archTest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "face0b17",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "# os.environ['CUDA_LAUNCH_BLOCKING'] = \"1\"\n",
    "# Helpful statement for debugging, prints the thing entered as x and the output, i.e.,\n",
    "# debugPrint(1+1) will output '1+1 [int] = 2'\n",
    "import inspect\n",
    "import re\n",
    "def debugPrint(x):\n",
    "    frame = inspect.currentframe().f_back\n",
    "    s = inspect.getframeinfo(frame).code_context[0]\n",
    "    r = re.search(r\"\\((.*)\\)\", s).group(1)\n",
    "    print(\"{} [{}] = {}\".format(r,type(x).__name__, x))\n",
    "    \n",
    "    \n",
    "import os\n",
    "import os, sys\n",
    "# sys.path.append(os.path.join('~/dev/pytorchSPH/', \"lib\"))\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import LogNorm\n",
    "from tqdm.notebook import trange, tqdm\n",
    "import yaml\n",
    "%matplotlib notebook\n",
    "import warnings\n",
    "warnings.filterwarnings(action='once')\n",
    "from datetime import datetime\n",
    "\n",
    "import torch\n",
    "from torch_geometric.nn import radius\n",
    "from torch_geometric.nn import SplineConv, fps, global_mean_pool, radius_graph, radius\n",
    "from torch_scatter import scatter\n",
    "\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "import ipywidgets as widgets\n",
    "\n",
    "import tomli\n",
    "from scipy.optimize import minimize\n",
    "import matplotlib.patches as patches\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "from matplotlib.colors import LogNorm\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "import matplotlib.ticker as mticker\n",
    "\n",
    "import torch\n",
    "# import torchvision.models as models\n",
    "from torch.profiler import profile, record_function, ProfilerActivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3779a041",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c5de793",
   "metadata": {},
   "source": [
    "# TODO:\n",
    "<!-- 1. Add kinematic visocisty -->\n",
    "<!-- 2. Backport velocity diffusion to DFSPH code (own module) -->\n",
    "3. IMPROVE PERFORMANCE\n",
    "4. Add drag forces\n",
    "5. delta sph with boundary integrals?!\n",
    "6. setup dambreak with obstacle\n",
    "7. setup flow past cylinder\n",
    "8. add wcsph (müller)\n",
    "9. add compressible sph\n",
    "10. setup shockwave scenario for compressible sph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6e51f54a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from src.deltaSPH import deltaSPHSimulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1183c8b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/winchenbach/anaconda3/envs/torch/lib/python3.9/site-packages/skimage/util/dtype.py:27: DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`.  (Deprecated NumPy 1.24)\n",
      "  np.bool8: (False, True),\n"
     ]
    }
   ],
   "source": [
    "from src.deltaSPH import deltaSPHSimulation\n",
    "from src.dfsph import dfsphSimulation\n",
    "\n",
    "def loadConfig(config):\n",
    "    with open(config, 'r') as file:\n",
    "        tomlConfig = file.read()\n",
    "    parsedConfig = tomli.loads(tomlConfig)\n",
    "    simulationScheme = 'deltaSPH'\n",
    "    if 'simulation' in parsedConfig:\n",
    "        if 'scheme' in parsedConfig['simulation']:\n",
    "            simulationScheme = parsedConfig['simulation']['scheme']\n",
    "            \n",
    "    if simulationScheme == 'deltaSPH' or simulationScheme == 'deltaPlus':\n",
    "        return parsedConfig, deltaSPHSimulation\n",
    "    if simulationScheme == 'dfsph':\n",
    "        return parsedConfig, dfsphSimulation\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d2b18850",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "velocities [list] = [array([2., 0.]), array([1.41421356, 1.41421356]), array([1.2246468e-16, 2.0000000e+00]), array([-1.41421356,  1.41421356]), array([-2.0000000e+00,  2.4492936e-16]), array([-1.41421356, -1.41421356]), array([-3.6739404e-16, -2.0000000e+00]), array([ 1.41421356, -1.41421356])]\n"
     ]
    }
   ],
   "source": [
    "velocities = []\n",
    "\n",
    "r = 2\n",
    "for i in range(8):\n",
    "#     for j in range(8):\n",
    "    theta_i = 2 * np.pi * i / 8\n",
    "    xi = r * np.cos(theta_i)\n",
    "    yi = r * np.sin(theta_i)\n",
    "    \n",
    "    velocities.append(np.array([xi,yi]))\n",
    "    \n",
    "#     debugPrint(xi)\n",
    "debugPrint(velocities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a4ee9815",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# def loadConfig(config, i, j):\n",
    "#     with open(config, 'r') as file:\n",
    "#         tomlConfig = file.read()\n",
    "#     parsedConfig = tomli.loads(tomlConfig)\n",
    "    \n",
    "#     parsedConfig['emitter']['fluidL']['velocity'] = velocities[i]\n",
    "#     parsedConfig['emitter']['fluidR']['velocity'] = velocities[j]\n",
    "#     parsedConfig['export']['prefix'] = 'collision %d x %d' %(i,j)\n",
    "#     parsedConfig['export']['active'] = False\n",
    "    \n",
    "#     simulationScheme = 'deltaSPH'\n",
    "#     if 'simulation' in parsedConfig:\n",
    "#         if 'scheme' in parsedConfig['simulation']:\n",
    "#             simulationScheme = parsedConfig['simulation']['scheme']\n",
    "            \n",
    "#     if simulationScheme == 'deltaSPH' or simulationScheme == 'deltaPlus':\n",
    "#         return parsedConfig, deltaSPHSimulation\n",
    "#     if simulationScheme == 'dfsph':\n",
    "#         return parsedConfig, dfsphSimulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5d4cc284",
   "metadata": {},
   "outputs": [],
   "source": [
    "# config = 'configs/dambreak_dfsph.toml'\n",
    "config = 'configs/dambreak_deltasph.toml'\n",
    "# config = 'configs/collision_dfsph.toml'\n",
    "# config = 'configs/generative.toml'\n",
    "# config = 'configs/generative_dfsph.toml'\n",
    "# config = 'configs/collision2_dfsph.toml'\n",
    "# config = 'configs/oscillating_drop_deltasph.toml'\n",
    "# parsedConfig, simulationModel = loadConfig(config,2,2)\n",
    "parsedConfig, simulationModel = loadConfig(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "53906211",
   "metadata": {},
   "outputs": [],
   "source": [
    "# parsedConfig['generative']['seed'] = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "74674b0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sphSimulation = simulationModel(parsedConfig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "92847765",
