|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 20010-2011 Hauke Heibel <hauke.heibel@gmail.com> | 
|  | // | 
|  | // This Source Code Form is subject to the terms of the Mozilla | 
|  | // Public License v. 2.0. If a copy of the MPL was not distributed | 
|  | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
|  |  | 
|  | #ifndef EIGEN_SPLINE_FITTING_H | 
|  | #define EIGEN_SPLINE_FITTING_H | 
|  |  | 
|  | #include <algorithm> | 
|  | #include <functional> | 
|  | #include <numeric> | 
|  | #include <vector> | 
|  |  | 
|  | // IWYU pragma: private | 
|  | #include "./InternalHeaderCheck.h" | 
|  |  | 
|  | #include "SplineFwd.h" | 
|  |  | 
|  | #include "../../../../Eigen/LU" | 
|  | #include "../../../../Eigen/QR" | 
|  |  | 
|  | namespace Eigen { | 
|  | /** | 
|  | * \brief Computes knot averages. | 
|  | * \ingroup Splines_Module | 
|  | * | 
|  | * The knots are computed as | 
|  | * \f{align*} | 
|  | *  u_0 & = \hdots = u_p = 0 \\ | 
|  | *  u_{m-p} & = \hdots = u_{m} = 1 \\ | 
|  | *  u_{j+p} & = \frac{1}{p}\sum_{i=j}^{j+p-1}\bar{u}_i \quad\quad j=1,\hdots,n-p | 
|  | * \f} | 
|  | * where \f$p\f$ is the degree and \f$m+1\f$ the number knots | 
|  | * of the desired interpolating spline. | 
|  | * | 
|  | * \param[in] parameters The input parameters. During interpolation one for each data point. | 
|  | * \param[in] degree The spline degree which is used during the interpolation. | 
|  | * \param[out] knots The output knot vector. | 
|  | * | 
|  | * \sa Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data | 
|  | **/ | 
|  | template <typename KnotVectorType> | 
|  | void KnotAveraging(const KnotVectorType& parameters, DenseIndex degree, KnotVectorType& knots) { | 
|  | knots.resize(parameters.size() + degree + 1); | 
|  |  | 
|  | for (DenseIndex j = 1; j < parameters.size() - degree; ++j) knots(j + degree) = parameters.segment(j, degree).mean(); | 
|  |  | 
|  | knots.segment(0, degree + 1) = KnotVectorType::Zero(degree + 1); | 
|  | knots.segment(knots.size() - degree - 1, degree + 1) = KnotVectorType::Ones(degree + 1); | 
|  | } | 
|  |  | 
|  | /** | 
|  | * \brief Computes knot averages when derivative constraints are present. | 
|  | * Note that this is a technical interpretation of the referenced article | 
|  | * since the algorithm contained therein is incorrect as written. | 
|  | * \ingroup Splines_Module | 
|  | * | 
|  | * \param[in] parameters The parameters at which the interpolation B-Spline | 
|  | *            will intersect the given interpolation points. The parameters | 
|  | *            are assumed to be a non-decreasing sequence. | 
|  | * \param[in] degree The degree of the interpolating B-Spline. This must be | 
|  | *            greater than zero. | 
|  | * \param[in] derivativeIndices The indices corresponding to parameters at | 
|  | *            which there are derivative constraints. The indices are assumed | 
|  | *            to be a non-decreasing sequence. | 
|  | * \param[out] knots The calculated knot vector. These will be returned as a | 
|  | *             non-decreasing sequence | 
|  | * | 
|  | * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008. | 
|  | * Curve interpolation with directional constraints for engineering design. | 
|  | * Engineering with Computers | 
|  | **/ | 
|  | template <typename KnotVectorType, typename ParameterVectorType, typename IndexArray> | 
