// For importing
PM > Install-Package Trady.Importer

// For computing & backtesting
PM > Install-Package Trady.Analysis

var importer = new YahooFinanceImporter();
var candles = await importer.ImportAsync("FB");
var last = candles.Sma(30).Last();
Console.WriteLine($"{last.DateTime}, {last.Tick}");

// From Quandl wiki database
var importer = new QuandlWikiImporter(apiKey);

// From Yahoo Finance
var importer = new YahooFinanceImporter();

// From Stooq
var importer = new StooqImporter();

// From AlphaVantage
var importer = new AlphaVantageImporter(apiKey);

// From Google Finance (Temporarily not available now)
// var importer = new GoogleFinanceImporter();

// Or from dedicated csv file
var importer = new CsvImporter("FB.csv");

// Get stock data from the above importer
var candles = await importer.ImportAsync("FB");

// Transform the series for computation, downcast is forbidden
// Supported period: PerSecond, PerMinute, Per15Minutes, Per30Minutes, Hourly, BiHourly, Daily, Weekly, Monthly

var transformedCandles = candles.Transform<Daily, Weekly>();

// This library supports computing from tuples or candles, extensions are recommended for computing
var closes = new List<decimal>{ ... };
var smaTs = closes.Sma(30);
var sma = closes.Sma(30)[index];

// or, traditional call
var sma = new SimpleMovingAverageByTuple(closes, 30)[index];

// the corresponding version of candle
var sma = new SimpleMovingAverage(candles, 30)[index];

// Simple operation on indicator is supported, now supports only diff, rDiff, sma, sd
var closes = new List<decimal>{ ... };
var smaDiff = closes.Sma(30).Diff(index);   // i-th term - (i-1)-th term
var smaSma = closes.Sma(30).Sma(10, index); // average(n items)
var smaRDiff = closes.Sma(30).RDiff(index); // (i-th term - (i-1)-th term) / (i-1)-th term * 100
var smaSd = closes.Sma(30).Sd(10, 2, index);

// This also applies to candles

// Sometimes, we want to utilize the Analyzable infra for some simple indicators but doesn't want to implement a new class, we are adding AsAnalyzable for conversion from Func

// Before conversion, on the very top of your file, you should add
using AFunc = System.Func<System.Collections.Generic.IReadOnlyList<Trady.Core.Candle>, int, System.Collections.Generic.IReadOnlyList<decimal>, Trady.Core.Infrastructure.IAnalyzeContext<Trady.Core.Candle>, decimal?>;

// And use it in your code
AFunc aFunc = (c, i, p, ctx) => c[i].High - c[i].Low;   // The four parameters: candles, index, parameters, context
var aFuncInstance = aFunc.AsAnalyzable(candles);
var a = aFuncInstance[index];

// You may also combine with simple operation computation
var aSma = aFuncInstance.Sma(30, index);

// To use your func globally for analysis, you can register you func by using FuncRegistry.Register method
// The four parameters is the same as the above section, namely: candles, index, parameters, context
FuncRegistry.Register("modified_sma", (c, i, p, ctx) => ctx.Get<SimpleMovingAverage>(p[0])[i].Tick);

// You can use your func globally using the extension
var lastModifiedSmaValue = candles.Func("modified_sma", 10)[candles.Count() - 1];

// The library also support register by plain text expression, you can dynamically create an analyzable as follows:
// Please notice that you must follow the naming convention: c, i, p, ctx when using this approach
FuncRegistry.Register("dy_sma", "var sma = ctx.Get<SimpleMovingAverage>(10); return sma[i].Tick;");

// And the use case is similar:
var lastModifiedSmaValue = candles.Func("modified_sma")[candles.Count() - 1];

// The following shows the number of candles that fulfill both the IsAboveSma(30) & IsAboveSma(10) rule
var rule = Rule.Create(c => c.IsAboveSma(30))
    .And(c => c.IsAboveSma(10));

// Use context here for caching indicator results
using (var ctx = new AnalyzeContext(candles))
{
    var validObjects = new SimpleRuleExecutor(ctx, rule).Execute();
    Console.WriteLine(validObjects.Count());
}

