bathymetry-closeup-KaraStr-Rayleighdamping.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bathymetry closeup\n",
    "\n",
    "Get a closeup to a particular part of bathymetry file and compare with underlying gebco data.\n",
    "See https://github.com/OceansAus/access-om2/issues/99"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
       "    return false;\n",
       "}"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
    "    return false;\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#notebook { padding-top:0px !important; } .container { width:100% !important; } .end_space { min-height:0px !important; } </style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Eliminate margins\n",
    "# from https://stackoverflow.com/questions/44298864/how-can-i-eliminate-the-gray-border-around-jupyter-ipython-notebooks-in-my-brows\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>\"\n",
    "    + \"#notebook { padding-top:0px !important; } \" \n",
    "    + \".container { width:100% !important; } \"\n",
    "    + \".end_space { min-height:0px !important; } \"\n",
    "    + \"</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# import cosima_cookbook as cc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from matplotlib import cm\n",
    "import netCDF4 as nc\n",
    "import IPython.display\n",
    "import regex as re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# file = '/g/data3/hh5/tmp/cosima/bathymetry/topog_latest.nc'\n",
    "\n",
    "# see https://github.com/OceansAus/access-om2/issues/99\n",
    "fixedbathyfile = '/g/data3/hh5/tmp/cosima/bathymetry/topog_13_06_2018.baffin.nc'\n",
    "\n",
    "depth = nc.Dataset(fixedbathyfile).variables['depth'][:,:]\n",
    "\n",
    "file2 = '/g/data3/hh5/tmp/cosima/bathymetry/ocean_hgrid.nc'\n",
    "data2 = nc.Dataset(file2)\n",
    "lons = data2.variables['x'][::2,::2]\n",
    "lats = data2.variables['y'][::2,::2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`ncdump -h /short/v45/aek156/access-om2/control/01deg_jra55_iaf/work/ocean/rregionocean_daily_30m.nc.3829`\n",
    "yields\n",
    "```\n",
    "\t\txt_ocean_sub01:domain_decomposition = 1, 3600, 3331, 3375 ;\n",
    "\t\tyt_ocean_sub01:domain_decomposition = 1, 2700, 2377, 2412 ;\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# location of region of interest as reported by MOM (-1 to index from 0)\n",
    "\n",
    "imin = 3331-1\n",
    "imax = 3375-1\n",
    "jmin = 2377-1\n",
    "jmax = 2412-1\n",
    "\n",
    "i = (imax + imin)/2\n",
    "j = (jmax + jmin)/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qWn2G41pf0/2SmlA9GDeuPB/3HOUyxSUn/Mf1unOQCd/TcjhuLO8b3DU9rqqdMg20vQIcVkWaMcBpuL7guQSsNQq55LNuuG6gp2sg31ijDFyL88Oky8vTdbmIyGB4AetxMpFB2EIvcfXBKe2eG5lv0LAnx3ya4lqeWxX6XNmS1fXqjFOak3EfAed5eWtc1+1X/jdl0Ss4BTkV13W5e9J1qqrF846v8DpE5Gci0t53tZ2CM4N+Ddd//3/qa15k5LNui3BmhfmkWJrcuVKG6xopGL475ixgaCHrkSKuPr57a5iqTipgvQ4XN7jdBNc6mUiloYhR3KwFzlfVHYC9cV15PXFTMN5U1e44q8ZUN+OhQHe/DMD17iRLNbTnAFzf8o84bfiLQmv0TWEhoa9VW9Y7p/39ffwiOZiClmp9NuYewo0bLsJ1c79J5dyvV6mc5B1dLtuIel4WyPPVjcjzd4E8Py/0dS/AffYirnv+C/xEVtwcsS/8//tZ35x8XbqkltRENMMwDKOWIyLdcON4OwHfqLMMTW37QVVbici/cHOlRnv5m7j5a2OTqkfW5m+GYRhGfthWRJdnmXauG7eJzoMbqqobdB17a8VncUYcS0SCholxGxJtoZjiMQzDKDJWAH/OMu0VsFJV+2RKI24eWMqLQ8oa+DsR6aCqc0WkA85SEZxVWnQuUScq5xIlgimeLGkqoqkZcw0CaeoH5I1DGwIsXxMvD4gzEqxTk8CG0Lzlmr5T0ueiexY1jt+wkkbBrFqzMFbeYElgYnVo/nnoGy80Tzz0Adk4x/Q14bc4nYqAPNtprlWR7ed6itWBbALTvUN23NX5LA9dhpDlVVWnaB6wRHWjJnUK4Wc357xc0+YhYLKq3hHZNBLnU3Cg/30xIj9bREbgzNUXq+rchKoDmOLJms2pNPnoFkizRUDeu21uZY0LfFt8Hy/OSLBOvQIb9s4xo6TYP178Yp/4Ck2iZzCr3/JkrLzrG4G3WChwRcgBSEhph3Rh6FyHnr7WAXl1CB1D6M0dkmftDMUzIcf06TO5POPujpdPDWRTnY+zzQLy0PdCqIyU/KJq1CGdOoTrVQ364uYVTRSR1JW5DKdwnhaRlIf03/htr+DmjU3FfUKcllxVHCWjePxM62FAe9z32lBVHRLZfgHOzXtbVZ0vItvjTHV3xznjvC2S9hCcl9u6OEegA6sqvx6V74PgyzzkfalzQB7KJyAfk6Gx+114UzyhK1/TCiZEYL76kT9uEF/PyVvEywECDZ7wyzDXpyDc2MqNhlUnyYpM0zhXBuQhnxS5KphaQKjBuyLHfJJqoYBr8ST1cvZGAqEW2AEx6ZXse/qqRckoHipt0cd7NyTjRGSUqk7ySukg1v9uWoibsXxUNBPvyuJun34W8JGIjNQCzpEwDMOIkmRXWzGysb7D8oaqzlXV8f7/Utws3JTX3UG4Fq5G0n+vqh+xYct4T2Cqqk5X50JmBM6JpWEYRlGQavFks5QiJVlvb4u+GzBGRI7AhWr4JIN5YJSOrO/faxZuAM0wDKMoqO0tnpJTPFFbdFz32+XAwblkESOLNVQRkQE4Tw1VBnwxDMNIiiTHeIqRkjq2dFt0cQHXtgJSrZ1OwHgR2VNVvw1kk7WNup+ENRRgGxFz8WAYRl6oQ9iqrjZQMoonzhZdVScSscMSkTKgj6rOz5DVR0B3cbGGZuNcqv82Q3qXN1mYN4YswkImyqGz/0G8uF6SU7h2CshDpr+5kqs57eKAPBSdJdNcl2KzOgsRMsvOlZDlGlQduKDICVmKlgWeheqYU1dlHp1OVV1gSX2hlszLuRqU0rHF2qKramyMHRFpD4zFTU2sEJG/4NzKLxGRs3GxXeoCD6uLN2IYhlEU2BhPkVCFLXoqTbfI/2+JhOtNS/cKyQWFMwzDSBQb4zEMwzDyirV4DMMwjLySsMucosMUj2EYRpFhXW1G9rQIyA8LyENWUwErpd5fh4sO+XcLlnFEvHjhwfEmYa0nBCqVq+fSkC+wH3NMn4nQdSj1uz10jkrccg3I+dpU57YI7ZO0e7okrNqsq80wDMPIK9biMQzDMPKKtXgMwzCMvGKKxzAMw8grAmyW7du5BGMomeIxDMMoMkSgnikeQ6n03ZTrdQ5Ziq0OmJy1fy/kuKwadIkXzzg4Ph73l/SIlffuNTZW3vo/mRyFxZAP06LQ6Qv5cAv5fUvK51vIb13fgDxkiRiyaiskufrkCxEK9x04F6EXV6aoodXx4xZH6FZNNAKpQP1M/ghLHFM8hmEYRUZOLZ4q85KHgV8C36vqTl72D1j3ldkSWKSqvXyss8nAF37bB6p6ZjI1qcQUj2EYRpEhQP3k3s6PAncBw1ICVT1uXVkit7N+P8E0VU3KT30spngMwzCKDSFz6I8cUNV3fUtmw2JcuJljgf2TKS076uSzMMMwDCML6uDGGLNZNo59gO9U9auIbCsR+VhE/iMi+2x0CTFYi8cwDKMYyf7t3EZEotY/Q3305Gw4AXgqsj4X6KKqC0SkN/CCiOyoqkuyrk0WmOIxDMMoNnLrapuvqn1yLkKkHvArIq4eVXUV3vufqo4TkWnAdrigmolhiidLojOJvwsl+ipeHHKwuTA0fJcHp48T2K3mC4mjvDDFAuEQ0aHuilxNv3N9mt7LMX1tJscuo9AlyGQyXVLTXfLjrO1AYIqqzlpXrEhbYKGqlovI1kB3YHrSBdsYj2EYRrGRUjzZLFVlJfIU8D+gh4jMEpHT/abjWb+bDWBf4FMR+QR4BjhTVRdu7OGkYy0ewzCMYkMITyTOEVU9ISA/NUb2LPBsMiWHMcVjGIZRbNTyuAi1+NAMwzBKGHOZYxiGYeQNa/EUByLSGefyoT1QgbNVHxLZfgFwK9BWVef7GblDcIGnlwOnqup4n7YcmOh3/UZVA4GgK4k6CQ2NtD0xJ15+4knx8ta/CZhZ/aeq2uRAwNLuyAlvxMpn94r31hgMfZ2rBV6OPkX5LMf0mdgpIA/VKfTFmZR5VMk8fQWkSaErUCBM8RQNa4HzVXW8iDQDxonIKFWd5JXSQcA3kfSH4kwBuwN7Aff6X4AVNe2LyDAMo9rUcsVTMubUqjo31WJR1aU4D6od/eZBwEW4hkmKI4Fh6vgAaCkiHfJZZ8MwjGqRsmrLZilBSkbxRPEO73YDxojIEcBsVf0kLVlHYGZkfRaViqqRiIwVkQ9E5KgM5Qzw6cYm6i/CMAwjEwnO4ylGSq7aItIUZ2f+F1z32+XAwXFJY2SpFlEXVZ3jZ+a+JSITVXXaBomdv6OhANuIaPp2wzCMGiFB79TFSEm1eESkPk7pPKmqzwHbAFsBn4hIGdAJGC8i7XEtnM6R3TsBcwBUNfU7HXgHCuU/xjAMIwZr8RQH3krtIWCyqt4BoKoTgS0iacqAPt6qbSRwtoiMwBkVLFbVuSLSCliuqqtEpA0uAPEt2dShKmOmUNjdRwOWWafm6IhiXMBqDqAsIG8ckB96dry841U5VirX0MdJ+aHLFAY61O8dspALWbuFSMrfXK7WcaGntWSe4mrQIrfkmcJP17SvttRliOtq2agMayGldGh9gZOAiSKSet1dpqqvBNK/gjOlnoozpz7Ny3cA7heRClyLb6CqTqq5ahuGYeRILe9qKxnFo6qjqeJjQlW7Rf4r8OeYNO8DOyddP8MwjMRIBYKrpZSM4jEMw9ikqMVv51p8aIZhGCWKdbUZhmEYeaWWey6oxYeWf3INWPlswEqteY75ZNq2ICAfF4h+2XtkYIcuGQqPI+T/LFTRkMXZ4oA8dGAQ7hvfMsM+SVDT1m4hi8BMT3HIwq9UnvxAPTcLJM8UgTQpQqcuVadErNpM8RiGYRh5JcFAcMWIKR7DMIxio5a3eErKc4FhGMYmQYKeC0TkYRH5XkQ+i8iuEZHZIjLBL4dFtl0qIlNF5AsR6Z/kYaUwxWMYhlGM1M1yqZpHgUNi5INUtZdfXgEQkZ7A8cCOfp97RCRx+zpTPIZhGMVGgi0eVX2XcPzKdI4ERqjqKlX9Guf5Zc8ca18ltbgXseYIWZ2FQieEjJSWJlCXFDV+IUPWZaEIkTXtky2TBVkmP25xJOUDLdfvwtA5Ct0woWPOdK5DeYWuW7G9EQJ+9DYLROkN+UuEsCVcpn3iCD3/Kb+IiXzN52eM52wRORkYiwuy+QMudMwHkTTRcDKJYS0ewzCMYiO3QHBtUnHD/DIgixLuxXn37wXMBW6PlJxO4iFhiu37xjAMw8itxTNfVfvkkr2qfreuKJEHgH/51WA4mSSxFo9hGEaxkXKZk4xxwYbZi3SIrB5N5RTukcDxItJQRLYCugMfVq+UMNbiMQzDKDYSHOMRkaeA/XBdcrOAq4H9RKQXrhutDPgjgKp+LiJPA5NwI4R/VtWkfHKswxSPYRhGMZLQ21lVT4gRP5Qh/Q3ADcmUHo8pnixRKv1AhaxjQvIQofQhq5lM0RWr8h+VTu/OgQ25FpCrg7pcSTJsZCjSaCjKZchlSahOIR9xufpey9XaLRO5+szbvBplFIDQfZ3phZbrcxvKq6rns4Ss2gpGLT40wzCMEqUO5qvNMAzDyDO1+O1ciw/NMAyjRLFAcIZhGEZesTEewzAMI6+Y4ikORKQzMAxoD1QAQ1V1SGT7BcCtQFtVnS8iAgwBDgOWA6eq6nif9hTgCr/r9ar6WJXlk9mqDHK3agsZEDXLMR+A3qHomqEBylBE0VClQr69QiTlqy1Ubqb6hO7qpI4t16cm1/RJWvKFCPmzC9U1ZPlXIHJ91jLtE3quc7V2S6VPpIfMAsElh4j8BDgR2AfogPPP9xnwMvCEqoZcUYJ7HM9X1fEi0gwYJyKjVHWSV0oHAd9E0h+Km3XbHdgL55toLxFpjZtA1QdnJT1OREZ6B3mGYRiFp5a3ePLmMkdEXgXOAF7HxXnoAPTEtTwaAS+KyBGh/VV1bqrFoqpLgclUek0dBFzE+s7sjgSGqeMDoKV3E9EfGKWqC72yGUV8rArDMIzCkGBYhGIkn9U+SVXnp8mWAeP9cruItMkmIxHpBuwGjPHKaraqfuJ619bREZgZWU+59w7JDcMwigezatt4UkpHRNrhXvQKzIl6SY1RTBsgIk2BZ4G/4LrfLgcOjksaV40M8riyBgADALLSiIZhGElQy7va8nZo3iHdfbhhytle3ElEFgFnpbrRqsijPk7pPKmqz4nIzsBWQKq10wkYLyJ7EnbvPQvnMC8qfyeuPFUdCgwF2EYk8ZgUhmEYsZjiSYxHgT+q6pioUET2Bh4Bds20s7dSewiYrKp3AKjqRGCLSJoyoI+3ahuJi7A3AmdcsFhV54rI68CNItLK73YwcGlVla9DpY+mNYE0IXnjgDxkvRa0UMtkfdU6IA9F6dgiIA/5G8uVXCOThvyofRaQZyJ0zPvHixf+LLeDbj0m4AAtZBozISDP1XqtOuciV0LXIWRhldT9EiKQf+gZWZshckzo+azKWrUgmFVbYjRJVzoAqvqBiGRj0NoXOAmYKCKpR/kyVX0lkP4VnCn1VJw59Wm+vIUich3wkU93rapmG4/cMAyj5rEWT2K8KiIv4+bipAb3OwMnA69VtbOqjiZ+fCaaplvkvwJ/DqR7GHg4q1obhmHkG1M8yaCq54rIoTgz5464UzsLuDtDq8UwDGOTRM2qLRlU9VXg1XyWaRiGUWqoQLm1eAzDMIx8oXVgVcNs5/dX1GhdagJTPFlSn7AhWIqQhUIoYmHQeq06Vm0ha6RQpffOMX3o4EKWWSFLrpD1XcjarW9AnsF32MKL4k2h/su+sfJJ9IyVlwdm8PXa6+NY+S8nvBWuVC6ErNdC/tWWVaOMpjmWHbq/kvJ/FyJ0fwXu070yZDUug8VbEqSe58bzNj4vFaG8Xrav59UbX2CeyZvLHMMwDCN7yuvWzWqpChF5WES+F5HPIrJbRWSKiHwqIs+LSEsv7yYiK0Rkgl/uq4ljy3uLR0S2As4BukXLV9WgnzbDMIxNCUWCLe5q8ChwF86iOMUo4FJVXSsiN+PmMl7st01T1V5JFR5HIbraXsBNBH2JUuycNAzDqGEUYW1CikdV3/X+LaOyNyKrHwC/TqSwLCmE4lmpqn8vQLmGYRglQ3n2r+dMCx8XAAAgAElEQVQ2IjI2sj7Uu/vKlt8D/4isbyUiHwNLgCtU9b855JUVhVA8Q0TkauANIkPK2fhqMwzD2BSooA6raZBt8vmqGnIUlRERuRxnwvGkF80FuqjqAhHpDbwgIjuq6pLq5B+iEIpnZ5zrm/2p7GpTgp60DMMwNj0SHOOJxUdi/iVwgPf0gqquwjcIVHWciEwDtgPGBjOqBoVQPEcDW6tqSdkANm4CvVPDbV/Hp8nZXDNkZx0yRQ2ZtELOZtOjDu4XK18ecGnai3gT4q4TArajoc+IXL3iBY5rRq+2wV2G87tYeehB/oIeOVYqnoa94m/pg74fHb/DG/HioAlxkubAoe/X0D0ZInRPho4hZAYfSp9rPiGTczJMXyhCkhzjiUNEDsEZE/xMVZdH5G2BhapaLiJb4yI4T0+6/EIonk+AlsD3BSjbMAyj6HFWbcm8nkXkKVwomDYiMgu4GmfF1hAY5UPKfKCqZwL7AteKyFqgHDizJpwoF0LxtAOmiMhHrD/GY+bUhmEYnqS62lT1hBjxQ4G0z+JintUohVA8VxegTMMwjJIh4Xk8RUfeFY+q/seHv97Diz5UVet2MwzD8CjCqlocCS7vLnNE5FjgQ+A3wLHAGBHJ6+QlwzCMYibV4slmKUUK0dV2ObBHqpXjrSj+DTxTgLpkT0sgNQoViB7UO9d7IORgMVeHjBAMETzj4Hjrr2GcHCufxA6x8p5MjpWf3GtYrHw7voivUI5MYLdY+UR2Du6TlJVarvmHLP9yJmC9VtNOLgF6hzaU55hR6B4OOYNN6v2ZyXItZPEWiGQerGvI0q6L/01oxkupKpVsKITiqZPWtbYAc1ZqGIaxDhvjSZ7XROR14Cm/fhzBNoRhGMamR03P4yk0hTAuuFBEfgX0w4W/Hqqqz+e7HoZhGMWKIqyuxcYFeVU8IlIXeF1VDwSey2fZhmEYpYJ1tSWId8OwXERaqOrifJZtGIZRSlhXW7KsBCaKyCgidiaqem6mnUSkMy6QUXucc9GhqjpERK4DjvSy74FTVXWOiLQCHga28WX+XlU/83mVAUtxtjprs/Hsurp9PWZc1AqArgcH/JONrCqXNDL4lYolQzjhULjnK7ghVv7EzX/IqejxxPt2m3RxvBXc0byQU/4hnueoWPm0Vdsmkj/ANg2nxspDlnw9crXYC123wHtlXMAXYHX8loQMsEKMCVjO7RWyFvsmxwIy+Rus6XxCYb1zDdMdKjv1No2/bXIiSZc5xUghjuxlv+TKWuB8VR0vIs2AcV553aqqVwKIyLnAVcCZwGXABFU9WkS2B+4GDojk93NVnb8xB2IYhlETWFdbQojIm6p6ANBTVS+ucoc0VHUuLlYEqrpURCYDHVV1UiRZE1yIBYCewE0+/RQfS7ydqn63UQdiGIaRB0zxJEMHEfkZcISIjMBZtK0jl0BwPozrbsAYv34DcDKwGPi5T/YJ8CtgtIjsCXQFOgHf4ZTTGyKiwP2haH0iMgAYANCxi001MgwjP1RQp1a7zMmn4rkKuAT38r8jbVvWgeBEpCnOe+pfUlHxVPVy4HIRuRQ4G+eIdCAu2ukEYCLwMZVd3n39ONAWOLfgU1T13fSyvEIaCrBLn/qavt0wDKOmsBZPAqjqM8AzInKlql5XnTxEpD5O6TypqnHm2MNx40dXe6V0mt9PcOHbvvZ1meN/vxeR54E9gQ0Uj2EYRiGwMZ6E2QilI7gYEpNV9Y6IvLuqfuVXjwCmeHlLYLmPdHoG8K6qLhGRJji3PUv9/4OBa6sqf5L2ZNdVrwNweK+XYtP07DUpXk68/MgxgRCUuVq7AfdzZqz8iU8C1msf5FhA+3jx+H/EW7tNOyoZq7PFUwIFT6lGZtvHi6cF5KGejpBVW72QQ7OQ1VTAv16I0OBkJsu10ANePyBfHpCvCVi79QtZu+U6kpqUtVuSZYSuT+uAPHWyQyc3B0zxFA99gZNwptgTvOwy4HQR6YEzp54B697AOwDDRKQcmASc7uXtgOd91L16wHBVfS0/h2AYhpEdNo+nCFDV0aQZJHhi/byp6v9w8cLT5dOBXZOtnWEYRnLYPJ6EEJFQAxWAmojrbRiGUYo4X20NEslLRB4Gfgl8r6o7eVlr4B9AN6AMOFZVf/BDGkOAw3A9r6fmYnGcLfm0ER4HjPW/84Avga/8/3F5rIdhGEZRk/JOnc2SBY8Ch6TJLgHeVNXuwJt+HeBQXE9Rd9xUknsTOaA08qZ4VHUrVd0aeB04XFXbqOrmOE1sDkMNwzA8qa62bJYq83JTRdJ7lI4EHvP/H4N1vqmOBIap4wOgpYh0SOiw1lGITsQ9VHWdCZaqvur9rRU15VPqs7ifs7B64tfxlmIt/vJtrPzwhvFWcOwVL24ctC0KM4me8RtCZhOzciwglD7+kFlcFrBGy5WygHxshn1CnvcCeS0OmeztGu/DLUTdXMN09o0X9/5ZvHzpf+Ll1XENluuDvyIg3yxg7RaMZNo0x4JDVMdSMDQfM9eT0SsgT9Xp4RzzC5CDVVsbEYk+EUNDk+IjtPPeYFDVuX5OI0BHYGYk3Swvm5ttZbKhEIpnvohcATyBmzh6Ii4KqWEYhkHO5tTzs3F0nCVxBlyJT54vhOI5AedZ4HncAb3rZYZhGAZO8axKyLggwHci0sG3djrgPPuDa+F0jqTrBATatdWnEBNIFwLniUhTVV2W7/INwzCKnTyYU48ETsG5FjsFeDEiP9v709wLWJzqkkuSvHu+FJGfisgk3KRORGRXEbkn3/UwDMMoZsqpm9VSFSLyFPA/oIeIzBKR03EK5yAR+Qo4yK+Dmxc5HZgKPACcVRPHVoiutkFAf3zYNFX9RET2LUA9Nhka1YPG9WDhyvXlDepDs8awIC0WbP160KIpLFwCFRWV8rp1oVUz+GEplEfG0evUgdZNYdGPsDbH8XXDMDYkSZc5qhoayjggXaCqCvw5kYIzUJCpsao607usSVH8r6vlS2DsKPd/ykGxSULWUU8cEvCXFvCfkHOES+ClVYdvIGuK8EA/OHZ3N5hWtgD+7xkYPQ1u/hOc+mtQhXkL4ZKb4cVRcPV58OeT3P7LlsPVg+CxZ+H/zoALBziltHoN3HwfDHkETj8Arj4XGm/m8rrzMbjuTtAJG1SnepSFLPzeC+8TuD6cGEgfsPybtn3A31yO3uoX9srNKVvrLVbGyvd7MD59s7vDeYUs3kJWaiG/b0sD8u8D8nEha7dco32GTl1C/u+AsJVaYMr7wj7xhSylGQCrm/5QjUqsT2oeT22lEIpnpoj8FFARaQCcSyLBYo107qvXggV1Yasr4YflcNiO8NTp8M6X0HAh7HAgfDsPfrYXDB8CRxwIW3WG3ofDjNnQe2d4+i74aW/YYxfY73j4YjrssC2MuBN26A4H/ASOHAAff+72HXY7lFfADXcV+ugNo7QxlznJcibOJUNHnAXFG+Shabep0ZW67FmnPp2fhNX+M/blz+CB0XD+gdChDyxa4uT/GQPX3QWDr4Qe+zulAzBuIvz1ehjxd+j3G6d0ACZPhT9eBm8Nh2P+5JQOwNcz4dQL4f1nYOC963fHGYaRPRXUScxlTjFSCKu2+cDvojLf8jESpKvU5UstZ/Xa9ZvrcxbBmvJKpZNi+jdQt06l0kkxYRI0agifTI6Xp5ROimkzYLNG0KQxLAn1zxiGUSW1OSxCIaza3vGhq1PrewAf5bsetZ3JupadpB6tGq8v33FLp2C6dlxfvueusGKV616L0n9fWLwUDkoLu3Owl/dPMwvZezf4foEpHcPYGBL21VZ0FKKr7SbgNRH5O6677TB8pFAjOeZRwRPlK3j5z0245AWY9QP8bk84clcY9Ca89CBccBN8MQ1+dQicczLceLcb0/nr9a5F039fuOF8Zyzw0M1w/g3w3jjYZw+47TK49u9wyyXO2m3UaOi9Ewy6Eq64vdBHbxiljYVFSBhVfV1EzgRGAfOB3VQ14PGrSFk2Kl5+ScCaKhDt84lr4q3dTtz1gZyrFBep8wKBF8vh3+dBvTow9wc48254eTxsdzq89ADUrw/zF8JFN8Gjz8JWbd2YTqOGsHgJXDsQBt0FW9SDB26EJk3gxx9h8GCnZOovhTsug+bNYeVKePRReHIwhGNZluV4ZLNjpaqBcw2IjInfcN/O8XIax0oXfxBvpXjbiAti5Rc3vDlYp1zYrle8VWOzu+Kbkb27xFvBAfQeEi8fHbA6m5ixZhtSFpBvFtoh1+i6+bBeC1gphqzXxgWcAY718oUMz7VmsdTmrra8Kx4RuRI4FtgX2AV4R0TOV9WX812X2s59nWD1NNj+bJi9AH63Lzx4NrwwBtq1hN0PdwYDR/eHu66BnXeAPXaHfQ6GCZ/CwQfAg3dBu7bwq8Ph0EPh/fehXz945BGoVw9OPBGOOw5GjYLeveHBB+Gcc+DOOwt99IZRuljo6+RpA+ypqiuA/4nIa8CDgCmeBOlUH37ZHLreDstXOdnDb8IOneDsw6BrX/h+vpP/82XouAXceBHs1he++NLJX30Dzr8MHrgLDj0ERo928nffhT/8AV58EU45BV5/3ck/+gh++1u3fvfd608+NQwje5yvthwnjJUQhehqOw9ARJqo6o+qOgPnssFIkO4N4bOVlUonxfTvnHeBlNJJ8flUNzk0pXRSvPeBs1B7//00+Xuu2y1d/vnn0KyZWxaneUQwDCM7anuLpxBWbT/xvtom+3Xz1VYDfLkKdm4ETdK6qbftAPXqQvu268t33s7N99mhx/ryfX7qxnT6pVm17bMPLFu2oXyXXWDJErcYhlE9UoonCV9txUjeFQ8wGOerbQE4X2248R4jQWavgRcWwz8vhO07QdNGMOBgOPFnrsvtmXugV0835+a3R8LFZ8Ldj8GIR2HvPaFRIzjiF3DbDTD4Hjem8/OfQ8OGcMAB8MADMGSIW375Syf/6U9h+HC46SbnPscwjOpj5tQJUx1fbSLSGRgGtAcqcFH2hvjopUd62ffAqao6R0Ra4WIBbgOsBH6vqp/5vA7BeU+oCzyoqgM3KDCN3r2bM3bsQb4uAas2AvIXAj2JgcCXk+7doarqZMWfZjlPrJ8Ocq2cOQvhjLvhX2NhxOnwwfPOUej8hXDhTc4nW4tL4a1/OcWzeDH87W/Ogq1exWpGjqxPkyaupTN48BquumotS5bU4/HH69OiBaxYAY88spZ77llD2N4p3kotSVQDoV1zJGQdt7hNfP6XjR4UK79u13gruFDE0rEBq6mezqH7BvS66ONYOUDXPvNi5f2ujU8/NRDlNOTbLURZjumD5OrbLWS5liGvhX2rZ72WTioK8IqwTV/WmDl18lTXV9ta4HxVHS8izYBx4jTArap6JYCInAtchXPLcxkwQVWPFpHtgbuBA0Skrv9/EM5lz0ciMlJV45/qEuaWLaHpfNj3ikqrtvvPhMfege22gkNPrbRqu+US6NwB9t8fjjkGPv4Y+veHW25xJtcnnliPU05Zzfvvl9OvX12GDKnP0qXKBRfU59xzVzNqVDm9e9fh739vwMknVzBsWKGP3jBKF0XMZU7CVMtXmw9GlIoRvlREJgMd0xRGEyrDtPbETVZFVaeISDcRaQdsDUxV1ekAPuDRkRD4nCxR2tWDU1rB1n914QoABj4HHTeH834J2+8P3/jGx93DoEUzuPQs2KcvTPCepR97zE0OveMOOPbY1bzxhjNTe+aZclauhCeeaMA556zm8cfdl/vLL1cwb95qRoxowOOPW3ebYVSX2m5cUBS+2nLFu9zZDRjj128ATgYWAz/3yT4BfgWMFpE9ga64MK4dgZmR7GbhIu3VKno2gk9WViqdFJNmOqu2b9J6vD76FBo1qFQ6KUaNcpND//3vijR5Oc2bu98oH35YweabC82a1WHJErOnNozqoFCy4zfZkDfFIyJ3Utka2QBVPTfLfJoCzwJ/UdUlft/LgctF5FLgbOBqXES9ISIyATch+2Ncd53EZBtbLxEZAAwA6NKlSzbVKxq+Xg09G0LD+rBqTaW80+bQoB60agE/RMydu3dz4Qy22gq+/rpS3ru380jQu3cdPvqoIiKvw4oV7vfllyvl3bsLK1fCsmWmdAyj+tTuMZ58WrWNBcbhnF3sDnzll15kGQhOROrjlM6TqvpcTJLhwDEAqrpEVU9T1V641lBb4GtcC6dzZJ9OQKwDEVUdqqp9VLVP27Zt45IULWWr4d0f4aE/Q9sWIAJH7QV/OAie+wAevwM6dXBpD+wHV5wNjz8Pw4bBNts4+d57w6BBzg3Ogw82YMcdnc7eeWdh6NAGPProWv7+9wbssYe7jbp3F4YNa8DgwWts8qhhbAS13Zw6bypVVR8DEJFTgZ+r6hq/fh9unCcj4szgHgImq+odEXl3Vf3Krx4BTPHylsByVV0NnAG8q6pLROQjoLuIbIUzsToe+G1uxxJvpRa2dgv4Lfs23kfYtFWByJc5cspMeKEFzHnIKZ75S+CP9zmrtqdOh+n/cWGrFy+FiwfCQ0/Dg1e4SaD16sHy5XD99c7A4NZby/nww0Y0bAirVsGdd67lkkvWcOmlP/Lmm81p3FhYswaGDfuRgQMXkQ/rtZomV+s4iWtLA1eOuC1Wvvtxo2PlPQO2NimrqXSe4dfBOvXcP37o8rf7PxkrP3W/eCu4ZwPWbqGIpYHgnbBFQL5laIcAIeu1UP6EI8GmIoemszzgwy90HZ74xPteXHF/uBI5kJRSEZEewD8ioq1xRlgtgT8AqYt+maq+kkihVVCIttyWQDNgoV9vSna3XV/gJGCi7z4DZ7l2uj+xFcAMnPECwA7AMBEpxxkOnA6gqmtF5GzgdZw59cOqmhZVpnZwQVtotxKOvw3mLYWj9oTbT4Vt20OvHeDUC2Dmt3BgX7j2/5z1Wv/+8Kc/wVdfQd++cP75sGABnHRSPS68cA2fflpOr151ufLK+nz1VQV//Wszrr12CR98sJrtt6/H3/7WgiOOWMmLLxb66A2jdKmgTmIuc1T1C7yq9la9s4HncVEBBqlq/JdRDVIIxTMQ+FhE3vbrPwOuqWonVR1N/PhMrIZW1f8B3QPbXgntV1toXRf+0gZ2+AN8t8jJ3v0cWjaBq46DPr+ojCj63w+d9dqNF8Lhv6j0yTZ6tJubM3Ag/PGPq3nuuXIvX8v8+cqddzbgyisXcd99P3r5aqZNK+fuu1ua4jGMjaSGutEOAKap6gwJNdHzQN49F6jqIzgrsuf98pNUN5yRHLs0gokrK5VOirFT3W9K6aR490No2rhS6aR48UXYfHMYObI8TV7u5etPLXz77VV06lSX5s1r78CoYdQ0OY7xtBGRsZFlQIasjweeiqyfLSKfisjDftJ9XiiEyxxwXVzzgB+A7UTEXOYkzJy1sG1D57EgStsWUL8uNE2bxd2pHVQobJnW6bnDDrB6NWy/vaTJxcvrryfv0qUua9bAjz9mZS9iGEYMilBeUTerBZifMoLyy9C4PP2E/SOAf3rRvTjPLr1wcyTzFsKxEE5CbwbeAy4HLvRLvE8Ro9p8ucp5p77tVNjMT4D+6fZwZn/49ydwz3XQ3I+p7rIDXHUejBwFQ4e6Fg7AttvC7bfDc8/Bvfc2oEMHp3w6dhTuvrsBzz5bzuDBLdl6a6fd2rSpw/33t+L++5dRXm6zRw2j2iisXVs3qyUHDgXGq+p3AKr6naqWq2oF8ACwZw0cSSyF6A85CuihqquqTGlsFCfMgBe2hkVPQLnCytVwzgPwwofw9ACYN9ZNJi0vh8tvh/uehGHXwuzZTgZw221wzTVw990VTJ/eiIoKZwn34INrOffcNVx//VomTmwHQN26wtNPL+eqq8w1tWFsDBUVdVi9MvF4PCcQ6WYTkQ7eIwzA0cBnSRcYohCKZzpQHzDFkyAttt8wevgZdRvTaVFzLnkRlq6E/XvAJcdBwzbQaye4+gH4fiHsvRP89Qz4frXz1XbjjfDNN7DrrnDGGc6bwa9/XYc77ljK1Klr6d69Hqef3oS3317O73/fkvvvX8inn66ia9f6nHVWa/bdt5y33oqvZ6aQ1aVOyEWQyKxY+fh3+sXL94uXBynLsK1bvPjmoy6Olf/znd/Eyo+5Jd70O34GXAZaBOTxfjfDBMymQybTEDabnsBusfKJxIdKf2nV4fEF3Od/4y3Sc0OhPLfWTEZEpDHOP+UfI+JbRKSXK42ytG01SiEUz3Jggoi8SUT5ZOu5wMiOZgiX1m3KboOhbIGTPfgejDgD7vg17D8Axk9x8odHwpDz4a4L4aQT4LXXKvOZP99FE73ggsUMG1Y5H2n69HLuuqsVd9wxn1tvXbBO/vHHK7ntti3Yffe0iHKGYWSNqrB2TXKKR1WXA5unyU5KrIAcKYRxwUjgOuB9nCeD1GIkSC+pz2Rdu07ppPjvV1C3TqXSSfHK+9Cy2fpKB1x8nfbtYcSI9SfBPvXUctq3r8NTT60fZvSll5ax3XYNadasNGdUG0ZxIFSU18tqKUUK4STUTKfzwAIq6Ch1EVm/C6hFY2fV1qghrIx0drZtCSi0aeNaOSm6doW1a6FLl3pMnbo2Iq/r5fWZNatSvsUWdVm7Vlm50nzmGEa1USDBrrZiI28tHhF52v9O9Hbj6y35qsemwiRdy1wt5/JDoI63hN6uHZzZD8Z8DQPPhvr+s6NTO7j89/DmWOebrZHvJm/TBm6+Gd54A4YMaUHTpi6jZs2EQYNa8sYbK7n11na0bu0ekM02E4YMac/jjy9mzRqzajOMaqPiFE82SwmSz6628/zvL4HDYxYjYU5bs4j+PaHsehhzMbx3AVz7Chx9P2zXBb75F7z/EHw63I3z/OpCaNDAGRa89x58+SW89RYcfTTMnl3OjBkdGD26LWVlHZg+fS1HHbWA999fwdSp2zJ6dDe++aY75eVw0UXfFfrQDaO0UWClZLeUIKJ5itYlIqJVFJZNmkLRp08fHTt2bMY0YSehfQOZxjshbDF6Qws1gG0aTs1Yfhzj/9SP7dtD68YwYRYsX+03jIWtO0KHNjBxKiz5sVLeuTN06QKTJ8PClEc9ltO+PWy7bR2++qqC79bplom0aVOPHj0aMWPGambNShVQsybVtcE6TiQQe7BpvBPKatEmR/mD8eIbd/1rrLwP8c/EdnwRK2/G0kDByRAKVw1hp58h67XbVsVPL1w8OBCz/pLUOGg/VMdvlEaQHfsoT2V+36xjVxmnqrnaBRaUfI7xvC0izwIvquo3KaGfTdsPOAV4G3g0j3XaJJgSr8eYPtst6cyc6ZZ0vv0Wvv12w7Gb+fPXMn/+so2spWEY63CR4Got+VQ8hwC/B57yIQkW4WLz1MWFRRikqhMy7G8YhrFpoMCaKlOVLPmMx7MSuAe4xwd0awOsUNVFmfc0DMPYxFCyDI9ZmhTECNwHgZtbZULDMIxNFetqMwzDMPJGBbCy0JWoOUzx5IWyePGUeOulxS8ErGaOy92qLeSri4DBAfMD8rJQAfH+r2raqq02oJqb9VrYajIDIZuPsoC81w6x4ssGDoqV735xwIdbgFBY7x4BK7iQ1VyIjwN+1yAcWO15joqVB63Xrg+V8J7/TcDQppYbF+RzAulo/7tURJakLYtF5GsROStf9TEMwyhaUoonm6UEyadxQT//G/uJLCKb4/y33ZOvOhmGYRQtJapUsqFoutpUdYGI7FfoehiGYRQcM6fOH5GgRIZhGJsuFdTqiGWFCItQLUSks4i8LSKTReRzETnPy6/zjkYniMgbIrKll7cQkZdE5BOf/rRIXuU+/QQRGVmoYzIMw4jFxniKhrXA+ao6XkSaAePEmfncqqpXAojIucBVwJnAn4FJqnq4iLQFvhCRJ1V1NW7iaq/8VT3GLw2EjV9GxFs7TTtq22SqAxAw2An68CqL93MFzQPywDEb1aaQ/umCUVSfCURL/XW8ePwhuUVX3X3XeKu5o3khp3wgbL02/uZAne6LF7Ms3rowdX1Evtr4+GK13KqtZBSP74ab6/8vFZHJQEdVjXpabIK7ZPjfZiIiQFNgIbX6UhqGUauoxW+rklE8UUSkG7AbMMav3wCcDCwGfu6T3YWLdjoHN9nkOFVNebhsJCJjcZd2oKrm/vlkGIZRUyTc4hGRMmApzhHPWlXtIyKtgX/gZvuVAceq6g/JlRqmZMZ4UohIU+BZ4C+qugRAVS9X1c7Ak8DZPml/YAKwJdALuEtEUv1CXbwb8d8Cg0Vkm0BZA0RkrIiMnTdvXs0dlGEYRpSaGeP5uar2ioRQuAR4U1W7A2/69bxQUorHOxd9FnhSVZ+LSTIcOMb/Pw14Th1Tga