Compute damage variability in the critically acclaimed MMORPG Final Fantasy XIV.
Project description
ffxiv_stats
Introduction
ffxiv_stats
is a Python package to compute statistics relating to damage variability in Final Fantasy XIV. Variability from hit types (critical, direct, critical-direct) and random +/- 5% rolls are considered. Either moments (mean, variance, and skewness) or damage distributions can be calculated. Both methods are exact or (asymptotically exact) and do not rely on sampling.
IMPORTANT: This package is still in the early stages of development and still some sharp edges. It is perfectly usable in its current state, but there is is effectively no error checking/handling. There are also no safety rails; if you try to model a rotation that is impossible in-game, you will still get mathematically correct values. Garbage in = garbage out. Also, be aware that class and method names changes are likely.
IMPORTANT: The effects of hit type rate buffs on skills with guaranteed critical/direct hits is currently not implemented.
ALSO IMPORTANT: Everything here is assuming level 90. There is currently no easy way to handle lower levels.
Getting started
Basic usage
Variability can be computed using either the Rotation
class or one of the role classes (currently only Healer
is supported, other roles have not been verified yet). The Rotation
class computes variability when d2
values are known. The role classes inherits the Rotation
class and converts potencies to d2
values based on supplied stats. Each role class varies in how it assigns main stats, traits, attack modifier, etc.
Using the Rotation
class
The rotation is supplied as a Pandas DataFrame with columns and types:
action_name
: str, unique name of an action. Unique action depends onbuffs
,p
, andl_c
present.base_action
: str, name of an action ignoring buffs. For example, Glare III with chain stratagem and Glare III with mug will have differentaction_names
, but the same base_action. Used for grouping actions together.n
: int, number of hits.p
: list of probability lists, in order[p_NH, p_CH, p_DH, p_CDH]
.d2
: int, base damage value of action before any variability.l_c
: int, damage multiplier for a critical hit. Value should be in the thousands (1250 -> 125% crit buff).buffs
: list of buffs present. A 10% buff should is represented as [1.10]. No buffs can be represented at [1] or None.is_dot
: boolean or 0/1, whether the action is a damage over time effect.
Using a role class
Using a role class is recommended to go from potencies to d2 values given various stats. Attributes like main_stat
, trait
, etc are automatically set to the corresponding values of each role. Rotations are attached using the attach_rotation()
method, which inherits the Rotation
class. However, the rotation_df
argument is similar to the above dataframe, but does have slightly different columns
action_name
: str, unique name of an action. Unique action depends onbuffs
,p
, andl_c
present.base_action
: str, name of an action ignoring buffs. For example, Glare III with chain stratagem and Glare III with mug will have differentaction_names
, but the same base_action. Used for grouping actions together.potency
: int, potency of the actionn
: int, number of hits for the action.p
: list of probability lists, in order[p_NH, p_CH, p_DH, p_CDH]
l_c
: int, damage multiplier for a critical hit. Value should be in the thousands (1250 -> 125% crit buff).buffs
: list of buffs present. A 10% buff should is represented as [1.10]. No buffs can be represented at [1] or None.damage_type
: str saying the type of damage, {'direct', 'magic-dot', 'physical-dot', 'auto'}main_stat_add
: int, how much to add to the main stat (used to account for medication, if present) when computing d2
Instead of a d2
column, potency
, damage_type
, and main-stat-add
are used together with player stats to compute and add a d2
column (along with the is-dot
column).
Examples
Check out examples/
for some basic usages.
Installation
ffxiv_stats
can be installed from source using flit. While in the root directory, use the command
flit install
Alternatively, the package can also be installed with pip.
pip install ffxiv_stats
Requirements
The usual scientific computing stack is used:
- numpy >= 1.20.2
- matplotlib >= 3.4.2
- pandas >= 1.2.4
- scipy >= 1.6.3
These are just the versions it was developed with. Specific versions haven't been tested, but ffxiv_stats
will probably work with lower versions since fairly basic functionalities are used.
Project details
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