/// <summary>
/// Determine the input fields.
/// </summary>
///
/// <param name="headerList">The headers.</param>
/// <returns>The indexes of the input fields.</returns>
private int[] DetermineInputFields(CSVHeaders headerList)
{
IList <Int32> fields = new List <Int32>();
for (int currentIndex = 0; currentIndex < headerList.Size(); currentIndex++)
{
String baseName = headerList.GetBaseHeader(currentIndex);
int slice = headerList.GetSlice(currentIndex);
AnalystField field = Analyst.Script
.FindNormalizedField(baseName, slice);
if (field != null && field.Input)
{
fields.Add(currentIndex);
}
}
// allocate result array
var result = new int[fields.Count];
for (int i = 0; i < result.Length; i++)
{
result[i] = (fields[i]);
}
return(result);
}
/// <summary>
/// Determine the ideal fields.
/// </summary>
///
/// <param name="headerList">The headers.</param>
/// <returns>The indexes of the ideal fields.</returns>
private int[] DetermineIdealFields(CSVHeaders headerList)
{
int[] result;
String type = Prop.GetPropertyString(
ScriptProperties.MlConfigType);
// is it non-supervised?
if (type.Equals(MLMethodFactory.TypeSOM))
{
result = new int[0];
return(result);
}
IList <Int32> fields = new List <Int32>();
for (int currentIndex = 0; currentIndex < headerList.Size(); currentIndex++)
{
String baseName = headerList.GetBaseHeader(currentIndex);
int slice = headerList.GetSlice(currentIndex);
AnalystField field = Analyst.Script
.FindNormalizedField(baseName, slice);
if (field != null && field.Output)
{
fields.Add(currentIndex);
}
}
// allocate result array
result = new int[fields.Count];
for (int i = 0; i < result.Length; i++)
{
result[i] = (fields[i]);
}
return(result);
}