2016-08-25-playing-with-movie-making.ipynb

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   "execution_count": 2,
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   "source": [
    "import matplotlib.animation as animation\n",
    "import numpy as np\n",
    "from pylab import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import scipy.ndimage"
   ]
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  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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   "outputs": [],
   "source": [
    "import glob\n",
    "files = glob.glob('/home/pmcroot/data1/2016-08-24_50mm_star_focus_test_100ms/*step_0005.npz')\n",
    "files.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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       "3141"
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     "execution_count": 7,
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   "source": [
    "len(files)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/pmcroot/data1/2016-08-24_50mm_star_focus_test_100ms/2016-08-24_220203_focus_step_0000.npz'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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   "source": [
    "files[0]"
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  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'np' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-3b561555434b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mimd\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'image'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'np' is not defined"
     ]
    }
   ],
   "source": [
    "imd = np.load(files[0])['image']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "dpi = 100\n",
    "def ani_frame(frames=10):\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111)\n",
    "    #ax.set_aspect('equal')\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "\n",
    "    im = ax.imshow(scipy.ndimage.gaussian_filter(imd,2)[::4,::4],cmap='gray',interpolation='nearest')\n",
    "    fig.set_size_inches([12,8])\n",
    "    txt = ax.text(0.1,0.9,'time:',ha='left',va='top',color='yellow')\n",
    "\n",
    "\n",
    "    tight_layout()\n",
    "\n",
    "\n",
    "    def update_img(n):\n",
    "        npz = np.load(files[n])\n",
    "        imd = npz['image']\n",
    "        data = scipy.ndimage.gaussian_filter(imd,2)[::4,::4]\n",
    "        im.set_data(data)\n",
    "        mn = data.mean(dtype='float64')\n",
    "        if mn < 1000:\n",
    "            mx = 1000\n",
    "        else:\n",
    "            mx = data.max()\n",
    "        im.set_clim(0,mx)\n",
    "        txt.set_text(time.ctime(npz['state'][()]['time']))\n",
    "        return im,txt\n",
    "\n",
    "    #legend(loc=0)\n",
    "    ani = animation.FuncAnimation(fig,update_img,frames,interval=30)\n",
    "    writer = animation.writers['ffmpeg'](fps=30)\n",
    "\n",
    "    ani.save('/home/gjones/demo.mp4',writer=writer,dpi=dpi)\n",
    "    return ani"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "ani_frame(frames=len(files))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
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