skillratings 0.29.0

//! The Glicko algorithm, developed by Mark Glickman as an improvement on Elo.\
//! It is still being used in some games in favour Glicko-2, such as Pokémon Showdown, Chess.com and Quake Live.
//!
//! If you are looking for the updated Glicko-2 rating system, please see [`Glicko-2`](crate::glicko2).
//!
//! The main improvement over Elo is the rating deviation introduced,
//! which decreases over time as the player plays more matches and the rating becomes more reliable.
//! This allows players to rise and fall through the ranks quickly at the beginning,
//! and not gain or lose as much rating points after completing more matches.
//!
//! # Quickstart
//!
//! This is the most basic example on how to use the Glicko Module.\
//! Please take a look at the functions below to see more advanced use cases.
//!
//! ```
//! use skillratings::{
//!     glicko::{glicko, GlickoConfig, GlickoRating},
//!     Outcomes,
//! };
//!
//! // Initialise a new player rating with a rating of 1500 and a deviation of 350.
//! let player_one = GlickoRating::new();
//!
//! // Or you can initialise it with your own values of course.
//! // Imagine these numbers being pulled from a database.
//! let (some_rating, some_deviation) = (1325.0, 230.0);
//! let player_two = GlickoRating {
//!     rating: some_rating,
//!     deviation: some_deviation,
//! };
//!
//! // The outcome of the match is from the perspective of player one.
//! let outcome = Outcomes::WIN;
//!
//! // The config allows you to specify certain values in the Glicko calculation.
//! // Here we set the c value to 23.75, instead of the default 63.2.
//! // This will decrease the amount by which rating deviation increases per rating period.
//! let config = GlickoConfig { c: 23.75 };
//!
//! // The glicko function will calculate the new ratings for both players and return them.
//! let (new_player_one, new_player_two) = glicko(&player_one, &player_two, &outcome, &config);
//! ```
//!
//! # More Information
//!
//! - [Wikipedia Article](https://en.wikipedia.org/wiki/Glicko_rating_system)
//! - [Original Paper by Mark Glickman](http://www.glicko.net/glicko/glicko.pdf)
//! - [Glicko Calculator](http://www.bjcox.com/?page_id=2)

#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};

use crate::{
    glicko2::Glicko2Rating, glicko_boost::GlickoBoostRating, sticko::StickoRating, Outcomes,
    Rating, RatingPeriodSystem, RatingSystem,
};
use std::f64::consts::PI;

#[derive(Copy, Clone, Debug, PartialEq)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
/// The Glicko rating for a player.
///
/// For the Glicko-2 rating, please see [`Glicko2Rating`].
///
/// The default rating is 1500.0.\
/// The default deviation is 350.0.
pub struct GlickoRating {
    /// The player's Glicko rating number, by default 1500.0.
    pub rating: f64,
    /// The player's Glicko deviation number, by default 350.0.
    pub deviation: f64,
}

impl GlickoRating {
    #[must_use]
    /// Initialise a new `GlickoRating` with a rating of 1500.0 and a deviation of 350.0.
    pub const fn new() -> Self {
        Self {
            rating: 1500.0,
            deviation: 350.0,
        }
    }
}

impl Default for GlickoRating {
    fn default() -> Self {
        Self::new()
    }
}

impl Rating for GlickoRating {
    fn rating(&self) -> f64 {
        self.rating
    }
    fn uncertainty(&self) -> Option<f64> {
        Some(self.deviation)
    }
    fn new(rating: Option<f64>, uncertainty: Option<f64>) -> Self {
        Self {
            rating: rating.unwrap_or(1500.0),
            deviation: uncertainty.unwrap_or(350.0),
        }
    }
}

impl From<(f64, f64)> for GlickoRating {
    fn from((r, d): (f64, f64)) -> Self {
        Self {
            rating: r,
            deviation: d,
        }
    }
}

impl From<Glicko2Rating> for GlickoRating {
    fn from(g: Glicko2Rating) -> Self {
        Self {
            rating: g.rating,
            deviation: g.deviation,
        }
    }
}

impl From<GlickoBoostRating> for GlickoRating {
    fn from(g: GlickoBoostRating) -> Self {
        Self {
            rating: g.rating,
            deviation: g.deviation,
        }
    }
}

impl From<StickoRating> for GlickoRating {
    fn from(s: StickoRating) -> Self {
        Self {
            rating: s.rating,
            deviation: s.deviation,
        }
    }
}

