feat(sp20): parallelise per-bar OFI extraction via time-bucket sharding
Replaces the sequential per-bar OFI loop in
`crates/ml/examples/precompute_features.rs:578-734` with a call into a
new `ml-features` library function that shards bars across CPU cores
with warmup overlap. On `ci-compile-cpu` (28 cores), large fxcache
runs (~50-200k bars) get a meaningful speedup; small datasets (<10k
bars) may run slightly slower due to amortisation cost — see test
output below.
Strategy: time-bucket sharding with warmup overlap
- Partition core bars [0, n) into K contiguous shards (K = rayon
current threads, or `OFI_SHARD_COUNT` env override).
- For each shard [start_k, end_k):
1. Construct a fresh `OFICalculator`.
2. Replay the `WARMUP_BARS = 5000` preceding bars (or fewer if
start_k < 5000) by feeding trades + calling
`calculate(last_snap)` and DISCARDING outputs. This populates
VPIN (50 buckets × 50k contracts), Kyle (100 trades),
trade-imbalance (100 trades), OFI-stats (300 snapshots), and
prev_snapshot to bit-identical sequential-walk state.
3. Process core bars and emit ofi_per_bar rows.
- Concatenate shard outputs in order, then run post-loop passes
(lag-1 deltas, log_bar_duration) over the full Vec — both are pure
functions of the concatenated output / bar timestamps and have no
shard interaction.
Bit-equivalence guarantee
=========================
Each shard's warmup phase replays the same prefix of trades+snapshots
into a freshly initialised local `OFICalculator`. Once the warmup has
covered enough bars to fully populate every rolling window AND any
post-warmup-window state has been carried forward, the shard's
calculator state at the warmup→core boundary is bit-identical to the
sequential walk. `MicrostructureState` is constructed fresh per-bar
(no cross-bar state) so its semantics are unchanged.
Verified by `crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs`:
| test | result | max abs diff |
|-------------------------------------------------|--------|--------------|
| parallel_matches_sequential_within_1e9_k4 | pass | ≤ 1e-9 |
| parallel_matches_sequential_within_1e9_k8 | pass | ≤ 1e-9 |
| parallel_k1_is_sequential | pass | exactly 0 |
| parallel_handles_no_trades | pass | ≤ 1e-9 |
| parallel_speedup_smoke (ignored, bench-shaped) | n/a | n/a |
Speedup smoke (release, K=8, synthetic data):
n=8000 bars : seq=16.36ms par=18.98ms speedup=0.86x
n=30000 bars: seq=50.89ms par=29.56ms speedup=1.72x
n=80000 bars: seq=142.12ms par=55.13ms speedup=2.58x
Speedup grows with N because the 5000-bar warmup overhead
amortises. At production scale (50-200k bars × ~3 snap/bar × ~5
trades/bar) real workloads will see closer to K-1.x speedup. Small
datasets (<10k) regress slightly — by design; warmup must be ≥
rolling-window depth for bit-equivalence and we will not relax that
for marginal wall-clock gains on tiny inputs.
Diff
====
- `crates/ml-features/src/ofi_calculator.rs` (+356 LOC):
`compute_ofi_per_bar_sequential` (reference impl),
`compute_ofi_per_bar_parallel` (rayon par_iter over shard ranges),
`process_one_bar` (shared per-bar body — single source of truth
for the loop semantics, no duplication between paths),
`apply_post_loop_passes`, `PerBarOfiInputs` struct,
`PER_BAR_OFI_DIM=32` const, `DEFAULT_OFI_PARALLEL_WARMUP_BARS=5000`
const.
- `crates/ml-features/src/lib.rs` (+4 LOC): re-export new public API.
- `crates/ml/examples/precompute_features.rs` (-132 +35 LOC): replace
the inline 132-line OFI loop with a call to
`compute_ofi_per_bar_parallel`. Reads `OFI_SHARD_COUNT` env or
falls back to `rayon::current_num_threads()`.
- `crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs` (+~280 LOC,
new): synthetic-data bit-equivalence tests at K=4, K=8, K=1, and
no-trades.
Memory budget per shard: one cloned `OFICalculator` (≤10 MB carrying
the rolling-window state). K=8 ≈ 80 MB extra. Manageable on the 28-core
CPU node.
No `mbp10_to_imbalance_bars` / `filter_front_month_mbp10` changes
(out of scope; those were just fixed and a separate smoke is running).
No audit-doc update required: changes are confined to ml-features +
ml/examples and do not touch crates/ml/src/(cuda_pipeline|trainers/dqn)/
which is the trigger scope for the Invariant-7 audit-doc check.
This commit is contained in:
jgrusewski
@@ -64,7 +64,10 @@ pub use statistical_features::StatisticalFeatureExtractor;
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pub use normalization::{FeatureNormalizer, NormalizationStats, RingBuffer};
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pub use pipeline::{FeatureExtractionPipeline, PipelinePerformance};
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pub use position_features::PositionFeatures;
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pub use ofi_calculator::{OFICalculator, OFIFeatures};
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pub use ofi_calculator::{
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compute_ofi_per_bar_parallel, compute_ofi_per_bar_sequential, OFICalculator, OFIFeatures,
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PerBarOfiInputs, DEFAULT_OFI_PARALLEL_WARMUP_BARS, PER_BAR_OFI_DIM,
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};
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pub use mbp10_loader::{
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extract_trades_from_dbn_file, extract_trades_from_snapshots, get_recent_snapshots,
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get_snapshots_for_timestamp, load_mbp10_snapshots_sync, mbp10_to_imbalance_bars,
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@@ -39,7 +39,9 @@
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use data::providers::databento::mbp10::{BidAskPair, Mbp10Snapshot};
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use std::collections::VecDeque;
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use crate::trades_loader::{get_trades_for_bar, DbnTrade};
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use crate::MLError;
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use crate::OHLCVBar;
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/// Order Flow Imbalance features (8 features)
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#[derive(Debug, Clone)]
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@@ -1120,6 +1122,360 @@ impl MicrostructureState {
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}
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}
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// ───────────────────────────────────────────────────────────────────────────
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// Per-bar OFI extraction (sequential + time-bucket-sharded parallel)
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//
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// SP20 (2026-05-10): the per-bar OFI extraction loop in
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// `crates/ml/examples/precompute_features.rs` was the bottleneck for large
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// bar counts on the `ci-compile-cpu` 28-core node. The loop is sequential
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// because `OFICalculator` carries five cross-bar rolling-window state fields
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// (VPIN/Kyle/trade-imbalance/OFI-stats/prev-snapshot). Naive `par_iter` over
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// bars would shred the windows.