|  | void KnotAveragingWithDerivatives(const ParameterVectorType& parameters, const unsigned int degree, | 
|  | const IndexArray& derivativeIndices, KnotVectorType& knots) { | 
|  | typedef typename ParameterVectorType::Scalar Scalar; | 
|  |  | 
|  | DenseIndex numParameters = parameters.size(); | 
|  | DenseIndex numDerivatives = derivativeIndices.size(); | 
|  |  | 
|  | if (numDerivatives < 1) { | 
|  | KnotAveraging(parameters, degree, knots); | 
|  | return; | 
|  | } | 
|  |  | 
|  | DenseIndex startIndex; | 
|  | DenseIndex endIndex; | 
|  |  | 
|  | DenseIndex numInternalDerivatives = numDerivatives; | 
|  |  | 
|  | if (derivativeIndices[0] == 0) { | 
|  | startIndex = 0; | 
|  | --numInternalDerivatives; | 
|  | } else { | 
|  | startIndex = 1; | 
|  | } | 
|  | if (derivativeIndices[numDerivatives - 1] == numParameters - 1) { | 
|  | endIndex = numParameters - degree; | 
|  | --numInternalDerivatives; | 
|  | } else { | 
|  | endIndex = numParameters - degree - 1; | 
|  | } | 
|  |  | 
|  | // There are (endIndex - startIndex + 1) knots obtained from the averaging | 
|  | // and 2 for the first and last parameters. | 
|  | DenseIndex numAverageKnots = endIndex - startIndex + 3; | 
|  | KnotVectorType averageKnots(numAverageKnots); | 
|  | averageKnots[0] = parameters[0]; | 
|  |  | 
|  | int newKnotIndex = 0; | 
|  | for (DenseIndex i = startIndex; i <= endIndex; ++i) | 
|  | averageKnots[++newKnotIndex] = parameters.segment(i, degree).mean(); | 
|  | averageKnots[++newKnotIndex] = parameters[numParameters - 1]; | 
|  |  | 
|  | newKnotIndex = -1; | 
|  |  | 
|  | ParameterVectorType temporaryParameters(numParameters + 1); | 
|  | KnotVectorType derivativeKnots(numInternalDerivatives); | 
|  | for (DenseIndex i = 0; i < numAverageKnots - 1; ++i) { | 
|  | temporaryParameters[0] = averageKnots[i]; | 
|  | ParameterVectorType parameterIndices(numParameters); | 
|  | int temporaryParameterIndex = 1; | 
|  | for (DenseIndex j = 0; j < numParameters; ++j) { | 
|  | Scalar parameter = parameters[j]; | 
|  | if (parameter >= averageKnots[i] && parameter < averageKnots[i + 1]) { | 
|  | parameterIndices[temporaryParameterIndex] = j; | 
|  | temporaryParameters[temporaryParameterIndex++] = parameter; | 
|  | } | 
|  | } | 
|  | temporaryParameters[temporaryParameterIndex] = averageKnots[i + 1]; | 
|  |  | 
|  | for (int j = 0; j <= temporaryParameterIndex - 2; ++j) { | 
|  | for (DenseIndex k = 0; k < derivativeIndices.size(); ++k) { | 
|  | if (parameterIndices[j + 1] == derivativeIndices[k] && parameterIndices[j + 1] != 0 && | 
|  | parameterIndices[j + 1] != numParameters - 1) { | 
|  | derivativeKnots[++newKnotIndex] = temporaryParameters.segment(j, 3).mean(); | 
|  | break; | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | KnotVectorType temporaryKnots(averageKnots.size() + derivativeKnots.size()); | 
|  |  | 
|  | std::merge(averageKnots.data(), averageKnots.data() + averageKnots.size(), derivativeKnots.data(), | 
|  | derivativeKnots.data() + derivativeKnots.size(), temporaryKnots.data()); | 
|  |  | 
|  | // Number of knots (one for each point and derivative) plus spline order. | 
|  | DenseIndex numKnots = numParameters + numDerivatives + degree + 1; | 
|  | knots.resize(numKnots); | 
|  |  | 
|  | knots.head(degree).fill(temporaryKnots[0]); | 
|  | knots.tail(degree).fill(temporaryKnots.template tail<1>()[0]); | 
|  | knots.segment(degree, temporaryKnots.size()) = temporaryKnots; | 