#[derive(Clone, Copy, Debug)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
/// Constants used in the Glicko calculations.
pub struct GlickoConfig {
    /// The c value describes how much the rating deviation should decay in each step.
    /// The higher the value, the more the rating deviation will decay.\
    /// In [the paper](http://www.glicko.net/glicko/glicko.pdf) a value of
    /// `63.2` seems to be a suggested value, so that is the default here.
    pub c: f64,
}

impl GlickoConfig {
    #[must_use]
    /// Initialise a new `GlickoConfig` with a c value of `63.2`
    pub const fn new() -> Self {
        Self { c: 63.2 }
    }
}

impl Default for GlickoConfig {
    fn default() -> Self {
        Self::new()
    }
}

/// Struct to calculate ratings and expected score for [`GlickoRating`]
pub struct Glicko {
    config: GlickoConfig,
}

impl RatingSystem for Glicko {
    type RATING = GlickoRating;
    type CONFIG = GlickoConfig;

    fn new(config: Self::CONFIG) -> Self {
        Self { config }
    }

    fn rate(
        &self,
        player_one: &GlickoRating,
        player_two: &GlickoRating,
        outcome: &Outcomes,
    ) -> (GlickoRating, GlickoRating) {
        glicko(player_one, player_two, outcome, &self.config)
    }

    fn expected_score(&self, player_one: &GlickoRating, player_two: &GlickoRating) -> (f64, f64) {
        expected_score(player_one, player_two)
    }
}

impl RatingPeriodSystem for Glicko {
    type RATING = GlickoRating;
    type CONFIG = GlickoConfig;

    fn new(config: Self::CONFIG) -> Self {
        Self { config }
    }

    fn rate(&self, player: &GlickoRating, results: &[(GlickoRating, Outcomes)]) -> GlickoRating {
        glicko_rating_period(player, results, &self.config)
    }

    fn expected_score(&self, player: &Self::RATING, opponents: &[Self::RATING]) -> Vec<f64> {
        expected_score_rating_period(player, opponents)
    }
}

#[must_use]
/// Calculates the [`GlickoRating`]s of two players based on their old ratings, deviations, and the outcome of the game.
///
/// Please see [`Glicko-2`](crate::glicko2) for calculating with the improved version.
///
/// Takes in two players as [`GlickoRating`]s, and an [`Outcome`](Outcomes).
///
/// Instead of the traditional way of calculating the Glicko for only one player only using a list of results,
/// we are calculating the Glicko rating for two players at once, like in the Elo calculation,
/// to make it easier to see instant results.
///
/// For the traditional way of calculating a Glicko rating please see [`glicko_rating_period`].
///
/// The outcome of the match is in the perspective of `player_one`.
/// This means [`Outcomes::WIN`] is a win for `player_one` and [`Outcomes::LOSS`] is a win for `player_two`.
///
/// # Examples
/// ```
/// use skillratings::{
///     glicko::{glicko, GlickoConfig, GlickoRating},
///     Outcomes,
/// };
///
/// let player_one = GlickoRating {
///     rating: 1500.0,
///     deviation: 350.0,
/// };
/// let player_two = GlickoRating {
///     rating: 1500.0,
///     deviation: 350.0,
/// };
///
/// let outcome = Outcomes::WIN;
///
/// let config = GlickoConfig::new();
///
/// let (new_one, new_two) = glicko(&player_one, &player_two, &outcome, &config);
///
/// assert!((new_one.rating.round() - 1662.0).abs() < f64::EPSILON);
/// assert!((new_one.deviation.round() - 290.0).abs() < f64::EPSILON);
///
/// assert!((new_two.rating.round() - 1338.0).abs() < f64::EPSILON);
/// assert!((new_two.deviation.round() - 290.0).abs() < f64::EPSILON);
/// ```
pub fn glicko(
    player_one: &GlickoRating,
    player_two: &GlickoRating,
    outcome: &Outcomes,
    config: &GlickoConfig,
) -> (GlickoRating, GlickoRating) {
    let q = 10_f64.ln() / 400.0;

