Allow for callback function to set uncertainty decay

[zass30]

Let a user specify a manual uncertainty decay function. This could either be run at set intervals in a game's history for all players (for example as a daily job), or else called ad-hoc when querying a given player's ranking, or else called as a callback when parsing new games.
As an example, a basic decay function could be that sigma is multiplied by some factor, like 1.1, for every day a player has not played.

[glandfried]

Hi @zass30,

The equation 11 of the documentation [1] models the forgetting rate.

The parameter History(... gamma = g) is the forgetting rate, as used in code 7, 11. This rate will govern all players without prior. We can set different rate initializing the parameter priors, History(..., priors), which is a dictionary Id - Player(Gaussian(mu, sigma), beta, gamma) class.

Note that the class History uses the temporal distance between events to determine the amount of dynamic uncertainty to be added between games. So the equation 11 is implemented as:

The amount of time between events is set out by the parameter times History(..., times).

At the moment this is the only forgetting function implemented in the three packages.

[1] https://github.com/glandfried/TrueSkillThroughTime/releases/download/doc/landfried-learning.pdf

[glandfried]

Python version V2.0.0 is coming soon and the Julia version is not far behind.