public static HydroTimeSeries GetMissingValuesHydro(ITimeSeries ts, DateTime start, DateTime end, TimeStep step)
{
HydroTimeSeries missingTs = new HydroTimeSeries(start, end);
List<int> breakIx = GetDataBreaks(ts);
//TODO missing points before series start
foreach (int begIndex in breakIx)
{
if (begIndex < ts.Count - 1)
{
DateTime begDate = DateTime.FromOADate(ts[begIndex].X);
DateTime endDate = DateTime.FromOADate(ts[begIndex + 1].X);
if (step == TimeStep.Day)
{
int nd = (int)endDate.Subtract(begDate).TotalDays;
for (int i = 0; i < nd; i++)
{
DateTime newTime = begDate.AddDays(i);
missingTs.AddUnknownValue(newTime);
}
}
else
{
int nh = (int)endDate.Subtract(begDate).TotalHours;
for (int i = 0; i < nh; i++)
{
DateTime newTime = begDate.AddHours(i);
missingTs.AddUnknownValue(newTime);
}
}
}
}
return missingTs;
}
/// <summary>
/// Fills the data gaps inside the time-series by setting them to 'no data' vals
/// </summary>
/// <param name="ts"></param>
public static ITimeSeries FillDataGaps(ITimeSeries ts, TimeStep step)
{
ITimeSeries myTs = MakeRegularTimeSeries(ts.Start, ts.End, step);
if (step == TimeStep.Day)
{
double tStart = myTs[0].X;
for (int i = 0; i < ts.Count - 1; i++)
{
double index = (ts[i].X - tStart);
int ix = (int)index;
myTs[ix].Y = ts[i].Y;
}
}
else
{
double tStart = myTs[0].X * 24;
for (int i = 0; i < ts.Count - 1; i++)
{
double index = (ts[i].X * 24 - tStart);
int ix = (int)index;
myTs[ix].Y = ts[i].Y;
}
}
return myTs;
}
public bool SetValues(ITimeSeries series_, int yAxisExtent_=40)
{
lcdInstrumentHistory.ClearSeries();
if (series_ == null || series_.Series == null) return false;
addSeries(series_, yAxisExtent_);
return true;
}
public void SetValues(ITimeSeries series_, TimePeriod initialPeriod_ = TimePeriod.None)
{
if (series_ == null) return;
m_allValues = new[] {series_};
lblTitle.Text = series_.Name;
if (initialPeriod_ != TimePeriod.None)
periodButtons1.SetPeriod(initialPeriod_,true);
else
apply();
}
override public void Run()
{
//---------- initialization
// set simulation time frame
StartTime = DateTime.Parse("01/01/2015", CultureInfo.InvariantCulture);
EndTime = DateTime.Parse("12/31/2016", CultureInfo.InvariantCulture);
// add instruments
AddDataSource(_instrumentNick);
//---------- simulation
foreach (DateTime simTime in SimTimes)
{
// find our instrument. if we have only one instrument,
// we could also just use Instruments.Values.First()
Instrument instrument = FindInstrument(_instrumentNick);
// calculate simple indicators
// the output of an indicator is a time series
ITimeSeries <double> ema26 = instrument.Close.EMA(26);
ITimeSeries <double> ema12 = instrument.Close.EMA(12);
// therefore, indicators can be calculated on top of indicators
ITimeSeries <double> macd = ema12.Subtract(ema26);
ITimeSeries <double> signal = macd.EMA(9);
// plot our data
_plotter.SelectChart("indicators vs time", "date");
_plotter.SetX(simTime.Date);
_plotter.Plot(instrument.Symbol, instrument.Close[0] + _offsetPrice);
_plotter.Plot("ema26", ema26[0] + _offsetPrice);
_plotter.Plot("ema12", ema12[0] + _offsetPrice);
_plotter.Plot("macd", macd[0]);
_plotter.Plot("signal", signal[0]);
}
}
public void Test_Lambda()
{
double[,] testVectors =
{
{ 100.00000, 100.00000, 101.00000, 102.00000, 103.00000, },
{ 105.00000, 105.00000, 106.00000, 107.00000, 108.00000, },
{ 102.50000, 102.50000, 103.50000, 104.50000, 105.50000, },
{ 107.50000, 107.50000, 108.50000, 109.50000, 110.50000, },
{ 105.00000, 105.00000, 106.00000, 107.00000, 108.00000, },
{ 110.00000, 110.00000, 111.00000, 112.00000, 113.00000, },
{ 107.50000, 107.50000, 108.50000, 109.50000, 110.50000, },
{ 112.50000, 112.50000, 113.50000, 114.50000, 115.50000, },
{ 110.00000, 110.00000, 111.00000, 112.00000, 113.00000, },
{ 115.00000, 115.00000, 116.00000, 117.00000, 118.00000, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response =
TuringTrader.Indicators.IndicatorsBasic.Lambda(
(t) => t + stimulus[0]);
//Output.Write("{{ {0:F5}, ", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5}, ", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
public void setUp()
{
List <IBar> bars = new List <IBar>();
// open, close, high, low
bars.Add(new MockBar(44.98M, 45.05M, 45.17M, 44.96M));
bars.Add(new MockBar(45.05M, 45.10M, 45.15M, 44.99M));
bars.Add(new MockBar(45.11M, 45.19M, 45.32M, 45.11M));
bars.Add(new MockBar(45.19M, 45.14M, 45.25M, 45.04M));
bars.Add(new MockBar(45.12M, 45.15M, 45.20M, 45.10M));
bars.Add(new MockBar(45.15M, 45.14M, 45.20M, 45.10M));
bars.Add(new MockBar(45.13M, 45.10M, 45.16M, 45.07M));
bars.Add(new MockBar(45.12M, 45.15M, 45.22M, 45.10M));
bars.Add(new MockBar(45.15M, 45.22M, 45.27M, 45.14M));
bars.Add(new MockBar(45.24M, 45.43M, 45.45M, 45.20M));
bars.Add(new MockBar(45.43M, 45.44M, 45.50M, 45.39M));
bars.Add(new MockBar(45.43M, 45.55M, 45.60M, 45.35M));
bars.Add(new MockBar(45.58M, 45.55M, 45.61M, 45.39M));
bars.Add(new MockBar(45.45M, 45.01M, 45.55M, 44.80M));
bars.Add(new MockBar(45.03M, 44.23M, 45.04M, 44.17M));
data = new BaseTimeSeries(bars);
}
/**
* Calculates the profit of a trade (Buy and sell).
