public void TestCSVLoader()
{
var loader = new CSVFinal();
loader.DateFormat = "yyyy.MM.dd hh:mm:ss";
var tickerAAPL = new TickerSymbol("AAPL", "NY");
var desc = new MarketDataDescription(tickerAAPL, MarketDataType.Close, true, true);
MarketMLDataSet marketData = new MarketMLDataSet(loader, 5, 1);
marketData.AddDescription(desc);
marketData.SequenceGrandularity = Util.Time.TimeUnit.Hours;
var begin = new DateTime(2006, 1, 1);
var end = new DateTime(2007, 7, 31);
loader.GetFile((AssemblyDirectory + "\\smallCSV.csv"));
marketData.Load(begin, end);
marketData.Generate();
// first test the points
IEnumerator <TemporalPoint> itr = marketData.Points.GetEnumerator();
itr.MoveNext();
TemporalPoint point = itr.Current;
Assert.AreEqual(0, point.Sequence);
Assert.AreEqual(1, point.Data.Length);
Assert.AreEqual(1.12884, point[0]);
Assert.AreEqual(5, marketData.Points.Count);
}
public void TestCSVLoader()
{
var loader = new CSVFinal();
loader.DateFormat = "yyyy.MM.dd hh:mm:ss";
var tickerAAPL = new TickerSymbol("AAPL", "NY");
var desc = new MarketDataDescription(tickerAAPL, MarketDataType.Close, true, true);
MarketMLDataSet marketData = new MarketMLDataSet(loader, 5, 1);
marketData.AddDescription(desc);
marketData.SequenceGrandularity = Util.Time.TimeUnit.Hours;
var begin = new DateTime(2006, 1, 1);
var end = new DateTime(2007, 7, 31);
loader.GetFile((AssemblyDirectory + "\\smallCSV.csv"));
marketData.Load(begin, end);
marketData.Generate();
// first test the points
IEnumerator<TemporalPoint> itr = marketData.Points.GetEnumerator();
itr.MoveNext();
TemporalPoint point = itr.Current;
Assert.AreEqual(0, point.Sequence);
Assert.AreEqual(1, point.Data.Length);
Assert.AreEqual(1.12884, point[0]);
Assert.AreEqual(5, marketData.Points.Count);
}
public bool Equals(TickerSymbol other)
{
if (other.Symbol.Equals(this.Symbol))
{
if ((other.Exchange == null) && (other.Exchange == null))
{
return true;
}
goto Label_001B;
}
return false;
Label_0017:
return false;
Label_001B:
if (other.Exchange == null)
{
goto Label_0017;
}
do
{
if (this.Exchange == null)
{
goto Label_0017;
}
if (3 != 0)
{
return other.Exchange.Equals(this.Exchange);
}
}
while (0 != 0);
goto Label_001B;
}
/// <summary>
/// Construct a MarketDataDescription item.
/// </summary>
/// <param name="ticker">The ticker symbol to use.</param>
/// <param name="dataType">The data type needed.</param>
/// <param name="type">The normalization type.</param>
/// <param name="activationFunction"> The activation function to apply to this data, can be null.</param>
/// <param name="input">Is this field used for input?</param>
/// <param name="predict">Is this field used for prediction?</param>
public MarketDataDescription(TickerSymbol ticker,
MarketDataType dataType, Type type,
IActivationFunction activationFunction, bool input,
bool predict)
: base(activationFunction, type, input, predict)
{
_ticker = ticker;
_dataType = dataType;
}
/// <summary>
/// Construct a MarketDataDescription item.
/// </summary>
/// <param name="ticker">The ticker symbol to use.</param>
/// <param name="dataType">The data type needed.</param>
/// <param name="type">The normalization type.</param>
/// <param name="activationFunction"> The activation function to apply to this data, can be null.</param>
/// <param name="input">Is this field used for input?</param>
/// <param name="predict">Is this field used for prediction?</param>
public MarketDataDescription(TickerSymbol ticker,
MarketDataType dataType, Type type,
IActivationFunction activationFunction, bool input,
bool predict)
: base(activationFunction, type, input, predict)
{
_ticker = ticker;
_dataType = dataType;
}
/// <summary>
/// Load one ticker symbol.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="from">Load data from this date.</param>
/// <param name="to">Load data to this date.</param>
private void LoadSymbol(TickerSymbol ticker, DateTime from,
DateTime to)
{
ICollection <LoadedMarketData> data = Loader.Load(ticker,
null, from, to);
foreach (LoadedMarketData item in data)
{
TemporalPoint point = CreatePoint(item.When);
LoadPointFromMarketData(ticker, point, item);
}
}
/// <summary>
/// Load one point of market data.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="point">The point to load at.</param>
/// <param name="item">The item being loaded.</param>
private void LoadPointFromMarketData(TickerSymbol ticker,
TemporalPoint point, LoadedMarketData item)
{
foreach (TemporalDataDescription desc in Descriptions)
{
var mdesc = (MarketDataDescription)desc;
if (mdesc.Ticker.Equals(ticker))
{
point.Data[mdesc.Index] = item.Data[mdesc.DataType];
}
}
}
/// <summary>
/// Determine if two ticker symbols equal each other.
