1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 20010-2011 Hauke Heibel <hauke.heibel@gmail.com>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_SPLINE_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_SPLINE_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "SplineFwd.h"
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \ingroup Splines_Module
197faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez     * \class Spline
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief A class representing multi-dimensional spline curves.
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * The class represents B-splines with non-uniform knot vectors. Each control
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * point of the B-spline is associated with a basis function
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   C(u) & = \sum_{i=0}^{n}N_{i,p}(u)P_i
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \tparam _Scalar The underlying data type (typically float or double)
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \tparam _Dim The curve dimension (e.g. 2 or 3)
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \tparam _Degree Per default set to Dynamic; could be set to the actual desired
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *                degree for optimization purposes (would result in stack allocation
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *                of several temporary variables).
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  class Spline
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef _Scalar Scalar; /*!< The spline curve's scalar type. */
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Dimension = _Dim /*!< The spline curve's dimension. */ };
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Degree = _Degree /*!< The spline curve's degree. */ };
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \brief The point type the spline is representing. */
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<Spline>::PointType PointType;
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \brief The data type used to store knot vectors. */
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<Spline>::KnotVectorType KnotVectorType;
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \brief The data type used to store non-zero basis functions. */
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<Spline>::BasisVectorType BasisVectorType;
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** \brief The data type representing the spline's control points. */
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<Spline>::ControlPointVectorType ControlPointVectorType;
537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
547faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    /**
557faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    * \brief Creates a (constant) zero spline.
567faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    * For Splines with dynamic degree, the resulting degree will be 0.
577faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    **/
587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    Spline()
597faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    : m_knots(1, (Degree==Dynamic ? 2 : 2*Degree+2))
607faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    , m_ctrls(ControlPointVectorType::Zero(2,(Degree==Dynamic ? 1 : Degree+1)))
617faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    {
627faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      // in theory this code can go to the initializer list but it will get pretty
637faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      // much unreadable ...
647faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      enum { MinDegree = (Degree==Dynamic ? 0 : Degree) };
657faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_knots.template segment<MinDegree+1>(0) = Array<Scalar,1,MinDegree+1>::Zero();
667faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez      m_knots.template segment<MinDegree+1>(MinDegree+1) = Array<Scalar,1,MinDegree+1>::Ones();
677faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    }
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    * \brief Creates a spline from a knot vector and control points.
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    * \param knots The spline's knot vector.
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    * \param ctrls The spline's control point vector.
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    **/
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template <typename OtherVectorType, typename OtherArrayType>
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline(const OtherVectorType& knots, const OtherArrayType& ctrls) : m_knots(knots), m_ctrls(ctrls) {}
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    * \brief Copy constructor for splines.
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    * \param spline The input spline.
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    **/
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template <int OtherDegree>
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline(const Spline<Scalar, Dimension, OtherDegree>& spline) :
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_knots(spline.knots()), m_ctrls(spline.ctrls()) {}
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the knots of the underlying spline.
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const KnotVectorType& knots() const { return m_knots; }
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the knots of the underlying spline.
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const ControlPointVectorType& ctrls() const { return m_ctrls; }
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the spline value at a given site \f$u\f$.
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * The function returns
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   C(u) & = \sum_{i=0}^{n}N_{i,p}P_i
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u Parameter \f$u \in [0;1]\f$ at which the spline is evaluated.
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \return The spline value at the given location \f$u\f$.
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PointType operator()(Scalar u) const;
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Evaluation of spline derivatives of up-to given order.
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * The function returns
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   \frac{d^i}{du^i}C(u) & = \sum_{i=0}^{n} \frac{d^i}{du^i} N_{i,p}(u)P_i
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * for i ranging between 0 and order.
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u Parameter \f$u \in [0;1]\f$ at which the spline derivative is evaluated.
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param order The order up to which the derivatives are computed.
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits<Spline>::DerivativeType
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      derivatives(Scalar u, DenseIndex order) const;
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \copydoc Spline::derivatives
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * Using the template version of this function is more efficieent since
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * temporary objects are allocated on the stack whenever this is possible.