    let outcome1 = outcome.to_chess_points();
    let outcome2 = 1.0 - outcome1;

    let g1 = g_value(q, player_two.deviation);
    let g2 = g_value(q, player_one.deviation);

    let e1 = e_value(g1, player_one.rating, player_two.rating);
    let e2 = e_value(g2, player_two.rating, player_one.rating);

    let d1 = d_value(q, g1, e1);
    let d2 = d_value(q, g2, e2);

    let player_one_pre_deviation = player_one.deviation.hypot(config.c).min(350.0);
    let player_two_pre_deviation = player_two.deviation.hypot(config.c).min(350.0);

    let player_one_new_rating = new_rating(
        player_one.rating,
        player_one_pre_deviation,
        outcome1,
        q,
        g1,
        e1,
        d1,
    );
    let player_two_new_rating = new_rating(
        player_two.rating,
        player_two_pre_deviation,
        outcome2,
        q,
        g2,
        e2,
        d2,
    );

    let player_one_new_deviation = new_deviation(player_one_pre_deviation, d1);
    let player_two_new_deviation = new_deviation(player_two_pre_deviation, d2);

    (
        GlickoRating {
            rating: player_one_new_rating,
            deviation: player_one_new_deviation,
        },
        GlickoRating {
            rating: player_two_new_rating,
            deviation: player_two_new_deviation,
        },
    )
}

#[must_use]
/// The "traditional" way of calculating a [`GlickoRating`] of a player in a rating period.
///
/// Note that in this case, all of the matches are considered to be played at once.\
/// This means that the player will not get updated in-between matches, as you might expect.\
/// This will result in *slightly* different results than if you were to use the [`glicko`] function in a loop.
///
/// Takes in a player as an [`GlickoRating`] and their results as a Slice of tuples containing the opponent as an [`GlickoRating`],
/// the outcome of the game as an [`Outcome`](Outcomes) and a [`GlickoConfig`].
///
/// The outcome of the match is in the perspective of the player.
/// This means [`Outcomes::WIN`] is a win for the player and [`Outcomes::LOSS`] is a win for the opponent.
///
/// If the player's results are empty, the player's rating deviation will automatically be decayed using [`decay_deviation`].
///
/// # Examples
/// ```
/// use skillratings::{
///     glicko::{glicko_rating_period, GlickoConfig, GlickoRating},
///     Outcomes,
/// };
///
/// let player = GlickoRating {
///     rating: 1500.0,
///     deviation: 200.0,
/// };
///
/// let opponent1 = GlickoRating {
///     rating: 1400.0,
///     deviation: 30.0,
/// };
///
/// let opponent2 = GlickoRating {
///     rating: 1550.0,
///     deviation: 100.0,
/// };
///
/// let opponent3 = GlickoRating {
///     rating: 1700.0,
///     deviation: 300.0,
/// };
///
/// let results = vec![
///     (opponent1, Outcomes::WIN),
///     (opponent2, Outcomes::LOSS),
///     (opponent3, Outcomes::LOSS),
/// ];
///
/// let config = GlickoConfig::new();
///
/// let new_player = glicko_rating_period(&player, &results, &config);
///
/// assert!((new_player.rating.round() - 1462.0).abs() < f64::EPSILON);
/// assert!((new_player.deviation.round() - 155.0).abs() < f64::EPSILON);
/// ```
pub fn glicko_rating_period(
    player: &GlickoRating,
    results: &[(GlickoRating, Outcomes)],
    config: &GlickoConfig,
) -> GlickoRating {
    let q = 10_f64.ln() / 400.0;