/// </summary>
/// <param name="other">The other ticker symbol.</param>
/// <returns>True if the two symbols equal.</returns>
public bool Equals(TickerSymbol other)
{
// if the symbols do not even match then they are not equal
if (!other.Symbol.Equals(this.Symbol))
{
return false;
}
// if the symbols match then we need to compare the exchanges
if (other.Exchange == null && other.Exchange == null)
{
return true;
}
if (other.Exchange == null || this.Exchange == null)
{
return false;
}
return other.Exchange.Equals(this.Exchange);
}
/// <summary>
/// Load one ticker symbol.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="from">Load data from this date.</param>
/// <param name="to">Load data to this date.</param>
private void LoadSymbol(TickerSymbol ticker, DateTime from,
DateTime to)
{
IList <MarketDataType> types = new List <MarketDataType>();
foreach (MarketDataDescription desc in Descriptions)
{
if (desc.Ticker.Equals(ticker))
{
types.Add(desc.DataType);
}
}
ICollection <LoadedMarketData> data = Loader.Load(ticker, types, from, to);
foreach (LoadedMarketData item in data)
{
TemporalPoint point = CreatePoint(item.When);
LoadPointFromMarketData(ticker, point, item);
}
}
/// <summary>
/// Determine if two ticker symbols equal each other.
/// </summary>
/// <param name="other">The other ticker symbol.</param>
/// <returns>True if the two symbols equal.</returns>
public bool Equals(TickerSymbol other)
{
// if the symbols do not even match then they are not equal
if (!other.Symbol.Equals(this.Symbol))
{
return(false);
}
// if the symbols match then we need to compare the exchanges
if (other.Exchange == null && other.Exchange == null)
{
return(true);
}
if (other.Exchange == null || this.Exchange == null)
{
return(false);
}
return(other.Exchange.Equals(this.Exchange));
}
/// <summary>
/// Load one ticker symbol.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="from">Load data from this date.</param>
/// <param name="to">Load data to this date.</param>
private void LoadSymbol(TickerSymbol ticker, DateTime from,
DateTime to)
{
IList < MarketDataType > types = new List<MarketDataType>();
foreach (MarketDataDescription desc in Descriptions)
{
if (desc.Ticker.Equals(ticker))
{
types.Add(desc.DataType);
}
}
ICollection<LoadedMarketData> data = Loader.Load(ticker, types, from, to);
foreach (LoadedMarketData item in data)
{
TemporalPoint point = CreatePoint(item.When);
LoadPointFromMarketData(ticker, point, item);
}
}
/// <summary>
/// Load one point of market data.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="point">The point to load at.</param>
/// <param name="item">The item being loaded.</param>
private void LoadPointFromMarketData(TickerSymbol ticker,
TemporalPoint point, LoadedMarketData item)
{
foreach (TemporalDataDescription desc in Descriptions)
{
var mdesc = (MarketDataDescription) desc;
if (mdesc.Ticker.Equals(ticker))
{
point.Data[mdesc.Index] = item.Data[mdesc.DataType];
}
}
}
public void MarketData()
{
IMarketLoader loader = new YahooFinanceLoader();
var tickerAAPL = new TickerSymbol("AAPL", null);
var tickerMSFT = new TickerSymbol("MSFT", null);
var marketData = new MarketMLDataSet(loader, 5, 1);
marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Close, true, true));
marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Close, true, false));
marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Volume, true, false));
marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Volume, true, false));
var begin = new DateTime(2008, 7, 1);
var end = new DateTime(2008, 7, 31);
marketData.Load(begin, end);
marketData.Generate();
Assert.AreEqual(22, marketData.Points.Count);
// first test the points
IEnumerator <TemporalPoint> itr = marketData.Points.GetEnumerator();
itr.MoveNext();
TemporalPoint point = itr.Current;
Assert.AreEqual(0, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(174.68, point[0]);
Assert.AreEqual(26.87, point[1]);
Assert.AreEqual(39, (int)(point[2] / 1000000));
