Commit Graph
5 Commits
Author SHA1 Message Date
kingchencandGitHub cb6da4d737 feat(data-layer): Resampler (candle resampling) in all 10 languages (#310)
* feat(data-layer): Resampler (candle resampling) in all 10 languages

Second data-layer feature (F3): resample candles into a higher timeframe.

- Native (Node.js/WASM): new Resampler(timeframe) -> update(o,h,l,c,v,ts):
  Candle|null + flush(): Candle|null. Python the same -> tuple|None.
- C ABI: wickra_resampler_new/update/flush/free (update has the multi-output
  shape so the generators auto-emit it; flush is bespoke). Go Update -> (Candle,
  bool) + Flush; C# Candle? Update/Flush; Java Candle update/flush; R update()
  generic + a flush() S3 method (extends base::flush); C/C++ direct.
- Cross-language golden (testdata/golden/data_resampled.csv): the shared input
  candles resampled into 5-unit buckets, the final partial bucket via flush,
  pinned bit-for-bit across every binding.

Verified locally in all 10 (3 candles for the 5-unit smoke; 16 for the golden).
The WickraCandle output record is shared with the tick aggregator (deduped).

* test(node): exclude data-layer types from the indicator completeness contract

The Resampler exposes update(), so the completeness test flagged it as an
indicator and required batch/reset/isReady/warmupPeriod, which a data-layer type
does not have. Exclude TickAggregator and Resampler like the bar builders.
2026-06-15 22:36:16 +02:00
kingchencandGitHub 8a103ef920 feat(data-layer): TickAggregator (tick-to-candle) in all 10 languages (#309)
* feat(data-layer): TickAggregator in Node, WASM, Python + C ABI hub

First data-layer feature (F2): roll trade ticks up into fixed-timeframe OHLCV
candles, exposed natively and over the C ABI.

- wickra-data wired as a binding dependency (workspace dep; its wickra-core dep
  is default-features=false so it never forces rayon into the rayon-free WASM
  build — native bindings re-enable parallel through their own dependency).
- Node `TickAggregator(bucket, gapFill?)` -> `push(price, size, ts): Candle[]`;
  WASM the same (array of objects); Python `push(...) -> list[tuple]`.
- C ABI: `WickraCandle` struct + `wickra_tick_aggregator_new/push/free` (push
  writes candles into a caller buffer and returns the count), generated via the
  capi generator's new DATA_LAYER section; cbindgen now parses wickra-data so
  `TickAggregator` is a forward-declared opaque; header vendored to bindings/go.

Verified bit-identical across Node/WASM/Python/C/C++ (o=100 h=101 l=100 c=101
v=3 ts=0 for the shared 3-tick probe). WIP: Go/C#/Java/R generated bindings and
the cross-language golden are still pending.

* feat(data-layer): TickAggregator in Go, C#, Java, R (lossless push/drain)

Complete F2 across all 10 languages: the C-ABI tick aggregator now uses a
two-step push/drain so gap-fill candles are never lost, and the four generated
bindings expose it idiomatically.

- C ABI redesigned: opaque TickAggregator handle (inner aggregator + pending
  buffer); push consumes a tick and returns the closed-candle count, drain copies
  them into a count-sized caller buffer.
- Go: NewTickAggregator + Push(price,size,ts) []Candle; C#: TickAggregator +
  Candle[] Push(...); Java: TickAggregator + Candle[] push(...); R: TickAggregator
  constructor + push() S3 generic returning an (n x 6) numeric matrix.
- Candle output record generated per language from WickraCandle.

Verified bit-identical to the native bindings (o=100 h=101 l=100 c=101 v=3 ts=0)
in Go, C#, Java, and R at runtime; R passes R CMD check (pre-existing doc
warnings only). WIP: cross-language data-layer golden + CHANGELOG still pending.

* test(data-layer): cross-language golden for the tick aggregator + CHANGELOG

gen_golden emits a deterministic tick stream (testdata/golden/data_ticks.csv) and
the reference candle streams with and without gap filling (data_candles.csv,
data_candles_gap.csv). Every binding replays the shared ticks through its
TickAggregator and checks the candles bit-for-bit (fp tolerance) against the Rust
reference:

- Node / WASM / Python / Go / C# / Java / R: a dedicated parity test each.
- C / C++: data_layer_test.c (compiled as both, run as ctest).

The gap-fill fixture closes several candles from a single push, exercising the
lossless push/drain path. Records the feature under CHANGELOG [Unreleased].

