public static List <NetIO> SplitDataInOut(ref List <List <double> > CsvData, int lengthOfOutput)
{
List <NetIO> FormattedData = new List <NetIO>();
uint i = 0;
foreach (List <double> row in CsvData)
{
NetIO FormattedRow = new NetIO(i++);
FormattedRow.Input = row.GetRange(0, row.Count() - lengthOfOutput);
FormattedRow.Output = row.GetRange(row.Count() - lengthOfOutput, lengthOfOutput);
FormattedData.Add(FormattedRow);
}
return(FormattedData);
}
public bool LoadRobotData(string filepath, out List <NetIO> data)
{
List <NetIO> outData = new List <NetIO>();
NetIO predictorsAndLabel = new NetIO();
// create dictionary of labels and index
Dictionary <string, int> labels = new Dictionary <string, int>();
string currentLabel = null;
int j = 1;
// open csv and read lines
var lines = File.ReadAllLines(filepath);
foreach (string line in lines)
{
// split at tab
string[] words = line.Split('\t');
if (words.Length == 1 && words[0] != "")
{
// header - label
try
{
currentLabel = words[0];
labels.Add(currentLabel, j++);
}
catch (ArgumentException)
{
// label already exists in dictionary
}
}
else if (words.Length > 1)
{
// add values to row vector
for (int i = 1; i < words.Length; ++i)
{
predictorsAndLabel.Input.Add(Convert.ToDouble(words[i]));
}
}
else if (words.Length == 1 && words[0] == "")
{
// end of instance
// add row vector to results
if (predictorsAndLabel.Input.Count > 0)
{
predictorsAndLabel.Output.Add(labels[currentLabel]);
outData.Add(predictorsAndLabel);
predictorsAndLabel = new NetIO();
}
}
}
// add final row vector to results
predictorsAndLabel.Output.Add(labels[currentLabel]);
outData.Add(predictorsAndLabel);
predictorsAndLabel = new NetIO();
// convert dictionary values, 1,2,3 to 100, 010, 001 in NetIO
foreach (NetIO set in outData)
{
List <double> labelArray = new List <double>();
for (int i = 0; i < labels.Count; ++i)
{
labelArray.Add(0.0);
}
labelArray[Convert.ToInt32(set.Output[0]) - 1] = 1.0;
set.Output = labelArray;
}
this.lengthOfOutputData = labels.Count;
data = outData;
return(true);
}