Assert.AreEqual(100, (int)(point[3] / 1000000));
itr.MoveNext();
point = itr.Current;
Assert.AreEqual(1, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(168.18, point[0]);
Assert.AreEqual(25.88, point[1]);
Assert.AreEqual(29, (int)(point[2] / 1000000));
Assert.AreEqual(84, (int)(point[3] / 1000000));
itr.MoveNext();
point = itr.Current;
Assert.AreEqual(2, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(170.12, point[0]);
Assert.AreEqual(25.98, point[1]);
Assert.AreEqual(18, (int)(point[2] / 1000000));
Assert.AreEqual(37, (int)(point[3] / 1000000));
// now check the actual data
Assert.AreEqual(16, marketData.Data.Count);
Assert.AreEqual(20, marketData.InputNeuronCount);
Assert.AreEqual(1, marketData.OutputNeuronCount);
IEnumerator <IMLDataPair> itr2 = marketData.Data.GetEnumerator();
itr2.MoveNext();
IMLDataPair pair = itr2.Current;
Assert.AreEqual(20, pair.Input.Count);
Assert.AreEqual(1, pair.Ideal.Count);
Assert.AreEqual(-0.037, Math.Round(pair.Input[0] * 1000.0) / 1000.0);
Assert.AreEqual(-0.037, Math.Round(pair.Input[1] * 1000.0) / 1000.0);
Assert.AreEqual(-0.246, Math.Round(pair.Input[2] * 1000.0) / 1000.0);
Assert.AreEqual(-0.156, Math.Round(pair.Input[3] * 1000.0) / 1000.0);
Assert.AreEqual(0.012, Math.Round(pair.Input[4] * 1000.0) / 1000.0);
Assert.AreEqual(0.0040, Math.Round(pair.Input[5] * 1000.0) / 1000.0);
Assert.AreEqual(-0.375, Math.Round(pair.Input[6] * 1000.0) / 1000.0);
Assert.AreEqual(-0.562, Math.Round(pair.Input[7] * 1000.0) / 1000.0);
Assert.AreEqual(0.03, Math.Round(pair.Input[8] * 1000.0) / 1000.0);
Assert.AreEqual(0.0020, Math.Round(pair.Input[9] * 1000.0) / 1000.0);
Assert.AreEqual(0.57, Math.Round(pair.Input[10] * 100.0) / 100.0);
Assert.AreEqual(0.929, Math.Round(pair.Input[11] * 1000.0) / 1000.0);
Assert.AreEqual(0.025, Math.Round(pair.Input[12] * 1000.0) / 1000.0);
Assert.AreEqual(-0.0070, Math.Round(pair.Input[13] * 1000.0) / 1000.0);
// for some reason, Yahoo likes to vary the volume numbers slightly, sometimes!
Assert.AreEqual(0.1, Math.Round(pair.Input[14] * 10.0) / 10.0);
Assert.AreEqual(-0.084, Math.Round(pair.Input[15] * 1000.0) / 1000.0);
Assert.AreEqual(-0.03, Math.Round(pair.Input[16] * 1000.0) / 1000.0);
Assert.AreEqual(-0.024, Math.Round(pair.Input[17] * 1000.0) / 1000.0);
Assert.AreEqual(0.008, Math.Round(pair.Input[18] * 1000.0) / 1000.0);
Assert.AreEqual(-0.172, Math.Round(pair.Input[19] * 1000.0) / 1000.0);
itr2.MoveNext();
pair = itr2.Current;
Assert.AreEqual(20, pair.Input.Count);
Assert.AreEqual(1, pair.Ideal.Count);
Assert.AreEqual(0.012, Math.Round(pair.Input[0] * 1000.0) / 1000.0);
Assert.AreEqual(0.0040, Math.Round(pair.Input[1] * 1000.0) / 1000.0);
Assert.AreEqual(-0.375, Math.Round(pair.Input[2] * 1000.0) / 1000.0);
Assert.AreEqual(-0.562, Math.Round(pair.Input[3] * 1000.0) / 1000.0);
Assert.AreEqual(0.03, Math.Round(pair.Input[4] * 1000.0) / 1000.0);
Assert.AreEqual(0.0020, Math.Round(pair.Input[5] * 1000.0) / 1000.0);
Assert.AreEqual(0.6, Math.Round(pair.Input[6] * 10.0) / 10.0);
Assert.AreEqual(0.929, Math.Round(pair.Input[7] * 1000.0) / 1000.0);
Assert.AreEqual(0.025, Math.Round(pair.Input[8] * 1000.0) / 1000.0);
Assert.AreEqual(-0.0070, Math.Round(pair.Input[9] * 1000.0) / 1000.0);
Assert.AreEqual(0.1, Math.Round(pair.Input[10] * 10.0) / 10.0);
Assert.AreEqual(-0.084, Math.Round(pair.Input[11] * 1000.0) / 1000.0);
Assert.AreEqual(-0.03, Math.Round(pair.Input[12] * 1000.0) / 1000.0);
Assert.AreEqual(-0.024, Math.Round(pair.Input[13] * 1000.0) / 1000.0);
Assert.AreEqual(0.0080, Math.Round(pair.Input[14] * 1000.0) / 1000.0);
Assert.AreEqual(-0.172, Math.Round(pair.Input[15] * 1000.0) / 1000.0);
Assert.AreEqual(0.014, Math.Round(pair.Input[16] * 1000.0) / 1000.0);
Assert.AreEqual(0.0090, Math.Round(pair.Input[17] * 1000.0) / 1000.0);
Assert.AreEqual(-0.1, Math.Round(pair.Input[18] * 10.0) / 10.0);
Assert.AreEqual(0.066, Math.Round(pair.Input[19] * 1000.0) / 1000.0);
}
/// <summary>
/// Load the market data.
