// --------------------------------------------------------------------------- // This file is part of reSID, a MOS6581 SID emulator engine. // Copyright (C) 2002 Dag Lem // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // --------------------------------------------------------------------------- #ifndef __SPLINE_H__ #define __SPLINE_H__ RESID_NAMESPACE_START // Our objective is to construct a smooth interpolating single-valued function // y = f(x). // // Catmull-Rom splines are widely used for interpolation, however these are // parametric curves [x(t) y(t) ...] and can not be used to directly calculate // y = f(x). // For a discussion of Catmull-Rom splines see Catmull, E., and R. Rom, // "A Class of Local Interpolating Splines", Computer Aided Geometric Design. // // Natural cubic splines are single-valued functions, and have been used in // several applications e.g. to specify gamma curves for image display. // These splines do not afford local control, and a set of linear equations // including all interpolation points must be solved before any point on the // curve can be calculated. The lack of local control makes the splines // more difficult to handle than e.g. Catmull-Rom splines, and real-time // interpolation of a stream of data points is not possible. // For a discussion of natural cubic splines, see e.g. Kreyszig, E., "Advanced // Engineering Mathematics". // // Our approach is to approximate the properties of Catmull-Rom splines for // piecewice cubic polynomials f(x) = ax^3 + bx^2 + cx + d as follows: // Each curve segment is specified by four interpolation points, // p0, p1, p2, p3. // The curve between p1 and p2 must interpolate both p1 and p2, and in addition // f'(p1.x) = k1 = (p2.y - p0.y)/(p2.x - p0.x) and // f'(p2.x) = k2 = (p3.y - p1.y)/(p3.x - p1.x). // // The constraints are expressed by the following system of linear equations // // [ 1 xi xi^2 xi^3 ] [ d ] [ yi ] // [ 1 2*xi 3*xi^2 ] * [ c ] = [ ki ] // [ 1 xj xj^2 xj^3 ] [ b ] [ yj ] // [ 1 2*xj 3*xj^2 ] [ a ] [ kj ] // // Solving using Gaussian elimination and back substitution, setting // dy = yj - yi, dx = xj - xi, we get // // a = ((ki + kj) - 2*dy/dx)/(dx*dx); // b = ((kj - ki)/dx - 3*(xi + xj)*a)/2; // c = ki - (3*xi*a + 2*b)*xi; // d = yi - ((xi*a + b)*xi + c)*xi; // // Having calculated the coefficients of the cubic polynomial we have the // choice of evaluation by brute force // // for (x = x1; x <= x2; x += res) { // y = ((a*x + b)*x + c)*x + d; // plot(x, y); // } // // or by forward differencing // // y = ((a*x1 + b)*x1 + c)*x1 + d; // dy = (3*a*(x1 + res) + 2*b)*x1*res + ((a*res + b)*res + c)*res; // d2y = (6*a*(x1 + res) + 2*b)*res*res; // d3y = 6*a*res*res*res; // // for (x = x1; x <= x2; x += res) { // plot(x, y); // y += dy; dy += d2y; d2y += d3y; // } // // See Foley, Van Dam, Feiner, Hughes, "Computer Graphics, Principles and // Practice" for a discussion of forward differencing. // // If we have a set of interpolation points p0, ..., pn, we may specify // curve segments between p0 and p1, and between pn-1 and pn by using the // following constraints: // f''(p0.x) = 0 and // f''(pn.x) = 0. // // Substituting the results for a and b in // // 2*b + 6*a*xi = 0 // // we get // // ki = (3*dy/dx - kj)/2; // // or by substituting the results for a and b in // // 2*b + 6*a*xj = 0 // // we get // // kj = (3*dy/dx - ki)/2; // // Finally, if we have only two interpolation points, the cubic polynomial // will degenerate to a straight line if we set // // ki = kj = dy/dx; // #if SPLINE_BRUTE_FORCE #define interpolate_segment interpolate_brute_force #else #define interpolate_segment interpolate_forward_difference #endif // ---------------------------------------------------------------------------- // Calculation