use ggplot_rs::data::DataFrame;
use ggplot_rs::prelude::*;
use ggplot_rs::scale::scale_set::ScaleSet;
use ggplot_rs::stat::Stat;
#[test]
fn qq_first_theoretical_matches_r_for_large_n() {
let mut df = DataFrame::new();
df.add_column(
"y".into(),
(0..100).map(|i| Value::Float(i as f64)).collect(),
);
let d = ggplot_rs::stat::qq::StatQQ.compute_group(&df, &ScaleSet::new());
let min_theo = d
.column("x")
.unwrap()
.iter()
.filter_map(|v| v.as_f64())
.fold(f64::INFINITY, f64::min);
assert!(
(min_theo - (-2.5758)).abs() < 2e-3,
"got {min_theo}, expected ~-2.5758"
);
}