   "metadata": {},
   "outputs": [],
   "source": [
    "sphSimulation.initializeSimulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bcae3686",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-v0_8', 'seaborn-v0_8-bright', 'seaborn-v0_8-colorblind', 'seaborn-v0_8-dark', 'seaborn-v0_8-dark-palette', 'seaborn-v0_8-darkgrid', 'seaborn-v0_8-deep', 'seaborn-v0_8-muted', 'seaborn-v0_8-notebook', 'seaborn-v0_8-paper', 'seaborn-v0_8-pastel', 'seaborn-v0_8-poster', 'seaborn-v0_8-talk', 'seaborn-v0_8-ticks', 'seaborn-v0_8-white', 'seaborn-v0_8-whitegrid', 'tableau-colorblind10']\n"
     ]
    }
   ],
   "source": [
    "print(plt.style.available)\n",
    "# from plotting import *\n",
    "plt.style.use('dark_background')\n",
    "# plt.style.use('default')\n",
    "from tqdm.notebook import trange, tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9dcec6b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# positions = sphSimulation.simulationState['fluidPosition']\n",
    "# velocities = sphSimulation.simulationState['fluidVelocity']\n",
    "\n",
    "# sigma = 1\n",
    "\n",
    "# velocities[:,0] = sigma * positions[:,0]\n",
    "# velocities[:,1] = -sigma * positions[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bba9a429",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "898241e0",
   "metadata": {},
   "outputs": [
    {
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       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
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       "\n",
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       "            // Full images could contain transparency (where diff images\n",
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       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
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       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
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       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
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       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
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       "        for (var i = 0; i < nentries; i++) {\n",
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       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig, axis = sphSimulation.createPlot(plotScale = 2, plotSolids = False, plotDomain = True)\n",
    "fig, axis = plt.subplots(1, 1, figsize=(12,12), sharex = False, sharey = False, squeeze = False)\n",
    "state = sphSimulation.simulationState\n",
    "axis[0,0].set_xticks([])\n",
    "axis[0,0].set_yticks([])\n",
    "\n",
    "positions = state['fluidPosition'].detach().cpu().numpy()\n",
    "data = state['fluidDensity'].detach().cpu().numpy()\n",
    "\n",
    "positions2 = sphSimulation.boundaryModule.boundaryPositions.detach().cpu().numpy()\n",
    "data2 = sphSimulation.boundaryModule.boundaryDensity.detach().cpu().numpy()\n",
    "# data2[:] = 0\n",
    "\n",
    "data2 = torch.linalg.norm(sphSimulation.boundaryModule.boundaryVelocity, dim=1).detach().cpu().numpy()\n",
    "data = torch.linalg.norm(state['fluidVelocity'], dim=1).detach().cpu().numpy()\n",
    "\n",
    "# data = state['residual'].detach().cpu().numpy()\n",
    "# data = state['fluidAlpha'].detach().cpu().numpy()\n",
    "# data2 = sphSimulation.boundaryModule.boundaryPressure.detach().cpu().numpy()\n",
    "\n",
    "positions = np.vstack((positions, positions2))\n",
    "data = np.hstack((data, data2))\n",
    "\n",
    "# positions = sphSimulation.boundaryModule.boundaryPositions.detach().cpu().numpy()\n",
    "# data = sphSimulation.boundaryModule.boundaryVelocity.detach().cpu().numpy() \n",
    "\n",
    "# axis[0,0].scatter(positions2[:,0], positions2[:,1], c ='white', s = 4)\n",
    "\n",
    "sc = axis[0,0].scatter(positions[:,0], positions[:,1], c = data, s = 8)\n",
    "axis[0,0].axis('equal')\n",
    "\n",
    "ax1_divider = make_axes_locatable(axis[0,0])\n",
    "cax1 = ax1_divider.append_axes(\"right\", size=\"4%\", pad=\"1%\")\n",
    "cbar = fig.colorbar(sc, cax=cax1,orientation='vertical')\n",
    "cbar.ax.tick_params(labelsize=8) \n",
    "\n",
    "# quiverData = state['fluidUpdate'].detach().cpu().numpy()\n",
    "# qv = axis[0,0].quiver(positions[:,0], positions[:,1], quiverData[:,0], quiverData[:,1], \\\n",
    "#                       scale_units='xy', scale = 0.1) #scale = 2/ sphSimulation.config['particle']['support'], alpha=0.5)\n",
    "\n",
    "fig.suptitle('Generated [%2d:%2d]+[%2d:%2d] res, %2dx%2d noise, %3.2g @ seed %5d' % (sphSimulation.config['generative']['nb'][0],sphSimulation.config['generative']['nb'][1],sphSimulation.config['generative']['nd'][0],sphSimulation.config['generative']['nd'][1], sphSimulation.config['generative']['res'], sphSimulation.config['generative']['octaves'], sphSimulation.config['generative']['persistance'], sphSimulation.config['generative']['seed']))\n",
    "axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles']))\n",
    "if 'densityErrors' in state and not 'divergenceErrors' in state:\n",
    "    axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'], state['numParticles'],state['realParticles'],len(state['densityErrors'])))\n",
    "if 'divergenceErrors' in state and not 'densityErrors' in state:\n",
    "    axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['divergenceErrors'])))\n",
    "if 'densityErrors' in state and 'divergenceErrors' in state:\n",
    "    axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d, %3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['densityErrors']),len(state['divergenceErrors'])))\n",
    "\n",
    "fig.tight_layout()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5f7f070e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(sphSimulation.config['fluid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fded6190",
   "metadata": {},
   "outputs": [],
   "source": [
    "# timestamp = datetime.now().strftime('%Y-%m-%d_%H-%M-%S')\n",
    "# path = './output/%s - %s/' % (config.split('/')[-1].split('.')[0], timestamp)\n",
    "# if not os.path.exists(path):\n",
