/**
* Compute the raw matrix for an instance run set
*
* @param data the data the instance runs
* @return the raw matrix
*/
private final IMatrix __computeInstanceRuns(final IInstanceRuns data) {
final _List list;
final DimensionTransformation xIn, yIn;
final Transformation yOut;
final IDimension timeDim, goalDim;
xIn = this.getXAxisTransformation();
try (final TransformationFunction xInFunc = xIn.use(data)) {
yIn = this.getYAxisInputTransformation();
try (final TransformationFunction yInFunc = yIn.use(data)) {
yOut = this.getYAxisOutputTransformation();
try (final TransformationFunction yOutFunc = yOut.use(data)) {
timeDim = xIn.getDimension();
goalDim = yIn.getDimension();
if (goalDim.getDataType().isInteger() && yInFunc.isLongArithmeticAccurate()) {
if (timeDim.getDataType().isInteger()) {
list =
new _LongTimeLongGoal(
timeDim, goalDim, this.m_criterion, yInFunc, this.m_goalValueLong);
} else {
list =
new _DoubleTimeLongGoal(
timeDim, goalDim, this.m_criterion, yInFunc, this.m_goalValueLong);
}
} else {
if (timeDim.getDataType().isInteger()) {
list =
new _LongTimeDoubleGoal(
timeDim, goalDim, this.m_criterion, yInFunc, this.m_goalValueDouble);
} else {
list =
new _DoubleTimeDoubleGoal(
timeDim, goalDim, this.m_criterion, yInFunc, this.m_goalValueDouble);
}
}
for (final IRun run : data.getData()) {
list._addRun(run);
}
return list._toMatrix(xInFunc, yOutFunc);
}
}
}
}
/**
* Create the ECDF attribute
*
* @param xAxisTransformation the transformation to be applied to the {@code x}-axis
* @param yAxisInputTransformation the transformation to be applied to the data of the {@code y}
* -axis before being fed to the actual computation
* @param yAxisOutputTransformation the transformation of the result of the function applied to
* the data on the {@code y}-axis.
* @param goalValue the goal value
* @param criterion the goal comparison criterion
* @param aggregate the method to aggregate the ECDFs
*/
public ECDF(
final DimensionTransformation xAxisTransformation,
final DimensionTransformation yAxisInputTransformation,
final Transformation yAxisOutputTransformation,
final Number goalValue,
final EComparison criterion,
final StatisticalParameter aggregate) {
super(
EAttributeType.NEVER_STORED,
xAxisTransformation,
yAxisInputTransformation,
yAxisOutputTransformation);
final IDimension goalDim;
if (goalValue == null) {
throw new IllegalArgumentException( //
"Goal value of ECDF cannot be null."); //$NON-NLS-1$
}
if (criterion == null) {
throw new IllegalArgumentException( //
"Comparison criterion of ECDF cannot be null."); //$NON-NLS-1$
}
if (aggregate == null) {
throw new IllegalArgumentException( //
"Aggregate to join ECDFs of different instance sets cannot be null."); //$NON-NLS-1$
}
goalDim = yAxisInputTransformation.getDimension();
switch (goalDim.getDataType()) {
case BYTE:
case SHORT:
case INT:
case LONG:
{
if (yAxisInputTransformation.isLongArithmeticAccurate()) {
this.m_useLongGoal = true;
if ((NumericalTypes.getTypes(goalValue) & NumericalTypes.IS_LONG) != 0) {
this.m_goalValueLong = goalValue.longValue();
} else {
this.m_goalValueLong = ECDF.__doubleToLong(goalValue.doubleValue(), criterion);
}
this.m_goalValueDouble = this.m_goalValueLong;
break;
}
// fall through
}
// $FALL-THROUGH$
default:
{
this.m_goalValueDouble = goalValue.doubleValue();
this.m_useLongGoal = false;
this.m_goalValueLong = ECDF.__doubleToLong(this.m_goalValueDouble, criterion);
}
}
this.m_criterion = criterion;
this.m_aggregate = aggregate;
}
/**
* Create an instance of {@link ECDF} based on an experiment set and a configuration
*
* @param data the data (experiment set)
* @param config the configuration
* @return the instance of the aggregate
*/
public static final ECDF create(final IExperimentSet data, final Configuration config) {
DimensionTransformationParser dimParser;
final DimensionTransformation xIn, yIn;
final Transformation yOut;
final StatisticalParameter aggregate;
final IDimension goalDim;
EComparison compare;
Number goal;
dimParser = new DimensionTransformationParser(data);
xIn =
config.get( //
FunctionAttribute.X_AXIS_PARAM, dimParser, null);
if (xIn == null) { //
throw new IllegalArgumentException(
"Must specify an x-dimension via parameter '" //$NON-NLS-1$
+ FunctionAttribute.X_AXIS_PARAM
+ '\'');
}
yIn = config.get(FunctionAttribute.Y_INPUT_AXIS_PARAM, dimParser, null);
if (yIn == null) { //
throw new IllegalArgumentException(
"Must specify an input dimension for the y-axis via parameter '" //$NON-NLS-1$
+ FunctionAttribute.Y_INPUT_AXIS_PARAM
+ '\'');
}
dimParser = null;
yOut =
config.get(
FunctionAttribute.Y_AXIS_OUTPUT_PARAM,
new NamedParameterTransformationParser(data),
new Transformation());
aggregate =
config.get(
ECDF.AGGREGATE_PARAM,
StatisticalParameterParser.getInstance(),
ArithmeticMean.INSTANCE);
goalDim = yIn.getDimension();
if (goalDim.getDirection().isIncreasing()) {
compare = EComparison.GREATER_OR_EQUAL;
if (goalDim.getDataType().isInteger()) {
goal = Long.valueOf(goalDim.getParser().getUpperBoundLong());
} else {
goal = Double.valueOf(goalDim.getParser().getUpperBoundDouble());
}
} else {
compare = EComparison.LESS_OR_EQUAL;
if (goalDim.getDataType().isInteger()) {
goal = Long.valueOf(goalDim.getParser().getLowerBoundLong());
} else {
goal = Double.valueOf(goalDim.getParser().getLowerBoundDouble());
}
}
goal = config.get(ECDF.GOAL_PARAM, AnyNumberParser.INSTANCE, goal);
compare = config.get(ECDF.CRITERION_PARAM, ComparisonParser.getInstance(), compare);
return new ECDF(xIn, yIn, yOut, goal, compare, aggregate);
}