public PriceSeries Clip(int startIndex, int endIndex)
{
var result = new PriceSeries(endIndex - startIndex);
for (int i = startIndex; i < endIndex; i++)
{
result.Add(this[i]);
}
return(result);
}
public PriceSeries GetPriceData(string dataset)
{
if (_dataSets.ContainsKey(dataset))
{
return(_dataSets[dataset]);
}
// e.g. resource format: Abt.Controls.SciChart.Example.Resources.EURUSD_Daily.csv
var csvResource = string.Format("{0}.{1}", ResourceDirectory, Path.ChangeExtension(dataset, "csv"));
var priceSeries = new PriceSeries();
priceSeries.Symbol = dataset;
var assembly = typeof(DataManager).Assembly;
// Debug.WriteLine(string.Join(", ", assembly.GetManifestResourceNames()));
using (var stream = assembly.GetManifestResourceStream(csvResource))
using (var streamReader = new StreamReader(stream))
{
string line = streamReader.ReadLine();
while (line != null)
{
var priceBar = new PriceBar();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
priceBar.DateTime = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo);
priceBar.Open = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
priceBar.High = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
priceBar.Low = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
priceBar.Close = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
priceBar.Volume = long.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
priceSeries.Add(priceBar);
line = streamReader.ReadLine();
}
}
_dataSets.Add(dataset, priceSeries);
return(priceSeries);
}
public PriceSeries GetRandomTrades(out List <Trade> trades, out List <NewsEvent> news)
{
var priceSeries = new PriceSeries();
trades = new List <Trade>();
news = new List <NewsEvent>();
var startDate = new DateTime(2012, 01, 01);
double randomWalk = 0.0;
// Note: Change the value below to increase or decrease the point count and trade frequency
const int Count = 1000;
const uint TradeFrequency = 14;
// Generate the X,Y data with sequential dates on the X-Axis and slightly positively biased random walk on the Y-Axis
for (int i = 0; i < Count; i++)
{
randomWalk += (_random.NextDouble() - 0.498);
priceSeries.Add(new PriceBar(startDate.AddMinutes(i * 10), randomWalk, randomWalk, randomWalk, randomWalk, 0));
}
// The random walk is a truly random series, so it may contain negative values. Here we find the minimum and offset it
// so it is always positive.
double yOffset = -priceSeries.CloseData.Min() + _random.NextDouble();
for (int i = 0; i < Count; i++)
{
// Now update with the offset so it is never negative
priceSeries[i].Close += yOffset;
// Every N'th tick create a random trade
if (i % TradeFrequency == 0)
{
var trade = new Trade();
// randomize buy or sell
trade.BuySell = _random.NextDouble() > 0.48 ? BuySell.Buy : BuySell.Sell;
// Set dealprice and date
trade.DealPrice = priceSeries[i].Close;
trade.TradeDate = priceSeries[i].DateTime;
// Set instrument and quantity
trade.Instrument = Instrument.CrudeOil;
trade.Quantity = _random.Next(100, 500);
trades.Add(trade);
}
// Every N'th tick create a random news event
if (_random.Next(0, 99) > 95)
{
var newsEvent = new NewsEvent();
newsEvent.EventDate = priceSeries[i].DateTime;
newsEvent.Headline = "OPEC meeting minutes";
newsEvent.Body = "The Organization of the Petroleum Exporting Countries voted today to increase production of Crude oil from its member states";
news.Add(newsEvent);
}
}
return(priceSeries);
}
private PriceBar Next(PriceSeries priceSeries)
{
return(priceSeries[_currentIndex++]);
}
