/* Copyright (C) 2013-2016, The Regents of The University of Michigan. All rights reserved. This software was developed in the APRIL Robotics Lab under the direction of Edwin Olson, ebolson@umich.edu. This software may be available under alternative licensing terms; contact the address above. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 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The views and conclusions contained in the software and documentation are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of the Regents of The University of Michigan. */ #include #include #include #include #include "common/doubles.h" /** SVD 2x2. Computes singular values and vectors without squaring the input matrix. With double precision math, results are accurate to about 1E-16. U = [ cos(theta) -sin(theta) ] [ sin(theta) cos(theta) ] S = [ e 0 ] [ 0 f ] V = [ cos(phi) -sin(phi) ] [ sin(phi) cos(phi) ] Our strategy is basically to analytically multiply everything out and then rearrange so that we can solve for theta, phi, e, and f. (Derivation by ebolson@umich.edu 5/2016) V' = [ CP SP ] [ -SP CP ] USV' = [ CT -ST ][ e*CP e*SP ] [ ST CT ][ -f*SP f*CP ] = [e*CT*CP + f*ST*SP e*CT*SP - f*ST*CP ] [e*ST*CP - f*SP*CT e*SP*ST + f*CP*CT ] A00+A11 = e*CT*CP + f*ST*SP + e*SP*ST + f*CP*CT = e*(CP*CT + SP*ST) + f*(SP*ST + CP*CT) = (e+f)(CP*CT + SP*ST) B0 = (e+f)*cos(P-T) A00-A11 = e*CT*CP + f*ST*SP - e*SP*ST - f*CP*CT = e*(CP*CT - SP*ST) - f*(-ST*SP + CP*CT) = (e-f)(CP*CT - SP*ST) B1 = (e-f)*cos(P+T) A01+A10 = e*CT*SP - f*ST*CP + e*ST*CP - f*SP*CT = e(CT*SP + ST*CP) - f*(ST*CP + SP*CT) = (e-f)*(CT*SP + ST*CP) B2 = (e-f)*sin(P+T) A01-A10 = e*CT*SP - f*ST*CP - e*ST*CP + f*SP*CT = e*(CT*SP - ST*CP) + f(SP*CT - ST*CP) = (e+f)*(CT*SP - ST*CP) B3 = (e+f)*sin(P-T) B0 = (e+f)*cos(P-T) B1 = (e-f)*cos(P+T) B2 = (e-f)*sin(P+T) B3 = (e+f)*sin(P-T) B3/B0 = tan(P-T) B2/B1 = tan(P+T) **/ void svd22(const double A[4], double U[4], double S[2], double V[4]) { double A00 = A[0]; double A01 = A[1]; double A10 = A[2]; double A11 = A[3]; double B0 = A00 + A11; double B1 = A00 - A11; double B2 = A01 + A10; double B3 = A01 - A10; double PminusT = atan2(B3, B0); double PplusT = atan2(B2, B1); double P = (PminusT + PplusT) / 2; double T = (-PminusT + PplusT) / 2; double CP = cos(P), SP = sin(P); double CT = cos(T), ST = sin(T); U[0] = CT; U[1] = -ST; U[2] = ST; U[3] = CT; V[0] = CP; V[1] = -SP; V[2] = SP; V[3] = CP; // C0 = e+f. There are two ways to compute C0; we pick the one // that is better conditioned. double CPmT = cos(P-T), SPmT = sin(P-T); double C0 = 0; if (fabs(CPmT) > fabs(SPmT)) C0 = B0 / CPmT; else C0 = B3 / SPmT; // C1 = e-f. There are two ways to compute C1; we pick the one // that is better conditioned. double CPpT = cos(P+T), SPpT = sin(P+T); double C1 = 0; if (fabs(CPpT) > fabs(SPpT)) C1 = B1 / CPpT; else C1 = B2 / SPpT; // e and f are the singular values double e = (C0 + C1) / 2; double f = (C0 - C1) / 2; if (e < 0) { e = -e; U[0] = -U[0]; U[2] = -U[2]; } if (f < 0) { f = -f; U[1] = -U[1]; U[3] = -U[3]; } // sort singular values. if (e > f) { // already in big-to-small order. S[0] = e; S[1] = f; } else { // Curiously, this code never seems to get invoked. Why is it // that S[0] always ends up the dominant vector? However, // this code has been tested (flipping the logic forces us to // sort the singular values in ascending order). // // P = [ 0 1 ; 1 0 ] // USV' = (UP)(PSP)(PV') // = (UP)(PSP)(VP)' // = (UP)(PSP)(P'V')' S[0] = f; S[1] = e; // exchange columns of U and V double tmp[2]; tmp[0] = U[0]; tmp[1] = U[2]; U[0] = U[1]; U[2] = U[3]; U[1] = tmp[0]; U[3] = tmp[1]; tmp[0] = V[0]; tmp[1] = V[2]; V[0] = V[1]; V[2] = V[3]; V[1] = tmp[0]; V[3] = tmp[1]; } /* double SM[4] = { S[0], 0, 0, S[1] }; doubles_print_mat(U, 2, 2, "%20.10g"); doubles_print_mat(SM, 2, 2, "%20.10g"); doubles_print_mat(V, 2, 2, "%20.10g"); printf("A:\n"); doubles_print_mat(A, 2, 2, "%20.10g"); double SVt[4]; doubles_mat_ABt(SM, 2, 2, V, 2, 2, SVt, 2, 2); double USVt[4]; doubles_mat_AB(U, 2, 2, SVt, 2, 2, USVt, 2, 2); printf("USVt\n"); doubles_print_mat(USVt, 2, 2, "%20.10g"); double diff[4]; for (int i = 0; i < 4; i++) diff[i] = A[i] - USVt[i]; printf("diff\n"); doubles_print_mat(diff, 2, 2, "%20.10g"); */ } // for the matrix [a b; b d] void svd_sym_singular_values(double A00, double A01, double A11, double *Lmin, double *Lmax) { double A10 = A01; double B0 = A00 + A11; double B1 = A00 - A11; double B2 = A01 + A10; double B3 = A01 - A10; double PminusT = atan2(B3, B0); double PplusT = atan2(B2, B1); double P = (PminusT + PplusT) / 2; double T = (-PminusT + PplusT) / 2; // C0 = e+f. There are two ways to compute C0; we pick the one // that is better conditioned. double CPmT = cos(P-T), SPmT = sin(P-T); double C0 = 0; if (fabs(CPmT) > fabs(SPmT)) C0 = B0 / CPmT; else C0 = B3 / SPmT; // C1 = e-f. There are two ways to compute C1; we pick the one // that is better conditioned. double CPpT = cos(P+T), SPpT = sin(P+T); double C1 = 0; if (fabs(CPpT) > fabs(SPpT)) C1 = B1 / CPpT; else C1 = B2 / SPpT; // e and f are the singular values double e = (C0 + C1) / 2; double f = (C0 - C1) / 2; *Lmin = fmin(e, f); *Lmax = fmax(e, f); }