208 lines
5.0 KiB
Rust
208 lines
5.0 KiB
Rust
use std::collections::HashMap;
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use time::Date;
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use trueskill_tt::{History, BETA, MU, P_DRAW};
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fn main() {
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let mut csv = csv::Reader::open("examples/atp.csv").unwrap();
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let mut composition = Vec::new();
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let mut results = Vec::new();
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let mut times = Vec::new();
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let time_format = time::format_description::parse("[year]-[month]-[day]").unwrap();
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for row in csv.records() {
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if &row["double"] == "t" {
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composition.push(vec![
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vec![row["w1_id"].to_string(), row["w2_id"].to_string()],
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vec![row["l1_id"].to_string(), row["l2_id"].to_string()],
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]);
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} else {
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composition.push(vec![
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vec![row["w1_id"].to_string()],
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vec![row["l1_id"].to_string()],
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]);
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}
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results.push(vec![1, 0]);
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let time = Date::parse(&row["time_start"], &time_format)
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.unwrap()
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.midnight()
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.assume_utc()
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.unix_timestamp();
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times.push(time as f64 / (60 * 60 * 24) as f64);
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}
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let mut h = History::new(
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composition,
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results,
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times,
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HashMap::new(),
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MU,
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1.6,
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BETA,
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0.036,
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P_DRAW,
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);
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h.epsilon = 0.01;
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h.iterations = 10;
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h.convergence();
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/*
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composition,
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results,
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times,
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priors,
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MU,
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BETA,
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SIGMA,
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GAMMA,
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P_DRAW,
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*/
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/*
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let mut priors = HashMap::new();
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for k in ["aj", "bj", "cj"] {
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let player = Player::new(
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Gaussian::new(25.0, 25.0 / 3.0),
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25.0 / 6.0,
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0.15 * 25.0 / 3.0,
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N_INF,
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);
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priors.insert(k.to_string(), player);
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}
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let mut h1 = History::new(
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composition,
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results,
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times,
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priors,
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MU,
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BETA,
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SIGMA,
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GAMMA,
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P_DRAW,
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);
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*/
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/*
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let columns = data
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.lines()
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.skip(1)
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.map(|line| {
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let columns = line.split(',').collect::<Vec<_>>();
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Column {
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w1_id: columns[3],
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w2_id: columns[3],
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l1_id: columns[3],
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l2_id: columns[3],
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double: columns[3],
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}
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})
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.collect::<Vec<_>>();
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*/
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// match_id,double,round_number,w1_id,w1_name,w2_id,w2_name,l1_id,l1_name,l2_id,l2_name,time_start,time_end,ground,tour_id,tour_name
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// 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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/*
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import pandas as pd
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#sudo pip3 install trueskillthroughtime
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from trueskillthroughtime import *
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import time
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from datetime import datetime
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# Data
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df = pd.read_csv('input/history.csv', low_memory=False)
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columns = zip(df.w1_id, df.w2_id, df.l1_id, df.l2_id, df.double)
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composition = [[[w1,w2],[l1,l2]] if d == 't' else [[w1],[l1]] for w1, w2, l1, l2, d in columns ]
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times = [ datetime.strptime(t, "%Y-%m-%d").timestamp()/(60*60*24) for t in df.time_start]
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#start = time.time()
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h = History(composition = composition, times = times, sigma = 1.6, gamma = 0.036)
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h.convergence(epsilon=0.01, iterations=10)
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#end = time.time()
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#print(end-start)
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*/
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}
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mod csv {
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use std::fs::File;
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use std::io::{self, BufRead, BufReader, Lines};
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use std::ops;
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use std::path::Path;
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pub struct Reader {
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header_map: Vec<String>,
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lines: Lines<BufReader<File>>,
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}
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impl Reader {
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pub fn open<P: AsRef<Path>>(path: P) -> Result<Self, io::Error> {
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let mut lines = File::open(path).map(BufReader::new)?.lines();
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let header_map = if let Some(header) = lines.next() {
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let header = header?;
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header.split(',').map(Into::into).collect::<Vec<_>>()
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} else {
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Vec::new()
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};
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Ok(Self { header_map, lines })
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}
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pub fn records(&mut self) -> Records<'_> {
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Records {
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header_map: &self.header_map,
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lines: &mut self.lines,
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}
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}
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}
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pub struct Records<'a> {
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header_map: &'a Vec<String>,
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lines: &'a mut Lines<BufReader<File>>,
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}
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impl<'a> Iterator for Records<'a> {
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type Item = Record<'a>;
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fn next(&mut self) -> Option<Self::Item> {
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let line = self.lines.next()?;
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Some(Record {
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header_map: self.header_map,
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columns: line.unwrap().split(',').map(Into::into).collect::<Vec<_>>(),
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})
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}
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}
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pub struct Record<'a> {
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header_map: &'a Vec<String>,
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columns: Vec<String>,
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}
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impl<'a> ops::Index<&str> for Record<'a> {
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type Output = str;
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fn index(&self, index: &str) -> &Self::Output {
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&self.columns[self
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.header_map
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.iter()
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.position(|header| header == index)
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.unwrap()]
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}
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}
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}
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