// Import your candles
var importer = new YahooFinanceImporter();
var fb = await importer.ImportAsync("FB");
var aapl = await importer.ImportAsync("AAPL");

// Build buy rule & sell rule based on various patterns
var buyRule = Rule.Create(c => c.IsFullStoBullishCross(14, 3, 3))
    .And(c => c.IsMacdOscBullish(12, 26, 9))
    .And(c => c.IsSmaOscBullish(10, 30))
    .And(c => c.IsAccumDistBullish());

var sellRule = Rule.Create(c => c.IsFullStoBearishCross(14, 3, 3))
    .Or(c => c.IsMacdBearishCross(12, 24, 9))
    .Or(c => c.IsSmaBearishCross(10, 30));

// Create portfolio instance by using PortfolioBuilder
var runner = new Builder()
    .Add(fb, 10)
    .Add(aapl, 30)
    .Buy(buyRule)
    .Sell(sellRule)
    .BuyWithAllAvailableCash()
    .FlatExchangeFeeRate(0.001m)
    .Premium(1)
    .Build();

// Start backtesting with the portfolio
var result = await runner.RunAsync(10000);

// Get backtest result for the portfolio
Console.WriteLine(string.Format("Transaction count: {0:#.##}, P/L ratio: {1:0.##}%, Principal: {2:#}, Total: {3:#}",
    resultresult.Transactions.Count(),
    result.CorrectedProfitLoss * 100,
    result.Principal,
    result.CorrectedBalance));

// Implement your pattern by creating a static class for extending IndexedCandle class
public static class IndexedCandleExtension
{
    public static bool IsEma10Rising(this IndexedCandle ic)
        => ic.Get<ExponentialMovingAverage>(10).Diff(ic.Index).Tick.IsPositive();

    public static bool IsEma10Dropping(this IndexedCandle ic)
        => ic.Get<ExponentialMovingAverage>(10).Diff(ic.Index).Tick.IsNegative();

    public static bool IsEma10BullishCrossEma30(this IndexedCandle ic)
        => ic.Get<ExponentialMovingAverageOscillator>(10, 30).ComputeNeighbour(ic.Index).IsTrue(
            (prev, current, next) => prev.Tick.IsNegative() && current.Tick.IsPositive());

    public static bool IsEma10BearishCrossEma30(this IndexedCandle ic)
        => ic.Get<ExponentialMovingAverageOscillator>(10, 30).ComputeNeighbour(ic.Index).IsTrue(
            (prev, current, next) => prev.Tick.IsPositive() && current.Tick.IsNegative());
}

// Use case
var buyRule = Rule.Create(c => c.IsEma10BullishCrossEma30()).And(c => c.IsEma10Rising());
var sellRule = Rule.Create(c => c.IsEma10BearishCrossEma30()).Or(c => c.IsEma10Dropping());
var runner = new Builder().Add(candles, 10).Buy(buyRule).Sell(sellRule).Build();
var result = await runner.RunAsync(10000, 1);

// To use your rule in global, you may register it by using RuleRegistry.Register method
RuleRegistry.Register("IsBelowSmaX", (ic, p) => ic.Get<SimpleMovingAverage>(p[0])[ic.Index].Tick.IsTrue(t => t > ic.Close));

// Or, using plain text
RuleRegistry.Register("IsBelowSma30", "ic.Get<SimpleMovingAverage>(30)[ic.Index].Tick.IsTrue(t => t > ic.Close)");

// Call it using GetRule method from AnalyzeContext
using (var ctx = new AnalyzeContext(candles))
{
    var ruleX = ctx.GetRule("IsBelowSmaX", 30); // Substitute parameter to the rule
    var rule30 = ctx.GetRule("IsBelowSma30");

    var ruleXByRuleCreateEval = Rule.Create(ic => ic.Eval("IsBelowSmaX", 30));  // Create rule with indexedCandle Eval

    var isAboveSma30Candles = new SimpleRuleExecutor(ctx, ruleX).Execute();
}

// You can also implement your own importer by implementing the IImporter interface
public class MyImporter : IImporter
{
    public async Task<IReadOnlyList<IOhlcv>> ImportAsync(string symbol, DateTime? startTime = null, DateTime? endTime = null, PeriodOption period = PeriodOption.Daily, CancellationToken token = default(CancellationToken))
    {
        // Your implementation to return a list of candles
    }
}