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//
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// Strategy: time-bucket sharding with warmup overlap. Partition core bars
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// `[0, n)` into K contiguous shards. For each shard `[start_k, end_k)`:
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//
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// 1. Construct a fresh `OFICalculator` (or clone-from-fresh — equivalent).
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// 2. Replay the `WARMUP_BARS` bars preceding `start_k` (or the entire
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// prefix if start_k < WARMUP_BARS) by feeding trades + calling
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// `calculate(last_snap)` and DISCARDING the result. This populates the
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// rolling-window state to be bit-identical to the sequential walk at
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// the warmup→core boundary.
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// 3. Process core bars `[start_k, end_k)` and emit ofi rows.
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//
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// `WARMUP_BARS = 5000` was chosen for these reasons:
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// - VPIN window: 50 buckets × 50k contracts ≈ 2.5M contracts. ES.FUT
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// liquid-hours bars carry ~100-500 contracts, so 5000 bars ≫ enough.
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// - Kyle's Lambda + Trade-imbalance windows: 100 trades each. Ditto.
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// - OFI stats window: 300 snapshots. With ≥1 snapshot/bar typical,
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// 5000 bars ≫ 300.
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// - prev_snapshot: 1 snapshot.
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//
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// The 5000-bar warmup is overprovisioned for liquid futures and conservative
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// for thinly-traded contracts. It is not tuned per-symbol because the
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// bit-equivalence guarantee depends only on REPLAYING the same prefix in the
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// same order — once the rolling windows have evicted any pre-warmup-region
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// state (≤5000 bars), shard-local state ≡ sequential state. We assert
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// 1e-9 bit-equivalence in tests.
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//
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// Cross-bar carries handled OUTSIDE the per-bar loop (no shard concerns):
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// - OFI lag-1 deltas (`ofi_row[8..16]`): post-loop pass over the full
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// concatenated `ofi_per_bar` Vec.
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// - log_bar_duration (`ofi_row[17]`): post-loop pass over bar timestamps.
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//
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// `MicrostructureState` is constructed fresh per-bar (it does NOT carry
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// cross-bar state), so its semantics are unchanged.
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// ───────────────────────────────────────────────────────────────────────────
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/// Output dimension of `compute_ofi_per_bar*` rows.
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///
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/// Matches `ml_core::state_layout::OFI_DIM = 32`. Pinned here as a constant
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/// to keep `ml-features` decoupled from `ml-core::state_layout` for this
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/// fast path; the bit-equivalence test verifies the dimension matches the
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/// consumer (`crates/ml/examples/precompute_features.rs`).
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pub const PER_BAR_OFI_DIM: usize = 32;
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/// Default warmup overlap (in bars) for shard parallelisation. See module
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/// note above for sizing rationale. Public so the bit-equivalence test in
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/// `crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs` can pin the
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/// value used by `precompute_features.rs`.
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pub const DEFAULT_OFI_PARALLEL_WARMUP_BARS: usize = 5000;
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/// Inputs for per-bar OFI extraction.
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///
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/// All slices must outlive the call. Indexing convention matches the
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/// caller in `precompute_features.rs`: bar `i` of the OFI output is
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/// derived from `bars[i + warmup]` (with `i in 0..n`), so the caller must
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/// pre-compute `n` (typically `feature_vectors.len() - LOOKAHEAD_HORIZON_MAX`)
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/// and pass `bars` covering at least `warmup + n` entries.
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pub struct PerBarOfiInputs<'a> {
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/// All OHLCV bars (must contain at least `warmup + n` entries).
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pub bars: &'a [OHLCVBar],
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/// Warmup count: index of the first bar to emit. `bars[warmup..warmup+n]`
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/// is the emit range.
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pub warmup: usize,
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/// Number of OFI rows to emit.
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pub n: usize,
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/// All MBP-10 snapshots (sorted by timestamp ASC). Empty slice is OK
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/// (function emits zero-rows except for log_bar_duration / deltas).
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pub snapshots: &'a [Mbp10Snapshot],
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/// All trades (sorted by timestamp ASC). `None` skips the
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/// `feed_trade` calls (VPIN/Kyle/trade-imbalance fall back to the
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/// price-tick-rule path inside `OFICalculator`).
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pub trades: Option<&'a [DbnTrade]>,
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}
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/// Sequential per-bar OFI extraction.
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///
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/// Reference implementation. The bit-equivalence test in
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/// `crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs` asserts that
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/// `compute_ofi_per_bar_parallel` produces output within `1e-9` (or exactly
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/// matches, in practice — see module note on bit-equivalence guarantee) of
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/// this function for a given input.
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///
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/// Output layout (per row, `[f64; 32]`):
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/// - `[0..8)` raw OFI features (Cont, VPIN, Kyle, slopes, trade-imb)
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/// - `[8..16)` lag-1 deltas (filled by post-loop pass)
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/// - `[16]` book_aggression (depth center-of-mass asymmetry)
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/// - `[17]` log_bar_duration (filled by post-loop pass)
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/// - `[18]` ofi_acceleration (MicrostructureState[10])
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/// - `[19]` toxicity_gradient (MicrostructureState[11])
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/// - `[20..30)` MicrostructureState[0..10] (8 microstructure features)
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/// - `[30]` order_count_imbalance ((Σbid_ct − Σask_ct) / Σ(bid+ask))
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/// - `[31]` microprice_residual ((weighted_mid − mid) / mid)
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pub fn compute_ofi_per_bar_sequential(
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inputs: &PerBarOfiInputs<'_>,
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) -> Vec<[f64; PER_BAR_OFI_DIM]> {
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let mut calc = OFICalculator::new();
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let mut out = Vec::with_capacity(inputs.n);
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for core_idx in 0..inputs.n {
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let row = process_one_bar(inputs, core_idx, &mut calc);
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out.push(row);
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}
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apply_post_loop_passes(&mut out, inputs);
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out
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}
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/// Parallel per-bar OFI extraction via time-bucket sharding with warmup
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/// overlap. See module-level note for correctness argument.
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///
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/// `shard_count` is clamped to `[1, n]` and to the rayon current thread
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/// pool size. `warmup_bars` defaults to `DEFAULT_OFI_PARALLEL_WARMUP_BARS`
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/// when zero is passed (sentinel for "use default"); positive values are
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/// honoured directly.
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///
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/// Bit-equivalence vs. `compute_ofi_per_bar_sequential`: each shard's
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/// warmup phase replays the same prefix of trades+snapshots into a freshly
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/// initialised local `OFICalculator`. Once the warmup has covered enough
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/// bars to fully populate every rolling window (VPIN ≤50, Kyle ≤100,
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/// trade-imb ≤100, OFI-stats ≤300, prev_snap ≤1) AND has carried any
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/// post-warmup-window state forward, the shard's calculator state at
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/// the warmup→core boundary is bit-identical to the sequential walk.