    "#     os.makedirs(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b5aac85b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b47c86579a2e496daadab5afca1e47b8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/3200 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[0;32mIn [24]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m tqdm(\u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m3200\u001b[39m)):\n\u001b[0;32m----> 2\u001b[0m     \u001b[43msphSimulation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mintegrate\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m#     break\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m#     sphSimulation.timestep()\u001b[39;00m\n\u001b[1;32m      5\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m i  \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m50\u001b[39m:\n",
      "File \u001b[0;32m~/dev/torchSPHv2/src/simulationBase.py:694\u001b[0m, in \u001b[0;36mSPHSimulation.integrate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    691\u001b[0m     bdudt_k2, bdxdt_k2, bdpdt_k2 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgetBodyUpdate()\n\u001b[1;32m    692\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mintegrateBoundaryValues(\u001b[38;5;241m0.5\u001b[39m \u001b[38;5;241m*\u001b[39m dt, bdudt_k2, bdxdt_k2, bdpdt_k2)\n\u001b[0;32m--> 694\u001b[0m dudt_k3, dxdt_k3, dpdt_k3 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimestep\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m     \n\u001b[1;32m    695\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msimulationState \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msetupSimulationState(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mperennialState)\n\u001b[1;32m    696\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mintegrateValues(dt, dudt_k3, dxdt_k3, dpdt_k3)   \n",
      "File \u001b[0;32m~/dev/torchSPHv2/src/deltaSPH.py:198\u001b[0m, in \u001b[0;36mdeltaSPHSimulation.timestep\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    196\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose: \u001b[38;5;28mprint\u001b[39m(step)\n\u001b[1;32m    197\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m record_function(step):       \n\u001b[0;32m--> 198\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlaminarViscosityModule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcomputeLaminarViscosity\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msimulationState\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m   \n\u001b[1;32m    200\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msimulationState[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfluidAcceleration\u001b[39m\u001b[38;5;124m'\u001b[39m], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msimulationState[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfluidVelocity\u001b[39m\u001b[38;5;124m'\u001b[39m], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msimulationState[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdpdt\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msimulation\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdensityScheme\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcontinuum\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/dev/torchSPHv2/src/modules/laminar.py:85\u001b[0m, in \u001b[0;36mlaminarViscosityModule.computeLaminarViscosity\u001b[0;34m(self, simulationState, simulation)\u001b[0m\n\u001b[1;32m     83\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcomputeLaminarViscosity\u001b[39m(\u001b[38;5;28mself\u001b[39m, simulationState, simulation):\n\u001b[1;32m     84\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m record_function(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdiffusion[laminar] - compute laminar diffusion\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m---> 85\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlaminarViscosity \u001b[38;5;241m=\u001b[39m \u001b[43mcomputeLaminarViscosity\u001b[49m\u001b[43m(\u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidNeighbors\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidNeighbors\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     86\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidPosition\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidPosition\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidVolume\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidVolume\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     87\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidDistances\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidRadialDistances\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     88\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msupport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidDensity\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43meps\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     89\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidDensity\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrestDensity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidDensity\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrestDensity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     90\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidVelocity\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43msimulationState\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfluidVelocity\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     91\u001b[0m \u001b[43m                                                                                              \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkinematic\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mc0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrestDensity\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     92\u001b[0m         \u001b[38;5;66;03m# if self.boundaryDiffusion:\u001b[39;00m\n\u001b[1;32m     93\u001b[0m             \u001b[38;5;66;03m# self.laminarViscosity += simulation.boundaryModule.computeLaminarViscosity(simulationState, simulation)\u001b[39;00m\n\u001b[1;32m     94\u001b[0m         simulationState[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfluidAcceleration\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlaminarViscosity\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(3200)):\n",
    "    sphSimulation.integrate()\n",
    "#     break\n",
    "#     sphSimulation.timestep()\n",
    "    if i  % 1 == 50:\n",
    "        state = sphSimulation.simulationState\n",
    "        positions = state['fluidPosition'].detach().cpu().numpy()\n",
    "\n",
    "        positions2 = sphSimulation.boundaryModule.boundaryPositions.detach().cpu().numpy()\n",