/// </summary>
/// <returns>True if the data was loaded.</returns>
private bool LoadMarketData()
{
try
{
IMarketLoader loader = new YahooFinanceLoader();
TickerSymbol ticker = new TickerSymbol(this.Company.Text);
IList<MarketDataType> needed = new List<MarketDataType>();
needed.Add(MarketDataType.AdjustedClose);
needed.Add(MarketDataType.Close);
needed.Add(MarketDataType.Open);
needed.Add(MarketDataType.High);
needed.Add(MarketDataType.Low);
DateTime from = this.starting -TimeSpan.FromDays(365);
DateTime to = this.starting + TimeSpan.FromDays(365*2);
this.marketData = (List<LoadedMarketData>)loader.Load(ticker, needed, from, to);
this.marketData.Sort();
this.numberOfDays = (int)((ActualWidth - FIRST_DAY_OFFSET) / DAY_WIDTH);
this.numberOfDays = Math.Min(numberOfDays, this.marketData.Count);
return true;
}
catch (Exception e)
{
MessageBox.Show("Ticker symbol likely invalid.\n"+e.Message, "Error Loading Data");
return false;
}
}
/// <summary>
/// Construct a MarketDataDescription item.
/// </summary>
/// <param name="ticker">The ticker symbol to use.</param>
/// <param name="dataType">The data type needed.</param>
/// <param name="input">Is this field used for input?</param>
/// <param name="predict">Is this field used for prediction?</param>
public MarketDataDescription(TickerSymbol ticker,
MarketDataType dataType, bool input,
bool predict)
: this(ticker, dataType, Type.PercentChange, null, input, predict)
{
}
private void xb45ce8e0e2f1da44(TickerSymbol x96e4701dec47675e, DateTime x7f8a886f51b477eb, DateTime x3ed4f4f0195b98d7)
{
foreach (LoadedMarketData data in this.Loader.Load(x96e4701dec47675e, null, x7f8a886f51b477eb, x3ed4f4f0195b98d7))
{
TemporalPoint point = this.CreatePoint(data.When);
this.xd619c0bf81b12658(x96e4701dec47675e, point, data);
}
}
public ICollection<LoadedMarketData> Load(TickerSymbol ticker, IList<MarketDataType> dataNeeded, DateTime from, DateTime to)
{
ICollection<LoadedMarketData> is2 = new List<LoadedMarketData>();
HttpWebResponse response = (HttpWebResponse) WebRequest.Create(x38c212309d8d5dd3(ticker, from, to)).GetResponse();
using (Stream stream = response.GetResponseStream())
{
DateTime time;
double num;
double num2;
double num3;
double num4;
double num5;
double num6;
LoadedMarketData data;
ReadCSV dcsv = new ReadCSV(stream, true, CSVFormat.DecimalPoint);
goto Label_005B;
Label_003F:
data.SetData(MarketDataType.Open, num2);
Label_0049:
data.SetData(MarketDataType.Volume, num6);
is2.Add(data);
Label_005B:
if (dcsv.Next())
{
goto Label_01AF;
}
dcsv.Close();
stream.Close();
if ((((uint) num) - ((uint) num5)) <= uint.MaxValue)
{
goto Label_0125;
}
if ((((uint) num) & 0) == 0)
{
goto Label_00B0;
}
Label_00A4:
data.SetData(MarketDataType.Low, num5);
goto Label_003F;
Label_00B0:
data.SetData(MarketDataType.AdjustedClose, num);
do
{
data.SetData(MarketDataType.Open, num2);
if ((((uint) num) - ((uint) num6)) > uint.MaxValue)
{
goto Label_0049;
}
data.SetData(MarketDataType.Close, num3);
data.SetData(MarketDataType.High, num4);
}
while ((((uint) num5) - ((uint) num3)) > uint.MaxValue);
if (((uint) num2) >= 0)
{
goto Label_00A4;
}
goto Label_003F;
Label_0125:
if (((uint) num2) >= 0)
{
return is2;
}
goto Label_005B;
Label_013C:
num6 = dcsv.GetDouble("volume");
data = new LoadedMarketData(time, ticker);
if ((((uint) num2) | 2) == 0)
{
goto Label_017C;
}
goto Label_00B0;
Label_016E:
num2 = dcsv.GetDouble("open");
Label_017C:
num3 = dcsv.GetDouble("close");
num4 = dcsv.GetDouble("high");
num5 = dcsv.GetDouble("low");
goto Label_013C;
Label_01AF:
time = dcsv.GetDate("date");
num = dcsv.GetDouble("adj close");
if ((((uint) num3) + ((uint) num6)) <= uint.MaxValue)
{
goto Label_016E;
}
goto Label_00B0;
}
}
/// <derived/>
public ICollection<LoadedMarketData> Load(TickerSymbol ticker, IList<MarketDataType> dataNeeded,
DateTime from, DateTime to)
{
try
{
string fileCSV = "";
foreach (TickerSymbol tickerSymbol in fileList.Keys)
{
if (tickerSymbol.Symbol.ToLower().Equals(ticker.Symbol.ToLower()))
{
if (fileList.TryGetValue(tickerSymbol, out fileCSV))
{
return File.Exists(fileCSV) ?
