From 86d30ad73ad8690019fc6e6411a7a567b35ed470 Mon Sep 17 00:00:00 2001 From: Peter Norvig Date: Sat, 20 Apr 2019 01:05:18 -0700 Subject: [PATCH] Add files via upload --- ipynb/Dice Baseball.ipynb | 88 +++++++++++++++++++++++++-------------- 1 file changed, 56 insertions(+), 32 deletions(-) diff --git a/ipynb/Dice Baseball.ipynb b/ipynb/Dice Baseball.ipynb index f18be45..a12f721 100644 --- a/ipynb/Dice Baseball.ipynb +++ b/ipynb/Dice Baseball.ipynb @@ -8,7 +8,7 @@ "\n", "# Dice Baseball\n", "\n", - "The [538 Riddler for March 22, 2019](https://fivethirtyeight.com/features/can-you-turn-americas-pastime-into-a-game-of-yahtzee/) asks us to simulate baseball using probabilities from a 19th century dice game called *Our National Ball Game*.:\n", + "The [538 Riddler for March 22, 2019](https://fivethirtyeight.com/features/can-you-turn-americas-pastime-into-a-game-of-yahtzee/) asks us to simulate baseball using probabilities from a 19th century dice game called *Our National Ball Game*:\n", "\n", " 1,1: double 2,2: strike 3,3: out at 1st 4,4: fly out\n", " 1,2: single 2,3: strike 3,4: out at 1st 4,5: fly out\n", @@ -40,9 +40,11 @@ "- A runner who advances to base 4 or higher has scored a run (unless there are already 3 outs).\n", "- The function `inning` simulates a half inning and returns the number of runs scored.\n", "- I want to be able to test `inning` by feeding it specific events, and I also want to generate random innings. So I'll make the interface be that I pass in an *iterable* of events. The function `event_stream` generates an endless stream of randomly sampled events.\n", - "- Note that it is consider good Pythonic style to automatically convert Booleans to integers, so for a runner on second (`r = 2`) when the event is a single (`e = '1'`), the expression `r + int(e) + (r == 2)` evaluates to `2 + 1 + 1` or `4`, meaning the runner scores.\n", + "- Note that it is consider good Pythonic style to automatically convert Booleans to integers, so for a runner on second (`r = 2`) when the event is a single (`e = '1'`), the expression `r + int(e) + (r == 2)` evaluates to `2 + 1 + 1` or `4`, meaning the runner on second scores.\n", "- I'll play 1 million innings and store the resulting scores in `innings`.\n", - "- To simulate a game I just sample 9 elements of `innings` and sum them." + "- To simulate a game I just sample 9 elements of `innings` and sum them.\n", + "\n", + "# The Code" ] }, { @@ -116,17 +118,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "0 outs, 0 runs, event: o, runners: []\n", - "1 outs, 0 runs, event: 1, runners: []\n", - "1 outs, 0 runs, event: o, runners: [1]\n", - "2 outs, 0 runs, event: 1, runners: [2]\n", - "2 outs, 1 runs, event: o, runners: [1]\n" + "0 outs, 0 runs, event: E, runners: []\n", + "0 outs, 0 runs, event: 4, runners: [1]\n", + "0 outs, 2 runs, event: E, runners: []\n", + "0 outs, 2 runs, event: 1, runners: [1]\n", + "0 outs, 2 runs, event: f, runners: [2, 1]\n", + "1 outs, 2 runs, event: B, runners: [2, 1]\n", + "1 outs, 2 runs, event: 1, runners: [3, 2, 1]\n", + "1 outs, 4 runs, event: E, runners: [2, 1]\n", + "1 outs, 4 runs, event: o, runners: [3, 2, 1]\n", + "2 outs, 5 runs, event: o, runners: [3, 2]\n" ] }, { "data": { "text/plain": [ - "1" + "5" ] }, "execution_count": 3, @@ -147,19 +154,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "0 outs, 0 runs, event: E, runners: []\n", - "0 outs, 0 runs, event: 1, runners: [1]\n", - "0 outs, 0 runs, event: 4, runners: [2, 1]\n", - "0 outs, 3 runs, event: o, runners: []\n", - "1 outs, 3 runs, event: 1, runners: []\n", - "1 outs, 3 runs, event: o, runners: [1]\n", - "2 outs, 3 runs, event: O, runners: [2]\n" + "0 outs, 0 runs, event: 1, runners: []\n", + "0 outs, 0 runs, event: B, runners: [1]\n", + "0 outs, 0 runs, event: O, runners: [2, 1]\n", + "1 outs, 0 runs, event: 1, runners: [2, 1]\n", + "1 outs, 1 runs, event: 3, runners: [2, 1]\n", + "1 outs, 3 runs, event: 1, runners: [3]\n", + "1 outs, 4 runs, event: f, runners: [1]\n", + "2 outs, 4 runs, event: o, runners: [1]\n" ] }, { "data": { "text/plain": [ - "3" + "4" ] }, "execution_count": 4, @@ -222,7 +230,7 @@ "\n", "# Simulating\n", "\n", - "Now, simulate a million innings, and then sample from them to simulate a million nine-inning games:" + "Now, simulate a million innings, and then sample from them to simulate a million nine-inning games (for one team):" ] }, { @@ -240,7 +248,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Finally, display the mean number of runs scored per team per nine-inning game, along with a histogram:" + "Let's see histograms:" ] }, { @@ -250,17 +258,7 @@ "outputs": [ { "data": { - "text/plain": [ - "14.525194" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -272,8 +270,34 @@ } ], "source": [ - "plt.hist(games, ec='black', bins=max(games)-min(games)+1)\n", - "sum(games) / N" + "def hist(nums, title): \n", + " \"Plot a histogram.\"\n", + " plt.hist(nums, ec='black', bins=max(nums)-min(nums)+1, align='left')\n", + " plt.title(f'{title} Mean: {sum(nums)/len(nums):.3f}, Min: {min(nums)}, Max: {max(nums)}')\n", + " \n", + "hist(innings, 'Runs per inning:')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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