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template <int DerivativeOrder>
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits<Spline,DerivativeOrder>::DerivativeType
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      derivatives(Scalar u, DenseIndex order = DerivativeOrder) const;
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Computes the non-zero basis functions at the given site.
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * Splines have local support and a point from their image is defined
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * by exactly \f$p+1\f$ control points \f$P_i\f$ where \f$p\f$ is the
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * spline degree.
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * This function computes the \f$p+1\f$ non-zero basis function values
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * for a given parameter value \f$u\f$. It returns
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}{
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   N_{i,p}(u), \hdots, N_{i+p+1,p}(u)
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u Parameter \f$u \in [0;1]\f$ at which the non-zero basis functions
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *          are computed.
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits<Spline>::BasisVectorType
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      basisFunctions(Scalar u) const;
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Computes the non-zero spline basis function derivatives up to given order.
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * The function computes
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}{
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   \frac{d^i}{du^i} N_{i,p}(u), \hdots, \frac{d^i}{du^i} N_{i+p+1,p}(u)
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * with i ranging from 0 up to the specified order.
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u Parameter \f$u \in [0;1]\f$ at which the non-zero basis function
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *          derivatives are computed.
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param order The order up to which the basis function derivatives are computes.
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits<Spline>::BasisDerivativeType
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      basisFunctionDerivatives(Scalar u, DenseIndex order) const;
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \copydoc Spline::basisFunctionDerivatives
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * Using the template version of this function is more efficieent since
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * temporary objects are allocated on the stack whenever this is possible.
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template <int DerivativeOrder>
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits<Spline,DerivativeOrder>::BasisDerivativeType
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      basisFunctionDerivatives(Scalar u, DenseIndex order = DerivativeOrder) const;
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the spline degree.
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex degree() const;
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the span within the knot vector in which u is falling.
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u The site for which the span is determined.
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex span(Scalar u) const;
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Computes the spang within the provided knot vector in which u is falling.
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    static DenseIndex Span(typename SplineTraits<Spline>::Scalar u, DenseIndex degree, const typename SplineTraits<Spline>::KnotVectorType& knots);
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /**
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \brief Returns the spline's non-zero basis functions.
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * The function computes and returns
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f{align*}{
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *   N_{i,p}(u), \hdots, N_{i+p+1,p}(u)
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \f}
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     *
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param u The site at which the basis functions are computed.
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param degree The degree of the underlying spline.
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     * \param knots The underlying spline's knot vector.
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     **/
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    static BasisVectorType BasisFunctions(Scalar u, DenseIndex degree, const KnotVectorType& knots);
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  private:
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    KnotVectorType m_knots; /*!< Knot vector. */
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ControlPointVectorType  m_ctrls; /*!< Control points. */
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  DenseIndex Spline<_Scalar, _Dim, _Degree>::Span(
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::Scalar u,
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex degree,
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::KnotVectorType& knots)
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // Piegl & Tiller, "The NURBS Book", A2.1 (p. 68)
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if (u <= knots(0)) return degree;
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const Scalar* pos = std::upper_bound(knots.data()+degree-1, knots.data()+knots.size()-degree-1, u);
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return static_cast<DenseIndex>( std::distance(knots.data(), pos) - 1 );
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename Spline<_Scalar, _Dim, _Degree>::BasisVectorType
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::BasisFunctions(
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename Spline<_Scalar, _Dim, _Degree>::Scalar u,
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex degree,
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const typename Spline<_Scalar, _Dim, _Degree>::KnotVectorType& knots)
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Spline<_Scalar, _Dim, _Degree>::BasisVectorType BasisVectorType;
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex p = degree;
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex i = Spline::Span(u, degree, knots);
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const KnotVectorType& U = knots;
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    BasisVectorType left(p+1); left(0) = Scalar(0);
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    BasisVectorType right(p+1); right(0) = Scalar(0);
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VectorBlock<BasisVectorType,Degree>(left,1,p) = u - VectorBlock<const KnotVectorType,Degree>(U,i+1-p,p).reverse();
