solver-test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook runs various solvers for a single step and dumps out some variables -- it is intended for unit testing.\n",
    "\n",
    "At the moment, it is required to be at the top-level `pyro/` directory, because not all the functions find pyro's home directory on their own."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyro import Pyro"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## advection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"advection\"\n",
    "problem_name = \"smooth\"\n",
    "param_file = \"inputs.smooth\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the smooth advection problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bf6686668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.10000    0.10000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee841ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "main:  0.5435585975646973\n",
      "   vis:  0.1849346160888672\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<advection.simulation.Simulation at 0x7f6bf6699048>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee820438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         1         1         1    1.0004    1.0014    1.0013    1.0002         1 \n",
      "         1         1    1.0003    1.0162    1.0626    1.0579    1.0077    1.0002 \n",
      "         1    1.0002    1.0116     1.185    1.5348    1.4466    1.0579    1.0013 \n",
      "         1    1.0001    1.0064    1.2169    1.6258    1.5348    1.0626    1.0014 \n",
      "         1   0.99994    0.9985     1.085    1.2169     1.185    1.0162    1.0004 \n",
      "         1   0.99995   0.99797    0.9985    1.0064    1.0116    1.0003         1 \n",
      "         1         1   0.99995   0.99994    1.0001    1.0002         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"density\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## advection_nonuniform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"advection_nonuniform\"\n",
    "problem_name = \"slotted\"\n",
    "param_file = \"inputs.slotted\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the slotted advection problem...\u001b[0m\n",
      "extrema:  0.46875 -0.46875\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.45714    0.45714\n",
      "\u001b[33moutputting...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWEAAAEaCAYAAADAGubVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAF35JREFUeJzt3X+wbWV93/H3515FioiINxoLCKiQSoiNegvaTBpafxSpA6kaA9YoHcZbTbG2QiyJiWFI4iRaY+tIEq+GKmZUkMnQWyUhanC0Rsi9Av4AB73iDy7+IIigxhHuPefbP/Y6zOawzznrXPbezz7b94tZc/da69lrffc+h+96zrOe51mpKiRJbWxqHYAk/SQzCUtSQyZhSWrIJCxJDZmEJakhk7AkNWQSlrShJHl3kt+f4PFvTHLypI6/3EOmdSJJ2giq6meXXie5AHhSVb10UuezJixJDZmEJc20JE9Ncl2SHyS5FDhwaN/zk9yQ5K4kf5fkKUP7vpbkvCSfS3J3kkuTHNjt25LkQ9377kzyySSbht737CSnAL8F/GqSHyb5bJJfSfKZZfG9Nsn/2d/PZxKWNLOSHABcAbwXOAz4IPDCbt9TgYuB/wQ8GngHsCPJw4YO8WLgFOAY4CnAWd32c4E9wE8Bj2WQbO83h0NV/TXwRuDSqjq4qv45sAM4JsmTh4r+GnDJ/n5Gk7CkWfYM4KHA/6yqvVV1ObCz27cNeEdVXVtVC1X1HuCe7j1L3lZV36yqO4H/C/x8t30v8DjgqO64n6weE+lU1T3ApcBLAZL8LHA08KH9/YAmYUmz7J8Cty1LkF/v/j0KOLdrUrgryV3Akd17lnx76PWPgIO7128GdgN/k+SWJOevI6b3AC9JEga14Mu65LxfTMKSZtm3gMO7hLfk8d2/twJ/UFWHDi0HVdX71zpoVf2gqs6tqicApwGvTfKsUUVHvPca4F7gF4GXMGgq2W8mYUmz7NPAPuC/JHlokhcAJ3b73gm8MslJGXh4kn+X5BFrHbS7ofekLrnfDSwAiyOKfgc4eumm3ZBLgLcDe6vq/+3nZwNMwpJmWFXdC7yAwQ21O4FfBf6y27cLeAWDZPg9Bs0LZ/U89LHAR4EfMkj0f1JVV48o98Hu3+8muW5o+3uBE4C/6P9pRouTukvS+iT5J8DtwNOq6ssP5ljWhCVp/V4F7HywCRhMwiMluTjJ7Um+sML+JHlbkt1dR/CnTTtGSW0k+RrwGgZ9jR80k/Bo72bQwXslz2PQpnQsg76KfzqFmCTNgKo6uqqOqqrrx3E8k/AIVfUJBjcBVnI6cEkNXAMcmuRx04lO0jxxFrX9cziDPopL9nTbvtUmHEmjJHl637JV9Zm1S42fSXjCkmxj0GTBZjY//SAOaRzRxpdNU/wD7n5jBCarFhamdq559WP+kXvrnvt+aI88ZNOuxz12c6/3Jrmjqn5qYsGtwCS8f25jMDxyyRHdtgeoqu3AdoBDclidNHJQjtZj08Fr9sUfm2yeXsJfuOvuqZ1rXl1bH7vf+pOOfih/f9XjVyh9f5sf9+Wvr11q/GwT3j87gJd1vSSeAdxdVTZFSDOmgMWe/7ViTXiEJO8HTga2JNkD/C6DmZyoqj8DrgROZTBC50fAf2wTqaTVFQvVLsH2YRIeoarOXGN/Af95SuFI2k8F7GO229pNwpLmVlEszPjUDCZhSXNt8YGzUc4Uk7CkuVXAgklYktqxJixJjRSw1zZhSWqjKJsjJKmZgoXZzsEmYUnzazBibraZhCXNsbDA9CZh2h8mYUlzq4BFmyMkqY0C7p3xecpMwpLm2mLZHCFJTQxGzJmEJamJIizYHCFJ7dgcIUmNFOHe6veMuVZMwpLm1mCwhs0RktSMN+YkqZGqsFDWhCWpmUVrwpLUxqCfsDVhaaxued0JUzvXFb/2lqmd65ffe+7UznX073x6audqqQh7a7bT3GxHJ0kP0oL9hCWpDUfMSVJji/aOkKQ2vDEnSQ0VsU1Yklqpwt4RktROHKwhSa0UOGxZklqa9Rtzsx2dJD0IRVisfksfSU5JcnOS3UnOH7H/8UmuTnJ9ks8lOXWtY1oTljS3ivHdmEuyGbgIeA6wB9iZZEdV3TRU7LeBy6rqT5McD1wJHL3aca0JS5pjYaHn0sOJwO6quqWq7gU+AJy+rEwBh3SvHwl8c62DWhOWNLeKsY6YOxy4dWh9D3DSsjIXAH+T5NXAw4Fnr3VQa8IrmETbj6TpW0dNeEuSXUPLtv043ZnAu6vqCOBU4L1JVs2z1oRHmFTbj6Tpqsp6asJ3VNXWVfbfBhw5tH5Et23Y2cApg3PXp5McCGwBbl/poNaER5tI24+k6VuoTb2WHnYCxyY5JskBwBnAjmVlvgE8CyDJk4EDgX9Y7aDWhEcbW9tP9yfNNoADOWjsgUpa2WBS9/E88r6q9iU5B7gK2AxcXFU3JrkQ2FVVO4BzgXcm+W8MKmpnVVWtdlyT8P5bavt5S5JnMmj7OaGqFocLVdV2YDvAITls1R+GpPEa3Jgb37DlqrqSQdPj8LY3DL2+CfiF9RzTJDzaRNp+JE2fI+Y2pom0/UiarnGPmJsEa8IjTKrtR9L0Lc54XdMkvIJJtP1Imq4qH/QpSc0UYd/ieHpHTIpJWNJc6zkvRDMmYUlza9xd1CbBJCxpjq1r2HITJmFJc81nzEljtvCEH0/tXE8+YHpDzQ+4e7aTxUZUBXu9MSdJbSwN1phlJmFJc83mCElqxN4RktSYvSMkqZXGk/P0YRKWNLcK2GdNWJLasE1YkhozCUtSI/YTlqTG7CcsSa2UzRGS1EwB+xbtHSFJTdgmLEmNlUlYktrxxpwkNVLemJOklsKCN+YkqR3bhCWpEeeOkKSWatAuPMtMwpLmmr0jJKmRwjZhSWooLCyahCWpGWvCktRIlUlYkpqyi5o0Zk/8D9dP7VynHvfCqZ3r8d//ytTOtW9qZ2pvnF3UkpwC/C9gM/CuqvrDEWVeDFzA4L7gZ6vqJasd0yQsaW4VYXFMw5aTbAYuAp4D7AF2JtlRVTcNlTkW+E3gF6rqe0kes9ZxZ3tQdSNJTklyc5LdSc5focyLk9yU5MYk75t2jJL6qZ5LDycCu6vqlqq6F/gAcPqyMq8ALqqq7wFU1e1rHdSa8DKTutpJamB9N+a2JNk1tL69qrYPrR8O3Dq0vgc4adkxjgNI8ikGTRYXVNVfr3ZSk/AD3Xe1A0iydLW7aajMuq92khrp3yZ8R1VtfZBnewhwLHAycATwiSQ/V1V3rfQGmyMeaNTV7vBlZY4DjkvyqSTXdI31kmZQVXotPdwGHDm0fkS3bdgeYEdV7a2qrwJfYpCUV2QS3j/DV7szgXcmOXRUwSTbkuxKsmsv90wxREmw1Fd47aWHncCxSY5JcgBwBrBjWZkrGOQFkmxhUGG7ZbWDmoQfaKxXu6raXlVbq2rrQ3nYRAKWNFoV1OKmXsvax6p9wDnAVcAXgcuq6sYkFyY5rSt2FfDdJDcBVwO/UVXfXe24tgk/0H1XOwbJ9wxgeT+/KxjUgP9336udpDbG2U+4qq4Erly27Q1Drwt4bbf0Yk14mUld7SQ1MsY+apNgTXiESVztJLXQ+6ZbMyZhSfPNJ2tIUiPOoiZJjZmEJakhmyMkqSGTsCQ1UtgcIUktjXOwxiSYhCXNN5+2LEntxJqwJDXSeEhyHyZhSXMs3piTpKasCUtSQyZhSWqksHeEJLU0670j5npS9ySvTvKo1nFIashJ3Zt6LLAzyXXAxcBV3YTsUi8LX/pK6xA05+a6JlxVv83gAZx/DpwFfDnJG5M8sWlgkqYm1W9pZa6TMNz3KKJvd8s+4FHA5Une1DQwSdNR6bc0MtfNEUleA7wMuAN4F4MHcu5Nsgn4MvC6lvFJmrACFlsHsbq5TsLAYcALqurrwxurajHJ8xvFJGmKZr13xFwn4ar63VX2fXGasUhqxCQsSQ2ZhCWpjdY9H/owCUuabw5blqR2rAlLUksmYUlqxDZhSWrMJCxJDZmEJakdmyMkqSWTsCQ1sgFuzM39VJaSfsKN8ckaSU5JcnOS3UnOX6XcC5NUkq1rHdMkLGm+jSkJJ9kMXAQ8DzgeODPJ8SPKPQJ4DXBtn/BMwiuYxBVP0nSFsT5Z40Rgd1XdUlX3Ah8ATh9R7veAPwJ+3OegJuERJnXFkzRlBVnst/RwOHDr0Pqebtt9kjwNOLKqPtw3RJPwaBO54klqoH9zxJYku4aWbes5TffEnj8Gzl3P++wdMdqoK95JwwWGr3hJfmOlA3U/yG0AB3LQBEKVtKr+vSPuqKrVmhVvA44cWj+i27bkEcAJwMeTAPw0sCPJaVW1a6WDmoT3w9AV76y1ylbVdmA7wCE5bMY7y0jzZ4xd1HYCxyY5hkHyPQN4ydLOqrob2HLfeZOPA+etloDB5oiVrOeK9zXgGQyueN6ck2bNmHpHVNU+4BzgKuCLwGVVdWOSC5Octr/hWRMebSJXPElTVr1vuvU7XNWVwJXLtr1hhbIn9zmmNeERJnXFk9TAGAdrTII14RVM4oonafpmfdiySVjSfDMJS1IjjZsa+jAJS5pb6ZZZZhKWNNfG2TtiEkzCkuabzRGS1JBJWJIa2QBP1jAJS5pvJmFJaseasCQ1ZO8ISWrFwRqS1JhJWJLaWHrQ5ywzCUuabyZhSWqkIIuznYVNwpLmms0RktSSSViS2rEmLEktmYQlqREn8JGkdoLDliWprZrtqrBJWNJcszlCklpxAh9Jass2YUlqyCQsSa0U3piTpJa8MSdJLZmEJakNJ3WXpJaqbBOWpJbsHSFJDc16c8Sm1gFI0sQUsFj9lh6SnJLk5iS7k5w/Yv9rk9yU5HNJPpbkqLWOaRIeYRJftKRGqueyhiSbgYuA5wHHA2cmOX5ZseuBrVX1FOBy4E1rHdckvMykvmhJbaT6LT2cCOyuqluq6l7gA8DpwwWq6uqq+lG3eg1wxFoHNQk/0ES+aEmNLPWQWGtZ2+HArUPre7ptKzkb+Ku1DuqNuQca9UWftEr5Xl+0pAZqXb0jtiTZNbS+vaq2789pk7wU2Ar80lplTcIPQp8vOsk2YBvAgRw0pcgkwdJgjd7dI+6oqq2r7L8NOHJo/Yhu2/3PmTwbeD3wS1V1z1ontTnigdb7RZ+22hddVduramtVbX0oDxt7sJLWsNhzWdtO4NgkxyQ5ADgD2DFcIMlTgXcwyAu39zmoSfiBJvJFS2ojVb2WtVTVPuAc4Crgi8BlVXVjkguTnNYVezNwMPDBJDck2bHC4e5jc8QyVbUvydIXvRm4eOmLBnZV1Q7u/0UDfKOqTlvxoJLaGPOTNarqSuDKZdveMPT62es9pkl4hEl80ZJaKNJzIEYrJmFJ880JfCSpkfV1UWvCJCxpvlkTlqSGZjsHm4Qlzbd1DNZowiQsaX4VsGASlqQmQr+BGC2ZhCXNN5OwJDVkEpakRoq+k/M0YxKWNNdsE5akZgoWZ7sqbBKWNL8K24QlqanZrgibhCXNN9uEJaklk7AkNVIFC7PdHmESljTfrAlLUkMmYUlqpACfMSdJrRSUbcKS1I7NEZLUSGHvCElqypqwJLVSJmFJaqZwFjVJasqasCQ1ZBKWpEaqqIWF1lGsyiQsab45Yk6SGrI5QpIaKZ8xJ0ltWROWpFa8MSdJ7WyAqSw3tQ5gViU5JcnNSXYnOX/E/oclubTbf22So6cfpaQ11WK/pYdJ5AWT8AhJNgMXAc8DjgfOTHL8smJnA9+rqicBbwX+aLpRSlpLAbVYvZa1TCov2Bwx2onA7qq6BSDJB4DTgZuGypwOXNC9vhx4e5JUzfhdAOknyGLt5fuLd4zrcBPJCybh0Q4Hbh1a3wOctFKZqtqX5G7g0cD9fuJJtgHbutV7PlqXf2EiEY/fFpZ9lhm3keLdSLHCxor3Z4ZX/pEf3HXtwke+1fe9SXYNrW+vqu1D62PLC8NMwhPW/RC3AyTZVVVbG4fUy0aKFTZWvBspVthY8S5LolTVo1rF0pdtwqPdBhw5tH5Et21kmSQPAR4JfHcq0UlqYSJ5wSQ82k7g2CTHJDkAOAPYsazMDuDl3esXAX9re7A01yaSF2yOGKFryzkHuArYDFxcVTcmuRDYVVU7gD8H3ptkN3Angx/IWravXWRmbKRYYWPFu5FihY0V78RinVReiJU3SWrH5ghJasgkLEkNmYTHbKMNd+4R72uT3JTkc0k+luSoFnF2sawa61C5FyapJE27VfWJN8mLu+/3xiTvm3aMQ3Gs9Xvw+CRXJ7m++104tUWcXSwXJ7k9ycg+9xl4W/dZPpfkadOOcV2qymVMC4PG+q8ATwAOAD4LHL+szK8Df9a9PgO4dMbj/dfAQd3rV7WKt0+sXblHAJ8ArgG2zvh3eyxwPfCobv0xMxzrduBV3evjga81/G7/FfA04Asr7D8V+CsgwDOAa1vF2mexJjxe9w1rrKp7gaVhjcNOB97Tvb4ceFaSTDHGYWvGW1VXV9WPutVrGPSNbKHPdwvwewzG6/94msGN0CfeVwAXVdX3AKrq9inHuKRPrAUc0r1+JPDNKcZ3/0CqPsGg58FKTgcuqYFrgEOTPG460a2fSXi8Rg1rPHylMlW1D1ga1thCn3iHnc2ghtHCmrF2f3YeWVUfnmZgK+jz3R4HHJfkU0muSXLK1KK7vz6xXgC8NMke4Erg1dMJbb+s9/e6KfsJq5ckLwW2Ar/UOpZRkmwC/hg4q3Eo6/EQBk0SJzP4C+MTSX6uqu5qGtVoZwLvrqq3JHkmg76wJ1T1nANSK7ImPF4bbbhzn3hJ8mzg9cBpVXXPlGJbbq1YHwGcAHw8ydcYtAXuaHhzrs93uwfYUVV7q+qrwJcYJOVp6xPr2cBlAFX1aeBABhP7zKJev9ezwiQ8XhttuPOa8SZ5KvAOBgm4VZslrBFrVd1dVVuq6uiqOppB+/VpVbVr9OEmrs/vwhUMasEk2cKgeeKWaQbZ6RPrN4BnASR5MoMk/A9TjbK/HcDLul4SzwDurqq+M6lNX+s7g/O2MLgz+yUGd5tf3227kEFCgMEv7weB3cDfA0+Y8Xg/CnwHuKFbdsxqrMvKfpyGvSN6frdh0IRyE/B54IwZjvV44FMMek7cADy3YazvB74F7GXw18TZwCuBVw59rxd1n+XzrX8P1loctixJDdkcIUkNmYQlqSGTsCQ1ZBKWpIZMwpLUkElYkhoyCUtSQyZhaZkk/6Kbh/bAJA/v5vo9oXVcmk+rJuEkhyb59WkF053z5Um+3C0vX6Psud3k3Vu69ZOT3J3khm55Q7f9Z4a23ZDk+0n+a7fvV7r/yRZHzTPQTWb9wyTnTeLzavZU1U4GQ19/H3gT8BdVNXICcenBWnXEXPfUhw9V1VRqAUkOA3YxmK2rgM8AT69uvtVlZY8E3gX8s67MHUlOBs6rquevco7NDCbzOKmqvt6Ng19kMD/CebVsroEkl3exXFtV/2MMH1MbQDeHwk4G8xL/y6paaByS5tRazRF/CDyxqz2+eQrx/FvgI1V1Z5d4PwKsNMfqW4HXMUiQ6/Es4CtV9XWAqvpiVd08qmCSXwa+Cty4znNo43s0cDCD2dkObByL5tha8wmfD5xQVT8/ameSTzL4JV3uvKr66H7E02sy5iSnA7dV1WdHPJTimUk+y2Dm//OqankCPYPBBCCrSnIw8N+B5wA2RfzkeQfwO8AxDJ7UcU7bcDSvHtSk7lX1i+MKpK8kBwG/BTx3xO7rgKOq6ofdgwivYGh+1u5PzNOA3+xxqguAt3bHetBxa+NI8jJgb1W9r2u++rsk/6aq/rZ1bJo/DyoJT6AmfBvd/KqdIxhMSTjsiQxqJ0u14COA65KcWFXfXipUVVcm+ZMkW6rqjm7z84Drquo7PWI5CXhRkjcBhwKLSX5cVW/fj8+lDaSqLgEu6V4vMPhdkCZirST8A0YnWWAiNeGrgDcmeVS3/lyW1Vqr6vPAY5bWu6cobO1uzP008J2qqiQnMmjzHn5qxZn0aIroznPfZ0tyAfBDE7CkcVv1xlxVfRf4VJIvTOPGXFXdyeBpuTu75cJuG0ne1eNRNS8CvtC1Cb+NwSTZ1b3/4Qzad/9y+A1J/n338MJnAh9OctU4P5MkrcZJ3SWpIUfMSVJDJmFJasgkLEkNmYQlqSGTsCQ1ZBKWpIZMwpLUkElYkhr6/0tpNQjJyPxbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter advection.u never used\u001b[0m\n",
      "\u001b[33mparameter advection.v never used\u001b[0m\n",
      "main:  0.40372467041015625\n",
      "   vis:  0.11815953254699707\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<advection_nonuniform.simulation.Simulation at 0x7f01475a5240>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         0         0         0  0.035918  0.045714         0         0         0 \n",
      "         0         0         0   0.44163   0.91837   0.44082         0         0 \n",
