notebooks/contributed/NEUWAVE-12/NEUWAVE_12_Examples_Installing_Plugins_Texture_exercise.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bErEbPpelXVq"
   },
   "source": [
    "## Texture plugin analysis example\n",
    "\n",
    "This exercise shows how to use the texture plugin, CrysText, together with NCrystal. In this example, the modifications to the coherent elastic cross-section are included in the NCrystal plugin.\n",
    "\n",
    "The coherent scattering cross-section is given by,\n",
    "\\begin{equation}\n",
    "\\sigma_{\\textrm{coh}}^{\\textrm{el}}(\\lambda)=\\dfrac{\\lambda^{2}}{2V}\\sum_{hkl}^{\\lambda\\leq 2d_{hkl}}d_{hkl}|F_{hkl}|^{2}P_{hkl}(\\lambda,d_{hkl}),\n",
    "\\end{equation}\n",
    "where $P_{hkl}(\\lambda,d_{hkl})$ is the modified\n",
    "March-Dollase preferred orientation distribution function, which uses an axially symmetric orientation distribution around the beam\n",
    "direction. The calculation is perferormed as described in Sato et al. [1] and is given by\n",
    "\\begin{equation}\n",
    "P_{hkl}(\\lambda,d_{hkl})=\\frac{1}{2\\pi}\\int^{2\\pi}_0 \\left( R^2B_{hkl}^2 +\\frac{1-B_{hkl}^2}{R}\\right)^{-3/2}d\\phi.\n",
    "\\end{equation}\n",
    "This plugin should only be used to generate cross-sections, and not to sample scattering events.\n",
    "\n",
    "[1] H. Sato, T. Kamiyama, and Y. Kiyanagi, Materials Transactions 52 (2011) 1294\n",
    ", http://dx.doi.org/10.2320/matertrans.M2010328"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TyceOhIqqr2e"
   },
   "source": [
    "## Preamble\n",
    "Install NCrystal with pip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9OHZoldyGwnu",
    "outputId": "8e4e957a-fd72-490f-aee5-dfa01a2e6a5a"
   },
   "outputs": [],
   "source": [
    "#By default we only do pip installs on Google Colab, but you\n",
    "#can set the variable in the next line to True if you need it:\n",
    "always_do_pip_installs = False\n",
    "try:\n",
    "    import google.colab as google_colab\n",
    "except ModuleNotFoundError:\n",
    "    google_colab=None#not on google colab\n",
    "if always_do_pip_installs or google_colab:\n",
    "    from importlib.util import find_spec as _fs\n",
    "    if not _fs('NCrystal'):\n",
    "        %pip -q install ncrystal ipympl numpy pandas spglib matplotlib pickleshare\n",
    "#enable inline and interactive matplotlib plots:\n",
    "if google_colab:\n",
    "    google_colab.output.enable_custom_widget_manager()\n",
    "%matplotlib ipympl\n",
    "import matplotlib\n",
    "matplotlib.rcParams.update({\"figure.autolayout\": True})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2LdJfxydrCjl"
   },
   "source": [
    "Get the plugin CrysText and other dependencies. The plugin is available in the HighNESS repository, https://github.com/highness-eu/ncplugin-CrysText."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Ak4QdkAfH3Fx",
    "outputId": "dd55b7ea-8007-450e-b4ed-473b5c3720d3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'ncplugin-CrysText'...\n",
      "remote: Enumerating objects: 224, done.\u001b[K\n",
      "remote: Counting objects: 100% (224/224), done.\u001b[K\n",
      "remote: Compressing objects: 100% (117/117), done.\u001b[K\n",
      "remote: Total 224 (delta 106), reused 190 (delta 96), pack-reused 0 (from 0)\u001b[K\n",
      "Receiving objects: 100% (224/224), 71.62 KiB | 1.94 MiB/s, done.\n",
      "Resolving deltas: 100% (106/106), done.\n",
      "\u001b[33mCMake Warning (dev) at /some/where/venv/lib/python3.12/site-packages/NCrystal/ncrystal_pyinst_data/lib/cmake/NCrystal/NCrystalTargets.cmake:61 (add_library):\n",
      "  ADD_LIBRARY called with SHARED option but the target platform does not\n",
      "  support dynamic linking.  Building a STATIC library instead.  This may lead\n",
      "  to problems.\n",
      "Call Stack (most recent call first):\n",
      "  /some/where/venv/lib/python3.12/site-packages/NCrystal/ncrystal_pyinst_data/lib/cmake/NCrystal/NCrystalConfig.cmake:108 (include)\n",
      "  CMakeLists.txt:12 (find_package)\n",
      "This warning is for project developers.  Use -Wno-dev to suppress it.\n",
      "\u001b[0m\n",
      "-- The CXX compiler identification is GNU 13.2.0\n",
      "-- Detecting CXX compiler ABI info\n",
      "-- Detecting CXX compiler ABI info - done\n",
      "-- Check for working CXX compiler: /usr/bin/c++ - skipped\n",
      "-- Detecting CXX compile features\n",
      "-- Detecting CXX compile features - done\n",
      "-- Performing Test COMPILER_SUPPORTS_MAXERRORS\n",
      "-- Performing Test COMPILER_SUPPORTS_MAXERRORS - Success\n",
      "\u001b[0m----> Will compile C++ library from sources in src/ and include/\u001b[0m\n",
      "\u001b[0m----> Will compile app_simpletest/main.cc as ncplugin_simpletest command\u001b[0m\n",
      "\u001b[0m----> Will install python module files as module named ncplugin\u001b[0m\n",
      "\u001b[0m----> Will install scripts/dumpexample as ncplugin_dumpexample command\u001b[0m\n",
      "\u001b[0m----> Will install scripts/helloworld as ncplugin_helloworld command\u001b[0m\n",
      "\u001b[0m----> Will install scripts/plotscat as ncplugin_plotscat command\u001b[0m\n",
      "\u001b[0m----> Will install scripts/plotviancrystal as ncplugin_plotviancrystal command\u001b[0m\n",
