{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello world\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a ** 2\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python for HPC\n",
    "\n",
    "* dfsafds\n",
    "* fdsafdsaf\n",
    "\n",
    "$\\chi^2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2b343bb8ecc0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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A1ar6XAVjWnrGISJxnsfdD2QDXUSko4iEA4nAe74Kb0x1+mn/MYZOWED+8SJmJMczoH0T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\nseI3xpggY8VvjDFB5v8B6zDXe54vk6EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2b3438581b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1,2,3,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "comet-07-18.sdsc.edu\r\n"
     ]
    }
   ],
   "source": [
    "!hostname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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