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.

bindings/r/tests/testthat/test-golden.R

@@ -0,0 +1,98 @@
+# Golden-fixture parity: replay the shared testdata/golden input series through
+# the R FFI and assert every value matches the Rust reference output. Where the
+# archetype test only checks finiteness, this pins exact values, catching wiring
+# bugs (swapped params, wrong multi-output field). Fixtures are generated by
+# `cargo run -p wickra-examples --bin gen_golden`.
+
+golden_dir <- local({
+  d <- normalizePath(getwd(), winslash = "/", mustWork = FALSE)
+  repeat {
+    g <- file.path(d, "testdata", "golden")
+    if (dir.exists(g)) return(g)
+    parent <- dirname(d)
+    if (identical(parent, d)) stop("testdata/golden not found from ", getwd())
+    d <- parent
+  }
+})
+
+read_golden <- function(name) {
+  read.csv(file.path(golden_dir, paste0(name, ".csv")),
+           colClasses = "character", check.names = FALSE)
+}
+
+gcell <- function(s) if (identical(s, "nan")) NA_real_ else as.numeric(s)
+
+expect_close <- function(got, want, row, field) {
+  if (is.na(want)) {
+    expect_true(is.na(got), info = paste("row", row, field, "expected warmup/NA"))
+  } else {
+    tol <- 1e-6 * max(1, abs(want))
+    expect_lte(abs(got - want), tol, label = paste("row", row, field, "got", got, "want", want))
+  }
+}
+
+golden_input <- read.csv(file.path(golden_dir, "input.csv"))
+
+test_that("scalar indicators match golden", {
+  specs <- list(c("sma", 14), c("ema", 14), c("rsi", 14))
+  for (spec in specs) {
+    name <- spec[[1]]
+    ind <- switch(name, sma = Sma(14), ema = Ema(14), rsi = Rsi(14))
+    exp <- read_golden(name)
+    for (i in seq_len(nrow(golden_input))) {
+      got <- update(ind, golden_input$close[i])
+      expect_close(got, gcell(exp[i, 1]), i, name)
+    }
+  }
+})
+
+test_that("candle Atr matches golden", {
+  atr <- Atr(14)
+  exp <- read_golden("atr")
+  for (i in seq_len(nrow(golden_input))) {
+    got <- update(atr, golden_input$open[i], golden_input$high[i], golden_input$low[i],
+                  golden_input$close[i], golden_input$volume[i], i - 1)
+    expect_close(got, gcell(exp[i, 1]), i, "atr")
+  }
+})
+
+test_that("pairwise Beta matches golden", {
+  beta <- Beta(20)
+  exp <- read_golden("beta")
+  for (i in seq_len(nrow(golden_input))) {
+    # generator fed (close, open)
+    got <- update(beta, golden_input$close[i], golden_input$open[i])
+    expect_close(got, gcell(exp[i, 1]), i, "beta")
+  }
+})
+
+test_that("multi-output MACD matches golden", {
+  macd <- MacdIndicator(12, 26, 9)
+  exp <- read_golden("macd")
+  for (i in seq_len(nrow(golden_input))) {
+    out <- update(macd, golden_input$close[i])
+    if (identical(exp[i, "macd"], "nan")) {
+      expect_true(all(is.na(out)), info = paste("row", i, "macd warmup"))
+    } else {
+      expect_close(out[["macd"]], gcell(exp[i, "macd"]), i, "macd.macd")
+      expect_close(out[["signal"]], gcell(exp[i, "signal"]), i, "macd.signal")
+      expect_close(out[["histogram"]], gcell(exp[i, "histogram"]), i, "macd.histogram")
+    }
+  }
+})
+
+test_that("multi-output ADX matches golden", {
+  adx <- Adx(14)
+  exp <- read_golden("adx")
+  for (i in seq_len(nrow(golden_input))) {
+    out <- update(adx, golden_input$open[i], golden_input$high[i], golden_input$low[i],
+                  golden_input$close[i], golden_input$volume[i], i - 1)
+    if (identical(exp[i, "plus_di"], "nan")) {
+      expect_true(all(is.na(out)), info = paste("row", i, "adx warmup"))
+    } else {
+      expect_close(out[["plus_di"]], gcell(exp[i, "plus_di"]), i, "adx.plus_di")
+      expect_close(out[["minus_di"]], gcell(exp[i, "minus_di"]), i, "adx.minus_di")
+      expect_close(out[["adx"]], gcell(exp[i, "adx"]), i, "adx.adx")
+    }
+  }
+})