/* * 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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. * * The Original Code is Copyright (C) 2015 by Blender Foundation. * All rights reserved. * */ /** \file * \ingroup bli */ #include "MEM_guardedalloc.h" #include "BLI_math.h" #include "BLI_utildefines.h" #include "BLI_strict_flags.h" #include "eigen_capi.h" /********************************** Eigen Solvers *********************************/ /** * \brief Compute the eigen values and/or vectors of given 3D symmetric (aka adjoint) matrix. * * \param m3: the 3D symmetric matrix. * \return r_eigen_values the computed eigen values (NULL if not needed). * \return r_eigen_vectors the computed eigen vectors (NULL if not needed). */ bool BLI_eigen_solve_selfadjoint_m3(const float m3[3][3], float r_eigen_values[3], float r_eigen_vectors[3][3]) { #ifndef NDEBUG /* We must assert given matrix is self-adjoint (i.e. symmetric) */ if ((m3[0][1] != m3[1][0]) || (m3[0][2] != m3[2][0]) || (m3[1][2] != m3[2][1])) { BLI_assert(0); } #endif return EIG_self_adjoint_eigen_solve( 3, (const float *)m3, r_eigen_values, (float *)r_eigen_vectors); } /** * \brief Compute the SVD (Singular Values Decomposition) of given 3D matrix (m3 = USV*). * * \param m3: the matrix to decompose. * \return r_U the computed left singular vector of \a m3 (NULL if not needed). * \return r_S the computed singular values of \a m3 (NULL if not needed). * \return r_V the computed right singular vector of \a m3 (NULL if not needed). */ void BLI_svd_m3(const float m3[3][3], float r_U[3][3], float r_S[3], float r_V[3][3]) { EIG_svd_square_matrix(3, (const float *)m3, (float *)r_U, (float *)r_S, (float *)r_V); } /***************************** Simple Solvers ************************************/ /** * \brief Solve a tridiagonal system of equations: * * a[i] * r_x[i-1] + b[i] * r_x[i] + c[i] * r_x[i+1] = d[i] * * Ignores a[0] and c[count-1]. Uses the Thomas algorithm, e.g. see wiki. * * \param r_x: output vector, may be shared with any of the input ones * \return true if success */ bool BLI_tridiagonal_solve( const float *a, const float *b, const float *c, const float *d, float *r_x, const int count) { if (count < 1) { return false; } size_t bytes = sizeof(double) * (unsigned)count; double *c1 = (double *)MEM_mallocN(bytes * 2, "tridiagonal_c1d1"); double *d1 = c1 + count; if (!c1) { return false; } int i; double c_prev, d_prev, x_prev; /* forward pass */ c1[0] = c_prev = ((double)c[0]) / b[0]; d1[0] = d_prev = ((double)d[0]) / b[0]; for (i = 1; i < count; i++) { double denum = b[i] - a[i] * c_prev; c1[i] = c_prev = c[i] / denum; d1[i] = d_prev = (d[i] - a[i] * d_prev) / denum; } /* back pass */ x_prev = d_prev; r_x[--i] = ((float)x_prev); while (--i >= 0) { x_prev = d1[i] - c1[i] * x_prev; r_x[i] = ((float)x_prev); } MEM_freeN(c1); return isfinite(x_prev); } /** * \brief Solve a possibly cyclic tridiagonal system using the Sherman-Morrison formula. * * \param r_x: output vector, may be shared with any of the input ones * \return true if success */ bool BLI_tridiagonal_solve_cyclic( const float *a, const float *b, const float *c, const float *d, float *r_x, const int count) { if (count < 1) { return false; } /* Degenerate case not handled correctly by the generic formula. */ if (count == 1) { r_x[0] = d[0] / (a[0] + b[0] + c[0]); return isfinite(r_x[0]); } /* Degenerate case that works but can be simplified. */ if (count == 2) { float a2[2] = {0, a[1] + c[1]}; float c2[2] = {a[0] + c[0], 