      "\u001b[0m----> Will install scripts/plotxs as ncplugin_plotxs command\u001b[0m\n",
      "\u001b[0m----> Will install custom.ncmat to be available as ncplugin/custom.ncmat\u001b[0m\n",
      "\u001b[0m----> Will install ncplugin-CrysText_Al_sg225.ncmat to be available as ncplugin-CrysText_Al_sg225.ncmat\u001b[0m\n",
      "\u001b[0m----> Will install ncplugin-CrysText_Al_sg225_ver.ncmat to be available as ncplugin-CrysText_Al_sg225_ver.ncmat\u001b[0m\n",
      "\u001b[0m----> Will install ncplugin-CrysText_Zr_sg194.ncmat to be available as ncplugin-CrysText_Zr_sg194.ncmat\u001b[0m\n",
      "\u001b[0m----> Will install ncplugin-CrysText_Zr_sg194_ver.ncmat to be available as ncplugin-CrysText_Zr_sg194_ver.ncmat\u001b[0m\n",
      "-- Configuring done (0.5s)\n",
      "-- Generating done (0.0s)\n",
      "-- Build files have been written to: /some/where/ncplugin-CrysText/build\n",
      "[ 10%] \u001b[32mBuilding CXX object CMakeFiles/pluginlib.dir/src/NCCrystallineTexture.cc.o\u001b[0m\n",
      "[ 20%] \u001b[32mBuilding CXX object CMakeFiles/pluginlib.dir/src/NCCrystallineTextureFactory.cc.o\u001b[0m\n",
      "[ 30%] \u001b[32mBuilding CXX object CMakeFiles/pluginlib.dir/src/NCPhysicsModel.cc.o\u001b[0m\n",
      "[ 40%] \u001b[32mBuilding CXX object CMakeFiles/pluginlib.dir/src/NCPluginBoilerPlate.cc.o\u001b[0m\n",
      "[ 50%] \u001b[32m\u001b[1mLinking CXX shared library libNCPlugin_CrysText.so\u001b[0m\n",
      "[ 50%] Built target pluginlib\n",
      "[ 60%] \u001b[32mBuilding CXX object testcode/CMakeFiles/testlib.dir/src/NCExtraTestUtils.cc.o\u001b[0m\n",
      "[ 70%] \u001b[32mBuilding CXX object testcode/CMakeFiles/testlib.dir/src/NCForPython.cc.o\u001b[0m\n",
      "[ 80%] \u001b[32m\u001b[1mLinking CXX shared library libNCPluginTestCode_CrysText.so\u001b[0m\n",
      "[ 80%] Built target testlib\n",
      "[ 90%] \u001b[32mBuilding CXX object testcode/CMakeFiles/app_simpletest.dir/app_simpletest/main.cc.o\u001b[0m\n",
      "[100%] \u001b[32m\u001b[1mLinking CXX executable ncplugin_simpletest\u001b[0m\n",
      "[100%] Built target app_simpletest\n",
      "Using plugin from file: ./ncplugin-CrysText/build/libNCPlugin_CrysText.so\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pathlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def find_pluginlib():\n",
    "    for pl in pathlib.Path(\"./ncplugin-CrysText/build/\").absolute().glob(\"**/lib*NCPlugin_CrysText*\"):\n",
    "        return pl\n",
    "pl = find_pluginlib()\n",
    "if not pl:\n",
    "  !git clone \"https://github.com/highness-eu/ncplugin-CrysText.git\"\n",
    "  !mkdir ncplugin-CrysText/build\n",
    "  %cd -q ncplugin-CrysText/build\n",
    "  !cmake ../ && make\n",
    "  %cd -q ../../\n",
    "  pl = find_pluginlib()\n",
    "assert pl and pl.is_file()\n",
    "print(f\"Using plugin from file: ./{pl.relative_to(pathlib.Path('.').absolute())}\")\n",
    "if (str(pl)+':') not in os.environ.get('NCRYSTAL_PLUGIN_LIST',''):\n",
    "  os.environ['NCRYSTAL_PLUGIN_LIST']=str(pl)+':'+os.environ.get('NCRYSTAL_PLUGIN_LIST','')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Pdmtp2AFrMHT"
   },
   "source": [
    "Check that the plugin is installed. It appears at the end of the list under the name `CrysText`. Also note that we only `import NCrystal` *after* the plugin has been compiled and added to `NCRYSTAL_PLUGIN_LIST`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Tt0jr9agKU1j",
    "outputId": "95eec0b5-1b46-4088-923c-279dfb4c3c22"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests completed succesfully\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[('stddatasrc', '', 'builtin'),\n",
       " ('stdscat', '', 'builtin'),\n",
       " ('stdmpscat', '', 'builtin'),\n",
       " ('stdexpscat', '', 'builtin'),\n",
       " ('stdlaz', '', 'builtin'),\n",
       " ('stdabs', '', 'builtin'),\n",
       " ('stdncmat', '', 'builtin'),\n",
       " ('stdquick', '', 'builtin'),\n",
       " ('CrysText',\n",
       "  '/some/where/ncplugin-CrysText/build/libNCPlugin_CrysText.so',\n",
       "  'dynamic')]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#always import NCrystal:\n",
    "import NCrystal as NC\n",
    "assert NC.version_num >=  3009007, \"too old NCrystal found\"\n",
    "NC.test() #< quick unit test that installation works\n",
    "NC.browsePlugins()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Pnyjm3rzSPy4"
   },
   "source": [
    "Let's create a file and set the parameters of the model.\n",
    "\n",
    "This is done by taking an existing file and adding the relevant section for the new physics through using \"c.set_custom_section_data()\".\n",
    "The name of the pluggin is `CRYSTEXT` followed by the data used by the model. The `CRYSTEXT` plugin currently supports two March-Dollase functions with a given weight.\n",
    "\n",
    "On each line, the first three numbers represent the hkl values of the preferred orientation axis, the fourth number is $R$, the degree of anistotropy, and the fifth is the weight. The data is added to the section called `@CUSTOM_CRYSTEXT`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nvKEFDThSOGq",
    "outputId": "2251ba37-4980-43d7-c924-f1a1a8aa8fc2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NCMAT v7\n",
      "# Autogenerated by NCMATComposer\n",
