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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.analysis.differentiation;
+
+import org.apache.commons.math3.analysis.MultivariateMatrixFunction;
+
+/** Class representing the Jacobian of a multivariate vector function.
+ * <p>
+ * The rows iterate on the model functions while the columns iterate on the parameters; thus,
+ * the numbers of rows is equal to the dimension of the underlying function vector
+ * value and the number of columns is equal to the number of free parameters of
+ * the underlying function.
+ * </p>
+ * @since 3.1
+ */
+public class JacobianFunction implements MultivariateMatrixFunction {
+
+    /** Underlying vector-valued function. */
+    private final MultivariateDifferentiableVectorFunction f;
+
+    /** Simple constructor.
+     * @param f underlying vector-valued function
+     */
+    public JacobianFunction(final MultivariateDifferentiableVectorFunction f) {
+        this.f = f;
+    }
+
+    /** {@inheritDoc} */
+    public double[][] value(double[] point) {
+
+        // set up parameters
+        final DerivativeStructure[] dsX = new DerivativeStructure[point.length];
+        for (int i = 0; i < point.length; ++i) {
+            dsX[i] = new DerivativeStructure(point.length, 1, i, point[i]);
+        }
+
+        // compute the derivatives
+        final DerivativeStructure[] dsY = f.value(dsX);
+
+        // extract the Jacobian
+        final double[][] y = new double[dsY.length][point.length];
+        final int[] orders = new int[point.length];
+        for (int i = 0; i < dsY.length; ++i) {
+            for (int j = 0; j < point.length; ++j) {
+                orders[j] = 1;
+                y[i][j] = dsY[i].getPartialDerivative(orders);
+                orders[j] = 0;
+            }
+        }
+
+        return y;
+
+    }
+
+}