//! Performance attribution (thin PyO3 wrapper over ferro_ta_core::attribution). use numpy::{IntoPyArray, PyArray1, PyReadonlyArray1}; use pyo3::exceptions::PyValueError; use pyo3::prelude::*; use crate::validation; /// Compute trade-level statistics from trade PnL and hold durations. #[pyfunction] pub fn trade_stats( pnl: PyReadonlyArray1<'_, f64>, hold_bars: PyReadonlyArray1<'_, f64>, ) -> PyResult<(f64, f64, f64, f64, f64)> { let p = pnl.as_slice()?; let h = hold_bars.as_slice()?; let n = p.len(); if n == 0 { return Err(PyValueError::new_err("pnl must be non-empty")); } validation::validate_equal_length(&[(n, "pnl"), (h.len(), "hold_bars")])?; Ok(ferro_ta_core::attribution::trade_stats(p, h)) } /// Group per-bar returns by month index and sum each month's contribution. #[pyfunction] #[allow(clippy::type_complexity)] pub fn monthly_contribution<'py>( py: Python<'py>, bar_returns: PyReadonlyArray1<'py, f64>, month_index: PyReadonlyArray1<'py, i64>, ) -> PyResult<(Bound<'py, PyArray1>, Bound<'py, PyArray1>)> { let ret = bar_returns.as_slice()?; let mi = month_index.as_slice()?; let n = ret.len(); validation::validate_equal_length(&[(n, "bar_returns"), (mi.len(), "month_index")])?; let (months, contributions) = ferro_ta_core::attribution::monthly_contribution(ret, mi); Ok((months.into_pyarray(py), contributions.into_pyarray(py))) } /// Attribute per-bar returns to each signal label. #[pyfunction] #[allow(clippy::type_complexity)] pub fn signal_attribution<'py>( py: Python<'py>, bar_returns: PyReadonlyArray1<'py, f64>, signal_labels: PyReadonlyArray1<'py, i64>, ) -> PyResult<(Bound<'py, PyArray1>, Bound<'py, PyArray1>)> { let ret = bar_returns.as_slice()?; let lbl = signal_labels.as_slice()?; let n = ret.len(); validation::validate_equal_length(&[(n, "bar_returns"), (lbl.len(), "signal_labels")])?; let (labels, contributions) = ferro_ta_core::attribution::signal_attribution(ret, lbl); Ok((labels.into_pyarray(py), contributions.into_pyarray(py))) } /// Extract trade-level pnl and hold durations from positions and strategy returns. #[pyfunction] #[allow(clippy::type_complexity)] pub fn extract_trades<'py>( py: Python<'py>, positions: PyReadonlyArray1<'py, f64>, strategy_returns: PyReadonlyArray1<'py, f64>, ) -> PyResult<(Bound<'py, PyArray1>, Bound<'py, PyArray1>)> { let pos = positions.as_slice()?; let ret = strategy_returns.as_slice()?; let n = pos.len(); validation::validate_equal_length(&[(n, "positions"), (ret.len(), "strategy_returns")])?; let (pnl, hold) = ferro_ta_core::attribution::extract_trades(pos, ret); Ok((pnl.into_pyarray(py), hold.into_pyarray(py))) } pub fn register(m: &Bound<'_, PyModule>) -> PyResult<()> { m.add_function(wrap_pyfunction!(trade_stats, m)?)?; m.add_function(wrap_pyfunction!(monthly_contribution, m)?)?; m.add_function(wrap_pyfunction!(signal_attribution, m)?)?; m.add_function(wrap_pyfunction!(extract_trades, m)?)?; Ok(()) }