2015-11-24 20:35:57 -04:00
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/*
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* matrix3.cpp
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* Copyright (C) Siddharth Bharat Purohit, 3DRobotics Inc. 2015
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*
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* This file is free software: you can redistribute it and/or modify it
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* under the terms of the GNU General Public License as published by the
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* Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This file is distributed in the hope that it will be useful, but
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* WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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* See the GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License along
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* with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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2019-09-27 17:45:12 -03:00
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#pragma GCC optimize("O2")
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2015-10-19 18:27:22 -03:00
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2015-08-11 03:28:42 -03:00
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#include <AP_HAL/AP_HAL.h>
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2016-05-09 14:53:30 -03:00
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2015-11-24 20:35:57 -04:00
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#include <stdio.h>
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2016-05-09 14:53:30 -03:00
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#if CONFIG_HAL_BOARD == HAL_BOARD_SITL
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#include <fenv.h>
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#endif
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#include <AP_Math/AP_Math.h>
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2015-05-29 04:04:29 -03:00
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extern const AP_HAL::HAL& hal;
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2015-12-28 19:19:05 -04:00
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//TODO: use higher precision datatypes to achieve more accuracy for matrix algebra operations
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2015-05-29 04:04:29 -03:00
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/*
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2015-11-24 20:35:57 -04:00
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* Does matrix multiplication of two regular/square matrices
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*
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2015-11-24 20:35:57 -04:00
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* @param A, Matrix A
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* @param B, Matrix B
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* @param n, dimemsion of square matrices
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* @returns multiplied matrix i.e. A*B
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2015-05-29 04:04:29 -03:00
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*/
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2015-11-24 20:35:57 -04:00
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float* mat_mul(float *A, float *B, uint8_t n)
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2015-05-29 04:04:29 -03:00
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{
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2015-11-24 20:35:57 -04:00
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float* ret = new float[n*n];
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memset(ret,0.0f,n*n*sizeof(float));
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2015-05-29 04:04:29 -03:00
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2015-11-24 20:35:57 -04:00
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for(uint8_t i = 0; i < n; i++) {
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for(uint8_t j = 0; j < n; j++) {
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for(uint8_t k = 0;k < n; k++) {
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ret[i*n + j] += A[i*n + k] * B[k*n + j];
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}
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2015-05-29 04:04:29 -03:00
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}
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}
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2015-11-24 20:35:57 -04:00
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return ret;
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}
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2015-05-29 04:04:29 -03:00
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2015-12-30 02:57:21 -04:00
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static inline void swap(float &a, float &b)
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2015-11-24 20:35:57 -04:00
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{
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float c;
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c = a;
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a = b;
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b = c;
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2015-05-29 04:04:29 -03:00
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}
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2015-11-24 20:35:57 -04:00
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2015-05-29 04:04:29 -03:00
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/*
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2015-11-24 20:35:57 -04:00
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* calculates pivot matrix such that all the larger elements in the row are on diagonal
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2015-05-29 04:04:29 -03:00
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*
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2015-11-24 20:35:57 -04:00
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* @param A, input matrix matrix
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* @param pivot
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* @param n, dimenstion of square matrix
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* @returns false = matrix is Singular or non positive definite, true = matrix inversion successful
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2015-05-29 04:04:29 -03:00
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*/
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2016-06-21 12:06:00 -03:00
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static void mat_pivot(float* A, float* pivot, uint8_t n)
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{
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2015-11-24 20:35:57 -04:00
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for(uint8_t i = 0;i<n;i++){
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for(uint8_t j=0;j<n;j++) {
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2016-12-05 04:19:50 -04:00
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pivot[i*n+j] = static_cast<float>(i==j);
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2015-11-24 20:35:57 -04:00
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}
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2015-05-29 04:04:29 -03:00
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}
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2015-11-24 20:35:57 -04:00
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for(uint8_t i = 0;i < n; i++) {
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uint8_t max_j = i;
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for(uint8_t j=i;j<n;j++){
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if(fabsf(A[j*n + i]) > fabsf(A[max_j*n + i])) {
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max_j = j;
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2015-05-29 04:04:29 -03:00