    "        \n",
    "        data = state['fluidDensity'].detach().cpu().numpy()\n",
    "        data2 = sphSimulation.boundaryModule.boundaryDensity.detach().cpu().numpy()\n",
    "        \n",
    "        data2 = torch.linalg.norm(sphSimulation.boundaryModule.boundaryVelocity, dim=1).detach().cpu().numpy()\n",
    "        data = torch.linalg.norm(state['fluidVelocity'], dim=1).detach().cpu().numpy()\n",
    "#         data = torch.linalg.norm(state['fluidUpdate'], dim=1).detach().cpu().numpy()\n",
    "        \n",
    "#         data = state['fluidPressure'].detach().cpu().numpy()\n",
    "#         data = sphSimulation.deltaSPH.pressure.detach().cpu().numpy()\n",
    "#         data2 = sphSimulation.boundaryModule.boundaryPressure.detach().cpu().numpy()\n",
    "\n",
    "        positions = np.vstack((positions, positions2))\n",
    "        data = np.hstack((data, data2))\n",
    "\n",
    "        cbar.mappable.set_clim(vmin=np.min(data), vmax=np.max(data))\n",
    "        sc.set_offsets(positions)\n",
    "        sc.set_array(data)\n",
    "\n",
    "\n",
    "        axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles']))\n",
    "        if 'densityErrors' in state and not 'divergenceErrors' in state:\n",
    "            axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'], state['numParticles'],state['realParticles'],len(state['densityErrors'])))\n",
    "        if 'divergenceErrors' in state and not 'densityErrors' in state:\n",
    "            axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['divergenceErrors'])))\n",
    "        if 'densityErrors' in state and 'divergenceErrors' in state:\n",
    "            axis[0,0].set_title('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d, %3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['densityErrors']),len(state['divergenceErrors'])))\n",
    "\n",
    "        \n",
    "        fig.canvas.draw()\n",
    "        fig.canvas.flush_events()\n",
    "        \n",
    "#         imagePath = path + '%05d.png' % state['timestep']\n",
    "#         plt.savefig(imagePath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "77d937e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# debugPrint(sphSimulation.config['particle']['support'])\n",
    "# debugPrint(sphSimulation.simulationState['fluidSupport'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "e9659f8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "sphSimulation.outFile.close()\n",
    "# debugPrint(sphSimulation.outFile.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b81481f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig, axis = sphSimulation.createPlot(plotScale = 2, plotSolids = False, plotDomain = False)\n",
    "# state = sphSimulation.simulationState\n",
    "\n",
    "# positions = state['fluidPosition'].detach().cpu().numpy()\n",
    "# data = state['fluidDensity'].detach().cpu().numpy()\n",
    "\n",
    "# positions2 = sphSimulation.boundaryModule.boundaryPositions.detach().cpu().numpy()\n",
    "# data2 = sphSimulation.boundaryModule.boundaryPressure.detach().cpu().numpy()\n",
    "\n",
    "# # data2 = torch.linalg.norm(sphSimulation.boundaryModule.boundaryVelocity, dim=1).detach().cpu().numpy()\n",
    "# # data = torch.linalg.norm(state['fluidVelocity'], dim=1).detach().cpu().numpy()\n",
    "\n",
    "# # positions = np.vstack((positions, positions2))\n",
    "# # data = np.hstack((data, data2))\n",
    "\n",
    "# # data = sphSimulation.DFSPH.fluidAlpha\n",
    "# data = state['fluidPressure']\n",
    "\n",
    "# # positions = positions2\n",
    "# # data = data2\n",
    "\n",
    "# sc = axis[0,0].scatter(positions[:,0], positions[:,1], c = data, s = 2)\n",
    "# axis[0,0].axis('equal')\n",
    "\n",
    "# ax1_divider = make_axes_locatable(axis[0,0])\n",
    "# cax1 = ax1_divider.append_axes(\"right\", size=\"4%\", pad=\"1%\")\n",
    "# cbar = fig.colorbar(sc, cax=cax1,orientation='vertical')\n",
    "# cbar.ax.tick_params(labelsize=8) \n",
    "\n",
    "# # quiverData = state['fluidUpdate'].detach().cpu().numpy()\n",
    "# # qv = axis[0,0].quiver(positions[:,0], positions[:,1], quiverData[:,0], quiverData[:,1], \\\n",
    "# #                       scale_units='xy', scale = 0.1) #scale = 2/ sphSimulation.config['particle']['support'], alpha=0.5)\n",
    "\n",
    "# fig.suptitle('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles']))\n",
    "# if 'densityErrors' in state and not 'divergenceErrors' in state:\n",
    "#     fig.suptitle('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'], state['numParticles'],state['realParticles'],len(state['densityErrors'])))\n",
    "# if 'divergenceErrors' in state and not 'densityErrors' in state:\n",
    "#     fig.suptitle('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['divergenceErrors'])))\n",
    "# if 'densityErrors' in state and 'divergenceErrors' in state:\n",
    "#     fig.suptitle('t=%2.4f[%4d] @ dt = %1.5fs, ptcls: %5d[%5d], dfsph: [%3d, %3d]'%(state['time'], state['timestep'], state['dt'],state['numParticles'],state['realParticles'],len(state['densityErrors']),len(state['divergenceErrors'])))\n",
    "\n",
    "# fig.tight_layout()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "271d4ee3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  \n",
      "                                                   Name    Self CPU %      Self CPU   CPU total %     CPU total  CPU time avg     Self CUDA   Self CUDA %    CUDA total  CUDA time avg       CPU Mem  Self CPU Mem      CUDA Mem  Self CUDA Mem    # of Calls  \n",
      "-------------------------------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  \n",
      "                                          full Timestep         0.73%       1.126ms        98.55%     151.014ms     151.014ms       0.000us         0.00%      79.950ms      79.950ms          -4 b        -268 b       1.11 Mb     -56.75 Mb             1  \n",
      "                                            aten::copy_         1.47%       2.259ms        31.45%      48.198ms      92.867us       1.336ms         1.41%       1.338ms       2.578us      15.93 Kb      15.86 Kb     -47.72 Mb     -47.72 Mb           519  \n",
      "                                            aten::index         3.15%       4.828ms        29.12%      44.617ms      76.662us       5.575ms         5.86%       6.667ms      11.455us           0 b           0 b     530.13 Mb    -113.76 Mb           582  \n",