+B7QFUdY7/nQ68A/HTnVV1qKr2UdU+bdu2TfRYDMMwgqRc5mSzVJ8jgcf8/8cgMAhWA5SM4vFjNQ8Bk1X1joi8eyTZEcAU//8b4ACfph3QA5guIq1EpKGXt8FFaQtE5DIMwygQybZ4FHhDRMaJyAAva5eawuJ/t0is7lVQSmM8fYGTgIkikorbcxlwuoj0wH0jzMBZtAFcBzwqIhMBAS5W1fki8lPgfhGpwCnegWkGCtUmZHUU9rEVsPz6d44+3KpDt4A85MNtSkAedEsVsnaL9+FWGyKK1mZUO8XKg/f22HifbzwTnw8B8fj28RZn0wbnbuG5eErg+QlZr5VVwzdeUuQ2xtPGj1mnGKqqQ9PS9FXVOSKyBTBKREJPdF4oGcWjqqNxCiSdVwLp5wAHx8jfh0CsW8MwjGIgN8Uzv6rQ15Hhhe9F5HlgT+A7EemgqnNFpAPw/UbUOCdKpqvNMAxjkyHlMiebpQpEpImf+4iINMF9kH+Gs/o9xSc7BXgxyUPIRMm0eAzDMDYZko1A2g543g2TUw8YrqqvichHwNMicjpuTPw3iZVYBaZ4DMMwig0lsUBw3np31xj5ArwBVr4xxWMYhlFsmHdqY2PJ2dptWbxfLEYETKUqfosAAA09SURBVH8A9s6xUoaRALlaI4at4HIrd/FrgXLPjBdnpGxMrLiglpbJdrUVHaZ4DMMwig1zEmoYhmHkHVM8hmEYRt5IucyppZjiMQzDKDasq80wDMPIK6Z4jPwT8uGWwaot5Mat28bWxRP0yTY5p2zMJ9umTVLXXyTeEo379qpGbvH+AwuKmVMbhmEYecfMqQ3DMIy8YV1thmEYRl6pAFYUuhI1hykewzCMYsM8FxiGYRh5x7rajKJg2fLwtm8bx8u71UhNInTMKXU4Gms8ZgVnxBOwRCvLPZhwUd5jNsZjGIZh5BUzpzYMwzDyio3xGIZhGHklwUBwxYgpHsMwjGKjlne11Sl0BQzDMIw0Ul1t2SxVICKdReRtEZksIp+LyHlefo2IzBaRCX45rGYOZkNKpsUjIp2BYTivZBXAUFUdIiLXAUd62ffAqao6R0RaAE8AXXDHeZuqPuLzOgW4wmd9vao+lt+jqYqQ76iF4V1mBazaynIsekJoQ8iirnlAXoT+r4xaQ1FaoiVJslZta4HzVXW8iDQDxkmleekgVb0tsZKypGQUD+GTd6uqXgkgIucCV+EC4P4ZmKSqh4tIW+ALEXkSaApcDfTBXd5xIjJSVX8owDEZhmFsSIKKR1XnAnP9/6UiMplc50EkTMl0tanqXFUd7/8vxblF7qiq0U/rJrhLhv9tJiKCUzYLcZeyPzBKVRd6ZTMKOCRPh2EYhlE1KeOCbJYcEJFuwG5Ayr332SLyqYg8LCKtEqh5VpSM4omSfvJE5AYRmQn8DtfiAbgL2AGYA0wEzlPVCpymnxnJbhYB7S8iA0RkrIiMnTdvXg0ciWEYRgDNcoE2qfeUXwbEZSciTYFngb/4D/Z7gW2AXrgW0e01ejwRSk7xxJw8VPVyVe0MPAmc7ZP2x41YbIk7sXeJSHNAYrLVGBmqOlRV+6hqn7Zt2yZ8JIZhGIkwP/We8svQ9AQiUh/33nxSVZ8DUNXvVLXcf5A/AOyZrwqXlOKJO3lpDAeO8f9PA55Tx1Tga2B7XAunc2SfTrhWkWEYRq3DDzc8BExW1Tsi8g6RZEcDn+WrTiWjeDKcvO6RZEcAU/z/b4ADfJp2QA9gOvA6cLCItPJ9mgd7mWEYRm2kL3ASsH+a6fQtIjJRRD4Ffg78NV8VKiWrttTJmygiKaPfy4DTRaQHzpx6Bs6iDeA64FERmYjrXrtYVecDeBPsj3y6a1U1g53yJsb8QlfAMIwkZ5Cq6mjihxheSaSAalAyiifXk6eqc3CtmbhtDwMPJ1c7wzCMJKndkeBKRvEYhmFsOtTuuAimeAzDMIqO2u2szRSPYRhG0WGKxzAMw8g71tVmZEGuYZ1zJ4PjzZA12n45FvFaQL4sx3xYmlPqWu/00TBywlo8hmEYRl4xqzbDMAwjr5hVm2EYhpFXrKvNMAzDyCvW4jEMwzDyirV4jKIhg6VYwKqtxVHf5lTC4nfax2+4LxBaO1M4bsMwqokZFxiGYRh5x7raDMMwjLxhXW2GYRhGXjHFYxiGYeQVs2ozDMMw8oq1eAxg3LiViEzya7MLVItm4U1t4sXbNJyaUwnj9wtYtY0N7DC2U075hwj5uTMfbsamSe22aqtT6AoYhmEY6aS62rJZqkZEDhGRL0RkqohcUiNVzgFr8RiGYRQdyXW1iUhd4G7gIGAW8JGIjFTVSZn3rDlM8WTN58tgxy8KXYsgZfHi8VLtHNsQDraQN6T69a8ORXHMecaOOXm6bnwWiRoX7AlMVdXpACIyAjgSMMVTAnyhqn0KXYl8ISJjN6XjBTvmTYXSOOZEjQs6AjMj67OAvZLKvDqY4jEMwyg65rwOVwRMhjagkYhEzX+GqurQyHpcv4FWv24bjykewzCMIkNVD0kwu1lA58h6J2BOgvnnjFm1Zc/QqpPUKja14wU75k2FTe2YPwK6i8hWItIAOB4YWcgKiWpBW1yGYRhGDSMihwGDgbrAw6p6Q0HrY4rHMAzDyCebbFebiDQSkQ9F5BMR+VxE/ublD3nZpyLyjIg09fIzRWSiiEwQkdEi0jOS16V+YtYXItK/UMdUFbkec2S/X4uIikifiKzoj7ka1/hUEZnnr/EEETkjktcpIvKVX04p1DFVRXWusYgcKyKTfPrhEXmtPGYRGRS5xl+KyKJIXiVxzCWPqm6SC87So6n/Xx8YA+wNNI+kuQO4xP+Pyo8AXvP/ewKfAA2BrYBpQN1CH18Sx+zXmwHvAh8AfUrpmKtxjU8F7orJpzUw3f+28v9bFfr4Ejrm7sDHqeMBtqjtx5y27zm4rqeSOuZSXzbZFo86lvnV+n5RVV0CICICbIY3O0zJPU2oNEc8Ehih+v/tnWuIVVUUx39/rcxAy3IIlXLCsggL7V2KKIghkkUWGVJpYVSK0ftLROWXKKiwpCIj6kOWleUrasxnWFrRw0cmaZmUmuGrByZlqw973TzZnWnObbxzz8z6wWH22Wfvffb/njNn3b3vPmvZPjP7BthAemGr5sir2ZkCPAz8lskrhOYK9ZbjYmCBme00s13AAqAlVx21GBVongBMc12Y2XbPb8uas1wNzPB0YTQXnXZreCC5kpD0GbCddMOt9PzngW3AacATmfITJW0kPYgne3a5l7N6VaH7FZFHs6QBwAlmNu+gZgqjOe81BkZnpmZKS1ALoxdya+4L9JW0XNIKSaUHbVvWXKrTmzRiX+RZhdJcZNq14TGz/WbWn7Su/TxJ/Tx/PNATWAdclSk/zcz6APcA93p2zb2c1RTN1SypA/AYcEeZZgqjOec1ngvUm9mZwLvAC55fGL2QW/NhpOm2IaRv/9MlHUPb1lxiDPCame33/UJpLjLt2vCUMLPdwBIyw2q/GV8BRpep8jJwmadr7uWs5tAMzV2AfsASSZtIc+ZzfIFB4TQ35xqb2Q4z2+eHnwXO9nTh9EKz7+vvgNlm9rtPm64nGaK2rLnEGA5Ms0FBNReRdmt4JNX5NzskdQaGAeslnex5Ai4BvvT9UzLVRwJfeXoOMEZSJ0knkf5pP6yOinzk0Wxme8ysu5nVm1k9aXHBKDP7mIJoruAa98hUH0X6lgzwDjBcUjdJ3YDhnldz5NUMvAkM9WPdSVNvX9O2NSPpVNICgg8yTRVGc9Fpzy5zegAvKLkM7wDMBOYD70nqShp2fw7c7OUnSRpG8ty3C7gOwMzWSppJ8vT6BzAxM3SvNfJqLkuBNOfVO1nSKJKmnaRVbpjZTklTSG+AAzxoZjurpiIfeTWXHrZfAPuBu8xsB0Ab1gxpWvFlM/t7Kq1g17nQxAukQRAEQVVpt1NtQRAEQesQhicIgiCoKmF4giAIgqoShicIgiCoKmF4giAIgqoShicIgiCoKmF4gppC0vuN5HeWtNR9cvWU9FrOdsdJerJletnoOTb5S5gH518paZ2kxYf4/JI0VSlcxSpJZ3l+naS3D+W5gyAPYXiCmsLMLmrk0PXALPfJtcXMrqhmv/4nNwC3mNnQbKakln6BewTJi8QpwI3AUwBm9iOwVdLAFj5fEFREGJ6gppD0SyOHxgKzvUy9pDWeHidplqS3lYJ3PZxpa7xSoK+lwMBMfp2k1yV95NtAz58q6T5PXyxpmaQOTZQ/TlKDpE8lPUMZJ5Pe3iDgaUmPeH9flTQXaPBRyiOS1igFGrzK6w3xEd5M1/CQpLFKAc9WS+pT5jO6FHjRwwSsAI7JuAF60z/DIGh98gbwiS22Q7kBv5TJOwLYltmvB9Z4ehzJt9jRwJHAtyRHjz2AzUCd11+OB3kDXgIGefpEYJ2njwLWknyXrQf6/Ef5qcB9nh5J8mTcvUz/l3AgiN44kjPKY31/NCnuS0fgeO9zD5K36N2e7gR8DzzgdW4FHi9znnmlfvr+wsx5ewGrW/v6xhabmbVrX21BcehOegg3xkIz2wPgPsd6e50llqaZkPQKyQEmJCeSpyffkQB0ldTFzH6WNIEUcfU2M9vYVHlgMHA5gJnNl7SrmXoW2AEfYIOAGZZ83f3go7NzgZ+Aj8xsq/d/I9DgdVbjjj0Poim3/ttJ4QGCoNUJwxMUgb2k0Uxj7Muk93Pgvm7MEWEH4EIz21vm2BnADv75kC5b3g1RJc4Of80200S5rK4/M/t/Uv5/tym3/keSPscgaHXiN56g5rEUhrijpKaMz8GsBIb47zCHA1dmjjUAk0o7kvr7396kwHcDgBGSzm+qPGlkNNbzRpDc7OdlGSnwXkdJdaRRVKUhJuYA1/rvRhcAe0ojJtJob02F7QZBixKGJygKDaRpqWbhD9z7SfFW3gU+yRyeDJzjS46/AG5SGr48B9xpZltIK9Gmu7H7V3lv5wFgsKRPSLFbNleg6w1gFclt/yLgbjPbVkE7AG+Rfu/aQApkd0vm2FBSqIAgaHUiLEJQCCQNAG43s2tauy9FRNIy4FIfPQZBqxIjnqAQmNmnwGIP9hXkwKfwHg2jE9QKMeIJgiAIqkqMeIIgCIKqEoYnCIIgqCpheIIgCIKqEoYnCIIgqCpheIIgCIKq8hcOChrO0/lRgQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# from ocean/field_table\n",
    "damp_table='''\n",
    "\"rayleigh_damp_table\",\"ocean_mod\",\"rayleigh_damp_table\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2389,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2389,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2389,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2389,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2389,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2390,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2390,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2390,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2390,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2390,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2391,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2391,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2391,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2391,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2391,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2392,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2392,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2392,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2392,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2392,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2393,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2393,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2393,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2393,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2393,ktable_1=1,ktable_2=75,rayleigh_damp_table=86400\"\n",
    "'''\n",
    "\n",
    "# subtract 1 to index from 0\n",
    "ii = [ int(i)-1 for i in re.findall('itable=(\\d+)', damp_table) ]\n",
    "jj = [ int(j)-1 for j in re.findall('jtable=(\\d+)', damp_table) ]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "fig,ax = plt.subplots()\n",
    "plt.imshow(depth, vmin=0, vmax=200, origin='lower', cmap=plt.cm.jet)\n",
    "plt.colorbar(ax=ax)\n",
    "plt.scatter(ii,jj, facecolors='none', edgecolors='w')\n",
    "plt.xlim(imin,imax)\n",
    "plt.ylim(jmin,jmax)\n",
    "plt.title(fixedbathyfile)\n",
    "plt.xlabel('i (indexed from 0)')\n",
    "plt.ylabel('j (indexed from 0)');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# from ocean/field_table\n",
    "damp_table='''\n",