|  | } | 
|  |  | 
|  | /** | 
|  | * \brief Computes chord length parameters which are required for spline interpolation. | 
|  | * \ingroup Splines_Module | 
|  | * | 
|  | * \param[in] pts The data points to which a spline should be fit. | 
|  | * \param[out] chord_lengths The resulting chord length vector. | 
|  | * | 
|  | * \sa Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data | 
|  | **/ | 
|  | template <typename PointArrayType, typename KnotVectorType> | 
|  | void ChordLengths(const PointArrayType& pts, KnotVectorType& chord_lengths) { | 
|  | typedef typename KnotVectorType::Scalar Scalar; | 
|  |  | 
|  | const DenseIndex n = pts.cols(); | 
|  |  | 
|  | // 1. compute the column-wise norms | 
|  | chord_lengths.resize(pts.cols()); | 
|  | chord_lengths[0] = 0; | 
|  | chord_lengths.rightCols(n - 1) = | 
|  | (pts.array().leftCols(n - 1) - pts.array().rightCols(n - 1)).matrix().colwise().norm(); | 
|  |  | 
|  | // 2. compute the partial sums | 
|  | std::partial_sum(chord_lengths.data(), chord_lengths.data() + n, chord_lengths.data()); | 
|  |  | 
|  | // 3. normalize the data | 
|  | chord_lengths /= chord_lengths(n - 1); | 
|  | chord_lengths(n - 1) = Scalar(1); | 
|  | } | 
|  |  | 
|  | /** | 
|  | * \brief Spline fitting methods. | 
|  | * \ingroup Splines_Module | 
|  | **/ | 
|  | template <typename SplineType> | 
|  | struct SplineFitting { | 
|  | typedef typename SplineType::KnotVectorType KnotVectorType; | 
|  | typedef typename SplineType::ParameterVectorType ParameterVectorType; | 
|  |  | 
|  | /** | 
|  | * \brief Fits an interpolating Spline to the given data points. | 
|  | * | 
|  | * \param pts The points for which an interpolating spline will be computed. | 
|  | * \param degree The degree of the interpolating spline. | 
|  | * | 
|  | * \returns A spline interpolating the initially provided points. | 
|  | **/ | 
|  | template <typename PointArrayType> | 
|  | static SplineType Interpolate(const PointArrayType& pts, DenseIndex degree); | 
|  |  | 
|  | /** | 
|  | * \brief Fits an interpolating Spline to the given data points. | 
|  | * | 
|  | * \param pts The points for which an interpolating spline will be computed. | 
|  | * \param degree The degree of the interpolating spline. | 
|  | * \param knot_parameters The knot parameters for the interpolation. | 
|  | * | 
|  | * \returns A spline interpolating the initially provided points. | 
|  | **/ | 
|  | template <typename PointArrayType> | 
|  | static SplineType Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters); | 
|  |  | 
|  | /** | 
|  | * \brief Fits an interpolating spline to the given data points and | 
|  | * derivatives. | 
|  | * | 
|  | * \param points The points for which an interpolating spline will be computed. | 
|  | * \param derivatives The desired derivatives of the interpolating spline at interpolation | 
|  | *                    points. | 
|  | * \param derivativeIndices An array indicating which point each derivative belongs to. This | 
|  | *                          must be the same size as @a derivatives. | 
|  | * \param degree The degree of the interpolating spline. | 
|  | * | 
|  | * \returns A spline interpolating @a points with @a derivatives at those points. | 
|  | * | 
|  | * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008. | 
|  | * Curve interpolation with directional constraints for engineering design. | 
