/// <summary>
/// Converts the dataframe to time serires <see cref="XYFrame"/> dataframe.
/// </summary>
/// <param name="lookback">The lookback count.</param>
/// <param name="useColumn">The column number to use for creating time series data.</param>
/// <returns></returns>
public XYFrame ConvertTimeSeries(int lookback = 1, int useColumn = 0)
{
XYFrame result = new XYFrame();
List <float> data = Data.Select(x => (x[useColumn])).ToList();
for (int i = 0; i < data.Count; i++)
{
if (i + lookback > data.Count - 1)
{
continue;
}
List <float> values = new List <float>();
int counter = i;
while (counter < i + lookback)
{
values.Add(data[counter]);
counter++;
}
result.XFrame.Add(values);
result.YFrame.Add(new List <float>()
{
data[i + lookback]
});
}
return(result);
}
/// <summary>
/// Trains the model for a fixed number of epochs.
/// </summary>
/// <param name="train">The training dataset.</param>
/// <param name="epoches">The no. of trainin epoches.</param>
/// <param name="batchSize">Size of the batch for training.</param>
/// <param name="validation">The validation dataset.</param>
public void Train(XYFrame train, int epoches, int batchSize, XYFrame validation = null)
{
OnTrainingStart();
trainPredict = new DataFrameTrainPredict(modelOut, lossFunc, lossName, metricFunc, metricName, learners, featureVariable, labelVariable);
TrainingResult = trainPredict.Train(train, validation, epoches, batchSize, OnEpochStart, OnEpochEnd, OnBatchStart, OnBatchEnd);
OnTrainingEnd(TrainingResult);
}
/// <summary>
/// Gets the next batch of data for training.
/// </summary>
/// <param name="current">The current batch number.</param>
/// <param name="batchSize">Size of the batch.</param>
/// <returns></returns>
public bool ToBatch(uint current, uint batchSize)
{
bool next = true;
int totalRows = XFrame.Data.Count;
uint skipRows = (current - 1) * batchSize;
if (skipRows < totalRows)
{
CurrentBatch = new XYFrame
{
XFrame =
{
Data = XFrame.Data.Skip((int)skipRows).Take((int)batchSize).ToList(),
Columns = XFrame.Columns
},
YFrame =
{
Data = YFrame.Data.Skip((int)skipRows).Take((int)batchSize).ToList(),
Columns = YFrame.Columns
}
};
}
else
{
next = false;
CurrentBatch = null;
}
return next;
}
/// <summary>
/// Splits the dataset to X and Y set.
/// </summary>
/// <param name="yCol">The y columns number.</param>
/// <param name="xCols">The x columns numbers.</param>
/// <returns>XY frame set.</returns>
public XYFrame SplitXY(int yCol, int[] xCols)
{
XYFrame result = new XYFrame();
result.XFrame = new DataFrame();
result.YFrame = new DataFrame();
List <float> xFrameRow = new List <float>();
List <float> yFrameRow = new List <float>();
if (xCols.Length != 2)
{
throw new Exception("xCols length must be 2 with column range. Eg. [1, 10]");
}
if (xCols[0] > xCols[1])
{
throw new Exception("xCols range must have first value lower than second value.");
}
Data.ForEach((record) =>
{
xFrameRow = new List <float>();
yFrameRow = new List <float>();
for (int i = xCols[0]; i <= xCols[1]; i++)
{
xFrameRow.Add(record[i]);
}
yFrameRow.Add(record[yCol]);
result.XFrame.Add(xFrameRow);
result.YFrame.Add(yFrameRow);
});
if (result.XFrame.Columns.Count == 0)
{
for (int i = xCols[0]; i <= xCols[1]; i++)
{
result.XFrame.Columns.Add(Columns[i]);
}
}
if (result.YFrame.Columns.Count == 0)
{
result.YFrame.Columns.Add(Columns[yCol]);
}
return(result);
}
/// <summary>
/// Loads the stream.
/// </summary>
/// <param name="filepath">The stream filepath to load the dataframe from.</param>
/// <returns></returns>
public static XYFrame LoadStream(string filepath)
{
if (!File.Exists(filepath))
return null;
IFormatter formatter = new BinaryFormatter();
XYFrame frame = null;
using (Stream stream = new FileStream(filepath, FileMode.Open, FileAccess.Read, FileShare.Read))
{
using (var gZipStream = new GZipStream(stream, CompressionMode.Decompress))
{
frame = (XYFrame)formatter.Deserialize(gZipStream);
}
}
return frame;
}
/// <summary>
/// Splits the dataset to X and Y set.
/// </summary>
/// <param name="yCol">The y columns part of this split.</param>
/// <param name="xCols">The x columns part of this split.</param>
/// <returns>XY frame set.</returns>
public XYFrame SplitXY(string yCol, params string[] xCols)
{
XYFrame result = new XYFrame();
result.XFrame = new DataFrame();
result.YFrame = new DataFrame();
List <float> xFrameRow = new List <float>();
List <float> yFrameRow = new List <float>();
Data.ForEach((record) =>
{
xFrameRow.Clear();
foreach (var col in Columns)
{
if (xCols.Contains(col))
{
xFrameRow.Add(record[Columns.IndexOf(col)]);
}
}
yFrameRow.Add(record[Columns.IndexOf(yCol)]);
result.XFrame.Add(xFrameRow);
result.YFrame.Add(yFrameRow);
});
foreach (var col in Columns)
{
if (xCols.Contains(col))
{
result.XFrame.Columns.Add(col);
}
}
result.YFrame.Columns.Add(yCol);
return(result);
}
/// <summary>
/// Initializes a new instance of the <see cref="TrainTestFrame"/> class.
/// </summary>
public TrainTestFrame()
{
Train = new XYFrame();
Test = new XYFrame();
}