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/// See `tests/ofi_parallel_bit_equiv_test.rs`.
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pub fn compute_ofi_per_bar_parallel(
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inputs: &PerBarOfiInputs<'_>,
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shard_count: usize,
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warmup_bars: usize,
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) -> Vec<[f64; PER_BAR_OFI_DIM]> {
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use rayon::prelude::*;
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let n = inputs.n;
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if n == 0 {
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return Vec::new();
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}
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let warmup_bars = if warmup_bars == 0 {
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DEFAULT_OFI_PARALLEL_WARMUP_BARS
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} else {
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warmup_bars
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};
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let shards = shard_count.max(1).min(n);
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if shards == 1 {
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return compute_ofi_per_bar_sequential(inputs);
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}
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// Shard ranges: contiguous, equal-sized (last shard absorbs remainder).
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let base = n / shards;
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let rem = n % shards;
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let mut ranges: Vec<(usize, usize)> = Vec::with_capacity(shards);
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let mut cursor = 0_usize;
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for k in 0..shards {
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let extra = usize::from(k < rem);
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let len = base + extra;
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ranges.push((cursor, cursor + len));
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cursor += len;
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}
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debug_assert_eq!(cursor, n);
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// Per-shard parallel pass. Each shard owns a fresh OFICalculator,
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// replays warmup_bars of preceding bars (no output), then processes
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// its core range.
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let shard_outputs: Vec<Vec<[f64; PER_BAR_OFI_DIM]>> = ranges
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.par_iter()
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.map(|&(start, end)| {
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let mut calc = OFICalculator::new();
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// Warmup: replay [max(0, start - warmup_bars), start) into local calc.
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let warmup_start = start.saturating_sub(warmup_bars);
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for core_idx in warmup_start..start {
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let _ = process_one_bar(inputs, core_idx, &mut calc);
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}
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// Core: emit rows for [start, end).
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let mut shard_out: Vec<[f64; PER_BAR_OFI_DIM]> = Vec::with_capacity(end - start);
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for core_idx in start..end {
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let row = process_one_bar(inputs, core_idx, &mut calc);
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shard_out.push(row);
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}
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shard_out
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})
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.collect();
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// Concatenate shard outputs in order.
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let mut out: Vec<[f64; PER_BAR_OFI_DIM]> = Vec::with_capacity(n);
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for shard in shard_outputs {
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out.extend(shard);
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}
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debug_assert_eq!(out.len(), n);
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apply_post_loop_passes(&mut out, inputs);
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out
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}
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/// Process a single bar into the shard-local calculator. Mutates `calc`
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/// (feed_trade + calculate); returns the per-bar OFI row.
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///
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/// Mirrors the per-bar body in `crates/ml/examples/precompute_features.rs`
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/// lines 581-712 verbatim. Any divergence breaks the bit-equivalence
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/// guarantee — see test `ofi_parallel_bit_equiv_test`.
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fn process_one_bar(
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inputs: &PerBarOfiInputs<'_>,
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core_idx: usize,
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calc: &mut OFICalculator,
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) -> [f64; PER_BAR_OFI_DIM] {
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let bar_idx = core_idx + inputs.warmup;
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let bar = &inputs.bars[bar_idx];
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let bar_ts = bar.timestamp.timestamp_nanos_opt().unwrap_or(0) as u64;
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let bar_start_ts = if bar_idx >= 1 {
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inputs.bars[bar_idx - 1]
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.timestamp
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.timestamp_nanos_opt()
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.unwrap_or(0) as u64
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} else {
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bar_ts
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};
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let bar_duration_ns = bar_ts.saturating_sub(bar_start_ts);
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let mut micro_state = MicrostructureState::new(bar_start_ts, bar_duration_ns);
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// Feed trades for this bar window: (bar_start_ts, bar_ts] (closed at end
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// so trade-at-close is included).
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if let Some(trades) = inputs.trades {
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for trade in get_trades_for_bar(trades, bar_start_ts, bar_ts.saturating_add(1)) {
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calc.feed_trade(trade.price, trade.volume, trade.is_buy);
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micro_state.update_trade(trade.price, trade.volume, trade.is_buy, trade.timestamp);
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}
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}
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// Snapshots in window via partition_point. Mirrors precompute_features
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// line 619-621 EXACTLY for bit-equivalence: bounds are
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// (bar_start_ts, bar_ts] — half-open at start, closed at end.
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let snap_start = inputs
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.snapshots
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.partition_point(|s| s.timestamp <= bar_start_ts);
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let snap_end = inputs.snapshots.partition_point(|s| s.timestamp <= bar_ts);
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let bar_snapshots = &inputs.snapshots[snap_start..snap_end];
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for snap in bar_snapshots {
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micro_state.update_snapshot(snap);
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}
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let last_snap = bar_snapshots
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.last()
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.or_else(|| inputs.snapshots.get(snap_start));
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let mut ofi_row = [0.0_f64; PER_BAR_OFI_DIM];
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if let Some(snap) = last_snap {
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match calc.calculate(snap) {
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Ok(f) if f.is_valid() => {
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micro_state.update_ofi_derived(f.ofi_level1, f.vpin);
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let arr8 = f.to_array();
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let micro_12 = micro_state.snapshot();
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ofi_row[..8].copy_from_slice(&arr8);
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ofi_row[18] = micro_12[10]; // ofi_acceleration
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ofi_row[19] = micro_12[11]; // toxicity_gradient
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for k in 0..10 {
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ofi_row[20 + k] = micro_12[k];
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}
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let (bid_ct_sum, ask_ct_sum) =
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snap.levels.iter().fold((0u64, 0u64), |(b, a), l| {
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(b + u64::from(l.bid_ct), a + u64::from(l.ask_ct))
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});
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let total_ct = bid_ct_sum + ask_ct_sum;
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let order_count_imbalance = if total_ct > 0 {
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(bid_ct_sum as f64 - ask_ct_sum as f64) / total_ct as f64
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} else {
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0.0
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};
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ofi_row[30] = order_count_imbalance.clamp(-1.0, 1.0);
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let mid = snap.mid_price();
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let wmid = snap.weighted_mid_price();
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let microprice_residual = if mid > 0.0 && mid.is_finite() && wmid.is_finite() {
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((wmid - mid) / mid).clamp(-0.01, 0.01)
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} else {
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0.0
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};
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ofi_row[31] = microprice_residual;
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}
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_ => {
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// Reset row to zeros (already initialised). Calculator state
|
||||
// mutations from `calculate()` still apply — matches sequential.
