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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::tail_ratio::TailRatio};
#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl TailRatio {
/// Calculates the tail ratio of portfolio returns.
///
/// The tail ratio compares the magnitude of the right (gain) tail to the left
/// (loss) tail of the return distribution. It is the absolute ratio of the 95th
/// to the 5th percentile of returns:
///
/// `TailRatio = | percentile(r, 95) / percentile(r, 5) |`
///
/// Percentiles use linear interpolation between closest ranks, matching
/// `numpy.percentile` and `pandas.Series.quantile` with the default `linear`
/// method (the convention used by the `quantstats` tail-ratio definition).
///
/// A value greater than `1` indicates a heavier upside tail (gains larger in
/// magnitude than losses); a value below `1` indicates a heavier downside tail.
/// Returns `NaN` for fewer than two returns or when the 5th percentile is zero.
///
/// # References
///
/// - empyrical `tail_ratio` (<https://github.com/quantopian/empyrical>).
#[new]
fn py_new() -> Self {
Self::new()
}
fn __repr__(&self) -> String {
self.name()
}
#[getter]
#[pyo3(name = "name")]
fn py_name(&self) -> String {
self.name()
}
#[pyo3(name = "calculate_from_returns")]
#[expect(clippy::needless_pass_by_value)]
fn py_calculate_from_returns(&mut self, raw_returns: BTreeMap<u64, f64>) -> Option<f64> {
self.calculate_from_returns(&transform_returns(&raw_returns))
}
#[pyo3(name = "calculate_from_realized_pnls")]
fn py_calculate_from_realized_pnls(&mut self, _realized_pnls: Vec<f64>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_positions")]
fn py_calculate_from_positions(&mut self, _positions: Vec<Py<PyAny>>) -> Option<f64> {
None
}
}