      "         0         0         0   0.58204   0.98041   0.38204         0         0 \n",
      "         0         0         0         0   0.10776  0.065306         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"density\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## advection_fv4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"advection_fv4\"\n",
    "problem_name = \"smooth\"\n",
    "param_file = \"inputs.smooth\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the smooth FV advection problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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/kYACAADAViSgAAAAFnD5+BlQf/0UpxWC55sAAAAgIJCAAgAAWMBlWsnlw62TfNmXvwXPNwEAAEBAIAEFAACwQJ0cqpPvVq77si9/owAFAACwAFPw3gXPNwEAAEBAIAEFAACwQJ18O21e57Oe/I8EFAAAALYiAQUAALAAz4B6FzzfBAAAAAGBAjQA5eTkqEePHoqIiFBiYqK2b9/eaPvs7Gz17t1brVu3Vnx8vObNm6evv/7aptECAHBxqjOtfH4EC6bgA8yGDRs0d+5c5eTkaPjw4Xr66aeVmpqqvXv3qlu3bvXav/DCC1qwYIGeeeYZDRs2TP/4xz/085//XJL0+OOP2zx6AAAuHkYOuXy4CMkE0T6gwVNKXySWL1+uadOmafr06erbt6+ys7MVHx+vlStXNti+sLBQw4cP189+9jN1795dKSkpmjx5snbv3m3zyAEAAM6iAA0g1dXVKioqUkpKisf5lJQU7dy5s8Frrr76ahUVFendd9+VJB04cEB5eXkaN26c18+pqqpSZWWlxwEAAJqHKXjvmIIPIMeOHVNdXZ2io6M9zkdHR6uioqLBayZNmqTPPvtMV199tYwxqq2t1V133aUFCxZ4/ZysrCw98MADPh07AADAOcFTSl9EHA7PZ0CMMfXOnVNQUKCHH35YOTk5ev/99/XKK6/o9ddf14MPPui1/8zMTJ08edJ9lJWV+XT8AABcDFzG4fMjWJCABpBOnTopJCSkXtp59OjReqnoOYsWLVJ6erqmT58uSRowYIDOnDmjO+64QwsXLlSrVvX/DeJ0OuV0On3/BQAAAEQCGlDCw8OVmJio/Px8j/P5+fkaNmxYg9d8+eWX9YrMkJAQGWNkjLFsrAAAXOzq1MrnR7AgAQ0wGRkZSk9PV1JSkpKTk7Vq1SqVlpZqxowZkqQpU6aoa9euysrKkiSlpaVp+fLlGjx4sIYMGaKPP/5YixYt0k033aSQkBB/fhUAAIKar6fNmYKH30ycOFHHjx/XkiVLVF5erv79+ysvL08JCQmSpNLSUo/E87777pPD4dB9992nI0eOqHPnzkpLS9PDDz/sr68AAAAucg7DPCy+R2VlpaKiojRS4xXqCPP3cADvvCzGQwDhryRc4GpNjQr0qk6ePKnIyMgG25z7e3P2jn+Xs63v/t6sOl2jJ6/e2OhnB4rgeZgAAAAAAYEpeAAAAAvUGYfqfPjcpi/78jcSUAAAANiKBBQAAMACrIL3jgQUAAAAtiIBBQAAsIAxreQyvsv6jA/78jcKUAAAAAvUyaE6+XARkg/78rfgKaUBAAAQEEhAAQAALOAyvl045Aqi32kgAQUAAICtSEABAAAs4PLxIiRf9uVvwfNNAAAAEBBIQAEAACzgkkMuH65c92Vf/kYBCgAAYAF+C947puABAABgKxJQ4CLRql07fw/BcjVJl/t7CDhPYbv3+3sIlnOdOuXvIcAmLELyLni+CQAAAAICCSgAAIAFXHL4diP6IFqERAIKAAAAW5GAAgAAWMD4eBsmE0QJKAUoAACABVzGx1PwbMMEAAAAtAwJKAAAgAXYhsm74PkmAAAACAgkoAAAABbgGVDvSEABAABgKxJQAAAAC7h8vA0TG9EDAAAALUQCCgAAYAGeAfWOAhQAAMACFKDeMQUPAAAAW5GAAgAAWIAE1DsSUAAAANiKBBQAAMACJKDekYACAADAViSgAAAAFjDy7ebxxmc9+R8FKAAAgAWYgveOKXgAAADYigQUAADAAiSg3pGAAgAAwFYkoAAAABYgAfWOBBQAAAC2IgEFAACwAAmodxSgAAAAFjDGIePDotGXffkbU/AAAACwFQkoAACABVxy+PSXkHzZl7+RgAIAAMBWJKAAAAAWYBGSdySgAAAAsBUJKAAAgAVYBe8dCSgAAABsRQIKAABgAZ4B9Y4CFAAAwAJMwXvHFDwAAABsRQIKAABgAePjKXgSUAAAAKCFSEABAAAsYCQZ49v+ggUJKAAAAGxFAgoAAGABlxxyyIfbMPmwL3+jAAUAALAA2zB5xxQ8AAAAbEUCCgAAYAGXccjBLyE1iAQUAAAAtiIBBQAAsIAxPt6GKYj2YSIBBQAAgK1IQAEAACzAKnjvKEABAAAsQAHqHVPwAAAAsBUJKAAAgAXYhsk7ElAAAADYigQUAADAAmzD5B0JKAAAAGxFAgqc4wieZ2saUpN0ub+HYLktLzzj7yHgPI2+9f/4ewiWCyko9vcQrBVMMd15OpuA+nIVvM+68jsSUAAAANiKBBQAAMAC7APqHQUoAACABcw3hy/7CxZMwQMAAMBWJKAAAAAWYAreOxJQAACAILVt2zalpaUpLi5ODodDmzZtarT9jh07NHz4cHXs2FGtW7dWnz599Pjjj3u0Wbx4sRwOh8cRExPTrHGRgAIAAFjhAngI9MyZMxo0aJBuv/12/fSnP/3e9m3atNHs2bM1cOBAtWnTRjt27NCdd96pNm3a6I477nC3u+KKK7Rlyxb365CQkGaNiwQ0AOXk5KhHjx6KiIhQYmKitm/f3mj7EydOaNasWYqNjVVERIT69u2rvLw8m0YLAAD8JTU1VQ899JB+8pOfNKn94MGDNXnyZF1xxRXq3r27brvtNo0dO7ZerREaGqqYmBj30blz52aNiwI0wGzYsEFz587VwoULVVxcrBEjRig1NVWlpaUNtq+urtaYMWN06NAhvfzyy/roo4+0evVqde3a1eaRAwBwkfnmGVBfHfrmGdDKykqPo6qqyrKvUFxcrJ07d+raa6/1OL9//37FxcWpR48emjRpkg4cONCsfilAA8zy5cs1bdo0TZ8+XX379lV2drbi4+O1cuXKBts/88wz+vzzz7Vp0yYNHz5cCQkJuvrqqzVo0CCbRw4AwMXl3G/B+/KQpPj4eEVFRbmPrKwsn4/9sssuk9PpVFJSkmbNmqXp06e73xsyZIiee+45vfnmm1q9erUqKio0bNgwHT9+vMn98wxoAKmurlZRUZEWLFjgcT4lJUU7d+5s8JrXXntNycnJmjVrll599VV17txZP/vZz/TrX//a6/MaVVVVHv+aqqys9N2XAAAA56WsrEyRkZHu106n0+efsX37dp0+fVq7du3SggUL9IMf/ECTJ0+WdHZa/5wBAwYoOTlZvXr10rPPPquMjIwm9U8BGkCOHTumuro6RUdHe5yPjo5WRUVFg9ccOHBAf/vb33TrrbcqLy9P+/fv16xZs1RbW6vf/OY3DV6TlZWlBx54wOfjBwDgYmLVNkyRkZEeBagVevToIelsgfnpp59q8eLF7gL0u9q0aaMBAwZo//79Te6fKfgA5HB4/mE2xtQ7d47L5VKXLl20atUqJSYmatKkSVq4cKHXKXtJyszM1MmTJ91HWVmZT8cPAAAChzGm0edMq6qqtG/fPsXGxja5TxLQANKpUyeFhITUSzuPHj1aLxU9JzY2VmFhYR7T7X379lVFRYWqq6sVHh5e7xqn02lJnA8AwEXlWwuHfNZfM50+fVoff/yx+/XBgwdVUlKiDh06qFu3bsrMzNSRI0f03HPPSZJWrFihbt26qU+fPpLO7gu6bNky3X333e4+5s+fr7S0NHXr1k1Hjx7VQw89pMrKSk2dOrXJ46IADSDh4eFKTExUfn6+/v3f/919Pj8/X+PHj2/wmuHDh+vFF1+Uy+VSq1ZnA+9//OMfio2NbbD4BAAAwWP37t0aNWqU+/W5ZzSnTp2qtWvXqry83GMnHZfLpczMTB08eFChoaHq1auXHnnkEd15553uNp988okmT56sY8eOqXPnzho6dKh27dqlhISEJo+LAjTAZGRkKD09XUlJSUpOTtaqVatUWlqqGTNmSJKmTJmirl27ulfE3XXXXfrP//xPzZkzR3fffbf279+vpUuX6p577vHn1wAAIOh9e+W6r/prrpEjR8o0cuHatWs9Xt99990eaWdD1q9f3/yBfAcFaICZOHGijh8/riVLlqi8vFz9+/dXXl6e+18dpaWl7qRTOrtVw+bNmzVv3jwNHDhQXbt21Zw5c/TrX//aX18BAICLwwXwS0gXKgrQADRz5kzNnDmzwfcKCgrqnUtOTtauXbssHhUAAEDTUIACAABYwKptmIIB2zABAADAViSgAAAAVgmi5zZ9iQQUAAAAtiIBBQAAsADPgHpHAgoAAABbkYACAABYgX1AvaIABQAAsITjm8OX/QUHpuABAABgKxJQAAAAKzAF7xUJKAAAAGxFAgoAAGAFElCvSEABAABgKxJQAAAAKxjH2cOX/QUJClAAAAALGHP28GV/wYIpeAAAANiKBBQAAMAKLELyigQUAAAAtiIBBQAAsAKLkLwiAQUAAICtSEABAAAs4DBnD1/2FywoQAEAAKzAIiSvmIIHAACArUhAAQAArMAiJK9IQAEAAGArElAAAAAr8AyoVySgAAAAsBUJKAAAgBVIQL0iAQUAAICtSEABAACsQALqFQUoAACAFdiGySum4AEAAGArElAAAAAL8Fvw3pGAAgAAwFYkoAAAAFZgEZJXJKAAAACwFQWoDX7+859r27Zt/h4GAADABYEC1AanTp1SSkqKLr/8ci1dulRHjhzx95AAAIDFHPr/C5F8cvj7C/kQBagNcnNzdeTIEc2ePVsvvfSSunfvrtTUVL388suqqanx9/AAAABsRQFqk44dO2rOnDkqLi7Wu+++qx/84AdKT09XXFyc5s2bp/379/t7iAAAwJfObUTvyyNIUIDarLy8XJs3b9bmzZsVEhKiG264QR9++KH69eunxx9/3N/DAwAAsBwFqA1qamqUm5urG2+8UQkJCXrppZc0b948lZeX69lnn9XmzZv1/PPPa8mSJf4eKgAA8BVjwREk2AfUBrGxsXK5XJo8ebLeffddXXnllfXajB07VpdeeqkfRgcAAGAvClAbPP744/qP//gPRUREeG3Tvn17HTx40MZRAQAAS7ERvVcUoDZIT0/39xAAAAAuGBSgAAAAFji3f6cv+wsWFKAAAABWYAreK1bBAwAAwFYkoAAAAFYgAfWKBBQAAAC2IgEFAACwAIuQvCMBBQAAgK1IQAEAAKxgHGcPX/YXJChAAQAArMAiJK+YggcAAICtSEABAAAswCIk70hAAQAAYCsSUAAAACvwDKhXJKAAAACwFQkoAACAFXz8DGgwJaAUoAAAAFZgCt4rpuABAABgKxJQAAAAK5CAekUCCgAAAFuRgAIAAFiAjei9IwEFAACArShAAQAAYCsKUAAAANiKZ0ABAACswCp4ryhAAQAALMAiJO+YggcAAICtSEABAACsEkSppS+RgAIAAMBWJKAAAABWYBGSVySgAAAAsBUJKAAAgAVYBe8dBSgAAIAVmIL3iil4AAAA2IoEFAAAwAJMwXtHAgoAAABbUYAGoJycHPXo0UMRERFKTEzU9u3bm3Td+vXr5XA4dPPNN1s8QgAA4H4G1JdHkKAADTAbNmzQ3LlztXDhQhUXF2vEiBFKTU1VaWlpo9cdPnxY8+fP14gRI2waKQAAQMMoQAPM8uXLNW3aNE2fPl19+/ZVdna24uPjtXLlSq/X1NXV6dZbb9UDDzygnj17fu9nVFVVqbKy0uMAAADNRALqFQVoAKmurlZRUZFSUlI8zqekpGjnzp1er1uyZIk6d+6sadOmNelzsrKyFBUV5T7i4+PPa9wAAFyMzi1C8uURLChAA8ixY8dUV1en6Ohoj/PR0dGqqKho8Jq3335ba9as0erVq5v8OZmZmTp58qT7KCsrO69xAwAAfBvbMAUgh8Ph8doYU++cJJ06dUq33XabVq9erU6dOjW5f6fTKafTed7jBADgosZG9F5RgAaQTp06KSQkpF7aefTo0XqpqCT985//1KFDh5SWluY+53K5JEmhoaH66KOP1KtXL2sHDQAA8B1MwQeQ8PBwJSYmKj8/3+N8fn6+hg0bVq99nz599MEHH6ikpMR93HTTTRo1apRKSkp4thMAACuxCMkrEtAAk5GRofT0dCUlJSk5OVmrVq1SaWmpZsyYIUmaMmWKunbtqqysLEVERKh///4e11966aWSVO88AACAXShAA8zEiRN1/PhxLVmyROXl5erfv7/y8vKUkJAgSSotLVWNQ7VxAAAenElEQVSrVgTbAAD4Gz/F6R0FaACaOXOmZs6c2eB7BQUFjV67du1a3w8IAACgGShAAQAArMAqeK8oQAEAACzAFLx3PCwIAAAAW5GAAueYIPqnZQPCdu/39xAsN/rW/+PvIeA8XQx/Tl1B/t8afAtT8F6RgAIAAMBWJKAAAABWIAH1igQUAAAAtiIBBQAAsIDjm8OX/QULClAAAAArMAXvFVPwAAAAsBUJKAAAgAXYiN47ElAAAADYigQUAADACjwD6hUJKAAAQJDatm2b0tLSFBcXJ4fDoU2bNjXa/pVXXtGYMWPUuXNnRUZGKjk5WW+++Wa9djk5OerRo4ciIiKUmJio7du3N2tcFKAAAABWMT48WuDMmTMaNGiQnnzyySa137Ztm8aMGaO8vDwVFRVp1KhRSktLU3FxsbvNhg0bNHfuXC1cuFDFxcUaMWKEUlNTVVpa2uRxMQUPAABggQthEVJqaqpSU1Ob3D47O9vj9dKlS/Xqq6/qz3/+swYPHixJWr58uaZNm6bp06e7r3nzzTe1cuVKZWVlNelzSEABAAACSGVlpcdRVVVl2We5XC6dOnVKHTp0kCRVV1erqKhIKSkpHu1SUlK0c+fOJvdLAQoAAGAFX06/f2saPj4+XlFRUe6jqaljS/zud7/TmTNnNGHCBEnSsWPHVFdXp+joaI920dHRqqioaHK/TMEDAAAEkLKyMkVGRrpfO51OSz5n3bp1Wrx4sV599VV16dLF4z2Hw/OHQY0x9c41hgIUAADAAlY9AxoZGelRgFphw4YNmjZtml566SWNHj3afb5Tp04KCQmpl3YePXq0XiraGKbgAQAA4LZu3Tr9/Oc/14svvqhx48Z5vBceHq7ExETl5+d7nM/Pz9ewYcOa/BkkoAAAAFa4ADaiP336tD7++GP364MHD6qkpEQdOnRQt27dlJmZqSNHjui5556TdLb4nDJlip544gkNHTrUnXS2bt1aUVFRkqSMjAylp6crKSlJycnJWrVqlUpLSzVjxowmj4sCFAAAIEjt3r1bo0aNcr/OyMiQJE2dOlVr165VeXm5x/6dTz/9tGprazVr1izNmjXLff5ce0maOHGijh8/riVLlqi8vFz9+/dXXl6eEhISmjwuClAAAAALXAj7gI4cOVLGeL/wXFF5TkFBQZP6nTlzpmbOnNn8AX2DAhQAAMAKF8AU/IWKRUgAAACwFQkoAACAFUhAvSIBBQAAgK1IQAEAACxwISxCulCRgAIAAMBWJKAAAABW4BlQryhAAQAALOAwRo5G9uBsSX/Bgil4AAAA2IoEFAAAwApMwXtFAgoAAABbkYACAABYgG2YvCMBBQAAgK1IQAEAAKzAM6BeUYACAABYgCl475iCBwAAgK1IQAEAAKzAFLxXJKAAAACwFQkoAACABXgG1DsSUAAAANiKBBQAAMAKPAPqFQkoAAAAbEUCCgAAYJFgem7TlyhAAQAArGDM2cOX/QUJpuABAABgKxJQAAAAC7ANk3ckoAAAALAVCSgAAIAV2IbJKxJQAAAA2IoEFAAAwAIO19nDl/0FCwpQAAAAKzAF7xVT8AAAALAVCSgAAIAF2IbJOxJQAAAA2IoEFAAAwAr8FKdXJKAAAACwFQkocJFwnTrl7yFYLqSg2N9DwHlyBVHCA/AMqHcUoAAAAFZgGyavmIIHAACArUhAAQAALMAUvHckoAAAALAVCSgAAIAV2IbJKxJQAAAA2IoEFAAAwAI8A+odCSgAAABsRQIKAABgBfYB9YoCFAAAwAJMwXvHFDwAAABsRQIKAABgBZc5e/iyvyBBAgoAAABbkYACAABYgUVIXpGAAgAAwFYkoAAAABZwyMer4H3Xld9RgAIAAFiB34L3iil4AAAA2IoCNADl5OSoR48eioiIUGJiorZv3+617erVqzVixAi1b99e7du31+jRo/Xuu+/aOFoAAC5O5zai9+URLChAA8yGDRs0d+5cLVy4UMXFxRoxYoRSU1NVWlraYPuCggJNnjxZb731lgoLC9WtWzelpKToyJEjNo8cAADgLArQALN8+XJNmzZN06dPV9++fZWdna34+HitXLmywfYvvPCCZs6cqSuvvFJ9+vTR6tWr5XK59Ne//tXmkQMAcJExFhxBggI0gFRXV6uoqEgpKSke51NSUrRz584m9fHll1+qpqZGHTp08NqmqqpKlZWVHgcAAICvUIAGkGPHjqmurk7R0dEe56Ojo1VRUdGkPhYsWKCuXbtq9OjRXttkZWUpKirKfcTHx5/XuAEAuBg5jPH5ESwoQAOQw+G5E5gxpt65hvz2t7/VunXr9MorrygiIsJru8zMTJ08edJ9lJWVnfeYAQC46LgsOIIE+4AGkE6dOikkJKRe2nn06NF6qeh3LVu2TEuXLtWWLVs0cODARts6nU45nc7zHi8AAEBDSEADSHh4uBITE5Wfn+9xPj8/X8OGDfN63WOPPaYHH3xQf/nLX5SUlGT1MAEAgJiCbwwJaIDJyMhQenq6kpKSlJycrFWrVqm0tFQzZsyQJE2ZMkVdu3ZVVlaWpLPT7osWLdKLL76o7t27u9PTtm3bqm3btn77HgAA4OJFARpgJk6cqOPHj2vJkiUqLy9X//79lZeXp4SEBElSaWmpWrX6/8F2Tk6Oqqurdcstt3j0c//992vx4sV2Dh0AgIuLr7dOCp4AlAI0EM2cOVMzZ85s8L2CggKP14cOHbJ+QAAAAM1AAQoAAGAFY84evuwvSLAICQAAALYiAQUAALCAw5w9fNlfsKAABQAAsAJT8F4xBQ8AAABbkYACAABYwOE6e/iyv2BBAgoAAABbkYACAABYgWdAvSIBBQAAgK1IQAEAAKzAT3F6RQEKAABgAYcxcvhw2tyXffkbU/AAAACwFQkoAACAFViE5BUJKAAAAGxFAgoAAGAFI8mXm8cHTwBKAgoAAAB7kYACAABYgFXw3lGAAgAAWMHIx4uQfNeVvzEFDwAAAFuRgAIAAFiBbZi8IgEFAACArUhAAQAArOCS5PBxf0GCBBQAAAC2IgEFAACwANsweUcCCgAAAFuRgAIAAFiBVfBeUYACCB5B9B9nAEGAAtQrpuABAABgKxJQAAAAK5CAekUCCgAAAFuRgAIAAFiBjei9IgEFAACArUhAAQAALMBG9N5RgAIAAFiBRUheMQUPAAAAW5GAAgAAWMFlJIcPU0sXCSgAAADQIiSgAAAAVuAZUK9IQAEAAGArElAAAABL+DgBVfAkoBSgAAAAVmAK3ium4AEAAILUtm3blJaWpri4ODkcDm3atOl7r9m6dasSExMVERGhnj176qmnnvJ4f/HixXI4HB5HTExMs8ZFAQoAAGAFl/H90UxnzpzRoEGD9OSTTzap/cGDB3XDDTdoxIgRKi4u1r333qt77rlHubm5Hu2uuOIKlZeXu48PPvigWeNiCh4AACCAVFZWerx2Op1yOp0Ntk1NTVVqamqT+37qqafUrVs3ZWdnS5L69u2r3bt3a9myZfrpT3/qbhcaGtrs1PPbSEABAACsYFy+PyTFx8crKirKfWRlZflsyIWFhUpJSfE4N3bsWO3evVs1NTXuc/v371dcXJx69OihSZMm6cCBA836HBJQAACAAFJWVqbIyEj3a2/pZ0tUVFQoOjra41x0dLRqa2t17NgxxcbGasiQIXruuef0b//2b/r000/10EMPadiwYfrwww/VsWPHJn0OBSgAAIAVLFoFHxkZ6VGA+prD4fjOxxqP89+e0h8wYICSk5PVq1cvPfvss8rIyGjSZzAFDwAAAElSTEyMKioqPM4dPXpUoaGhXtPNNm3aaMCAAdq/f3+TP4cCFAAAwAoXwCr45kpOTlZ+fr7Huc2bNyspKUlhYWENXlNVVaV9+/YpNja2yZ9DAQoAAGCFc1Pwvjya6fTp0yopKVFJSYmks9sslZSUqLS0VJKUmZmpKVOmuNvPmDFDhw8fVkZGhvbt26dnnnlGa9as0fz5891t5s+fr61bt+rgwYN65513dMstt6iyslJTp05t8rh4BhQAACBI7d69W6NGjXK/PveM5tSpU7V27VqVl5e7i1FJ6tGjh/Ly8jRv3jytWLFCcXFx+v3vf++xBdMnn3yiyZMn69ixY+rcubOGDh2qXbt2KSEhocnjchgTRL/rBEtUVlYqKipKIzVeoY6G43cAAC4GtaZGBXpVJ0+e9LoQ6Nzfm6Nj71Roq3DffbarWlvKn270swMFU/AAAACwFVPwAAAAVrBoG6ZgQAIKAAAAW5GAAgAAWMHlkuTycX/BgQIUAADACkzBe8UUPAAAAGxFAgoAAGAFElCvSEABAABgKxJQAAAAK7iMJB+mljb8FrxdSEABAABgKxJQAAAACxjjkjG+2zrJl335GwUoAACAFYzx7bQ5i5AAAACAliEBBQAAsILx8SIkElAAAACgZUhAAQAArOBySQ4fLhwKokVIJKAAAACwFQkoAACAFXgG1CsSUAAAANiKBBQAAMACxuWS8eEzoGxEDwAAgMYxBe8VU/AAAACwFQkoAACAFVxGcpCANoQEFAAAALYiAQUAALCCMZJ8uRE9CSgAAADQIiSgAAAAFjAuI+PDZ0BNECWgFKAAAABWMC75dgo+ePYBZQo+AOXk5KhHjx6KiIhQYmKitm/f3mj73Nxc9evXT06nU/369dPGjRttGikAAEB9FKABZsOGDZo7d64WLlyo4uJijRgxQqmpqSotLW2wfWFhoSZOnKj09HTt2bNH6enpmjBhgt555x2bRw4AwMXFuIzPj2DhMMH0QMFFYMiQIfrhD3+olStXus/17dtXN998s7Kysuq1nzhxoiorK/Xf//3f7nPXX3+92rdvr3Xr1jXpMysrKxUVFaWRGq9QR9j5fwkAAAJUralRgV7VyZMnFRkZ2WAb99+bjn/36d+btaZGBWZjo58dKHgGNIBUV1erqKhICxYs8DifkpKinTt3NnhNYWGh5s2b53Fu7Nixys7O9vo5VVVVqqqqcr8+efKkJOn5sicD/g88AADno7KyUvHxrza6IOjce7WmyqfPbdaqxqP/QEYBGkCOHTumuro6RUdHe5yPjo5WRUVFg9dUVFQ0q70kZWVl6YEHHqh3Pj4+vgWjBgAg+Bw/flxRUVGNttmhPJtGE3goQAOQw+HweG2MqXfufNpnZmYqIyPD/frEiRNKSEhQaWnp9/4/G1ru7L+q41VWVkbSbDHutT24z/bhXtvn5MmT6tatmzp06OC1TWRkpHv20Art2rWzrG+7UIAGkE6dOikkJKReenn06NF6Kec5MTExzWovSU6nU06ns975qKgo/sNmg8jISO6zTbjX9uA+24d7bZ9Wrbyv43Y4HPzf4XuwCj6AhIeHKzExUfn5+R7n8/PzNWzYsAavSU5Ortd+8+bNXtsDAABYjQQ0wGRkZCg9PV1JSUlKTk7WqlWrVFpaqhkzZkiSpkyZoq5du7pXxM+ZM0fXXHONHn30UY0fP16vvvqqtmzZoh07dvjzawAAgItYyOLFixf7exBouv79+6tjx45aunSpli1bpq+++krPP/+8Bg0aJEl64oknFBoaqptvvlnS2YVD/fr10/Lly7V06VKVlpZq5cqVGjNmTLM+NyQkRCNHjlRoKP9msRL32T7ca3twn+3DvbYP9/r8sQ8oAAAAbMUzoAAAALAVBSgAAABsRQEKAAAAW1GAAgAAwFYUoJAk5eTkqEePHoqIiFBiYqK2b9/eaPvc3Fz169dPTqdT/fr108aNG20aaWBrzn1evXq1RowYofbt26t9+/YaPXq03n33XRtHG9ia+2f6nPXr18vhcLh3kkDjmnufT5w4oVmzZik2NlYRERHq27ev8vL4ucKmaO69zs7OVu/evdW6dWvFx8dr3rx5+vrrr20abWDatm2b0tLSFBcXJ4fDoU2bNn3vNVu3blViYqIiIiLUs2dPPfXUUzaMNAgYXPTWr19vwsLCzOrVq83evXvNnDlzTJs2bczhw4cbbL9z504TEhJili5davbt22eWLl1qQkNDza5du2weeWBp7n3+2c9+ZlasWGGKi4vNvn37zO23326ioqLMJ598YvPIA09z7/U5hw4dMl27djUjRoww48ePt2m0gau597mqqsokJSWZG264wezYscMcOnTIbN++3ZSUlNg88sDT3Hv9pz/9yTidTvPCCy+YgwcPmjfffNPExsaauXPn2jzywJKXl2cWLlxocnNzjSSzcePGRtsfOHDAXHLJJWbOnDlm7969ZvXq1SYsLMy8/PLLNo04cFGAwlx11VVmxowZHuf69OljFixY0GD7CRMmmOuvv97j3NixY82kSZMsG2MwaO59/q7a2lrTrl078+yzz1oxvKDSkntdW1trhg8fbv7whz+YqVOnUoA2QXPv88qVK03Pnj1NdXW1HcMLKs2917NmzTI//vGPPc5lZGSYq6++2rIxBpumFKC/+tWvTJ8+fTzO3XnnnWbo0KFWDi0oMAV/kauurlZRUZFSUlI8zqekpGjnzp0NXlNYWFiv/dixY722R8vu83d9+eWXqqmpUYcOHawYYtBo6b1esmSJOnfurGnTplk9xKDQkvv82muvKTk5WbNmzVJ0dLT69++vpUuXqq6uzo4hB6yW3Ourr75aRUVF7sd2Dhw4oLy8PI0bN87y8V5MvP19uHv3btXU1PhpVIGBLfwvcseOHVNdXZ2io6M9zkdHR6uioqLBayoqKprVHi27z9+1YMECde3aVaNHj7ZiiEGjJff67bff1po1a1RSUmLHEINCS+7zgQMH9Le//U233nqr8vLytH//fs2aNUu1tbX6zW9+Y8ewA1JL7vWkSZP02Wef6eqrr5YxRrW1tbrrrru0YMECO4Z80fD292Ftba2OHTum2NhYP43swkcBCkmSw+HweG2MqXfufNrjrJbet9/+9rdat26dCgoKFBERYdXwgkpT7/WpU6d02223afXq1erUqZNdwwsazfkz7XK51KVLF61atUohISFKTEzUv/71Lz322GMUoE3QnHtdUFCghx9+WDk5ORoyZIg+/vhjzZkzR7GxsVq0aJEdw71oNPR/l4bOwxMF6EWuU6dOCgkJqfev6KNHj9b7V905MTExzWqPlt3nc5YtW6alS5dqy5YtGjhwoJXDDArNvdf//Oc/dejQIaWlpbnPuVwuSVJoaKg++ugj9erVy9pBB6CW/JmOjY1VWFiYQkJC3Of69u2riooKVVdXKzw83NIxB6qW3OtFixYpPT1d06dPlyQNGDBAZ86c0R133KGFCxeqVSuewPMFb38fhoaGqmPHjn4aVWDgT+BFLjw8XImJicrPz/c4n5+fr2HDhjV4TXJycr32mzdv9toeLbvPkvTYY4/pwQcf1F/+8hclJSVZPcyg0Nx73adPH33wwQcqKSlxHzfddJNGjRqlkpISxcfH2zX0gNKSP9PDhw/Xxx9/7C7wJekf//iHYmNjKT4b0ZJ7/eWXX9YrMkNCQmTOLj62bKwXG29/HyYlJSksLMxPowoQ/lr9hAvHue091qxZY/bu3Wvmzp1r2rRpYw4dOmSMMSY9Pd1jpeXbb79tQkJCzCOPPGL27dtnHnnkEbZhaoLm3udHH33UhIeHm5dfftmUl5e7j1OnTvnrKwSM5t7r72IVfNM09z6Xlpaatm3bmtmzZ5uPPvrIvP7666ZLly7moYce8tdXCBjNvdf333+/adeunVm3bp05cOCA2bx5s+nVq5eZMGGCv75CQDh16pQpLi42xcXFRpJZvny5KS4udm93tWDBApOenu5uf24bpnnz5pm9e/eaNWvWsA1TE1GAwhhjzIoVK0xCQoIJDw83P/zhD83WrVvd71177bVm6tSpHu1feukl07t3bxMWFmb69OljcnNzbR5xYGrOfU5ISDCS6h3333+//QMPQM39M/1tFKBN19z7vHPnTjNkyBDjdDpNz549zcMPP2xqa2ttHnVgas69rqmpMYsXLza9evUyERERJj4+3sycOdN88cUXfhh54Hjrrbca/O/uuXs7depUc+2113pcU1BQYAYPHmzCw8NN9+7dzcqVK+0feAByGEMWDwAAAPvwDCgAAABsRQEKAAAAW1GAAgAAwFYUoAAAALAVBSgAAABsRQEKAAAAW1GAAgAAwFYUoAAAALAVBSgAAABsRQEKAAAAW1GAAgAAwFYUoABwgfrss88UExOjpUuXus+98847Cg8P1+bNm/04MgA4Pw5jjPH3IAAADcvLy9PNN9+snTt3qk+fPho8eLDGjRun7Oxsfw8NAFqMAhQALnCzZs3Sli1b9KMf/Uh79uzRe++9p4iICH8PCwBajAIUAC5wX331lfr376+ysjLt3r1bAwcO9PeQAOC88AwoAFzgDhw4oH/9619yuVw6fPiwv4cDAOeNBBQALmDV1dW66qqrdOWVV6pPnz5avny5PvjgA0VHR/t7aADQYhSgAHAB+7//9//q5Zdf1p49e9S2bVuNGjVK7dq10+uvv+7voQFAizEFDwAXqIKCAmVnZ+v5559XZGSkWrVqpeeff147duzQypUr/T08AGgxElAAAADYigQUAAAAtqIABQAAgK0oQAEAAGArClAAAADYigIUAAAAtqIABQAAgK0oQAEAAGArClAAAADYigIUAAAAtqIABQAAgK0oQAEAAGArClAAAADYigIUAAAAtqIABQAAgK0oQAEAAGArClAAAADYqlkF6MiRIzV37lyrxnLecnNz1a9fPzmdTvXr108bN2783mu2bt2qxMRERUREqGfPnnrqqafqtcnJyVGPHj0UERGhxMREbd++3eP9qqoq3X333erUqZPatGmjm266SZ988olHm9LSUqWlpalNmzbq1KmT7rnnHlVXVzd7LAAAAIEuaBLQwsJCTZw4Uenp6dqzZ4/S09M1YcIEvfPOO16vOXjwoG644QaNGDFCxcXFuvfee3XPPfcoNzfX3WbDhg2aO3euFi5cqOLiYo0YMUKpqakqLS11t5k7d642btyo9evXa8eOHTp9+rRuvPFG1dXVSZLq6uo0btw4nTlzRjt27ND69euVm5urX/7yl80aCwAAQFAwTTR16lQjyeM4ePBgUy+33IQJE8z111/vcW7s2LFm0qRJXq/51a9+Zfr06eNx7s477zRDhw51v77qqqvMjBkzPNr06dPHLFiwwBhjzIkTJ0xYWJhZv369+/0jR46YVq1amb/85S/GGGPy8vJMq1atzJEjR9xt1q1bZ5xOpzl58mSTxwIAABAMmpyAPvHEE0pOTtYvfvELlZeXq7y8XPHx8Q22nTFjhtq2bdvo8e0E0RcKCwuVkpLicW7s2LHauXNns6/ZvXu3ampqVF1draKionptUlJS3P0WFRWppqbGo01cXJz69+/vblNYWKj+/fsrLi7O43OqqqpUVFTUpLEAAAAEi9CmNoyKilJ4eLguueQSxcTENNp2yZIlmj9/fqNtvl2M+UJFRYWio6M9zkVHR6uioqLZ19TW1urYsWMyxqiurq7RfisqKhQeHq727ds32ua7fbRv317h4eGNtvn2WGJjY7/vFgAAAASEJhegzdGlSxd16dLFiq4b5XA4PF4bY+qda8o1585/+39vbr/fbdNQ++9r4+3zAQAAApkli5D8MQUfExNTL+08evRovVSxKdeEhoaqY8eO6tSpk0JCQhrtNyYmRtXV1friiy8abfPdPr744gvV1NQ02ubbYwEAAAgWzSpAw8PD3Su7G7NkyRKVlJQ0evh6Cj45OVn5+fke5zZv3qxhw4Y1+5qkpCSFhYUpPDxciYmJ9drk5+e7+01MTFRYWJhHm/Lycv397393t0lOTtbf//53lZeXe3yO0+lUYmJik8YCAAAQNJqzYukXv/iF+dGPfmQOHjxoPvvsM1NXV+frRVEt9vbbb5uQkBDzyCOPmH379plHHnnEhIaGml27drnbLFiwwKSnp7tfHzhwwFxyySVm3rx5Zu/evWbNmjUmLCzMvPzyy+4269evN2FhYWbNmjVm7969Zu7cuaZNmzbm0KFD7jYzZswwl112mdmyZYt5//33zY9//GMzaNAgU1tba4wxpra21vTv399cd9115v333zdbtmwxl112mZk9e3azxgIAABAMmlWAfvTRR2bo0KGmdevWF9w2TMYY89JLL5nevXubsLAw06dPH5Obm+vx/tSpU821117rca6goMAMHjzYhIeHm+7du5uVK1fW63fFihUmISHBhIeHmx/+8Idm69atHu9/9dVXZvbs2aZDhw6mdevW5sYbbzSlpaUebQ4fPmzGjRtnWrdubTp06GBmz55tvv7662aPBQAAINA5jPlmpQsAAABgg6D5JSQAAAAEBgpQAAAA2IoCFAAAALaiAAUAAICtKEABAABgKwpQAAAA2IoCFMD/a7eOBQAAAAAG+VvPYldRBAArAQUAYCWgAACsBBQAgJWAAgCwCj6ueO/0eSkHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bf6686400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.05000    0.05000\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee704f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "main:  0.40309882164001465\n",
      "   evolve:  0.002089262008666992\n",
      "   vis:  0.1676931381225586\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<advection_fv4.simulation.Simulation at 0x7f6bee861550>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee4a50b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         1         1   0.99983   0.99859   0.99773   0.99854   0.99976         1 \n",
      "   0.99997    1.0001     1.002    1.0275    1.0421    1.0212    1.0024   0.99976 \n",
      "   0.99969    1.0009    1.0174    1.2163    1.3164     1.157    1.0212   0.99854 \n",
      "   0.99921     1.002    1.0357    1.4336    1.6289    1.3164    1.0421   0.99773 \n",
      "   0.99952    1.0008    1.0228    1.2966    1.4336    1.2163    1.0275   0.99859 \n",
      "         1         1    1.0025    1.0228    1.0357    1.0174     1.002   0.99983 \n",
      "         1    1.0001         1    1.0008     1.002    1.0009    1.0001         1 \n",
      "         1         1         1   0.99952   0.99921   0.99969   0.99997         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"density\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## advection_rk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"advection_rk\"\n",
    "problem_name = \"tophat\"\n",
    "param_file = \"inputs.tophat\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the tophat advection problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee7a34e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.05000    0.05000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee35ec50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "main:  0.4256000518798828\n",
      "   evolve:  0.004318952560424805\n",
      "   vis:  0.1750965118408203\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<advection_rk.simulation.Simulation at 0x7f6bff998c88>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee2c5ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0 0.0030222 0.0040889 0.00278520.00071111         0 \n",
      "         0         0         0    0.2403   0.39295   0.15301 0.0027852         0 \n",
      "         0         0         0   0.60178   0.99111   0.39295 0.0040889         0 \n",
      "         0         0         0   0.36533   0.60178    0.2403 0.0030222         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"density\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## compressible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"compressible\"\n",
    "problem_name = \"rt\"\n",
    "param_file = \"inputs.rt\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=24\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the rt problem...\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/Documents/pyro2/compressible/problems/rt.py:69: RuntimeWarning: invalid value encountered in true_divide\n",
      "  0.5*(xmom[:, :]**2 + ymom[:, :]**2)/dens[:, :]\n",
      "/home/alice/Documents/pyro2/compressible/simulation.py:61: RuntimeWarning: invalid value encountered in true_divide\n",
      "  q[:, :, ivars.iu] = U[:, :, ivars.ixmom]/U[:, :, ivars.idens]\n",
      "/home/alice/Documents/pyro2/compressible/simulation.py:62: RuntimeWarning: invalid value encountered in true_divide\n",
      "  q[:, :, ivars.iv] = U[:, :, ivars.iymom]/U[:, :, ivars.idens]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee4725f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee29d860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<compressible.simulation.Simulation at 0x7f6bee2ff470>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee247208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "         2         2         2         2         2         2         2         2 \n",
      "    2.0004    2.0002    1.9999    1.9997    1.9997    1.9999    2.0002    2.0004 \n",
      "         2         2    1.9999    1.9997    1.9997    1.9999         2         2 \n",
      "   0.99984   0.99993    1.0002    1.0005    1.0005    1.0002   0.99993   0.99984 \n",
      "   0.99983   0.99993    1.0001    1.0002    1.0002    1.0001   0.99993   0.99983 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"density\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## compressible_fv4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"compressible_fv4\"\n",
    "problem_name = \"kh\"\n",
    "param_file = \"inputs.kh\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[33mwarning, key: driver.splitting not defined\u001b[0m\n",
      "\u001b[33mwarning, key: io.tplot not defined\u001b[0m\n",