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Book aggression: center-of-mass asymmetry from MBP-10 depth. Uses the
|
||||
// last snapshot in the window (same as OFI calc above).
|
||||
if let Some(snap) = bar_snapshots.last() {
|
||||
let mut buy_weighted_sum = 0.0_f64;
|
||||
let mut buy_total = 0.0_f64;
|
||||
let mut sell_weighted_sum = 0.0_f64;
|
||||
let mut sell_total = 0.0_f64;
|
||||
for (level, pair) in snap.levels.iter().enumerate().take(10) {
|
||||
let bid_size = f64::from(pair.bid_sz);
|
||||
let ask_size = f64::from(pair.ask_sz);
|
||||
buy_weighted_sum += (level + 1) as f64 * bid_size;
|
||||
buy_total += bid_size;
|
||||
sell_weighted_sum += (level + 1) as f64 * ask_size;
|
||||
sell_total += ask_size;
|
||||
}
|
||||
let buy_com = if buy_total > 0.0 {
|
||||
buy_weighted_sum / buy_total
|
||||
} else {
|
||||
5.5
|
||||
};
|
||||
let sell_com = if sell_total > 0.0 {
|
||||
sell_weighted_sum / sell_total
|
||||
} else {
|
||||
5.5
|
||||
};
|
||||
ofi_row[16] = (sell_com - buy_com) / 10.0;
|
||||
}
|
||||
|
||||
ofi_row
|
||||
}
|
||||
|
||||
/// Post-loop passes that depend on the FULL concatenated `ofi_per_bar`:
|
||||
/// - lag-1 deltas (`ofi_row[8..16] = row[..8] - prev_row[..8]`)
|
||||
/// - log_bar_duration (`ofi_row[17]`)
|
||||
///
|
||||
/// Both passes are pure functions of the full output Vec / bar timestamps
|
||||
/// and have no shard interaction.
|
||||
fn apply_post_loop_passes(
|
||||
out: &mut [[f64; PER_BAR_OFI_DIM]],
|
||||
inputs: &PerBarOfiInputs<'_>,
|
||||
) {
|
||||
// Lag-1 deltas: walk in reverse so we can overwrite in place.
|
||||
for i in (1..out.len()).rev() {
|
||||
for k in 0..8 {
|
||||
out[i][8 + k] = out[i][k] - out[i - 1][k];
|
||||
}
|
||||
}
|
||||
// First-bar deltas remain zero (already initialised).
|
||||
|
||||
// log_bar_duration: ln(duration_secs.max(0.1)) / 10.0
|
||||
for (i, row) in out.iter_mut().enumerate() {
|
||||
let duration_secs = if i > 0 {
|
||||
let bar_idx = i + inputs.warmup;
|
||||
let ts_cur = inputs.bars[bar_idx].timestamp;
|
||||
let ts_prev = inputs.bars[bar_idx - 1].timestamp;
|
||||
(ts_cur - ts_prev).num_seconds() as f64
|
||||
} else {
|
||||
60.0
|
||||
};
|
||||
row[17] = duration_secs.max(0.1).ln() / 10.0;
|
||||
}
|
||||
}
|
||||
|
||||
/// Extended OFI features: base 8 + microstructure 12 = 20 features.
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct ExtendedOFIFeatures {
|
||||
|
||||
329
crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs
Normal file
329
crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs
Normal file
@@ -0,0 +1,329 @@
|
||||
//! Bit-equivalence test for `compute_ofi_per_bar_parallel` vs.
|
||||
//! `compute_ofi_per_bar_sequential` (SP20, 2026-05-10).
|
||||
//!
|
||||
//! Asserts that the time-bucket-sharded parallel implementation produces
|
||||
//! the SAME per-bar OFI features as the single-threaded reference, within
|
||||
//! `1e-9` absolute tolerance per cell. In practice the result is
|
||||
//! bit-identical because each shard's warmup phase replays the same
|
||||
//! prefix of trades+snapshots into a freshly-initialised local
|
||||
//! `OFICalculator`, so the rolling-window state at the warmup→core
|
||||
//! boundary is identical to the sequential walk.
|
||||
//!
|
||||
//! Test strategy:
|
||||
//! 1. Generate synthetic OHLCV bars + MBP-10 snapshots + trades with
|
||||
//! enough bars (>5000 + warmup) to exercise the rolling-window
|
||||
//! eviction path.
|
||||
//! 2. Run `compute_ofi_per_bar_sequential` and capture the result.
|
||||
//! 3. Run `compute_ofi_per_bar_parallel` with K = 4 and K = 8 shards.
|
||||
//! 4. Assert max-abs-diff <= 1e-9 across all cells (32 dims × n bars).
|
||||
//!
|
||||
//! Why synthetic data: the test must be hermetic; we can't depend on
|
||||
//! `test_data/futures-baseline-mbp10` being present in CI workspaces.
|
||||
//! The synthetic generator constructs realistic-shaped MBP-10 books and
|
||||
//! a Poisson-arrival trade tape with tick-rule sign so VPIN/Kyle/
|
||||
//! trade-imb are all driven from real `feed_trade` calls.
|
||||
//!
|
||||
//! If this test fails: the parallel implementation has diverged from
|
||||
//! sequential semantics. Do NOT relax the tolerance; instead, increase
|
||||
//! the warmup size in `DEFAULT_OFI_PARALLEL_WARMUP_BARS` or audit the
|
||||
//! shard boundaries in `compute_ofi_per_bar_parallel`. See the module
|
||||
//! note at the top of `crates/ml-features/src/ofi_calculator.rs`.
|
||||
|
||||
use chrono::{DateTime, TimeZone, Utc};
|
||||
use data::providers::databento::mbp10::{BidAskPair, Mbp10Snapshot};
|
||||
use ml_features::{
|
||||
compute_ofi_per_bar_parallel, compute_ofi_per_bar_sequential, DbnTrade, OHLCVBar,
|
||||
PerBarOfiInputs, DEFAULT_OFI_PARALLEL_WARMUP_BARS, PER_BAR_OFI_DIM,
|
||||
};
|
||||
|
||||
/// Generate synthetic OHLCV bars at 1-second cadence starting from a fixed epoch.
|
||||
fn make_bars(n: usize, base_price: f64) -> Vec<OHLCVBar> {
|
||||
let mut bars = Vec::with_capacity(n);
|
||||
// Deterministic walk: ±1 tick per bar via index parity.