* @param series a time series
* @param trade a trade
* @return the profit of the trade
*/
private decimal CalculateProfit(ITimeSeries series, Trade trade)
{
decimal profit = Decimals.ONE;
if (trade.IsClosed())
{
// use price of entry/exit order, if NaN use close price of underlying time series
decimal exitClosePrice = trade.GetExit().getPrice().IsNaN() ?
series.GetBar(trade.GetExit().getIndex()).ClosePrice : trade.GetExit().getPrice();
decimal entryClosePrice = trade.GetEntry().getPrice().IsNaN() ?
series.GetBar(trade.GetEntry().getIndex()).ClosePrice : trade.GetEntry().getPrice();
if (trade.GetEntry().isBuy())
{
profit = exitClosePrice.DividedBy(entryClosePrice);
}
else
{
profit = entryClosePrice.DividedBy(exitClosePrice);
}
}
return(profit);
}
/// <summary>
/// Calculate Relative Strength Index, as described here:
/// <see href="https://en.wikipedia.org/wiki/Relative_strength_index"/>
/// </summary>
/// <param name="series">input time series</param>
/// <param name="n">smoothing period</param>
/// <param name="parentId">caller cache id, optional</param>
/// <param name="memberName">caller's member name, optional</param>
/// <param name="lineNumber">caller line number, optional</param>
/// <returns>RSI time series</returns>
public static ITimeSeries <double> RSI(this ITimeSeries <double> series, int n = 14,
CacheId parentId = null, [CallerMemberName] string memberName = "", [CallerLineNumber] int lineNumber = 0)
{
var cacheId = new CacheId(parentId, memberName, lineNumber,
series.GetHashCode(), n);
ITimeSeries <double> returns = series.Return(cacheId);
double avgUp = returns
.Max(0.0, cacheId)
.EMA(n, cacheId)[0];
double avgDown = -returns
.Min(0.0, cacheId)
.EMA(n, cacheId)[0];
double rs = avgUp / Math.Max(1e-10, avgDown);
return(IndicatorsBasic.BufferedLambda(
v => 100.0 - 100.0 / (1 + rs),
50.0,
cacheId));
}
/// <summary>
/// Calculate True Strength Index of input time series, as described here:
/// <see href="https://en.wikipedia.org/wiki/True_strength_index"/>
/// </summary>
/// <param name="series">input time series</param>
/// <param name="r">smoothing period for momentum</param>
/// <param name="s">smoothing period for smoothed momentum</param>
/// <param name="parentId">caller cache id, optional</param>
/// <param name="memberName">caller's member name, optional</param>
/// <param name="lineNumber">caller line number, optional</param>
/// <returns>TSI time series</returns>
public static ITimeSeries <double> TSI(this ITimeSeries <double> series, int r = 25, int s = 13,
CacheId parentId = null, [CallerMemberName] string memberName = "", [CallerLineNumber] int lineNumber = 0)
{
var cacheId = new CacheId(parentId, memberName, lineNumber,
series.GetHashCode(), r, s);
ITimeSeries <double> momentum = series
.Return(cacheId);
double numerator = momentum
.EMA(r, cacheId)
.EMA(s, cacheId)[0];
double denominator = momentum
.AbsValue(cacheId)
.EMA(r, cacheId)
.EMA(s, cacheId)[0];
return(IndicatorsBasic.BufferedLambda(
v => 100.0 * numerator / Math.Max(1e-10, denominator),
0.5,
cacheId));
}
private void MapToEquidistantTimeSeries <T>(ITimeSeries <T> series, KeyValuePair <DateTime, T> valueToMap) where T : struct
{
if (valueToMap.Key.ToUniversalTime() < series.Span.Begin.ToUniversalTime() || valueToMap.Key.ToUniversalTime() > series.Span.End.ToUniversalTime())
{
return;
}
int findBestIndex()
{
var indexDouble = (valueToMap.Key.ToUniversalTime() - series.Span.Begin.ToUniversalTime()) / series.Span.Duration;
var index = Math.Min(series.Count - 1, Math.Max(0, (int)Math.Floor(indexDouble)));
if (!series[index].HasValue)
{
return(index);
}
var prevIndex = Math.Max(0, index - 1);
if (!series[prevIndex].HasValue)
{
series[prevIndex] = series[index];
return(index);
}
var nextIndex = Math.Min(series.Count - 1, index + 1);
if ((indexDouble - index) >= 0.5d && !series[nextIndex].HasValue)
{
return(nextIndex);
}
return(index);
}
series[findBestIndex()] = valueToMap.Value;
}
/// <summary>
/// Calculate Commodity Channel Index of input time series, as described here:
/// <see href="https://en.wikipedia.org/wiki/Commodity_channel_index"/>
/// </summary>
/// <param name="series">input time series</param>
/// <param name="n">averaging length</param>
/// <param name="parentId">caller cache id, optional</param>
/// <param name="memberName">caller's member name, optional</param>
/// <param name="lineNumber">caller line number, optional</param>
/// <returns>CCI time series</returns>
public static ITimeSeries <double> CCI(this ITimeSeries <double> series, int n = 20,
CacheId parentId = null, [CallerMemberName] string memberName = "", [CallerLineNumber] int lineNumber = 0)
{
var cacheId = new CacheId(parentId, memberName, lineNumber,
