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      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f017b665bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the pangenome pie chart\n",
    "plt.figure(figsize=(10, 10))\n",
    "\n",
    "core = roary[roary.sum(axis=1) == roary.shape[1]].shape[0]\n",
    "softcore = roary[(roary.sum(axis=1) < roary.shape[1]) &\n",
    "                 (roary.sum(axis=1) >= roary.shape[1]*0.95)].shape[0]\n",
    "shell = roary[(roary.sum(axis=1) < roary.shape[1]*0.95) &\n",
    "                 (roary.sum(axis=1) >= roary.shape[1]*0.15)].shape[0]\n",
    "cloud = roary[roary.sum(axis=1) < roary.shape[1]*0.15].shape[0]\n",
    "\n",
    "total = roary.shape[0]\n",
    "\n",
    "def my_autopct(pct):\n",
    "    val=int(pct*total/100.0)\n",
    "    return '{v:d}'.format(v=val)\n",
    "\n",
    "a=plt.pie([core, softcore, shell, cloud],\n",
    "      labels=['core\\n(%d strains)'%roary.shape[1],\n",
    "              'soft-core\\n(%d <= strains < %d)'%(roary.shape[1]*.95,\n",
    "                                                 roary.shape[1]),\n",
    "              'shell\\n(%d <= strains < %d)'%(roary.shape[1]*.15,\n",
    "                                             roary.shape[1]*.95),\n",
    "              'cloud\\n(strains < %d)'%(roary.shape[1]*.15)],\n",
    "      explode=[0.1, 0.05, 0.02, 0], radius=0.9,\n",
    "      colors=[(0, 0, 1, float(x)/total) for x in (core, softcore, shell, cloud)],\n",
    "      autopct=my_autopct)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",