{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import ipyvolume\n",
    "import ipywidgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%javascript\n",
    "require.onResourceLoad = function(context, map)\n",
    "{\n",
    "    console.log(\"loading \" +map.name)\n",
    "    require.undef(map.name);\n",
    "};\n",
    "require.undef(\"nbextensions/ipyvolume/index\")\n",
    "require([\"nbextensions/ipyvolume/index\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ds = ipyvolume.datasets.aquariusA2.fetch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "v = ipyvolume.quickvolshow(ds.data.T, width=200, height=200, lighting=True,\n",
    "                     level=[0.3, 0.4, 0.9], opacity=[0.03, 0.2, 0.1])\n",
    "v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ipyvolume.embed.embed_html(\"/tmp/test.html\", v)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}