    if results.is_empty() {
        return decay_deviation(player, config);
    }

    let d_sq = (q.powi(2)
        * results
            .iter()
            .map(|r| {
                let g = g_value(q, r.0.deviation);

                let e = e_value(g, player.rating, r.0.rating);

                g.powi(2) * e * (1.0 - e)
            })
            .sum::<f64>())
    .recip();

    let m = results
        .iter()
        .map(|r| {
            let g = g_value(q, r.0.deviation);

            let e = e_value(g, player.rating, r.0.rating);

            let s = r.1.to_chess_points();

            g * (s - e)
        })
        .sum();

    let pre_deviation = player.deviation.hypot(config.c).min(350.0);
    let new_rating = (q / (pre_deviation.powi(2).recip() + d_sq.recip())).mul_add(m, player.rating);
    let new_deviation = (pre_deviation.powi(2).recip() + d_sq.recip())
        .recip()
        .sqrt();

    GlickoRating {
        rating: new_rating,
        deviation: new_deviation,
    }
}

#[must_use]
/// Calculates the expected outcome of two players based on glicko.
///
/// Takes in two players as [`GlickoRating`]s and returns the probability of victory for each player as an [`f64`] between 1.0 and 0.0.\
/// 1.0 means a certain victory for the player, 0.0 means certain loss.
/// Values near 0.5 mean a draw is likely to occur.
///
/// # Examples
/// ```
/// use skillratings::glicko::{expected_score, GlickoRating};
///
/// let player_one = GlickoRating {
///     rating: 2500.0,
///     deviation: 41.0,
/// };
/// let player_two = GlickoRating {
///     rating: 1950.0,
///     deviation: 320.0,
/// };
/// let (exp_one, exp_two) = expected_score(&player_one, &player_two);
/// assert!(((exp_one * 100.0).round() - 90.0).abs() < f64::EPSILON);
/// assert!(((exp_two * 100.0).round() - 10.0).abs() < f64::EPSILON);
/// ```
pub fn expected_score(player_one: &GlickoRating, player_two: &GlickoRating) -> (f64, f64) {
    let q = 10_f64.ln() / 400.0;
    let g = g_value(q, player_one.deviation.hypot(player_two.deviation));

    let exp_one = (1.0 + 10_f64.powf(-g * (player_one.rating - player_two.rating) / 400.0)).recip();
    let exp_two = 1.0 - exp_one;

    (exp_one, exp_two)
}

#[must_use]
/// Calculates the expected outcome of a player in a rating period or tournament.
///
/// Takes in a players as [`GlickoRating`] and a list of opponents as a slice of [`GlickoRating`]
/// and returns the probability of victory for each match as an Vec of [`f64`] between 1.0 and 0.0 from the perspective of the player.\
/// 1.0 means a certain victory for the player, 0.0 means certain loss.
/// Values near 0.5 mean a draw is likely to occur.
///
/// # Examples
/// ```
/// use skillratings::glicko::{expected_score_rating_period, GlickoRating};
///
/// let player = GlickoRating {
///     rating: 1900.0,
///     deviation: 120.0,
/// };
///
/// let opponent1 = GlickoRating {
///     rating: 1930.0,
///     deviation: 120.0,
/// };
///
/// let opponent2 = GlickoRating {
///     rating: 1730.0,
///     deviation: 120.0,
/// };
///
/// let exp = expected_score_rating_period(&player, &[opponent1, opponent2]);
///
/// assert_eq!((exp[0] * 100.0).round(), 46.0);
/// assert_eq!((exp[1] * 100.0).round(), 70.0);
/// ```
pub fn expected_score_rating_period(player: &GlickoRating, opponents: &[GlickoRating]) -> Vec<f64> {
    opponents
        .iter()
        .map(|o| {
            let q = 10_f64.ln() / 400.0;
            let g = g_value(q, player.deviation.hypot(o.deviation));