// Use case
var importer = new MyImporter();
var candles = await importer.ImportAsync("FB");

// You can also implement your own indicator by extending the AnalyzableBase<TInput, TOutput> class
public class MyIndicator : AnalyzableBase<IOhlcv, AnalyzableTick<decimal?>>
{
    // Backing indicator for the indicator
    SimpleMovingAverageByTuple _sma;

    public MyIndicator(IEnumerable<IOhlcv> inputs, int periodCount) : base(inputs)
    {
        // Initialize reference indicators, or other required stuff here
        _sma = new SimpleMovingAverageByTuple(inputs.Select(i => i.Close).ToList(), periodCount);
    }

    // Implement the compute algorithm, uses mappedInputs, index & backing indicators for computation here
    protected override AnalyzableTick<decimal?> ComputeByIndexImpl(IReadOnlyList<IOhlcv> mappedInputs, int index)
    {
		return new AnalyzableTick<decimal?>(mappedInputs[index].DateTime, _sma[index]);
	}
}

// Use case
var results = new MyIndicator(candles, 30).Compute();
foreach (var r in results)
{
    Console.WriteLine($"{r.DateTime}, {r.Tick.Value}");
}

// You can implement your own indicator by extending the CummulativeAnalyzableBase<TInput, TOutput> class
public class MyCumulativeIndicator : CumulativeAnalyzableBase<IOhlcv, AnalyzableTick<decimal?>>
{
    // Backing indicator for the indicator
    readonly SimpleMovingAverageByTuple _sma;

    public MyCumulativeIndicator(IEnumerable<IOhlcv> inputs, int periodCount) : base(inputs)
    {
        // Initialize reference indicators, or other required stuff here
        _sma = new SimpleMovingAverageByTuple(inputs.Select(i => i.Close).ToList(), periodCount);
    }

    // Implement the compute algorithm for index > InitialValueIndex, uses mappedInputs, index, prev analyzable tick & backing indicators for computation here
    protected override AnalyzableTick<decimal?> ComputeCumulativeValue(IReadOnlyList<IOhlcv> mappedInputs, int index, AnalyzableTick<decimal?> prevOutputToMap)
    {
        return new AnalyzableTick<decimal?>(mappedInputs[index].DateTime, _sma[index] + prevOutputToMap.Tick);
    }

    // Same for the above but for index = InitialValueIndex
    protected override AnalyzableTick<decimal?> ComputeInitialValue(IReadOnlyList<IOhlcv> mappedInputs, int index)
    {
        return new AnalyzableTick<decimal?>(mappedInputs[index].DateTime, _sma[index]);
    }

    // You can also override the InitialValueIndex property & ComputeNullValue method if needed
}

// Use case
var results = new MyCumulativeIndicator(candles).Compute();
foreach (var r in results)
{
    Console.WriteLine($"{r.DateTime}, {r.Tick.Value}");
}   

// You can make use of the GenericMovingAverage class to get rid of implementing MA-related indicator on your own
 public class MyGmaIndicator : AnalyzableBase<IOhlcv, AnalyzableTick<decimal?>>
{
    GenericMovingAverage _gma;

    public MyGmaIndicator(IEnumerable<IOhlcv> inputs, int periodCount) : base(inputs)
    {
        // parameters: initialValueIndex, initialValueFunction, indexValueFunction, smoothingFactorFunction
		_gma = new GenericMovingAverage(
			i => inputs.Select(ip => ip.Close).ElementAt(i),
			2.0m / (periodCount + 1),
			inputs.Count());
    }

    protected override AnalyzableTick<decimal?> ComputeByIndexImpl(IReadOnlyList<IOhlcv> mappedInputs, int index)
    {
        return new AnalyzableTick<decimal?>(mappedInputs[index].DateTime, _gma[index]);
    }
}