* 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
251 lines
6.0 KiB
Go
251 lines
6.0 KiB
Go
package wickra
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import (
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"bufio"
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"math"
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"os"
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"strconv"
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"strings"
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"testing"
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)
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// Golden-fixture parity: replay the shared testdata/golden input series through
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// the Go FFI and assert every value matches the Rust reference output. Where the
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// archetype test only checks finiteness, this pins exact values, catching wiring
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// bugs (swapped params, wrong multi-output field). Fixtures are generated by
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// `cargo run -p wickra-examples --bin gen_golden`.
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const goldenTol = 1e-6
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func readGolden(t *testing.T, name string) [][]string {
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t.Helper()
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f, err := os.Open("../../testdata/golden/" + name + ".csv")
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if err != nil {
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t.Fatalf("open %s: %v", name, err)
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}
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defer f.Close()
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var rows [][]string
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sc := bufio.NewScanner(f)
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first := true
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for sc.Scan() {
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line := sc.Text()
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if first {
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first = false
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continue
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}
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if line == "" {
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continue
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}
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rows = append(rows, strings.Split(line, ","))
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}
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return rows
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}
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func goldenCell(s string) float64 {
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if s == "nan" {
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return math.NaN()
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}
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v, _ := strconv.ParseFloat(s, 64)
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return v
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}
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func goldenInput(t *testing.T) [][]float64 {
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rows := readGolden(t, "input")
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out := make([][]float64, len(rows))
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for i, r := range rows {
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vals := make([]float64, len(r))
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for j, c := range r {
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vals[j] = goldenCell(c)
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}
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out[i] = vals
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}
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return out
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}
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func assertGoldenClose(t *testing.T, got, want float64, row int, field string) {
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t.Helper()
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if math.IsNaN(want) {
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if !math.IsNaN(got) {
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t.Errorf("row %d %s: expected warmup/NaN, got %v", row, field, got)
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}
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return
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}
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tol := goldenTol * math.Max(1.0, math.Abs(want))
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if math.Abs(got-want) > tol {
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t.Errorf("row %d %s: got %v want %v", row, field, got, want)
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}
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}
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func TestGoldenScalar(t *testing.T) {
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input := goldenInput(t)
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sma, err := NewSma(14)
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if err != nil {
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t.Fatal(err)
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}
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defer sma.Close()
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ema, err := NewEma(14)
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if err != nil {
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t.Fatal(err)
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}
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defer ema.Close()
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rsi, err := NewRsi(14)
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if err != nil {
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t.Fatal(err)
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}
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defer rsi.Close()
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cases := []struct {
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name string
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upd func(close float64) float64
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}{
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{"sma", sma.Update},
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{"ema", ema.Update},
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{"rsi", rsi.Update},
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}
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for _, tc := range cases {
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exp := readGolden(t, tc.name)
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for i := range input {
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assertGoldenClose(t, tc.upd(input[i][3]), goldenCell(exp[i][0]), i, tc.name)
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}
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}
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}
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func TestGoldenAtr(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "atr")
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atr, err := NewAtr(14)
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if err != nil {
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t.Fatal(err)
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}
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defer atr.Close()
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for i := range input {
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got := atr.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], int64(i))
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assertGoldenClose(t, got, goldenCell(exp[i][0]), i, "atr")
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}
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}
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func TestGoldenBeta(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "beta")
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beta, err := NewBeta(20)
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if err != nil {
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t.Fatal(err)
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}
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defer beta.Close()
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for i := range input {
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// generator fed (close, open)
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assertGoldenClose(t, beta.Update(input[i][3], input[i][0]), goldenCell(exp[i][0]), i, "beta")
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}
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}
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func TestGoldenMacd(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "macd")
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macd, err := NewMacdIndicator(12, 26, 9)
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if err != nil {
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t.Fatal(err)
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}
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defer macd.Close()
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for i := range input {
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out, ok := macd.Update(input[i][3])
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if exp[i][0] == "nan" {
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if ok {
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t.Errorf("row %d macd: expected warmup, got %+v", i, out)
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}
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continue
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}
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if !ok {
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t.Errorf("row %d macd: expected value, got warmup", i)
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continue
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}
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assertGoldenClose(t, out.Macd, goldenCell(exp[i][0]), i, "macd.macd")
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assertGoldenClose(t, out.Signal, goldenCell(exp[i][1]), i, "macd.signal")
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assertGoldenClose(t, out.Histogram, goldenCell(exp[i][2]), i, "macd.histogram")
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}
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}
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func TestGoldenAdx(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "adx")
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adx, err := NewAdx(14)
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if err != nil {
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t.Fatal(err)
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}
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defer adx.Close()
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for i := range input {
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out, ok := adx.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], int64(i))
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if exp[i][0] == "nan" {
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if ok {
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t.Errorf("row %d adx: expected warmup, got %+v", i, out)
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}
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continue
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}
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if !ok {
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t.Errorf("row %d adx: expected value, got warmup", i)
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continue
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}
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assertGoldenClose(t, out.PlusDi, goldenCell(exp[i][0]), i, "adx.plus_di")
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assertGoldenClose(t, out.MinusDi, goldenCell(exp[i][1]), i, "adx.minus_di")
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assertGoldenClose(t, out.Adx, goldenCell(exp[i][2]), i, "adx.adx")
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}
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}
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// The four de-duplicated indicators: pin their corrected definitions against
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// the Rust reference so the Go FFI stays bit-identical.
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func TestGoldenAdOscillator(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "ad_oscillator")
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ad, err := NewAdOscillator()
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if err != nil {
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t.Fatal(err)
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}
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defer ad.Close()
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for i := range input {
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got := ad.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], int64(i))
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assertGoldenClose(t, got, goldenCell(exp[i][0]), i, "ad_oscillator")
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}
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}
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func TestGoldenIntradayIntensity(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "intraday_intensity")
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ii, err := NewIntradayIntensity()
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if err != nil {
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t.Fatal(err)
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}
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defer ii.Close()
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for i := range input {
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got := ii.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], int64(i))
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assertGoldenClose(t, got, goldenCell(exp[i][0]), i, "intraday_intensity")
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}
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}
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func TestGoldenAwesomeOscillatorHistogram(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "awesome_oscillator_histogram")
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aoh, err := NewAwesomeOscillatorHistogram(5, 34, 1)
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if err != nil {
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t.Fatal(err)
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}
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defer aoh.Close()
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for i := range input {
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got := aoh.Update(input[i][0], input[i][1], input[i][2], input[i][3], input[i][4], int64(i))
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assertGoldenClose(t, got, goldenCell(exp[i][0]), i, "awesome_oscillator_histogram")
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}
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}
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func TestGoldenAverageDrawdown(t *testing.T) {
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input := goldenInput(t)
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exp := readGolden(t, "average_drawdown")
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avg, err := NewAverageDrawdown(20)
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if err != nil {
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t.Fatal(err)
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}
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defer avg.Close()
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for i := range input {
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// generator fed the close column as the equity-curve sample.
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assertGoldenClose(t, avg.Update(input[i][3]), goldenCell(exp[i][0]), i, "average_drawdown")
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}
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}
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