Python库 | CombatWiz-0.12.tar.gz

CombatWiz is a combat simulation intended to determine the victory probabilities of combatants using Monte Carlo simulation methods. Current Status: Allows combat between two sides, and produces simple output. #Next Steps: * Creature editor * Graphical output * Map-awareness in which only one object can occupy a block * Missile weapons * Intelligent manuevering * Surrender, Panic, Fleeing * Changing weapons * Multiple attacks per round * Special effect attacks #Its objectives include: * run on linux or mac * web front-end * run multiple scenarios (each many times) to determine best tactics #Example Run: $ combatwiz_runner.py --charid1 3 --charid2 2 --charid3 4 --iterations 1000 --charfile data/characters.csv char1 ---------------------------------------------------------------- charid: char1 side: side-2 critid: 2 name: orc_chieftain hd: 2 hp: 13 ac: 7 race: orc class1: monster class1_level: 0 attack1_thaco: 18 attack1_damage: 2-9 vision: Infra-6 move: 12 char3 ---------------------------------------------------------------- charid: char3 side: side-2 critid: 4 name: giant hd: 0 hp: 50 ac: 4 race: giant class1: monster class1_level: 10 attack1_thaco: 6 attack1_damage: 11-20 vision: standard move: 12 char2 ---------------------------------------------------------------- charid: char2 side: side-1 critid: 3 name: paladin hd: 0 hp: 86 ac: -3 race: human class1: paladin class1_level: 8 attack1_thaco: 10 attack1_damage: 10-17 vision: standard move: 8 ---------------------------------------------------------------- For: paladin Games: 1000 Total Wins: 740 Total Damage Taken: 31247 Total Rounds Required: 4995 Mean Rounds Required: 6.8 Percentage of Wins: 74 Mean PCT HP Taken: 49% For: orc_chieftain Games: 1000 Total Wins: 7 Total Damage Taken: 10 Total Rounds Required: 45 Mean Rounds Required: 6.4 Percentage of Wins: 0 Mean PCT HP Taken: 11% For: giant Games: 1000 Total Wins: 260 Total Damage Taken: 6884 Total Rounds Required: 2069 Mean Rounds Required: 8.0 Percentage of Wins: 26 Mean PCT HP Taken: 52% #Installation * Using [pip](http://www.pip-installer.org/en/latest/) (preferred) or [easyinstall](http://peak.telecommunity.com/DevCenter/EasyInstall): ~~~ TBD ~~~ * Or install manually from [pypi]: ~~~ TBD ~~~ #Dependencies * Python 2.6 or Python 2.7 #Licensing * Gristle uses the BSD license - see the separate LICENSE file for further information #Copyright * Copyright 2013 Ben Farmer, Ken Farmer