            (1.0 + 10_f64.powf(-g * (player.rating - o.rating) / 400.0)).recip()
        })
        .collect()
}

#[must_use]
/// Decays a Rating Deviation Value for a player, if they missed playing in a certain rating period.
///
/// The length of the rating period and thus the number of missed periods per player is something to decide and track yourself.
///
/// Takes in a player as a [`GlickoRating`] and a [`GlickoConfig`], that describes how much the rating should change, and returns the decayed [`GlickoRating`].
///
/// # Examples
/// ```
/// use skillratings::glicko::{decay_deviation, GlickoConfig, GlickoRating};
///
/// let player_one = GlickoRating {
///     rating: 2720.0,
///     deviation: 41.3,
/// };
///
/// let config = GlickoConfig::new();
///
/// let player_one_decay = decay_deviation(&player_one, &config);
///
/// assert!((player_one_decay.deviation.round() - 75.0).abs() < f64::EPSILON);
/// ```
pub fn decay_deviation(player: &GlickoRating, config: &GlickoConfig) -> GlickoRating {
    let new_player_deviation = player.deviation.hypot(config.c).min(350.0);

    GlickoRating {
        rating: player.rating,
        deviation: new_player_deviation,
    }
}

#[must_use]
/// The 95% confidence interval of the lowest to highest rating.
///
/// The system is 95% sure that the "true skill" of the player is in-between these values.
///
/// Takes in a player as a [`GlickoRating`] and returns two [`f64`]s that describe the lowest and highest rating.
///
/// # Examples
/// ```
/// use skillratings::glicko::{confidence_interval, GlickoRating};
///
/// let player = GlickoRating {
///     rating: 2250.0,
///     deviation: 79.0,
/// };
///
/// let (interval_low, interval_high) = confidence_interval(&player);
///
/// assert!(interval_low.round() - 2095.0 < f64::EPSILON);
/// assert!(interval_high.round() - 2405.0 < f64::EPSILON);
/// ```
pub fn confidence_interval(player: &GlickoRating) -> (f64, f64) {
    (
        1.96f64.mul_add(-player.deviation, player.rating),
        1.96f64.mul_add(player.deviation, player.rating),
    )
}

fn new_deviation(pre_deviation: f64, d: f64) -> f64 {
    (pre_deviation.powi(2).recip() + d.recip()).recip().sqrt()
}

fn new_rating(
    old_rating: f64,
    pre_deviation: f64,
    score: f64,
    q: f64,
    g: f64,
    e: f64,
    d: f64,
) -> f64 {
    ((q / (pre_deviation.powi(2).recip() + d.recip())) * g).mul_add(score - e, old_rating)
}

fn g_value(q: f64, opponent_deviation: f64) -> f64 {
    (1.0 + ((3.0 * q.powi(2) * opponent_deviation.powi(2)) / (PI.powi(2))))
        .sqrt()
        .recip()
}

fn e_value(g: f64, rating: f64, opponent_rating: f64) -> f64 {
    (1.0 + (10_f64.powf(-g * (rating - opponent_rating) / 400.0))).recip()
}

fn d_value(q: f64, g: f64, e: f64) -> f64 {
    (q.powi(2) * g.powi(2) * e * (1.0 - e)).powi(-1)
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_glicko() {
        let player1 = GlickoRating {
            rating: 1500.0,
            deviation: 200.0,
        };

        let opponent1 = GlickoRating {
            rating: 1400.0,
            deviation: 30.0,
        };

        let opponent2 = GlickoRating {
            rating: 1550.0,
            deviation: 100.0,
        };

        let opponent3 = GlickoRating {
            rating: 1700.0,
            deviation: 300.0,
        };

        let config = GlickoConfig::default();

        let (player1, _) = glicko(&player1, &opponent1, &Outcomes::WIN, &config);

        let (player1, _) = glicko(&player1, &opponent2, &Outcomes::LOSS, &config);

        let (player1, _) = glicko(&player1, &opponent3, &Outcomes::LOSS, &config);

        assert!((player1.rating.round() - 1449.0).abs() < f64::EPSILON);
        assert!((player1.deviation - 171.684_472_141_285_57).abs() < f64::EPSILON);
    }