(ReadAndCallLoader(tickerSymbol, dataNeeded, from, to, fileCSV)) : null; //If file does not exist
}
return null; //Problem reading list
}
}
return null; //if ticker is not defined
}
catch (FileNotFoundException fnfe)
{
Console.WriteLine("Problem with loading data for instruments", fnfe);
return null;
}
}
/// <summary>
/// Construct a MarketDataDescription item.
/// </summary>
/// <param name="ticker">The ticker symbol to use.</param>
/// <param name="dataType">The data type needed.</param>
/// <param name="input">Is this field used for input?</param>
/// <param name="predict">Is this field used for prediction?</param>
public MarketDataDescription(TickerSymbol ticker,
MarketDataType dataType, bool input,
bool predict)
: this(ticker, dataType, Type.PercentChange, null, input, predict)
{
}
public ICollection<LoadedMarketData> ReadAndCallLoader(TickerSymbol symbol, IList<MarketDataType> neededTypes, DateTime from, DateTime to, string File)
{
try
{
ReadCSV dcsv;
DateTime time;
double num;
double num2;
double num3;
double num4;
double num5;
LoadedMarketData data;
ICollection<LoadedMarketData> is3;
ICollection<LoadedMarketData> is2 = new List<LoadedMarketData>();
goto Label_0109;
Label_000B:
is3 = is2;
if ((((uint) num5) + ((uint) num4)) >= 0)
{
return is3;
}
if ((((uint) num3) & 0) == 0)
{
goto Label_0088;
}
Label_003D:
is2.Add(data);
Label_0045:
if (dcsv.Next())
{
goto Label_00EF;
}
Label_0050:
dcsv.Close();
if (0 == 0)
{
goto Label_000B;
}
goto Label_0088;
Label_005E:
data.SetData(MarketDataType.High, num3);
data.SetData(MarketDataType.Low, num4);
data.SetData(MarketDataType.Close, num2);
data.SetData(MarketDataType.Volume, num5);
goto Label_003D;
Label_0088:
num2 = dcsv.GetDouble("High");
num3 = dcsv.GetDouble("Low");
num4 = dcsv.GetDouble("Close");
num5 = dcsv.GetDouble("Volume");
new LoadedMarketData(time, symbol).SetData(MarketDataType.Open, num);
if (((uint) num3) >= 0)
{
goto Label_005E;
}
goto Label_003D;
Label_00EF:
time = dcsv.GetDate("Time");
num = dcsv.GetDouble("Open");
goto Label_0088;
Label_0109:
dcsv = new ReadCSV(File, true, this.x9c5d9c5f2c877175);
if (((uint) num3) > uint.MaxValue)
{
goto Label_000B;
}
dcsv.DateFormat = this.x21d82b8f3e4c4642.Normalize();
if (((uint) num3) > uint.MaxValue)
{
goto Label_0050;
}
goto Label_0045;
}
catch (Exception exception)
{
Console.WriteLine("Something went wrong reading the csv");
Console.WriteLine("Something went wrong reading the csv:" + exception.Message);
}
Console.WriteLine("Something went wrong reading the csv");
return null;
}
private static Uri x38c212309d8d5dd3(TickerSymbol x96e4701dec47675e, DateTime x7f8a886f51b477eb, DateTime x3ed4f4f0195b98d7)
{
byte[] buffer;
MemoryStream os = new MemoryStream();
FormUtility utility = new FormUtility(os, null);
utility.Add("s", x96e4701dec47675e.Symbol.ToUpper());
if (0 == 0)
{
utility.Add("a", (x7f8a886f51b477eb.Month - 1));
utility.Add("b", x7f8a886f51b477eb.Day);
if (4 == 0)
{
goto Label_0018;
}
utility.Add("c", x7f8a886f51b477eb.Year);
utility.Add("d", (x3ed4f4f0195b98d7.Month - 1));
utility.Add("e", x3ed4f4f0195b98d7.Day);
utility.Add("f", x3ed4f4f0195b98d7.Year);
utility.Add("g", "d");
goto Label_0061;
}
Label_000B:
if (0x7fffffff == 0)
{
goto Label_0061;
}
os.Close();
Label_0018:
buffer = os.GetBuffer();