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VectorBlock<BasisVectorType,Degree>(right,1,p) = VectorBlock<const KnotVectorType,Degree>(U,i+1,p) - u;
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    BasisVectorType N(1,p+1);
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    N(0) = Scalar(1);
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (DenseIndex j=1; j<=p; ++j)
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar saved = Scalar(0);
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (DenseIndex r=0; r<j; r++)
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const Scalar tmp = N(r)/(right(r+1)+left(j-r));
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        N[r] = saved + right(r+1)*tmp;
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        saved = left(j-r)*tmp;
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      N(j) = saved;
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return N;
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  DenseIndex Spline<_Scalar, _Dim, _Degree>::degree() const
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if (_Degree == Dynamic)
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return m_knots.size() - m_ctrls.cols() - 1;
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return _Degree;
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  DenseIndex Spline<_Scalar, _Dim, _Degree>::span(Scalar u) const
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return Spline::Span(u, degree(), knots());
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename Spline<_Scalar, _Dim, _Degree>::PointType Spline<_Scalar, _Dim, _Degree>::operator()(Scalar u) const
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Order = SplineTraits<Spline>::OrderAtCompileTime };
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex span = this->span(u);
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex p = degree();
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const BasisVectorType basis_funcs = basisFunctions(u);
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const Replicate<BasisVectorType,Dimension,1> ctrl_weights(basis_funcs);
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const Block<const ControlPointVectorType,Dimension,Order> ctrl_pts(ctrls(),0,span-p,Dimension,p+1);
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return (ctrl_weights * ctrl_pts).rowwise().sum();
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  /* --------------------------------------------------------------------------------------------- */
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename SplineType, typename DerivativeType>
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  void derivativesImpl(const SplineType& spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType& der)
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Dimension = SplineTraits<SplineType>::Dimension };
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Order = SplineTraits<SplineType>::OrderAtCompileTime };
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { DerivativeOrder = DerivativeType::ColsAtCompileTime };
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<SplineType>::ControlPointVectorType ControlPointVectorType;
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<SplineType,DerivativeOrder>::BasisDerivativeType BasisDerivativeType;
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename BasisDerivativeType::ConstRowXpr BasisDerivativeRowXpr;
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex p = spline.degree();
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex span = spline.span(u);
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex n = (std::min)(p, order);
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    der.resize(Dimension,n+1);
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // Retrieve the basis function derivatives up to the desired order...
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const BasisDerivativeType basis_func_ders = spline.template basisFunctionDerivatives<DerivativeOrder>(u, n+1);
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // ... and perform the linear combinations of the control points.
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (DenseIndex der_order=0; der_order<n+1; ++der_order)
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      const Replicate<BasisDerivativeRowXpr,Dimension,1> ctrl_weights( basis_func_ders.row(der_order) );
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      const Block<const ControlPointVectorType,Dimension,Order> ctrl_pts(spline.ctrls(),0,span-p,Dimension,p+1);
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      der.col(der_order) = (ctrl_weights * ctrl_pts).rowwise().sum();
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::DerivativeType
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::derivatives(Scalar u, DenseIndex order) const
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits< Spline >::DerivativeType res;
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    derivativesImpl(*this, u, order, res);
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return res;
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <int DerivativeOrder>
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::DerivativeType
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::derivatives(Scalar u, DenseIndex order) const
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits< Spline, DerivativeOrder >::DerivativeType res;
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    derivativesImpl(*this, u, order, res);
337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return res;
338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::BasisVectorType
342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::basisFunctions(Scalar u) const
343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return Spline::BasisFunctions(u, degree(), knots());
345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  /* --------------------------------------------------------------------------------------------- */
348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename SplineType, typename DerivativeType>
350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  void basisFunctionDerivativesImpl(const SplineType& spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType& N_)
351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Order = SplineTraits<SplineType>::OrderAtCompileTime };
353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<SplineType>::Scalar Scalar;
355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<SplineType>::BasisVectorType BasisVectorType;
356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename SplineTraits<SplineType>::KnotVectorType KnotVectorType;
357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const KnotVectorType& U = spline.knots();
359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex p = spline.degree();
361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex span = spline.span(u);
362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const DenseIndex n = (std::min)(p, order);
364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    N_.resize(n+1, p+1);
366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    BasisVectorType left = BasisVectorType::Zero(p+1);