    "\"rayleigh_damp_table\",\"ocean_mod\",\"rayleigh_damp_table\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3335,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3336,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3337,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3338,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3344,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=86400\"\n",
    "/\n",
    "'''\n",
    "\n",
    "# subtract 1 to index from 0\n",
    "ii = [ int(i)-1 for i in re.findall('itable=(\\d+)', damp_table) ]\n",
    "jj = [ int(j)-1 for j in re.findall('jtable=(\\d+)', damp_table) ]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "fig,ax = plt.subplots()\n",
    "plt.imshow(depth, vmin=0, vmax=200, origin='lower', cmap=plt.cm.jet)\n",
    "plt.colorbar(ax=ax)\n",
    "plt.scatter(ii,jj, facecolors='none', edgecolors='r')\n",
    "plt.xlim(imin,imax)\n",
    "plt.ylim(jmin,jmax)\n",
    "plt.title(fixedbathyfile)\n",
    "plt.xlabel('i (indexed from 0)')\n",
    "plt.ylabel('j (indexed from 0)');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# from ocean/field_table\n",
    "damp_table='''\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3335,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3336,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3337,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3338,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3344,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3345,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3346,jtable=2380,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3335,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3336,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3337,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3338,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3344,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3345,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3346,jtable=2381,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3335,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3336,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3337,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3338,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3344,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3345,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3346,jtable=2382,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3335,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3336,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3337,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3338,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3339,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3340,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3341,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3342,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3343,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "\"rayleigh\",\"KaraStr\",\"itable=3344,jtable=2383,ktable_1=1,ktable_2=22,rayleigh_damp_table=5400\"\n",
    "'''\n",
    "\n",
    "# subtract 1 to index from 0\n",
    "ii = [ int(i)-1 for i in re.findall('itable=(\\d+)', damp_table) ]\n",
    "jj = [ int(j)-1 for j in re.findall('jtable=(\\d+)', damp_table) ]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "fig,ax = plt.subplots()\n",
    "plt.imshow(depth, vmin=0, vmax=200, origin='lower', cmap=plt.cm.jet)\n",
    "plt.colorbar(ax=ax)\n",
    "plt.scatter(ii,jj, facecolors='none', edgecolors='r')\n",
    "plt.xlim(imin,imax)\n",
    "plt.ylim(jmin,jmax)\n",
    "plt.title(fixedbathyfile)\n",
    "plt.xlabel('i (indexed from 0)')\n",
    "plt.ylabel('j (indexed from 0)');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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