modules/agent-framework/deployments/jupyterhub/data/gkeyll/plotE_z.ipynb

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    "#### ​Initialize, Authenticate, and Configure Remote Execution Environment\n",
    "\n",
    "##### Start a Cybershuttle Remote Executor: This will submit a remote job to Anvil\n",
    "- **Cluster** - Anvil\n",
    "- **Community Allocation** - Gkeyll\n",
    "- **Requested Resources** - 4 CPUs, 4GB Memory, 60 Minutes, Shared Queue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae3f8f6f-2c94-44de-9a33-073a02bf05a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install --force-reinstall airavata-jupyter-magic\n",
    "import airavata_jupyter_magic\n",
    "\n",
    "%authenticate\n",
    "%request_runtime test_cpu --cluster=Anvil --cpus=4 --memory=4096 --walltime=60 --queue=shared --group=Gkeyll\n",
    "%switch_runtime test_cpu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aebd5d11-8f1d-4251-99e2-60bd06bed837",
   "metadata": {},
   "outputs": [],
   "source": [
    "!ls /anvil/projects/x-phy220105/gkylMarch2025/vlabApps/gemReconnection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c5308aa-a6d2-4b8e-8e9e-ad6c2a6b7380",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import matplotlib.pyplot as plt\n",
    "import postgkyl as pg\n",
    "\n",
    "data_base_path = \"/anvil/projects/x-phy220105/gkylMarch2025/vlabApps/gemReconnection\"\n",
    "run = Path.cwd()\n",
    "\n",
    "def getModelType():\n",
    "    frame = 0\n",
    "    models = [\"5m\", \"10m\"]\n",
    "    for model in models:\n",
    "        path = Path(f\"{data_base_path}/rt_{model}_gem_gzero-field_{frame}.gkyl\")\n",
    "        if path.is_file():\n",
    "            return model\n",
    "    error = \"Failed to find input file \" + str(path)\n",
    "    assert False, error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9723cde9-abad-4d95-85cb-c618b383ae48",
   "metadata": {},
   "outputs": [],
   "source": [
    "frame = 0\n",
    "model = getModelType()\n",
    "filename = run / f\"{data_base_path}/rt_{model}_gem_gzero-field_{frame}.gkyl\"\n",
    "filename = str(filename)\n",
    "print(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcc09aec-5821-4e58-ad38-3765afc28fc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdata = pg.GData(filename)\n",
    "\n",
    "vals = gdata.get_values() # cell-center values, shape is Ny * Nx * Ncomponents\n",
    "grid = gdata.get_grid() # cell corner coordinates\n",
    "ndim = gdata.get_num_dims() # number of spatial dimensions\n",
    "\n",
    "assert len(vals.shape) == ndim+1 and len(grid) == ndim\n",
    "\n",
    "icomp = 3\n",
    "compName = r'$E_z^2$'\n",
    "fileName = \"E_z.png\"\n",
    "\n",
    "my_vals = vals[..., icomp]\n",
    "x, y = grid\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "im = ax.pcolormesh(x, y, my_vals.T)\n",
    "fig.colorbar(im, ax=ax)\n",
    "\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_title(compName)\n",
    "ax.set_aspect(1)\n",
    "\n",
    "plt.savefig(fileName)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eee0d482-0d84-41d0-bf6d-820ac7c3bbf3",
   "metadata": {},
   "source": [
    "#### To Stop the Agent Run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a5581f6-e963-4e2b-bd6e-8a122e906ca6",
   "metadata": {},
   "outputs": [],
   "source": [
    "%stop_runtime test_cpu\n",
    "%switch_runtime local"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d87f6d9-2547-473d-987a-af5306d6f00b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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