montecarlo_ftd.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "# see https://www.beerfestboots.com/fuck-the-dealer-rules\n",
    "%pylab inline\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def multimode(x):\n",
    "    if len(x) == 0:\n",
    "        return []\n",
    "    mx = max(x)\n",
    "    return list(filter(lambda i: x[i] == mx, range(len(x))))\n",
    "\n",
    "# return a pivot, a high, and a low\n",
    "def get_player_move(remain):\n",
    "    # guess the median for the pivot\n",
    "    cc = []\n",
    "    for i,r in enumerate(remain):\n",
    "        if r != 0:\n",
    "            cc += [i]*r\n",
    "    p = sorted(cc)[len(cc)//2]\n",
    "    \n",
    "    # guess a mode for the final guesses\n",
    "    cl = multimode(remain[0:p])\n",
    "    ch = [x+p+1 for x in multimode(remain[p+1:])]\n",
    "    if len(cl) == 0:\n",
    "        cl = [None]\n",
    "    if len(ch) == 0:\n",
    "        ch = [None]\n",
    "    #print(cl, ch)\n",
    "    \n",
    "    return p, random.choice(cl), random.choice(ch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([6, 7, 43, 30, 3, 4, 1, 5, 8, 9, 4, 6, 2, 4, 3], 3, 3)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NUM_PLAYERS = 15\n",
    "\n",
    "def simulate():\n",
    "    deck = []\n",
    "    for suits in range(4):\n",
    "        for cards in range(13):\n",
    "            # suits don't matter\n",
    "            deck.append(cards)\n",
    "    random.shuffle(deck)\n",
    "\n",
    "    # initial\n",
    "    dealer_num = 0\n",
    "    dealer_count = 0\n",
    "    player_num = 1\n",
    "\n",
    "    remain = [4]*13\n",
    "    drinks = [0]*NUM_PLAYERS\n",
    "\n",
    "    last_correct = 0\n",
    "\n",
    "    while len(deck) != 0:\n",
    "        mc = deck.pop()\n",
    "\n",
    "        # player strategy in that function\n",
    "        p,l,h = get_player_move(remain)\n",
    "        pg = l if mc < p else h\n",
    "        if mc == p:\n",
    "            drinks[dealer_num] += 4\n",
    "            last_correct = 0\n",
    "        elif mc == pg:\n",
    "            # lower\n",
    "            drinks[dealer_num] += 2\n",
    "            last_correct = 0\n",
    "        else:\n",
    "            # miss\n",
    "            drinks[player_num] += abs(pg - mc)\n",
    "            last_correct += 1\n",
    "\n",
    "        if last_correct == 3:\n",
    "            # dealer advance\n",
    "            dealer_num += 1\n",
    "            dealer_num %= NUM_PLAYERS\n",
    "            last_correct = 0\n",
    "            dealer_count += 1\n",
    "\n",
    "        # advance player\n",
    "        player_num += 1\n",
    "        if player_num == dealer_num:\n",
    "            player_num += 1\n",
    "        player_num %= NUM_PLAYERS\n",
    "\n",
    "        # \n",
    "        remain[mc] -= 1\n",
    "    \n",
    "    return drinks, dealer_num, dealer_count\n",
    "\n",
    "simulate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "SIM_COUNT = 1000\n",
    "adn = []\n",
    "add = np.array([0]*NUM_PLAYERS)\n",
    "dc = np.array([0]*NUM_PLAYERS)\n",
    "for i in range(SIM_COUNT):\n",
    "    drinks, dealer_num, dealer_count = simulate()\n",
    "    adn.append(dealer_count)\n",
    "    add[dealer_num] += 1\n",
    "    dc += drinks\n",
    "add //= (SIM_COUNT//400)\n",
    "dc //= SIM_COUNT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.139"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figsize(12,12)\n",
    "plt.bar(range(len(add)), add)\n",
    "plt.bar(range(len(dc)), dc)\n",
    "np.mean(adn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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