kingchenc
75eefbbd08
The strategy_* examples were only syntax-smoked in CI, never run, which hid two classes of problem: 1. Python strategy_macd_adx / strategy_bollinger_squeeze passed three separate arguments to the candle indicators ADX/ATR, whose .update() takes a single candle — a TypeError at runtime — and read the ADX tuple at index 0 (plus_di) instead of 2 (adx). Both fixed. 2. The Go / C# / R / Java strategies defaulted to synthetic data and used a different (annualised) one-line summary, so they printed wildly different numbers from the Rust/Python/Node/C/WASM suite. Rewrite them to the shared per-trade backtest (load the bundled BTCUSDT CSV by default, same entry/exit logic, same print_summary output). All nine runnable bindings now print byte-identical backtest summaries on the same data (MACD+ADX 246 trades / -47.19%, RSI 37 / -17.84%, Bollinger 1 / -7.82%), verified by diffing each language's output against the Python reference. WASM shares the same logic and bundled dataset (browser-rendered).
73 lines
2.8 KiB
C#
73 lines
2.8 KiB
C#
namespace Wickra.Examples;
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/// <summary>One OHLCV bar with a millisecond timestamp.</summary>
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public readonly record struct Bar(double Open, double High, double Low, double Close, double Volume, long Timestamp);
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/// <summary>
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/// Deterministic synthetic market data plus a small OHLCV CSV loader, shared by
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/// the offline examples so they run without network access.
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/// </summary>
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public static class MarketData
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{
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/// <summary>A reproducible price path (trend + two cycles), no randomness.</summary>
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public static double[] SyntheticPrices(int count, double start = 100.0)
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{
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var prices = new double[count];
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for (var i = 0; i < count; i++)
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{
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prices[i] = start + 12.0 * Math.Sin(i * 0.05) + 5.0 * Math.Sin(i * 0.013) + i * 0.01;
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}
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return prices;
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}
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/// <summary>A reproducible OHLCV series derived from <see cref="SyntheticPrices"/>.</summary>
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public static Bar[] SyntheticCandles(int count, long startTimestamp = 0, long stepMs = 3_600_000)
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{
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var prices = SyntheticPrices(count + 1);
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var bars = new Bar[count];
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for (var i = 0; i < count; i++)
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{
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var open = prices[i];
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var close = prices[i + 1];
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var high = Math.Max(open, close) + 0.5 + Math.Abs(Math.Sin(i * 0.7));
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var low = Math.Min(open, close) - 0.5 - Math.Abs(Math.Cos(i * 0.7));
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var volume = 1_000.0 + 500.0 * (1.0 + Math.Sin(i * 0.1));
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bars[i] = new Bar(open, high, low, close, volume, startTimestamp + i * stepMs);
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}
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return bars;
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}
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/// <summary>
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/// Loads an OHLCV CSV. Accepts rows of <c>timestamp,open,high,low,close,volume</c>
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/// or <c>open,high,low,close,volume</c>; a non-numeric first row is treated as a header.
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/// </summary>
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public static Bar[] LoadOhlcvCsv(string path)
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{
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// Native CandleReader: header validation, BOM and field-whitespace tolerance.
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// No manual CSV parsing.
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using var reader = new Wickra.CandleReader(File.ReadAllText(path));
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var candles = reader.Read();
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var bars = new Bar[candles.Length];
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for (var i = 0; i < candles.Length; i++)
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{
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var c = candles[i];
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bars[i] = new Bar(c.Open, c.High, c.Low, c.Close, c.Volume, (long)c.Timestamp);
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}
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return bars;
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}
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/// <summary>
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/// Loads one of the checked-in datasets under examples/data, resolved
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/// relative to this source file so it works from any working directory.
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/// </summary>
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public static Bar[] BundledCandles(string filename,
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[System.Runtime.CompilerServices.CallerFilePath] string self = "")
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{
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var dir = Path.GetDirectoryName(self)!;
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return LoadOhlcvCsv(Path.Combine(dir, "..", "..", "data", filename));
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}
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}
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