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// -------------------------------------------------------------------------------------------------
// Copyright (C) 2015-2026 Nautech Systems Pty Ltd. All rights reserved.
// https://nautechsystems.io
//
// Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
// You may not use this file except in compliance with the License.
// You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// -------------------------------------------------------------------------------------------------
use std::collections::BTreeMap;
use pyo3::prelude::*;
use super::transform_returns;
use crate::{statistic::PortfolioStatistic, statistics::up_capture_ratio::UpCaptureRatio};
#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl UpCaptureRatio {
/// Calculates the up capture ratio of portfolio returns relative to a benchmark.
///
/// The up capture ratio measures how the portfolio performed, on average, during the
/// periods when the benchmark return was positive. It is the ratio of the portfolio's
/// geometric annualized return to the benchmark's geometric annualized return, both
/// computed over the up-market subset only:
///
/// `UpCapture = annualized_return(portfolio | benchmark > 0) / annualized_return(benchmark | benchmark > 0)`
///
/// where each side's annualized return is the geometric (CAGR-style) value
/// `(prod(1 + x_i))^(period / m) - 1` and `m` is the number of up-market periods (the
/// size of the filtered subset, not the full aligned length). The period defaults to
/// 252 trading days. A value above 1.0 means the portfolio outperformed the benchmark
/// in up markets.
///
/// This is the `empyrical.up_capture` convention (geometric annualized-return ratio over
/// the `benchmark > 0` subset). Note that this differs from the Morningstar definition,
/// which uses a ratio of *cumulative* (non-annualized) returns; the two coincide only
/// when both subsets contain the same number of periods.
///
/// # References
///
/// - empyrical `up_capture` / `capture` / `annual_return`
/// (<https://github.com/quantopian/empyrical>).
/// - CFA Institute Investment Foundations, 3rd Edition
#[new]
#[pyo3(signature = (period=None))]
fn py_new(period: Option<usize>) -> Self {
Self::new(period)
}
fn __repr__(&self) -> String {
self.to_string()
}
#[getter]
#[pyo3(name = "name")]
fn py_name(&self) -> String {
self.name()
}
#[pyo3(name = "calculate_from_returns")]
fn py_calculate_from_returns(&self, _returns: BTreeMap<u64, f64>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_realized_pnls")]
fn py_calculate_from_realized_pnls(&self, _realized_pnls: Vec<f64>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_positions")]
fn py_calculate_from_positions(&self, _positions: Vec<Py<PyAny>>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_returns_with_benchmark")]
#[expect(clippy::needless_pass_by_value)]
fn py_calculate_from_returns_with_benchmark(
&self,
returns: BTreeMap<u64, f64>,
benchmark: BTreeMap<u64, f64>,
) -> Option<f64> {
self.calculate_from_returns_with_benchmark(
&transform_returns(&returns),
&transform_returns(&benchmark),
)
}
}