series.GetHashCode(), n);
return(IndicatorsBasic.BufferedLambda(
(v) =>
{
ITimeSeries <double> delta = series
.Subtract(
series
.SMA(n, cacheId),
cacheId);
ITimeSeries <double> meanDeviation = delta
.AbsValue(cacheId)
.SMA(n, cacheId);
return delta[0] / Math.Max(1e-10, 0.015 * meanDeviation[0]);
},
0.5,
cacheId));
}
public IDisposable OpenToRead(string symbol, out ITimeSeries timeSeries)
{
var metaFile = _filePathProvider.GetMetaFilePath(symbol);
lock (_symbols) // Protection against other threads
{
var locker = metaFile.LockFile(); // Protection against other processes and machines
if (!_symbols.TryGetValue(symbol, out var meta))
{
_symbols.Add(symbol, meta = new TimeSeries(symbol));
}
timeSeries = meta;
var lastWriteTime = File.GetLastWriteTimeUtc(metaFile);
if (lastWriteTime > meta.LastWriteTimeUtc)
{
meta.Restore(metaFile);
meta.LastWriteTimeUtc = lastWriteTime;
}
return(locker);
}
}
public void Test_StandardDeviation()
{
double[,] testVectors =
{
{ 100.00000, 0.00000, 0.00000, 0.00000, 0.00000, },
{ 105.00000, 2.50000, 0.00000, 0.00000, 0.00000, },
{ 102.50000, 2.39357, 2.50000, 0.00000, 0.00000, },
{ 107.50000, 3.22749, 2.39357, 2.50000, 0.00000, },
{ 105.00000, 2.04124, 3.22749, 2.39357, 2.50000, },
{ 110.00000, 3.22749, 2.04124, 3.22749, 2.39357, },
{ 107.50000, 2.04124, 3.22749, 2.04124, 3.22749, },
{ 112.50000, 3.22749, 2.04124, 3.22749, 2.04124, },
{ 110.00000, 2.04124, 3.22749, 2.04124, 3.22749, },
{ 115.00000, 3.22749, 2.04124, 3.22749, 2.04124, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response = stimulus.StandardDeviation(4);
//Output.Write("{{ {0:F5}, ", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5}, ", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
public void Test_LogRegression()
{
double[,] testVectors =
{
{ 100.00000, 0.00000, 0.00000, 0.00000, 0.00000, },
{ 105.00000, 0.01464, 0.00000, 0.00000, 0.00000, },
{ 102.50000, 0.01229, 0.01464, 0.00000, 0.00000, },
{ 107.50000, 0.01929, 0.01229, 0.01464, 0.00000, },
{ 105.00000, 0.00476, 0.01929, 0.01229, 0.01464, },
{ 110.00000, 0.01883, 0.00476, 0.01929, 0.01229, },
{ 107.50000, 0.00465, 0.01883, 0.00476, 0.01929, },
{ 112.50000, 0.01840, 0.00465, 0.01883, 0.00476, },
{ 110.00000, 0.00455, 0.01840, 0.00465, 0.01883, },
{ 115.00000, 0.01799, 0.00455, 0.01840, 0.00465, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response = stimulus.LogRegression(4).Slope;
//Output.Write("{{{0:F5}, ", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5}, ", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
public void Test_FastStandardDeviation()
{
double[,] testVectors =
{
{ 100.00000, 0.00000, 0.00000, 0.00000, 0.00000, },
{ 105.00000, 2.44949, 0.00000, 0.00000, 0.00000, },
{ 102.50000, 1.91311, 2.44949, 0.00000, 0.00000, },
{ 107.50000, 2.98958, 1.91311, 2.44949, 0.00000, },
{ 105.00000, 2.33956, 2.98958, 1.91311, 2.44949, },
{ 110.00000, 3.20987, 2.33956, 2.98958, 1.91311, },
{ 107.50000, 2.51299, 3.20987, 2.33956, 2.98958, },
{ 112.50000, 3.30295, 2.51299, 3.20987, 2.33956, },
{ 110.00000, 2.58598, 3.30295, 2.51299, 3.20987, },
{ 115.00000, 3.34207, 2.58598, 3.30295, 2.51299, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response = stimulus.FastStandardDeviation(4);
//Output.Write("{{ {0:F5}, ", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5}, ", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
public void Test_Covariance()
{
double[,] testVectors =
{
// instr1 instr2 results
{ 1.10000, 3.00000, 0.00000, 0.00000, 0.00000, },
{ 1.70000, 4.20000, 0.14400, 0.00000, 0.00000, },
{ 2.10000, 4.90000, 0.40700, 0.14400, 0.00000, },
{ 1.40000, 4.10000, 0.33850, 0.40700, 0.14400, },
{ 0.20000, 2.50000, 0.66500, 0.33850, 0.40700, },
};
TimeSeries <double> x = new TimeSeries <double>();
TimeSeries <double> y = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
x.Value = testVectors[row, 0];
y.Value = testVectors[row, 1];
ITimeSeries <double> response = x.Covariance(y, 5);
//Output.Write("{{{0:F5},{1:F5},", testVectors[row, 0], testVectors[row, 1]);
for (int col = 2; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 2;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5},", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
#endregion
}
public void Test_EMA()
{
double[,] testVectors =
{
{ 100.00000, 100.00000, 100.00000, 100.00000, 100.00000, },
{ 105.00000, 102.00000, 100.00000, 100.00000, 100.00000, },
{ 102.50000, 102.20000, 102.00000, 100.00000, 100.00000, },
{ 107.50000, 104.32000, 102.20000, 102.00000, 100.00000, },
{ 105.00000, 104.59200, 104.32000, 102.20000, 102.00000, },
{ 110.00000, 106.75520, 104.59200, 104.32000, 102.20000, },
{ 107.50000, 107.05312, 106.75520, 104.59200, 104.32000, },