      "                                          aten::nonzero         4.35%       6.667ms        25.60%      39.223ms     210.876us       1.670ms         1.76%       1.670ms       8.978us           0 b           0 b     135.12 Mb     114.00 Kb           186  \n",
      "                                  5 - surface detection         1.79%       2.749ms        23.14%      35.466ms       8.867ms       0.000us         0.00%      28.684ms       7.171ms         -16 b        -164 b       2.77 Mb    -228.95 Mb             4  \n",
      "                                        cudaMemcpyAsync        21.16%      32.426ms        21.16%      32.426ms      93.988us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b           345  \n",
      "                                               aten::to         0.15%     237.000us        19.77%      30.300ms      94.099us       0.000us         0.00%     289.000us       0.898us     128.30 Kb         -28 b      28.79 Mb    -377.00 Kb           322  \n",
      "                                         aten::_to_copy         0.33%     509.000us        19.62%      30.063ms     133.022us       0.000us         0.00%     289.000us       1.279us     128.33 Kb     -16.11 Kb      29.15 Mb     -11.00 Kb           226  \n",
      "                                  cudaStreamSynchronize        16.84%      25.813ms        16.84%      25.813ms      96.317us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b           268  \n",
      "                               10 - pressure evaluation         0.05%      72.000us        14.88%      22.805ms       5.701ms       0.000us         0.00%       1.474ms     368.500us         -16 b        -552 b     -24.00 Kb           0 b             4  \n",
      "          pressure[EOS] - compute pressure acceleration         0.23%     349.000us        14.29%      21.898ms       5.474ms       0.000us         0.00%       1.417ms     354.250us         -16 b        -256 b      78.50 Kb    -865.50 Kb             4  \n",
      "                                11 - velocity diffusion         0.03%      43.000us        14.24%      21.829ms       5.457ms       0.000us         0.00%      11.962ms       2.990ms         -16 b        -548 b     110.50 Kb           0 b             4  \n",
      "       velocity[diffusion] - compute velocity diffusion         0.22%     331.000us        14.21%      21.778ms       5.444ms       0.000us         0.00%      11.962ms       2.990ms         -16 b        -248 b     110.50 Kb    -993.50 Kb             4  \n",
      "                          computePressureAccelDeltaPlus         0.52%     796.000us        13.58%      20.810ms       2.601ms       0.000us         0.00%       1.367ms     170.875us         -64 b         -64 b     628.00 Kb      15.71 Mb             8  \n",
      "                               computeVelocityDiffusion         0.95%       1.456ms        13.21%      20.244ms       1.265ms       0.000us         0.00%      11.897ms     743.562us        -128 b         -32 b     884.00 Kb     -28.29 Mb            16  \n",
      "                          2 - Fluid neighborhood search         0.04%      59.000us        13.01%      19.941ms       4.985ms       0.000us         0.00%       4.558ms       1.139ms         -16 b        -544 b      48.89 Mb     -27.94 Mb             4  \n",
      "                   neighborhood - fluid neighbor search         0.65%       1.002ms        12.97%      19.874ms       4.968ms       0.000us         0.00%       4.558ms       1.139ms         -16 b         -16 b      76.83 Mb     -97.15 Mb             4  \n",
      "                                4 - density  evaluation         0.13%     198.000us        11.70%      17.936ms       4.484ms       0.000us         0.00%       3.637ms     909.250us         -16 b        -544 b     222.00 Kb      -2.38 Mb             4  \n",
      "                      boundaryCondition[mDBC] - density         1.40%       2.148ms        11.47%      17.570ms       4.393ms       0.000us         0.00%       3.629ms     907.250us         -16 b         -56 b       2.44 Mb    -480.00 Kb             4  \n",
      "                          7 - External force evaluation         0.03%      52.000us         7.82%      11.985ms       2.996ms       0.000us         0.00%     205.000us      51.250us         -16 b        -544 b           0 b    -472.00 Kb             4  \n",
      "                                     gravity - evaluate         0.32%     486.000us         7.78%      11.924ms       2.981ms       0.000us         0.00%     205.000us      51.250us         -16 b        -304 b     472.00 Kb      -1.50 Mb             4  \n",
      "                                       cudaLaunchKernel         7.77%      11.903ms         7.77%      11.903ms       4.387us       0.000us         0.00%       0.000us       0.000us           0 b           0 b       3.43 Mb       3.43 Mb          2713  \n",
      "                                                pinv2x2         0.03%      41.000us         6.36%       9.753ms       1.219ms       0.000us         0.00%       1.158ms     144.750us           0 b          32 b       1.29 Mb           0 b             8  \n",
      "                                     Pseudo Inverse 2x2         1.21%       1.859ms         6.28%       9.622ms       1.203ms       0.000us         0.00%       1.158ms     144.750us         -32 b      -1.06 Kb       1.29 Mb       2.29 Mb             8  \n",
      "     boundaryCondition[mDBC] - computeVelocityDiffusion         0.32%     493.000us         6.09%       9.325ms       2.331ms       0.000us         0.00%       1.866ms     466.500us         -16 b        -184 b     474.00 Kb    -668.00 Kb             4  \n",
      "boundaryCondition[mDBC] - computeNormalizationMatric...         0.30%     467.000us         5.81%       8.900ms       2.225ms       0.000us         0.00%     862.000us     215.500us         -16 b        -448 b       1.02 Mb    -672.00 Kb             4  \n",
      "                                       constructHashMap         0.11%     170.000us         5.59%       8.563ms       1.070ms       0.000us         0.00%     708.000us      88.500us         -16 b        -264 b     700.00 Kb           0 b             8  \n",
      "                                       aten::index_put_         0.22%     330.000us         4.48%       6.871ms      56.785us       0.000us         0.00%       1.104ms       9.124us         -20 b         -20 b     -11.44 Mb     -11.44 Mb           121  \n",
