use dcfr::{
    kuhn::{History, Kuhn},
    lcfr::{expected_value, TabularLcfr},
};
use indicatif::ProgressIterator;
use itertools::Itertools;
use rand::SeedableRng;
use rand_pcg::Pcg64Mcg;
fn main() {
    let game = Kuhn::<2>::new();
    let mut cfr_trainer = TabularLcfr::new();
    let mut rng = Pcg64Mcg::seed_from_u64(4);
    for _ in (0..100000).progress() {
        cfr_trainer.single_iter(&game, &mut rng);
    }
    for ((p, info_set), ss) in &cfr_trainer.strategy_sum {
        let sum: f32 = ss.iter().sum();
        let (s1, s2) = ss.iter().map(|s| s / sum).collect_tuple().unwrap();
        let info_set_str = info_set
            .iter()
            .flatten()
            .map(History::concise_repr)
            .join(" ");
        println!("{s1:.4} {s2:.4} {p:.2} [{info_set_str}]");
    }
    println!(
        "evs = {:?}",
        expected_value(
            game,
            &|player, infoset| {
                let strat = &cfr_trainer.strategy_sum[&(player, infoset.clone())];
                let s_sum: f32 = strat.iter().sum();
                strat.iter().map(|s| s / s_sum).collect()
            },
            &mut rng
        )
    );
}