* fix(examples): rename the CSV-loader candle to WickraBar

The example CSV helper (wickra_csv.h) defined its own struct WickraCandle, which
now collides with the public C ABI WickraCandle (the tick aggregator output) in
any example that includes both headers (backtest, multi_timeframe, the strategy
examples). The public type owns the name; rename the example loader's bar to
WickraBar. The generated golden_test.c is untouched (its only match was the
unrelated WickraCandleVolumeOutput).
2026-06-15 21:24:33 +02:00
kingchencandGitHub 4f708d410d test: golden-pin the four de-duplicated indicators across all bindings (#305)
* test: golden-pin the four de-duplicated indicators across all C-ABI bindings

Extend gen_golden to emit reference fixtures for AdOscillator (ADOSC),
IntradayIntensity, AwesomeOscillatorHistogram and AverageDrawdown, and replay
them through the Go / C# / Java / R golden harnesses so their corrected
definitions stay bit-identical to the Rust core in every binding. Go suite
verified locally (gcc 13 + cgo): all 9 golden tests pass; C#/Java/R use the
same fixtures and harness pattern (CI-verified). First step of extending the
golden coverage beyond the seven archetype representatives.

* test: golden-pin the scalar-output tranche (308 indicators) against Rust

Extend gen_golden with a generated emit_scalar that writes reference fixtures
for every single-f64-output indicator (scalar / candle / pairwise input) using
valid constructor params, and add a manifest-driven generic Python golden
replay that reconstructs each by its native name and checks it bit-for-bit
against the Rust output. 308 indicators now value-tied to the Rust core in
Python (pytest: 308/308). Takes golden coverage from the 7 archetype
representatives to 308+ of the catalogue.

22 scalar indicators with non-default constructor constraints are skipped by
gen_golden for now (logged), as are non-f64-output ones; multi-output, exotic
inputs and the per-indicator arg arities of the C-ABI/Node replays follow.
Generated + verified locally with the full toolchain.

* test: golden-pin the multi-output tranche (70 indicators) in Python

Add a generated emit_multi to gen_golden (per-indicator Output-field access,
one CSV column per field) and a manifest-driven generic Python replay that
checks every field of each multi-output indicator against the Rust reference.
70 multi-output indicators now value-tied to Rust in Python; combined with the
scalar tranche, 378 indicators are golden-pinned. 8 multi with non-default
param constraints and 5 with non-f64 Output fields (Option/Vec/i64) are
deferred. pytest green.

* test(golden): add 30 constraint-tuned indicators to scalar/multi golden suite

Emit golden fixtures for 22 scalar-output and 8 multi-output indicators
whose constructors need non-default parameters (Alma, Jma, Psar, T3, Mama,
DoubleBollinger, ZigZag, ...). All 408 fixtures replay bit-for-bit through
the Python binding.

* test(golden): cover 36 missed scalar/multi indicators

Add 26 single-output (LinearRegression family, HT cycle, Candle
volatility estimators, DrawdownDuration) and 10 multi-output
(BollingerBands, MACD/MACDEXT/MACDFIX, Camarilla, VWAP bands, ...)
indicators to the golden suite. 444 fixtures replay bit-for-bit
through the Python binding.

* test(golden): cover 50 exotic-input indicators

Add deterministic synthetic feeders for the DerivativesTick (17),
CrossSection (15), Trade (8), TradeQuote (3) and OrderBook (7)
families, derived from the shared OHLCV input series in both
gen_golden and a new Python replay harness (test_golden_exotic).
All 494 fixtures replay bit-for-bit through the Python binding.

* test(golden): complete 514-indicator golden coverage

Add the final tranches: 3 mixed multi-output indicators (Ichimoku,
WilliamsFractals, LeadLagCrossCorrelation), 6 histogram profiles
(time/volume seasonality + TPO/volume price profiles), 10 alt-chart
bar builders and the footprint. Every one of the 514 distinct
indicators now has a Rust-generated g_<Canonical>.csv fixture and a
generic Python replay (scalar/multi/exotic/profile/bars), all passing
bit-for-bit.

* test(golden): add generic Node replay for all 514 indicators

A manifest-driven node:test harness reconstructs every indicator by its
native class, feeds the same synthetic stream derived from the shared
golden input, and checks output bit-for-bit against the Rust reference
fixtures (scalar/multi/exotic/profile/bars). node_manifest.json is
generated from index.d.ts plus the Python-side manifests. 514/514 pass.

* test(golden): add generated Go replay for all 514 indicators

golden_all_test.go (generated by gen_golden_test.py) reconstructs every
Go indicator, feeds the shared synthetic stream and checks output
bit-for-bit against the Rust reference fixtures. A reflection-based
comparator flattens multi-output structs, profiles and bar slices so one
path covers all archetypes. This is the first C-ABI binding verified
across the full catalogue. 514/514 pass.

* test(golden): add generated C# replay for all 514 indicators

GoldenAllTests.g.cs (generated by gen_golden_test.py) reconstructs every
C# indicator, feeds the shared synthetic stream and checks output
bit-for-bit against the Rust reference fixtures via a reflection-based
flatten covering scalar/multi/profile/bar archetypes. 514/514 pass.