      "\u001b[1minitializing the Kelvin-Helmholtz problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed9eedd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed705a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<compressible_fv4.simulation.Simulation at 0x7f6bed9ee550>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed7961d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377 \n",
      "    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296 \n",
      "    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605 \n",
      "    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281 \n",
      "    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281    3.1281 \n",
      "    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605    3.2605 \n",
      "    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296    5.8296 \n",
      "    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377    6.2377 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "e = pyro_sim.sim.cc_data.get_var(\"eint\")\n",
    "e.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## compressible_rk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"compressible_rk\"\n",
    "problem_name = \"quad\"\n",
    "param_file = \"inputs.quad\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=16\",  \"mesh.ny=16\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the quadrant problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6beda03320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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I0nW2b+1w7kpgJcAinjB6q0P5DPMa3NtujbHddknhVzNBw8XY1tEBAEnTowM3tB13BtmQ7mlFLppCz7tIfQokvQx4F7DC9ubp523flf/3NuAS4KBOL2J7le3ltpcvZNvyWh9KMz0eWYeKb8NojbGddpw/7uaEDrrE2JL80/v0trLttL6jA5IOAna1/e9F25LCn/et9SmAX5LVp3hd6wH5P8zngMNb6zFLWgw8YntzXrfiELK/fKGJHOPcoWKdY6xX8TPoMzogaR7wCeD4QZrS+ORdsD7FR4EnAd+QBHCn7RXAPsDnJE2RfQr5UNtdKqFJDJqI5B0qNFyM9Rsd2A7YD7gkz087A2slrbDdWs54hsYnbyhUn+JlXc67HNi/2taF2VSX2W8hXUPEWM/RAdsPAku2Xl+6BDitV+KGRJJ3CDC9OGwk71CdYWKs4OjAwCJ5h6TEmHeo2jAx1m90oO35Q4tcM5J3SEd8YRmqVqMYS+FWwRAyQ8x+K1AX568kXZfXvvlBp8kVYQ6p0SzeSN4hKZqcmrH1PLbYzLev2t4/r3/zEeDjVbQ7NMcgMValGDYJyZCNJgb6Zeo78832Qy3HP5Eus3fD3DBEjFUmkndIy9RAv1idZr69oP0gSSeTLYO2DfCSUZoXEjBYjFUmhk1COgyamJqx0XvqcqG6OLbPsr0X8A7g3dU0PjRC5xgbi+h5h3TYnXpFvaYuF6qL0+Jc4DPDNzA0XucYG4voeYekDNgr2jrzTdI2ZDPfZkyYkLSs5eGfALeU2uDQONHzDqFsNgzw7X/BmW+n5BUptwD3A8dV0PLQFAPGWJUieYd0GJgYbAWGAnVx/qaUtoU0DBFjVYnkHdJhw8TEuFsRUlajGIvkHdJSky+TQsJqEmORvEM6atQrComqUYxF8g4Jqc+XSSFV9YmxZG4VLFBgaFtJ5+X7r5C0R8u+d+bP3yTpFbPZ7lAigycmZmwhlGrIGBslP3WTRPIuWGDoBOB+288iWy/uw/m5+5Ld3/sc4HDg0/n1QtPYMDk5cwuhTEPE2Cj5qZckkjctBYZsP0Y2E+6otmOOAr6U/7wGeKmyBeOOAs61vdn27cCG/HqhaWy8ZWLGFkKphouxUfJTV6mMeRcpMLT1mHxyxoPAjvnz69rO3aW6poaqTHqCByfuGXczQsKGjLFR8tO93S6aSvIuUmCo2zGFihPlBY2mixptvtBrfjZQC+tpCT2Co1L/sqbMqz0b4Dc89MAVE9/7Vdu+3ct8oSq1x9j8pRsixkbyqTIv1ivGni2pdbHgVbZXtTweJT91lUryLlJgaPqYjZIWANsDmwqeS/4/YxWApPU9ih01RkrvA8D24nG3ZRQRY/U1YoyNkp+6SmXMu2+BofzxdF2K1wAX2Xb+/DH5t717AsuAH89Su0MI6RslP3WVRM+7YIGhLwJflrSB7C/aMfm510v6OtnqKRPAybbjNoUQQilGyU+9qE9yDx1IWtk2ptVI8T7qK5X3FO+jOpG85xhJPwc+B7wRWAp8CzjJ9qPjbFdIi6SnA/8X+CPgYeATtkv9BnGuS2XMOwzm9cArgL2AvYmlvUKJJM0DvgNcQ3YL3EuBv43Zy+WK5D03nWn7F7Y3Ae8Hjh13g0JSngfsZPt024/Zvg34PAXGcUNxSXxhGQbWOmHgDuDp42pISNLuwNMlPdDy3HzgsjG1J0mRvOem1ntOd6P3orshDOoXwO22l/U9Mgwthk3mppMlPUPSU4B/AM4bd4NCUn4MPCTpHZJ+T9J8SftJet64G5aSSN5z01eB/wRuy7d/HG9zQkryeRJ/ChwI3E42Pf4LZLMGQ0niVsE5Jr9V8ETbF467LSGE4UXPO4QQGiiJ5C1ptaS7JXWswqbMp/JVKq6V9NyWfcdJuiXfjut0fkhXgdg5VNKDkq7Ot/fMdhtD6CSJYRNJ07O4zrG9X4f9RwJvAY4kq6P7SdsvyL+wWw8sJyu/eBVwsO37Z63xYawKxM6hwGm2XznbbQuhlyR63rYvpXf5xKPIfjltex2wg6SlZLMML7C9KU/YF5AthRbmiAKxE0ItzZX7vDutZLFLj+dDA0k6uP0521eVcOkXSbqG7H7402xfX8I1QwNVGGMDmyvJe6RVdGDmKifz5m1z8BOfsKS81s1Bez/zvtKuddW1m++1vdP2T563funTZq4dLelh4KaWp9pXOennJ8Duth/Oh9++RVbzvXStMaaF2xy87Y5PreJl5oznPLW8JfH6xNi9tncq7cUKmivJu9tKFhuBQ9uev6TTBVpXOXnydrv4ec89uYp2zhkXnPcvpV1r/tINdwDstccCLv+PmR+cFj399ptGWcnF9kMtP58v6dOSltgufWmv1hj7vaW7eo+/OLXsl0hTl2V6f3zKp0t7iT4xdkdpLzSAJMa8C1gLvCm/6+SFwIO2f0VWHP0wSYslLQYOy58LDWRggskZ26gk7Ty9irek55P9zpT3sSE0ShUxNqwket6SvkbWg14iaSPwXmAhgO3PAueT3WmyAXgEeHO+b5OkM8iWKQI4Pa+0FxpoCvPogIsgFYid1wAnSZoAfgsc0295qpCuYWKsKkkkb9s9S5rmv2wdxzlsrwZWV9GuMLsMbPHUYOf0j50zgTNHaFZIyDAxJmlX4BxgZ2CK7HuXT7YdcyjwbbJyAgDftH16r+smkbxDALDNo9EpDhUaMsYmgLfb/omk7YCrJF1g+4a24y4bZD5BJO+QDCO2dPv2KoQSDBNj+fdrv8p//rWkG8luSW5P3gOZK19YhjlgCnjU82ZsIZRp1BiTtAdwEHBFh90vknSNpO9Kek6/a0XPOyRjCvGoI6RDdbrE2BJJ61sed5xLIOlJwP8D/rb1FtTcwPMJItJDMrIvk6K3HarTJcbu7TeXQNJCssT9FdvffNx1h5hPEMk7JMOIR71w3M0ICRsmxvJ5Al8EbrT98S7H7Az8r20XnU8QyTskwxZbPL//gSEMacgYOwR4I3CdpKvz5/6BbP3YoecTRPIOycjGI7cZdzNCwoaJMds/oOsk/q3HDDyfIJJ3SIYRj0XPO1SoTjEWyTskYwrx6FSMeYfq1CnGInmHZNhic3xhGSpUpxiL+6pCMgw85gUztn4KrGH5+nzd02slXS7p98tud2iOYWKsKpG8QzKmEJunFs7YCjib3kvf3Q78se0DgDPI622HuWnIGKtEDJsM4+HfMu+yn467FY328te+ucSrvQvI604M+GWS7UvzKcvd9l/e8nAd2YIdlVv4P7/hGR+8vP+BAeZ1/n/+HP66xBfJFsYYJsaqEsk7JMOu/MukE4DvVvkCod5mIcYKi+QdktGlV1So7kQ/kl5Mlrz/YIQmhoaLnnfJJB0OfBKYD3zB9ofa9n8CeHH+8AnAU23vkO+bBK7L991pe8XstDqULRuPfFxI96070Y+kA4AvAEfYjiXQ5rAuMTYW9WjFCCTNB84CXk62oPCVkta2Fjq3/baW499CVpJx2m9tHzhb7Q3VsSn9F0vSbsA3gTfavrnUi4fGqSLGhlWPVozm+cAG27cBSDoXOIruhc6PJVunMCRmmI+0BdawfA+wI/DpfB3iiVF78qG5YtikXLsAv2h5vBF4QacDJe0O7Alc1PL0onxMdAL4kO1vVdXQUC0jHhuwV1RgDcsTgRNHaVeo2FSXBYErWBFvmBirSj1aMZpOBV+6/W87Blhjz1j+eTfbd0l6JnCRpOts3/q4F5FWAisBFvGEUdscKmDDlql69IqGETFWf3WKsRQm6WwEdm15/Azgri7HHgN8rfUJ23fl/70NuISZ4+Gtx62yvdz28oVsO2qbQwWmEI9NzZ+xNUnEWP3VKcZSSN5XAssk7SlpG7IEvbb9IEnPBhYDP2p5brGkbfOfl5DV3R1pUdAwRhYTU/NnbCGUaogYk7SrpIsl3Sjpekl/0+EYSfqUpA15KYbn9rtu44dNbE9IOgX4HtmtgqttXy/pdGC97elEfixwbluB832Az0maIvtD9qHWu1RCs0xB43rboVmGjLEJ4O22fyJpO+AqSRe05ZojyNasXEb2nd1n6PLd3bTGJ2/I1nwDzm977j1tj9/X4bzLgf0rbVyYNUZMTKXwYTLU1TAxZvtXwK/yn38t6UayGy1ak/dRwDl553KdpB0kLc3P7SiJ5B0CZF8mRc87VGnUGMvr6BwEXNG2q9Ndc7uQJ/1OInmHZBixZTKSd6hOlxgrVIJB0pPIVpD/29bV4qd3d3y5HiJ5h2TYMOEYNgnV6RJjfUswSFpIlri/YvubHQ4Z5K45II27TULIiYnJ+TO2EMo1eIwpm5r7ReBG2x/vctha4E35XScvBB7sNd4N0fMOCbFhcqrnIt0hjGTIGDsEeCNwnaSr8+f+Adgtu6Y/S3bDxZHABuARoG/B+0jeIRlGtZn9FtI0TIzZ/gGdx7RbjzFw8iDXjeQdkjIVPe9QsbrEWIx5h2TYMDE5b8bWj6TDJd2Uz2z7+w77d5f0/XzW2yWSZmUZtFBPw8RYVSJ5h2QYMTk1b8bWS0st+COAfYFjJe3bdtjHyCZPHACcDnywgqaHhhg0xqoUyTukw+Apzdj62FoL3vZjwHQt+Fb7At/Pf764w/4wlwweY5WJ5B2SYWByct6MjXwCRcu2suWUbrPaWl0DHJ3//GfAdpJ2rOgthJrrEmNjEV9YhnTkvaI2vSZQFJnVdhpwpqTjgUuBX5IVGgpzUecYG4tI3iEhwpMD/WL1ndWW13t/NWyd3ny07QdHbGhorIFjrDIxbBLSMfh4ZN9a8JKWSJr+PXknsLr0dofmiDHvECoypZlbD7YngOla8DcCX5+uBS9pRX7YocBNkm4Gnga8v7rGh0YYIMaqFMMmIR1m4I+0/WrB214DrCmlfaH5hoixqiTR8y4w0eJ4SfdIujrfTmzZd5ykW/LtuNlteSibpjRjC6FsdYmxxve8WyZavJzsC6grJa3tsJzZebZPaTv3KcB7geVkdxlclZ97/yw0PZTNgpr0ikKiahRjtep5SzpF0uIBTysy0aKbVwAX2N6UJ+wLgMMHfP1QJ1NtWwhlq0mM1Sp5AzuT9Zy/ng+FFPkTV2SiBcDReX2KNZKmbw8rem5oAoMmNWMLoVQ1irFaJW/b7yZbPfmLwPHALZI+IGmvHqcVmWjxHWCPvD7FhcCXBjg3O1BaOT1LbwubezQnjJM8c2uSiLFmqEuM1Sp5w9a6tv+TbxPAYmCNpI90OaXIRIv7bE//NnweOLjouS3XWGV7ue3lC9l2gHcUZo3JxiNbtwaJGGuAIWJM0mpJd0v6WZf9h0p6sOWGivd0Oq5drZK3pLdKugr4CPBDYH/bJ5El26O7nFZkosXSlocryO7phez+3sMkLc7H2g/LnwsNpcmZWwhlGyLGzqb/d2mX2T4w304vctG63W2yBHi17Ttan7Q9JemVnU6wPSFpeqLFfGD19EQLYL3ttcBb80kXE8AmsiEZbG+SdAbZHwCA021vquKNherJxO2BoVLDxJjtSyXtUXZbapW8WydHdNh3Y499/SZavJNsanOnc1cTU56TEb3tULUOMbZE0vqWx6tsrxrwsi+SdA3ZsO1ptq/vd0KtkncIIzEobg8MVeocY70qVxbxE2B32w9LOhL4FtmNGz3Vasw7hFFpauYWQtnKjjHbD9l+OP/5fGChpCX9zovkHdLhwX+x+pVWyI/5c0k3SLpe0lfLbnZokCFirB9JO0/PaZH0fLK8fF+/82LYJCRDDDbmXaS0gqRlZN+XHGL7fklPLbXRoVEGjTEASV8jq065RNJGspIcCwFsfxZ4DXCSpAngt8Ax+S3TPUXyDunwwL9YW0srAEiaLq3QWhfnL4Gzpuvd2L67nMaGRho8xrB9bJ/9ZwJnDtqUGDYJSRnwI22R8gh7A3tL+qGkdZKi9s0cV5fvVaLnHdLRuVfU6zauIuURFpB9838o2QzcyyTtZ/uB0RscGmeInndVInmHpAx4G1eR8ggbgXW2twC3S7qJLJlfSZiT6nIXUwybhGRo8DsB+pZWILvn9sWQrWdJNoxyW7ktD00xRIxVJpJ3SMogv1gF17D8HnCfpBuAi4G/s933Nq6Qrrok7xg2CekY7k6AfqUVDJyab2GuizHvEKp2HtDsAAAKqUlEQVRRl/HIkK66xFgk75COGvWKQqJqFGORvEMyhpn9FsIg6hRjkbxDOgyaatjaZ6FZahRjkbxDUubVpFcU0lWXGEviVsF+leEknZpXhbtW0vcl7d6yb7Jl7bj2e3xDk9ToHtyQqBrFWON73kUqwwE/BZbbfkTSSWRrZL423/db2wfOaqNDJbLxyHp8pA1pqlOMpdDz3loZzvZjwHRluK1sX2z7kfzhOrJp0CE1NeoVhUTVKMZSSN5FKsO1OgH4bsvjRZLW5xXjXtXtJEkr8+PWb2HzaC0OlZk3MXNrkoixZhg0xiStlnS3pJ912S9Jn8qHfa+V9NxC7Ris2bVUpDJcdqD0BmA58NGWp3fLCxe9DvhnSXt1Otf2KtvLbS9fyLajtjlUwdlH2tatSSLGGmC4GDsb6FVK+AiyYmfLgJXAZ4pcNIXkXaQyHJJeBrwLWGF7a7fG9l35f28DLgEOqrKxoTqy0dTMLYQyDRNjti8FNvU45CjgHGfWATtIWtrvuikk776V4SQdBHyOLHHf3fL8Yknb5j8vAQ5h5ioqoWHmTc7c+ilwp9JfSbouvxvpB5L2raLdoTk6xNiS6eGufFs54CUHHfoFErjbxPaEpOnKcPOB1dOV4YD1tteSDZM8CfhGvs7nnbZXAPsAn5M0RfaH7ENtd6mEJjEwwFBJwTuVvpqvM0heafDj9P4IHFLWOcZ61YwvovDQb6vGJ28oVBnuZV3OuxzYv9rWhdk0b7Bx7r5rWNp+qOX4J1LglyqkbcAYK6LQ0O/j2lF2K0IYF+VTlwcYjyz0cVXSyZJuJZsf8NbSGhwaZ4gYK2It8Kb8rpMXAg/a/lW/k5LoeYcAZHcCTDzul2nUNSyxfRZwlqTXAe8GjiujuaGBOsdYT5K+RrYG6hJJG4H3AgsB8iG584EjgQ3AI8Cbi1w3kndIiNHk42ZNjLqGZatzKXgbV0hVxxjrfYZ9bJ/9Bk4etCUxbBLSMfg9uEXuVFrW8vBPgFtKbXNolhrNJYied0jKIL2igncqnZLPEdgC3E8Mmcx5g/a8qxLJOyRDHrwnVOBOpb8pp3UhBcPEWFUieYd0GJioR68oJKpGMRbJOyRFU/X4xQrpqkuMRfIO6bBr0ysKiapRjEXyDukwaKIma1SFNNUoxiJ5h4QYavKRNqSqPjEWyTukw4aJhq3AEJqlRjEWyTukw0BN7sENiapRjEXyDgkxTNZjPDKkqj4xFsk7pMPU5hcrJKpGMRbJO6TDxjUZjwyJqlGMJVOYqsByVttKOi/ff4WkPVr2vTN//iZJr5jNdoeSTU7N3EIoW01iLImed8HlrE4A7rf9LEnHAB8GXpuvSXgM8Bzg6cCFkva2XY/PRqE4G2/ZMu5WhJTVKMaSSN4UWM4qf/y+/Oc1wJnKFrQ8Cjg3X1H+dkkb8uv9aJbaHkoy6S089Njd/Q8MYUh1irFUknen5axe0O2YvBTog8CO+fPr2s7ttBTWSmB6VejNF3rNz8pp+lgtAe4dyytfuqbMqz0b4Dd+6IF1W/6jffmo3ct8oSpFjJXsA2nHWCrJu8hyVt2OKboU1ipgFYCk9SOuFl0LKb0PANuLx92WUUSM1VcdYyyVLyyLLGe19RhJC4DtgU0Fzw0hhFpJJXn3Xc4qfzy9CsprgIvytePWAsfkd6PsCSwDfjxL7Q4hhKEkMWxScDmrLwJfzr+Q3ESW4MmP+zrZl5sTwMkF7jRZ1Wd/U8T7qK9U3lO8j4oo63yGEEJoklSGTUIIYU6J5B1CCA0UybuHUabc10WB93C8pHskXZ1vJ46jnf1IWi3pbkkd731W5lP5+7xW0nNnu43DSCHGII04a1yM2Y6tw0b2xeetwDOBbYBrgH3bjvlr4LP5z8cA54273UO8h+OBM8fd1gLv5Y+A5wI/67L/SOC7ZPftvxC4YtxtngsxllKcNS3Goufd3dYp97YfA6an3Lc6CvhS/vMa4KX5lPu6KPIeGsH2pWR3CXVzFHCOM+uAHSQtnZ3WDS2FGINE4qxpMRbJu7tOU+7bp83PmHIPTE+5r4si7wHg6Pxj4BpJu3bY3wRF32udpBBjMHfirFYxFsm7u1Gm3NdFkfZ9B9jD9gHAhfyul9c0df9/0UkKMQZzJ85q9f8iknd3o0y5r4u+78H2fc4qKgJ8Hjh4ltpWtiaWOUghxmDuxFmtYiySd3ejTLmvi77voW3MbgVw4yy2r0xrgTfldwS8EHjQdnv1t7pJIcZg7sRZrWIsienxVfAIU+7rouB7eKukFWSlATaR3RVQO5K+BhwKLJG0EXgvsBDA9meB88nuBtgAPAK8eTwtLS6FGIN04qxpMRbT40MIoYFi2CSEEBookncIITRQJO8QQmigSN4hhNBAkbxDCKGBInmHEEIDRfIOIYQGiuQ9x0h6Xl4caJGkJ0q6XtJ+425XSEvEWfV6Jm9JO0j66zJeqGhR+W5F3fOpt1dIuiW/zja9ritpR0kXS3pY0pldXmtta+F1SR+V9N950P2bpB3y57eR9C+SrpN0jaRDW87ZRtIqSTfn5x498j9WhWxfSTbN9x+BjwD/artj8fkQhhVxVr1+Pe8dyIrBl+EE4H7bzwI+AXy4/QBJ84GzgCOAfYFjJe2b7/4w8Anby4D78+v1uu6jwP8BTuvUGEmvBh5ue/oCYL+88tnNwDvz5/8SwPb+wMuBf5I0/W/3LuBu23vnbf6v/v8UY3c62ftYTvaLFUIVIs4q1C95fwjYK1+26KMjvlaRovIdi7rnx70kP4/8Oq/qdV3bv7H9A7IkPoOkJwGnkvUKtrL9n3nNZIB1ZFXDIEvK38+PuRt4gCwgAf4C+GC+b8r2vUX+McbsKcCTgO2ARWNuS0hXxFmF+iXvvwdutX2g7b9r3ynpMv1uTbrW7WUdrlWkqHy3Yuc7Ag+0JNbWIujDFKs/A/gnsuIy3fwF2ZJHkC3rdJSkBZL2JCtnuev0sApwhqSfSPqGpKf1ee06WEX2qeQrdPgEFEJJIs4qNFJVQdt/OMDhoxSe73XuQAXSJR0IPMv223qMu7+LrPrZV/KnVgP7AOuBO4DL8/0LyHrnP7R9qqRTgY8Bb+z2+uMm6U3AhO2v5sNUl0t6ie2Lxt22kI6Is+qNlLwlXUb2kajdabYvbHtuupD5RnUvKt+t2Pm9ZOvFLch7161F0Itct9WLgIMl/Zzs/T9V0iW2D83f03HAK4GXTtdNzl/zbS3v+3LgFuA+st77v+W7vsHvxuJryfY5wDn5z5PAC8bbopCiiLPq9Rs2+TWdkzOQ9bzzIZX2rT1xQ7Gi8h2LuufHXZyfR36dbw9w3dY2f8b2023vAfwBcHNL4j4ceAewwvbWIRVJT5D0xPznl5P1KG7IX+c7ZDWAAV4K3NDttUMIoSx963lL+ipwAPDdTuPehV9IWgR8GTiIvKi87dskPR34gu0j8+OOBP6Z3xV1f3/+/DPJvsB8CvBT4A22N3e7bn7Oz4EnA9uQfcl4mO2tyTUfNvl32/vljzcA25L1qAHW2f6r/LjvAVPAL4ETbN+Rn7N7/vo7APcAb7Z957D/TiGEUEQsxhBCCA0UMyxDCKGBInmHEEIDRfIOIYQGiuQdQggNFMk7hBAaKJJ3CCE0UCTvEEJooEjeIYTQQP8ftZwYZBpYhdUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6c074c3d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<compressible_rk.simulation.Simulation at 0x7f6bee419710>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee4b0fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3   0.30292    1.4997       1.5       1.5 \n",
