Aura/crates/aura-engine/tests/streaming_reduction_equivalence.rs

//! Folded sink reductions are byte-for-byte equal to the raw-recorder path.
//! Drives the folding sinks node-by-node (the `r_sma_e2e.rs` direct-node
//! style) over a synthetic dense R-record + equity/exposure series, and asserts
//! `summarize_r` over `GatedRecorder`'s emitted rows equals `summarize_r` over
//! the full record, and a `SeriesReducer` summary equals `summarize`'s fields.

use aura_core::{AnyColumn, Ctx, Node, Scalar, ScalarKind, Timestamp};
use aura_engine::{summarize, summarize_r};
use aura_backtest::{PM_RECORD_KINDS, PM_WIDTH};
use aura_std::{GatedRecorder, SeriesReducer};
use std::sync::mpsc;

const CLOSED: usize = 0;
const REALIZED_R: usize = 1;
const OPEN: usize = 11;
const UNREALIZED_R: usize = 12;
const ENTRY_PRICE: usize = 6;
const STOP_PRICE: usize = 7;

/// The kind-correct zero for a dense-record column. The PM record is
/// heterogeneous (`PM_RECORD_KINDS`: Bool/I64/Timestamp slots beside the f64s),
/// so each unset slot must default to a scalar of its column's kind — a blanket
/// f64 zero would be rejected by the kind-typed `AnyColumn::push`.
fn zero_of(kind: ScalarKind) -> Scalar {
    match kind {
        ScalarKind::F64 => Scalar::f64(0.0),
        ScalarKind::I64 => Scalar::i64(0),
        ScalarKind::Bool => Scalar::bool(false),
        ScalarKind::Timestamp => Scalar::ts(Timestamp(0)),
    }
}

/// One dense R-record row. `closed`/`open` set the gate + the open-at-end flag;
/// the priced fields make `summarize_r`'s R arithmetic well-defined.
fn pm_row(closed: bool, realized: f64, open: bool, entry: f64, stop: f64) -> Vec<Scalar> {
    let mut v: Vec<Scalar> = PM_RECORD_KINDS.iter().map(|&k| zero_of(k)).collect();
    debug_assert_eq!(v.len(), PM_WIDTH);
    v[CLOSED] = Scalar::bool(closed);
    v[REALIZED_R] = Scalar::f64(realized);
    v[OPEN] = Scalar::bool(open);
    v[UNREALIZED_R] = Scalar::f64(if open { realized } else { 0.0 });
    v[ENTRY_PRICE] = Scalar::f64(entry);
    v[STOP_PRICE] = Scalar::f64(stop);
    v
}

#[test]
fn gated_recorder_then_summarize_r_equals_raw_summarize_r() {
    // a realistic mix: holds, closed wins/losses, a hold tail, then an open-at-end row.
    let full: Vec<(Timestamp, Vec<Scalar>)> = [
        pm_row(false, 0.0, false, 0.0, 0.0),
        pm_row(true, 1.5, false, 100.0, 95.0),
        pm_row(false, 0.0, false, 0.0, 0.0),
        pm_row(true, -1.0, false, 100.0, 95.0),
        pm_row(false, 0.0, false, 0.0, 0.0),
        pm_row(false, 0.7, true, 100.0, 95.0), // open at end
    ]
    .into_iter()
    .enumerate()
    .map(|(i, r)| (Timestamp(i as i64 + 1), r))
    .collect();

    // RAW: summarize_r over the whole dense record.
    let raw = summarize_r(&full, &[]);

    // FOLDED: drive GatedRecorder (gate = CLOSED), collect its emitted rows, fold.
    let (tx, rx) = mpsc::channel();
    let mut g = GatedRecorder::new(&PM_RECORD_KINDS, CLOSED, tx);
    let mut cols: Vec<AnyColumn> =
        PM_RECORD_KINDS.iter().map(|&k| AnyColumn::with_capacity(k, 1)).collect();
    for (ts, row) in &full {
        for (i, s) in row.iter().enumerate() {
            cols[i].push(*s).unwrap();
        }
        assert_eq!(g.eval(Ctx::new(&cols, *ts)), None);
    }
    g.finalize();
    let folded_rows: Vec<(Timestamp, Vec<Scalar>)> = rx.try_iter().collect();
    let folded = summarize_r(&folded_rows, &[]);

    assert_eq!(folded, raw, "GatedRecorder+summarize_r must equal raw summarize_r");
}

#[test]
fn series_reducer_equals_summarize_pip_fields() {
    let equity: Vec<(Timestamp, f64)> =
        [10.0, 12.0, 8.0, 9.0, 7.0].iter().enumerate().map(|(i, &v)| (Timestamp(i as i64), v)).collect();
    let exposure: Vec<(Timestamp, f64)> =
        [1.0, 1.0, -1.0, 0.0, 1.0].iter().enumerate().map(|(i, &v)| (Timestamp(i as i64), v)).collect();

    let raw = summarize(&equity, &exposure);

    // FOLDED: one SeriesReducer per series; read pip fields from their summaries.
    let fold_series = |series: &[(Timestamp, f64)]| -> Vec<Scalar> {
        let (tx, rx) = mpsc::channel();
        let mut r = SeriesReducer::new(tx);
        let mut col = vec![AnyColumn::with_capacity(ScalarKind::F64, 1)];
        for &(ts, v) in series {
            col[0].push(Scalar::f64(v)).unwrap();
            r.eval(Ctx::new(&col, ts));
        }
        r.finalize();
        rx.try_iter().next().expect("one summary row").1
    };
    let eqs = fold_series(&equity);
    let exs = fold_series(&exposure);

    assert_eq!(eqs[0].as_f64(), raw.total_pips, "total_pips");
    assert_eq!(eqs[1].as_f64(), raw.max_drawdown, "max_drawdown");
    assert_eq!(exs[2].as_i64() as u64, raw.bias_sign_flips, "bias_sign_flips");
}