LeastSquaresOptimizer.JacobianFunction Property

public Func<Vector<double>, Matrix<double>?, Matrix<double>> JacobianFunction { get; set; }

Public Property JacobianFunction As Func(Of Vector(Of Double), Matrix(Of Double), Matrix(Of Double))
	Get
	Set

public:
property Func<Vector<double>^, Matrix<double>^, Matrix<double>^>^ JacobianFunction {
	Func<Vector<double>^, Matrix<double>^, Matrix<double>^>^ get ();
	void set (Func<Vector<double>^, Matrix<double>^, Matrix<double>^>^ value);
}

member JacobianFunction : Func<Vector<float>, Matrix<float>, Matrix<float>> with get, set

Property Value

The Jacobian contains the derivative of each residual with respect to each variable. A residual is one of the values returned by ObjectiveFunction. The returned matrix must have one row per residual and one column per variable. The callback may update the supplied buffer or return another matrix. The callback must return a non-null matrix and overwrite entries that change, including derivatives that become zero. Its dimensions must remain fixed during a solve. Both standard least-squares optimizers support sparse Jacobians; UseSparseJacobian avoids its initial dense buffer.

Reference