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   "source": [
    "# Overview\n",
    "\n",
    "This a notebook that inspects the results of a WarpX simulation.\n",
    "\n",
    "# Instructions\n",
    "\n",
    "Execute the cells below one by one, by selecting them with your mouse and typing `Shift + Enter`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# General imports\n",
    "import glob, sys\n",
    "# Import numpy and matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib\n",
    "# Import yt\n",
    "import yt\n",
    "yt.funcs.mylog.setLevel(50) # Deactivate yt verbose\n",
    "\n",
    "# Import interactive notebook feature\n",
    "#from IPython.display import clear_output\n",
    "from ipywidgets import interact, IntSlider, RadioButtons\n",
    "\n",
    "# Find output iterations\n",
    "file_list = glob.glob('plt?????')\n",
    "iterations = [ int(file_name[3:]) for file_name in file_list ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Functions to extract and plot the fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def extra_data( field, iteration ):\n",
    "    \"\"\"\n",
    "    Extract the 3D array that corresponds to `field` at the \n",
    "    requested iteration, and returns as a `YTarray`, which \n",
    "    can be used exactly like a numpy array.\n",
    "    \"\"\"\n",
    "    ds = yt.load( './plt%05d/' %iteration )\n",
    "    data = ds.covering_grid(level=0, \n",
    "            left_edge=ds.domain_left_edge, \n",
    "            dims=ds.domain_dimensions)\n",
    "    return( data[field] ) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def plot_field( iteration, field, slicing_direction='y' ):\n",
    "    # Get the data\n",
    "    field_array = extra_data( field, iteration )\n",
    "    \n",
    "    # Get the position of the edges\n",
    "    ds = yt.load( './plt%05d/' %iteration )\n",
    "    left_edge = ds.domain_left_edge.convert_to_mks()*1.e6\n",
    "    right_edge = ds.domain_right_edge.convert_to_mks()*1.e6\n",
    "\n",
    "    if slicing_direction == 'x':\n",
    "        n = int( ds.domain_dimensions[0]//2 )\n",
    "        data2d = field_array[n, :, :]\n",
    "        extent = [ left_edge[2], right_edge[2], left_edge[1], right_edge[1] ]\n",
    "    elif slicing_direction == 'y':\n",
    "        n = int( ds.domain_dimensions[1]//2 )\n",
    "        data2d = field_array[:, n, :]\n",
    "        extent = [ left_edge[2], right_edge[2], left_edge[0], right_edge[0] ]\n",
    "    elif slicing_direction == 'z':\n",
    "        n = int( ds.domain_dimensions[2]//2 )\n",
    "        data2d = field_array[:, :, n]\n",
    "        extent = [ left_edge[1], right_edge[1], left_edge[0], right_edge[0] ]\n",
    "    plt.clf()\n",
    "    plt.imshow( data2d, interpolation='nearest', cmap='viridis',\n",
    "              origin='lower', extent=extent )\n",
    "    plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Interactive viewer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "interact(plot_field, \n",
    "         iteration = IntSlider(min=min(iterations), max=max(iterations), step=iterations[1]-iterations[0]),\n",
    "         field = RadioButtons( options=['jx', 'jy', 'jz', 'Ex', 'Ey', 'Ez'], value='jz'),\n",
    "         slicing_direction = RadioButtons( options=[ 'x', 'y', 'z'], value='y') )"
   ]
  }
 ],
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