591ac4bdeb
Output should be the same as before refactor, except for max cap reward for quests. The fix for using carving god on tail carves in the cap calculation was only applied to the print_monsters_and_rewards copy of the code. It should be less than the previous value by the differece between min and max for tail carve.
= Monster Hunter scripts This repository contains scripts for calculating probabilities and expected values for rewards and carves in Monster Hunter games. == 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). == Example usage For a list of quests providing the specified monster part: ./mhrewards.py "Zinogre Jasper" This gives expected values for the item from different sources, including quest rewards, carves, capture, and shiny drops. An expected value of 8% means that on average, you would get 8 of the item from 100 quests. Note that this is different from the probability of getting at least one, which will be lower and is a pain to calculate when there can be different number of rewards. It also takes into account Carving and Luck skills. The main value shown assumes no food or armor skills. For Carves the extra values listed on the right are for felyne skills Carver Lo, Carver Hi, then armor skills Carving Master and Carving God. For quest rewards the extra values are for food/armor skills Lucky Cat/Good Luck and Ultra Lucky Cat/Great Luck. The totals at the end list the range from no skills to the best skill. For capture rewards the extra values are for armor skills Capture Expect, Master, and God. 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: ./mhprop.py 5 2 3 69 ./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/Binomial_distribution#Mean_and_variance[Wikipedia article].