      "                                 aten::_index_put_impl_         0.62%     947.000us         4.27%       6.541ms      54.058us     389.000us         0.41%       1.104ms       9.124us           0 b           0 b      -1.50 Kb     -35.86 Mb           121  \n",
      "                                      aten::linalg_pinv         0.07%     110.000us         4.15%       6.361ms       1.590ms       0.000us         0.00%       3.241ms     810.250us           0 b           0 b     576.00 Kb      -2.51 Mb             4  \n",
      "                       3 - Boundary neighborhood search         0.03%      51.000us         3.76%       5.769ms       1.442ms       0.000us         0.00%     163.000us      40.750us         -16 b         -20 b           0 b           0 b             4  \n",
      "                 boundaryCondition[mDBC] - neighborhood         0.11%     162.000us         3.72%       5.707ms       1.427ms       0.000us         0.00%     163.000us      40.750us         -16 b         -16 b           0 b     -64.00 Kb             4  \n",
      "                      neighborhood - searching existing         0.53%     813.000us         3.54%       5.430ms     678.750us       0.000us         0.00%     159.000us      19.875us         -32 b        -564 b           0 b           0 b             8  \n",
      "                                              aten::svd         0.01%       9.000us         3.53%       5.416ms       1.354ms       0.000us         0.00%       1.400ms     350.000us           0 b           0 b       1.31 Mb           0 b             4  \n",
      "                                       aten::linalg_svd         0.01%       9.000us         3.52%       5.396ms       1.349ms       0.000us         0.00%       1.400ms     350.000us           0 b           0 b       1.31 Mb           0 b             4  \n",
      "                                      aten::_linalg_svd         0.13%     194.000us         3.52%       5.387ms       1.347ms       1.380ms         1.45%       1.400ms     350.000us           0 b     -64.00 Kb       1.31 Mb     704.00 Kb             4  \n",
      "                                              aten::mul         2.55%       3.915ms         3.25%       4.988ms       8.675us       1.623ms         1.71%       1.623ms       2.823us        -156 b        -156 b      76.98 Mb      76.98 Mb           575  \n",
      "                             computeNormalizationMatrix         0.68%       1.035ms         3.24%       4.971ms     310.688us       0.000us         0.00%       2.387ms     149.188us        -128 b         -88 b       1.73 Mb      16.74 Mb            16  \n",
      "                                            aten::empty         3.10%       4.754ms         3.10%       4.754ms       3.338us       0.000us         0.00%       0.000us       0.000us     178.07 Kb     178.07 Kb     568.53 Mb     568.53 Mb          1424  \n",
      "                                  8 - momentum equation         0.03%      42.000us         3.07%       4.699ms       1.175ms       0.000us         0.00%       9.002ms       2.251ms         -16 b         -20 b      16.00 Kb           0 b             4  \n",
      "                  density[continuity] - compute drho/dt         0.21%     315.000us         3.03%       4.647ms       1.162ms       0.000us         0.00%       9.002ms       2.251ms         -16 b        -248 b      16.00 Kb    -632.00 Kb             4  \n",
      "                                            aten::zeros         0.52%     797.000us         2.84%       4.358ms       9.837us       0.000us         0.00%     226.000us       0.510us      79.30 Kb        -124 b      21.45 Mb     -32.00 Kb           443  \n",
      "                                      fallback_function         0.30%     464.000us         2.80%       4.296ms      46.696us       0.000us         0.00%       0.000us       0.000us        -112 b         -56 b           0 b           0 b            92  \n",
      "                                                hashmap         0.03%      48.000us         2.71%       4.156ms       1.039ms       0.000us         0.00%     354.000us      88.500us         -16 b        -488 b     350.00 Kb           0 b             4  \n",
      "                                          sortPositions         0.15%     231.000us         2.48%       3.806ms     475.750us       0.000us         0.00%     448.000us      56.000us         -16 b        -528 b       1.85 Mb      -3.50 Kb             8  \n",
      "                             aten::_linalg_check_errors         2.27%       3.482ms         2.32%       3.559ms     889.750us       0.000us         0.00%       4.000us       1.000us           0 b     -64.00 Kb           0 b           0 b             4  \n",
      "                                  computeDivergenceTerm         0.45%     688.000us         2.15%       3.300ms     275.000us       0.000us         0.00%       8.944ms     745.333us         -96 b         -56 b     380.00 Kb           0 b            12  \n",
      "boundaryCondition[mDBC] - computePressureAcceleratio...         0.15%     228.000us         2.03%       3.118ms     779.500us       0.000us         0.00%      62.000us      15.500us         -16 b        -776 b     314.00 Kb    -286.00 Kb             4  \n",
      "                                           aten::einsum         0.41%     621.000us         2.02%       3.094ms      45.500us       0.000us         0.00%      43.864ms     645.059us           0 b           0 b     -80.99 Mb    -150.79 Mb            68  \n",
      "                                      buildNeighborList         0.58%     886.000us         1.90%       2.914ms     242.833us       0.000us         0.00%     212.000us      17.667us         -48 b      -1.34 Kb      13.97 Mb      -1.12 Mb            12  \n",
      "                                            aten::zero_         0.44%     680.000us         1.90%       2.905ms       5.965us       0.000us         0.00%     275.000us       0.565us         160 b         156 b           0 b           0 b           487  \n",
      "                                            aten::fill_         0.93%       1.419ms         1.88%       2.881ms       9.003us     363.000us         0.38%     363.000us       1.134us           0 b           0 b           0 b           0 b           320  \n",
      "                  boundaryCondition[mDBC] - computeDpDt         0.24%     375.000us         1.64%       2.517ms     629.250us       0.000us         0.00%      57.000us      14.250us         -16 b          48 b     174.00 Kb    -684.00 Kb             4  \n",
