Source for generating https://mhapi.info
				
			
			
		
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| README.adoc | 3 years ago | |
| RECOMMENDATIONS.adoc | 11 years ago | |
		
			
				
				README.adoc
			
		
		
			
			
		
	
	= Monster Hunter scripts This repository contains the source code for http://mhapi.info, a site for monster hunter related calculators and tools. It also contains scripts that can be used directly from the command line, and python modules that can be used to build other monster hunter related tools. == Dependencies Tested using Python 2.7, might work with 2.6. Uses sqlite3, which is part of the standard library now but I'm not sure it's always compiled in by default in all Python distributions (e.g. for Windows or Mac OS X). == Acknowledgements The bundled monster hunter db is from the excellent link:https://github.com/kamegami13/MonsterHunter4UDatabase[MonsterHunter4UDatabase] Android app by DavianCorp, which is also MIT licensed. See link:db/COPYING.mh4udb[] for license details. Rise data is from link:https://mhrise.mhrice.info/about.html[MHRice]. == Example usage For a list of quests and hunts providing the specified monster part: bin/mhrewards.py "Zinogre Jasper" This gives detailed expected values for the item from different sources, including quest rewards, carves, capture, and shiny drops. It also gives recommendations for which quests and strategy (capture or kill) will give the best results. See link:RECOMMENDATIONS.adoc[] for a more detailed explanation of the output. For more manual calculations, mhprob.py can be used directly. The quest "Plain Dangerous" in 3U has 2 fixed rewards in A, one in B. Diablos hardhorns have a 5% chance: bin/mhprop.py 5 2 3 69 bin/mhprop.py 5 1 1 69 For great luck, you would replace 69 with 90. The output includes both expected value and probability of getting at least one. == Math Monster hunter rewards can be modeled using the Binomial distribution. The most popular method I've seen online is to calculate the probability of getting at least one. I prefer to use expected (mean) value, which is easier to calculate and provides a more intuitive quantity. For more information see the link:http://en.wikipedia.org/wiki/Expected_value[Wikipedia article] on expected value, and the description of how to calculate expected value on the link:http://en.wikipedia.org/wiki/Binomial_distribution#Mean_and_variance[Binomial distribution].