      "       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3       0.3   0.30292    1.4997       1.5       1.5 \n",
      "   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.29994   0.30304    1.4991    1.4997    1.4997 \n",
      "  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029558  0.029559  0.030208   0.30304   0.30292   0.30292 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029559   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029032  0.029558   0.29994       0.3       0.3 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"pressure\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## compressible_sdc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"compressible_sdc\"\n",
    "problem_name = \"sod\"\n",
    "param_file = \"inputs.sod.y\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=4\",  \"mesh.ny=16\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the sod problem...\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=0.0, top=0.0\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n"
     ]
    },
    {
     "data": {
      "image/png": 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xzTffYPfu3S35+B2CuS8vUePPARERUQcqLS1FVVWVbYuPj2+yrUZj/x8SSZIcjrW2/e3aOHv9hm3Ky8uxYMECPP300zh9+jSOHDkCDw8PzJgxA5IkNdk3os6Oy+6JFKrx6g4L/2PVKfj4+MDHx6fZNn5+fnBzc3OoBlVUVDhUeOoFBgY22z4wMBDArQFNnz59mmzz3XffObz2pUuXbG1ee+01+Pj4YP369ba/Z2ZmQqfT4eTJkxg+fHizn60jMPflJWr8WSEiUqhbNzbabyQGDw8PhIWFwWQy2R03mUwYMWKE03P0er1D+9zcXFv74OBgBAYG2rWpra3FkSNHbG30ej2qqqpw6tQpW5uTJ0+iqqrK1ubGjRtwc3Oze5/6favVeicft80x9+UlavxZISIi6oTi4uJgNBoRHh4OvV6PLVu2wGw2Y9GiRQCAefPmISgoyHYP0rJlyzB69Gj8+c9/xuOPP459+/bh/fffx/HjxwHcmgqLjY3FunXrMGjQIAwaNAjr1q1D9+7dMXv2bABASEgIHnnkESxcuBCbN28GADzzzDOYPHky7r33XgDAY489ho0bNyIpKQmzZs3CtWvX8OKLL6J///546KGHOjpMRG2GAyIihbI2+sVpK8QoW9MtkZGRqKysRFJSEsrKyhAaGors7Gz0798fAGA2m9Gly0//+44YMQK7d+/GihUrsHLlSgwcOBBZWVl2K8aef/55/PDDD4iOjsaVK1cwbNgw5Obmwtvb29Zm586dWLp0qW012tSpU7Fp0ybb33/zm99g165dWL9+PdavX4/u3btDr9cjJycH3bp1a++wtAhzX16ixp8DIiKiTio6OhrR0dFO/5aXl+dwbMaMGZgxY0aTr6fRaJCYmIjExMQm2/Tq1QuZmZnN9uupp57CU0891WwbItFwQESkUKLe2EjkKua+vESNP2+qJiIiItVjhYhIoeofm//Tvhjf0ohcxdyXl6jxZ4WIiIiIVI8VIiKFskgaWCSN3T6RGjD35SVq/DkgIlIoS6OlrxZBytZErmLuy0vU+HPKjIiIiFSPFSIihbJKXWBtsPTVKsjSVyJXMfflJWr8WSEiIiIi1WOFiEihRJ3HJ3IVc19eosafFSIiIiJSPVaIiBTKCvvlrlb5ukLUoZj78hI1/hwQESmU49NiWRAmdWDuy0vU+IvRSyIiIqJ2xAoRkUI5/uI0v/+QOjD35SVq/MXoJREREVE7YoWISKGs0MAKjd0+kRow9+UlavxZISIiIiLVY4WISKFEnccnchVzX16ixp8DIiKFcnxarBgXJSJXMfflJWr8xeglERERUTtihYhIoaySBtaGT4uVxLixkchVzH15iRp/VoiIiIhI9VghIlIoa6N5fFEen0/kKua+vESNvxi9JCIiImpHrBARKZRV6gJrg+WuVkGWvhK5irkvL1HjL0YviYiIiNoRK0RECmWBBpYGj8y3CPL4fCJXMfflJWr8OSAiUihRy9ZErmLuy0vU+IvRSyIiIqJ2xAoRkUJZgEZlayJ1YO7LS9T4s0JEREREqscKEZFCiTqPT+Qq5r68RI2/GL0kIiIiakccEJGqpaWlITg4GF5eXggLC8OxY8eabZ+amop7770X3bp1g06nw/Lly/Hjjz92UG9bxyJ1cdiI1IC5Ly9X4p+cnIyhQ4fC29sb/v7+mDZtGkpKSlp8/u7du6HRaDBt2rRW95tZQqqVlZWF2NhYJCQkoKioCBEREZg0aRLMZrPT9jt37sQLL7yAVatW4ezZs9i6dSuysrIQHx/fwT1vGQkaWBtskiDPAiFyFXNfXq7E/8iRI4iJicGJEydgMplQV1cHg8GA69ev3/bcCxcu4LnnnkNERMQd9Zv3EJFqpaSkICoqCgsWLABwq/pz8OBBpKenIzk52aF9QUEBRo4cidmzZwMABgwYgFmzZuHUqVMd2m8iIqXKycmx29++fTv8/f1RWFiI0aNHN3mexWLBnDlzsHr1ahw7dgxXr15t9XuzQkSqVFtbi8LCQhgMBrvjBoMB+fn5Ts8ZNWoUCgsLbQOgr7/+GtnZ2XjssceafJ+amhpUV1fbbR2F0wbyxp/kiz9zv3Neexr3p6am5ravVVVVBQDo1atXs+2SkpLQu3dvREVF3XG/1ZclRAAuX74Mi8WCgIAAu+MBAQEoLy93es5TTz2FNWvWYNSoUejatSsGDhyIcePG4YUXXmjyfZKTk6HVam2bTqdr089BzWP85cX4y6czxl6n09n1yVklviFJkhAXF4dRo0YhNDS0yXYffvghtm7dioyMDJf6xwERqZpGYz+3LUmSw7F6eXl5WLt2LdLS0vDxxx9j7969OHDgANasWdPk68fHx6Oqqsq2lZaWtmn/m2OVNA6b2sgZf5Iv/sz9znntKS0ttevT7e6/XLx4Mc6cOYO33nqryTbXrl3D3LlzkZGRAT8/P5f6zXuISJX8/Pzg5ubmUA2qqKhwqBrVW7lyJYxGo+2eo/vuuw/Xr1/HM888g4SEBHTp4vj9wtPTE56enm3/AahFGH95Mf7y6Yyx9/HxgY+PT4vaLlmyBPv378fRo0dx9913N9nuP//5D86fP48pU6bYjlmtVgCAu7s7SkpKMHDgwBa9JytEpEoeHh4ICwuDyWSyO24ymTBixAin59y4ccNh0OPm5gZJkiBJUrv19U5Z0MVhI1ID5r68XIm/JElYvHgx9u7di8OHDyM4OLjZ9oMHD8ann36K4uJi2zZ16lSMGzcOxcXFrZoqZIWIVCsuLg5GoxHh4eHQ6/XYsmULzGYzFi1aBACYN28egoKCbPPcU6ZMQUpKCh566CEMGzYMX331FVauXImpU6fCzc1Nzo/iVOOpAjVOG5A6Mffl5Ur8Y2JisGvXLuzbtw/e3t62Kr5Wq0W3bt0A2F+bvby8HO4v6tmzJwA0e9+RMxwQkWpFRkaisrISSUlJKCsrQ2hoKLKzs9G/f38AgNlstqsIrVixAhqNBitWrMDFixfRu3dvTJkyBWvXrpXrIxARKUp6ejoAYOzYsXbHt2/fjvnz5wNwvDa3FQ6ISNWio6MRHR3t9G95eXl2++7u7li1ahVWrVrVAT1znRVdYG1QqrZy2oBUoq1yPy0tDS+99BLKysrwy1/+Eqmpqc0+9C81NRXp6ekwm83w8/PDjBkzbFUMNXEl/i25/aDxtbmxHTt2tPj9GuIVkoiIqBGlP8meHHFARKRQFknjsBGpQVvkfsMn2YeEhCA1NRU6nc42pdNYwyfZDxgwAAaDAbNmzcJHH33k6scRjqjXHg6IiKhZSv4BXFKXlj4puaOeZE+dC+8hIlKotlhpUz9tkJaWhpEjR2Lz5s2YNGkSPv/8c/Tr18+hff20wbZt2zBixAh88cUXthshN27ceMefhag1msr9xkuwV61ahcTERIfz7/RJ9pcuXcKoUaMgSRLq6urw7LPPNvske6USdZUfB0RE1CT+AC4pSWlpqd2DAW/34MI7fZJ9/WM5li1bhj59+mDlypWud57aHQdERAolSV1gbfCjllKDH1hsqKkn2tZPGzT+hnu7aYPMzEycOnUKv/71r23TBk8//bSrH4eoxZrK/ZY+KbmjnmSvVE3Fv7MTo5dE1GoWaBw2oOU/sNhRP4BL1Naayv2WUsOT7NuTq/GXCytERCrDaQOi21P6k+zJEQdERAplldDoxsZb/+S0ASldU7nfGnyS/Z1ri/jLgQMiInKq4bTBE088YTtuMpnw+OOPOz2H0wakJEp+kj054oCISKGsjW5stN7BjY2cNiARtUXu050TNf4cEBFRkzhtQERqwQERkUJZoYG1weoO6x2u9OC0AYmmrXKf7oyo8eeAiEihGv+GkCi/J0TkKua+vESNvxgTe0RERETtiBUiIoUS9cZGIlcx9+UlavzF6CURERFRO2KFiEihrGj0i9OC3NhI5CrmvrxEjT8rRERERKR6rBARKZTUaOmrJMi3NCJXMfflJWr8OSAiUiir1KhsLcjSVyJXMfflJWr8OWVGREREqscKEZFCibr0lchVzH15iRp/MXpJRERE1I5YISJSKFHn8YlcxdyXl6jxZ4WIiIiIVI8VIiKFEvUXp4lcxdyXl6jxZ4WIiIiIVI8VIiKFEnUen8hVzH15iRp/DoiIFErUixKRq5j78hI1/pwyIyIiItVjhYhIoUT9lkbkKua+vESNPytEREREpHqsEBEplKjf0ohcxdyXl6jxZ4WIiIiIVI8DIiKFkvDTA9Ks0ECSu0PUamlpaQgODoaXlxfCwsJw7NixZtu//fbbGDJkCDw9PTFkyBC88847dn+XJAmJiYno27cvunXrhrFjx+Kzzz6za3PlyhUYjUZotVpotVoYjUZcvXrV6ft99dVX8Pb2Rs+ePV37oG2MuS8vUePPARGRQtWXrRtuJI6srCzExsYiISEBRUVFiIiIwKRJk2A2m522LygoQGRkJIxGIz755BMYjUbMnDkTJ0+etLVZv349UlJSsGnTJpw+fRqBgYGYMGECrl27Zmsze/ZsFBcXIycnBzk5OSguLobRaHR4v5s3b2LWrFmIiIho+w/vIua+vESNPwdEREQdqLq62m6rqalx2i4lJQVRUVFYsGABQkJCkJqaCp1Oh/T0dKftU1NTMWHCBMTHx2Pw4MGIj4/Hww8/jNTUVAC3qkOpqalISEjA9OnTERoaijfeeAM3btzArl27AABnz55FTk4OXn/9dej1euj1emRkZODAgQMoKSmxe78VK1Zg8ODBmDlzZhtGh0g+HBARKZSo39KUTqfT2aajtFotkpOTHdrU1taisLAQBoPB7rjBYEB+fr7T1y0oKHBoP3HiRFv7c+fOoby83K6Np6cnxowZY2tTUFAArVaLYcOG2doMHz4cWq3W7n0PHz6Mf/zjH3jttdda+ek7BnNfXqLGn6vMiIg6UGlpKXx8fGz7np6eDm0uX74Mi8WCgIAAu+MBAQEoLy93+rrl5eXNtq//p7M2Fy5csLXx9/d3eG1/f3/b+ZWVlZg/fz4yMzPtPgeR6DggIlIoUZe+Kp2Pj0+LBxIajf3/ZpIkORxrbfvbtXH2+g3bLFy4ELNnz8bo0aNb9BnkwNyXl6jx55QZEVEn4+fnBzc3N4dqUEVFhUOFp15gYGCz7QMDAwHgtm2+++47h9e+dOmSrc3hw4exYcMGuLu7w93dHVFRUaiqqoK7uzu2bdt2B5+WqHPggIhIoUSdxyfAw8MDYWFhMJlMdsdNJhNGjBjh9By9Xu/QPjc319Y+ODgYgYGBdm1qa2tx5MgRWxu9Xo+qqiqcOnXK1ubkyZOoqqqytSkoKEBxcbFtS0pKgre3N4qLi/HEE0+4/uHbAHNfXqLGn1NmRAolSRpIDS5EkiAXJbolLi4ORqMR4eHh0Ov12LJlC8xmMxYtWgQAmDdvHoKCgmw3ZS9btgyjR4/Gn//8Zzz++OPYt28f3n//fRw/fhzAramw2NhYrFu3DoMGDcKgQYOwbt06dO/eHbNnzwYAhISE4JFHHsHChQuxefNmAMAzzzyDyZMn495777W1aeijjz5Cly5dEBoa2iFxaQnmvrxEjT8HREREnVBkZCQqKyuRlJSEsrIyhIaGIjs7G/379wcAmM1mdOnyU5F/xIgR2L17N1asWIGVK1di4MCByMrKslsx9vzzz+OHH35AdHQ0rly5gmHDhiE3Nxfe3t62Njt37sTSpUttq9GmTp2KTZs2ddCnJpIPB0REClX/lNiG+ySW6OhoREdHO/1bXl6ew7EZM2ZgxowZTb6eRqNBYmIiEhMTm2zTq1cvZGZmtriP8+fPx/z581vcviMw9+Ulavx5DxERERGpHitERAol6tJXIlcx9+UlavxZISIiIiLVY4WISKFEXelB5CrmvrxEjT8rRERERKR6rBARKZSo8/hErmLuy0vU+HNARKRQopatiVzF3JeXqPHnlBkRERGpHitERAolNSpbi/ItjchVzH15iRp/VoiIiIhI9VghIlIoCYAk2e8TqQFzX16ixp8VIiIiIlI9VoiIFMoKDTQC/sAikauY+/ISNf4cEBEplKhLX4lcxdyXl6jx55QZERERqR4rREQKZZU00Aj4tFgiVzH35SVq/FkhIiIiItVjhYhvuSh3AAAgAElEQVRIoSSp0dJXUda+ErmIuS8vUePPChERERGpHitERAol6koPIlcx9+Ulavw5ICJSKFEvSkSuYu7LS9T4c8qMiIiIVI8VIiKFEnXpK5GrmPvyEjX+rBARERGR6rFCRKRQoi59JXIVc19eosafFSIiIiJSPVaIiBTq1rc0jd0+kRow9+UlavxZISIiIiLVY4WISKFEfRYIkauY+/ISNf4cEBEplPS/reE+kRow9+Ulavw5ZUZERESqxwoRkUKJWrYmchVzX16ixp8VIiIiIlI9VoiIlErUiXwiVzH35SVo/FkhIlVLS0tDcHAwvLy8EBYWhmPHjjXb/urVq4iJiUGfPn3g5eWFkJAQZGdnd1BviYiULTk5GUOHDoW3tzf8/f0xbdo0lJSUNHvO3r17ER4ejp49e+JnP/sZHnzwQbz55putfm8OiEi1srKyEBsbi4SEBBQVFSEiIgKTJk2C2Wx22r62thYTJkzA+fPnsWfPHpSUlCAjIwNBQUEd3PMW+t88vm0+X5B5fCKXMffl5UL8jxw5gpiYGJw4cQImkwl1dXUwGAy4fv16k+f06tULCQkJKCgowJkzZ/Db3/4Wv/3tb3Hw4MFWdZtTZqRaKSkpiIqKwoIFCwAAqampOHjwINLT05GcnOzQftu2bfjvf/+L/Px8dO3aFQDQv3//Du1za4j6e0JErmLuy8uV+Ofk5Njtb9++Hf7+/igsLMTo0aOdnjN27Fi7/WXLluGNN97A8ePHMXHixBa/NytEpEq1tbUoLCyEwWCwO24wGJCfn+/0nP3790Ov1yMmJgYBAQEIDQ3FunXrYLFYmnyfmpoaVFdX223UcRh/eTH+8umMsW/cn5qamtueU1VVBeBWFaglJEnCoUOHUFJS0uQAqikcEJEqXb58GRaLBQEBAXbHAwICUF5e7vScr7/+Gnv27IHFYkF2djZWrFiBl19+GWvXrm3yfZKTk6HVam2bTqdr08/RHKlR2VqUpa9tSc74k3zxZ+53zmuPTqez65OzSrz960iIi4vDqFGjEBoa2mzbqqoq9OjRAx4eHnjsscfw6quvYsKECa3qNwdEpGoajf2FUpIkh2P1rFYr/P39sWXLFoSFheGpp55CQkIC0tPTm3z9+Ph4VFVV2bbS0tI27T81j/GXF+Mvn84Y+9LSUrs+xcfHN9t+8eLFOHPmDN56663bvra3tzeKi4tx+vRprF27FnFxccjLy2tV/3gPEamSn58f3NzcHKpBFRUVDlWjen369EHXrl3h5uZmOxYSEoLy8nLU1tbCw8PD4RxPT094enq2bedbqvHNjCr8lixr/Em++DP3O+W1x8fHBz4+Pi16iSVLlmD//v04evQo7r777tu279KlC37+858DAB588EGcPXsWycnJDvcXNfsaLW5JpCAeHh4ICwuDyWSyO24ymTBixAin54wcORJfffUVrFar7dgXX3yBPn36OB0MERFR60iShMWLF2Pv3r04fPgwgoOD7/h1WnKPUkMcEJFqxcXF4fXXX8e2bdtw9uxZLF++HGazGYsWLQIAzJs3z66k++yzz6KyshLLli3DF198gffeew/r1q1DTEyMXB+hWfUrPRpuRGrA3JeXK/GPiYlBZmYmdu3aBW9vb5SXl6O8vBw//PCDrU3ja3NycjJMJhO+/vpr/Pvf/0ZKSgr+9re/Ye7cua3qN6fMSLUiIyNRWVmJpKQklJWVITQ0FNnZ2bal9GazGV26/PSdQafTITc3F8uXL8f999+PoKAgLFu2DL///e/l+gjNE/RpsUQuY+7Ly4X419+T2Xiqa/v27Zg/fz4Ax2vz9evXER0djW+++QbdunXD4MGDkZmZicjIyFZ1mwMiUrXo6GhER0c7/ZuzG/L0ej1OnDjRzr0iIlInqQXlpMbX5j/+8Y/44x//6PJ7c0BEpFCi/uI0kauY+/ISNf68h4iIiIhUjxUiIiXjvROkVsx9eQkYf1aIiIiISPVYISJSKFHn8YlcxdyXl6jxZ4WIiIiIVI8VIiKl4rNYSK2Y+/ISNP4cEBEpluZ/W8N9IjVg7stLzPhzyoyIiIhUjwMiIqWSnGxEatBGuZ+Wlobg4GB4eXkhLCwMx44da7b91atXERMTgz59+sDLywshISHIzs6+szdvJxp393bZ7Ah67eGUGRERUSNZWVmIjY1FWloaRo4cic2bN2PSpEn4/PPP0a9fP4f2tbW1mDBhAvz9/bFnzx7cfffdKC0thbe3twy9pzvBARGRUgl6YyORy9og91NSUhAVFYUFCxYAAFJTU3Hw4EGkp6cjOTnZof22bdvw3//+F/n5+ejatSsA2H4oWnUEvfZwyoyIiFShurrabqupqXHarra2FoWFhTAYDHbHDQYD8vPznZ6zf/9+6PV6xMTEICAgAKGhoVi3bh0sFkubfw5qHxwQESmVpHHciNSgidzX6XTQarW2zVmlBwAuX74Mi8WCgIAAu+MBAQEoLy93es7XX3+NPXv2wGKxIDs7GytWrMDLL7+MtWvXtu1nE4Gg1x5OmREplCTd2hruE6lBU7lfWloKHx8f23FPT89mX0ejsf8PuSRJDsfqWa1W+Pv7Y8uWLXBzc0NYWBi+/fZbvPTSS/jDH/5wZx9EUKJee1ghIqJmKXGlDamTj4+P3dbUgMjPzw9ubm4O1aCKigqHqlG9Pn364Be/+AXc3Nxsx0JCQlBeXo7a2tq2+xDUbjggIlKqNlj6Wr/SJiEhAUVFRYiIiMCkSZNgNpudtq9faXP+/Hns2bMHJSUlyMjIQFBQkAsfhKiVXMx9Dw8PhIWFwWQy2R03mUwYMWKE03NGjhyJr776Clar1Xbsiy++QJ8+feDh4dG6DohO0GX3HBARUZMarrQJCQlBamoqdDod0tPTnbavX2nzz3/+EyNHjkT//v0xatQoPPDAAx3ccyLXxMXF4fXXX8e2bdtw9uxZLF++HGazGYsWLQIAzJs3D/Hx8bb2zz77LCorK7Fs2TJ88cUXeO+997Bu3TrExMTI9RGolXgPEZFSNb6Z8X//Xl1dbdfM09PT6dRB/UqbF154we54S1fa7Nu3D71798bs2bPx+9//3m4qgahdNZH7rREZGYnKykokJSWhrKwMoaGhyM7Oti2lN5vN6NLlp5qCTqdDbm4uli9fjvvvvx9BQUFYtmwZfv/737v8cYTTBvGXAwdERCqj0+ns9letWoXExESHdne60ubw4cOYM2cOsrOz8eWXXyImJgZ1dXWqu7GUxBcdHY3o6Ginf8vLy3M4ptfrceLEiXbuFbUXDoiIFEoj3doa7gNcaUPK11TuU8cQNf4