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}
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}
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2015-11-24 20:35:57 -04:00
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if(max_j != i) {
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for(uint8_t k = 0; k < n; k++) {
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swap(pivot[i*n + k], pivot[max_j*n + k]);
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2015-05-29 04:04:29 -03:00
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}
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}
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2015-11-24 20:35:57 -04:00
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}
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}
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2015-05-29 04:04:29 -03:00
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2015-11-24 20:35:57 -04:00
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/*
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* calculates matrix inverse of Lower trangular matrix using forward substitution
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*
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* @param L, lower triangular matrix
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* @param out, Output inverted lower triangular matrix
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* @param n, dimension of matrix
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*/
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2015-05-29 04:04:29 -03:00
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2016-06-21 12:06:00 -03:00
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static void mat_forward_sub(float *L, float *out, uint8_t n)
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2015-11-24 20:35:57 -04:00
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{
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// Forward substitution solve LY = I
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for(int i = 0; i < n; i++) {
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out[i*n + i] = 1/L[i*n + i];
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for (int j = i+1; j < n; j++) {
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for (int k = i; k < j; k++) {
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out[j*n + i] -= L[j*n + k] * out[k*n + i];
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}
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out[j*n + i] /= L[j*n + j];
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2015-05-29 04:04:29 -03:00
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}
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}
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2015-11-24 20:35:57 -04:00
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}
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2015-05-29 04:04:29 -03:00
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2015-11-24 20:35:57 -04:00
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/*
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* calculates matrix inverse of Upper trangular matrix using backward substitution
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*
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* @param U, upper triangular matrix
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* @param out, Output inverted upper triangular matrix
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* @param n, dimension of matrix
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*/
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2015-05-29 04:04:29 -03:00
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2016-06-21 12:06:00 -03:00
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static void mat_back_sub(float *U, float *out, uint8_t n)
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2015-11-24 20:35:57 -04:00
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{
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// Backward Substitution solve UY = I
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for(int i = n-1; i >= 0; i--) {
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out[i*n + i] = 1/U[i*n + i];
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for (int j = i - 1; j >= 0; j--) {
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for (int k = i; k > j; k--) {
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out[j*n + i] -= U[j*n + k] * out[k*n + i];
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}
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out[j*n + i] /= U[j*n + j];
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2015-05-29 04:04:29 -03:00
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}
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}
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2015-11-24 20:35:57 -04:00
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}
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/*
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* Decomposes square matrix into Lower and Upper triangular matrices such that
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* A*P = L*U, where P is the pivot matrix
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* ref: http://rosettacode.org/wiki/LU_decomposition
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* @param U, upper triangular matrix
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* @param out, Output inverted upper triangular matrix
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* @param n, dimension of matrix
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*/
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2015-05-29 04:04:29 -03:00
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2016-06-21 12:06:00 -03:00
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static void mat_LU_decompose(float* A, float* L, float* U, float *P, uint8_t n)
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{
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memset(L,0,n*n*sizeof(float));
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memset(U,0,n*n*sizeof(float));
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memset(P,0,n*n*sizeof(float));
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mat_pivot(A,P,n);
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float *APrime = mat_mul(P,A,n);
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for(uint8_t i = 0; i < n; i++) {
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L[i*n + i] = 1;
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}
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for(uint8_t i = 0; i < n; i++) {
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for(uint8_t j = 0; j < n; j++) {
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if(j <= i) {
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U[j*n + i] = APrime[j*n + i];
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for(uint8_t k = 0; k < j; k++) {
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U[j*n + i] -= L[j*n + k] * U[k*n + i];
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}
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}
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if(j >= i) {
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L[j*n + i] = APrime[j*n + i];
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for(uint8_t k = 0; k < i; k++) {
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L[j*n + i] -= L[j*n + k] * U[k*n + i];
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2015-05-29 04:04:29 -03:00
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}
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2015-11-24 20:35:57 -04:00
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L[j*n + i] /= U[i*n + i];
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2015-05-29 04:04:29 -03:00
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}
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}
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}
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2016-08-02 18:15:01 -03:00