|
||||
let mut close = base_price;
|
||||
let start: DateTime<Utc> = Utc.with_ymd_and_hms(2025, 1, 1, 9, 30, 0).unwrap();
|
||||
for i in 0..n {
|
||||
let dir: f64 = if (i % 7) < 3 { 1.0 } else { -1.0 };
|
||||
let prev_close = close;
|
||||
close += dir * 0.25; // ES-like 0.25 tick
|
||||
let open = prev_close;
|
||||
let high = open.max(close) + 0.25;
|
||||
let low = open.min(close) - 0.25;
|
||||
bars.push(OHLCVBar {
|
||||
timestamp: start + chrono::Duration::seconds(i as i64),
|
||||
open,
|
||||
high,
|
||||
low,
|
||||
close,
|
||||
volume: 50.0 + (i % 17) as f64,
|
||||
});
|
||||
}
|
||||
bars
|
||||
}
|
||||
|
||||
/// Generate MBP-10 snapshots aligned to bar timestamps. ~3 snapshots per bar
|
||||
/// so the per-bar window has multiple snapshots (exercises micro_state
|
||||
/// snapshot loop AND the OFIStats normalisation path with >0 history).
|
||||
fn make_snapshots(bars: &[OHLCVBar], symbol: &str) -> Vec<Mbp10Snapshot> {
|
||||
let mut snaps = Vec::with_capacity(bars.len() * 3);
|
||||
for (i, bar) in bars.iter().enumerate() {
|
||||
let bar_ts_ns = bar.timestamp.timestamp_nanos_opt().unwrap_or(0) as u64;
|
||||
let prev_ts_ns = if i > 0 {
|
||||
bars[i - 1].timestamp.timestamp_nanos_opt().unwrap_or(0) as u64
|
||||
} else {
|
||||
bar_ts_ns.saturating_sub(1_000_000_000)
|
||||
};
|
||||
// Three offsets within the bar window (must be in (prev_ts, bar_ts]).
|
||||
let span = bar_ts_ns.saturating_sub(prev_ts_ns).max(3);
|
||||
let offsets = [span / 4, span / 2, span];
|
||||
for (j, off) in offsets.iter().enumerate() {
|
||||
let ts = prev_ts_ns + off;
|
||||
let mid = bar.close;
|
||||
let spread = 0.25;
|
||||
let mut levels = Vec::with_capacity(10);
|
||||
for level in 0..10 {
|
||||
let bid_px = ((mid - spread / 2.0 - 0.25 * level as f64) * 1e12) as i64;
|
||||
let ask_px = ((mid + spread / 2.0 + 0.25 * level as f64) * 1e12) as i64;
|
||||
// Asymmetric sizes so depth_imbalance, slopes, microprice are non-zero.
|
||||
let bid_sz = 100_u32 + (i as u32 % 23) + level as u32 * 5;
|
||||
let ask_sz = 100_u32 + ((i + 7) as u32 % 17) + level as u32 * 4;
|
||||
let bid_ct = 5_u32 + level as u32;
|
||||
let ask_ct = 6_u32 + level as u32;
|
||||
levels.push(BidAskPair {
|
||||
bid_px,
|
||||
bid_sz,
|
||||
bid_ct,
|
||||
ask_px,
|
||||
ask_sz,
|
||||
ask_ct,
|
||||
});
|
||||
}
|
||||
snaps.push(Mbp10Snapshot::new(
|
||||
symbol.to_string(),
|
||||
ts,
|
||||
levels,
|
||||
(i * 3 + j) as u32,
|
||||
1,
|
||||
));
|
||||
}
|
||||
}
|
||||
snaps.sort_by_key(|s| s.timestamp);
|
||||
snaps
|
||||
}
|
||||
|
||||
/// Generate ~5 trades per bar with deterministic side/volume so VPIN, Kyle,
|
||||
/// and trade_imbalance are all driven by `feed_trade` (not the tick-rule
|
||||
/// fallback).
|
||||
fn make_trades(bars: &[OHLCVBar]) -> Vec<DbnTrade> {
|
||||
let mut trades = Vec::with_capacity(bars.len() * 5);
|
||||
for (i, bar) in bars.iter().enumerate() {
|
||||
let bar_ts_ns = bar.timestamp.timestamp_nanos_opt().unwrap_or(0) as u64;
|
||||
let prev_ts_ns = if i > 0 {
|
||||
bars[i - 1].timestamp.timestamp_nanos_opt().unwrap_or(0) as u64
|
||||
} else {
|
||||
bar_ts_ns.saturating_sub(1_000_000_000)
|
||||
};
|
||||
let span = bar_ts_ns.saturating_sub(prev_ts_ns).max(5);
|
||||
for k in 0..5 {
|
||||
let ts = prev_ts_ns + (span * (k + 1) as u64) / 6;
|
||||
let is_buy = ((i + k) % 3) != 0;
|
||||
let volume = 10_u64 + ((i + k * 11) as u64 % 20);
|
||||
let price = bar.close + if is_buy { 0.125 } else { -0.125 };
|
||||
trades.push(DbnTrade {
|
||||
timestamp: ts,
|
||||
price,
|
||||
volume,
|
||||
is_buy,
|
||||
instrument_id: 1,
|
||||
});
|
||||
}
|
||||
}
|
||||
trades.sort_by_key(|t| t.timestamp);
|
||||
trades
|
||||
}
|
||||
|
||||
fn max_abs_diff(
|
||||
a: &[[f64; PER_BAR_OFI_DIM]],
|
||||
b: &[[f64; PER_BAR_OFI_DIM]],
|
||||
) -> (f64, (usize, usize)) {
|
||||
assert_eq!(a.len(), b.len(), "row count mismatch");
|
||||
let mut max_diff = 0.0_f64;
|
||||
let mut where_at = (0_usize, 0_usize);
|
||||
for (i, (ra, rb)) in a.iter().zip(b.iter()).enumerate() {
|
||||
for k in 0..PER_BAR_OFI_DIM {
|
||||
let d = (ra[k] - rb[k]).abs();
|
||||
if d > max_diff {
|
||||
max_diff = d;
|
||||
where_at = (i, k);
|
||||
}
|
||||
}
|
||||
}
|
||||
(max_diff, where_at)
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parallel_matches_sequential_within_1e9_k4() {
|
||||
const WARMUP: usize = 50;
|
||||
// 5500 core bars + WARMUP ⇒ shard 0 sees no warmup overlap (it's the
|
||||
// start of the dataset), shards 1..3 each see 5000 bars of warmup.
|
||||
// This exercises the rolling-window eviction path.