      "                                 12 - laminar viscosity         0.03%      42.000us         1.53%       2.351ms     587.750us       0.000us         0.00%       9.553ms       2.388ms         -16 b        -288 b      78.50 Kb           0 b             4  \n",
      "                                              aten::bmm         1.00%       1.532ms         1.51%       2.314ms      41.321us      54.307ms        57.12%      54.307ms     969.768us           0 b           0 b      55.93 Mb      55.93 Mb            56  \n",
      "         diffusion[laminar] - compute laminar diffusion         0.16%     244.000us         1.50%       2.301ms     575.250us       0.000us         0.00%       9.553ms       2.388ms         -16 b        -528 b      78.50 Kb    -551.50 Kb             4  \n",
      "                                  9 - density diffusion         0.03%      39.000us         1.37%       2.105ms     526.250us       0.000us         0.00%      10.190ms       2.547ms         -16 b         -16 b      39.50 Kb           0 b             4  \n",
      "                                  cudaDeviceSynchronize         1.35%       2.062ms         1.35%       2.062ms       2.062ms       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b             1  \n",
      "         density[diffusion] - compute density diffusion         0.15%     235.000us         1.34%       2.055ms     513.750us       0.000us         0.00%      10.190ms       2.547ms         -16 b        -248 b      39.50 Kb    -434.50 Kb             4  \n",
      "                                             aten::item         0.04%      55.000us         1.32%       2.024ms      29.765us       0.000us         0.00%       8.000us       0.118us           0 b           0 b      -1.00 Kb      -1.00 Kb            68  \n",
      "                              aten::_local_scalar_dense         0.10%     150.000us         1.28%       1.969ms      28.956us       8.000us         0.01%       8.000us       0.118us           0 b           0 b           0 b           0 b            68  \n",
      "                                               aten::gt         1.04%       1.591ms         1.27%       1.945ms      25.260us     127.000us         0.13%     127.000us       1.649us           0 b           0 b       2.56 Mb       2.56 Mb            77  \n",
      "                                              aten::pow         0.94%       1.440ms         1.25%       1.912ms      14.059us      25.000us         0.03%      25.000us       0.184us          80 b        -172 b     222.00 Kb     222.00 Kb           136  \n",
      "                                computeLaminarViscosity         0.35%     530.000us         1.17%       1.793ms     448.250us       0.000us         0.00%       9.533ms       2.383ms         -32 b         -32 b     314.00 Kb     -45.08 Mb             4  \n",
      "                             torch_scatter::scatter_max         0.30%     460.000us         1.16%       1.772ms      88.600us       4.332ms         4.56%       4.457ms     222.850us           0 b           0 b       2.30 Mb    -100.00 Kb            20  \n",
      "                                             aten::sort         0.42%     644.000us         1.11%       1.703ms     100.176us       1.964ms         2.07%       2.113ms     124.294us           0 b           0 b      42.51 Mb      39.00 Mb            17  \n",
      "                                           aten::select         0.88%       1.354ms         1.07%       1.642ms       1.576us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b          1042  \n",
      "                             computeDensityDiffusionMOG         0.24%     373.000us         1.05%       1.602ms     400.500us       0.000us         0.00%      10.173ms       2.543ms         -32 b         -24 b     158.00 Kb           0 b             4  \n",
      "                                                   sort         0.01%      20.000us         1.03%       1.579ms     394.750us       0.000us         0.00%     224.000us      56.000us         -16 b        -212 b     950.00 Kb           0 b             4  \n",
      "                                         aten::_unique2         0.09%     139.000us         1.01%       1.549ms     387.250us       4.000us         0.00%       4.000us       1.000us           0 b           0 b           0 b        -512 b             4  \n",
      "                         hashmap - hashmap construction         0.09%     137.000us         0.85%       1.302ms     325.500us       0.000us         0.00%      88.000us      22.000us         -16 b         -20 b     298.00 Kb           0 b             4  \n",
      "                                            aten::slice         0.67%       1.023ms         0.81%       1.242ms       1.987us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b           625  \n",
      "                              periodicBC - enforce BC I         0.01%      21.000us         0.79%       1.212ms       1.212ms       0.000us         0.00%     162.000us     162.000us          -4 b          -4 b      78.50 Kb    -471.00 Kb             1  \n",
      "                              hashmap - cell cumulation         0.05%      78.000us         0.78%       1.196ms     299.000us       0.000us         0.00%      72.000us      18.000us         -16 b         -20 b     182.00 Kb           0 b             4  \n",
      "                boundaryCondition[periodic] - filtering         0.12%     191.000us         0.78%       1.188ms       1.188ms       0.000us         0.00%     162.000us     162.000us          -4 b    -156.71 Kb     549.50 Kb    -511.00 Kb             1  \n",
      "                                              aten::div         0.61%     938.000us         0.77%       1.187ms       8.479us     159.000us         0.17%     159.000us       1.136us        -268 b        -268 b       8.36 Mb       8.36 Mb           140  \n",
      "                                    aten::empty_strided         0.77%       1.182ms         0.77%       1.182ms       3.497us       0.000us         0.00%       0.000us       0.000us     128.41 Kb     128.41 Kb      35.78 Mb      35.78 Mb           338  \n",
      "                                       aten::as_strided         0.76%       1.157ms         0.76%       1.157ms       0.330us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b          3501  \n",
