iter-surfaces.ipynb

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     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "ITER Fly-Through\n",
      "=================\n",
      "This video of a MOAB-based ITER surface model was generate with the yt using the following notebook! "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import YouTubeVideo\n",
      "YouTubeVideo('KKQc-wSEOxQ')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "        <iframe\n",
        "            width=\"400\"\n",
        "            height=300\"\n",
        "            src=\"http://www.youtube.com/embed/KKQc-wSEOxQ\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "<IPython.lib.display.YouTubeVideo at 0x683ce10>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import h5py\n",
      "from yt.mods import *\n",
      "import matplotlib.pyplot as plt\n",
      "from matplotlib import collections\n",
      "from yt.utilities.lib.geometry_utils import triangle_plane_intersect"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def intersect_plane(ax, coord, tri):\n",
      "    # Tri is [ (p0, p1, p2), (p0, p1, p2), (p0, p1, p2) ]\n",
      "    p = []\n",
      "    for i0, i1 in [(0, 1), (1, 2), (2, 0)]:\n",
      "        p0 = tri[i0,:]\n",
      "        p1 = tri[i1,:]\n",
      "        vec = p1 - p0\n",
      "        t = (coord - p0[ax])/vec[ax]\n",
      "        # coord = t0[ax] + vec[ax]*t\n",
      "        if 0.0 <= t <= 1.0:\n",
      "            p.append(p0 + vec * t)\n",
      "    return p"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#f = h5py.File(\"teapot.h5m\", \"r\")\n",
      "#f = h5py.File(\"iter_imprinted.h5m\", \"r\")\n",
      "f = h5py.File(\"bllite30matls_zip.h5m\", \"r\")\n",
      "coords = f[\"/tstt/nodes/coordinates\"][:]\n",
      "conn = f[\"/tstt/elements/Tri3/connectivity\"][:]\n",
      "points = coords[conn-1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%time\n",
      "ax = 2\n",
      "xax, yax = x_dict[ax], y_dict[ax]\n",
      "mi = coords.min(axis=0)\n",
      "ma = coords.max(axis=0)\n",
      "cut_points = np.mgrid[coords[:,ax].min():coords[:,ax].max():1008j]\n",
      "for i, coord in parallel_objects(enumerate(cut_points)):\n",
      "    plt.clf()\n",
      "    l_cy = triangle_plane_intersect(ax, coord, points)[:,:,(xax, yax)]\n",
      "    lc = collections.LineCollection(l_cy, colors='k')\n",
      "    plt.gca().add_collection(lc)\n",
      "    plt.xlim(mi[xax], ma[xax])\n",
      "    plt.ylim(mi[yax], ma[yax])\n",
      "    plt.title(\"z = {0:.4} cm\".format(coord))\n",
      "    plt.xlabel(\"x [cm]\")\n",
      "    plt.ylabel(\"y [cm]\")\n",
      "    plt.savefig(\"iter{0:03}.png\".format(i))\n",
      "    print(\"generated {0:.4} {1}\".format(coord, i))"
     ],
     "language": "python",
     "metadata": {},
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       "text": [
        "\n",
        "generated 828.1 994"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 829.7 995"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 831.4 996"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 833.1 997"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 834.8 998"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 836.5 999"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 838.2 1000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 839.9 1001"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 841.6 1002"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 843.2 1003"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 844.9 1004"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 846.6 1005"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 848.3 1006"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "generated 850.0 1007"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "CPU times: user 17min 57s, sys: 4.24 s, total: 18min 1s\n",
        "Wall time: 18min 3s\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x681e850>"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mencoder 'mf://iter*.png' -mf fps=24 -o iter-surfaces.mp4 -ovc lavc -lavcopts vcodec=mpeg4"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "MEncoder svn r34540 (Ubuntu), built with gcc-4.7 (C) 2000-2012 MPlayer Team\r\n",
        "\r\n",
        "WARNING: OUTPUT FILE FORMAT IS _AVI_. See -of help.\r\n",
        "success: format: 16  data: 0x0 - 0x0\r\n",
        "MF file format detected.\r\n",
