nautilus_analysis/statistics/
winner_min.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2025 Nautech Systems Pty Ltd. All rights reserved.
3//  https://nautechsystems.io
4//
5//  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
6//  You may not use this file except in compliance with the License.
7//  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
8//
9//  Unless required by applicable law or agreed to in writing, software
10//  distributed under the License is distributed on an "AS IS" BASIS,
11//  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12//  See the License for the specific language governing permissions and
13//  limitations under the License.
14// -------------------------------------------------------------------------------------------------
15
16use crate::statistic::PortfolioStatistic;
17
18#[repr(C)]
19#[derive(Debug)]
20#[cfg_attr(
21    feature = "python",
22    pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.analysis")
23)]
24pub struct MinWinner {}
25
26impl PortfolioStatistic for MinWinner {
27    type Item = f64;
28
29    fn name(&self) -> String {
30        stringify!(MinWinner).to_string()
31    }
32
33    fn calculate_from_realized_pnls(&self, realized_pnls: &[f64]) -> Option<Self::Item> {
34        if realized_pnls.is_empty() {
35            return Some(0.0);
36        }
37
38        realized_pnls
39            .iter()
40            .filter(|&&pnl| pnl > 0.0)
41            .min_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
42            .copied()
43    }
44}
45
46#[cfg(test)]
47mod tests {
48    use super::*;
49
50    #[test]
51    fn test_empty_pnls() {
52        let min_winner = MinWinner {};
53        let result = min_winner.calculate_from_realized_pnls(&[]);
54        assert!(result.is_some());
55        assert_eq!(result.unwrap(), 0.0);
56    }
57
58    #[test]
59    fn test_no_winning_trades() {
60        let min_winner = MinWinner {};
61        let realized_pnls = vec![-100.0, -50.0, -200.0];
62        let result = min_winner.calculate_from_realized_pnls(&realized_pnls);
63        assert!(result.is_none());
64    }
65
66    #[test]
67    fn test_all_winning_trades() {
68        let min_winner = MinWinner {};
69        let realized_pnls = vec![100.0, 50.0, 200.0];
70        let result = min_winner.calculate_from_realized_pnls(&realized_pnls);
71        assert!(result.is_some());
72        assert_eq!(result.unwrap(), 50.0); // Minimum of 100.0, 50.0, and 200.0 is 50.0
73    }
74
75    #[test]
76    fn test_mixed_trades() {
77        let min_winner = MinWinner {};
78        let realized_pnls = vec![100.0, -50.0, 200.0, -100.0];
79        let result = min_winner.calculate_from_realized_pnls(&realized_pnls);
80        assert!(result.is_some());
81        assert_eq!(result.unwrap(), 100.0); // Minimum of 100.0 and 200.0 is 100.0
82    }
83
84    #[test]
85    fn test_single_winning_trade() {
86        let min_winner = MinWinner {};
87        let realized_pnls = vec![50.0];
88        let result = min_winner.calculate_from_realized_pnls(&realized_pnls);
89        assert!(result.is_some());
90        assert_eq!(result.unwrap(), 50.0);
91    }
92
93    #[test]
94    fn test_name() {
95        let min_winner = MinWinner {};
96        assert_eq!(min_winner.name(), "MinWinner");
97    }
98}
nautilus_analysis/statistics/winner_min.rs

nautilus_analysis/statistics/
winner_min.rs
