Template for monthly notebooks

Baseline.ipynb

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   "metadata": {
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   "source": [
    "# Table of Contents\n",
    " <p><div class=\"lev1 toc-item\"><a href=\"#Watermark\" data-toc-modified-id=\"Watermark-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Watermark</a></div><div class=\"lev1 toc-item\"><a href=\"#Imports-and-Setups\" data-toc-modified-id=\"Imports-and-Setups-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Imports and Setups</a></div><div class=\"lev3 toc-item\"><a href=\"#Autoimport-my-code\" data-toc-modified-id=\"Autoimport-my-code-201\"><span class=\"toc-item-num\">2.0.1&nbsp;&nbsp;</span>Autoimport my code</a></div><div class=\"lev3 toc-item\"><a href=\"#Plotting\" data-toc-modified-id=\"Plotting-202\"><span class=\"toc-item-num\">2.0.2&nbsp;&nbsp;</span>Plotting</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The watermark extension is already loaded. To reload it, use:\n",
      "  %reload_ext watermark\n",
      "Jessime Kirk Mon Oct 31 2016 \n",
      "\n",
      "CPython 2.7.12\n",
      "IPython 5.1.0\n",
      "\n",
      "numpy 1.11.1\n",
      "scipy 0.18.1\n",
      "pandas 0.18.1\n",
      "scikit-learn 0.17.1\n",
      "matplotlib 1.5.3\n",
      "seaborn 0.7.1\n",
      "networkx 1.11\n",
      "notebook 4.2.3\n",
      "jupyter_contrib_nbextensions 0.2.1\n",
      "\n",
      "compiler   : GCC 4.4.7 20120313 (Red Hat 4.4.7-1)\n",
      "system     : Linux\n",
      "release    : 4.4.8-040408-generic\n",
      "machine    : x86_64\n",
      "processor  : x86_64\n",
      "CPU cores  : 4\n",
      "interpreter: 64bit\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a 'Jessime Kirk' -nmv --packages numpy,scipy,pandas,scikit-learn,matplotlib,seaborn,networkx,notebook,jupyter_contrib_nbextensions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports and Setups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import cPickle\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import networkx as nx\n",
    "\n",
    "from tqdm import tqdm, trange, tqdm_notebook, tnrange"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Autoimport my code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'/home/jessime/Code/kmers/Notebooks'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jessime/Code/kmers\n"
     ]
    }
   ],
   "source": [
    "cd .."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "plt.style.use(\"seaborn-whitegrid\")\n",
    "plt.rcParams['figure.figsize'] = [6.0, 4.0]\n",
    "plt.rcParams['axes.titlesize'] = 20\n",
    "plt.rcParams['axes.labelsize'] = 18\n",
    "plt.rcParams['xtick.labelsize'] = 14\n",
    "plt.rcParams['ytick.labelsize'] = 14\n",
    "plt.rcParams['legend.fontsize'] = 14\n",
    "colors = [i['color'] for i in plt.rcParams['axes.prop_cycle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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