO6dG2QgPSKlMku5s7X8K5qNnYXiDNGFMnOube92zGyJv\naVzgMzPOJkhINMjgb6AnTQhH7zcZnHU+EW11ObnN9Lj/2X9zmCYpeWgEb0Toqquugr+/PwICAnD+\n/Hn06NEDVVVVapSN4EBMNwAvbwh8oq37OAgLYwVNmCUq5G0AKJeOEmz26NBRiHoLvZCoqQmjQYA1\nNCEneusis2vBWS9tZqVNC+7vDvOIPUr01/ZF7t1iXG+g1/pY8EaEUlJScPbsWcyaNQvJyclIEveX\nGgAAIABJREFUSkrC8OHD1Sgb4QWhjloR5500yef89HZHIAaraELrxkksQuqU+zqy1cMQDk2YfGyQ\nHatoQk60vNHg07Ycuhg5qf19c3pv722MMcEx2YqKCjQ0NCA+Pl7+gthsiGIHZd+u2eGKDHFVPIcA\nnN+gDXQc67AHHe9w7Y26/a72t3A+l6A9lU1uQRy1JUBEFZYdpTWB49qOlzBaVIhLD+5RISERVXtd\nPYQ4x2fB+vFkgLiiQXJ3i0X4mVoTZrtOaHXD4e0N9M4vR7Uvt4+js3G8S4w5dYk5Tzhw1pF9mTuK\nHwMeTQgyQjU1NThx4gSam5vBGIPNZsOoUaNkLacZK7jecKls7g054H3gp3PD7maEAO0umFoZIbU0\nobURAoxlhrwZHDFmiKvx5jRCfHjrEjOJEaLrhHS0MEOedO3tTfHuLyp2x3mcnV0v7jpyXmZHlX3n\n0QTvGKHc3Fx8/PHHiImJgb+/v2O53BWc0IhUtDfmXLNgPJkgC2M1TRhpvJC38XPu44VkiU4668fb\nOlwYfJC0Hatpwgx40rWzfux6sS+z6yUG5R4nF3B1O3szQXqB1wj9/e9/x5EjR9C5c2c1ykNojd30\nmPwlkb5AmjAuYp6eyzWwE0CbgbFHhexGx90Q8d00mMQEAaQJX9HT4GkuMyQ0rTN8Jkgv+8xrhCIi\nItDU1EQV3OB4rXCe7mrFjHGAsaIGvmJFTRjp/PI+MPG3xpnLELkbIMF3sWKipSYyQYA1NSE3Wpgh\nLl27myEAbrPJuPF0A6FnEwQInD6fmJiIsWPHOiq5zWbD0qVLFS8cQegRq2rCTGYI4In4CME5KiQ2\nncmwqibkRm9mCEAHQyQG3kk7OoHXCE2ZMgVTpkxxWWazSRC/AIzU0JoOrvC+8288WOX8qakJQjpy\nPG+LNxok1gyZ0AQBpAk50ZMZAjoaIiHodSwQF6KmzyuJ8wwZK1xM1YRTVN4a8G8gaZCn2udO6+nz\nSqKXWWPuGE2fUs2Q6HC+Nz2paYA0nj6vJGadNeYJvcwkkxPNIkFSZ43dfffd+OSTTxAX17HgNpsN\nZWVl8hTQA1aJLKiB5IoncXaYmc+dlpogpKPaHa1Joz3eIE2YCyXbb711hznDGRGqra1F7969UVlZ\n6TFheHi4vAXxcPdr1guqmki+g/UGT4Ov5nlTMyKkB03oBaNrU+rDPvXcmDtQMSKkhSasEhECtK1v\ncmlcF5qR44GKauCt0Td6o6sVgiqgQoM91Tpn1DWmDVbVpC4adT6oa8xU6KHOidW7HsrsgtSuseDg\nYM7BbjabDfX19b4XTiBm7m7RHBrsKRg9aUJrSJMEQJpQAz08Y0jr/JWG0whduHABADBv3jz07t0b\nM2bMAACsXbsWtbW16pTOCWp4xSGq4go1QyJMkBnPl940QRBaQ5pQBz2YITPD2zUWHx/fYcCbp2U+\nF0RgN4DZLq5KIFkwCsx6UXwWggZdY3rThFZYVYu6vyBp0DWmpias1jXmjO7rnl7h0YQfX/qrr74a\na9asQUtLC1paWrB27VoEBwfLWkYxUEXwjk/HJ4W1/3n6rnZ5dIreNKEVZjy3hDRIE4SR4TVCH374\nIdatW4eePXuiZ8+eWLduHT788EM1ysYJNcCekfW4WHgsEB961ARBaAlpQh2sGoVVGq9GqKWlBW+/\n/TbWr1+P06dP4/Tp0ygqKpI8JXLLli0YNGgQIiMjkZ+fL2kbdsgMuaLn46HnsolFz5ogCC2QUxOk\nB37IDMmPVyPk7++Pr7/+Wpb+5paWFjz++OPYsmULysvL8de//hXff/+9T9s00wXWF4xwHIxQRiHo\nXRMEoTZyaYL0IBwyQ/LC+66xxMRE3Hbbbbj77rsRFBQEoG3A2p133ikqo3379mHgwIGOu4T77rsP\nRUVFiI6OFl9qJ8w4O0kMRjIYZjlXeteEmpjlnBK+IYcmzKAHNaGZZPLBa4QuX76M6667Dtu2bXNZ\nLrbRr6mpQZ8+fRzfw8LC8M03nt7wKR4rNsZGFYAZzpURNEEoB12AOiKHJkgP4qG6KA+8Ruj999+X\nJSNBbyIuWND+OXU0MCxD8PbNcIEVitErvi/n6lJxCRqLS2UukTiMognCIuwtBr7ZoWkR5NCE0LfV\nn8lb4fh8VUYygjJSfM7byJAZ8oBITfAaoaqqKsyZMwdff/01AGDUqFEoKChAWFiYqHLdcMMNqKqq\nctluh208OV/UNt0xuxkyU2WXeq6CMlJcGr4zC/4sZ7EEYSRNEMqgq4vPsAxXg7x0AdeaiiGHJgTp\nAUC3vNm+F9hk6Ko+6gGRmuCdPp+dnY0pU6agtrYWtbW1yMrKQnZ2tuhyJScn49ixY6isrERTUxM+\n/vhjTJkyRfR2+DBjZTj6Q5xp98uIGE0TBKE0cmiC9OAbZg4CKA2vETp16hSys7MRGBiIwMBAPPjg\ng/jll19EZxQQEIC33noL48ePR0xMDO69914aBCcAo5oFoRhx/0gTBOGKHJogPfgOmSFp8HaNdevW\nDatXr8a0adPAGMNHH32E7t27S8ps4sSJmDhxoqS0YjBLF5kRTYIUjHa+jKgJJTHa+ZML6o5oRy5N\nGF0PQuuDknqheike3neNVVZW4oknnsDevXsBAMOHD8eyZcvQt29feQuiwHuVjNw4W7Uiiz1nWrxr\nzMiaUAoja81XdKdVDd41pqYm9PauMTnOvxL60V291BIeTfAaIbVQqtGXu4LFoNzlezliZN0+QBVY\nzDnTwgipBRkhY6A7vWpghNRCL0ZIqXMut450Vze1wteXrlZVVeGOO+5AaGgoQkNDcdddd6G6ulrW\nMuqdGJQ7/rh+kwuquPo/BqQJwhkrm0A7VtGE0hNX5N4+1U1hqDZrTCt8rVRCTY4chkjvBkBN9DxT\nzuiaIOTH6hccs2tC7faIzJC68HaNJSQk4ODBg7zLfC6Iwt0AUiqDVGMjpbtMrxd9PeDt3GnRNWYW\nTcgJNbZt6ELHGnSNqakJtbvGtD6ncmpL633RDF+7xuyzAVpaWtDc3Iw1a9ZIniFjJOTs7uLDspVT\nIHqLDllVEwQ/VjWEZtWEHtodig4pD68RKiwsxLp169CrVy9cf/31+OSTT7By5Uo1yiYralZoNU2U\nldCLITKLJghlsOLFxoya0ENbY4fMkLKYftaYM0IrgBxGRmj3mJ7EZiTs55JmjekDIdri05USMzC1\nRDNt06wxn9Fru0zdZBLxtWts5syZOHfunOP72bNnkZOTI0/hVIaiQuZBy+iQmTThkRJb+58MCJ1I\nIPcMTK2x0p23mTThU7virB33P51hpfrJB++TpcvKynDttdc6voeEhGD//v2KFkpLaGwQwYcpNcHV\nUNuXp0iLMEjRkz2NGSJEVnnKr1k0IelcCTU5zutJ1JPcT3F3RNYtUEe9wRsRYoyhrq7O8b2urg4t\nLS2KFkpJfD3hcTjk+NOyHIR2mEoTQu9WJdzV+npTYZbokBXuvM2gCdFtsi+RHh/SKnHtsEId9QZv\nROiZZ55BWloa7rnnHjDG8Mknn+Cll15So2y6wpPxsS87BDI1VsI0mpDSEJfYJN/NSiEG5RQZMgCm\n0YRQ+LTzjdPnVAHbUVFTXJi9jnpD0GDp7777Dtu2bYPNZsOYMWMQEyN/w6T2wFAuB+zpLlRI9IfL\nDHE14latcLKj0cBQw2vC1zELbg23u57kjuaYwQzZUVz7JteEEoOlRZ0TLu1843lxB7iMkUgzpFQU\nx5TXJqu/a4wLoUZITBeYJzPkqQE3ZUXTCpPPkFFEE3IM3CQj5BOKtgEm14SmRsiTdoQaIHc8GSIR\nZkjJ7izTXaN4NMHbNUYIJw6HqJuM0DdyzV7x0kUmNqoqRDNm6SKzY+VuCL0h2QR5MkClXtInu33/\nBt67zTTEaoOoeQdLmxUhJ9jXAdEEYVi+cfvzAT4dWVVnUQMOWX6QqmHgM0Gl8G6CuNZx346IGxU1\nTIpV6idFhJyw38numZyPk5u+xecSttFzUiLSvsjl/N0qDpvQIUIaWS7T8+JkoGITZ7KjHJ8B4PCk\nCPzui3u9Ziskmmq2qJAdig4ZlM+9a4KTnQD6TwJu/6Ltu3tkSOUJCXxYoX5yGqHg4OC2MQoesNls\nqK+vV6xQWnNy07eapCX0jek14S3yI6XB/43/bDouaD0rdy0btSvC6JoQdLy5okE+aMKntBpgdjPE\naYQuXLigZjl0yR/ZH1y+cw0Atd+lvmxbpHiZCO0wtCbETPf1xlPM9e71tztX+4XcWSNxOCRaE3xm\nyKxRITtGM0SG1oQUPOlkJAP2OH1vPtZxnYBIp99/02Ip2scN6TwqBBivbopBcNfYL7/8gsuXLzu+\n9+3bV5EC6RWzPNyNkA+ra4JQDqPegZtOE1w3EM5jfewmyJMBgttvzobIvh33QdQ6x6h10xu8g6XX\nr1+PyMhI9O/fH6NHj0Z4eDgmTpwoKpO1a9ciISEB8fHxSE9PR1lZmeQCy4lcJ5NMkrUwnSZ8HAwt\nFPu7xEgvwjDSYGrTacITonSyw+nPCW9mSYIOtTIkRqmXQuE1QvPmzcOePXsQFRWFiooK/POf/0Rq\nqrg5fwMGDMBXX32FsrIy/PGPf8QjjzwiucBaQA034YzhNCH3Cx8FNNjuM8HcNeRNU1adRcaFEQyR\n4TQBmU2Ew+B4MD8elznBN9tMp+i9ToqB1wgFBgaie/fuaG1tRUtLCzIzM1FaKu7MpaWloWvXrgCA\n1NRUVFdXSystQegAy2iiFMKmBUuEbjDEoWdDZBlNAB314C3K4409PL/r8I317ui5ToqBd4xQSEgI\nGhoaMHLkSEyfPh09evRAcHCw5Azfe+89TJo0yfOPBQvaP6eOBoZlSM5Hj5itX1UT9hYD33i5u1IB\n0gShJR0GrVpME2fyVjg+X5WRjKCMFMn5yAvfOdgBYLQaBVEd3Y0bEqkJXiNUVFSE//qv/8Ibb7yB\ntWvXor6+HvPnz5dUtu3bt6OwsBC7du3yvMKT0rZLWIhhGa5mYOkCrjUVgzRB6AGHIUKGpTTRLW+2\nL0UlFEJXZkjkdYK3a2zhwoXw9/dHYGAgHnzwQcyZMwd/+tOfeMuxfPlyJCUlYciQIfj5559RVlaG\nWbNmYf369QgJCeFNTxB6hTRB6Ak9dE+QJgD+aI85o0HOaF0PpcJrhLZu3dph2aZN/A+DevTRR3Hg\nwAHs378fTU1NuPPOO7FmzRoMHDhQWklNgFErCeGKZTSR7PZfZsz8PCAt0NIQWUYTnnCfEi8XAp4j\npMdrih6MuVg4u8ZWrFiB5cuX4/jx44iLaw93NTQ0ID09XVQmCxcuxNmzZzF7dltIMzAwEPv27ZNY\nZPUpRwwN7CSMq4kUJn3gpUwmSIyGrPp0aSNiWE3Ah66cZHiZQDAanscKeYgGpTltz4ToqquMB04j\nNG3aNEycOBEvvPAC8vPzHa+w79KlC7p16yYqk3fffRfvvvuubyXVMXRnaw1Mq4lUiHuGiYBZ0YcQ\n12EaPOnEfJhWE57wppOASKfZY166wAIigWaZy6VjjGKGOLvGunbtivDwcHz00UcICwtDp06d4Ofn\nh4sXL+LHH39Us4yKYbTwHaEtVtAEQYjB9Jrg6p7yFMXh6yLz9LvzdsQ9dskwGKGrjHfW2LJly7Bg\nwQL06NED/v7+juWHDul7x+RA+HuSpLynnjAqptSE0KjQG5672I66/QekqYKvW4yiSvrElJrwhCed\nNAvsdhYTCTLo+CBv6Dk6xGuE3nzzTRw5ckR0mNOIyDEWqOekRJlKQ+gVQ2pCyDghsV1kAhk4KUL+\njRK6wpCagIYX55BJlogGuaNXM8RrhPr27YtrrrlGjbLohtvZXwFIe9Q/DfQ0P6bWBJcZ+sjDHarT\nXavz3an7zYRQHVE0yLiYWhPuNxF2jTz1W/3nGji9B+0Dot3xZoJ09tZ5udGjGeI1Qv3790dmZiYm\nT56MTp06AQBsNhuefvppxQunNZ4GfPqKHisBIQ7DakLo7DGZ7075dEQ3D8bHsJoQCpcZAtpNjbsh\n8mSC3McWSdSa0brF3OnwdHSNERQR6tu3L5qamtDU1ATGGGw2/b8DhQ8lKhI16NbA0JrwZSq9+3ZE\nYNeGsyESoxeKBukbI2tC8s2pe/TU3eSUcix3Tu+OyaNB7uglMGBj9vmOPDQ0NABomxapSEFsNuB4\nqyLb9gSXEfI0RkhIVMhTo87VeOvhxJuGCD8IrMKyY2hN+GqG3Bpsdz3J/dwtMkLCOWpLMLUmothB\n2bcruE3m0o0cj58QaIKMHg3iQtHrIs91gvfJ0ocOHUJSUhIGDx6MwYMHY+jQoTh8+LCsZdQ7ckd6\nzFqRrYLlNaHyXSuZIP1jdE0IbpO56n6q0x8X3n63WCTIE1peF3m7xh555BH87//+LzIzMwEAxcXF\neOSRR7B7927FC6cUUg441zgH6g6zHqbQhL3hFRsZEthgy/U0djJBxsAUmhAKn3bEjPsRaYDMfhOt\nVVcZrxG6dOmSo3IDQEZGBi5evKhoobTEWwNOpocATKYJMWOGRDbavpohMkHGwQyaEH0Rlnoz4Z5e\nIGY3QXa0GEjN2zXWv39/vPzyy6isrERFRQX+53/+BwMGDFCjbIqgVmXia8StUqnNiNk0gRTmvVHm\n+90LUsxMOWLIBBkMs2hCUrssRh/2dakrjBc1r5G8g6Xr6uowf/587Nq1CwAwcuRI5OXlISQkRN6C\nqDRYWsjBVSukT4OmZUCDwdJm04QcyKErMj/yoMVgaTU1ocRgaXf01jZb/cbZ5/PBc53gNUI7d+5E\nWloaAgLae9H279+PIUOG+FYw94Ko0OiLqUy+miGhjbreBGc4NDBCZtKEXFi9odYTWhghNTWhhhEC\n9NM2k7ba8Ol8+DprbPz48Rg7dixOnjzpWPbQQw9JL5AFoDtbc0OaIAhXzKgJPRgQPZRBLyh5LHiN\n0I033ohnn30WGRkZjrCnERF7EKWaGbHpqKIbD7NogiDkwqya0Kp9NsIb27VAqePCO2sMALKysjBo\n0CDce++9yM7Olr0QekXsrBeKBFkHq2qCILgwqybUnsVEBogfuafZ80aE7P1qkZGR+Oqrr7Bz506U\nlZXJVgA18KViCZ3BQibIOphBEwQhJ1bQhNIGhaJA4pDzeAl+xYYzP/74I/r27StLARwFUXBgqBEq\nl14G5hkODV+x4YzRNCE3RtCYVdDyFRvOKKUJtQZLe0PO9pq04zu854PnOsHZNZafn4/c3Fw88cQT\nHX6z2WxYunSp8FJqiFEqmV5ePkdwYxZNEIRcWFUTztcVKe22Ua5LRsHX7ktOIxQT09bVk5zs+upc\nX94qXFJSgrS0NKxbtw533nmnpG0QhFaQJgjCFdIEmRo9ITWgwGmEsrKy0NLSgrKyMixZssSnwgFA\nS0sLcnNzMWHCBNXCtkaroBQV0jdm0ARByAlpgtAbUqJDXgdL+/v7Y9euXbJUyGXLlmHq1KkIDQ31\neVsEoRWkCYJwhTRB6BExgRDe6fOJiYm47bbbcPfddyMoKAhAW9+vmJBlTU0NioqKsG3bNpSUlEgO\nmYrBaNEgOxQV0j9G1QRBKAVpgtAjjugQz3q8Rujy5cu47rrrsG3bNpflYir43LlzsXjxYthsNjDG\nuO8cCha0f04dDQzLEJyHM0Y1QYQA9hYD3+zQtAhG1ARhXi4Vl6CxuFTTMqipiTN5Kxyfr8pIRlBG\nirRCE6ZFrCYkTZ8XwvLly/HOO+8AAM6fP++o1KdPn0ZQUBDeeecdTJkypb0gMk4VNoMRoqiQQHQy\nfV4IWmpCacygObOgl+nzQpCiCT1MnyeMBZ8meI1QVVUV5syZg6+//hoAMGrUKBQUFCAsLExSgbKz\ns5GVldXhTkGuRt8sDTIZIYFoYISMpgk1MIvuzIAWRkhNTZARIsTCpwneJ0tnZ2djypQpqK2tRW1t\nLbKyskz1+HS9QhcW/UKaIAhXSBOEkeGNCCUkJODgwYO8y3wuiAx3v2YzDxQVEoAGESEjaUItzKY9\nI6NFREhNTVBEiBCLzxGhbt26YfXq1WhpaUFzczPWrFmD7t27y1pIOTBjQ2zGfTIDRtEEQagFaYIw\nMrxGqLCwEOvWrUOvXr1w/fXX45NPPsHKlSvVKBtB6BLSBEG4QpogjIxis8bE4ks3gNkjJ9RF5gUD\nzRoTC3WNEVIw0qwxsVDXGCEFPk1wPkfI+SV69uc6OH/Xy8v0qAEm1MIomiAItSBNEGaA0wgNHTrU\nUbHnz5+PhQsXOio5PfFTXehp0/qANEEQrpAmCDMgqGssKSkJBw4cULYgEroBogYcwqXiEtWfLKp2\nnpeKS1DdN0e1/AC0PcFZzacYS81Po64xvWoCgPrnDkDYj4Wqa8LM+fmSp1ZdY2ppQkrXmJHOH+Un\nf54+zxrTK/YuMS0eLa92no3Fpep3Aar9GguNX5thKjQ4llpowsz5aZWnWbHC+TN7fkrmaVgjRBAE\nQRAE4SucY4SCg4MdfbyNjY3o0qWL4zebzYb6+nrlS8eBVQdI01ghbdGzJghCC0gThBnQ1/R5gpCA\nTqqw7JAmCKmQJgjCFZ9eukoQBEEQBGFWaIwQQRAEQRCWhYwQQRAEQRCWxRRGqKSkBAEBAfjss88U\nz2vt2rVISEhAfHw80tPTUVZWpmh+W7ZswaBBgxAZGYn8/HxF8wKAqqoqZGZmYvDgwYiNjVXtybAt\nLS1ISkpCVlaWKvmZHdKEfJAmzAFpQj5MpwlmcJqbm1lmZiabPHky+/TTTxXPb/fu3ezcuXOMMcY2\nb97MUlNTFcurubmZRUREsIqKCtbU1MQSEhJYeXm5YvkxxthPP/3EDhw4wBhjrKGhgUVFRSmeJ2OM\nLVmyhE2bNo1lZWUpnpfZIU3IC2nC+JAm5MVsmjB8RGjZsmWYOnUqQkNDVckvLS0NXbt2BQCkpqai\nurpasbz27duHgQMHIjw8HIGBgbjvvvtQVFSkWH4A0KtXLyQmJgJomxobHR2N2tpaRfOsrq7Gpk2b\n8PDDD5t2touakCbkhTRhfEgT8mI2TRjaCNXU1KCoqAizZ88GoP7Uyvfeew+TJk1SbPs1NTXo06eP\n43tYWBhqamoUy8+dyspKHDhwAKmpqYrm89RTT+G1116Dn5+hq6MuIE0oC2nCeJAmlMUMmjC0yubO\nnYvFixc7Xvqn5p3T9u3bUVhYqGh/rJbPzLhw4QKmTp2KgoICBAcHK5bPxo0b0aNHDyQlJdGdrwyQ\nJpSDNGFMSBPKYRZNcD5ZWq8sX74c77zzDgDg/PnzuO+++wAAp0+fxubNmxEYGIgpU6YokqfNZsOm\nTZvwyy+/YNasWdiyZQtCQkJkzcuZG264AVVVVY7vVVVVCAsLUyw/O1euXMFdd92FGTNm4Pbbb1c0\nr927d2P9+vXYtGkTLl++jPr6esycOROrVq1SNF8zQZogTRCukCZIE6KQdcSRhjz44IPsb3/7m+L5\nnDhxgkVERLA9e/YonteVK1fYgAEDWEVFBfv1119VGQTX2trK7r//fjZ37lxF8/FEcXExu/XWW1XP\n16yQJuSBNGEeSBPyYDZNGC4ipDULFy7E2bNnHf3NgYGB2LdvnyJ5BQQE4K233sL48ePR0tKChx56\nCNHR0YrkZWfXrl1Ys2YN4uPjkZSUBAB49dVXMWHCBEXztUOP0DcepAllIU0YD9KEssitCXrFBkEQ\nBEEQlsXQg6UJgiAIgiB8gYwQQRAEQRCWhYwQQRAEQRCWhYwQQRAEQRCWRXdGyP2hTO+//z6eeOIJ\nUdvYsGGDrA+wOn/+PFasWCFoXSUfKiU079raWtx9992St/Pmm2+isbFRrmK58Oyzz2LHjh0AgPDw\ncNTV1Unazvr16/Hyyy/LWTTdQpqQDmnCnJAmpEOa8ICsk/FlIDg42OX7+++/zx5//HHB6Zubm+Uu\nEquoqGCxsbGC1nUvv1J42k+58g4PD2enT5+WZVvO1NfXs5SUFJd8zpw5I2lbra2tLCEhgTU1NclV\nPN1CmhAGaYI0IRTShO+YSRO6iwi5w5xm91dWVmLMmDFISEjAuHHjHE/TfPDBB/H73/8ew4YNw/PP\nP48PPvjAcXeQmJiIpKQkJCUlISgoCDt37kRdXR1uv/12JCQkIC0tDYcOHQIA5OXlIScnB5mZmYiI\niMCyZcsAAC+88AKOHz+OpKQk5Obm4uLFixg3bhyGDh2K+Ph4rF+/nnc/Vq1ahYSEBCQmJmLmzJle\n90fIfubm5qKiogJpaWmIj4/HvHnzXI5TXFwcgLY7pTvvvBMTJ05EVFQUcnNzHes9+uijSElJQWxs\nLPLy8gAAS5cuRW1tLTIzMzF27FgAwNatWzF8+HAMHToU99xzDy5evOiyb8ePH8fQoUMd348dO+by\n3U5RURHGjRvXYXljYyMmTpyI9957DydOnMCgQYOQnZ2NG2+8EdOnT8fWrVuRnp6OqKgolJSUAGh7\njkRaWhq2bt3Ke+zNBmmCNEGacIU0QZrwSROSbJaC+Pv7s8TERMdf37592RNPPMEYY+zWW29lq1at\nYowxVlhYyG6//XbGGGMPPPAAy8rKYq2trYwxz3cH