|  | * Engineering with Computers | 
|  | **/ | 
|  | template <typename PointArrayType, typename IndexArray> | 
|  | static SplineType InterpolateWithDerivatives(const PointArrayType& points, const PointArrayType& derivatives, | 
|  | const IndexArray& derivativeIndices, const unsigned int degree); | 
|  |  | 
|  | /** | 
|  | * \brief Fits an interpolating spline to the given data points and derivatives. | 
|  | * | 
|  | * \param points The points for which an interpolating spline will be computed. | 
|  | * \param derivatives The desired derivatives of the interpolating spline at interpolation points. | 
|  | * \param derivativeIndices An array indicating which point each derivative belongs to. This | 
|  | *                          must be the same size as @a derivatives. | 
|  | * \param degree The degree of the interpolating spline. | 
|  | * \param parameters The parameters corresponding to the interpolation points. | 
|  | * | 
|  | * \returns A spline interpolating @a points with @a derivatives at those points. | 
|  | * | 
|  | * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008. | 
|  | * Curve interpolation with directional constraints for engineering design. | 
|  | * Engineering with Computers | 
|  | */ | 
|  | template <typename PointArrayType, typename IndexArray> | 
|  | static SplineType InterpolateWithDerivatives(const PointArrayType& points, const PointArrayType& derivatives, | 
|  | const IndexArray& derivativeIndices, const unsigned int degree, | 
|  | const ParameterVectorType& parameters); | 
|  | }; | 
|  |  | 
|  | template <typename SplineType> | 
|  | template <typename PointArrayType> | 
|  | SplineType SplineFitting<SplineType>::Interpolate(const PointArrayType& pts, DenseIndex degree, | 
|  | const KnotVectorType& knot_parameters) { | 
|  | typedef typename SplineType::KnotVectorType::Scalar Scalar; | 
|  | typedef typename SplineType::ControlPointVectorType ControlPointVectorType; | 
|  |  | 
|  | typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType; | 
|  |  | 
|  | KnotVectorType knots; | 
|  | KnotAveraging(knot_parameters, degree, knots); | 
|  |  | 
|  | DenseIndex n = pts.cols(); | 
|  | MatrixType A = MatrixType::Zero(n, n); | 
|  | for (DenseIndex i = 1; i < n - 1; ++i) { | 
|  | const DenseIndex span = SplineType::Span(knot_parameters[i], degree, knots); | 
|  |  | 
|  | // The segment call should somehow be told the spline order at compile time. | 
|  | A.row(i).segment(span - degree, degree + 1) = SplineType::BasisFunctions(knot_parameters[i], degree, knots); | 
|  | } | 
|  | A(0, 0) = 1.0; | 
|  | A(n - 1, n - 1) = 1.0; | 
|  |  | 
|  | HouseholderQR<MatrixType> qr(A); | 
|  |  | 
|  | // Here, we are creating a temporary due to an Eigen issue. | 
|  | ControlPointVectorType ctrls = qr.solve(MatrixType(pts.transpose())).transpose(); | 
|  |  | 
|  | return SplineType(knots, ctrls); | 
|  | } | 
|  |  | 
|  | template <typename SplineType> | 
|  | template <typename PointArrayType> | 
|  | SplineType SplineFitting<SplineType>::Interpolate(const PointArrayType& pts, DenseIndex degree) { | 
|  | KnotVectorType chord_lengths;  // knot parameters | 
|  | ChordLengths(pts, chord_lengths); | 
|  | return Interpolate(pts, degree, chord_lengths); | 
|  | } | 
|  |  | 
|  | template <typename SplineType> | 
|  | template <typename PointArrayType, typename IndexArray> | 
|  | SplineType SplineFitting<SplineType>::InterpolateWithDerivatives(const PointArrayType& points, | 
