/**
* Determine the ideal fields.
*
* @param headerList The headers.
* @return The indexes of the ideal fields.
*/
private int[] determineIdealFields(final CSVHeaders headerList) {
int[] result;
final String type = getProp().getPropertyString(ScriptProperties.ML_CONFIG_TYPE);
// is it non-supervised?
if (type.equals(MLMethodFactory.TYPE_SOM)) {
result = new int[0];
return result;
}
final List<Integer> fields = new ArrayList<Integer>();
for (int currentIndex = 0; currentIndex < headerList.size(); currentIndex++) {
final String baseName = headerList.getBaseHeader(currentIndex);
final int slice = headerList.getSlice(currentIndex);
final AnalystField field = getAnalyst().getScript().findNormalizedField(baseName, slice);
if (field != null && field.isOutput()) {
fields.add(currentIndex);
}
}
// allocate result array
result = new int[fields.size()];
for (int i = 0; i < result.length; i++) {
result[i] = fields.get(i);
}
return result;
}
/**
* Determine the input fields.
*
* @param headerList The headers.
* @return The indexes of the input fields.
*/
private int[] determineInputFields(final CSVHeaders headerList) {
final List<Integer> fields = new ArrayList<Integer>();
for (int currentIndex = 0; currentIndex < headerList.size(); currentIndex++) {
final String baseName = headerList.getBaseHeader(currentIndex);
final int slice = headerList.getSlice(currentIndex);
final AnalystField field = getAnalyst().getScript().findNormalizedField(baseName, slice);
if (field != null && field.isInput()) {
fields.add(currentIndex);
}
}
// allocate result array
final int[] result = new int[fields.size()];
for (int i = 0; i < result.length; i++) {
result[i] = fields.get(i);
}
return result;
}