LocalDBPredictionTable(DBExampleTable pet, DBDataSource dataSource, DBConnection conn) {
super(pet, dataSource, conn);
original = pet;
newTableHackVariable = false;
// subset = pet.subset;
num_original_columns = original.getNumColumns();
predictionSet = new int[outputColumns.length];
for (int j = 0; j < predictionSet.length; j++) predictionSet[j] = j + original.getNumColumns();
// handle indirection and prediction
indirection = new int[original.getNumColumns() + predictionSet.length];
prediction = new boolean[indirection.length];
for (int j = 0; j < original.getNumColumns(); j++) {
// indirection[j] = j;
prediction[j] = false;
}
for (int j = 0; j < predictionSet.length; j++) {
indirection[original.getNumColumns() + j] = j;
prediction[original.getNumColumns() + j] = true;
}
predictionColumns = new Column[outputColumns.length];
// this will make sure that the prediction columns are as long
// as the redular columns and subsetted.
int numRows = dataSource.getNumRows();
for (int i = 0; i < outputColumns.length; i++) {
int type = original.getColumnType(outputColumns[i]);
switch (type) {
case ColumnTypes.BOOLEAN:
predictionColumns[i] = new BooleanColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.BYTE:
predictionColumns[i] = new ByteColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.BYTE_ARRAY:
predictionColumns[i] = new ContinuousByteArrayColumn(numRows, true);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.CHAR:
predictionColumns[i] = new CharColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.CHAR_ARRAY:
predictionColumns[i] = new ContinuousCharArrayColumn(numRows, true);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.DOUBLE:
predictionColumns[i] = new DoubleColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.FLOAT:
predictionColumns[i] = new FloatColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.INTEGER:
predictionColumns[i] = new IntColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.LONG:
predictionColumns[i] = new LongColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.OBJECT:
predictionColumns[i] = new ObjectColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.SHORT:
predictionColumns[i] = new ShortColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
case ColumnTypes.STRING:
predictionColumns[i] = new StringColumn(numRows);
predictionColumns[i].setLabel(original.getColumnLabel(outputColumns[i]) + " Predictions");
break;
default:
break;
}
predictionColumnsTable = new SubsetTableImpl(predictionColumns, subset);
// (MutableTableImpl)DefaultTableFactory.getInstance().createTable(c);
}
}
public int getColumnType(int position) {
if (prediction[position]) return predictionColumnsTable.getColumnType(indirection[position]);
else return original.getColumnType(position);
}