|  | const PointArrayType& derivatives, | 
|  | const IndexArray& derivativeIndices, | 
|  | const unsigned int degree, | 
|  | const ParameterVectorType& parameters) { | 
|  | typedef typename SplineType::KnotVectorType::Scalar Scalar; | 
|  | typedef typename SplineType::ControlPointVectorType ControlPointVectorType; | 
|  |  | 
|  | typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType; | 
|  |  | 
|  | const DenseIndex n = points.cols() + derivatives.cols(); | 
|  |  | 
|  | KnotVectorType knots; | 
|  |  | 
|  | KnotAveragingWithDerivatives(parameters, degree, derivativeIndices, knots); | 
|  |  | 
|  | // fill matrix | 
|  | MatrixType A = MatrixType::Zero(n, n); | 
|  |  | 
|  | // Use these dimensions for quicker populating, then transpose for solving. | 
|  | MatrixType b(points.rows(), n); | 
|  |  | 
|  | DenseIndex startRow; | 
|  | DenseIndex derivativeStart; | 
|  |  | 
|  | // End derivatives. | 
|  | if (derivativeIndices[0] == 0) { | 
|  | A.template block<1, 2>(1, 0) << -1, 1; | 
|  |  | 
|  | Scalar y = (knots(degree + 1) - knots(0)) / degree; | 
|  | b.col(1) = y * derivatives.col(0); | 
|  |  | 
|  | startRow = 2; | 
|  | derivativeStart = 1; | 
|  | } else { | 
|  | startRow = 1; | 
|  | derivativeStart = 0; | 
|  | } | 
|  | if (derivativeIndices[derivatives.cols() - 1] == points.cols() - 1) { | 
|  | A.template block<1, 2>(n - 2, n - 2) << -1, 1; | 
|  |  | 
|  | Scalar y = (knots(knots.size() - 1) - knots(knots.size() - (degree + 2))) / degree; | 
|  | b.col(b.cols() - 2) = y * derivatives.col(derivatives.cols() - 1); | 
|  | } | 
|  |  | 
|  | DenseIndex row = startRow; | 
|  | DenseIndex derivativeIndex = derivativeStart; | 
|  | for (DenseIndex i = 1; i < parameters.size() - 1; ++i) { | 
|  | const DenseIndex span = SplineType::Span(parameters[i], degree, knots); | 
|  |  | 
|  | if (derivativeIndex < derivativeIndices.size() && derivativeIndices[derivativeIndex] == i) { | 
|  | A.block(row, span - degree, 2, degree + 1) = | 
|  | SplineType::BasisFunctionDerivatives(parameters[i], 1, degree, knots); | 
|  |  | 
|  | b.col(row++) = points.col(i); | 
|  | b.col(row++) = derivatives.col(derivativeIndex++); | 
|  | } else { | 
|  | A.row(row).segment(span - degree, degree + 1) = SplineType::BasisFunctions(parameters[i], degree, knots); | 
|  | b.col(row++) = points.col(i); | 
|  | } | 
|  | } | 
|  | b.col(0) = points.col(0); | 
|  | b.col(b.cols() - 1) = points.col(points.cols() - 1); | 
|  | A(0, 0) = 1; | 
|  | A(n - 1, n - 1) = 1; | 
|  |  | 
|  | // Solve | 
|  | FullPivLU<MatrixType> lu(A); | 
|  | ControlPointVectorType controlPoints = lu.solve(MatrixType(b.transpose())).transpose(); | 
|  |  | 
|  | SplineType spline(knots, controlPoints); | 
|  |  | 
|  | return spline; | 
|  | } | 
|  |  | 
|  | template <typename SplineType> | 
|  | template <typename PointArrayType, typename IndexArray> | 
|  | SplineType SplineFitting<SplineType>::InterpolateWithDerivatives(const PointArrayType& points, | 
|  | const PointArrayType& derivatives, | 
|  | const IndexArray& derivativeIndices, | 
|  | const unsigned int degree) { | 
|  | ParameterVectorType parameters; | 
|  | ChordLengths(points, parameters); | 
|  | return InterpolateWithDerivatives(points, derivatives, derivativeIndices, degree, parameters); | 
|  | } | 
|  | }  // namespace Eigen | 
|  |  | 
|  | #endif  // EIGEN_SPLINE_FITTING_H |