// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 20010-2011 Hauke Heibel // // 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 #include #include #include #include "SplineFwd.h" #include #include 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 void KnotAveraging(const KnotVectorType& parameters, DenseIndex degree, KnotVectorType& knots) { knots.resize(parameters.size()+degree+1); for (DenseIndex j=1; j 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 lenggth vector. * * \sa Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data **/ template 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 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 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 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 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 static SplineType InterpolateWithDerivatives(const PointArrayType& points, const PointArrayType& derivatives, const IndexArray& derivativeIndices, const unsigned int degree, const ParameterVectorType& parameters); }; template template SplineType SplineFitting::Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters) { typedef typename SplineType::KnotVectorType::Scalar Scalar; typedef typename SplineType::ControlPointVectorType ControlPointVectorType; typedef Matrix MatrixType; KnotVectorType knots; KnotAveraging(knot_parameters, degree, knots); DenseIndex n = pts.cols(); MatrixType A = MatrixType::Zero(n,n); for (DenseIndex i=1; i 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 template SplineType SplineFitting::Interpolate(const PointArrayType& pts, DenseIndex degree) { KnotVectorType chord_lengths; // knot parameters ChordLengths(pts, chord_lengths); return Interpolate(pts, degree, chord_lengths); } template template SplineType SplineFitting::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 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 (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(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 lu(A); ControlPointVectorType controlPoints = lu.solve(MatrixType(b.transpose())).transpose(); SplineType spline(knots, controlPoints); return spline; } template template SplineType SplineFitting::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); } } #endif // EIGEN_SPLINE_FITTING_H