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
This commit is contained in:
kingchenc
2026-06-15 04:48:51 +02:00
committed by GitHub
parent de1112ea91
commit 4f708d410d
573 changed files with 102337 additions and 77 deletions
+81
View File
@@ -0,0 +1,81 @@
Autocorrelation
nan
nan
nan
nan
nan
nan
nan
nan
nan
0.6350373907840188
0.5405958230224509
0.5715509867319618
0.6847209376927287
0.7382107181033117
0.7579207987906323
0.762822432921618
0.7572980491605352
0.7363889001173629
0.6799889443191299
0.5648879977703694
0.54489228047915
0.6396550255535112
0.6974753084777462
0.7246269314937726
0.737356237098341
0.7424339180343317
0.7421497527004213
0.7363829456099225
0.7224953185679739
0.692943015254534
0.6302595069491079
0.5367533355339029
0.578450958314291
0.6892271578296308
0.7399336462425192
0.758500447439642
0.7627917441846417
0.7566305617172937
0.7344628307695249
0.6750260473147637
0.5585359164341555
0.5495761556376604
0.6441109481859122
0.6995996374123962
0.7256276173803344
0.737808053951148
0.7425514974267139
0.7419828113973262
0.735860098072037
0.7213607302420498
0.690526496586784
0.625324582684563
0.5334303166974939
0.585517119455116
0.6935137858338126
0.7415627500956398
0.7590385074166992
0.7627302918469656
0.7559165686210035
0.7324268451189209
0.6698284783594914
0.5525700479734488
0.5545816350091717
0.6484051513599884
0.701634870935319
0.7265871731416474
0.7382375020131329
0.7426529432973633
0.741799024970625
0.7353121322341262
0.720177679673926
0.6880037896027371
0.6202378952393583
0.5306891887744772
0.5926832075977227
0.6975877865016052
0.7431028082864907
0.7595363725248612
0.7626379258822382
0.7551541640582837
1 Autocorrelation
2 nan
3 nan
4 nan
5 nan
6 nan
7 nan
8 nan
9 nan
10 nan
11 0.6350373907840188
12 0.5405958230224509
13 0.5715509867319618
14 0.6847209376927287
15 0.7382107181033117
16 0.7579207987906323
17 0.762822432921618
18 0.7572980491605352
19 0.7363889001173629
20 0.6799889443191299
21 0.5648879977703694
22 0.54489228047915
23 0.6396550255535112
24 0.6974753084777462
25 0.7246269314937726
26 0.737356237098341
27 0.7424339180343317
28 0.7421497527004213
29 0.7363829456099225
30 0.7224953185679739
31 0.692943015254534
32 0.6302595069491079
33 0.5367533355339029
34 0.578450958314291
35 0.6892271578296308
36 0.7399336462425192
37 0.758500447439642
38 0.7627917441846417
39 0.7566305617172937
40 0.7344628307695249
41 0.6750260473147637
42 0.5585359164341555
43 0.5495761556376604
44 0.6441109481859122
45 0.6995996374123962
46 0.7256276173803344
47 0.737808053951148
48 0.7425514974267139
49 0.7419828113973262
50 0.735860098072037
51 0.7213607302420498
52 0.690526496586784
53 0.625324582684563
54 0.5334303166974939
55 0.585517119455116
56 0.6935137858338126
57 0.7415627500956398
58 0.7590385074166992
59 0.7627302918469656
60 0.7559165686210035
61 0.7324268451189209
62 0.6698284783594914
63 0.5525700479734488
64 0.5545816350091717
65 0.6484051513599884
66 0.701634870935319
67 0.7265871731416474
68 0.7382375020131329
69 0.7426529432973633
70 0.741799024970625
71 0.7353121322341262
72 0.720177679673926
73 0.6880037896027371
74 0.6202378952393583
75 0.5306891887744772
76 0.5926832075977227
77 0.6975877865016052
78 0.7431028082864907
79 0.7595363725248612
80 0.7626379258822382
81 0.7551541640582837