368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    BasisVectorType right = BasisVectorType::Zero(p+1);
369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
370c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Matrix<Scalar,Order,Order> ndu(p+1,p+1);
371c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    double saved, temp;
373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ndu(0,0) = 1.0;
375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex j;
377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (j=1; j<=p; ++j)
378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      left[j] = u-U[span+1-j];
380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      right[j] = U[span+j]-u;
381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      saved = 0.0;
382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (DenseIndex r=0; r<j; ++r)
384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /* Lower triangle */
386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ndu(j,r) = right[r+1]+left[j-r];
387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        temp = ndu(r,j-1)/ndu(j,r);
388c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        /* Upper triangle */
389c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ndu(r,j) = static_cast<Scalar>(saved+right[r+1] * temp);
390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        saved = left[j-r] * temp;
391c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
393c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ndu(j,j) = static_cast<Scalar>(saved);
394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (j = p; j>=0; --j)
397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      N_(0,j) = ndu(j,p);
398c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
399c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // Compute the derivatives
400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DerivativeType a(n+1,p+1);
401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex r=0;
402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (; r<=p; ++r)
403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      DenseIndex s1,s2;
405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      s1 = 0; s2 = 1; // alternate rows in array a
406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a(0,0) = 1.0;
407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // Compute the k-th derivative
409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (DenseIndex k=1; k<=static_cast<DenseIndex>(n); ++k)
410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        double d = 0.0;
412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        DenseIndex rk,pk,j1,j2;
413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        rk = r-k; pk = p-k;
414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (r>=k)
416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          a(s2,0) = a(s1,0)/ndu(pk+1,rk);
418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          d = a(s2,0)*ndu(rk,pk);
419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
420c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
421c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (rk>=-1) j1 = 1;
422c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else        j1 = -rk;
423c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
424c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (r-1 <= pk) j2 = k-1;
425c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else           j2 = p-r;
426c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
427c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        for (j=j1; j<=j2; ++j)
428c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
429c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          a(s2,j) = (a(s1,j)-a(s1,j-1))/ndu(pk+1,rk+j);
430c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          d += a(s2,j)*ndu(rk+j,pk);
431c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
432c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
433c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if (r<=pk)
434c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        {
435c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          a(s2,k) = -a(s1,k-1)/ndu(pk+1,r);
436c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          d += a(s2,k)*ndu(r,pk);
437c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        }
438c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
439c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        N_(k,r) = static_cast<Scalar>(d);
440c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        j = s1; s1 = s2; s2 = j; // Switch rows
441c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
442c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
443c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
444c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /* Multiply through by the correct factors */
445c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /* (Eq. [2.9])                             */
446c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    r = p;
447c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (DenseIndex k=1; k<=static_cast<DenseIndex>(n); ++k)
448c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
449c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (DenseIndex j=p; j>=0; --j) N_(k,j) *= r;
450c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      r *= p-k;
451c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
452c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
453c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
454c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
455c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::BasisDerivativeType
456c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const
457c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
458c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits< Spline >::BasisDerivativeType der;
459c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    basisFunctionDerivativesImpl(*this, u, order, der);
460c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return der;
461c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
462c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
463c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <typename _Scalar, int _Dim, int _Degree>
464c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template <int DerivativeOrder>
465c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::BasisDerivativeType
466c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const
467c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
468c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename SplineTraits< Spline, DerivativeOrder >::BasisDerivativeType der;
469c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    basisFunctionDerivativesImpl(*this, u, order, der);
470c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return der;
471c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
472c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
473c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
474c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_SPLINE_H
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