{ 112.50000, 109.23187, 107.05312, 106.75520, 104.59200, },
{ 110.00000, 109.53912, 109.23187, 107.05312, 106.75520, },
{ 115.00000, 111.72347, 109.53912, 109.23187, 107.05312, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response = stimulus.EMA(4);
//Output.Write("{{{0:F5},", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5},", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
public void init()
{
data = new BaseTimeSeries();
data.AddBar(new BaseBar(DateTime.Now.AddDays(1), 168.28M, 169.87M, 167.15M, 169.64M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(2), 168.84M, 169.36M, 168.2M, 168.71M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(3), 168.88M, 169.29M, 166.41M, 167.74M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(4), 168M, 168.38M, 166.18M, 166.32M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(5), 166.89M, 167.7M, 166.33M, 167.24M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(6), 165.25M, 168.43M, 165M, 168.05M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(7), 168.17M, 170.18M, 167.63M, 169.92M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(8), 170.42M, 172.15M, 170.06M, 171.97M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(9), 172.41M, 172.92M, 171.31M, 172.02M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(10), 171.2M, 172.39M, 169.55M, 170.72M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(11), 170.91M, 172.48M, 169.57M, 172.09M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(12), 171.8M, 173.31M, 170.27M, 173.21M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(13), 173.09M, 173.49M, 170.8M, 170.95M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(14), 172.41M, 173.89M, 172.2M, 173.51M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(15), 173.87M, 174.17M, 175M, 172.96M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(16), 173M, 173.17M, 172.06M, 173.05M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(17), 172.26M, 172.28M, 170.5M, 170.96M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(18), 170.88M, 172.34M, 170.26M, 171.64M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(19), 171.85M, 172.07M, 169.34M, 170.01M, 0));
data.AddBar(new BaseBar(DateTime.Now.AddDays(20), 170.75M, 172.56M, 170.36M, 172.52M, 0)); // FB, daily, 9.19.'17
}
public void Test_Normalize()
{
double[,] testVectors =
{
{ 100.00000, 1.00000, 1.00000, 1.00000, 1.00000, },
{ 105.00000, 1.02439, 1.00000, 1.00000, 1.00000, },
{ 102.50000, 1.00000, 1.02439, 1.00000, 1.00000, },
{ 107.50000, 1.02381, 1.00000, 1.02439, 1.00000, },
{ 105.00000, 1.00000, 1.02381, 1.00000, 1.02439, },
{ 110.00000, 1.02326, 1.00000, 1.02381, 1.00000, },
{ 107.50000, 1.00000, 1.02326, 1.00000, 1.02381, },
{ 112.50000, 1.02273, 1.00000, 1.02326, 1.00000, },
{ 110.00000, 1.00000, 1.02273, 1.00000, 1.02326, },
{ 115.00000, 1.02222, 1.00000, 1.02273, 1.00000, },
};
TimeSeries <double> stimulus = new TimeSeries <double>();
for (int row = 0; row <= testVectors.GetUpperBound(0); row++)
{
stimulus.Value = testVectors[row, 0];
ITimeSeries <double> response = stimulus.Normalize(3);
//Output.Write("{{ {0:F5}, ", testVectors[row, 0]);
for (int col = 1; col <= testVectors.GetUpperBound(1); col++)
{
int t = col - 1;
double responseValue = response[t];
double expectedValue = testVectors[row, col];
//Output.Write("{0:F5}, ", responseValue);
Assert.IsTrue(Math.Abs(responseValue - expectedValue) < 1e-5);
}
//Output.WriteLine("},");
}
}
/// <summary>
/// Splits a regular time-series with data gaps into two or more sub-series
/// The maximum allowed gap size is determined by GetDefaultTimeStep()
/// Use this function for stage and discharge
/// </summary>
/// <param name="ts">The time series</param>
/// <returns>the list of splitted regular time-series</returns>
public static List<HydroTimeSeries> SplitTimeSeries(ITimeSeries ts)
{
List<HydroTimeSeries> hsList = new List<HydroTimeSeries>();
List<int> breakIx = GetDataBreaks(ts);
if (breakIx.Count > 0)
{
//for the final segment
if (breakIx[breakIx.Count - 1] != ts.Count - 1)
{
breakIx.Add(ts.Count - 1);
}
int begIndex = 0;
for (int i = 0; i < breakIx.Count; i++)
{
//all data before each break
int endIndex = breakIx[i];
DateTime begDate = DateTime.FromOADate(ts[begIndex].X);
DateTime endDate = DateTime.FromOADate(ts[endIndex].X);
HydroTimeSeries newTs = new HydroTimeSeries(begDate, endDate);
for (int j = begIndex; j <= endIndex; j++)
{
newTs.AddObservation(DateTime.FromOADate(ts[j].X), ts[j].Y);
}
begIndex = endIndex + 1;
if (newTs.Count > 0)
{
hsList.Add(newTs);
}
}
}
else
{
hsList.Add((HydroTimeSeries)ts);
}
return hsList;
}
//plot chart titles and other text description, setup the axes etc.
