nautilus_analysis/statistics/
winner_max.rsuse crate::statistic::PortfolioStatistic;
#[repr(C)]
#[derive(Debug)]
#[cfg_attr(
feature = "python",
pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis")
)]
pub struct MaxWinner {}
impl PortfolioStatistic for MaxWinner {
type Item = f64;
fn name(&self) -> String {
stringify!(MaxWinner).to_string()
}
fn calculate_from_realized_pnls(&self, realized_pnls: &[f64]) -> Option<Self::Item> {
if realized_pnls.is_empty() {
return Some(0.0);
}
realized_pnls
.iter()
.copied()
.filter(|&pnl| pnl > 0.0)
.max_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_empty_pnls() {
let max_winner = MaxWinner {};
let result = max_winner.calculate_from_realized_pnls(&[]);
assert!(result.is_some());
assert_eq!(result.unwrap(), 0.0);
}
#[test]
fn test_no_winning_trades() {
let max_winner = MaxWinner {};
let realized_pnls = vec![-100.0, -50.0, -200.0];
let result = max_winner.calculate_from_realized_pnls(&realized_pnls);
assert!(result.is_none());
}
#[test]
fn test_all_winning_trades() {
let max_winner = MaxWinner {};
let realized_pnls = vec![100.0, 50.0, 200.0];
let result = max_winner.calculate_from_realized_pnls(&realized_pnls);
assert!(result.is_some());
assert_eq!(result.unwrap(), 200.0);
}
#[test]
fn test_mixed_trades() {
let max_winner = MaxWinner {};
let realized_pnls = vec![100.0, -50.0, 200.0, -100.0];
let result = max_winner.calculate_from_realized_pnls(&realized_pnls);
assert!(result.is_some());
assert_eq!(result.unwrap(), 200.0);
}
#[test]
fn test_name() {
let max_winner = MaxWinner {};
assert_eq!(max_winner.name(), "MaxWinner");
}
}