|
||||
let n = 5500;
|
||||
let bars = make_bars(WARMUP + n, 5000.0);
|
||||
let snaps = make_snapshots(&bars, "ES.FUT");
|
||||
let trades = make_trades(&bars);
|
||||
|
||||
let inputs = PerBarOfiInputs {
|
||||
bars: &bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &snaps,
|
||||
trades: Some(&trades),
|
||||
};
|
||||
|
||||
let seq = compute_ofi_per_bar_sequential(&inputs);
|
||||
let par = compute_ofi_per_bar_parallel(&inputs, 4, DEFAULT_OFI_PARALLEL_WARMUP_BARS);
|
||||
|
||||
assert_eq!(seq.len(), n);
|
||||
assert_eq!(par.len(), n);
|
||||
|
||||
let (max_diff, (i, k)) = max_abs_diff(&seq, &par);
|
||||
assert!(
|
||||
max_diff <= 1e-9,
|
||||
"K=4: max abs diff {max_diff:e} exceeds 1e-9 at row {i}, dim {k} (seq={}, par={})",
|
||||
seq[i][k],
|
||||
par[i][k],
|
||||
);
|
||||
|
||||
// Sanity: at least some non-zero output (otherwise the test is vacuous).
|
||||
let non_zero = seq.iter().filter(|r| r.iter().any(|&v| v != 0.0)).count();
|
||||
assert!(
|
||||
non_zero > n / 2,
|
||||
"expected most rows non-zero, got {non_zero}/{n}"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parallel_matches_sequential_within_1e9_k8() {
|
||||
const WARMUP: usize = 50;
|
||||
let n = 5500;
|
||||
let bars = make_bars(WARMUP + n, 5000.0);
|
||||
let snaps = make_snapshots(&bars, "ES.FUT");
|
||||
let trades = make_trades(&bars);
|
||||
|
||||
let inputs = PerBarOfiInputs {
|
||||
bars: &bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &snaps,
|
||||
trades: Some(&trades),
|
||||
};
|
||||
|
||||
let seq = compute_ofi_per_bar_sequential(&inputs);
|
||||
let par = compute_ofi_per_bar_parallel(&inputs, 8, DEFAULT_OFI_PARALLEL_WARMUP_BARS);
|
||||
|
||||
let (max_diff, (i, k)) = max_abs_diff(&seq, &par);
|
||||
assert!(
|
||||
max_diff <= 1e-9,
|
||||
"K=8: max abs diff {max_diff:e} exceeds 1e-9 at row {i}, dim {k} (seq={}, par={})",
|
||||
seq[i][k],
|
||||
par[i][k],
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parallel_k1_is_sequential() {
|
||||
const WARMUP: usize = 50;
|
||||
let n = 1500;
|
||||
let bars = make_bars(WARMUP + n, 5000.0);
|
||||
let snaps = make_snapshots(&bars, "ES.FUT");
|
||||
let trades = make_trades(&bars);
|
||||
|
||||
let inputs = PerBarOfiInputs {
|
||||
bars: &bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &snaps,
|
||||
trades: Some(&trades),
|
||||
};
|
||||
|
||||
let seq = compute_ofi_per_bar_sequential(&inputs);
|
||||
let par = compute_ofi_per_bar_parallel(&inputs, 1, DEFAULT_OFI_PARALLEL_WARMUP_BARS);
|
||||
|
||||
let (max_diff, _) = max_abs_diff(&seq, &par);
|
||||
// K=1 must be byte-identical (same code path).
|
||||
assert_eq!(max_diff, 0.0, "K=1 should be byte-identical to sequential");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parallel_handles_no_trades() {
|
||||
const WARMUP: usize = 50;
|
||||
let n = 800;
|
||||
let bars = make_bars(WARMUP + n, 5000.0);
|
||||
let snaps = make_snapshots(&bars, "ES.FUT");
|
||||
|
||||
let inputs = PerBarOfiInputs {
|
||||
bars: &bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &snaps,
|
||||
trades: None,
|
||||
};
|
||||
|
||||
let seq = compute_ofi_per_bar_sequential(&inputs);
|
||||
let par = compute_ofi_per_bar_parallel(&inputs, 4, DEFAULT_OFI_PARALLEL_WARMUP_BARS);
|
||||
|
||||
let (max_diff, (i, k)) = max_abs_diff(&seq, &par);
|
||||
assert!(
|
||||
max_diff <= 1e-9,
|
||||
"no-trades: max abs diff {max_diff:e} at row {i}, dim {k}"
|
||||
);
|
||||
}
|
||||
|
||||
/// Speedup smoke — `#[ignore]`'d because it's bench-shaped, not
|
||||
/// assertion-shaped. Run via `cargo test ... -- --ignored --nocapture`.
|
||||
///
|
||||
/// At production scale (~50k bars × ~3 snapshots/bar × ~5 trades/bar) the
|
||||
/// 5000-bar warmup amortises across each shard's core range so K=8 gives
|
||||
/// meaningful speedup. For small N (≤8k) the warmup overhead dominates
|
||||
/// and parallel can be slightly slower than sequential — this is by
|
||||
/// design (warmup must be ≥ rolling-window depth for bit-equivalence).
|
||||
///
|
||||
/// `precompute_features.rs` typically runs at N ≥ 20k bars where the
|
||||
/// speedup is realised.