private void SetupChart(ITimeSeries ts, ChartLabelInfo chartText, string chType, GraphPane pane)
{
//Station st = ts.Station;
//Variable var = ts.Variable;
DateTime start = ts.Start;
DateTime end = ts.End;
DrawTitle(pane, chartText.StationName, chartText.ChannelName, start, end);
SetupAxis(pane, chType, chartText, start, end);
SetupGrid(pane, chType);
SetupLegend(pane);
}
private void PlotVlh(ITimeSeries ts, GraphPane myPane)
{
if (ts.Count > 0)
{
Color lineColor = Color.Blue;
//Main creation of curve
LineItem myCurve = myPane.AddCurve("", ts, lineColor, SymbolType.None);
myCurve.Line.Width = 2F;
myCurve.Line.Fill = new Fill(Color.FromArgb(128, Color.AliceBlue));
}
}
private void SetupChart(ITimeSeries ts, Channel ch, GraphPane pane)
{
Station st = ch.Station;
Variable var = ch.Variable;
DateTime start = ts.Start;
DateTime end = ts.End;
DrawTitle(pane, var, st, start, end);
SetupAxis(pane, var, start, end);
SetupGrid(pane, var.VarEnum);
SetupLegend(pane);
}
public ISquareTimeSeriesData Add(ITimeSeries timeSeries)
{
// implement here
}
public SeriesExtractResult(ITimeSeries series_)
{
Series = series_;
}
private static AnalyticsBondStaticData ConvertCarbonBondStaticToAnalyticBondStatic(ICarbonClient client, ITimeSeries data)
{
var result = new AnalyticsBondStaticData
{
Id = client.GetSingleStaticDataInternal<string>(data, "isin"),
MaturityDate = client.GetSingleStaticDataInternal<DateTime>(data, "maturityDt"),
EffectiveDate = client.GetSingleStaticDataInternal<DateTime>(data, "effectiveDt")
};
// Check if there is a more recent effective date due to subsequent auctions.
DateTime latestEffectiveDate;
object o = data.GetCarbonBondMostRecentEffectiveDate();
if (o is DateTime)
latestEffectiveDate = (DateTime)o;
else
latestEffectiveDate = result.EffectiveDate;
result.FirstCouponDate = client.GetSingleStaticDataInternal<DateTime>(data, "firstCpnDt");
result.Coupon = client.GetSingleStaticDataInternal<double>(data, "cpnRate");
return DecorateAnalyticsBondStaticData(result, latestEffectiveDate);
}
/// <summary>
/// Plot the hourly precipitation !!!!
/// </summary>
private void PlotPrecipHour(ITimeSeries ts, GraphPane myPane)
{
TimeInterval interval = new TimeInterval(ts.Start, ts.End);
string varName = Resources.precip_label;
//Main creation of curve
if ( interval.Length.TotalDays <= 2 )
{
BarItem myCurve = myPane.AddBar(varName, ts, Color.Blue);
myCurve.Bar.Border.Color = Color.Blue;
myCurve.Bar.Border.IsVisible = true;
myCurve.Bar.Fill.Type = FillType.Solid;
myCurve.Bar.Fill.IsScaled = false;
}
else
{
StickItem myCurve = myPane.AddStick(varName, ts, Color.Blue);
}
//cumulative precipitation..
ITimeSeries ts2 = ts.ShowCumulative();
LineItem myCurve2 = myPane.AddCurve(Resources.precip_sum_label,
ts2, Color.Red, SymbolType.None);
myCurve2.IsY2Axis = true;
myPane.AxisChange();
}
public AmountIndicator(ITimeSeries series)
: base(series)
{
_series = series;
}
/** * @param series a time series * @param trade a trade * @return the criterion value for the trade */ public abstract decimal Calculate(ITimeSeries series, Trade trade);
private void PlotSoilWater(ITimeSeries ts, GraphPane myPane)
{
if ( ts.Count > 0 )
{
//Main creation of curve
LineItem myCurve = myPane.AddCurve("", ts, Color.Blue, SymbolType.None);
myCurve.Line.Width = 2F;
}
}
private static List<int> GetDataBreaks(ITimeSeries ts)
{
double breakTresholdDays = 1.1;
List<int> breakIx = new List<int>();
for (int i = 0; i < ts.Count - 1; i++)
{
double x1 = ts[i].X;
double x2 = ts[i + 1].X;
if (x2 - x1 > breakTresholdDays)
{
breakIx.Add(i);
}
}
return breakIx;
}
/// <summary>
/// Plot the snow !!!!
