{
 "cells": [
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "#Lets have matplotlib \"inline\"\n",
    "%matplotlib inline\n",
    "\n",
    "# Add line profiler\n",
    "%load_ext line_profiler\n",
    "\n",
    "#Import packages we need\n",
    "from matplotlib import animation, rc\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "import importlib\n",
    "\n",
    "try:\n",
    "    from StringIO import StringIO\n",
    "except ImportError:\n",
    "    from io import StringIO\n",
    "    \n",
    "#Set large figure sizes\n",
    "#Note, this prevents nice figures for articles...\n",
    "rc('figure', figsize=(16.0, 12.0))\n",
    "rc('animation', html='html5')\n",
    "\n",
    "from GPUSimulators.common import Timer\n",
    "from GPUSimulators.helpers import InitialConditions"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "%setup_logging --out=test_schemes.log TestSchemes"
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Registering my_context in user workspace\n",
      "PyCUDA version 2024.1\n",
      "CUDA version (11, 8, 0)\n",
      "Driver version 12080\n",
      "Using device 0/1 'NVIDIA GeForce GTX 970' (0000:07:00.0) GPU\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Created context handle <98151551869168>\n",
      "Using CUDA cache dir /home/smyalygames/PycharmProjects/FiniteVolumeGPU/GPUSimulators/cuda_cache\n",
      "Autotuning enabled. It may take several minutes to run the code the first time: have patience\n"
     ]
    }
   ],
   "source": [
    "%cuda_context_handler my_context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx = 256\n",
    "ny = 128\n",
    "g = 9.81\n",
    "\n",
    "h0, hu0, hv0, dx, dy = InitialConditions.bump(nx, ny, 100, 100, 15)\n",
    "\n",
    "# print(my_context.autotuner.get)\n",
    "\n",
    "arguments = {\n",
    "    'context': my_context,\n",
    "    'h0': h0, 'hu0': hu0, 'hv0': hv0,\n",
    "    'nx': nx, 'ny': ny,\n",
    "    'dx': dx, 'dy': dy, \n",
    "    'g': g,\n",
    "    'compile_opts': ['-Wno-deprecated-gpu-targets', '-arch=sm_52']\n",
    "}\n",
    "\n",
    "t_end = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(sim):\n",
    "    h = sim.u0[0].download(sim.stream)\n",
    "    \n",
    "    plt.figure()\n",
    "    plt.title(str(sim) + \", t=\" + str(sim.sim_time()) + \", nt=\" + str(sim.sim_steps()))\n",
    "    extent = [0, sim.dx*sim.nx, 0, sim.dy*sim.ny]\n",
    "    plt.imshow(h, vmin=0.49, vmax=0.52, extent=extent)\n",
    "    plt.colorbar()"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import LxF\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = LxF(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import Force\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = Force(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import HLL\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = HLL(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import HLL2\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = HLL2(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import KP07\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = KP07(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import KP07Dimsplit\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = KP07Dimsplit(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": [
    "from GPUSimulators.model import WAF\n",
    "\n",
    "with Timer(\"construct\") as t:\n",
    "    sim = WAF(**arguments)\n",
    "\n",
    "with Timer(\"step\") as t:\n",
    "    t = sim.simulate(t_end)\n",
    "    \n",
    "with Timer(\"download\") as t:\n",
    "    h1, hu1, hv1 = sim.download()\n",
    "\n",
    "plot(sim)"
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": ""
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ShallowWaterGPU",
   "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": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}