gistfile1.json

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   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
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   "source": [
    "def prices(p, a, b, c, d, n):\n",
    "    price = lambda k: p * (np.sin(a * k + b) + np.cos(c * k + d) + 2)\n",
    "    return pd.Series([price(k+1) for k in range(n)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def sol(p, a, b, c, d, n):\n",
    "    a =  prices(p, a, b, c, d, n)\n",
    "    max = a.cummax()\n",
    "    min = a[::-1].cummin()\n",
    "    diff = (max-min)\n",
    "    return np.max(diff.max(), 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
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     "data": {
      "text/plain": [
       "104.85511047739418"
      ]
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     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "sol(42, 1, 23, 4, 8, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
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    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol(100,7,615,998,801,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
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    {
     "data": {
      "text/plain": [
       "399.30381259211197"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol(100,432,406,867,60,1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!open ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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