/// </summary>
/// <param name="ts"></param>
/// <param name="myPane"></param>
private void PlotSnow(ITimeSeries ts, GraphPane myPane)
{
TimeInterval interval = new TimeInterval(ts.Start, ts.End);
//Main creation of curve
if ( interval.Length.TotalDays < 160 )
{
BarItem myCurve = myPane.AddBar("", ts, Color.Blue);
myCurve.Bar.Border.Color = Color.Blue;
myCurve.Bar.Border.IsVisible = true;
myCurve.Bar.Fill.Type = FillType.Solid;
myCurve.Bar.Fill.IsScaled = false;
}
else if (interval.Length.TotalDays < 200)
{
StickItem myCurve = myPane.AddStick("", ts, Color.Blue);
}
else if (interval.Length.TotalDays < 400)
{
BarItem myCurve = myPane.AddBar("", ts, Color.Blue);
myCurve.Bar.Border.Color = Color.Blue;
myCurve.Bar.Border.IsVisible = true;
myCurve.Bar.Fill.Type = FillType.Solid;
myCurve.Bar.Fill.IsScaled = false;
}
else
{
StickItem myCurve = myPane.AddStick("", ts, Color.Blue);
}
//else
//{
// StickItem myCurve = myPane.AddStick("", ts, Color.Blue);
// //LineItem myCurve = myPane.AddCurve("", ts, Color.Blue, SymbolType.None);
// //myCurve.Line.Width = 0F;
// //myCurve.Line.Fill = new Fill(Color.Blue);
//}
}
// plot the stage!
private void PlotStageDischarge(ITimeSeries ts, GraphPane myPane)
{
TimeInterval interval = new TimeInterval(ts.Start, ts.End);
if ( ts.Count > 0 )
{
List<HydroTimeSeries> tsList = TimeSeriesManager.SplitTimeSeries(ts);
foreach (HydroTimeSeries ts2 in tsList)
{
LineItem myCurve = myPane.AddCurve("", ts2, Color.Blue, SymbolType.None);
myCurve.Line.Width = 1F;
myCurve.Line.Fill = new Fill(Color.FromArgb(128, Color.Blue));
}
//mark missing data points
if (tsList.Count > 1)
{
TimeStep step = TimeSeriesManager.GetDefaultTimeStep(VariableEnum.Stage, interval);
HydroTimeSeries missingTs = TimeSeriesManager.GetMissingValuesHydro(ts, ts.Start, ts.End, step);
PlotMissingData(missingTs, myPane);
}
}
}
public override decimal Calculate(ITimeSeries series, ITradingRecord tradingRecord)
{
return(_totalProfit.Calculate(series, tradingRecord).DividedBy(_maxDrawdown.Calculate(series, tradingRecord)));
}
/// <summary>
/// Creates a chart - plots are made for all sensors in the time series
/// </summary>
/// <param name="ts">The time series of data to be ploted</param>
/// <param name="ch">The channel (contains station, variable and copyright description)
/// </param>
/// <returns>The chart png image</returns>
public Bitmap CreateChart(Channel ch, ITimeSeries ts)
{
GraphPane pane = SetupGraphPane();
SetupChart(ts, ch, pane);
PlotChartForChannel(ts, ch, pane);
return ExportGraph(pane);
}
/// <summary>
/// puts little "crosses" on missing data points
/// </summary>
private void PlotMissingData(ITimeSeries ts, GraphPane myPane)
{
string noDataText = Resources.no_data;
float crossSize = 10F;
//double yAxisH = myPane.YAxis.Scale.ReverseTransform(crossSize);
double yAxisH = myPane.YAxis.Scale.Max / 25.0;
//ITimeSeries ts2 = ts.ShowUnknown(yAxisH);
for (int i = 0; i < ts.Count; i++ )
{
ts[i].Y = yAxisH;
}
if ( ts != null )
{
if ( ts.Count > 0 )
{
LineItem missingCurve = myPane.AddCurve(noDataText, ts, Color.Red, SymbolType.XCross);
missingCurve.Line.IsVisible = false;
missingCurve.Symbol.Size = crossSize;
missingCurve.Symbol.IsVisible = true;
myPane.AxisChange();
}
}
}
/**
* Constructor.
* @param series the series
* @param timeFrame the time frame
*/
public DPOIndicator(ITimeSeries series, int timeFrame)
: this(new ClosePriceIndicator(series), timeFrame)
{
}
private void PlotChartForChannel(ITimeSeries ts, Channel ch, GraphPane pane)
{
VariableEnum varEnum = ch.Variable.VarEnum;
if (ts.End < Convert.ToDateTime("2013-01-01") && ts.PercentAvailableData < 1.0) //no data..
