You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
48 lines
2.0 KiB
48 lines
2.0 KiB
= 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 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].
|