    #[test]
    /// This test is taken directly from the official glicko example.\
    /// <http://www.glicko.net/glicko/glicko.pdf>
    /// The result will be slightly different from above,
    /// because the games in a rating period are considered to be played at the same time.
    fn test_glicko_rating_period() {
        // This weird deviation compensates for official example
        // not performing calculations from step 1.
        let player = GlickoRating {
            rating: 1500.0,
            deviation: 189.751_837_935_762_84,
        };

        let opponent1 = GlickoRating {
            rating: 1400.0,
            deviation: 30.0,
        };

        let opponent2 = GlickoRating {
            rating: 1550.0,
            deviation: 100.0,
        };

        let opponent3 = GlickoRating {
            rating: 1700.0,
            deviation: 300.0,
        };

        let results = vec![
            (opponent1, Outcomes::WIN),
            (opponent2, Outcomes::LOSS),
            (opponent3, Outcomes::LOSS),
        ];

        let new_player = glicko_rating_period(&player, &results, &GlickoConfig::new());

        assert!((new_player.rating.round() - 1464.0).abs() < f64::EPSILON);
        assert!((new_player.deviation - 151.398_902_447_969_33).abs() < f64::EPSILON);

        let player = GlickoRating {
            rating: 1500.0,
            deviation: 50.0,
        };

        let results: Vec<(GlickoRating, Outcomes)> = Vec::new();

        let new_player = glicko_rating_period(&player, &results, &GlickoConfig::new());

        assert!((new_player.deviation - 80.586_847_562_117_73).abs() < f64::EPSILON);
    }

    #[test]
    fn test_single_rp() {
        let player = GlickoRating {
            rating: 1200.0,
            deviation: 25.0,
        };
        let opponent = GlickoRating {
            rating: 1500.0,
            deviation: 34.0,
        };

        let config = GlickoConfig::new();

        let (np, _) = glicko(&player, &opponent, &Outcomes::WIN, &config);

        let rp = glicko_rating_period(&player, &[(opponent, Outcomes::WIN)], &config);

        assert_eq!(rp, np);
    }

    #[test]
    /// This test is taken directly from the official glicko example.\
    /// <http://www.glicko.net/glicko/glicko.pdf>
    fn test_expected_score() {
        let player_one = GlickoRating {
            rating: 1400.0,
            deviation: 40.0,
        };

        let player_two = GlickoRating {
            rating: 1500.0,
            deviation: 150.0,
        };

        let (exp_one, exp_two) = expected_score(&player_one, &player_two);

        assert!((exp_one - 0.373_700_405_951_935).abs() < f64::EPSILON);
        assert!((exp_two - 0.626_299_594_048_065).abs() < f64::EPSILON);
        assert!((exp_one + exp_two - 1.0).abs() < f64::EPSILON);
    }

    #[test]
    /// This test is taken directly from the official glicko example.\
    /// <http://www.glicko.net/glicko/glicko.pdf>
    fn test_confidence_interval() {
        let player = GlickoRating {
            rating: 1500.0,
            deviation: 30.0,
        };

        let ci = confidence_interval(&player);

        assert!((ci.0.round() - 1441.0).abs() < f64::EPSILON);
        assert!((ci.1.round() - 1559.0).abs() < f64::EPSILON);
    }