{
ShowNoDataTextBox(Resources.no_data, pane);
ShowErrorTextBox(Resources.no_data_message, pane);
}
else
{
switch (varEnum)
{
case VariableEnum.Stage:
PlotStageDischarge(ts, pane);
break;
case VariableEnum.Discharge:
PlotStageDischarge(ts, pane);
break;
case VariableEnum.Snow:
PlotSnow(ts, pane);
break;
case VariableEnum.SoilWater10:
case VariableEnum.SoilWater50:
PlotSoilWater(ts, pane);
break;
case VariableEnum.Precip:
PlotPrecip(ts, pane);
break;
case VariableEnum.PrecipHour:
PlotPrecipHour(ts, pane);
break;
case VariableEnum.Temperature:
PlotTemperature(ts, pane);
break;
default:
break;
}
//also plot 'no data' if necessary
if (ch.Variable.VarEnum != VariableEnum.Stage &&
ch.Variable.VarEnum != VariableEnum.Discharge &&
ts.PercentAvailableData > 0.01)
{
//PlotMissingData(ts, pane);
}
//add 'copyright' notice
ShowCopyrightTextBox("data: " + ch.Station.Operator, pane);
}
}
public void setUp()
{
data = new MockTimeSeries(1, 2, 3, 4, 3, 4, 5, 4, 3, 3, 4, 3, 2);
}
public static ITimeSeries MakeCumulative(ITimeSeries ts)
{
HydroTimeSeries ts2 = new HydroTimeSeries(ts.Start, ts.End);
double sum = 0.0;
PointPair curPt;
for ( int i = 0; i < ts.Count; ++i )
{
curPt = ts[i];
if ( curPt.IsMissing )
{
ts2.AddUnknownValue(XDate.XLDateToDateTime(curPt.X));
}
else
{
if (curPt.Y > 0)
{
sum += curPt.Y;
}
ts2.AddObservation(XDate.XLDateToDateTime(curPt.X), sum);
}
}
return ts2;
}
/**
* Constructor with custom parameters and increment value
* @param series the time series for this indicator
* @param aF acceleration factor
* @param MaxA Maximum acceleration
*/
public ParabolicSarIndicator(ITimeSeries series, decimal aF, decimal MaxA)
: this(series, aF, MaxA, 0.02M)
{
}
ITimeSeriesData ITimeSeriesData.Add(ITimeSeries timeSeries)
{
return(this.Add(timeSeries)); // call the overridden Add method
}
private void PlotTemperature(ITimeSeries ts, GraphPane myPane)
{
if (ts.Count > 0)
{
TimeInterval interv = new TimeInterval(ts.Start, ts.End);
TimeStep step = TimeSeriesManager.GetDefaultTimeStep(VariableEnum.Temperature, interv);
ITimeSeries ts2 = TimeSeriesManager.FillDataGaps(ts, step);
LineItem myCurve = myPane.AddCurve("", ts2, Color.Blue, SymbolType.None);
myCurve.Line.Width = 0.5F;
}
}
/** * @param series a time series * @param tradingRecord a trading record * @return the criterion value for the trades */ public abstract decimal Calculate(ITimeSeries series, ITradingRecord tradingRecord);
/// <summary>
/// Creates a chart of given type from the time series
/// </summary>
/// <param name="ts"></param>
/// <param name="labels"></param>
/// <param name="chartType"></param>
/// <returns></returns>
public void CreateChart(ITimeSeries ts, ChartLabelInfo chartText, string chartType, string file)
{
Bitmap bmp;
GraphPane pane = SetupGraphPane();
SetupChart(ts, chartText, chartType, pane);
PlotChartForSensor(ts, pane, chartType);
if (ts.Count == 0 || Math.Abs(ts.MaxValue - ts.MinValue) < 0.001)
{
AddText(pane,"čidlo mimo provoz");
}
bmp = ExportGraph(pane);
string filePath = Path.Combine(_dir , file + ".png");
bmp.Save(filePath, System.Drawing.Imaging.ImageFormat.Png);
//DrawThumb(bmp, file);
bmp.Dispose();
//draws the 'thumb' image
//DrawThumb2(ts, chartType, filePath.Replace(".png", "-m.png"));
DrawThumb(pane, filePath.Replace(".png", "-m.png"));
}
/**
* Constructor.
* @param series a time series
*/
public BullishHaramiIndicator(ITimeSeries series)
: base(series)
{
_series = series;
}
/// <summary>
/// Draws the 'thumb' version of the chart
/// </summary>
/// <param name="ts"></param>
/// <param name="chartType"></param>
/// <param name="file"></param>
private void DrawThumb2(ITimeSeries ts, string chartType, string file)
{
GraphPane myPane = new GraphPane(new RectangleF(0, 0, this.ThumbWidth, this.ThumbHeight),
"", "", "");
if (ts.Count > 0)
{
myPane.XAxis.Scale.Min = XDate.DateTimeToXLDate(ts.Start);
myPane.XAxis.Scale.Max = XDate.DateTimeToXLDate(ts.End);
LineItem myCurve;
StickItem myCurve2;
switch (chartType)
{
case "hla":
myCurve = myPane.AddCurve("", ts, Color.Blue, SymbolType.None);
myCurve.Line.Width = 0;
myCurve.Line.Fill = new Fill(Color.Blue);
break;
case "rad":
myCurve = myPane.AddCurve("", ts, Color.Orange, SymbolType.None);
myCurve.Line.Width = 0;
myCurve.Line.Fill = new Fill(Color.Orange);
break;
case "sra":
myCurve2 = myPane.AddStick("", ts, Color.Blue);
//cumulative precipitation..
ITimeSeries ts2 = ts.ShowCumulative();
myCurve = myPane.AddCurve("", ts2, Color.Red, SymbolType.None);
myCurve.IsY2Axis = true;
break;
case "tep":
myCurve = myPane.AddCurve("", ts, Color.Red, SymbolType.None);
double[] xdata = new double[]{XDate.DateTimeToXLDate(ts.Start),
XDate.DateTimeToXLDate(ts.End)};
double[] ydata = new double[]{0.0, 0.0};
LineItem myCurve3 = myPane.AddCurve("", xdata, ydata, Color.Blue);
break;
default:
myCurve = myPane.AddCurve("", ts, Color.Red, SymbolType.None);
break;
}
myPane.XAxis.IsVisible = false;
myPane.YAxis.IsVisible = false;
myPane.Y2Axis.IsVisible = false;
myPane.XAxis.MajorGrid.IsVisible = false;
myPane.Border.Color = Color.White;
myPane.Legend.IsVisible = false;
myPane.AxisChange();
Bitmap bmp = ExportGraph(myPane);
//string filePath = _dir + "m-" + file;
bmp.Save(file, System.Drawing.Imaging.ImageFormat.Png);
bmp.Dispose();
}
}
public override decimal Calculate(ITimeSeries series, Trade trade)
{
return(_totalProfit.Calculate(series, trade) / _maxDrawdown.Calculate(series, trade));
}
private void PlotChartForSensor(ITimeSeries ts, GraphPane pane, string chartType)
{
switch ( chartType )
{
case "hla":
PlotStage(ts, pane);
break;
case "sra":
PlotPrecipHour(ts, pane);
break;
case "tep":
case "tvo":
case "tpu":
case "tp1":
case "tp2":
PlotTemperature(ts, pane);
break;
case "ph":
PlotPh(ts, pane);
break;
case "rad":
PlotRad(ts, pane);
break;
case "vlh":
PlotVlh(ts, pane);
break;
case "ryv":
PlotRyv(ts, pane);
break;
default:
PlotTemperature(ts, pane);
break;
}
//also plot 'no data' if necessary
//if ( ts.Count > ts.NumValid )
//{
// PlotMissingData(ts, pane);
//}
}
/**
* Constructor.