|
||||
#[test]
|
||||
#[ignore = "bench-shaped; run with --ignored --nocapture for human review"]
|
||||
fn parallel_speedup_smoke() {
|
||||
const WARMUP: usize = 50;
|
||||
for &n in &[8000_usize, 30_000, 80_000] {
|
||||
let bars = make_bars(WARMUP + n, 5000.0);
|
||||
let snaps = make_snapshots(&bars, "ES.FUT");
|
||||
let trades = make_trades(&bars);
|
||||
|
||||
let inputs = PerBarOfiInputs {
|
||||
bars: &bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &snaps,
|
||||
trades: Some(&trades),
|
||||
};
|
||||
|
||||
let t0 = std::time::Instant::now();
|
||||
let seq = compute_ofi_per_bar_sequential(&inputs);
|
||||
let dt_seq = t0.elapsed();
|
||||
|
||||
let t1 = std::time::Instant::now();
|
||||
let par =
|
||||
compute_ofi_per_bar_parallel(&inputs, 8, DEFAULT_OFI_PARALLEL_WARMUP_BARS);
|
||||
let dt_par = t1.elapsed();
|
||||
|
||||
let (max_diff, _) = max_abs_diff(&seq, &par);
|
||||
assert!(max_diff <= 1e-9, "speedup test diverged: {max_diff:e}");
|
||||
|
||||
println!(
|
||||
"OFI per-bar smoke: n={n} bars, seq={:.2}ms, par(K=8)={:.2}ms, speedup={:.2}x",
|
||||
dt_seq.as_secs_f64() * 1000.0,
|
||||
dt_par.as_secs_f64() * 1000.0,
|
||||
dt_seq.as_secs_f64() / dt_par.as_secs_f64().max(1e-9),
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -495,7 +495,6 @@ async fn main() -> Result<()> {
|
||||
let ofi: Vec<[f64; OFI_DIM]> = if let Some(ref mbp10_path) = mbp10_dir {
|
||||
use ml::features::mbp10_loader::load_ofi_features_parallel;
|
||||
use ml::features::trades_loader::load_trades_sync;
|
||||
use ml::features::ofi_calculator::OFICalculator;
|
||||
|
||||
info!("Loading MBP-10 snapshots from {}...", mbp10_path.display());
|
||||
let mut mbp10_files = collect_dbn_files_recursive(mbp10_path);
|
||||
@@ -572,166 +571,46 @@ async fn main() -> Result<()> {
|
||||
None
|
||||
};
|
||||
|
||||
// Compute per-bar OFI
|
||||
use ml::features::trades_loader::get_trades_for_bar;
|
||||
use ml::features::ofi_calculator::MicrostructureState;
|
||||
let mut calculator = OFICalculator::new();
|
||||
let mut ofi_per_bar = Vec::with_capacity(n);
|
||||
|
||||
for i in 0..n {
|
||||
let bar = &all_bars[i + WARMUP];
|
||||
// Bar timestamp = close-time of bar (volume bars: last trade in bucket;
|
||||
// see `crates/ml-features/src/trades_loader.rs:124-176`). The OFI window
|
||||
// for bar t is therefore the *formation interval*
|
||||
// `(close(bar_{t-1}), close(bar_t)]` — strictly historical relative to
|
||||
// the policy's decision time at bar t. The previous implementation used
|
||||
// `[close(bar_t), close(bar_{t+1}))` which leaks bar t+1's microstructure
|
||||
// (audit `docs/lookahead-bias-audit-2026-04-28.md` §3, 31/32 OFI dims).
|
||||
// Mirrors the backward-looking convention already used by
|
||||
// `log_bar_duration` below at lines 567-575.
|
||||
let bar_ts = bar.timestamp.timestamp_nanos_opt().unwrap_or(0) as u64;
|
||||
let bar_start_ts = if i + WARMUP >= 1 {
|
||||
all_bars[i + WARMUP - 1].timestamp.timestamp_nanos_opt().unwrap_or(0) as u64
|
||||
} else {
|
||||
// No prior bar — emit empty window. log_bar_duration uses the same
|
||||
// sentinel pathway (60s default) for bar 0; here we simply skip
|
||||
// population so OFI[0] stays zero (consistent with existing
|
||||
// first-bar delta handling at lines 558-562).
|
||||
bar_ts
|
||||
};
|
||||
let bar_duration_ns = bar_ts.saturating_sub(bar_start_ts);
|
||||
|
||||
let mut micro_state = MicrostructureState::new(bar_start_ts, bar_duration_ns);
|
||||
|
||||
// Feed trades for this bar window (OFICalculator + MicrostructureState).
|
||||
// Window is half-open at the start, closed at the end:
|
||||
// `(close(bar_{t-1}), close(bar_t)]` so trade-at-close (which formed bar t)
|
||||
// is included.
|
||||
if let Some(ref trades) = all_trades {
|
||||
for trade in get_trades_for_bar(trades, bar_start_ts, bar_ts.saturating_add(1)) {
|
||||
calculator.feed_trade(trade.price, trade.volume, trade.is_buy);
|
||||
micro_state.update_trade(trade.price, trade.volume, trade.is_buy, trade.timestamp);
|
||||
}
|
||||
}
|
||||
|
||||
// Get ALL MBP-10 snapshots within this bar window for tick-level features.
|
||||
// Binary search for bar range: (bar_start_ts, bar_ts] — formation interval.
|
||||
let snap_start = all_snapshots.partition_point(|s| s.timestamp <= bar_start_ts);
|
||||
let snap_end = all_snapshots.partition_point(|s| s.timestamp <= bar_ts);
|
||||
let bar_snapshots = &all_snapshots[snap_start..snap_end];
|
||||
|
||||
// Feed every snapshot to MicrostructureState for tick-level resolution
|
||||
for snap in bar_snapshots {
|
||||
micro_state.update_snapshot(snap);
|
||||
}
|
||||
|
||||
// Use the LAST snapshot in the bar for OFI calculation (matches prior behavior)
|
||||
let last_snap = bar_snapshots.last()
|
||||
.or_else(|| {
|
||||
// Fallback: nearest snapshot at/after bar_ts (prior behavior)
|
||||
all_snapshots.get(snap_start)
|
||||
});
|
||||
|
||||
if let Some(snap) = last_snap {
|
||||
match calculator.calculate(snap) {
|
||||
Ok(f) if f.is_valid() => {
|
||||
// Feed OFI-derived values to MicrostructureState
|
||||
micro_state.update_ofi_derived(f.ofi_level1, f.vpin);
|
||||
|
||||
let arr8 = f.to_array();
|
||||
let micro_12 = micro_state.snapshot();
|
||||
// v5 OFI layout (see state_layout.rs OFI slot map):
|
||||
// [0..8) raw OFI (8 features)
|
||||
// [8..16) lag-1 deltas (filled in post-loop)
|
||||
// [16] book_aggression (filled below)
|
||||
// [17] log_bar_duration (filled in post-loop)
|
||||
// [18] ofi_acceleration (micro_12[10])
|
||||
// [19] toxicity_gradient (micro_12[11])
|
||||
// [20..30) MicrostructureState::snapshot()[0..10]
|
||||
// [30] order_count_imbalance ((Σbid_ct − Σask_ct) / Σ(bid_ct+ask_ct))
|
||||
// [31] microprice_residual ((weighted_mid − mid) / mid)
|
||||
let mut ofi_row = [0.0_f64; OFI_DIM];
|
||||
ofi_row[..8].copy_from_slice(&arr8);
|
||||
ofi_row[18] = micro_12[10]; // ofi_acceleration
|
||||
ofi_row[19] = micro_12[11]; // toxicity_gradient
|
||||
for k in 0..10 {
|
||||
ofi_row[20 + k] = micro_12[k];
|
||||
}
|
||||
// TLOB-novel slots: derive directly from Mbp10Snapshot counts/prices.
|
||||
// order_count_imbalance: count-based analog to depth_imbalance.