        "[mf] search expr: iter*.png\r\n",
        "[mf] number of files: 1008 (8064)\r\n",
        "[demux_mf] file type was not set! trying 'type=png'...\r\n",
        "VIDEO:  [MPNG]  0x0  24bpp  24.000 fps    0.0 kbps ( 0.0 kbyte/s)\r\n",
        "[V] filefmt:16  fourcc:0x474E504D  size:0x0  fps:24.000  ftime:=0.0417\r\n",
        "libavcodec version 53.35.0 (external)\r\n",
        "Mismatching header version 53.32.2\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Opening video filter: [expand osd=1]\r\n",
        "Expand: -1 x -1, -1 ; -1, osd: 1, aspect: 0.000000, round: 1\r\n",
        "==========================================================================\r\n",
        "Opening video decoder: [ffmpeg] FFmpeg's libavcodec codec family\r\n",
        "Selected video codec: [ffpng] vfm: ffmpeg (FFmpeg PNG)\r\n",
        "==========================================================================\r\n",
        "Could not find matching colorspace - retrying with -vf scale...\r\n",
        "Opening video filter: [scale]\r\n",
        "Movie-Aspect is undefined - no prescaling applied.\r\n",
        "[swscaler @ 0x7fe74c4e3640]BICUBIC scaler, from bgra to yuv420p using MMX2\r\n",
        "videocodec: libavcodec (432x288 fourcc=34504d46 [FMP4])\r\n"
       ]
      },
      {
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       "stream": "stdout",
       "text": [
        "Writing header...\r\n",
        "ODML: Aspect information not (yet?) available or unspecified, not writing vprp header.\r\n",
        "Writing header...\r\n",
        "ODML: Aspect information not (yet?) available or unspecified, not writing vprp header.\r\n",
        "Pos:   0.0s      1f ( 0%)  0.00fps Trem:   0min   0mb  A-V:0.000 [0:0]\r",
        "\r\n",
        "[VD_FFMPEG] DRI failure.\r\n",
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        "Pos:  41.0s    985f (97%) 290.30fps Trem:   0min   2mb  A-V:0.000 [433:0]\r",
        "Pos:  41.1s    986f (97%) 290.34fps Trem:   0min   2mb  A-V:0.000 [433:0]\r",
        "Pos:  41.1s    987f (97%) 290.46fps Trem:   0min   2mb  A-V:0.000 [432:0]\r"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Pos:  41.2s    988f (98%) 290.50fps Trem:   0min   2mb  A-V:0.000 [432:0]\r",
        "Pos:  41.2s    989f (98%) 290.54fps Trem:   0min   2mb  A-V:0.000 [432:0]\r",
        "Pos:  41.2s    990f (98%) 290.58fps Trem:   0min   2mb  A-V:0.000 [431:0]\r",
        "Pos:  41.3s    991f (98%) 290.70fps Trem:   0min   2mb  A-V:0.000 [431:0]\r",
        "Pos:  41.3s    992f (98%) 290.74fps Trem:   0min   2mb  A-V:0.000 [431:0]\r",
        "Pos:  41.4s    993f (98%) 290.86fps Trem:   0min   2mb  A-V:0.000 [431:0]\r",
        "Pos:  41.4s    994f (98%) 290.90fps Trem:   0min   2mb  A-V:0.000 [430:0]\r",
        "Pos:  41.5s    995f (98%) 290.94fps Trem:   0min   2mb  A-V:0.000 [430:0]\r",
        "Pos:  41.5s    996f (98%) 291.06fps Trem:   0min   2mb  A-V:0.000 [430:0]\r",
        "Pos:  41.5s    997f (98%) 291.09fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.6s    998f (99%) 291.22fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.6s    999f (99%) 291.25fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.7s   1000f (99%) 291.29fps Trem:   0min   2mb  A-V:0.000 [428:0]\r",
        "Pos:  41.7s   1001f (99%) 291.41fps Trem:   0min   2mb  A-V:0.000 [430:0]\r",
        "Pos:  41.8s   1002f (99%) 291.45fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.8s   1003f (99%) 291.49fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.8s   1004f (99%) 291.61fps Trem:   0min   2mb  A-V:0.000 [429:0]\r",
        "Pos:  41.9s   1005f (99%) 291.64fps Trem:   0min   2mb  A-V:0.000 [428:0]\r",
        "Pos:  41.9s   1006f (99%) 291.76fps Trem:   0min   2mb  A-V:0.000 [428:0]\r"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Pos:  42.0s   1007f (99%) 291.80fps Trem:   0min   2mb  A-V:0.000 [428:0]\r",
        "Pos:  42.0s   1008f (100%) 291.84fps Trem:   0min   2mb  A-V:0.000 [428:0]\r",
        "\r\n",
        "\r\n",
        "Flushing video frames.\r\n",
        "Writing index...\r\n",
        "Writing header...\r\n",
        "ODML: Aspect information not (yet?) available or unspecified, not writing vprp header.\r\n",
        "\r\n",
        "Video stream:  428.022 kbit/s  (53502 B/s)  size: 2247118 bytes  42.000 secs  1008 frames\r\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!rm iter*.png"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}