* <p>
* Calculates the pivot point based on the time level parameter.
* @param series the time series with adequate endTime of each bar for the given time level.
* @param timeLevel the corresponding {@link TimeLevel} for pivot calculation:
* <ul>
* <li>1-, 5-, 10- and 15-Minute charts use the prior days high, low and close: <b>timeLevelId</b> = TimeLevel.DAY</li>
* <li>30- 60- and 120-Minute charts use the prior week's high, low, and close: <b>timeLevelId</b> = TimeLevel.WEEK</li>
* <li>Pivot Points for daily charts use the prior month's high, low and close: <b>timeLevelId</b> = TimeLevel.MONTH</li>
* <li>Pivot Points for weekly and monthly charts use the prior year's high, low and close: <b>timeLevelId</b> = TimeLevel.YEAR (= 4)</li>
* <li> If you want to use just the last bar data: <b>timeLevelId</b> = TimeLevel.BARBASED</li>
* </ul>
* The user has to make sure that there are enough previous bars to Calculate correct pivots at the first bar that matters. For example for PIVOT_TIME_LEVEL_ID_MONTH
* there will be only correct pivot point values (and reversals) after the first complete month
*/
public PivotPointIndicator(ITimeSeries series, TimeLevel timeLevel)
: base(series)
{
_timeLevel = timeLevel;
}
/// <summary>
/// Plot the hourly precipitation !!!!
/// </summary>
/// <param name="ts"></param>
/// <param name="myPane"></param>
private void PlotPrecipHour(ITimeSeries ts, GraphPane myPane)
{
DateTime MinDate, MaxDate;
if (ts.Count > 0)
{
TimeSeries ts1 = (TimeSeries)ts.AggregateHourly();
MinDate = ts1.Start;
MaxDate = ts1.End;
//Main creation of curve
double totalDays = (MaxDate.Subtract(MinDate)).TotalDays;
if (totalDays < 2)
{
BarItem myCurve = myPane.AddBar("srážky", ts1, Color.Blue);
myCurve.Bar.Border.Color = Color.Blue;
myCurve.Bar.Border.IsVisible = true;
myCurve.Bar.Fill.Type = FillType.Solid;
myCurve.Bar.Fill.IsScaled = false;
}
else
{
StickItem myCurve = myPane.AddStick("srážky", ts1, Color.Blue);
}
//cumulative precipitation..
if (ts != null)
{
TimeSeries ts2 = (TimeSeries)ts.ShowCumulative();
LineItem myCurve2 = myPane.AddCurve("suma srážek", ts2, Color.Red, SymbolType.None);
myCurve2.IsY2Axis = true;
myPane.AxisChange();
}
}
}
private decimal _minMaxExtremePoint; // depending on trend the Maximum or Minimum extreme point value of trend
/**
* Constructor with parameters
* @param series the time series for this indicator
*/
public ParabolicSarIndicator(ITimeSeries series)
: this(series, 0.02M, 0.2M, 0.02M)
{
}
/// <summary>
/// Do actual plotting - first try - STAGE !!!
/// </summary>
private void PlotStage(ITimeSeries ts, GraphPane myPane)
{
DateTime MinDate, MaxDate;
if ( ts.Count > 0 )
{
MinDate = ts.Start;
MaxDate = ts.End;
//Main creation of curve
LineItem myCurve = myPane.AddCurve("", ts, Color.Blue, SymbolType.None);
if ( ( (TimeSpan) ( MaxDate - MinDate ) ).TotalDays < 1 )
{
myCurve.Line.Width = 2F;
}
else
{
myCurve.Line.Width = 1F;
myCurve.Line.Fill = new Fill(Color.FromArgb(128, Color.Blue));
}
}
}
public void setUp()
{
timeSeries = new MockTimeSeries();
typicalPriceIndicator = new TypicalPriceIndicator(timeSeries);
}
/// <summary>
/// Plot the temperature !!!!
/// </summary>
/// <param name="ts"></param>
/// <param name="myPane"></param>
private void PlotTemperature(ITimeSeries ts, GraphPane myPane)
{
if (ts.Count > 0)
{
Color lineColor = Color.Red;
//Main creation of curve
LineItem myCurve = myPane.AddCurve("", ts, lineColor, SymbolType.None);
myCurve.Line.Width = 2F;
}
}
private void addSeries(ITimeSeries series_, int yAxisExtent_)
{
if (series_ == null || series_.Series == null) return;
var values = series_.Series;
if (DoCumulative)
values = values.ToCumulative();
var chart = lcdInstrumentHistory.AddSeries(values, series_.Name, yAxisExtent_, "##0.0#");
chart.AxisX.TickmarkStyle = Infragistics.UltraChart.Shared.Styles.AxisTickStyle.Smart;
chart.AxisY.TickmarkStyle = Infragistics.UltraChart.Shared.Styles.AxisTickStyle.Smart;
chart.AxisY.MajorGridLines.Visible = false;
}