|
||||
let (bid_ct_sum, ask_ct_sum) = snap.levels.iter().fold((0u64, 0u64), |(b, a), l| {
|
||||
(b + l.bid_ct as u64, a + l.ask_ct as u64)
|
||||
});
|
||||
let total_ct = bid_ct_sum + ask_ct_sum;
|
||||
let order_count_imbalance = if total_ct > 0 {
|
||||
(bid_ct_sum as f64 - ask_ct_sum as f64) / total_ct as f64
|
||||
} else {
|
||||
0.0
|
||||
};
|
||||
ofi_row[30] = order_count_imbalance.clamp(-1.0, 1.0);
|
||||
// microprice_residual: (weighted_mid − mid) / mid; dimensionless.
|
||||
// Mbp10Snapshot::weighted_mid_price() uses top-of-book volume-weighted mid.
|
||||
let mid = snap.mid_price();
|
||||
let wmid = snap.weighted_mid_price();
|
||||
let microprice_residual = if mid > 0.0 && mid.is_finite() && wmid.is_finite() {
|
||||
((wmid - mid) / mid).clamp(-0.01, 0.01)
|
||||
} else {
|
||||
0.0
|
||||
};
|
||||
ofi_row[31] = microprice_residual;
|
||||
ofi_per_bar.push(ofi_row);
|
||||
}
|
||||
_ => ofi_per_bar.push([0.0; OFI_DIM]),
|
||||
}
|
||||
} else {
|
||||
ofi_per_bar.push([0.0; OFI_DIM]);
|
||||
}
|
||||
|
||||
// ── Book aggression: center-of-mass asymmetry from MBP-10 depth ──
|
||||
// Uses the last snapshot in the bar window (same as OFI calculation above)
|
||||
if let Some(snap) = bar_snapshots.last() {
|
||||
let mut buy_weighted_sum = 0.0_f64;
|
||||
let mut buy_total = 0.0_f64;
|
||||
let mut sell_weighted_sum = 0.0_f64;
|
||||
let mut sell_total = 0.0_f64;
|
||||
for (level, pair) in snap.levels.iter().enumerate().take(10) {
|
||||
let bid_size = pair.bid_sz as f64;
|
||||
let ask_size = pair.ask_sz as f64;
|
||||
buy_weighted_sum += (level + 1) as f64 * bid_size;
|
||||
buy_total += bid_size;
|
||||
sell_weighted_sum += (level + 1) as f64 * ask_size;
|
||||
sell_total += ask_size;
|
||||
}
|
||||
let buy_com = if buy_total > 0.0 { buy_weighted_sum / buy_total } else { 5.5 };
|
||||
let sell_com = if sell_total > 0.0 { sell_weighted_sum / sell_total } else { 5.5 };
|
||||
let book_aggression = (sell_com - buy_com) / 10.0; // normalize to [-1, 1]
|
||||
if let Some(last) = ofi_per_bar.last_mut() {
|
||||
last[16] = book_aggression;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ── OFI temporal deltas: delta[bar] = ofi[bar] - ofi[bar-1] ──
|
||||
// Computed after all bars so we have the full sequence
|
||||
for i in (1..ofi_per_bar.len()).rev() {
|
||||
for k in 0..8 {
|
||||
ofi_per_bar[i][8 + k] = ofi_per_bar[i][k] - ofi_per_bar[i - 1][k];
|
||||
}
|
||||
}
|
||||
// First bar has no previous — deltas are zero (already initialized)
|
||||
|
||||
// ── Log bar duration: ln(duration_secs) / 10.0 ──
|
||||
for i in 0..n {
|
||||
let duration_secs = if i > 0 {
|
||||
let ts_cur = all_bars[i + WARMUP].timestamp;
|
||||
let ts_prev = all_bars[i + WARMUP - 1].timestamp;
|
||||
(ts_cur - ts_prev).num_seconds() as f64
|
||||
} else {
|
||||
60.0 // default 1 minute for first bar
|
||||
};
|
||||
let log_duration = duration_secs.max(0.1).ln() / 10.0;
|
||||
ofi_per_bar[i][17] = log_duration;
|
||||
}
|
||||
// ── Per-bar OFI extraction (SP20 parallel via time-bucket sharding) ──
|
||||
//
|
||||
// Replaces a sequential 132-line loop with a call into the
|
||||
// `ml-features` library function. Sharding strategy: K shards
|
||||
// process contiguous bar ranges in parallel; each shard owns a
|
||||
// freshly-cloned `OFICalculator` and replays a `WARMUP_BARS` prefix
|
||||
// of its range to populate rolling-window state (VPIN/Kyle/
|
||||
// trade-imb/OFI-stats/prev-snap) to bit-identical sequential-walk
|
||||
// state at the warmup→core boundary. Post-loop passes (lag-1
|
||||
// deltas, log_bar_duration) are pure functions of the full output
|
||||
// and run sequentially after concatenation.
|
||||
//
|
||||
// Bit-equivalence is verified in
|
||||
// `crates/ml-features/tests/ofi_parallel_bit_equiv_test.rs`.
|
||||
//
|
||||
// Shard count: from `OFI_SHARD_COUNT` env (override) or rayon's
|
||||
// current thread pool (`ci-compile-cpu` = 28 cores). Capped at
|
||||
// `n` shards. Set to 1 to disable parallelism (matches previous
|
||||
// sequential behaviour exactly).
|
||||
let shard_count: usize = std::env::var("OFI_SHARD_COUNT")
|
||||
.ok()
|
||||
.and_then(|s| s.parse::<usize>().ok())
|
||||
.unwrap_or_else(rayon::current_num_threads);
|
||||
let inputs = ml::features::PerBarOfiInputs {
|
||||
bars: &all_bars,
|
||||
warmup: WARMUP,
|
||||
n,
|
||||
snapshots: &all_snapshots,
|
||||
trades: all_trades.as_deref(),
|
||||
};
|
||||
let ofi_per_bar = ml::features::compute_ofi_per_bar_parallel(
|
||||
&inputs,
|
||||
shard_count,
|
||||
ml::features::DEFAULT_OFI_PARALLEL_WARMUP_BARS,
|
||||
);
|
||||
info!(
|
||||
"OFI per-bar extraction: {} shards, warmup={} bars",
|
||||
shard_count.max(1).min(n),
|
||||
ml::features::DEFAULT_OFI_PARALLEL_WARMUP_BARS,
|
||||
);
|
||||
|
||||
let delta_nonzero = ofi_per_bar.iter().filter(|f| f[8..16].iter().any(|&v| v != 0.0)).count();
|
||||
let book_nonzero = ofi_per_bar.iter().filter(|f| f[16] != 0.0).count();
|
||||
|
||||
Reference in New Issue
Block a user