return new Uri("http://ichart.finance.yahoo.com/table.csv?" + StringUtil.FromBytes(buffer));
Label_0061:
utility.Add("ignore", ".csv");
goto Label_000B;
}
public MarketDataDescription(TickerSymbol ticker, MarketDataType dataType, TemporalDataDescription.Type type, IActivationFunction activationFunction, bool input, bool predict)
: base(activationFunction, type, input, predict)
{
this._x96e4701dec47675e = ticker;
this._xd2f3d36b96df4542 = dataType;
}
public MarketDataDescription(TickerSymbol ticker, MarketDataType dataType, TemporalDataDescription.Type type, bool input, bool predict)
: this(ticker, dataType, type, null, input, predict)
{
}
private void xd619c0bf81b12658(TickerSymbol x96e4701dec47675e, TemporalPoint x2f7096dac971d6ec, LoadedMarketData xccb63ca5f63dc470)
{
foreach (TemporalDataDescription description in this.Descriptions)
{
MarketDataDescription description2 = (MarketDataDescription) description;
if (description2.Ticker.Equals(x96e4701dec47675e))
{
x2f7096dac971d6ec.Data[description2.Index] = xccb63ca5f63dc470.Data[description2.DataType];
}
}
}
/// <summary>
/// Reads and parses CSV data from file
/// </summary>
/// <param name="ticker">Ticker associated with CSV file</param>
/// <param name="neededTypes">Columns to parse (headers)</param>
/// <param name="from">DateTime from</param>
/// <param name="to">DateTime to</param>
/// <param name="File">Filepath to CSV</param>
/// <returns>Marketdata</returns>
public ICollection<LoadedMarketData> ReadAndCallLoader(TickerSymbol ticker, IList<MarketDataType> neededTypes, DateTime from, DateTime to, string File)
{
try
{
LoadedFile = File;
Console.WriteLine("Loading instrument: " + ticker.Symbol + " from: " + File);
//We got a file, lets load it.
ICollection<LoadedMarketData> result = new List<LoadedMarketData>();
ReadCSV csv = new ReadCSV(File, true, LoadedFormat);
if (DateTimeDualColumn)
{
csv.DateFormat = DateFormat;
csv.TimeFormat = TimeFormat;
}
else
{
csv.DateFormat = DateFormat;
}
//"Date","Time","Open","High","Low","Close","Volume"
while (csv.Next())
{
string datetime = "";
if (DateTimeDualColumn)
{
datetime = csv.GetDate("Date").ToShortDateString() + " " +
csv.GetTime("Time").ToShortTimeString();
}
else
{
datetime = csv.GetDate("Date").ToShortDateString();
}
DateTime date = DateTime.Parse(datetime);
if (date > from && date < to)
{
// CSV columns
double open = csv.GetDouble("Open");
double high = csv.GetDouble("High");
double low = csv.GetDouble("Low");
double close = csv.GetDouble("Close");
double volume = csv.GetDouble("Volume");
LoadedMarketData data = new LoadedMarketData(date, ticker);
foreach (MarketDataType marketDataType in neededTypes)
{
switch (marketDataType.ToString())
{
case "Open":
data.SetData(MarketDataType.Open, open);
break;
case "High":
data.SetData(MarketDataType.High, high);
break;
case "Low":
data.SetData(MarketDataType.Low, low);
break;
case "Close":
data.SetData(MarketDataType.Close, close);
break;
case "Volume":
data.SetData(MarketDataType.Volume, volume);
break;
case "RangeHighLow":
data.SetData(MarketDataType.RangeHighLow, Math.Round(Math.Abs(high - low), 6));
break;
case "RangeOpenClose":
data.SetData(MarketDataType.RangeOpenClose, Math.Round(Math.Abs(close - open), 6));
break;
case "RangeOpenCloseNonAbsolute":
data.SetData(MarketDataType.RangeOpenCloseNonAbsolute, Math.Round(close - open, 6));