0}; return BLI_tridiagonal_solve(a2, b, c2, d, r_x, count); } /* If not really cyclic, fall back to the simple solver. */ float a0 = a[0], cN = c[count - 1]; if (a0 == 0.0f && cN == 0.0f) { return BLI_tridiagonal_solve(a, b, c, d, r_x, count); } size_t bytes = sizeof(float) * (unsigned)count; float *tmp = (float *)MEM_mallocN(bytes * 2, "tridiagonal_ex"); float *b2 = tmp + count; if (!tmp) { return false; } /* prepare the noncyclic system; relies on tridiagonal_solve ignoring values */ memcpy(b2, b, bytes); b2[0] -= a0; b2[count - 1] -= cN; memset(tmp, 0, bytes); tmp[0] = a0; tmp[count - 1] = cN; /* solve for partial solution and adjustment vector */ bool success = BLI_tridiagonal_solve(a, b2, c, tmp, tmp, count) && BLI_tridiagonal_solve(a, b2, c, d, r_x, count); /* apply adjustment */ if (success) { float coeff = (r_x[0] + r_x[count - 1]) / (1.0f + tmp[0] + tmp[count - 1]); for (int i = 0; i < count; i++) { r_x[i] -= coeff * tmp[i]; } } MEM_freeN(tmp); return success; } /** * \brief Solve a generic f(x) = 0 equation using Newton's method. * * \param func_delta: Callback computing the value of f(x). * \param func_jacobian: Callback computing the Jacobian matrix of the function at x. * \param func_correction: Callback for forcing the search into an arbitrary custom domain. * May be NULL. * \param userdata: Data for the callbacks. * \param epsilon: Desired precision. * \param max_iterations: Limit on the iterations. * \param trace: Enables logging to console. * \param x_init: Initial solution vector. * \param result: Final result. * \return true if success */ bool BLI_newton3d_solve(Newton3D_DeltaFunc func_delta, Newton3D_JacobianFunc func_jacobian, Newton3D_CorrectionFunc func_correction, void *userdata, float epsilon, int max_iterations, bool trace, const float x_init[3], float result[3]) { float fdelta[3], fdeltav, next_fdeltav; float jacobian[3][3], step[3], x[3], x_next[3]; epsilon *= epsilon; copy_v3_v3(x, x_init); func_delta(userdata, x, fdelta); fdeltav = len_squared_v3(fdelta); if (trace) { printf("START (%g, %g, %g) %g %g\n", x[0], x[1], x[2], fdeltav, epsilon); } for (int i = 0; i == 0 || (i < max_iterations && fdeltav > epsilon); i++) { /* Newton's method step. */ func_jacobian(userdata, x, jacobian); if (!invert_m3(jacobian)) { return false; } mul_v3_m3v3(step, jacobian, fdelta); sub_v3_v3v3(x_next, x, step); /* Custom out-of-bounds value correction. */ if (func_correction) { if (trace) { printf("%3d * (%g, %g, %g)\n", i, x_next[0], x_next[1], x_next[2]); } if (!func_correction(userdata, x, step, x_next)) { return false; } } func_delta(userdata, x_next, fdelta); next_fdeltav = len_squared_v3(fdelta); if (trace) { printf("%3d ? (%g, %g, %g) %g\n", i, x_next[0], x_next[1], x_next[2], next_fdeltav); } /* Line search correction. */ while (next_fdeltav > fdeltav && next_fdeltav > epsilon) { float g0 = sqrtf(fdeltav), g1 = sqrtf(next_fdeltav); float g01 = -g0 / len_v3(step); float det = 2.0f * (g1 - g0 - g01); float l = (det == 0.0f) ? 0.1f : -g01 / det; CLAMP_MIN(l, 0.1f); mul_v3_fl(step, l); sub_v3_v3v3(x_next, x, step); func_delta(userdata, x_next, fdelta); next_fdeltav = len_squared_v3(fdelta); if (trace) { printf("%3d . (%g, %g, %g) %g\n", i, x_next[0], x_next[1], x_next[2], next_fdeltav); } } copy_v3_v3(x, x_next); fdeltav = next_fdeltav; } bool success = (fdeltav <= epsilon); if (trace) { printf("%s (%g, %g, %g) %g\n", success ? "OK " : "FAIL", x[0], x[1], x[2], fdeltav); } copy_v3_v3(result, x); return success; }