cEBEpVRNPi61fYXM7d7rSpmvXrk2utFHdzaUkD0GflKwYgsafN1UTkVNcaUNEasIBEZFStcHTYrnShoQk6JOSFUPQ+HPKjIiaxJU2RKQWHBARKVUbzeNzpQ0JR9B7WBRD0PhzyoyIiIhUjxUiIqUS9FsakcuY+/ISNP6sEBEREZHqsUJEpFSCfksjchlzX16Cxp8DIiKlEvT3hIhcxtyXl6Dx55QZERERqR4rREQKJervCRG5irkvL1HjzwoRERERqR4HRERKJTnZSChpaWkIDg6Gl5cXwsLCcOzYsWbbv/322xgyZAg8PT0xZMgQvPPOO3Z/lyQJiYmJ6Nu3L7p164axY8fis88+s2tz5coVGI1GaLVaaLVaGI1GXL161a7Np59+ijFjxqBbt24ICgpCUlISJKkTJRhzX16Cxp8DIiKiTigrKwuxsbFISEhAUVERIiIiMGnSJJjNZqftCwoKEBkZCaPRiE8++QRGoxEzZ87EyZMnbW3Wr1+PlJQUbNq0CadPn0ZgYCAmTJiAa9eu2drMnj0bxcXFyMnJQU5ODoqLi2E0Gm1/r66uxoQJE9C3b1+cPn0ar776KjZs2ICUlJT2CwZRB+CAiIQzf/58HD16VO5uELWrlJQUREVFYcGCBQgJCUFqaip0Oh3S09Odtk9NTcWECRMQHx+PwYMHIz4+Hg8//DBSU1MB3KoOpaamIiEhAdOnT0doaCjeeOMN3LhxA7t27QIAnD17Fjk5OXj99deh1+uh1+uRkZGBAwcOoKSkBACwc+dO/Pjjj9ixYwdCQ0Mxffp0vPjii0hJSelcVSKiVuKAiIRz7do1GAwGDBo0COvWrcPFixfl7lKnpMFPNzdqpFv71HEe187DhC7/Z9se184DcKvC0nCrqalxOLe2thaFhYUwGAx2xw0GA/Lz852+X0FBgUP7iRMn2tqfO3cO5eXldm08PT0xZswYW5uCggJotVoMGzbM1mb48OHQarV2bcaMGQNPT0+79/n2229x/vz5loanXTH35SVq/LnKjITz9ttvo7KyEpmZmdixYwdWrVqF8ePHIyoqCo8//ji6du0qdxdv650vPoWPd9t+H6m+ZoXvL9r0Jakd6HQ6u/1Vq1YhMTHR7tjly5dhsVgQEBBgdzwgIADl5eVOX7e8vLzZ9vX/dNbmwoULtjb+/v4Or+3v72/3OgMGDHB4jfq/BQcHO+1fQ22d/8z9ltv7eRGvPU3ggIiEdNddd2HZsmVYtmwZioqKsG3bNhiNRvTo0QNz585FdHQ0Bg0aJHc35SXow9GUYl/V3+Dj42Pbr66uhlarRWlpqd3xhpWWxjQa+//NJElyONba9rdr4+z1b9emfqqsub51KOa+vASNP6fMSGhlZWXIzc1Fbm4u3Nzc8Oijj+Kzzz7DkCFDsHHjRrm7R+TAx8fHbnM2IPLz84Obm5tDNaiiosKhwlMvMDCw2faBgYEAcNs23333ncNrX7p0ya6Ns9cAHKtPRCLhgIiEc/PmTbz99tuYPHky+vfvj3/84x9Yvnw5ysrK8MYbbyA3NxdvvvkmkpKS5O6qvARd+kqAh4cHwsLCYDKZ7I6bTCaMGDHC6Tl6vd6hfW5urq19cHAwAgMD7drU1tbiyJEjtjZ6vR5VVVU4deqUrc3JkydRVVVl1+bo0aOora21e5++ffs6TKXJhrkvL0HjzykzEk6fPn1gtVoxa9YsnDp1Cg8++KBDm4kTJ6Jnz54y9I6obcTFxcFoNCI8PBx6vR5btmyB2WzGokWLAADz5s1DUFAQkpOTAQDLli3D6NGj8ec//xmPP/449u3bh/fffx/Hjx8HcGs6KzY2FuvWrcOgQYNsixK6d++O2bNnAwBCQkLwyCOPYOHChdi8eTMA4JlnnsHkyZNx7733Ari1LH/16tWYP38+XnzxRXz55ZdYt24d/vCHP3SeKTOiO8ABEQln48aN+L//+z94eXk12cbX1xfnzp3rwF51QoL+4jTdEhkZicrKSiQlJaGsrAyhoaHIzs5G//79AQBmsxlduvxU5B8xYgR2796NFStWYOXKlRg4cCCysrLsVow9//zz+OGHHxAdHY0rV65g2LBhyM3Nhbe3t63Nzp07sXTpUttqtKlTp2LTpk22v2u1WphMJsTExCA8PBy+vr6Ii4tDXFxce4ek5Zj78hI0/hwQkXAaPiSOSMmio6MRHR3t9G95eXkOx2bMmIEZM2Y0+XoajQaJiYkOq9oa6tWrFzIzM5vt13333cdngZHicEBEpFCi/sAikauY+/ISNf4cEBEplaBlayKXMfflJWj8ucqMiIiIVI8VIiKlEvRbGpHLmPvyEjT+rBARERGR6rFCRKRQot7YSOQq5r68RI0/K0RERESkeqwQESmVoD+wSOQy5r68BI0/B0RESiXojY1ELmPuy0vQ+HPKjIiIiFSPFSIihRL1xkYiVzH35SVq/FkhIiIiItVjhYhIqQSdxydyGXNfXoLGnxUiIiIiUj1WiIiUqtE8vijf0ohcxtyXl6Dx54CISKkELVsTuYy5Ly9B488pMyIiIlI9VoiIlErQb2lELmPuy0vQ+LNCRERERKrHChGRQon6cDQiVzH35SVq/FkhIiIiItXjgIiIiIhUjwMiIiIiUj3eQ0SkVIKu9CByGXNfXoLGnwMiIoUS9cZGIlcx9+Ulavw5ZUZERESqxwoRkZIJ8s2MqM0x9+UlYPxZISIiIiLVY4WISKkEvbGRyGXMfXkJGn9WiIiIiEj1WCEiUihRV3oQuYq5Ly9R488BEZFSCVq2JnIZc19egsafU2ZERESkeqwQESmUqGVrIlcx9+UlavxZISIiIiLV44CIVC8tLQ3BwcHw8vJCWFgYjh071qLzdu/eDY1Gg2nTprVzD++Q5GQjUgPmvrxciH9ycjKGDh0Kb29v+Pv7Y9q0aSgpKWn2nIyMDERERMDX1xe+vr4YP348Tp061epuc0BEqpaVlYXY2FgkJCSgqKgIERERmDRpEsxmc7PnXbhwAc899xwiIiI6qKdERMp35MgRxMTE4MSJEzCZTKirq4PBYMD169ebPCcvLw+zZs3CBx98gIKCAvTr1w8GgwEXL15s1XvzHiJStZSUFERFRWHBggUAgNTUVBw8eBDp6elITk52eo7FYsGcOXOwevVqHDt2DFevXm3y9WtqalBTU2Pbr66ubtsP0BxBV3q0JVnjT/LFn7nfKa89jfvg6ekJT09Pu2M5OTl2+9u3b4e/vz8KCwsxevRop2+3c+dOu/2MjAzs2bMHhw4dwrx581rcbVaISLVqa2tRWFgIg8Fgd9xgMCA/P7/J85KSktC7d29ERUXd9j2Sk5Oh1Wptm06nc7nfLVV/Y2PDTW3kjD/JF3/mfue89uh0Ors+NfWls6GqqioAQK9evVr8/jdu3MDNmzdbdQ7AARGp2OXLl2GxWBAQEGB3PCAgAOXl5U7P+fDDD7F161ZkZGS06D3i4+NRVVVl20pLS13uN7Uc4y8vxl8+nTH2paWldn2Kj49vtr0kSYiLi8OoUaMQGhra4vd54YUXEBQUhPHjx7eqf5wyI9XTaDR2+5IkORwDgGvXrmHu3LnIyMiAn59fi17bWUm4w3DaQN74k3zxZ+53ymuPj48PfHx8WvwyixcvxpkzZ3D8+PEWn7N+/Xq89dZbyMvLg5eXV4vPAzggIhXz8/ODm5ubQzWooqLCoWoEAP/5z39w/vx5TJkyxXbMarUCANzd3VFSUoKBAwe2b6eJiFRgyZIl2L9/P44ePYq77767Reds2LAB69atw/vvv4/777+/1e/JKTNSLQ8PD4SFhcFkMtkdN5lMGDFihEP7wYMH49NPP0VxcbFtmzp1KsaNG4fi4uLOd38Klx6TWjH35eVC/CVJwuLFi7F3714cPnwYwcHBLTrvpZdewpo1a5CTk4Pw8PA76DQrRKRycXFxMBqNCA8Ph16vx5YtW2A2m7Fo0SIAwLx58xAUFITk5GR4eXk5zGP37NkTAFo1v01ERM7FxMRg165d2LdvH7y9vW0VfK1Wi27dugGwvy4Dt6bJVq5ciV27dmHAgAG2c3r06IEePXq0+L05ICJVi4yMRGVlJZKSklBWVobQ0FBkZ2ejf//+AACz2YwuXcQspIr6+HwiVzH35eVK/NPT0wEAY8eOtTu+fft2zJ8/H4DjdTktLQ21tbWYMWOG3TmrVq1CYmJii9+bAyJSvejoaERHRzv9W15eXrPn7tixo+07RESkUpJ0+9FT4+vy+fPn2+S9OSAiUiqutCG1Yu7LS9D4c0BEpFCcNiC1Yu7LS9T4i3lzBBEREVEbYoWISKkELVsTuYy5Ly9B488KEREREakeK0RESiXotzQilzH35SVo/FkhIiIiItVjhYhIoTT/2xruE6kBc19eosafAyIipRK0bE3kMua+vASNP6fMiIiISPVYISJSKFEfjkbkKua+vESNPytEREREpHqsEBEplaDz+EQuY+7LS9D4s0JEREREqscKEZGSCfLNjKjNMfflJWD8OSAiUihRb2wkchVzX16ixp9TZkRERKR6rBARKZWgNzYSuYy5Ly9B488KEREREakeB0REClU/j99wI1KDtsr9tLQ0BAcHw8vLC2FhYTh27FiLztu9ezc0Gg2mTZt2Z28sOFGvPRwQERERNZKVlYXY2FgkJCSgqKgIERERmDRpEsxmc7PnXbhwAc899xwiIiI6qKfUVjggIlIqyclGpAZtkPspKSmIiorCggULEBISgtTUVOh0OqSnpzd5jsViwZw5c7B69Wrcc889d9h5BRD02sMBERERqUJ1dbXdVlNT47RdbW0tCgsLYTAY7I4bDAbk5+c3+fpJSUno3bs3oqKi2rTf1DE4ICJSKFHn8Ylc1VTu63Q6aLVa25acnOz0/MuXL8NisSAgIMDueEBAAMrLy52e8+GHH2Lr1q3IyMho088iIlGvPVx2T6RUgi59JXJZE7lfWloKHx8f22FPT89mX0aj0di/rCQ5HAOAa9euYe7cucjIyICfn9+d9lo5BL32cEBERESq4OPjYzcgaoqfnx/c3NwcqkEVFRUOVSMA+M9//oPz589jypQptmNWqxUA4O7ujpKSEgwcONDF3lN745QZkVIJemMjkctczH0PDw+EhYXBZDLZHTeZTBgxYoRD+8GDB+PTTz9FcXGxbZs6dSrGjRuH4uJi6HS6O/0kYhL02sMBERE1i89iITWKi4vD66+/jm3btuHs2bNYvnw5zGYzFi1aBACYN28e4uPjAQBeXl4IDQ2123r27Alvb2+EhobCw8NDzo9CLcQpMyKFaosfWKx/FktaWhpGjhyJzZs3Y9KkSfj888/Rr1+/Js/js1hITm2R+5GRkaisrERSUhLKysoQGhqK7Oxs9O/fHwBgNpvRpQtrCs6I+uOuHBARUZMaPosFAFJTU3Hw4EGkp6c3uUKn4bNYjh07hqtXr3Zkl4naTHR0NKKjo53+LS8vr9lzd+zY0fYdonbF4S2RUjUxj89nsZDiCXoPi2IIGn8OiIgUSiNJDhvAZ7GQ8jWV+9QxRI0/p8yIVIbPYiEicsQBEZFSNfFwND6LhRRP0AcDKoag8eeUGRE5xWexiOPKlSswGo22aVCj0Xjbm9lramqwZMkS+Pn54Wc/+xmmTp2Kb775xq6N2WzGlClT8LOf/Qx+fn5YunQpamtr7docOXIEYWFh8PLywj333IO//vWvTb7nyy+/DACIX3v5Dj8pUfthhYhIodpi6WtcXByMRiPCw8Oh1+uxZcsWh2exBAUFITk52fYsloZ69uwJAA7HqW3Nnj0b33zzDXJycgAAzzzzDIxGI959990mz4mNjcW7776L3bt346677sLvfvc7TJ48GYWFhXBzc4PFYsFjjz2G3r174/jx46isrMTTTz8NSZLw6quvAgDOnTuHRx99FAsXLkRmZiY+/PBDREdHo3fv3njyySft3u/06dMdtvJK1GXfSiFq/DkgIqIm8Vksnd/Zs2eRk5ODEydOYNiwYQCAjIwM6PV6lJSU4N5773U4p6qqClu3bsWbb76J8ePHAwAyMzOh0+nw/vvvY+LEicjNzcXnn3+O0tJS9O3bF8CtCs/8+fOxdu1a+Pj44K9//Sv69euH1NRUAEBISAg++ugjbNiwwW5A9P3332POnDl45ZVX+KBO6rQ4ICJSqjaax+ezWNpWdXW13b6np+dtb2xvTkFBAbRarW0wBADDhw+HVqtFfn6+0wFRYWEhbt68afdIhb59+yI0NBT5+fmYOHEiCgoKEBoaahsMAcDEiRNRU1ODwsJCjBs3DgUFBQ6PZZg4cSK2bt2KmzdvomvXrgCAmJgYPPbYYxg3btwdf85WEfQeFsUQNP78akekUPVl64Ybya+ljz1oqfLycvj7+zsc9/f3b/LxCOXl5fDw8ICvr6/d8YaPVCgvL3e4ed7X1xceHh7NtgkICEBdXR0uX751n9Du3bvx8ccfu/w5W4O5Ly9R488KERFRB2rpYw8SExOxevXqZl/r9OnTABwfjQA0/XiE5jQ+pyWv6+yxDPXHS0tLsWzZMuTm5sLLy8vhhmyizoQDIiKlErRsrXQtfezB4sWL8dRTTzXbZsCAAThz5gy+++47h79dunTJ6eMRACAwMBC1tbW4cuWKXZWooqLCtoIwMDAQJ0+etDvvypUruHnzpu11AwMDnT6Wwd3dHXfddRfee+89VFRUICwszK7N5r9VIyOzGj9cGAg3t9YN2lqEuS8vQePPARERUSfk5+fXogdc6vV6VFVV4dSpU/j1r38NADh58iSqqqqcPh4BAMLCwtC1a1eYTCbMnDkTAFBWVoZ//etfWL9+ve11165di7KyMvTp0wcAkJubC09PT9sAR6/XO6xky83NRXh4OLp27YqHH34Yn376qe1v33//PfR6Pf5vSg8kLPdtn8EQ0R3iPURECiXqPD61TkhICB555BEsXLgQJ06cwIkTJ7Bw4UJMnjzZdkP1xYsXMXjwYJw6dQoAoNVqERUVhd/97nc4dOgQioqKMHfuXNx33322VWcGgwFDhgyB0WhEUVERDh06hOeeew4LFy60VbgWLVqECxcuIC4uDmfPnsW2bduwdetWPPfccwAAb29vhIaG2rYhQ4YAAHr5dkHo4Du/kfx2mPvyEjX+HBAREQlu586duO+++2AwGGAwGHD//ffjzTfftP395s2bKCkpwY0bN2zHNm7ciGnTpmHmzJkYOXIkunfvjnfffRdubm4AADc3N7z33nvw8vLCyJEjMXPmTEybNg0bNmywvUZwcDCys7ORl5eHBx98EGvWrMErr7zi8AwiIhFwyoxIqQSdx6fW69WrFzIzM5v8+4ABA2w3O9fz8vLCq6++anvIojP9+vXDgQMHmn3vMWPG4OOPP25Vf5MT2vm37pj78hI0/qwQERERkeqxQkSkYKLM3RO1Nea+vESMPwdEREolSbe2hvtEasDcl5eg8eeUGREREakeK0RECiXqL04TuYq5Ly9R488KEREREakeK0RESiXo0lcilzH35SVo/FkhIiIiItVjhYhIoTTWW1vDfSI1YO7LS9T4c0BEpFSClq2JXMbcl5eg8eeUGREREakeK0RECiXq0lciVzH35fOUHYoAAB2sSURBVCVq/FkhIiIiItVjhYhIqQR9fD6Ry5j78hI0/qwQERERkeqxQkSkUKLO4xO5irkvL1HjzwERkVIJuvSVyGXMfXkJGn9OmREREZHqsUJEpFCilq2JXMXcl5eo8WeFiIiIiFSPFSIipRJ06SuRy5j78hI0/qwQERERkeqxQkSkUKLO4xO5irkvL1HjzwoRERERqR4rRERKJeizQIhcxtyXl6Dx54CISKFELVsTuYq5Ly9R488pMyIiIlI9VoiIlMoq3doa7hOpAXNfXoLGnxUiIiIiUj1WiIiUStAbG4lcxtyXl6DxZ4WIiIiIVI8VIiKF0qDRSg/ZekLUsZj78hI1/hwQESmVoL8nROQy5r68BI0/p8yIiIhI9TggItVLS0tDcHAwvLy8EBYWhmPHjjXZNiMjAxEREfD19YWvry/Gjx+PU6dOdWBvW67+4WgNNyI1YO7Ly5X4JycnY+jQofD29oa/vz+mTZuGkpKSZs/57LPP8OSTT2LAgAHQaDRITU29o35zQESqlpWVhdjYWCQkJKCoqAgRERGYNGkSzGaz0/Z5eXmYNWsWPvjgAxQUFKBfv34wGAy4ePFiB/eciEh5jhw5gpiYGJw4cQImkwl1dXUwGAy4fv16k+fcuHED99xzD/70pz8hMDDwjt+b9xCRqqWkpCAqKgoLFiwAAKSmpuLgwYNIT09HcnKyQ/udO3fa7WdkZGDPnj04dOgQ5s2b1yF9bjFBl74SuYy5Ly8X4p+Tk2O3v337dvj7+6OwsBCjR492es7QoUMxdOhQAMALL7zQys7+hAMiUq3a2loUFhY6/B/IYDAgPz+/Ra9x48YN3Lx5E7169XL695qaGtTU1Nj2q6ur77zD1GqMv7wYf/l0xtg37oOnpyc8PT2bPaeqqgoAmrzGtiVOmZFqXb58GRaLBQEBAXbHAwICUF5e3qLXeOGFFxAUFITx48c7/XtycjK0Wq1t0+l0Lve7pTSS5LCpjZzxJ/niz9zvnNcenU5n1ydnVfiGJElCXFwcRo0ahdDQ0HbvNwdEpHoajf1TMiRJcjjmzPr16/HWW29h79698PLyctomPj4eVVVVtq20tLRN+twiViebysgaf5Iv/sz9TnntKS0ttetTfHx8sy+zePFinDlzBm+99VY7d/gWTpmRavn5+cHNzc2hGlRRUeFQNWpsw4YNWLduHd5//33cf//9TbZrSUmY2g/jLy/GXz6dMfY+Pj7w8fFpUdslS5Zg//79OHr0KO6+++527tktrBCRanl4eCAsLAwmk8nuuMlkwogRI5o876WXXsKaNWuQk5OD8PDw9u7mHeO0AakVc19ersRfkiQsXrwYe/fuxeHDhxEcHNyOPbXHChGpWlxcHIxGI8LDw6HX67FlyxaYzWYsWrQIADBv3jwEBQXZ5rrXr1+PlStXYteuXRgwYICtutSjRw/06NFDts9BRKQEMTEx2LVrF/bt2wdvb2/bNVar1aJbt24AHK/LtbW1+Pzzz23/fvHiRRQXF6NHjx74+c9/3uL35oCIVC0yMhKVlZVISkpCWVkZQkNDkZ2djf79+wMAzGYzunT5qZCalpaG2tpazJgxw+51Vq1ahcTExI7s+u1x6TGpFXNfXi7EPz09HQAwduxYu+Pbt2/H/PnzAThel7/99ls89NBDtv0NGzZgw4YNGDNmDPLy8lr83hwQkepFR0cjOjra6d8a/5/p/Pnz7d8hIiKVklowvdb4ujxgwIAWnXc7HBARKZWgP7BI5DLmvrwEjT9vqiYiIiLVY4WISKEa/6gif+CS1IK5Ly9R488BEZFSCVq2JnIZc19egsafU2ZERESkeqwQESmUxnpra7hPpAbMfXmJGn9WiIiIiEj1WCEiUipB5/GJXMbcl5eg8WeFiIiIiFSPFSIipeLPF5BaMfflJWj8OSAiUqjGvzLNX/wmtWDuy0vU+HPKjIiIiFSPFSIipRL0xkYilzH35SVo/FkhIiIiItVjhYhIqSQA1kb7RGrA3JeXoPFnhYiIiIhUjxUiIoUSdaUHkauY+/ISNf4cEBEplYRGNzbK1hOijsXcl5eg8eeUGREREakeK0RESiXo0lcilzH35SVo/FkhIiIiItVjhYhIqawANI32idSAuS8vQePPChERERGpHitERAol6tJXIlcx9+UlavxZISIiIiLVY4WISKkEXelB5DLmvrwEjT8HRERKJehFichlzH15CRp/TpkRERGR6rFCRKRUgn5LI3IZc19egsafFSIiIiIn0tLSEBwcDC8vL4SFheHYsWNNts3IyEBERAR8fX3h6+uL8ePH49SpUx3YW3IVB0RESmV1shGpQRvkflZWFmJjY5GQkICioiJERERg0qRJMJvNTtvn5eVh1qxZ+OCDD1BQUIB+/frBYDDg4sWLLnwQQQl67eGAiIiIqJGUlBRERUVhwYIFCAkJQWpqKnQ6HdLT052237lzJ6Kjo/Hggw9i8ODByMjIgNVqxaFDhzq453SnOCAiUqj6h6M13IjUoKncr66utttqamqcnl9bW4vCwkIYDAa74waDAfn5+S3qw40bN3Dz5k306tXLtQ8jIFGvPRwQESlV/Y2NDTciNWgi93U6HbRarW1L/v/t3X1MVFfeB/DvwLwhL7NSyoxQQJrNCkhdU6jtaLvUdgvaN326jfo0nULSZcOirRbts2pfpDRVtLZLi6WmG2sarbUvrLGthoC2oBZwhVW2jUSbrAKtTKmugn2RtznPH3buOs4MAjPD5c79fpKJ3jvnnjn3l+P1N+eeM3fdOo+Hnz17FoODgzCbzS77zWYz7Hb7sJqwcuVKxMfH4/e//71v56JECr32cJUZERGpQkdHB6KioqRtg8EwZHmNRuOyLYRw2+fJhg0b8N5776G2thZGo3F0jaUxxxEiomDlEO4vCkrnz5+HzWaTRj5sNhsuXLgw5DG9vb144oknEBMTg/DwcDz44IP45ptvXMq0t7fjgQceQHh4OGJiYvDkk0+ir6/PpUxdXR0yMjJgNBpx4403YvPmzS7vDwwM4Nlnn0VycrI04rJh03k4AtkfvfT9qKgol5e3hCgmJgahoaFuo0FdXV1uo0ZX27hxI9auXYvq6mpMmzbNP+ejNAq99jAhIiJSuEceeQTHjh1DVVUVqqqqcOzYMdhstiGPWbZsGXbt2oWdO3fi0KFD+OGHH3D//fdjcHAQADA4OIj77rsPP/74Iw4dOoSdO3eisrISy5cvl+o4deoU7r33Xtxxxx04evQoVq9ejSeffBKVlZVSmfXr12Pz5s3YtGmTtAy9fMsFbNrSHYBI+Ider0dGRgZqampc9tfU1GDmzJlej3v55Zfx4osvoqqqCpmZmYFuJvkZb5kRBSuF/jhasOvp6XHZNhgM17x1M5TW1lZUVVWhsbERt956K4DLv4ljtVpx4sQJTJkyxe2Y7u5ubNmyBdu2bZPmuGzfvh0JCQnYt28fcnJyUF1djePHj6OjowNxcXEAgFdeeQV5eXl46aWXEBUVhc2bNyMxMRFlZWUAgNTUVDQ1NWHjxo34wx/+AABoaGjAvHnzcN9990nnPntWGJpaPE9o9gs/9P2ioiLYbDZkZmbCarXirbfeQnt7OwoKCgAAjz32GOLj46V5SBs2bMBzzz2HHTt2YPLkydLoUkREBCIiInw/JyVR6LWHI0RERGNouBN7h6uhoQEmk0lKhgDgtttug8lk8roiqrm5Gf39/S6rqOLi4pCeni4d09DQgPT0dCkZAoCcnBz09vaiublZKnP1SqycnBw0NTWhv78fAHD77bdj//79OHnypFSmsbkXc++e4NN5B9rChQtRVlaGkpISTJ8+HQcOHMDevXuRlJQE4PLtxM7OTql8RUUF+vr68PDDD2PSpEnSa+PGjXKdAo0QR4iIgtbVqzuU8S0t2I10Yu+12O12xMbGuu2PjY31uiLKbrdDr9dj4sSJLvuvXEVlt9vd5stMnDgRer1+yDJmsxkDAwM4e/YsJk2ahL/85S/o7u5GSkoKQkNDAQAFuVH43/+JHN0JD4t/+n5hYSEKCws9vldbW+uyffr06VF9RnBS5rWHI0REwUqhS1+D3XAn9hYXF0Oj0Qz5ampqAuC+GgoY/oqooY4ZTr2eVmJduf/999/H9u3bsWPHDhw4cAAAsOntbrzzgeutQ79i35eXQuPPhIiIhsTnOcljyZIlaG1tHfKVnp4Oi8WC7777zu3477//3uuKKIvFgr6+Ppw/f95l/5WrqCwWi9sI0/nz59Hf3z9kma6uLmi1Wlx33XUAgKeffhorV67EokWLMHXqVABAYZ4J6193/WwiuTEhIgpWflj6yuc5yScmJgYpKSlDvoxGI6xWK7q7u10Sz8OHD6O7u9vriqiMjAzodDqXVVSdnZ346quvpGOsViu++uorl3ky1dXVMBgMyMjIkMpcvRKruroamZmZ0Ol0AC7/YnNIiOt/NSEhAV6JrdBl30FDofFnQkREXvF5TuNfamoq5syZg/z8fDQ2NqKxsRH5+fm4//77pRVm3377LVJSUqSkyWQy4fHHH8fy5cuxf/9+HD16FI8++ihuuukmadVZdnY20tLSYLPZcPToUezfvx8rVqxAfn6+NAeqoKAAbW1tKCoqQmtrK95++21s2bIFK1askNr3wAMP4KWXXsKePXvQ1tYGAKjY2o35c8PHMkxE18SEiChYCYf7C3yeUzB69913cdNNNyE7OxvZ2dmYNm0atm3bJr3f39+PEydO4KeffpL2/fWvf8X8+fOxYMECzJo1CxMmTMAnn3wiTXwODQ3Fnj17YDQaMWvWLCxYsADz5893WTWVnJyMvXv3ora2FtOnT8eLL76I119/XVpyDwDl5eV4+OGHUVhYiBkzZgAA8hZFoeT/rgtcQLz0fRojCo0/V5kRqUxCQoLL9po1a1BcXOxWjs9zUo7o6Ghs377d6/uTJ0+WJjs7GY1GlJeXo7y83OtxiYmJ+PTTT4f87KysLPzzn//0+n5kZCTKyspQVlaGnp4emEwmPPtUNPT6kU34Jgo0JkREwcrLj6PxeU4U9BT6w4BBQ6HxZ0JEpDLO5d7X4o/nOe3bt0+9z3MiIkXhHCKiYOXjSg8+z4kUS6GrnIKGQuPPESKiYMXnOZFaKfSWTdBQaPyZEBGRVwsXLsS5c+dQUlKCzs5OpKenuz3P6crfmLnyeU5X8jZxm4hovGBCRBSsBK76lja6avg8J1IcP/V9GiWFxp9ziIiIiEj1OEJEFKwUeh+fyGfs+/JSaPw5QkRERESqxxEiomDlcABwXLVNpALs+/JSaPyZEBEFK4UOWxP5jH1fXgqNP2+ZERERkepxhIgoWCn0WxqRz9j35aXQ+HOEiIiIiFSPI0REwcoh4PKLaAp5nhCRz9j35aXQ+HOEiIiIiFSPI0REQUoIB4RwuGwTqQH7vryUGn8mRETBSgjXoWqFTGwk8hn7vrwUGn/eMiMiIiLV4wgRUbASV01sVMi3NCKfse/LS6Hx5wgRERERqR5HiIiClcMBaK6YzKiQiY1EPmPfl5dC488RIiIiIlI9jhARBSuF3scn8hn7vrwUGn+OEBEREZHqcYSIKEgJhwNCo7wfRyPyFfu+vJQafyZERMFKocPWRD5j35eXQuPPW2ZERESkehwhIgpWDgFolPctjchn7PvyUmj8OUJEREREqscRIqJgJQQAx1XbRCrAvi8vhcafI0RERESkehwhIgpSwiEgrriPLxTyLY3IV+z78lJq/JkQEQUr4YDrsLUyfguEyGfs+/JSaPx5y4xUr6KiAsnJyTAajcjIyMDBgweHLF9ZWYm0tDQYDAakpaVh165dY9RSIqLgtm7dOtxyyy2IjIxEbGws5s+fjxMnTlzzOH9cl5kQkaq9//77WLZsGZ555hkcPXoUd9xxB+bOnYv29naP5RsaGrBw4ULYbDa0tLTAZrNhwYIFOHz48Bi3/NqEQ7i9iNSAfV9evsS/rq4OixcvRmNjI2pqajAwMIDs7Gz8+OOPXo/x13WZCRGp2quvvorHH38cf/zjH5GamoqysjIkJCTgzTff9Fi+rKwM99xzD1atWoWUlBSsWrUKd999N8rKysa45UREwaeqqgp5eXmYOnUqfvvb32Lr1q1ob29Hc3Oz12P8dV3mHCJSrb6+PjQ3N2PlypUu+7Ozs1FfX+/xmIaGBjz11FMu+3Jycrz+w+vt7UVvb6+03d3dDQD4IawOIROifGm+mx8GegAkwOG4fL9+QPS63LsfQD8A5Uxw9Adv8d/WsQlRUf6Nf09PDxISdkvx7+npcXsfYPwB//d/9n134/Ha42yDk8FggMFgGLJu5zHR0dFey4z0uuwNEyJSrbNnz2JwcBBms9llv9lsht1u93iM3W4fUfl169bhhRdecNufkJAwylZf23/+8x8AwCHsDdhnKIUc8e/o6BjyMy5evAiTyRSwzx9Pxjr+zth76/uM/dj0fW/xT0xMdNles2YNiouLvdYnhEBRURFuv/12pKeney030uuyN0yISPU0Go3LthDCbd9oy69atQpFRUXS9oULF5CUlIT29na/X5i7u7uRmJiIpKQkt29iV4qMjPTr545ncsQ/NTUVHR0diIyMdOkXQghcvHgRcXFxfv3c8Wys4s/Yuxtvff/cuXOIjo5GSMh/Z+pca3RoyZIl+Ne//oVDhw5dsw0jvY57woSIVCsmJgahoaFu3yK6urrcvm04WSyWEZX3NiRsMpn8fsvGKTQ0NGB1K40c8ddqtbjhhhs8vqeW0QmnsY4/Y/9fSu/7TzzxBD7++GMcOHDAa51OI70ue8NJ1aRaer0eGRkZqKmpcdlfU1ODmTNnejzGarW6la+urvZanoiIhk8IgSVLluDvf/87PvvsMyQnJ1/zGH9dlzlCRKpWVFQEm82GzMxMWK1WvPXWW2hvb0dBQQEA4LHHHkN8fDzWrVsHAFi6dCl+97vfYf369Zg3bx52796Nffv2DWtIl4iIhrZ48WLs2LEDu3fvRmRkpDTyYzKZEBYWBiCA12VBpHJvvPGGSEpKEnq9Xtx8882irq5Oei8rK0vk5ua6lP/www/FlClThE6nEykpKaKysnLYn3Xp0iWxZs0acenSJX81f0zqDhaMv7wCFSPG/tqU0vcBeHxt3bpVKuPv67KT5pcGEBEREakW5xARERGR6jEhIiIiItVjQkRERESqx4SIiIiIVI8JEZGPKioqkJycDKPRiIyMDBw8eHDI8pWVlUhLS4PBYEBaWhp27drl8r4QAsXFxTCZTAgJCUFISAimTp3qc715eXnQaDQur9tuu210Jz1OBCr2cXFx0Ol0CAsLg8Fg8EvdjD/j72+89vjZqNfGEZHYuXOn0Ol04m9/+5s4fvy4WLp0qQgPDxdtbW0ey9fX14vQ0FCxdu1a0draKtauXSu0Wq1obGyUypSWlgqj0Si0Wq0oLi4Wc+fOFRMmTPC53tzcXDFnzhzR2dkpvc6dO+ffgIyhQMU+MjJSFBUVCa1WKzIzM0VMTIz485//zPhfhfGXF689/seEiMgHM2bMEAUFBS77UlJSxMqVKz2WX7BggZgzZ47LvpycHLFo0SIhhBAOh0NYLBaRkJAg1Xvp0iVhMpmExWIZdb1CXL4ozZs3b2QnOI4FKvalpaVS3c7Yb9682ae6hWD8GX//4rXH/3jLjGiU+vr60NzcjOzsbJf92dnZqK+v93hMQ0ODW/mcnByp/KlTp2C323HmzBmpnMFgQFZWFn71q1+Nul6n2tpaxMbG4je/+Q3y8/PR1dU1/BMeRwIZ+9mzZ0t1O2NfX1/vU91OjD/j7w+89gQGEyKiUTp79iwGBwfdHiBoNpvdHjToZLfbhyzv/PPqes1mMwYGBkZdLwDMnTsX7777Lj777DO88sorOHLkCO666y709vYO84zHj0DGXqvVutTtLONL3QDjz/j7D689gcFnmRH5SKPRuGwLIdz2jab8lfvELz8o70u9CxculP6enp6OzMxMJCUlYc+ePXjooYe81jueBSL2zm3nn84yvtbN+DP+/sZrj38xISIapZiYGISGhrp9c+rq6nL7xuRksViGLG+xWADArd6uri5otVrExsaOql5PJk2ahKSkJHz99ddey4xXgYx9f3+/S93OMr7U7Qnjz/iPFq89gcFbZkSjpNfrkZGRgZqaGpf9NTU1mDlzpsdjrFarW/nq6mqpfHJyMiwWC+Li4qRyfX19qKurw4ULF0Zdryfnzp1DR0cHJk2aNPSJjkOBjH1tba1UtzP2M2fO9KluTxh/xn+0eO0JkLGexU0UTJxLX7ds2SKOHz8uli1bJsLDw8Xp06eFEELYbDaX1RlffPGFCA0NFaWlpaK1tVWUlpZ6XPoaFhYmtFqtKCkpEffee68IDw/3qd6LFy+K5cuXi/r6enHq1Cnx+eefC6vVKuLj40VPT89YhMrvAhV7k8kkLfueMWOGiImJEYWFhYz/VRh/efHa439MiIh89MYbb4ikpCSh1+vFzTffLOrq6qT3srKyRG5urkv5Dz/8UEyZMkXodDqRkpIiKisrXd53OBxizZo1IioqSgAQGo1GpKam+lTvTz/9JLKzs8X1118vdDqdSExMFLm5uaK9vd1/gZBBoGJvsViEVqsVBoNB6HQ6n+tm/C9j/P2L1x7/0gjxy4wpIiIiIpXiHCIiIiJSPSZEREREpHpMiIiIiEj1mBARERGR6jEhIiIiItVjQkRERESqx4SIiIiIVI8JEREREakeEyIiIiJSPSZEREREpHpMiIiIiEj1mBARjTPff/89LBYL1q5dK+07fPgw9Ho9qqurZWyZOjD+8mHs5aX6+Mv9dFkicrdnzx6h0+nEkSNHxMWLF8Wvf/1rsXTpUrmbpRqMv3wYe3mpOf582j3ROLV48WLs27cPt9xyC1paWnDkyBEYjUa5m6UajL98GHt5qTX+TIiIxqmff/4Z6enp6OjoQFNTE6ZNmyZ3k1SF8ZcPYy8vtcafc4iIxql///vfOHPmDBwOB9ra2uRujuow/vJh7OWl1vhzhIhoHOrr68OMGTMwffp0pKSk4NVXX8WXX34Js9ksd9NUgfGXD2MvLzXHnwkR0Tj09NNP46OPPkJLSwsiIiIwe/ZsREZG4tNPP5W7aarA+MuHsZeXquMv33xuIvLk888/F1qtVhw8eFDa19bWJkwmk6ioqJCxZerA+MuHsZeX2uPPESIiIiJSPU6qJiIiItVjQkRERESqx4SIiIiIVI8JEREREakeEyIiIiJSPSZEREREpHpMiIiIiEj1mBARERGR6jEhIiIiItVjQkRERESqx4SIiIiIVI8JEREREakeEyIiIiJSPSZEREREpHpMiIiIiEj1mBARERGR6o0oIbrzzjuxbNmyQLVFMb788ktkZWUhLCwM8fHxKCkpgRBC7mYRERHRKGnlboDS9PT04J577sHs2bNx5MgRnDx5Enl5eQgPD8fy5cvlbh4RERGNgkYMc2gjLy8P77zzjsu+U6dOYfLkyYFo17j15ptvYtWqVfjuu+9gMBgAAKWlpSgvL8c333wDjUYjcwuJiIhopIZ9y+y1116D1WpFfn4+Ojs70dnZiYSEBI9lCwoKEBERMeSrvb3dbycxlhoaGpCVlSUlQwCQk5ODM2fO4PTp0/I1jIiIiEZt2LfMTCYT9Ho9JkyYAIvFMmTZkpISrFixYsgycXFxw/3occVut7uNipnNZum95ORkGVpFREREvgjIHKLY2FjExsYGoupx4erbYs67jrxdRkREpEwBWXYfzLfMLBYL7Ha7y76uri4A/x0pIiIiImUZ0QiRXq/H4ODgNcsF8y0zq9WK1atXo6+vD3q9HgBQXV2NuLg41U0wJyIiChbDXmUGAH/6059w7NgxfPDBB4iIiEB0dDRCQtT1247d3d2YMmUK7rrrLqxevRpff/018vLy8Pzzz3PZPRERkUKNKCE6efIkcnNz0dLSgp9//lmVy+6Byz/MuHjxYvzjH//AxIkTUVBQgOeff55ziIiIiBRqRAkRERERUTBS1/0uIiIiIg+YEBEREZHqMSEiIiIi1WNCRERERKrHhIiIiIhUjwkRERERqR4TIiIiIlI9JkRERESkekyIiIiISPWYEBEREZHqMSEiIiIi1ft/qGmKb1+EBgEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed91ff28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed9237b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "          The script analysis/sod_compare.py can be used to compare\n",
      "          this output to the exact solution.  Some sample exact solution\n",
      "          data is present as analysis/sod-exact.out\n",
      "          \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<compressible_sdc.simulation.Simulation at 0x7f6bed955080>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee3a9a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       0.1       0.1       0.1       0.1 \n",
      "       0.1       0.1       0.1       0.1 \n",
      "       0.1       0.1       0.1       0.1 \n",
      "       0.1       0.1       0.1       0.1 \n",
      "       0.1       0.1       0.1       0.1 \n",
      "       0.1       0.1       0.1       0.1 \n",
      "  0.099996  0.099996  0.099996  0.099996 \n",
      "   0.10175   0.10175   0.10175   0.10175 \n",
      "   0.99825   0.99825   0.99825   0.99825 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "         1         1         1         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"pressure\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## diffusion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"diffusion\"\n",
    "problem_name = \"gaussian\"\n",
    "param_file = \"inputs.gaussian\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=16\",  \"mesh.ny=16\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the Gaussian diffusion problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6beda427b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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o6V1tisnMJrhuqd8vomsTQERcXWfdj1sZi5l1kMF2B9A6XZsAzMzGqpt6+BThBGBmltclPXyKcAIwM8vzHYCZWTW5CsjMrKqcAMzMKihA7gVkZlZRvgMwM6smtwFYNZX4w5+0u9ypJj1/aKn93rLlvWPe58Fn/6HUucoqE2PZ76PU91+hHzirzwnAzCyvQgnSCcDMbIgbgc3MKsx3AGZm1SOq1Qjc1RPClJWmkHxCUq+kK+tsd4GkkDSrlfGZ2Tiq0IQwTgDDSJoM3AzMB2YCiyXNrLHdUcDHgYdbG6GZjZuC8wF3y12CE8BIZwG9EfFUROwGvg4srLHdtcANwIutDM7MxpnvACrtROCZ3Pu+VLaPpDcCJ0XEt+sdSNJSSZslbR7Y9evmR2pmTafBYks3cAIYqdZg4PvyfZpT+EbgU40OFBGrImJWRMyafMSRTQzRzMaN7wAqrQ84Kfd+OvBs7v1RwGnAfZKeBuYAa90QbNYFiv74F0gAklZL2ibp0VHWS9JNqbPJFkln5tYtkfRkWpbkyt8k6V/TPjdJUio/TtKGtP0GSVOLfFwngJE2ATMknSLpUGARsHZoZUTsjIieiDg5Ik4GNgLnR8Tm9oRrZs3UxEbgW4B5ddbPB2akZSmwArIfc+AaYDZZm+Q1uR/0FWnbof2Gjn8lcG9EzADuTe8bcgIYJiL2ApcD64EfA3dGxGOSlks6v73Rmdm4a9IdQETcD/TX2WQhsCYyG4FjJU0DzgM2RER/ROwANgDz0rqjI+KhiAhgDfDu3LFuTa9vzZXX5QfBaoiIdcC6YWVXj7Lt2a2IaSxKd1Er0bA1aW+5U03ZWe7a47nHThjzPq/d9pFS5yqrzMBuZb+PMt9/2QbMbun62EgLP+doHU7qlffVKAd4ZURsBYiIrZIK/UNxAjAzGxKM5UKoR1K+6ndVRKwaw9lG63Ay1vLSnADMzBJR+1d2FNsj4mA6f4zW4aQPOHtY+X2pfHqN7QGekzQtXf1PA7YVCcBtAGZmea3rBroWuDD1BpoD7EzVOOuBuZKmpsbfucD6tO6Xkuak3j8XAt/MHWuot9CSXHldvgMwM8tpVhuApNvJruR7JPWR9eyZAhARK8naGRcAvcAu4OK0rl/StWQ9EgGWR8RQY/KlZL2LXgbcnRaALwB3SroE+Bnw/iIxOgGYmeU1KQFExOIG6wO4bJR1q4HVNco3kz2HNLz8BeDcscboBGBmNsQTwpiZVVhFuruCE4CZ2QGq8rwDOAGYmR3ICcDMrJp8B2BmVkVdNNRzEU4AZmaJcC8gM7Pq8h2ANV3ZW8sxDExy0ErEp4Fyp5r8Urn91D/20UsGf3V4uZOVNGl3iX1Kjqpa6vvvhB+4MjE26wne6IQvqDmcAMzMhrgNwMysutwLyMysotwIbGZWVb4DMDOroOITvncFJwAzszwnADOz6hG+AzAzqy4/B2BmVkGeEMbMrLqcAMzMqqo6NUBOAGZmeW4ENjOrosCNwDaBtHAE0VJXPiXrS8teZZWpn528p9y5SiszqmrZeucy52r171uH/Z76DsDMrII8IYyZWVVFVKoKaOyza5iZdTFFsaXQsaR5kp6Q1CvpyhrrXyPpXklbJN0naXpu3fWSHk3LB3Plb5f0g1R+q6RDUvnZknZK+lFarm4UnxOAmVleFFwakDQZuBmYD8wEFkuaOWyzvwDWRMTpwHLg82nfPwDOBM4AZgPLJB0taRJwK7AoIk4DfgosyR3vgYg4Iy3LG8XoBGBmltPEO4CzgN6IeCoidgNfBxYO22YmcG96/b3c+pnAP0fE3oj4NfAIMA84HngpIn6SttsAvK/sZ3UCMDMbEsBAFFsaOxF4Jve+L5XlPcL+H/D3AEdJOj6Vz5d0hKQe4BzgJGA7MEXSrLTPBal8yO9JekTS3ZLe0ChAJ4AaCtTbfVLS46ne7l5Jr2lHnGbWfGO4A+iRtDm3LB1+qBqHH545Pg28TdIPgbcBPwf2RsQ9wDrg+8DtwEOpPIBFwI2S/h/wS2BvOtYPgNdExO8C/wv4RqPP6l5Aw+Tq7d5JlrE3SVobEY/nNvshMCsidkm6FLgB+ODIo5lZxyneC2h7RMyqs76PA6/OpwPPHniqeBZ4L4CklwPvi4idad11wHVp3W3Ak6n8IeCtqXwucGoq/0XuuOsk/W9JPRGxfbQAfQcwUsN6u4j4XkTsSm83kv2PNbMu0MQ2gE3ADEmnSDqU7Mp97QHnknpSwy7AVcDqVD45VQUh6XTgdOCe9P6E9N/DgM8AK9P7V0lSen0W2e/7C/UC9B3ASLXq7WbX2f4S4O5xjcjMWqNgD59Ch4rYK+lyYD0wGVgdEY9JWg5sjoi1wNnA5yUFcD9wWdp9CvBA+j3/BfDhiBiq6lkm6V1kP/ArIuK7qfwC4FJJe4HfkPUUqvtpnABGKlJvl20ofRiYRVZ3V2v9UmApwJSjpjYrPjMbJ9mMYM17ECwi1pHV5efLrs69vgu4q8Z+L5L1BKp1zGXAshrlXwK+NJb4nABGalhvByDpHcCfAm+LiJdqHSgiVgGrAF72ypOq83ihWQdTsR4+XcEJYKR99XZkLfKLgA/lN5D0RuBvgHkRsa31ITZQ9u+3xCBypQfOavV+E1xHDEDWCTEerCZWAXUCJ4BhCtbbfRF4OfD3qY7uZxFxftuCNrMmqdZYQE4ANRSot3tHy4Mys5boiLuxJnECMDPL8x2AmVkFhecDMDOrrkHfAZiZVVIznwOY6JwAzMzynADMzCooALcBmJlVjwhXAZmZVdZgdW4BnADMzIa4CsjMrLpcBWRmVlVOAFZJZf7uS4wgejCqNE7LuPF3WIcHgzMzq6bACcDMrKo8IYyZWVX5DsDMrIICDwZnZlZNbgQ2M6suJwAzs4pyAjAzq6AIGBhodxQt4wRgZpZXoTuASe0OwMxswhjqBVRkKUDSPElPSOqVdGWN9a+RdK+kLZLukzQ9t+56SY+m5YO58rdL+kEqv1XSIalckm5K59oi6cxG8TkBmJnlRRRbGpA0GbgZmA/MBBZLmjlss78A1kTE6cBy4PNp3z8AzgTOAGYDyyQdLWkScCuwKCJOA34KLEnHmg/MSMtSYEWjGJ0AzMzympQAgLOA3oh4KiJ2A18HFg7bZiZwb3r9vdz6mcA/R8TeiPg18AgwDzgeeCkifpK22wC8L71eSJZMIiI2AsdKmlYvQCcAOzhRcrHm8HffXEONwEWWxk4Ensm970tleY+w/wf8PcBRko5P5fMlHSGpBzgHOAnYDkyRNCvtc0EqL3q+A7gR2Mwsr3gjcI+kzbn3qyJiVe59rbFyhx/808CXJF0E3A/8HNgbEfdIejPwfeB54KFUHpIWATdKOgy4B9g7hvMdwAnAzCyveALYHhGz6qzvY//VOcB04NkDTxXPAu8FkPRy4H0RsTOtuw64Lq27DXgylT8EvDWVzwVOLXq+4VwFZGa2T8EeQMV6AW0CZkg6RdKhwCJgbX4DST2pYRfgKmB1Kp+cqoKQdDpwOtnVPpJOSP89DPgMsDLtvxa4MPUGmgPsjIit9QL0HYCZ2ZCAiOZMChwReyVdDqwHJgOrI+IxScuBzRGxFjgb+LykIKsCuiztPgV4QBLAL4APR8RQVc8ySe8iu4BfERHfTeXrgAVAL7ALuLhRjE4AZmZ5TRwNNCLWkf0w58uuzr2+C7irxn4vkvUEqnXMZcCyGuXB/gRSiBOAmdkQDwVhZlZhFRoKwgnAzCwnBpvTBtAJnADMzPbxhDBmZtVUsSkh/RxADQVG8DtM0h1p/cOSTm59lGY2LmKw2NIFnACGKTiC3yXAjoh4PXAjcH1rozSz8RARxMBAoaUbOAGMVGQEv4VkQ7JC1of3XKUnNsyss8VgFFq6gdsARqo1ot7s0bZJT/vtJBumdXt+I0lLycblBnjp0Rs/+ei4RNx8PQz7LBNcJ8XbSbFCZ8X72wd7gF+yY/13Bu/sKbh5p3wvo3ICGKnIiHqFRt1LIwOuApC0ucHAURNGJ8UKnRVvJ8UKnRXvsJE5S4mIec2IpVO4CmikIiPq7dsmTcd2DNDfkujMzJrECWCkhiP4pfdD07BdAHw3jcNhZtYxXAU0TMER/L4KfE1SL9mV/6ICh17VeJMJo5Nihc6Kt5Nihc6Kt5NinRDkC1czs2pyFZCZWUU5AZiZVZQTQJN10jASBWL9pKTHJW2RdK+k17Qjzlw8dePNbXeBpJDUtu6LRWKV9IH0/T6W5nxtmwJ/C6+W9D1JP0x/DwvaEWeKZbWkbZJqPleTpkS8KX2WLZLObHWMHSMivDRpIWs0/jfgtcChwCPAzGHb/DGwMr1eBNwxgWM9Bzgivb60XbEWjTdtdxTZ1HobgVkTNVZgBvBDYGp6f8JE/m7JGlgvTa9nAk+3Md7fB84EHh1l/QLgbrLndeYAD7cr1om++A6guTppGImGsUbE9yJiV3q7keyZiHYp8t0CXAvcALzYyuCGKRLrHwE3R8QOgIjY1uIY84rEG8DR6fUxjHw2pmUi4n7qP3ezEFgTmY3AsZKmtSa6zuIE0Fy1hpE4cbRtIpvkeWgYiVYrEmveJWRXVe3SMF5JbwROiohvtzKwGop8t6cCp0p6UNJGSe18ArVIvJ8DPiypj2yO24+1JrRSxvq3XVl+DqC5mjaMRAsUjkPSh4FZwNvGNaL66sYraRLZyKwXtSqgOop8t4eQVQOdTXZn9YCk0yLiP8c5tlqKxLsYuCUi/lLS75E9B3NaxIQcF3mi/Bub8HwH0FydNIxEkViR9A7gT4HzI+KlFsVWS6N4jwJOA+6T9DRZ3e/aNjUEF/07+GZE7ImIfweeIEsI7VAk3kuAOwEi4iHgcLKB4iaiQn/b5gTQbJ00jETDWFOVyt+Q/fi3s44aGsQbETsjoiciTo6Ik8naLM6PiIMeIKzZsSbfIGtkR1IPWZXQUy2Ncr8i8f4MOBdA0u+QJYDnWxplcWuBC1NvoDnAzojY2u6gJiJXATVRjN8wEu2K9YvAy4G/T+3UP4uI8ydwvBNCwVjXA3MlPQ4MAMsi4oUJHO+ngC9L+gRZdcpFbbpwQdLtZFVnPalN4hpgCkBErCRro1gA9AK7gIvbEWcn8FAQZmYV5SogM7OKcgIwM6soJwAzs4pyAjAzqygnADOzinICMDOrKCcAM7OKcgIwy5H05jSG/OGSjkxj9Z/W7rjMxkPdBCDpWEl/3Kpg0jmXSHoyLUtG2eY4SRvSNhskTU3lNSeCkHSOpB/llhclvTutO1fSD1L5/5X0+lT++6l8r6QLWvX5rb0iYhPZUAJ/Tjas9P+JiJoTj5h1urpPAiubrerbEdGSKyBJxwGbyUaeDOBfgDcNjZme2+4GoD8ivpBmL5oaEZ9JsxR9jOwx8NnAX0fE7Brn6AWmR8QuST8BFkbEj1OyOysiLkqf/Wjg08DaiLhr/D65TSRpPJxNZHMK/NeIGGhzSGbjolEV0BeA16Wr4y+2IJ7zgA0R0Z9+9DcAtcZJz0+qcivw7lx5o4kgLgDuzk10UnOii4h4OiK2ABNxuFsbX8eRjYF0FNmgZ2ZdqdFgcFcCp0XEGbVWSnqA7B/JcJ+OiO+UiKfoRA6vHBrdLyK2Sjqhwf75kQAXAX+Ve/9RYJ2k3wC/IBtG2KptFfBnwCnA9cDl7Q3HbHwc1GigEfHWZgWSHOxEDo0mDZkG/BeyUQ+HfAJYEBEPS1pGlhw+OoZzWheRdCGwNyJukzQZ+L6kt0fEd9sdm1mzHVQCGIc7gD6yYV6HTAfuq7Hdc5Kmpav/acDQWPWNJoL4APCPEbEnxf8K4Hcj4uG0/g7gn0rEbV0iItYAa9LrAbK2JLOu1KgN4JfU/oEHsjuAiDijxlLmxx/2j5E+NfXsmcuBV+tD8pOqLAG+mSuvNxHEYuD23PsdwDGSTk3v3wn8uGTsZmYdpeF8AJJuA04nazhdNu4BSR8B/iS9vS4i/jaVfwVYGRGbJR1PNj3dq8lmKnp/RPQrm7XkS2QNx7uAi4dmhEq9eh4kmzR8MHe+9wDLyRp7dwAfiYinJL0Z+EdgKllvkP+IiDeM64c3M2shTwhjZlZRfhLYzKyinADMzCrKCcDMrKKcAMzMKsoJwMysopwAzMwqygmD4DQPAAAAEElEQVTAzKyinADMzCrq/wPuCgqGUjU0hwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed9b9b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "          The solution can be compared to the analytic solution with\n",
      "          the script analysis/gauss_diffusion_compare.py\n",
      "          \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<diffusion.simulation.Simulation at 0x7f6bed942198>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed9b7240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1    1.0001    1.0001    1.0001    1.0001         1         1         1         1         1         1 \n",
      "         1         1         1         1         1    1.0001    1.0001    1.0002    1.0002    1.0001    1.0001         1         1         1         1         1 \n",
      "         1         1         1         1    1.0001    1.0002    1.0004    1.0007    1.0007    1.0004    1.0002    1.0001         1         1         1         1 \n",
      "         1         1         1    1.0001    1.0001    1.0004     1.001     1.002     1.002     1.001    1.0004    1.0001    1.0001         1         1         1 \n",
      "         1         1         1    1.0001    1.0002    1.0007     1.002   0.99881   0.99881     1.002    1.0007    1.0002    1.0001         1         1         1 \n",
      "         1         1         1    1.0001    1.0002    1.0007     1.002   0.99881   0.99881     1.002    1.0007    1.0002    1.0001         1         1         1 \n",
      "         1         1         1    1.0001    1.0001    1.0004     1.001     1.002     1.002     1.001    1.0004    1.0001    1.0001         1         1         1 \n",
      "         1         1         1         1    1.0001    1.0002    1.0004    1.0007    1.0007    1.0004    1.0002    1.0001         1         1         1         1 \n",
      "         1         1         1         1         1    1.0001    1.0001    1.0002    1.0002    1.0001    1.0001         1         1         1         1         1 \n",
      "         1         1         1         1         1         1    1.0001    1.0001    1.0001    1.0001         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "dens = pyro_sim.sim.cc_data.get_var(\"phi\")\n",
    "dens.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## incompressible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"incompressible\"\n",
    "problem_name = \"shear\"\n",
    "param_file = \"inputs.shear\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the incompressible shear problem...\u001b[0m\n",
      "y_half =  0.5\n",
      "delta_s =  0.05\n",
      "rho_s =  42.0\n",
      "extrema:  -1.0 0.9999997110039925\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee4478d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6c074e5048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<incompressible.simulation.Simulation at 0x7f6bee447e80>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee748240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        -1   -1.0001   -1.0001        -1  -0.99995  -0.99992  -0.99992  -0.99995 \n",
      "  -0.98937  -0.98915  -0.98915  -0.98937   -0.9894  -0.98929  -0.98929   -0.9894 \n",
      "    0.9894   0.98929   0.98929    0.9894   0.98937   0.98915   0.98915   0.98937 \n",
      "   0.99995   0.99992   0.99992   0.99995         1    1.0001    1.0001         1 \n",
      "         1    1.0001    1.0001         1   0.99995   0.99992   0.99992   0.99995 \n",
      "   0.98937   0.98915   0.98915   0.98937    0.9894   0.98929   0.98929    0.9894 \n",
      "   -0.9894  -0.98929  -0.98929   -0.9894  -0.98937  -0.98915  -0.98915  -0.98937 \n",
      "  -0.99995  -0.99992  -0.99992  -0.99995        -1   -1.0001   -1.0001        -1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "u = pyro_sim.sim.cc_data.get_var(\"x-velocity\")\n",
    "u.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## lm_atm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = \"lm_atm\"\n",
    "problem_name = \"bubble\"\n",
    "param_file = \"inputs.bubble\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=16\",  \"mesh.ny=16\", \"driver.verbose=0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the bubble problem...\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee36feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bed4d7198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<lm_atm.simulation.Simulation at 0x7f6beda26ac8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bee761d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " -4.31e-05 -3.83e-05 -2.87e-05 -1.44e-05  3.88e-06  2.41e-05  4.25e-05  5.39e-05  5.39e-05  4.25e-05  2.41e-05  3.88e-06 -1.44e-05 -2.87e-05 -3.83e-05 -4.31e-05 \n",
      "  -4.7e-05 -4.23e-05 -3.28e-05  -1.8e-05  1.86e-06  2.54e-05  4.86e-05  6.42e-05  6.42e-05  4.86e-05  2.54e-05  1.86e-06  -1.8e-05 -3.28e-05 -4.23e-05  -4.7e-05 \n",
      " -5.51e-05 -5.09e-05 -4.18e-05 -2.65e-05 -3.73e-06  2.69e-05  6.19e-05  8.92e-05  8.92e-05  6.19e-05  2.69e-05 -3.73e-06 -2.65e-05 -4.18e-05 -5.09e-05 -5.51e-05 \n",
      " -6.73e-05  -6.4e-05 -5.65e-05 -4.22e-05 -1.69e-05  2.42e-05  8.24e-05   0.00014   0.00014  8.24e-05  2.42e-05 -1.69e-05 -4.22e-05 -5.65e-05  -6.4e-05 -6.73e-05 \n",
      " -8.22e-05 -8.11e-05 -7.75e-05 -6.81e-05 -4.53e-05  4.76e-06  0.000103  0.000247  0.000247  0.000103  4.76e-06 -4.53e-05 -6.81e-05 -7.75e-05 -8.11e-05 -8.22e-05 \n",
      " -9.77e-05 -9.99e-05 -0.000104 -0.000106 -9.99e-05 -6.11e-05  7.66e-05  0.000492  0.000492  7.66e-05 -6.11e-05 -9.99e-05 -0.000106 -0.000104 -9.99e-05 -9.77e-05 \n",
      " -6.65e-05 -7.26e-05 -8.57e-05 -0.000108  -0.00014 -0.000178 -0.000178 -0.000209 -0.000209 -0.000178 -0.000178  -0.00014 -0.000108 -8.57e-05 -7.26e-05 -6.65e-05 \n",
      "  -0.00016 -0.000169 -0.000189 -0.000229 -0.000305  -0.00046 -0.000809   0.00331   0.00331 -0.000809  -0.00046 -0.000305 -0.000229 -0.000189 -0.000169  -0.00016 \n",
      " -0.000159 -0.000168 -0.000188 -0.000228 -0.000303 -0.000457 -0.000806   0.00336   0.00336 -0.000806 -0.000457 -0.000303 -0.000228 -0.000188 -0.000168 -0.000159 \n",
      " -6.09e-05 -6.71e-05 -8.04e-05 -0.000103 -0.000135 -0.000174 -0.000179 -0.000211 -0.000211 -0.000179 -0.000174 -0.000135 -0.000103 -8.04e-05 -6.71e-05 -6.09e-05 \n",
      " -8.68e-05 -8.95e-05 -9.41e-05 -9.82e-05 -9.43e-05 -6.03e-05  6.65e-05  0.000457  0.000457  6.65e-05 -6.03e-05 -9.43e-05 -9.82e-05 -9.41e-05 -8.95e-05 -8.68e-05 \n",
      " -6.77e-05 -6.76e-05 -6.62e-05 -6.02e-05 -4.24e-05  2.28e-07  8.69e-05  0.000217  0.000217  8.69e-05  2.28e-07 -4.24e-05 -6.02e-05 -6.62e-05 -6.76e-05 -6.77e-05 \n",
      " -4.93e-05 -4.78e-05 -4.38e-05 -3.47e-05 -1.66e-05  1.56e-05  6.37e-05  0.000113  0.000113  6.37e-05  1.56e-05 -1.66e-05 -3.47e-05 -4.38e-05 -4.78e-05 -4.93e-05 \n",
      " -3.28e-05 -3.11e-05  -2.7e-05  -1.9e-05 -5.48e-06  1.49e-05     4e-05  6.06e-05  6.06e-05     4e-05  1.49e-05 -5.48e-06  -1.9e-05  -2.7e-05 -3.11e-05 -3.28e-05 \n",
      " -1.86e-05 -1.73e-05 -1.45e-05 -9.35e-06 -1.36e-06  9.48e-06  2.14e-05  3.01e-05  3.01e-05  2.14e-05  9.48e-06 -1.36e-06 -9.35e-06 -1.45e-05 -1.73e-05 -1.86e-05 \n",
      " -5.95e-06 -5.51e-06 -4.51e-06 -2.78e-06 -1.91e-07  3.17e-06  6.68e-06   9.1e-06   9.1e-06  6.68e-06  3.17e-06 -1.91e-07 -2.78e-06 -4.51e-06 -5.51e-06 -5.95e-06 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "v = pyro_sim.sim.cc_data.get_var(\"y-velocity\")\n",
    "v.pretty_print(show_ghost=False, fmt=\"%10.3g\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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