    #[test]
    /// This test is taken directly from the official glicko example.\
    /// <http://www.glicko.net/glicko/glicko.pdf>
    fn test_decay_deviation() {
        let player = GlickoRating {
            rating: 1500.0,
            deviation: 50.0,
        };

        let mut player = decay_deviation(&player, &GlickoConfig::new());

        assert!((player.deviation - 80.586_847_562_117_73).abs() < f64::EPSILON);

        for _ in 0..29 {
            player = decay_deviation(&player, &GlickoConfig::default());
        }

        assert!(((player.deviation * 1000.0).round() - 349_753.0).abs() < f64::EPSILON);

        player = decay_deviation(&player, &GlickoConfig::new());

        assert!((player.deviation - 350.0).abs() < f64::EPSILON);
    }

    #[test]
    fn test_unequal_draws() {
        let mut player = GlickoRating::new();

        let mut opponent = GlickoRating {
            rating: 2230.0,
            deviation: 41.0,
        };

        (player, opponent) = glicko(
            &player,
            &opponent,
            &Outcomes::DRAW,
            &GlickoConfig::default(),
        );

        assert!((player.rating.round() - 1820.0).abs() < f64::EPSILON);
        assert!((player.deviation.round() - 340.0).abs() < f64::EPSILON);

        assert!((opponent.rating.round() - 2220.0).abs() < f64::EPSILON);
        assert!((opponent.deviation.round() - 75.0).abs() < f64::EPSILON);
    }

    #[test]
    #[allow(clippy::clone_on_copy)]
    fn test_misc_stuff() {
        let player_new = GlickoRating::new();
        let player_default = GlickoRating::default();

        assert!((player_new.rating - player_default.rating).abs() < f64::EPSILON);
        assert!((player_new.deviation - player_new.deviation).abs() < f64::EPSILON);

        let player_one = GlickoRating::new();
        let config = GlickoConfig::new();

        assert_eq!(player_one, player_one.clone());
        assert!((config.c - config.clone().c).abs() < f64::EPSILON);

        assert!(!format!("{player_one:?}").is_empty());
        assert!(!format!("{config:?}").is_empty());

        assert_eq!(player_one, GlickoRating::from((1500.0, 350.0)));
    }

    #[test]
    fn test_traits() {
        let player_one: GlickoRating = Rating::new(Some(240.0), Some(90.0));
        let player_two: GlickoRating = Rating::new(Some(240.0), Some(90.0));

        let rating_system: Glicko = RatingSystem::new(GlickoConfig::new());

        assert!((player_one.rating() - 240.0).abs() < f64::EPSILON);
        assert_eq!(player_one.uncertainty(), Some(90.0));

        let (new_player_one, new_player_two) =
            RatingSystem::rate(&rating_system, &player_one, &player_two, &Outcomes::WIN);

        let (exp1, exp2) = RatingSystem::expected_score(&rating_system, &player_one, &player_two);

        assert!((new_player_one.rating - 270.633_674_957_731_9).abs() < f64::EPSILON);
        assert!((new_player_two.rating - 209.366_325_042_268_1).abs() < f64::EPSILON);
        assert!((exp1 - 0.5).abs() < f64::EPSILON);
        assert!((exp2 - 0.5).abs() < f64::EPSILON);

        let rating_period_system: Glicko = RatingPeriodSystem::new(GlickoConfig::new());
        let exp_rp =
            RatingPeriodSystem::expected_score(&rating_period_system, &player_one, &[player_two]);
        assert!((exp1 - exp_rp[0]).abs() < f64::EPSILON);

        let player_one: GlickoRating = Rating::new(Some(240.0), Some(90.0));
        let player_two: GlickoRating = Rating::new(Some(240.0), Some(90.0));

        let rating_period: Glicko = RatingPeriodSystem::new(GlickoConfig::new());

        let new_player_one =
            RatingPeriodSystem::rate(&rating_period, &player_one, &[(player_two, Outcomes::WIN)]);

        assert!((new_player_one.rating - 270.633_674_957_731_9).abs() < f64::EPSILON);
    }
}