| // 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 |