Also add the '#nullable enable' directive the compiler requires to the
generated Indicators.g.cs, clearing the four CS8669 warnings on the
nullable double[] profile return types.

* fix(java): marshal C ABI bool params correctly; add 514 golden replay

The Java FFM binding marshalled the cross-section state flags (newHigh,
newLow, aboveMa, onBuySignal) as JAVA_DOUBLE arrays, but the C ABI takes
them as const bool* (one byte each), so the native side read the low byte
of each 8-byte double and saw every flag as false. Add WickraNative.
boolSegment and use it across the 15 cross-section indicators. Also pass
the MacdExt MaType arguments as byte to match the uint8_t downcall
descriptor (was int, throwing WrongMethodTypeException).

Add GoldenAllTest.java (generated by gen_golden_test.py): a reflection
runner replaying all 514 indicators against the Rust reference fixtures.
The bugs above were found by this test; 514/514 now pass.

* fix(r): marshal C ABI bool flags correctly; add 514 golden replay

The R wrapper passed the cross-section state flags as (bool *)REAL(x),
reinterpreting the 8-byte doubles as 1-byte bools so the native side read
every flag as false. Add wk_bool_vec to convert each flag vector into a
real C bool buffer and use it for all 15 cross-section update wrappers.

Add test-golden-all.R + generated golden_specs.R: a reflective runner
replaying all 514 indicators against the Rust reference fixtures. The bug
above was found by this test; verified 514/514 pass locally.

* test(golden): add WASM replay for all 514 indicators

A manifest-driven node:test harness loads the nodejs-target wasm-pack
build, reconstructs every indicator by its JS class, feeds the shared
synthetic stream and checks output bit-for-bit against the Rust
reference fixtures. wasm_manifest.json is generated from the wasm .d.ts
plus the shared manifests; a recursive flattener covers scalar, multi
(Reflect objects), profile and bar shapes. 514/514 pass locally
(wasm-pack build --target nodejs, then node --test).

* test(golden): add C and C++ replay for all 514 indicators

golden_test.c (generated by gen_golden_test.py) drives every indicator
through the C ABI (wickra.h) and checks output bit-for-bit against the
Rust reference fixtures. golden_test.cpp #includes the same source so the
identical runner is compiled and run under both gcc (C) and g++ (C++) via
the CMake targets golden_test / golden_test_cpp — proving the extern "C"
header is consumable from each language. Both 514/514 (verified via ctest).

* test(golden): gofmt the generated Go golden replay

* test(golden): make the Node fixture reader CRLF-safe and pin fixtures to LF
2026-06-15 04:48:51 +02:00
kingchencandGitHub 2ef60874b9 fix(examples): satisfy clippy -D warnings in gen_golden (#291)
Replace `i as i64` with `i64::try_from(i)` (cast_possible_wrap) and rename
the OHLCV destructure to descriptive names (many_single_char_names) so
`cargo clippy --all-targets --all-features -- -D warnings` passes on the 1.95
toolchain. Dev-tool only; no library change.
2026-06-13 23:35:29 +02:00
kingchencandGitHub 8bfe24ac1d test(golden): language-neutral fixtures + per-binding parity runners (#255)
**Task 5 — golden-fixture parity for the C-ABI bindings.** Lifts the C#/Go/Java/R tests from *one indicator per archetype* toward reference-value parity, catching FFI wiring bugs (swapped params, wrong multi-output field) the math-only core tests cannot see.

## What's here
- **`examples/rust/src/bin/gen_golden.rs`** + **`testdata/golden/*.csv`** — a Rust generator computing a deterministic OHLCV series plus the core's reference outputs for a curated archetype-spanning set: scalar (`Sma`/`Ema`/`Rsi`), candle (`Atr`), scalar multi-output (`MACD`), candle multi-output (`ADX`), pairwise (`Beta`). `nan` marks warmup. Regenerate with `cargo run -p wickra-examples --bin gen_golden`.
- **Parity runners** replaying the identical fixtures through each FFI (rel-tol 1e-6), each a standard test in the binding's existing suite (no `ci.yml` change — rides `dotnet test` / `go test` / `mvn install` / `R CMD`+testthat). A walk-up search locates `testdata/golden` regardless of run dir.
  - **C#** (`bindings/csharp/.../GoldenTests.cs`) —  validated locally, 7/7 pass.
  - **Go** (`bindings/go/golden_test.go`) —  validated locally, pass.
  - **Java** (`bindings/java/.../GoldenTests.java`) — modeled on the archetype API; validated by CI (no local mvn).
  - **R** (`bindings/r/tests/testthat/test-golden.R`) — modeled on the archetype API; validated by CI (no local Rscript).

## Notes
- The curated set spans every marshalling archetype; extending the indicator list is mechanical (add to the generator + regenerate). Bars/profile archetypes can be added next.
- No new CI jobs.
2026-06-11 15:22:29 +02:00