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delete[] APrime;
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2015-11-24 20:35:57 -04:00
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}
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2015-05-29 04:04:29 -03:00
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2015-11-24 20:35:57 -04:00
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/*
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* matrix inverse code for any square matrix using LU decomposition
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* inv = inv(U)*inv(L)*P, where L and U are triagular matrices and P the pivot matrix
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* ref: http://www.cl.cam.ac.uk/teaching/1314/NumMethods/supporting/mcmaster-kiruba-ludecomp.pdf
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* @param m, input 4x4 matrix
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* @param inv, Output inverted 4x4 matrix
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* @param n, dimension of square matrix
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* @returns false = matrix is Singular, true = matrix inversion successful
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*/
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2016-06-21 12:06:00 -03:00
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static bool mat_inverse(float* A, float* inv, uint8_t n)
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2015-11-24 20:35:57 -04:00
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{
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float *L, *U, *P;
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bool ret = true;
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L = new float[n*n];
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U = new float[n*n];
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P = new float[n*n];
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mat_LU_decompose(A,L,U,P,n);
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float *L_inv = new float[n*n];
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float *U_inv = new float[n*n];
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memset(L_inv,0,n*n*sizeof(float));
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mat_forward_sub(L,L_inv,n);
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memset(U_inv,0,n*n*sizeof(float));
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mat_back_sub(U,U_inv,n);
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2016-05-12 14:02:03 -03:00
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// decomposed matrices no longer required
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2016-08-02 18:15:01 -03:00
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delete[] L;
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delete[] U;
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2015-11-24 20:35:57 -04:00
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float *inv_unpivoted = mat_mul(U_inv,L_inv,n);
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float *inv_pivoted = mat_mul(inv_unpivoted, P, n);
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//check sanity of results
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for(uint8_t i = 0; i < n; i++) {
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for(uint8_t j = 0; j < n; j++) {
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if(isnan(inv_pivoted[i*n+j]) || isinf(inv_pivoted[i*n+j])){
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ret = false;
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2015-05-29 04:04:29 -03:00
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}
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}
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}
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2015-11-24 20:35:57 -04:00
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memcpy(inv,inv_pivoted,n*n*sizeof(float));
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//free memory
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2016-08-02 18:15:01 -03:00
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delete[] inv_pivoted;
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delete[] inv_unpivoted;
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delete[] P;
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delete[] U_inv;
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delete[] L_inv;
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2015-11-24 20:35:57 -04:00
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return ret;
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2015-05-29 04:04:29 -03:00
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}
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/*
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2015-11-24 20:35:57 -04:00
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* fast matrix inverse code only for 3x3 square matrix
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2015-05-29 04:04:29 -03:00
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*
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* @param m, input 4x4 matrix
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* @param invOut, Output inverted 4x4 matrix
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* @returns false = matrix is Singular, true = matrix inversion successful
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*/
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bool inverse3x3(float m[], float invOut[])
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{
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float inv[9];
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// computes the inverse of a matrix m
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float det = m[0] * (m[4] * m[8] - m[7] * m[5]) -
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m[1] * (m[3] * m[8] - m[5] * m[6]) +
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m[2] * (m[3] * m[7] - m[4] * m[6]);
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2016-05-09 14:48:08 -03:00
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if (is_zero(det) || isinf(det)) {
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2015-05-29 04:04:29 -03:00
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return false;
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}
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float invdet = 1 / det;
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inv[0] = (m[4] * m[8] - m[7] * m[5]) * invdet;
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inv[1] = (m[2] * m[7] - m[1] * m[8]) * invdet;
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inv[2] = (m[1] * m[5] - m[2] * m[4]) * invdet;
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2015-11-24 20:35:57 -04:00
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inv[3] = (m[5] * m[6] - m[3] * m[8]) * invdet;
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2015-05-29 04:04:29 -03:00
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inv[4] = (m[0] * m[8] - m[2] * m[6]) * invdet;
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inv[5] = (m[3] * m[2] - m[0] * m[5]) * invdet;
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inv[6] = (m[3] * m[7] - m[6] * m[4]) * invdet;
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inv[7] = (m[6] * m[1] - m[0] * m[7]) * invdet;
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inv[8] = (m[0] * m[4] - m[3] * m[1]) * invdet;
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for(uint8_t i = 0; i < 9; i++){
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invOut[i] = inv[i];
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}
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return true;
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}
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/*
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2015-11-24 20:35:57 -04:00
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* fast matrix inverse code only for 4x4 square matrix copied from
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* gluInvertMatrix implementation in opengl for 4x4 matrices.