      "                                              aten::sub         0.57%     870.000us         0.74%       1.131ms      10.098us       1.132ms         1.19%       1.132ms      10.107us           0 b           0 b     -70.54 Mb     -70.54 Mb           112  \n",
      "                                         kernelGradient         0.10%     157.000us         0.73%       1.116ms      69.750us       0.000us         0.00%       0.000us       0.000us        -128 b          56 b           0 b           0 b            16  \n",
      "                                            scatter_sum         0.16%     244.000us         0.73%       1.112ms      39.714us       0.000us         0.00%      30.000us       1.071us           0 b           0 b     832.00 Kb           0 b            28  \n",
      "                                               finalize         0.10%     152.000us         0.72%       1.104ms     276.000us       0.000us         0.00%       1.991ms     497.750us         -16 b        -544 b      27.94 Mb     -27.94 Mb             4  \n",
      "                                                 kernel         0.05%      77.000us         0.71%       1.090ms      68.125us       0.000us         0.00%       0.000us       0.000us        -128 b         -96 b           0 b           0 b            16  \n",
      "                                              aten::add         0.63%     962.000us         0.70%       1.071ms       8.238us     120.000us         0.13%     120.000us       0.923us         -24 b         -24 b      -5.41 Mb      -5.41 Mb           130  \n",
      "                                           aten::cumsum         0.33%     503.000us         0.69%       1.060ms      53.000us      74.000us         0.08%     124.000us       6.200us           0 b           0 b     598.00 Kb           0 b            20  \n",
      "                                          aten::reshape         0.42%     651.000us         0.66%       1.007ms       1.320us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b           763  \n",
      "                                           aten::matmul         0.11%     176.000us         0.64%     984.000us      41.000us       0.000us         0.00%       2.295ms      95.625us           0 b           0 b   -1000.00 Kb      -3.45 Mb            24  \n",
      "                                          aten::argsort         0.01%      22.000us         0.62%     947.000us     105.222us       0.000us         0.00%     342.000us      38.000us           0 b           0 b     414.50 Kb    -206.00 Kb             9  \n",
      "                                              aten::neg         0.52%     801.000us         0.59%     901.000us       5.928us     153.000us         0.16%     153.000us       1.007us          -8 b          -8 b      20.65 Mb      20.65 Mb           152  \n",
      "                                     aten::scatter_add_         0.45%     688.000us         0.58%     890.000us       9.082us       1.570ms         1.65%       1.570ms      16.020us           0 b           0 b     -92.14 Mb     -92.14 Mb            98  \n",
      "                       pressure[EOS] - compute pressure         0.14%     212.000us         0.54%     820.000us     205.000us       0.000us         0.00%      57.000us      14.250us         -16 b        -280 b    -102.50 Kb    -656.50 Kb             4  \n",
      "                                            aten::clone         0.06%      91.000us         0.52%     792.000us      16.500us       0.000us         0.00%      92.000us       1.917us           0 b           0 b       2.87 Mb           0 b            48  \n",
      "                                      aten::linalg_norm         0.05%      69.000us         0.51%     781.000us      17.750us       0.000us         0.00%     606.000us      13.773us           0 b           0 b      32.81 Mb           0 b            44  \n",
      "                          hashmap - collision detection         0.03%      41.000us         0.47%     715.000us     178.750us       0.000us         0.00%      74.000us      18.500us         -16 b        -272 b    -164.00 Kb           0 b             4  \n",
      "                               aten::linalg_vector_norm         0.35%     530.000us         0.46%     712.000us      16.182us     606.000us         0.64%     606.000us      13.773us           0 b           0 b      32.81 Mb      32.81 Mb            44  \n",
      "                                       aten::zeros_like         0.04%      61.000us         0.46%     710.000us      19.722us       0.000us         0.00%      37.000us       1.028us           0 b           0 b       2.47 Mb           0 b            36  \n",
      "                                              aten::cat         0.29%     448.000us         0.46%     698.000us      17.450us     274.000us         0.29%     274.000us       6.850us           0 b           0 b      29.01 Mb      29.01 Mb            40  \n",
      "                                        aten::unsqueeze         0.35%     537.000us         0.42%     651.000us       1.750us       0.000us         0.00%       0.000us       0.000us           0 b           0 b           0 b           0 b           372  \n",
      "                                          aten::resize_         0.42%     638.000us         0.42%     638.000us       2.626us       0.000us         0.00%       0.000us       0.000us           0 b           0 b     137.55 Mb     137.55 Mb           243  \n",
      "                               aten::unique_consecutive         0.17%     255.000us         0.42%     638.000us      79.750us      33.000us         0.03%      36.000us       4.500us           0 b           0 b     494.00 Kb     -13.50 Kb             8  \n",
      "-------------------------------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  \n",
      "Self CPU time total: 153.242ms\n",
      "Self CUDA time total: 95.068ms\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA],with_stack=False, profile_memory=True) as prof:    \n",
    "    for i in range(1):\n",
    "        with record_function(\"full Timestep\"): \n",
    "            sphSimulation.integrate()\n",
    "        \n",
    "# print(prof.key_averages().table(sort_by='self_cpu_time_total'))\n",
    "print(prof.key_averages().table(sort_by='cpu_time_total'))\n",
    "\n",
    "prof.export_chrome_trace(\"traceGPU.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "99e1cd63",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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