{ "metadata": { "name": "Dice rolling stats" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": "#Dice rolling statistics\n\nSimply call `roll(string)` where `string` is a dice combination with addition and multiplier modifiers.\n\nThe string can take the form:\n\n`(nds+a)*m` where `n` is the number of dice, `s` is the number of sides the dice has, `a` is an addition modifier and `m` is a multiplier. Note that the parenthesis are optional (and multiplication always happens last, regardless of their presence). The addition and multiplier are also optional. The `d` may be capital and the `*` may be `x` or `X`.\n\nThe code calculates statistics and presents a plot with probability information.\n\nSee the examples following the code." }, { "cell_type": "code", "collapsed": false, "input": "%matplotlib inline\nimport numpy as np\nimport itertools\nimport matplotlib.pyplot as plt\nimport re\nimport sys\n\n# Copyright (c) 2014, Casey Webster.\n# All rights reserved.\n# Licensed under BSD 3-clause license.\n# get a copy at http://opensource.org/licenses/BSD-3-Clause\n\ndef roll(dicestr):\n p = re.compile(r\"\"\"\n \\(?\n (?P\\d+)?\n [dD]\n (?P\\d+)\n (?:\\+\n (?P\\d+)\n )?\n \\)?\n (?:[xX*]\n (?P\\d+)\n )?\n \"\"\", re.VERBOSE)\n m = p.match(dicestr)\n if not m:\n raise ValueError(\"Invalid string contents\")\n if m.group('ndice') == None:\n ndice = 1\n else:\n ndice = int(m.group('ndice'))\n dtype = int(m.group('dtype'))\n if m.group('add') == None: \n add = 0\n else:\n add = int(m.group('add'))\n if m.group('mult') == None: \n mult = 1\n else:\n mult = int(m.group('mult'))\n \n rollinfo(ndice,dtype,add,mult)\n\ndef rollinfo(ndice,nsides,add,mult):\n min = (ndice+add)*mult\n max = ((ndice*nsides)+add)*mult\n n = max-min+1\n rolls = list(itertools.product(range(1,nsides+1),repeat=ndice))\n outcomes = len(rolls)\n rolls = [(sum(x)+add)*mult for x in rolls]\n counts = list(np.zeros(n))\n for i in rolls:\n counts[i-min] += 1\n sums = list(range(min,max+1,mult))\n # remove 0-valued elements\n counts = list(filter((0.).__ne__,counts))\n \n #calc probability stuff\n p = [float(x/outcomes)*100 for x in counts]\n ap = np.cumsum(p)\n mean = np.mean(rolls)\n std = np.std(rolls)\n \n plt.plot(sums,p) \n plt.fill_between(sums,p,0,where=[(x > mean-std) and (x < mean+std) for x in sums], color='0.75')\n plt.plot([mean,mean],[0,np.max(p)], color='k')\n plt.xlim(min,max)\n plt.ylim(0,np.max(p))\n ax2 = plt.twinx()\n ax2.plot(sums,ap)\n ax2.set_ylim(0,100)\n ax2.set_xlim(min,max)\n \n title=\"{0}d{1}\".format(ndice,nsides)\n if add > 0: title +=\"+{0}\".format(add)\n if mult > 1: title +=\"*{0}\".format(mult)\n plt.text(0.05,0.90,title, size='x-large', transform=ax2.transAxes)\n plt.text(0.05,0.85,r\"$\\mu$ = {0}\".format(mean), transform=ax2.transAxes)\n plt.text(0.05,0.80,r\"$\\sigma$ = {0:1.2f}\".format(std), transform=ax2.transAxes)\n plt.text(0.05,0.75,r\"range = [{0}-{1}]\".format(min,max), transform=ax2.transAxes)\n #plt.xticks([np.arange(min,mean+1,1),np.arange(mean,max,1)])", "language": "python", "metadata": {}, "outputs": [], "prompt_number": 354 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"2d6\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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eolKYF7PLCQjrtX27sjewpIGN49y5Gkya5Ee/fpcYO9b0DQDupIqjo6sTESGp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\nuH79Ovv27WPMP+dXVatWxcn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"text": "" } ], "prompt_number": 355 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"(3d6+6)*2\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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nzp0cP36c+vXrZ9UZio5+fpvERYsWcfLkyee+Jk6cqPU5PXz4kNGjR3P69Gn+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\nx3PvC5HTWvLtp5/g0SMx71p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"text": "" } ], "prompt_number": 356 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"4d6\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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OyaQi8Oiel4ULFyZfvnw0bNjQ3NmEDTlwIJ5ffsnJW29F6Y5i8+Ljs/Dhh2pB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\n1qxZw7BhwyhYsCDDhw8nODi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"text": "" } ], "prompt_number": 357 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"4d6+6\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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ICxcu0LhxY3x8fBg2bBhLliwx2XsVLVqUjRs3ZiwW00L6YrGsBrmN5fLlZD7/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\nI8qeXq92VRo+XA16vfKK1hEJYV0aN4Y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"text": "" } ], "prompt_number": 358 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"5d8\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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7aDcpYRtOnVKjzbZttY5EOytWeFCmzF0CA/8x6Xn69oXFiyHNdt9ACRPJVa2X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\nT7lRa2sk2VuwyZPhnXe0jiL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"text": "" } ], "prompt_number": 359 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"d20\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": "" } ], "prompt_number": 360 }, { "cell_type": "code", "collapsed": false, "input": "roll(\"4d10*10\")", "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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VY1E3Xfv11yQePLDk5Zfv6P1YpmD//v9w4MB/+Oqrk7kWN+vdO5ohQ1oSE5NK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\nWLxY7SikklSgZG9hYUF4eDj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