      "#\n",
      "# Zr (hexagonal, SG-194)\n",
      "#\n",
      "# Atoms per unit cell: 2xZr\n",
      "#\n",
      "# NOTICE: crystal structure was verified with spglib to be self-consistent.\n",
      "#\n",
      "@CELL\n",
      "  lengths 3.232 !! 5.147\n",
      "  angles 90 90 120\n",
      "@SPACEGROUP\n",
      "  194\n",
      "@ATOMPOSITIONS\n",
      "  Zr 1/3 2/3 1/4\n",
      "  Zr 2/3 1/3 3/4\n",
      "@CUSTOM_CRYSTEXT\n",
      "  0  0  2  0.465 0.5\n",
      "  0  0  2  0.465 0.5\n",
      "@DYNINFO\n",
      "  # Transferred from \"Zr\" in existing NCrystal.DynamicInfo object\n",
      "  element Zr\n",
      "  fraction 1\n",
      "  type vdos\n",
      "  vdos_egrid .00188884 .0229022\n",
      "  vdos_density .00580803 .00699617 .00673608 .00416859 .00354729 .00362673\n",
      "     .00450489 .00710242 .00970558 .00996095 .0104084 .011033 .0126313 .0150165\n",
      "     .0172456 .019314 .0210789 .0210557 .0197406 .0180921 .0163888 .0143851\n",
      "     .0123014 .00998849 .00884003 .00879537 .0107318 .0140536 .019036 .0230005\n",
      "     .0265534 .0292249 .0303077 .0292462 .0247515 .0193833 .0153172 .0133485\n",
      "     .0156425 .0187844 .0231609 .0271647 .0302139 .0328087 .0348181 .0364424\n",
      "     .0379672 .039688 .0414352 .044429 .0478959 .0498049 .0492414 .0470342\n",
      "     .0446157 .0427659 .0419047 .0427471 .0444864 .0472776 .0501909 .0534146\n",
      "     .0540577 .0531831 .0521805 .05084 .0493318 .0484803 .0509086 .0569028\n",
      "     .0639763 .0682031 .068871 .0660106 .0622962 .0596912 .0592903 .0603288\n",
      "     .0627987 .0658798 .0685178 .0697241 .0703695 .0727463 .0790771 .0968184\n",
      "     .113115 .124957 .127758 .122055 .110556 .0996503 .0954017 .0958222 .0984303\n",
      "     .0985671 .0982696 .0981045 .100929 .104909 .108726 .115628 .121804 .125481\n",
      "     .12687 .125839 .122386 .119039 .115573 .113868 .117997 .133552 .147816\n",
      "     .165521 .177716 .188421 .194453 .197305 .193718 .187683 .182099 .183173\n",
      "     .189289 .195179 .202414 .21045 .218308 .224897 .227976 .228711 .226566\n",
      "     .219427 .211762 .208102 .211443 .224432 .242393 .263302 .281325 .292609\n",
      "     .301068 .308877 .314338 .322721 .329456 .346892 .363873 .375891 .381396\n",
      "     .384346 .386425 .389664 .395931 .406427 .420399 .437229 .457655 .484352\n",
      "     .512755 .541288 .563169 .576575 .572144 .56488 .570284 .599935 .663796\n",
      "     .720607 .765635 .78989 .807288 .83767 .875204 .929759 .927105 .912959 .871193\n",
      "     .813548 .759869 .713165 .708796 .728073 .754341 .771276 .764967 .733441\n",
      "     .674178 .618218 .607003 .607395 .640065 .661562 .67982 .695986 .721588\n",
      "     .746366 .765061 .761083 .74531 .706098 .676575 .656939 .650975 .649836\n",
      "     .651191 .654853 .660397 .672543 .687551 .712527 .742315 .759301 .756364\n",
      "     .748446 .7264 .71521 .714059 .713121 .711415 .707343 .681262 .646836 .603239\n",
      "     .575081 .551671 .52552 .515934 .520437 .524916 .520023 .511656 .510493\n",
      "     .518587 .532605 .539476 .541203 .53496 .529079 .51375 .49134 .459665 .427226\n",
      "     .399867 .395046 .392774 .392078 .392698 .393876 .397295 .40659 .419055\n",
      "     .428605 .431295 .421825 .406305 .388817 .364669 .353362 .349955 .367592\n",
      "     .388811 .404349 .405807 .398091 .390883 .391361 .401539 .417827 .425372\n",
      "     .415352 .399884 .384165 .373929 .365394 .357565 .348323 .335086 .3241 .315111\n",
      "     .304702 .298184 .295539 .298036 .303408 .309785 .310462 .308415 .308323\n",
      "     .312885 .322326 .334832 .356606 .382442 .415024 .451277 .477698 .486236\n",
      "     .488053 .490273 .498539 .526486 .554176 .572218 .575891 .578697 .586213\n",
      "     .597965 .615529 .648221 .70698 .779849 .859885 .914359 .962748 .979679\n",
      "     .990444 1 .998659 .987706 .974908 .953319 .913369 .8662 .805871 .757883\n",
      "     .704897 .659215 .63038 .60789 .578812 .550989 .525887 .511623 .494841 .46662\n",
      "     .433422 .400712 .375473 .36041 .350005 .337785 .321476 .30235 .282184 .256947\n",
      "     .216511 .170844 .128736 .0960426 .0624465 .0365649 .0193463 .0114496\n",
      "     .00615589 .00277092 .000477786 0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "c=NC.NCMATComposer('Zr_sg194.ncmat')\n",
    "# Set hkl, R and fraction\n",
    "c.set_custom_section_data(\"CRYSTEXT\", \" 0  0  2  0.465 0.5 \\n 0  0  2  0.465 0.5 \")\n",
    "c.write('Zr_sg225-CrysText.ncmat')\n",
    "print( pathlib.Path('Zr_sg225-CrysText.ncmat').read_text())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2RXHHs59siVH"
   },
   "source": [
    "\n",
    "\n",
    "Compare against the ideal Zr cross-seciton.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 604,
     "referenced_widgets": [
      "3fded6f30d41401285c70d79619c00ed",
      "56abedffdc6043a3b3e69a05ea6fdf2b",
      "dd386ac0b9d14840ab8db7817b6a095c",
      "eafcd0a441cc485d80d29eaf1423d4ca"
     ]
    },
    "id": "j0U_Slqd5BT8",
    "outputId": "1204e19b-500d-489a-94a6-4dc13b07a706"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NCrystal WARNING: Loading NCMAT data which has @CUSTOM_ section(s). This is OK if intended.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0a0ee00c58664878be21cf9f0a6702ab",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wl = np.linspace(0.5, 6, 100)\n",