69evZ6NGjWJXrlxhjz/+OFu4cCFjjLFt27ax\nxMRExhhj8+fPZ+np6aypqYmdPn2adevWjTU3N7PKykoXp9/c3Mzq6+sZY4ydOnWKDRw40PGbJ7d9\n+PBhFhUV5XC1Z8+e9bo/QvczKyuLrV69mjHG2Ntvv+3I2/nOZOXKlWzAgAGsvr6eXb58mfXr149V\nV1czxhirq6tz7E9GRgY7dOgQY8zVgZ86dYqNGjWKXbp0iTHG2OLFix3HzpnMzEz27bffMsYYe/HF\nF9lbb73VYZ3f//73Lk91DQ8PZ5WVlWzcuHGO/aioqGABAQHs8OHDrLW1lQ0dOpTl5OQwxhgrKipy\nHAv7sXn++ec75GM2SBOkCdKEK6QJ0oScmtCdEfIW8uzevbsj1NfU1MS6d+/OGGt7bLp2r48kAAAP\nMUlEQVS9QrinYYyxo0ePskGDBrGff/6ZMcZYUlISq6iocPzep08fVl9fz/Ly8tiiRYscy6Ojo1lN\nTU2HkGdTUxN77LHHWHx8PEtMTGRBQUHs5MmTHsvPGGNLly5l8+bN67Cca3+E7qddgIwxdv78ec4K\nPmvWLEeaiRMnsl27djHGGFuxYgUbMmQIi4+PZ6Ghoezjjz9mjLlW8A0bNrDu3bs7GpyYmBj28MMP\nd9iXtWvXsieffJK1tLSwiIgIh3icmThxItu9e7fje79+/VhCQgL78MMPHcsqKipYZGSk4/vMmTMd\nvx8/ftzRGDHG2JYtW9g999zTIR+zQZogTZAmXCFNkCbk1ITuX7HB3B587f7dTlBQkMflFy5cwL33\n3ot3330XPXv25N1Op06dHJ/9/f3R3NzcYZ21a9fi9OnT2L9/P/z9/dG/f39cvnyZcx/sbz32hNjl\nXPvpjc6dOzs+2/epoqICS5YsQWlpKbp27Yrs7GzOfbj55pvx4Ycfes3jrrvuwoIFCzBmzBgkJydz\nvmSwtbXV8dlms2HEiBHYvHkzfve733ksr5+fn+Oc+Pn5uZyP1tZWS75+gDThCmmCNEGacIU0IU4T\nuh8j5Mzw4cPx0UcfAWirZKNGjfK4nnPlyMnJQXZ2NtLT0x3LRo4cibVr1wIAiouLERoaii5dunBW\nqi5duqChocHxvb6+Hj169IC/vz+2b9+OEydOeC33mDFj8MknnzhGvp89e9br/gjdz/T0dJf1hMIY\nQ0NDA66++mpcc801OHnyJDZv3uyyv/X19QCA1NRU7Nq1C8ePHwcAXLx4EceOHeuwzc6dO2P8+PGY\nPXs2srOzPebbr18//Pzzzy7LFi5ciJCQEDz22GOCy2/np59+Qr9+/USnMxOkCVdIE6QJ0oQrpAl+\nTejOCLk7N5vN5li2bNkyrFy5EgkJCVi7di0KCgo8prOn+fHHH/G3v/0NhYWFjoFw+/fvR15eHv71\nr38hISEBf/jDH/DBBx90yMuZbt26IT09HXFxccjNzcX06dNRWlqK+Ph4rF692uUFd57Sx8TE4KWX\nXsLo0aORmJiIZ555xuv+CN3PgoICvP3224iPj0dtbW2HY8C1TzabzfGyvEGDBmH69OkYMWKE4/dH\nHnkEEyZMwNixYxEaGor3338fv/vd75CQkIDhw4fjyJEjHfYRAKZNmwY/Pz/ccsstHn8fMWIESktL\nO5SxoKAAjY2NeOGFFzjL6+nzvn37OMVvJkgTpAnShCukCdKEnJqgl64SsvH666+joaEBCxYs8Pj7\nhQsXkJmZ6RjR7wutra0YMmQISktLERCg+x5ewqKQJgjCFT1qgtRCyMIdd9yBiooKbNu2jXOd4OBg\nZGZmYvv27cjMzPQpv40bN2Lq1KnU4BO6hTRBEK7oVRMUESIIgiAIwrLobowQQRAEQRCEWpARIgiC\nIAjCsui6M/m6665zTCEkiODgYJfpqVaENEE4Q5ogTRCuSNGErscItU2Be4fj1/UAlnAnDoj0vLw1\nD0jP406XzLG8Kg+YypEuhfsQdlv1KLrlzfb4WwzKOdPV5S3H6LyRotJ9mvdv/Hdeq8ffACCu7qjH\n5QvygbzxnMmAUs+L8/4B5IWKTzfnGMD1nugdXjY3C9wPELMKpAkDa4IjDUCa8AXVNcGlB4A04YG8\n1UBenLg0gLqaoK4xgiAIgiAsi4GN0BlpyViltHSnpKW7UlkrKd25ynOi05yqvCQpr8ofJSVDpcRo\ndLW0ZAQvpAl3SBNWhzThjuqauMi/jifU1ISBjZC1w8EE0RHSBEG4Qpog+DGwEeouLZktXFq6UGnp\nAsN7S0p3bfi1otOEhot/0R4AhPeVlAzhnt+Xx0uYtGQEL6QJd0gTVoc04Y7qmrhaWjo1NWFgI0QQ\nBEEQBOEbBpg1RhBt0FRh0gThCmmCNEG4Yrrp8wRBEARBEEpCXWMEQRAEQVgWMkIEQRAEQVgWwxuh\nZcuWITo6GrGxscjNzRWVdsmSJfDz80NdXZ2g9Z977jlER0cjISEBd955J86fP+91/S1btmDQoEGI\njIxEfn6+oDyqqqqQmZmJwYMHIzY2FkuXLhWUDgBaWlqQlJSErKwswWnOnTuHqVOnIjo6GjExMdi7\nd6+gdK+++ioGDx6MuLg4TJs2Db/++qvH9XJyctCzZ0/ExbU/WrSurg4333wzoqKicMstt+DcuY7P\nwvCUTuzxtyqkiXZIEwRAmnCGNOEBZmC2bdvGxo0bx5qamhhjjP3yyy+C0/74449s/PjxLDw8nJ05\nc0ZQmq1bt7KWlhbGGGO5ubksNzeXc93m5mYWERHBKioqWFNTE0tISGDl5eW8efz000/swIEDjDHG\nGhoaWFRUlKB0jDG2ZMkSNm3aNJaVlSVofcYYmzlzJnvvvfcYY4xduXKFnTt3jjdNRUUF69+/P7t8\n+TJjjLF77rmHvf/++x7X/eqrr9j+/ftZbGysY9lzzz3H8vPzGWOMLV682ONx9JROzPG3KqQJV0gT\nBGnCFdJERwwdEVqxYgVefPFFBAYGAgBCQ729+MqVp59+Gn/6059E5XfzzTfDz6/tkKWmpqK6mvvZ\nl/v27cPAgQMRHh6OwMBA3HfffSgqKuLNo1evXkhMTATQNvo9OjoatbX8Tx2trq7Gpk2b8PDDDwt+\nz8r58+exc+dO5OTkAAACAgLQtWtX3nTXXHMNAgMDcenSJTQ3N+PSpUu44YYbPK47cuRIhIS4Plxl\n/fr1eOCBBwAADzzwAD7//HNB6cQcf6tCmmiHNEEApAlnSBOeMbQROnbsGL766isMGzYMGRkZKC31\n8gY3J4qKihAWFob4+HjJeRcWFmLSpEmcv9fU1KBPnz6O72FhYaipqRGVR2VlJQ4cOIDU1FTedZ96\n6im89tprjgoghIqKCoSGhiI7OxtDhgzBrFmzcOkS/+PXr7vuOjzzzDPo27cvevfujWuvvRbjxo0T\nnO/JkyfRs2dPAEDPnj1x8uRJwWnt8B1/q0KaaIc0QQCkCWdIE54JEL1llbn55pvx888/d1j+yiuv\noLm5GWfPnsXevXtRUlKCe+65Bz/88ANvuldffRVbt251LHN2xlzpFi1a5OhTfeWVV9CpUydMmzaN\ns9y+PtviwoULmDp1KgoKChAcHOx13Y0bN6JHjx5ISkpCcXGx4Dyam5uxf/9+vPXWW0hJScHcuXOx\nePFiLFy40Gu648eP480330RlZSW6du2Ku+++G2vXrsX06dMF523HZrOJPlZCjr+ZIU2QJtwhTZAm\nSBOuiNIEb+eZjpkwYQIrLi52fI+IiGCnT5/2mubQoUOsR48eLDw8nIWHh7OAgADWr18/dvLkSUF5\nrly5kg0fPpw1NjZ6XW/Pnj1s/Pjxju+LFi1iixcvFpRHU1MTu+WWW9gbb7whaP0XX3yRhYWFsfDw\ncNarVy8WFBTE7r//ft50P/30EwsPD3d837lzJ5s8eTJvuo8++og99NBDju+rVq1ijz76KOf6FRUV\nLn24N954I/vpp58YY4zV1tayG2+8UVA6xoQff6tCmmiDNEHYIU20QZrgxtBG6M9//jP77//+b8YY\nY0eOHGF9+vQRvQ0xg+A2b97MYmJi2KlTp3jXvXLlChswYACrqKhgv/76q+BBcK2trez+++9nc+fO\nFVQmd4qLi9mtt94qeP2RI0eyI0eOMMYYmz9/Pnv++ed503z77bds8ODB7NKlS6y1tZXNnDmTvfXW\nW5zru1fU5557ziH2V199lXMwm3s6McffqpAmOkKasDakiY6QJlwxtBFqampiM2bMYLGxsWzIkCFs\n+/btorfRv39/wRV84MCBrG/fviwxMZElJiay2bNne11/06ZNLCoqikVERLBFixYJymPnzp3MZrOx\nhIQERz6bN28WlJaxtgouZjbAt99