break;
case "Weighted":
data.SetData(MarketDataType.Weighted, Math.Round((high + low + 2 * close) / 4, 6));
break;
}
}
result.Add(data);
}
}
csv.Close();
return result;
}
catch (Exception ex)
{
Console.WriteLine("Something went wrong reading the csv: " + ex.Message);
}
return null;
}
public void MarketData()
{
IMarketLoader loader = new YahooFinanceLoader();
var tickerAAPL = new TickerSymbol("AAPL", null);
var tickerMSFT = new TickerSymbol("MSFT", null);
var marketData = new MarketMLDataSet(loader, 5, 1);
marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Close, true, true));
marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Close, true, false));
marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Volume, true, false));
marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Volume, true, false));
var begin = new DateTime(2008, 7, 1);
var end = new DateTime(2008, 7, 31);
marketData.Load(begin, end);
marketData.Generate();
Assert.AreEqual(22, marketData.Points.Count);
// first test the points
IEnumerator<TemporalPoint> itr = marketData.Points.GetEnumerator();
itr.MoveNext();
TemporalPoint point = itr.Current;
Assert.AreEqual(0, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(174.68, point[0]);
Assert.AreEqual(26.87, point[1]);
Assert.AreEqual(39, (int) (point[2]/1000000));
Assert.AreEqual(100, (int) (point[3]/1000000));
itr.MoveNext();
point = itr.Current;
Assert.AreEqual(1, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(168.18, point[0]);
Assert.AreEqual(25.88, point[1]);
Assert.AreEqual(29, (int) (point[2]/1000000));
Assert.AreEqual(84, (int) (point[3]/1000000));
itr.MoveNext();
point = itr.Current;
Assert.AreEqual(2, point.Sequence);
Assert.AreEqual(4, point.Data.Length);
Assert.AreEqual(170.12, point[0]);
Assert.AreEqual(25.98, point[1]);
Assert.AreEqual(18, (int) (point[2]/1000000));
Assert.AreEqual(37, (int) (point[3]/1000000));
// now check the actual data
Assert.AreEqual(16, marketData.Data.Count);
Assert.AreEqual(20, marketData.InputNeuronCount);
Assert.AreEqual(1, marketData.OutputNeuronCount);
IEnumerator<IMLDataPair> itr2 = marketData.Data.GetEnumerator();
itr2.MoveNext();
IMLDataPair pair = itr2.Current;
Assert.AreEqual(20, pair.Input.Count);
Assert.AreEqual(1, pair.Ideal.Count);
Assert.AreEqual(-0.037, Math.Round(pair.Input[0]*1000.0)/1000.0);
Assert.AreEqual(-0.037, Math.Round(pair.Input[1]*1000.0)/1000.0);
Assert.AreEqual(-0.246, Math.Round(pair.Input[2]*1000.0)/1000.0);
Assert.AreEqual(-0.156, Math.Round(pair.Input[3]*1000.0)/1000.0);
Assert.AreEqual(0.012, Math.Round(pair.Input[4]*1000.0)/1000.0);
Assert.AreEqual(0.0040, Math.Round(pair.Input[5]*1000.0)/1000.0);
Assert.AreEqual(-0.375, Math.Round(pair.Input[6]*1000.0)/1000.0);
Assert.AreEqual(-0.562, Math.Round(pair.Input[7]*1000.0)/1000.0);
Assert.AreEqual(0.03, Math.Round(pair.Input[8]*1000.0)/1000.0);
Assert.AreEqual(0.0020, Math.Round(pair.Input[9]*1000.0)/1000.0);
Assert.AreEqual(0.57, Math.Round(pair.Input[10]*100.0)/100.0);
Assert.AreEqual(0.929, Math.Round(pair.Input[11]*1000.0)/1000.0);
Assert.AreEqual(0.025, Math.Round(pair.Input[12]*1000.0)/1000.0);
Assert.AreEqual(-0.0070, Math.Round(pair.Input[13]*1000.0)/1000.0);
// for some reason, Yahoo likes to vary the volume numbers slightly, sometimes!
