ogs-jupyter-lab-h1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c76f1dec-f210-423c-8e48-57d15c66f6f6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "title = \"ogs@jupyter-lab: Elliptic: H process: Pumping well\"\n",
    "variable = \"pressure\"\n",
    "coordinates = \"r\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6942104-ce23-48c0-bc3f-035f086c825f",
   "metadata": {},
   "source": [
    "**ogs@jupyter-lab: Elliptic: H process: Pumping well**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b900a0bc",
   "metadata": {
    "tags": []
   },
   "source": [
    "<!--- ![tu-dresden-blue.png](attachment:tu-dresden-blue.png) --->\n",
    "<img src=\"ogs-teaching.png\" alt=\"drawing\" width=\"300\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8af117f3-3ade-4aea-a18f-e9023cdaeae0",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Running ogs using [ogs6py](https://github.com/joergbuchwald/ogs6py)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "85143f21-f2ef-43ab-a2a3-9412f1ca55fa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===============\n",
      ">>> run ogs <<<\n",
      "OGS finished with project file circle_1e3_axi.prj.\n",
      "Execution took 0.03668785095214844 s\n"
     ]
    }
   ],
   "source": [
    "from ogs6py import ogs\n",
    "#run ogs\n",
    "PATH_OGS=\"/home/ok/ogs/build/release/bin/\"\n",
    "print(\"===============\")\n",
    "print(\">>> run ogs <<<\")\n",
    "model = ogs.OGS(PROJECT_FILE=\"circle_1e3_axi.prj\")\n",
    "model.run_model(path=PATH_OGS,LOGFILE=\"console.log\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cb395b7-9b10-4a39-b914-929265094f56",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Extracting results using [VTUInterface](https://github.com/joergbuchwald/VTUinterface)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ddae910b-4fc6-4384-bebf-723113924613",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=====================\n",
      ">>> print results <<<\n",
      "circle_1e3_axi.pvd\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# read and process (point interpolation) vtu- and pvd-files \n",
    "import vtuIO\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.tri as tri\n",
    "print(\"=====================\")\n",
    "print(\">>> print results <<<\")\n",
    "pvdfile=vtuIO.PVDIO(\"circle_1e3_axi.pvd\", dim=1)\n",
    "# define xaxis and diagonal (list)\n",
    "xaxis =  [(i,0,0) for i in np.linspace(start=0.0, stop=1.0, num=100)]\n",
    "r_x = np.array(xaxis)[:,0]\n",
    "# define timestep\n",
    "time = [0.0,1.0]\n",
    "# read and interpolate from vtu-files listed in pvd\n",
    "for t in time:\n",
    "    function_xaxis_t = pvdfile.read_point_set_data(t, 'pressure', pointsetarray=xaxis)\n",
    "    plt.plot(r_x, function_xaxis_t, label='t='+str(t))\n",
    "# plot formatting\n",
    "plt.title(title)\n",
    "#plt.xscale('log')\n",
    "plt.xlabel(coordinates)\n",
    "plt.ylabel(variable)\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.savefig(\"profile.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "016db304-89da-40b4-8d3b-1eb0aa6adc4a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thu Jun  3 01:21:39 2021\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "print(time.ctime())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54a4390e-6829-4e80-a9d1-27438146702d",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Results have been shown using [matplotlib](https://matplotlib.org/)**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d3ebdb5",
   "metadata": {
    "tags": []
   },
   "source": [
    "**OGS links**\n",
    "- description: https://www.opengeosys.org/docs/benchmarks/elliptic/elliptic-pde-with-dirichlet-and-nodal-source-term/\n",
    "- project file: https://gitlab.opengeosys.org/ogs/ogs/-/blob/master/Tests/Data/Elliptic/circle_radius_1/circle_1e6_axi.prj\n",
    "- notebook compilation by OK (https://github.com/OlafKolditz/ogs-jupyter-lab)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fa49ad9",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Credits**\n",
    "- Jörg Buchwald for ogs6py and VTUInterface (JOSS review pending) https://joss.theoj.org/papers/6ddcac13634c6373e6e808952fdf4abc\n",
    "- Tom Fischer for this benchmark set up"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}