demonstration.ipynb

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from emperor.qiime_backports.parse import parse_mapping_file\n",
    "from skbio.stats.ordination import OrdinationResults\n",
    "from skbio.io.util import open_file\n",
    "from emperor import Emperor\n",
    "\n",
    "def load_mf(fn):\n",
    "    with open_file(fn, 'U') as f:\n",
    "        mapping_data, header, _ = parse_mapping_file(f)\n",
    "        _mapping_file = pd.DataFrame(mapping_data, columns=header)\n",
    "        _mapping_file.set_index('SampleID', inplace=True)\n",
    "    return _mapping_file"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "from skbio import DistanceMatrix\n",
    "from skbio.stats.ordination import PCoA\n",
    "\n",
    "mf = load_mf('/Users/yoshikivazquezbaeza/Desktop/emperor_pg/Fasting_Map.txt')\n",
    "\n",
    "dm = DistanceMatrix.from_file('/Users/yoshikivazquezbaeza/Desktop/emperor_pg/unweighted_unifrac_dm.txt')\n",
    "res = PCoA(dm).scores()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "res.proportion_explained"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "np.random.randn(3, 3)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
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   "source": [
    "eigvals = np.array([0.47941212, 0.29201496, 0.24744925,\n",
    "                    0.20149607, 0.18007613, 0.14780677,\n",
    "                    0.13579593, 0.1122597, 0.])\n",
    "n = eigvals.shape[0]\n",
    "site = np.random.rand(n, n)\n",
    "site_ids = ('PC.636', 'PC.635', 'PC.356', 'PC.481', 'PC.354', 'PC.593',\n",
    "            'PC.355', 'PC.607', 'PC.634')\n",
    "p_explained = np.array([0.26688705, 0.1625637, 0.13775413, 0.11217216,\n",
    "                             0.10024775, 0.08228351, 0.07559712, 0.06249458,\n",
    "                             0.])\n",
    "OrdinationResults(eigvals, site=site, site_ids=site_ids, proportion_explained=p_explained)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Emperor(mf, _19)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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