foxhunt/crates/ml-backtesting/tests/threshold_and_cost.rs

//! P4 regression: threshold gate + per-fill cost integration.
//!
//! Tight tests focused on the GATE's pre-Kelly skip path and the cost
//! plumbing in apply_fill_to_pos. The full kelly_state_sees_net_return
//! end-to-end test requires a full submit_market → fill → close sequence
//! which is exercised by the production smoke; here we test the kernel
//! contract in isolation.

use anyhow::Result;
use ml_backtesting::policy::N_HORIZONS;
use ml_backtesting::sim::{BatchedSimConfig, LobSimCuda, UniformSimParams};
use ml_core::device::MlDevice;

fn cfg_with_threshold(n: usize, threshold: f32, cost: f32) -> BatchedSimConfig {
    BatchedSimConfig::from_uniform(n, &UniformSimParams {
        target_annual_vol_units: 50.0,
        annualisation_factor:    825.0,
        max_lots:                5,
        latency_ns:              0,
        kelly_frac_floor:        0.20,
        sharpe_weight_floor:     0.10,
        threshold,
        cost_per_lot_per_side:   cost,
        max_hold_ns:             0,
        min_reasonable_px:       0.0,
        max_reasonable_px:       f32::INFINITY,
        delta_floor:             0.0,
    })
}

#[test]
#[ignore = "requires CUDA"]
fn threshold_gate_skips_low_conviction() -> Result<()> {
    let dev = match MlDevice::cuda(0) {
        Ok(d) => d,
        Err(e) => { eprintln!("skipping: cuda device unavailable ({e})"); return Ok(()); }
    };
    let mut sim = LobSimCuda::new(1, &dev)?;
    // CRT.1 C1.2: at cold-start ISV all weights are eps_edge / cost² and
    // identical across horizons. With uniform alpha=0.51 across all 5
    // horizons (all bullish), magnitude_h = 0.02 and conviction_signed =
    // 0.02 — well below threshold = 0.10. Kernel writes side=2 (no-op).
    sim.broadcast_alpha(&[0.51; N_HORIZONS])?;
    sim.step_decision_with_latency(0, &cfg_with_threshold(1, 0.10, 1.0))?;
    let (side, size) = sim.read_market_target(0)?;
    assert_eq!(side, 2, "side should be noop under threshold gate; got side={side}");
    assert_eq!(size, 0);
    Ok(())
}

#[test]
#[ignore = "requires CUDA"]
fn threshold_gate_allows_high_conviction() -> Result<()> {
    let dev = match MlDevice::cuda(0) {
        Ok(d) => d,
        Err(e) => { eprintln!("skipping: cuda device unavailable ({e})"); return Ok(()); }
    };
    let mut sim = LobSimCuda::new(1, &dev)?;
    // CRT.1 C1.2: uniform alpha=0.8 across horizons → magnitude_h = 0.6,
    // direction_h = +1 for all → conviction_signed = 0.6, above threshold
    // = 0.10. target_lots = round(1 * 0.6 * 5) = 3.
    sim.broadcast_alpha(&[0.8; N_HORIZONS])?;
    sim.step_decision_with_latency(0, &cfg_with_threshold(1, 0.10, 1.0))?;
    let (side, size) = sim.read_market_target(0)?;
    assert_eq!(side, 0, "side should be buy with strong alpha; got side={side}");
    assert!(size >= 1, "size {size} < 1 — threshold gate may be over-restricting");
    Ok(())
}

#[test]
#[ignore = "requires CUDA"]
fn threshold_zero_is_passthrough() -> Result<()> {
    // Sanity check: threshold = 0.0 should pass any non-zero conviction
    // through to a non-zero target. conviction_abs >= 0 always.
    let dev = match MlDevice::cuda(0) {
        Ok(d) => d,
        Err(e) => { eprintln!("skipping: cuda device unavailable ({e})"); return Ok(()); }
    };
    let mut sim = LobSimCuda::new(1, &dev)?;
    sim.broadcast_alpha(&[0.8; N_HORIZONS])?;
    sim.step_decision_with_latency(0, &cfg_with_threshold(1, 0.0, 1.0))?;
    let (side, size) = sim.read_market_target(0)?;
    assert_eq!(side, 0, "threshold=0 with strong alpha should pass through; got side={side}");
    assert!(size >= 1, "size {size} < 1 — passthrough behaviour broken");
    Ok(())
}