/**
* Build a simple converter for correlated residuals with the specific weights.
*
* <p>The scalar objective function value is computed as:
*
* <pre>
* objective = y<sup>T</sup>y with y = scale×(observation-objective)
* </pre>
*
* <p>The array computed by the objective function, the observations array and the the scaling
* matrix must have consistent sizes or a {@link FunctionEvaluationException} will be triggered
* while computing the scalar objective.
*
* @param function vectorial residuals function to wrap
* @param observations observations to be compared to objective function to compute residuals
* @param scale scaling matrix
* @exception IllegalArgumentException if the observations vector and the scale matrix dimensions
* don't match (objective function dimension is checked only when the {@link #value(double[])}
* method is called)
*/
public LeastSquaresConverter(
final MultivariateVectorialFunction function,
final double[] observations,
final RealMatrix scale)
throws IllegalArgumentException {
if (observations.length != scale.getColumnDimension()) {
throw MathRuntimeException.createIllegalArgumentException(
"dimension mismatch {0} != {1}", observations.length, scale.getColumnDimension());
}
this.function = function;
this.observations = observations.clone();
this.weights = null;
this.scale = scale.copy();
}