    "\n",
    "# Definition of the material requires the single-crystal information to be defined, however it is not used.\n",
    "cfg1 = 'Zr_sg225-CrysText.ncmat;dir1=@crys_hkl:1,1,1@lab:1,0,0;dir2=@crys_hkl:0,0,2@lab:0,1,0;mos=1deg;dirtol=180deg'\n",
    "pc = NC.createScatter( cfg1)\n",
    "pc_a=NC.createAbsorption(cfg1)\n",
    "xs1 = pc.crossSection(NC.wl2ekin(wl),direction=(0,0,1))+pc_a.xsect(wl=wl)\n",
    "\n",
    "cfg2 = 'Zr_sg194.ncmat'\n",
    "pc = NC.createScatter( cfg2)\n",
    "pc_a=NC.createAbsorption(cfg2)\n",
    "xs2 = pc.xsect(wl=wl)+pc_a.xsect(wl=wl)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(wl, xs1, 'r-', label='RT with texture')\n",
    "plt.plot(wl, xs2, 'b-', label='RT')\n",
    "plt.legend()\n",
    "plt.yscale(\"log\")\n",
    "plt.xlabel('Wavelength [Å]')\n",
    "plt.ylabel('Micro total cross section [b/atom]')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4Ksf9hO36gZs"
   },
   "source": [
    "## Exercise #1\n",
    "Compare the total cross section data for Al, using the plugin, with experimental data from the IAEA database [EXFOR](https://www-nds.iaea.org/exfor/). We will access the experimental data using the [Web API](https://www-nds.iaea.org/exfor/x4guide/API/). Can you adjust the parameters of the model to match the measured data?\n",
    "\n",
    "Modify this cell to compare the experimental data with NCrystal results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 586,
     "referenced_widgets": [
      "cdf70d2dd48b48b19d6f81d30c767682",
      "a103fe465c9f4fb2a5d32e2d84d6a04f",
      "db68d16262494036b85d2df4775ba28c",
      "b09372e6e45f4d36b0827e635ce040a9"
     ]
    },
    "id": "GnpyHXm_JSRn",
    "outputId": "4520ed2b-ba4b-4cad-90b8-b90de69612e6"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b745806395c64fcab9f1f07a793aaf54",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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p4H/2cWEhLiKrdhw4aaMWOGatasqXnz5umRRx5xqz8vKlasqIiICK1evVobN25U165dFRUVpX79+unnn3/W/v37s/QApt8qTedwOLLMRrXaypUrdfDgwSy9PX379tWNN96o1atXu/Zmbdasmet8aGioqlatqvj4y0MNpkyZopCQEL366quuaz7++GOFh4dr8+bNuv7661WjRo0sM0n/+9//Kjg4WEFBQfL395e/v7/HazLffk1KStItt9yiChUqaMGCBVleu9w4ffq0Bg0apLFjx8oYo8GDB6tTp06u3rzcvDZFJSkpSVu3blVMTIwrbKalpckYo1KlSunbb7/VTTfdpJo1a7q9T5LUtGlTffHFF5KklJQUjR49WgsWLHDN3G/VqpViY2P1+uuvq0uXLqpRo4YuXryoM2fOuD33jO9DjRo13GZnp59PP5fR3Llz9cgjj+izzz674gQXAPZFD2A+1AwJ0sQ7W8r/z9tX/g6HXr6zhWqGBBVKfX/88Yf+85//6I033lBsbKzra8eOHQoLC9OcOXNyVU61atXUsGFD11du+fn5afTo0Ro7dqxSUqy9zZ2+B2lO5TZo0EABAQH6/vvvXccuXbqkLVu2uP3y7dSpk1atWqW1a9eqc+fOqly5spo2baoJEyaoZs2aOfbkFJWRI0dq586dbu+jJP3zn//UzJkzJcnV05lxPOKpU6d08uRJ1a1bV9LlsXKZZ86mv5bpITYyMlLfffed2zXLly9XZGSkJCkgIEBt27Z1uyYtLU3fffed6xrpcs9ft27dFBAQoEWLFqlMmTL5eu7Dhg1TjRo1NHr0aI0ZM0a1atVyW9omN69NUQkODtauXbvc2vLoo4+qcePGio2NdY1b7dixY5Zxoz///LPrfbp06ZIuXbrk8b1Kf5/atm2r0qVLu70P+/btU3x8vOt9iIyM1K5du9x6qJcvX67g4GC3n4E5c+Zo4MCBmjNnTqEuFQWgBLBqNoqvKOpZwBsOnCz0WcALFiwwAQEB5syZM1nOPfvss6Zdu3bGmMKdBXzp0iVTq1Yt10zb+fPnm8aNG7vOe5r12rhxYzN//nzX9506dTKDBg0yCQkJJiEhwcTGxpq+ffuaMmXKmL179+b4HEaMGGHCwsLMkiVLzI8//mgeeOABU6lSJXPq1CnXNQsXLjT+/v6mRo0abo/z9/c3f/3rX93Kq1u3rvnnP//pdiwiIsI8//zz2b4uSUlJJiYmxsTExBhJZvLkySYmJsYcOXLEdc3vv/9uYmJizDfffGMkmblz55qYmBiTkJCQbbnyMNP19ttvN82bNzfff/+92bVrl7n11ltNs2bNXDN8v/vuO+NwOMy4cePMzz//bLZt22a6d+9u6tata86du/z/8dChQ6Zs2bLmmWeeMXv27DFTpkwx/v7+ZunSpa565s6dawIDA82sWbPMTz/9ZP72t7+ZihUrumabOp1Oc91115mWLVuaAwcOuN67hIQE88cff2T7nDKbP3++CQgIMLt27XId27lzpwkICDCff/55nl6bm266ybz99ts51rd//34TExNj/v73v5tGjRq53reMM2Z//PFHExMTY3r37m06d+7suiY7nmYB//DDD6ZUqVJmwoQJZv/+/eaTTz4xZcuWNR9//LHrmk6dOpnmzZubVatWmUOHDpmZM2eaMmXKmHfffdd1zaOPPmrq1KljVq5cabZu3WoiIyNNZGSk6/wff/xhWrRoYbp162ZiY2PN0qVLTWhoqBk1apTrmk8++cSUKlXKTJkyxe198vS5YQyzgIHirqCzgAmAxcCtt95qevbs6fHc5s2bjSSzY8eOQg2AxhgzceJEExoaapKTk83MmTNNxr8fDh48aCS5/YKXZGbOnOn6vlOnTkaS66tSpUqmU6dOZuXKla5rsnsOKSkpZtiwYaZq1aoel4Ex5nL4cjgcpl+/fq5jCxYsMJLMe++953ZtfgJgetsyfz3wwAOua9Jfl8xfOZXrKeQ4nU7z0EMPmYoVK5rKlSubPn36mPj4eLdr5syZY1q3bm3KlStnQkNDzW233Wb27NmTpc3XXHONCQgIMFdddZXb+5Hu7bffNnXq1DEBAQHm2muvNZs2bbric5Zk4uLiXNfVrVs32+f422+/mWrVqmVZtsgYYyZMmGCqVatmfvvtt1y/NjnVlS7z/7Xs2uzpmuxkt6TMV199ZVq0aGECAwNNkyZNzL///W+38wkJCebBBx80YWFhpkyZMqZx48bmjTfeMGlpaa5rUlJSzODBg02lSpVM2bJlTZ8+fbL80XD48GHTo0cPExQUZKpWrWqeeuopt6V4snvOGf9/ZlRcPw8BXFbQAOgwpgjWESlCiYmJCgkJcS1VkdH58+cVFxen+vXr5/s2FjzbtGmTIiMj9dtvvxXJDE34jnPnzqlKlSpasmRJlok28F18HgLFW055JzeYBIIC+eOPP3T48GG99tprioiIIPzZ0KpVq3TTTTcR/gCgGGESCApk9+7datWqlRISEvSf//zH282BF/Tq1UvffPONt5sBAMgDegBRINdcc43OnSu89Q8BAID16AEEAACwGQIgAACAzdgyAJawic8AkGd8DgL2ZqsAmL59FWPWANhd+udgfrb1A1D82WoSiL+/vypWrOjaTqls2bJy/LmdGwDYgTFG586d04kTJ1SxYkXXFoIA7MVWAVD638bpGffUBAC7qVixouvzEID92C4AOhwO1axZU9WqVdOlS5e83RwAKHKlS5em5w+wOdsFwHT+/v58AAIAAFuy1SQQAAAAEAABAABshwAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDN+HQAnDRpkhwOhx5//HFvNwUAAKDE8NkAuGXLFk2bNk2tWrXydlMAAABKFJ8MgMnJyRowYICmT5+uSpUqebs5AAAAJYpPBsAhQ4aoV69e6tKli7ebAgAAUOKU8nYDMps7d662b9+uLVu25Or6Cxcu6MKFC67vExMTC6tpAAAAJYJP9QAePXpUI0aM0CeffKIyZcrk6jETJ05USEiI6ys8PLyQWwkAAFC8OYwxxtuNSLdw4UL16dNH/v7+rmOpqalyOBzy8/PThQsX3M5JnnsAw8PD5XQ6FRwcXGRtBwAAKCqJiYkKCQnJd97xqVvAN998s3bt2uV2bODAgWrSpImee+65LOFPkgIDAxUYGFhUTQQAACj2fCoAVqhQQS1atHA7Vq5cOVWpUiXLcQAAAOSPT40BBAAAQOHzqR5AT1avXu3tJgAAAJQo9AACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGymVEELSEtL05o1a7Ru3TodOXJE586dU2hoqFq3bq0uXbooPDzcinYCAADAIvnuAUxJSdFLL72k8PBw9ezZU0uWLNGZM2fk7++vAwcO6Pnnn1f9+vXVs2dPbdq0yco2AwAAoADy3QPYqFEjRUZGavr06eratatKly6d5ZojR45o9uzZ+utf/6oxY8Zo0KBBBWosAAAACs5hjDH5eeCePXvUtGnTXF176dIlxcfHq0GDBvmpKk8SExMVEhIip9Op4ODgQq8PAACgqBU07+T7FnBuw58klS5dukjCHwAAAK6swJNA0p0/f147d+7UiRMnlJaW5nbutttus6oaAAAAFJAlAXDp0qW6//77dfLkySznHA6HUlNTragGAAAAFrBkHcBhw4bprrvuUkJCgtLS0ty+CH8AAAC+xZIA+N///ldPPvmkqlevbkVxAAAAKESWBMC//OUvWr16tRVFAQAAoJDlexmYjM6dO6e77rpLoaGhatmyZZY1AYcPH17QKnKNZWAAAEBJV9C8Y8kkkDlz5ujbb79VmTJltHr1ajkcDtc5h8NRpAEQAAAAObMkAI4ZM0bjxo3TyJEj5ednyV1lAAAAFBJL0trFixfVr18/wh8AAEAxYElie+CBBzRv3jwrigIAAEAhs+QWcGpqql599VUtW7ZMrVq1yjIJZPLkyVZUAwAAAAtYEgB37dql1q1bS5J2797tdi7jhBAAAAB4nyUBcNWqVVYUAwAAgCJg+ayNX375Rb/88ovVxQIAAMAilgTAtLQ0jR8/XiEhIapbt67q1q2rihUr6sUXX1RaWpoVVQAAAMAilq0DOGPGDE2aNEkdO3aUJK1fv14vvPCCzp8/rwkTJlhRDQAAACxgyVZwYWFheu+993Tbbbe5Hf/yyy81ePBg/frrrwWtItfYCg4AAJR0Bc07ltwCPnXqlJo0aZLleJMmTXTq1CkrqgAAAIBFLAmAEREReuedd7Icf+eddxQREWFFFQAAALCIJWMAX331VfXq1UsrVqxQZGSkJGnjxo06evSoFi9ebEUVAAAAsIglPYCdOnXSzz//rD59+ujMmTM6c+aM7rzzTu3bt0833nijFVUAAADAIpZMAomPj1d4eLjHXT/i4+NVp06dglaRa0wCAQAAJZ1PTAKpX7++fvvttyzHf//9d9WvX9+KKgAAAGARSwKgMcZj719ycrLKlCljRRUAAACwSIEmgTz55JOSJIfDoX/84x8qW7as61xqaqo2b96sa665pkANBAAAgLUKFABjYmIkXe4B3LVrlwICAlznAgICFBERoaeffrpgLQQAAIClChQAV61aJUkaOHCg3nzzTSZdAAAAFAOWrAM4c+ZMK4oBAABAEbAkAErS1q1b9emnnyo+Pl4XL150Ozd//nyrqgEAAEABWTILeO7cuerQoYP27NmjBQsW6NKlS/rxxx+1cuVKhYSEWFEFAAAALGJJAHz55Zf1z3/+U1999ZUCAgL05ptvau/evbr77ruLdBFoAAAAXJklAfDgwYPq1auXpMuzf8+ePSuHw6EnnnhC//73v62oAgAAABaxJABWqlRJSUlJkqRatWpp9+7dkqQzZ87o3LlzVlQBAAAAi1gyCSQqKkrLly9Xy5Ytddddd2nEiBFauXKlli9frptvvtmKKgAAAGARSwLgO++8o/Pnz0uSxowZo9KlS2vDhg3q27evxo4da0UVAAAAsIjDGGO83QgrJSYmKiQkRE6nk4WpAQBAiVTQvGPJGEAAAAAUHwRAAAAAmyEAAgAA2AwBEAAAwGYKHAAvXbqkUqVKudb+AwAAgG8rcAAsXbq06tSpo9TUVCvaAwAAgEJmyS3gMWPGaPTo0Tp16pQVxQEAAKAQWbYQ9IEDBxQWFqa6deuqXLlybue3b99uRTUAAACwgCUB8I477rCiGEnS1KlTNXXqVB0+fFiS1Lx5c/3f//2fevToYVkdAAAAduZzO4F89dVX8vf319VXXy1jjD788EO99tpriomJUfPmza/4eHYCAQAAJV1B845lAfDMmTP6/PPPdfDgQT3zzDOqXLmytm/frurVq6tWrVoFKrty5cp67bXX9PDDD1/xWgIgAAAo6Qqadyy5Bbxz50516dJFISEhOnz4sAYNGqTKlStr/vz5io+P13/+8598lZuamqrPPvtMZ8+eVWRkpMdrLly4oAsXLri+T0xMzFddAAAAdmHJLOAnn3xSDz74oPbv368yZcq4jvfs2VNr167Nc3m7du1S+fLlFRgYqEcffVQLFixQs2bNPF47ceJEhYSEuL7Cw8Pz/TwAAADswJJbwCEhIdq+fbsaNGigChUqaMeOHbrqqqt05MgRNW7cWOfPn89TeRcvXlR8fLycTqc+//xzvf/++1qzZo3HEOipBzA8PJxbwAAAoMTyiVvAgYGBHm+9/vzzzwoNDc1zeQEBAWrYsKEkqW3bttqyZYvefPNNTZs2zWPdgYGBeW80AACATVlyC/i2227T+PHjdenSJUmSw+FQfHy8nnvuOfXt27fA5aelpbn18gEAUJgSnCnacPCkEpwp3m4KUCgs6QF844039Je//EXVqlVTSkqKOnXqpOPHjysyMlITJkzIU1mjRo1Sjx49VKdOHSUlJWn27NlavXq1li1bZkVTAQDI0bwt8Ro1f5fSjOTnkCbe2VL92tfxdrMAS1kSAENCQrR8+XKtX79eO3fuVHJystq0aaMuXbrkuawTJ07o/vvvV0JCgkJCQtSqVSstW7ZMXbt2taKpAABkK8GZ4gp/kpRmpNHzdyuqUahqhgR5t3GAhSwJgOluuOEG3XDDDQUqY8aMGRa1BgCAvIk7edYV/tKlGqNvdiaoV6uahECUGJaMAZSk7777TrfeeqsaNGigBg0a6NZbb9WKFSusKh4AgEJXv2o5+TmyHn/pmz3qOGml5m2JL/pGAYXAkgD47rvv6pZbblGFChU0YsQIjRgxQsHBwerZs6emTJliRRUAABS6miFBmnhnS/k7sqbA9NvBTAxBSWDJOoC1a9fWyJEjNXToULfjU6ZM0csvv6xff/21oFXkGlvBAQAKKsGZom92Juilb/ZkOTdn0PWKbFDFC60C/qegeceSHsAzZ87olltuyXK8W7ducjqdVlQBAECRSHCmKO7kWbWvVynL7WB/h0P1qpb1TsMAC1m2DuCCBQuyHP/yyy916623WlEFAACFbt6WeHWctFL9p29Wn3c3qE/rWq7bwf4Oh16+swUTQVAiWDILuFmzZpowYYJWr16tyMhISdKmTZv0/fff66mnntJbb73lunb48OFWVAkAgKU8LQGzMOaY5g+O1LmLaapXtSzhDyWGJWMA69evn7vKHA4dOnSooNXliDGAAID82HDwpPpP35zlOGP+4It8Yi/guLg4K4oBAMBr0peAybgOIGP+UFJZtg4gAADFWeYlYBjzh5LM0p1AAAAozvq1r6OoRqE6fPIcY/5QohEAAQDIoGZIEMEPJR63gAEAAGyGAAgAAGAzlt0CPn36tGbMmKE9ey5vm9O0aVM99NBDqly5slVVAAAAwAKW9ACuXbtW9evX11tvvaXTp0/r9OnTevvtt1W/fn2tXbvWiioAAABgEUsWgm7ZsqUiIyM1depU+fv7S5JSU1M1ePBgbdiwQbt27SpwQ3OLhaABAEBJV9C8Y0kP4IEDB/TUU0+5wp8k+fv768knn9SBAwesqAIAAAAWsSQAtmnTxjX2L6M9e/YoIiLCiioAACgUCc4UbTh4UgnOFG83BSgy+Z4EsnPnTte/hw8frhEjRujAgQO6/vrrJUmbNm3SlClTNGnSpIK3EgCAQjBvS7xGzd+lNCP5OaSJd7ZUv/Z1vN0soNDlewygn5+fHA6HrvRwh8Oh1NTUfDUuPxgDCADIjQRnijpOWpll79/1I6NZCBo+r6B5J989gHFxcfl9KAAAXhd38qxb+JOkVGN0+OQ5AiBKvHwHwLp161rZDgAAilT9quXk51CWHsB6Vct6r1FAEcn3JJBNmzbl+tpz587pxx9/zG9VAABYrmZIkCbe2VL+Doeky+Hv5Ttb0PsHW8h3D+B9992nq666So888oh69uypcuXKZbnmp59+0scff6yZM2fqlVdeUfPmzQvUWAAArNSvfR1FNQrV4ZPnVK9qWcIfbCPfAfCnn37S1KlTNXbsWPXv31+NGjVSWFiYypQpo9OnT2vv3r1KTk5Wnz599O2336ply5ZWthsAAEvUDAki+MF2LNkJZOvWrVq/fr2OHDmilJQUVa1aVa1bt1Z0dHSR7wXMLGAAAFDSeW0WcEbt2rVTu3btrCgKAAAAhcySnUAAAABQfBAAAQAAbIYACACwLfYBhl1ZMgYQAIDihn2AYWf0AAIAbCfBmeIKf9Ll3UBGz99NTyBsw7IewO+++07fffedTpw4obS0NLdzH3zwgVXVAABQYOwDDLuzJACOGzdO48ePV7t27VSzZk05/txWBwAAX8Q+wLA7SwLge++9p1mzZum+++6zojgAAApV+j7Ao+fvVqox7AMM27EkAF68eFEdOnSwoigAAIoE+wDDziyZBPLII49o9uzZVhQFAECRqRkSpMgGVQh/sB1LegDPnz+vf//731qxYoVatWql0qVLu52fPHmyFdUAAFBgCc4UxZ08q/pVyxH8YFuWBMCdO3fqmmuukSTt3r3b7RwTQgAAvoK1/4DLLAmAq1atsqIYAAAKTXZr/0U1CqUnELZj+ULQv/zyi3755ReriwUAoEByWvsPsBtLAmBaWprGjx+vkJAQ1a1bV3Xr1lXFihX14osvZlkUGgAAb6hftZwyD0pi7T/YlSW3gMeMGaMZM2Zo0qRJ6tixoyRp/fr1euGFF3T+/HlNmDDBimoAAMi3tT//5va9Q2LtP9iWJQHwww8/1Pvvv6/bbrvNdaxVq1aqVauWBg8eTAAEAHhV+vi/jHeAHQ4pqlGo19oEeJMlt4BPnTqlJk2aZDnepEkTnTp1yooqAADIN0/j/9KMGP8H27IkAEZEROidd97Jcvydd95RRESEFVUAAJBv6Xv/ZsT4P9iZJbeAX331VfXq1UsrVqxQZGSkJGnjxo06evSoFi9ebEUVAADkG3v/Au4cxhhz5cuu7NixY5oyZYr27t0rSWratKkGDx6ssLAwK4rPtcTERIWEhMjpdCo4OLhI6wYA+LYEZwp7/6JEKGjesSwA+goCIADAE7aAQ0lS0LyT71vAO3fuVIsWLeTn56edO3fmeG2rVq3yWw0AAAXGFnCAu3z3APr5+en48eOqVq2a/Pz85HA45Kkoh8Oh1NTUAjc0t+gBBABklOBMUcdJK91mAfs7HFo/MpqeQBRbXusBjIuLU2hoqOvfAAD4opy2gCMAwq7yHQDr1q3r+veRI0fUoUMHlSrlXtwff/yhDRs2uF0LAEBRSl8CJnMPIEvAwM4sWQcwOjra44LPTqdT0dHRVlQBAEC+pC8B4++4vBAgS8AAFq0DaIyRw5F5i23p999/V7ly5ayoAgCAfOvXvo6iGoWyBAzwpwIFwDvvvFPS5YkeDz74oAIDA13nUlNTtXPnTnXo0KFgLQQAwAI1Q4IIfsCfChQAQ0JCJF3uAaxQoYKCgv73gxUQEKDrr79egwYNKlgLAQAAYKkCBcCZM2dKkurVq6dnnnlGZcsyoBYAAMDXWTIJ5P7779evv/6a5fj+/ft1+PBhK6oAAACARSwJgA8++KA2bNiQ5fjmzZv14IMPWlEFAAAALGJJAIyJiVHHjh2zHL/++usVGxtrRRUAAORbgjNFGw6eVIIzpUgfC/gqS5aBcTgcSkpKynLc6XQW6TZwAABkVpB9gO26h3CCM0VxJ8+qftVyzJwuoSzpAYyKitLEiRPdwl5qaqomTpyoG264wYoqAADIswRniivASZd3Axk9f3euevMK8tjibN6WeHWctFL9p29Wx0krNW9LvLebhEJgSQ/gK6+8oqioKDVu3Fg33nijJGndunVKTEzUypUrragCAIA8K8g+wHbcQzi70BvVKLTEPme7sqQHsFmzZtq5c6fuvvtunThxQklJSbr//vu1d+9etWjRwooqABRTjJ+CN6XvA5xRbvcBLshji6uth09lG3pRsljSAyhJYWFhevnll60qDkAxl+BM0cz1cZq+Lk5G9ho/Bd+Rvg/w6Pm7lWpMnvYBLshji6P08Y6ZlfTQa1cOY4y58mVXtm7dOk2bNk2HDh3SZ599plq1aumjjz5S/fr1i3QcYGJiokJCQuR0OhUcHFxk9QL4n4wD5zPydzi0fmR0if0FCt+V4EzJ9z7ABXlscZHgTFHHSSuz/Mw6JD1yY309dEP9Evvci6uC5h1LbgF/8cUX6t69u4KCgrR9+3ZduHBB0uVZwPQKAvaSeQxRRtxKgrfUDAlSZIMq+QoxBXlsceFpvKMkGUnT18UxGaQEsiQAvvTSS3rvvfc0ffp0lS5d2nW8Y8eO2r59uxVVACgmsvtFInErCfBVnsY7ZmSXGdB2YkkA3Ldvn6KiorIcDwkJ0ZkzZ6yoAkAxUS7AX55+jzgkPXRDvSJuDYDcSB/v6O+4/NPrKQzSg1+yWBIAa9SooQMHDmQ5vn79el111VV5KmvixIlq3769KlSooGrVqumOO+7Qvn37rGgmgEI2b0u8+ry7QRk7AP0cUtTVVSVlfyuJmcKA9/VrX0frR0ZrzqDrtWBwB9vNgLYbSwLgoEGDNGLECG3evFkOh0PHjh3TJ598oqefflqPPfZYnspas2aNhgwZok2bNmn58uW6dOmSunXrprNnz1rRVACFxNPYPz+HNP3+tlp/4KQrFGa+lcSis4DvSB/vGBFeya1HsKTPgLYjS5aBGTlypNLS0nTzzTfr3LlzioqKUmBgoJ5++mkNGzYsT2UtXbrU7ftZs2apWrVq2rZtm8fbzAC8K33LqN+TL2QZ+5dmpLiT53JcV4xFZwHf1K99HUU1Ci3xM6DtyrK9gMeMGaNnnnlGBw4cUHJyspo1a6by5csXuGyn0ylJqly5coHLAmCtzPukOiS327/+Dofa16skP4fcQqC/w6GyAX76eucx2+20ABQnNUOC+FksoSxbCFqSAgIC1KxZMyUmJmrFihVq3LixmjZtmu/y0tLS9Pjjj6tjx47Z7ihy4cIF17Iz0uV1cQAUPk9bRjkckp+R0vS/W0bpt5LSF9P1c0gdG1bRHVPcxwqm83NIZQMsGZ1SaNJ7PetXLccvx2KC9wxwZ0kAvPvuuxUVFaWhQ4cqJSVF7du3V1xcnIwxmjt3rvr27ZuvcocMGaLdu3dr/fr12V4zceJEjRs3Lr9NB5BPnpZ7MUZ6p39rVS4X6HbLKP1W0szv4zR9bZzW7j+ZbblpRurz7gaf3TUkc6+nr7YT/8N7BmRlyZ/Za9eu1Y033ihJWrBggdLS0nTmzBm99dZbeumll/JV5tChQ/X1119r1apVql27drbXjRo1Sk6n0/V19OjRfNUHIHueZulmt09qm7qVsl009/0/t4W7El9dc8xTr6cvthP/w3sGeGZJAHQ6na4xekuXLlXfvn1VtmxZ9erVS/v3789TWcYYDR06VAsWLNDKlStVv379HK8PDAxUcHCw2xcA62Q3SzfzumFXmiWY0wLRnvjimmOenoMvthP/w3sGeGbJLeDw8HBt3LhRlStX1tKlSzV37lxJ0unTp1WmTJk8lTVkyBDNnj1bX375pSpUqKDjx49LuryodFAQ4zaAopRd70n6LN28zBJM7zHMbQj0xTXHPD0HX2ynXeRmXB/vGeCZJT2Ajz/+uAYMGKDatWurZs2a6ty5s6TLt4ZbtmyZp7KmTp0qp9Opzp07q2bNmq6vefPmWdFUAHmQm96T3O6T6mmngb/deJW+HNJBcwZdr1E9mvj8mmN57fVE4cnt+pG8Z4BnDmNMHm7KZG/btm2Kj49X165dXcu/fPPNN6pYsaI6duxoRRW5kpiYqJCQEDmdTm4HAwWU4ExRx0krs/SerB8Zne9foAnOlGx7DHM65wvSe5zKBfjr3MU0n21nSZef/5e+/n/Lm5ghXTwVNO9YtgxM27Zt1bZtW33//fdq166dAgMD1atXL6uKB+AF6b0n6Uu4WNF7ktO6Yr665liCM0Uz18dp+p+TWNJnkkY2qOLtptlSTj3Txe3/lrcxQ9q+LF0HUJJ69Oih2NjYPO8BDMA32X03gIy/INOxY4l3Ma7PGlca44uSzfLVVi26owzAh+R2nJ9VPC074w2e9jdOx0xS72FcnzWy60n9ZmeC13/2UPgs7wEEUHz5wlggX7olldPSNX4O6WTyeSU4UwgeXmD3nmkrZDcz/6Vv9ujlxXu4HVzCWd4DOG3aNFWvXt3qYgHkU25703I7q7Iw+dqivZ4Wu05njDRsTqzXXisUfc90SVMzJEh9WtfyeM7bP3sofJYHwP79+ys1NVULFy7Unj17rC4eQB7kNtT5SvDytUV7PS1dM+C6OnJIrh1N+EWJ4irBmaIFMb9me55hDiVboewF3K5dOx0+fLjAewEDyD9PoW7U/F1qUqOCIsIruV2bn1mVhcFbg/tzuvWd+VZj3Mmz+mSze5D2xmtVkvnCUAQ7uNLuPEysKdkKZS9gY0yB9wIGUDCePtzTjHTHlA1ZegKz29e3qD/8vTG4Pze9pBlvNfrKa1VS+cJQBLvIaYgDE2tKPp/bCxiANbL7cDdyv2WZ3tvy3C2+sRNHv/Z1tH5ktOYMul7rR0YX6iD0/Nz6ZgZq4fGVoQh24en/8qieTYrkZw/e53N7AQOwRvqHu6dlTNJvWa79+Te3GbfP9WiiVrUqen1WZVEt2pvfW9/MQC0cvjIUwU74v2xflu8FHBYWVqC9gAFYp1/7OlowuIMydwT6OaRzFy9p5BfuvS2vLtlnq18CBbmdywxU63F73Tv4v2xPlgTAwYMHa+PGjfrggw+0fv16+fldLvaqq65iDCDgZRHhlTSpb0s5MvxiTTPSwx9uU+bx33ab9cft3KKTm+WIeD+AouMwhbB1R2pqqnbt2qW6deuqUqVKV36AhQq6OTJQEiU4U9Rh4sosgS8zf4dD60dG2+4XboIzJd+3wJixemV5Xdy7IO8HYBcFzTuW3QKeMWOGpMvhr1OnTmrTpo3Cw8O1evVqK6oAUABxJ89eMfz5SbbtbcnvLTC7z1jNTa9efifacEsSKFyWBMDPP/9cERERkqSvvvpKcXFx2rt3r5544gmNGTPGiioAFEBOyz1Il3tlFgzpUGJm/RXFXsJ2n7Ga2/Dra4t7A7jMkgB48uRJ1ahRQ5K0ePFi3XXXXWrUqJEeeugh7dq1y4oqAORDehCS5Da2KiPHn+cyLw5dXBVVr5ydg01ewi8TOwDfZEkArF69un766SelpqZq6dKl6tq1qyTp3Llz8vf3t6IKAHmUOQhJ0qOdr8pyncMhRTUKLermFYqi7JWzc7DJS/hlYgfgmyxZB3DgwIG6++67VbNmTTkcDnXp0kWStHnzZjVp0sSKKgDkQXbbwHna9inNyOfXWcs80SK7iRdFuY5cerAZPX+3Uo2xVbDJ65Z9rDXnu5jEZF+WBMAXXnhBLVq00NGjR3XXXXcpMDBQkuTv76+RI0daUQWAPMhuGzhP/CSf7rXKPIO0T+taWhDzq8cZpUW9l3BJDDa5CQT5Cb9Ftbg3ci+vs7NRshTKMjDexDIw9sZfs5d5WvbFzyEZoyyzgUf1aKK/d2pQlM3LtR1HT+uOKRtynMGceemaeVviswQTu/5Sy+vPA8u12EeCM0UdJ63M8seSHZeBKq4Kmncs6QGUpDVr1uj111/Xnj17JEnNmjXTM888oxtvvNGqKoAcZfzl5XBII3s00d+jfDPYFLZFscfcQlP6RA9JrnCUvvWbr75G87bEa+T8XVdcvibzLd6S2CuXH/kJc57GT0Y1Cs2xJ9Cur29xx7Z7sCQAfvzxxxo4cKDuvPNODR8+XJL0/fff6+abb9asWbPUv39/K6oBspX5l5cx0sTFeyUjn+3dKizT1h7UxCV73Y6lT/SoGRJULMJR+vuZm/sTnm7xlvRgcqWevfyEOQKBvRT1cAn4HktmAU+YMEGvvvqq5s2bp+HDh2v48OGaN2+eJk2apBdffNGKKoAcbT18yuMYt0lL9mrH0dP5Lrco1pOzUoIzRZMyhT/pfxM9pOKxyK6nMCJd/sDq26ZWsZhRmpf/O3m5NjfL3ORniRo7z2q2I2Znw5IewEOHDql3795Zjt92220aPXq0FVUA2Zq3JV4jv/C83qSRdMeUDZrUN++Dm4vjAOm4k2c99pr5+kSPzDz1Tvg5pAWDOygivJKe7t7Yp3sx8/J/Jy/X5rZnLz+9O3ae1WxXDJewN0t6AMPDw/Xdd99lOb5ixQqFh4dbUQXgketWYQ7XGHleCy5zr0vG7xOcKRr5RdZlVHy9JzC7HT+e69GkWH24e+qdyLhYtS/3YuZlLcK8rluY2569/Pbu9GtfR+tHRmvOoOu1fmS0z//BU1SK252AvDJXHGmLksiSHsCnnnpKw4cPV2xsrDp06CDp8hjAWbNm6c0337SiCthYTuOdsrtVmFnmsUxXWlqkY8OqWT4S04z00tc/aeytzSwPHunPsVyAv85eTM33LObMvTi+PtEjJ8W1dyIvY+nyOu4uLz17+X39Svr4ybwqjncCcqskPzdcmSUB8LHHHlONGjX0xhtv6NNPP5UkNW3aVPPmzdPtt99uRRWwqew+oDIGpsy/ELNTNuByh7enXpcvtv/qui7NSOv2n/RYxje7jmvxruMebynndwmajM8xXUE+jItrcPKkOIaRvIS0vN6qzett2uL4+vmS/Eymyaksby9RlbENkix7biieChwA//jjD7388st66KGHtH79eivaBEjK/sP3zLlLemXpXrfeu/kxv7rGvjmUda07SfrldIrOXkzV78kXchUYs5N+SznjB2V+/5LecfS0Rn6R9RZ2QT+M+cXvPXkJafkZd1eSAr6vs2pmtC/0tGVuw8M31GfWt81ZshB0+fLltXv3btWrV8+CJhWMLy4E7Qt/+eWnHUXZbk91bTh4Uv2nb85ybeaA5+9waP7gSP1yOkXGSOGVg9Tn3Q1uH24ZH+P4c0Hkgpoz6HpFNqiS7aLL34+8ye11S3CmaNuR0zLGqF29ylr782+X17nLoS3pdeTEV/5/wV1eFklmQWXf5Gmx5PSfbUm5+rnzhQWXs3semReGZyHo4sUnFoK++eabtWbNGp8IgL6msP/yy+0v/7y2oyj/Yp225qAmLdkrI/e6spsJ6umv1nMX09SrVZjrWMZeFcn9Qy5z4HJIurNNLS2MOebqhbmjdZjre0/8HJdvKSc4U/TS1z957MGb+X2cRvdsJul/M5VdITS9LVd4bXb+cibHAOgLPQvwLC+9sPTY+qb0HtqMf6gZI72+bF+22xFm5gvrK2a3NeTfouprxrrDzPq2KUt6AN977z2NGzdOAwYMUNu2bVWuXDm387fddltBq8i1ouoBzE3wKshffrkpP7e//PPajqL8i3Xa2oOXF2zOIGNdmbf1erZHY72yZG+u2pabbcSky2Fsw6jLf9Fn7IVJ75UpG+Cnb3Yl6P21cUrL9Dgp+xDnkPTWPdeoTuWyWXokc8vPIb3512vUrl7lLM/PF3oWgJLOUw9/Zpl/7jKPtbvSz2lh353J6bNCEr3PxZRP9AAOHjxYkjR58uQs5xwOh1JTU62oxmfkNnjl9y+/3JSfl8HJeW1HUf3Fmt2ixRnr8jTeqWJQ6VyNmTp7MTVXixsYXf4AzLysSMZemYjwSurVsqZboLxS2UbSsDmxub7l7Om6NHO5DE//D3yhZwEo6eJOns3TdoSePr9zGudZFHdnrjTWlM8Le7IkAKalpV35ohIiL8ErP4ux5rb8vPzyz2s7CmuLoMx/teZ20eLMt8dyOwje0/PwJLeLJOc2UGaWU/jzk5QmZdu7mc7T/wO2cgIKX24+R9J/7rL7/F4/MlrrR0Zn+czK6yzjK12fU88gk4eQmSULQdtJXrZYys9irLktPy/bNuW1Hflp95UWSvW0fVVBFi3OzULA6c/D4aGOdA5JE/u2zNWHYXbtzQ+HpFf6ttT3o25yLbr796gGObY31RhtP3La9VpLYisnoJB5+jzMbjvCK/1hnvkzK69b9uV0fW62CPTlBdRR9ArUA7hy5UoNHTpUmzZtynL/2el0qkOHDpo6daqioqIK1Ehfktdel7z+1ZXb8vO6fERe25GX6690SyKnv4oLe9Hi9Oex/chpGSO1rXd5J4mM3+dloP7EO1tmWbMvXf9r66hf+9r65XSKhs6OyXGmcsZ6M9Yf1Sg0x3vLQ2bHuGY0p7/WnnoWAFjH0+ehp+0IC/tuS3bXlw3wY00/5FmBJoHcdtttio6O1hNPPOHx/FtvvaVVq1ZpwYIF+W5gXhXFJJDMExNevrOFpTMv81K+t5ePyM1EhOyWc8m4jEpxCjBf7fhVw+bEZjmeccmW/P4fye61yg6TPgDfkteffSuuD69cNsfPWJRMXp0EsmPHDr3yyivZnu/WrZtef/31glThkwp7LEVeyvf28hG5GYt4pb9yvf0c8qpdvcpX/Ks9v/9H6lctl6d1Cpn0AfgWK++2eBrT5+n6BGdKoY0HZp3RkqtAAfC///2vSpcunX3hpUrpt99+K0gVPquwQ0txCUW5uYWRn90OfFlun09+3sOaIUEa2aNJlqVxssOkD8D35PVn39P1OQ2tyXx9YX3Gss5oyVagAFirVi3t3r1bDRs29Hh+586dqlmzZkGqgI/L7QdPSZuBVpjP5+9RDSSjyzOClf3WdpJ0R+uwYv9aAnCXnz2Irf5MsnIfZPimAgXAnj176h//+IduueUWlSlTxu1cSkqKnn/+ed16660FaiB8X24/eIpLr2ZuFebz+XunBrrtmjAdPnlOJ5PPexxzKEkLY47p6e6NS9TrCthdftf4tPIziXVGS74CBcCxY8dq/vz5atSokYYOHarGjRtLkvbu3aspU6YoNTVVY8aMsaSh8G0lLdz5gvTX1NP4nnR8IAMljy+s8ekLbUDhKtA6gNWrV9eGDRvUokULjRo1Sn369FGfPn00evRotWjRQuvXr1f16tWtaitgS+m32T2tQcgHMlDy5Gct1pLYBhQuS/YClqTTp0/rwIEDMsbo6quvVqVKlawoNs+Kai9goKglOFM08/s4157EhbEEEQDf4QtLZPlCG+BZQfOOZQHQVxAAUdLxgQwA8Oo6gACKHuMtAQAFxV7AAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBmfC4Br165V7969FRYWJofDoYULF3q7SQAAACWKzwXAs2fPKiIiQlOmTPF2UwAAgI0lOFO04eBJJThTvN0Uy5XydgMy69Gjh3r06OHtZgAAABubtyVeo+bvUpqR/BzSxDtbql/7Ot5ulmV8rgcwry5cuKDExES3LwAAgPxKcKa4wp8kpRlp9PzdJaonsNgHwIkTJyokJMT1FR4e7u0mAQCAYizu5FlX+EuXaowOnzznnQYVgmIfAEeNGiWn0+n6Onr0qLebBABAiZGbcXAlbaxc/arl5OdwP+bvcKhe1bLeaVAh8LkxgHkVGBiowMBAbzcDAIASJzfj4EriWLmaIUGaeGdLjZ6/W6nGyN/h0Mt3tlDNkCBvN80yxT4AAgAA62U3Di6qUagrCOXmmuKqX/s6imoUqsMnz6le1bLF/vlk5nMBMDk5WQcOHHB9HxcXp9jYWFWuXFl16hTvvygAACguchoHlx6GcnNNcVYzJKhEPA9PfC4Abt26VdHR0a7vn3zySUnSAw88oFmzZnmpVQAA2Ev6OLiMAS/zOLjcXONrEpwpijt5VvWrliux4S43fG4SSOfOnWWMyfJF+AMAoOikj4Pzd1yeDZFxHFz6pA9J2V6TWWFPFMlN+fO2xKvjpJXqP32zOk5aqXlb4r3SDl/gMMaYK19WfCQmJiokJEROp1PBwcHebg4AAMVagjPFbRycp0kfVxorV9gTRXJTfoIzRR0nrczSW7l+ZLRlPYFFOSGmoHnH53oAAQCA76gZEqTIBlVcPX+eJn1Icl2TmRWLKufUq5bb8gt7bb/itni0z40BBAAAvik/kz4KOlHkSr1quS2/sMcrFrcJMfQAAgCAXMnPAskFWVQ5N71quS0/pzGNVihui0cTAAEAQK7kJ0QVJHjl5rZtXsrv176O1o+M1pxB12v9yGhLx+cVdsC0GpNAAABAnmSeGFKYj8ntxI38lF8YiqodBc07BEAAAOCz5m2Jz7IlW3Hfas4KBc07TAIBAAA+q6RvyeYtBEAAAODTSvKWbN7CJBAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbKeXtBljNGCNJSkxM9HJLAAAACkd6zknPPXlV4gJgUlKSJCk8PNzLLQEAAChcSUlJCgkJyfPjHCa/0dFHpaWl6dixY6pQoYIcDoe3m2MbiYmJCg8P19GjRxUcHOzt5uBPvC++iffFN/G++CbeF8+MMUpKSlJYWJj8/PI+oq/E9QD6+fmpdu3a3m6GbQUHB/MD6oN4X3wT74tv4n3xTbwvWeWn5y8dk0AAAABshgAIAABgMwRAWCIwMFDPP/+8AgMDvd0UZMD74pt4X3wT74tv4n0pHCVuEggAAAByRg8gAACAzRAAAQAAbIYACAAAYDMEQBTI2rVr1bt3b4WFhcnhcGjhwoXebpLtTZw4Ue3bt1eFChVUrVo13XHHHdq3b5+3m2V7U6dOVatWrVxrmUVGRmrJkiXebhYymTRpkhwOhx5//HFvN8XWXnjhBTkcDrevJk2aeLtZJQoBEAVy9uxZRUREaMqUKd5uCv60Zs0aDRkyRJs2bdLy5ct16dIldevWTWfPnvV202ytdu3amjRpkrZt26atW7fqpptu0u23364ff/zR203Dn7Zs2aJp06apVatW3m4KJDVv3lwJCQmur/Xr13u7SSVKidsJBEWrR48e6tGjh7ebgQyWLl3q9v2sWbNUrVo1bdu2TVFRUV5qFXr37u32/YQJEzR16lRt2rRJzZs391KrkC45OVkDBgzQ9OnT9dJLL3m7OZBUqlQp1ahRw9vNKLHoAQRKOKfTKUmqXLmyl1uCdKmpqZo7d67Onj2ryMhIbzcHkoYMGaJevXqpS5cu3m4K/rR//36FhYXpqquu0oABAxQfH+/tJpUo9AACJVhaWpoef/xxdezYUS1atPB2c2xv165dioyM1Pnz51W+fHktWLBAzZo183azbG/u3Lnavn27tmzZ4u2m4E/XXXedZs2apcaNGyshIUHjxo3TjTfeqN27d6tChQrebl6JQAAESrAhQ4Zo9+7djJ3xEY0bN1ZsbKycTqc+//xzPfDAA1qzZg0h0IuOHj2qESNGaPny5SpTpoy3m4M/ZRxa1KpVK1133XWqW7euPv30Uz388MNebFnJQQAESqihQ4fq66+/1tq1a1W7dm1vNweSAgIC1LBhQ0lS27ZttWXLFr355puaNm2al1tmX9u2bdOJEyfUpk0b17HU1FStXbtW77zzji5cuCB/f38vthCSVLFiRTVq1EgHDhzwdlNKDAIgUMIYYzRs2DAtWLBAq1evVv369b3dJGQjLS1NFy5c8HYzbO3mm2/Wrl273I4NHDhQTZo00XPPPUf48xHJyck6ePCg7rvvPm83pcQgAKJAkpOT3f4ii4uLU2xsrCpXrqw6dep4sWX2NWTIEM2ePVtffvmlKlSooOPHj0uSQkJCFBQU5OXW2deoUaPUo0cP1alTR0lJSZo9e7ZWr16tZcuWebtptlahQoUs42PLlSunKlWqMG7Wi55++mn17t1bdevW1bFjx/T888/L399f99xzj7ebVmIQAFEgW7duVXR0tOv7J598UpL0wAMPaNasWV5qlb1NnTpVktS5c2e34zNnztSDDz5Y9A2CJOnEiRO6//77lZCQoJCQELVq1UrLli1T165dvd00wOf88ssvuueee/T7778rNDRUN9xwgzZt2qTQ0FBvN63EcBhjjLcbAQAAgKLDOoAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAUMLt27dP7du3V/369fXll196uzkAfAA7gQBACdevXz9de+21atWqlR5++GHFx8d7u0kAvIweQAC298ILL+iaa67xdjNcHA6HFi5cmOfH7du3TzVq1FBSUpLb8ZCQENWtW1cNGzZUtWrVsjzu+uuv1xdffJHf5gIohgiAAIrEe++9pwoVKuiPP/5wHUtOTlbp0qXVuXNnt2tXr14th8OhgwcPFnEri5bVwXPUqFEaNmyYKlSo4HZ8/Pjx6tevnxo2bKhRo0ZledzYsWM1cuRIpaWlWdYWAL6NAAigSERHRys5OVlbt251HVu3bp1q1KihzZs36/z5867jq1atUp06ddSgQQNvNLVYio+P19dff60HH3wwy7nNmzerdu3a+utf/6oNGzZkOd+jRw8lJSVpyZIlRdBSAL6AAAigSDRu3Fg1a9bU6tWrXcdWr16t22+/XfXr19emTZvcjkdHR0uSPvroI7Vr104VKlRQjRo11L9/f504cUKSlJaWptq1a2vq1KludcXExMjPz09HjhyRJJ05c0aPPPKIQkNDFRwcrJtuukk7duzIsb3vv/++mjZtqjJlyqhJkyZ69913XecOHz4sh8Oh+fPnKzo6WmXLllVERIQ2btzoVsb06dMVHh6usmXLqk+fPpo8ebIqVqwoSZo1a5bGjRunHTt2yOFwyOFwaNasWa7Hnjx5Un369FHZsmV19dVXa9GiRTm299NPP1VERIRq1aqV5dzMmTPVv39/3Xffffr444/demElyd/fXz179tTcuXNzrANAyUEABFBkoqOjtWrVKtf3q1atUufOndWpUyfX8ZSUFG3evNkVAC9duqQXX3xRO3bs0MKFC3X48GFXL5efn5/uuecezZ49262eTz75RB07dlTdunUlSXfddZdOnDihJUuWaNu2bWrTpo1uvvlmnTp1ymM7P/nkE/3f//2fJkyYoD179ujll1/WP/7xD3344Ydu140ZM0ZPP/20YmNj1ahRI91zzz2ucPX999/r0Ucf1YgRIxQbG6uuXbtqwoQJrsf269dPTz31lJo3b66EhAQlJCSoX79+rvPjxo3T3XffrZ07d6pnz54aMGBAtu2VLvemtmvXLsvxEydOaPHixbr33nvVtWtXORwOffPNN1muu/baa7Vu3bpsywdQwhgAKCLTp0835cqVM5cuXTKJiYmmVKlS5sSJE2b27NkmKirKGGPMd999ZySZI0eOeCxjy5YtRpJJSkoyxhgTExNjHA6H6/rU1FRTq1YtM3XqVGOMMevWrTPBwcHm/PnzbuU0aNDATJs2zRhjzPPPP28iIiLczs2ePdvt+hdffNFERkYaY4yJi4szksz777/vOv/jjz8aSWbPnj3GGGP69etnevXq5VbGgAEDTEhIiOv7zPWmk2TGjh3r+j45OdlIMkuWLPH4mhhjTEREhBk/fnyW42+88Ya55pprXN+PGDHC3HHHHVmu+/LLL42fn59JTU3Ntg4AJQc9gACKTOfOnXX27Flt2bJF69atU6NGjRQaGqpOnTq5xgGuXr1aV111lerUqSNJ2rZtm3r37q06deqoQoUK6tSpkyS5ljK55ppr1LRpU1cv4Jo1a3TixAndddddkqQdO3YoOTlZVapUUfny5V1fcXFxHieZnD17VgcPHtTDDz/sdv1LL72U5fpWrVq5/l2zZk1Jct2e3rdvn6699lq36zN/n5OMZZcrV07BwcGusj1JSUlRmTJlshyfOXOm7r33Xtf39957r7755hv99ttvbtcFBQUpLS1NFy5cyHUbARRfpbzdAAD20bBhQ9WuXVurVq3S6dOnXWEuLCxM4eHh2rBhg1atWqWbbrpJ0uUw1r17d3Xv3l2ffPKJQkNDFR8fr+7du+vixYuucgcMGKDZs2dr5MiRmj17tm655RZVqVJF0uWZxpnHHqZLH4+XUXJysqTL4/euu+46t3P+/v5u35cuXdr1b4fDIUmWzaTNWHZ6+TmVXbVqVZ0+fdrt2NatW7V79249++yzeu6551zHU1NT9fHHH+uJJ55wHTt16pTKlSunoKAgS9oPwLcRAAEUqejoaK1evVqnT5/WM8884zoeFRWlJUuW6IcfftBjjz0mSdq7d69+//13TZo0SeHh4ZLkNos4Xf/+/TV27Fht27ZNn3/+ud577z3XuTZt2uj48eMqVaqU6tWrd8X2Va9eXWFhYTp06JAGDBiQ7+fZuHFjbdmyxe1Y5u8DAgKUmpqa7zoyat26tX766Se3YzNnzlRUVJSmTJnidvyjjz7SrFmz3ALg7t271bp1a0vaAsD3cQsYQJGKjo7W+vXrFRsb6+oBlKROnTpp2rRpunjxomsCSJ06dRQQEKC3335bhw4d0qJFi/Tiiy9mKbNevXrq0KGDHn74YaWmpuq2225znevSpYsiIyN1xx136Ntvv9Xhw4e1YcMGjRkzxmOYlC5PwJg4caLeeust/fzzz9q1a5dmzpypyZMn5/p5Dhs2TIsXL9bkyZO1f/9+TZs2TUuWLHH1FKa3Oy4uTrGxsTp58mSBbr92795dGzdudAXKCxcuaM6cObrnnnvUokULt69HHnlEO3fu1Pbt212PX7dunbp165bv+gEULwRAAEUqOjpaKSkpatiwoapXr+463qlTJyUlJbmWi5Gk0NBQzZo1S5999pmaNWumSZMm6fXXX/dY7oABA7Rjxw716dPH7Tamw+HQ4sWLFRUVpYEDB6pRo0b661//qiNHjrjVn9Ejjzyi999/XzNnzlTLli3VqVMnzZo1S/Xr18/18+zYsaPee+89TZ48WREREVq6dKmeeOIJt3F6ffv21S233KLo6GiFhoZqzpw5uS4/sx49eqhUqVJasWKFJGnhwoVyOp3q06dPlmuvvvpqtWzZUjNnzpQk/frrr9qwYYMGDhyY7/oBFC/sBQwARWTQoEHau3dvoS23MmXKFC1atEjLli3L0+Oee+45nT59Wv/+978LpV0AfA9jAAGgkLz++uvq2rWrypUrpyVLlujDDz90W1Daan//+9915swZJSUlZdkOLifVqlXTk08+WWjtAuB76AEEgEJy9913a/Xq1UpKStJVV12lYcOG6dFHH/V2swCAAAgAAGA3TAIBAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANjM/wMzn3yUAFtHVAAAAABJRU5ErkJggg==' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from urllib.request import urlopen, Request\n",
    "import pandas as pd\n",
    "import io\n",
    "x4ids = [11468002]\n",
    "x4label = ['Al - R.J.Brown 11468002']\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "#for x4id in x4ids:\n",
    "for i, x4id in enumerate(x4ids):\n",
    "    req = Request(\n",
    "        url=f'https://nds.iaea.org/exfor/x4get?DatasetID={x4id}&op=csv',\n",
    "        data=None,\n",
    "        headers={\n",
    "            'User-Agent': 'Mozilla/5.0 (X11; Fedora; Linux x86_64; rv:52.0) Gecko/20100101 Firefox/52.0'\n",
    "        }\n",
    "    )\n",
    "    with urlopen(req) as f:\n",
    "        df = pd.read_csv(io.StringIO(f.read().decode('utf-8')))\n",
    "    if 'EN (EV) 1.1' in list(df):\n",
    "        x4_E, x4_xs = df['EN (EV) 1.1'].values, df['DATA (B) 0.1'].values\n",
    "    elif 'EN (MEV) 1.1' in list(df):\n",
    "        x4_E, x4_xs = 1e6*df['EN (MEV) 1.1'].values, df['DATA (B) 0.1'].values\n",
    "\n",
    "    if (i==0):\n",
    "      ax.plot(NC.ekin2wl(x4_E), x4_xs, '.', label=x4label[i]+ f', X4: {x4id}')\n",
    "    else:\n",
    "      ax.plot(NC.ekin2wl(x4_E), x4_xs, '.', label=x4label[i]+ f', X4: {x4id}')\n",
    "\n",
    "ax.legend(loc='upper left')\n",
    "ax.set_ylim(0.1,5)\n",
    "ax.set_xlabel(\"Wavelength (Å) \")\n",
    "ax.set_ylabel(\"Cross-section (b per atom)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.5"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "3fded6f30d41401285c70d79619c00ed": {
     "model_module": "jupyter-matplotlib",
     "model_module_version": "^0.11",
     "model_name": "MPLCanvasModel",
     "state": {
      "_cursor": "default",
      "_data_url": 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