of coefficients. // ---------------------------------------------------------------------------- inline void cubic_coefficients(double x1, double y1, double x2, double y2, double k1, double k2, double& a, double& b, double& c, double& d) { double dx = x2 - x1, dy = y2 - y1; a = ((k1 + k2) - 2*dy/dx)/(dx*dx); b = ((k2 - k1)/dx - 3*(x1 + x2)*a)/2; c = k1 - (3*x1*a + 2*b)*x1; d = y1 - ((x1*a + b)*x1 + c)*x1; } // ---------------------------------------------------------------------------- // Evaluation of cubic polynomial by brute force. // ---------------------------------------------------------------------------- template inline void interpolate_brute_force(double x1, double y1, double x2, double y2, double k1, double k2, PointPlotter plot, double res) { double a, b, c, d; cubic_coefficients(x1, y1, x2, y2, k1, k2, a, b, c, d); // Calculate each point. for (double x = x1; x <= x2; x += res) { double y = ((a*x + b)*x + c)*x + d; plot(x, y); } } // ---------------------------------------------------------------------------- // Evaluation of cubic polynomial by forward differencing. // ---------------------------------------------------------------------------- template inline void interpolate_forward_difference(double x1, double y1, double x2, double y2, double k1, double k2, PointPlotter plot, double res) { double a, b, c, d; cubic_coefficients(x1, y1, x2, y2, k1, k2, a, b, c, d); double y = ((a*x1 + b)*x1 + c)*x1 + d; double dy = (3*a*(x1 + res) + 2*b)*x1*res + ((a*res + b)*res + c)*res; double d2y = (6*a*(x1 + res) + 2*b)*res*res; double d3y = 6*a*res*res*res; // Calculate each point. for (double x = x1; x <= x2; x += res) { plot(x, y); y += dy; dy += d2y; d2y += d3y; } } template inline double x(PointIter p) { return (*p)[0]; } template inline double y(PointIter p) { return (*p)[1]; } // ---------------------------------------------------------------------------- // Evaluation of complete interpolating function. // Note that since each curve segment is controlled by four points, the // end points will not be interpolated. If extra control points are not // desirable, the end points can simply be repeated to ensure interpolation. // Note also that points of non-differentiability and discontinuity can be // introduced by repeating points. // ---------------------------------------------------------------------------- template inline void interpolate(PointIter p0, PointIter pn, PointPlotter plot, double res) { double k1, k2; // Set up points for first curve segment. PointIter p1 = p0; ++p1; PointIter p2 = p1; ++p2; PointIter p3 = p2; ++p3; // Draw each curve segment. for (; p2 != pn; ++p0, ++p1, ++p2, ++p3) { // p1 and p2 equal; single point. if (x(p1) == x(p2)) { continue; } // Both end points repeated; straight line. if (x(p0) == x(p1) && x(p2) == x(p3)) { k1 = k2 = (y(p2) - y(p1))/(x(p2) - x(p1)); } // p0 and p1 equal; use f''(x1) = 0. else if (x(p0) == x(p1)) { k2 = (y(p3) - y(p1))/(x(p3) - x(p1)); k1 = (3*(y(p2) - y(p1))/(x(p2) - x(p1)) - k2)/2; } // p2 and p3 equal; use f''(x2) = 0. else if (x(p2) == x(p3)) { k1 = (y(p2) - y(p0))/(x(p2) - x(p0)); k2 = (3*(y(p2) - y(p1))/(x(p2) - x(p1)) - k1)/2; } // Normal curve. else { k1 = (y(p2) - y(p0))/(x(p2) - x(p0)); k2 = (y(p3) - y(p1))/(x(p3) - x(p1)); } interpolate_segment(x(p1), y(p1), x(p2), y(p2), k1, k2, plot, res); } } // ---------------------------------------------------------------------------- // Class for plotting integers into an array. // ---------------------------------------------------------------------------- template class PointPlotter { protected: F* f; public: PointPlotter(F* arr) : f(arr) { } void operator ()(double x, double y) { f[F(x)] = F(y); } }; RESID_NAMESPACE_STOP #endif // not __SPLINE_H__