+y5KTk1l8fDy74447BM0GYIyx/Px8FhMTw2JjY9nMmTMdMzLc\nue+++9j111/PAgMDWVhYGCssLGRnzpxhY8eOZZGRkezmm29mZ8+e5U333nvviT7+VoQ00RHShLUh\nTXSENOEKvWKDIAiCIAjLYuhZYwRBEARBEL5ARoggCIIgCMtCRoggCIIgCMtCRoggCIIgCMtCRogg\nCIIgCMtCRoggCIIgCMtCRkgD/vKXvyA0NBTvvPMO3n33Xbz00kvIyclBWloaWlpacNNNNwne1rBh\nw0SnIQi9QZogiHZIDyoj6KlIhKwcOHCATZs2zWXZ3//+d3bhwgXGGHP8Z4yx8vJy9sorr3Buy1Ma\ngjAapAmCaIf0oC4UEdKAvXv3Ij09HQDwxRdfAABSU1Nx9dVXA4DjPwBs374dSUlJnNvylIYgjAZp\ngiDaIT2oi39eXl6e1oWwGitWrEDnzp2xYcMGNDY2Ij09HV26dMHGjRuxZ88efPnllwgJCcG//vUv\nvP7664iKikJjYyM+++wzVFdXIygoCE8++STuuOOODmlCQ0Nx+PBhbNmyBXv37kV0dDQ6deqk9S4T\nhFdIEwTRDulBXSgipAFlZWV46aWX8Oyzz+Kmm27Cr7/+ioMHD2LNmjV44IEHMGnSJCxfvhwTJkxA\n7969MWvWLPj7+6NHjx64fPkywsPDERERgaNHj3ZIAwCFhYUYNGgQOnfujAsXLmi8twTBD2mCINoh\nPagLGSGVaWhogL+/P/z8/NCtWzekp6dj27ZtWLduHaZPnw4AOHHiBEJCQnDy5En06tULAJCWlobP\nP/8cEydOBAAMHjwYH3zwQYc0ADBjxgw8/fTT+Oyzz9CzZ08N9pIghEOaIIh2SA/qQ0ZIZUpKSpCQ\nkAAACAwMhJ+fH/7zn//g119/Rd++fQEAn376Ke6//37s27cPN910E0pKSnDx4kWcPHkS3bp1Q2lp\nKYYNG+YxzT/+8Q+UlZXh66+/Rvfu3TXbT4IQCmmCINohPagPjRFSkZKSErz22mtoampCQ0MDdu/e\njdzcXEyZMgXjxo3Dpk2b8J///AcpKSlITU3FhQsXUFpait69eyMqKgo//PAD6urqwBhDYmIi+vXr\n5zFNXV0dvv/+ewwZMgQDBw7UercJghPSBEG0Q3rQBhtjjGldCIIgCIIgCC2grjGCIAiCICwLGSGC\nIAiCICwLGSGCIAiCICwLGSGCIAiCICwLGSGCIAiCICwLGSGCIAiCICwLGSGCIAiCICwLGSGCIAiC\nICwLGSGCIAiCICzL/wPo5vNGJ07DYAAAAABJRU5ErkJggg==\n"
}
],
"prompt_number": 20
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And also plot the model with Mayavi:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"bounds = area + [0, 2000]\n",
"myv.figure()\n",
"myv.prisms(prisms, 'density')\n",
"myv.axes(myv.outline(bounds), nlabels=5, ranges=[b*0.001 for b in bounds], fmt='%.1f')\n",
"myv.wall_bottom(bounds)\n",
"myv.wall_north(bounds)\n",
"myv.savefig('figure3d.png')\n",
"myv.show()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from IPython.display import Image\n",
"Image(filename='figure3d.png')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"png": 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"prompt_number": 22,
"text": [
"<IPython.core.display.Image at 0x41e7450>"
]
}
],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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