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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.math3.fitting.leastsquares;
+
+import org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum;
+import org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation;
+import org.apache.commons.math3.linear.RealMatrix;
+import org.apache.commons.math3.linear.RealVector;
+
+/**
+ * A pedantic implementation of {@link Optimum}.
+ *
+ * @since 3.3
+ */
+class OptimumImpl implements Optimum {
+
+ /** abscissa and ordinate */
+ private final Evaluation value;
+ /** number of evaluations to compute this optimum */
+ private final int evaluations;
+ /** number of iterations to compute this optimum */
+ private final int iterations;
+
+ /**
+ * Construct an optimum from an evaluation and the values of the counters.
+ *
+ * @param value the function value
+ * @param evaluations number of times the function was evaluated
+ * @param iterations number of iterations of the algorithm
+ */
+ OptimumImpl(final Evaluation value, final int evaluations, final int iterations) {
+ this.value = value;
+ this.evaluations = evaluations;
+ this.iterations = iterations;
+ }
+
+ /* auto-generated implementations */
+
+ /** {@inheritDoc} */
+ public int getEvaluations() {
+ return evaluations;
+ }
+
+ /** {@inheritDoc} */
+ public int getIterations() {
+ return iterations;
+ }
+
+ /** {@inheritDoc} */
+ public RealMatrix getCovariances(double threshold) {
+ return value.getCovariances(threshold);
+ }
+
+ /** {@inheritDoc} */
+ public RealVector getSigma(double covarianceSingularityThreshold) {
+ return value.getSigma(covarianceSingularityThreshold);
+ }
+
+ /** {@inheritDoc} */
+ public double getRMS() {
+ return value.getRMS();
+ }
+
+ /** {@inheritDoc} */
+ public RealMatrix getJacobian() {
+ return value.getJacobian();
+ }
+
+ /** {@inheritDoc} */
+ public double getCost() {
+ return value.getCost();
+ }
+
+ /** {@inheritDoc} */
+ public RealVector getResiduals() {
+ return value.getResiduals();
+ }
+
+ /** {@inheritDoc} */
+ public RealVector getPoint() {
+ return value.getPoint();
+ }
+}