Assert.AreEqual(0.1, Math.Round(pair.Input[14]*10.0)/10.0);
Assert.AreEqual(-0.084, Math.Round(pair.Input[15]*1000.0)/1000.0);
Assert.AreEqual(-0.03, Math.Round(pair.Input[16]*1000.0)/1000.0);
Assert.AreEqual(-0.024, Math.Round(pair.Input[17]*1000.0)/1000.0);
Assert.AreEqual(0.008, Math.Round(pair.Input[18]*1000.0)/1000.0);
Assert.AreEqual(-0.172, Math.Round(pair.Input[19]*1000.0)/1000.0);
itr2.MoveNext();
pair = itr2.Current;
Assert.AreEqual(20, pair.Input.Count);
Assert.AreEqual(1, pair.Ideal.Count);
Assert.AreEqual(0.012, Math.Round(pair.Input[0]*1000.0)/1000.0);
Assert.AreEqual(0.0040, Math.Round(pair.Input[1]*1000.0)/1000.0);
Assert.AreEqual(-0.375, Math.Round(pair.Input[2]*1000.0)/1000.0);
Assert.AreEqual(-0.562, Math.Round(pair.Input[3]*1000.0)/1000.0);
Assert.AreEqual(0.03, Math.Round(pair.Input[4]*1000.0)/1000.0);
Assert.AreEqual(0.0020, Math.Round(pair.Input[5]*1000.0)/1000.0);
Assert.AreEqual(0.6, Math.Round(pair.Input[6]*10.0)/10.0);
Assert.AreEqual(0.929, Math.Round(pair.Input[7]*1000.0)/1000.0);
Assert.AreEqual(0.025, Math.Round(pair.Input[8]*1000.0)/1000.0);
Assert.AreEqual(-0.0070, Math.Round(pair.Input[9]*1000.0)/1000.0);
Assert.AreEqual(0.1, Math.Round(pair.Input[10]*10.0)/10.0);
Assert.AreEqual(-0.084, Math.Round(pair.Input[11]*1000.0)/1000.0);
Assert.AreEqual(-0.03, Math.Round(pair.Input[12]*1000.0)/1000.0);
Assert.AreEqual(-0.024, Math.Round(pair.Input[13]*1000.0)/1000.0);
Assert.AreEqual(0.0080, Math.Round(pair.Input[14]*1000.0)/1000.0);
Assert.AreEqual(-0.172, Math.Round(pair.Input[15]*1000.0)/1000.0);
Assert.AreEqual(0.014, Math.Round(pair.Input[16]*1000.0)/1000.0);
Assert.AreEqual(0.0090, Math.Round(pair.Input[17]*1000.0)/1000.0);
Assert.AreEqual(-0.1, Math.Round(pair.Input[18]*10.0)/10.0);
Assert.AreEqual(0.066, Math.Round(pair.Input[19]*1000.0)/1000.0);
}
/// <summary>
/// Load one ticker symbol.
/// </summary>
/// <param name="ticker">The ticker symbol to load.</param>
/// <param name="from">Load data from this date.</param>
/// <param name="to">Load data to this date.</param>
private void LoadSymbol(TickerSymbol ticker, DateTime from,
DateTime to)
{
ICollection<LoadedMarketData> data = Loader.Load(ticker,
null, from, to);
foreach (LoadedMarketData item in data)
{
TemporalPoint point = CreatePoint(item.When);
LoadPointFromMarketData(ticker, point, item);
}
}
public ICollection<LoadedMarketData> Load(TickerSymbol ticker, IList<MarketDataType> dataNeeded, DateTime from, DateTime to)
{
CSVFormLoader loader;
ICollection<LoadedMarketData> is2 = new List<LoadedMarketData>();
if (0 == 0)
{
loader = new CSVFormLoader();
if ((0 == 0) && !File.Exists(loader.Chosenfile))
{
return null;
}
}
this.x9c5d9c5f2c877175 = loader.format;
foreach (MarketDataType type in loader.TypesLoaded)
{
this.TypesLoaded.Add(type);
}
this.x21d82b8f3e4c4642 = loader.DateTimeFormatTextBox.Text;
return this.ReadAndCallLoader(ticker, dataNeeded, from, to, loader.Chosenfile);
}
/// <summary>
/// Called to load training data for a company. This is how the training data is actually created.
/// To prepare input data for recognition use the CreateData method. The training set will be
/// added to. This allows the network to learn from multiple companies if this method is called
/// multiple times.
/// </summary>
/// <param name="symbol">The ticker symbol.</param>
/// <param name="training">The training set to add to.</param>
/// <param name="from">Beginning date</param>
/// <param name="to">Ending date</param>
public void LoadCompany(String symbol, BasicMLDataSet training, DateTime from, DateTime to)
{
IMarketLoader loader = new YahooFinanceLoader();
TickerSymbol ticker = new TickerSymbol(symbol);
IList<MarketDataType> dataNeeded = new List<MarketDataType>();
dataNeeded.Add(MarketDataType.AdjustedClose);
dataNeeded.Add(MarketDataType.Close);
dataNeeded.Add(MarketDataType.Open);
dataNeeded.Add(MarketDataType.High);
dataNeeded.Add(MarketDataType.Low);
List<LoadedMarketData> results = (List<LoadedMarketData>)loader.Load(ticker, dataNeeded, from, to);
results.Sort();
for (int index = PredictWindow; index < results.Count - EvalWindow; index++)
{
LoadedMarketData data = results[index];
// determine bull or bear position, or neither
bool bullish = false;
bool bearish = false;
for (int search = 1; search <= EvalWindow; search++)
{
LoadedMarketData data2 = results[index + search];
double priceBase = data.GetData(MarketDataType.AdjustedClose);
double priceCompare = data2.GetData(MarketDataType.AdjustedClose);
double diff = priceCompare - priceBase;
double percent = diff / priceBase;
if (percent > BullPercent)
{
bullish = true;
}
else if (percent < BearPercent)
{
bearish = true;
}
}
IMLDataPair pair = null;
if (bullish)
{
pair = CreateData(results, index, true);
}
else if (bearish)
{
pair = CreateData(results, index, false);
}
if (pair != null)
{
training.Add(pair);
}
}
}