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2015-05-29 04:04:29 -03:00
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*
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* @param m, input 4x4 matrix
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* @param invOut, Output inverted 4x4 matrix
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* @returns false = matrix is Singular, true = matrix inversion successful
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*/
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bool inverse4x4(float m[],float invOut[])
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{
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float inv[16], det;
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uint8_t i;
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2016-05-09 14:53:30 -03:00
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#if CONFIG_HAL_BOARD == HAL_BOARD_SITL
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2020-05-13 14:08:19 -03:00
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//disable FE_INEXACT detection as it fails on mac os runs
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int old = fedisableexcept(FE_INEXACT | FE_OVERFLOW);
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2016-05-09 14:53:30 -03:00
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if (old < 0) {
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hal.console->printf("inverse4x4(): warning: error on disabling FE_OVERFLOW floating point exception\n");
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}
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#endif
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2015-05-29 04:04:29 -03:00
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inv[0] = m[5] * m[10] * m[15] -
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m[5] * m[11] * m[14] -
|
|
|
|
m[9] * m[6] * m[15] +
|
|
|
|
m[9] * m[7] * m[14] +
|
|
|
|
m[13] * m[6] * m[11] -
|
|
|
|
m[13] * m[7] * m[10];
|
|
|
|
|
|
|
|
inv[4] = -m[4] * m[10] * m[15] +
|
|
|
|
m[4] * m[11] * m[14] +
|
|
|
|
m[8] * m[6] * m[15] -
|
|
|
|
m[8] * m[7] * m[14] -
|
|
|
|
m[12] * m[6] * m[11] +
|
|
|
|
m[12] * m[7] * m[10];
|
|
|
|
|
|
|
|
inv[8] = m[4] * m[9] * m[15] -
|
|
|
|
m[4] * m[11] * m[13] -
|
|
|
|
m[8] * m[5] * m[15] +
|
|
|
|
m[8] * m[7] * m[13] +
|
|
|
|
m[12] * m[5] * m[11] -
|
|
|
|
m[12] * m[7] * m[9];
|
|
|
|
|
|
|
|
inv[12] = -m[4] * m[9] * m[14] +
|
|
|
|
m[4] * m[10] * m[13] +
|
|
|
|
m[8] * m[5] * m[14] -
|
|
|
|
m[8] * m[6] * m[13] -
|
|
|
|
m[12] * m[5] * m[10] +
|
|
|
|
m[12] * m[6] * m[9];
|
|
|
|
|
|
|
|
inv[1] = -m[1] * m[10] * m[15] +
|
|
|
|
m[1] * m[11] * m[14] +
|
|
|
|
m[9] * m[2] * m[15] -
|
|
|
|
m[9] * m[3] * m[14] -
|
|
|
|
m[13] * m[2] * m[11] +
|
|
|
|
m[13] * m[3] * m[10];
|
|
|
|
|
|
|
|
inv[5] = m[0] * m[10] * m[15] -
|
|
|
|
m[0] * m[11] * m[14] -
|
|
|
|
m[8] * m[2] * m[15] +
|
|
|
|
m[8] * m[3] * m[14] +
|
|
|
|
m[12] * m[2] * m[11] -
|
|
|
|
m[12] * m[3] * m[10];
|
|
|
|
|
|
|
|
inv[9] = -m[0] * m[9] * m[15] +
|
|
|
|
m[0] * m[11] * m[13] +
|
|
|
|
m[8] * m[1] * m[15] -
|
|
|
|
m[8] * m[3] * m[13] -
|
|
|
|
m[12] * m[1] * m[11] +
|
|
|
|
m[12] * m[3] * m[9];
|
|
|
|
|
|
|
|
inv[13] = m[0] * m[9] * m[14] -
|
|
|
|
m[0] * m[10] * m[13] -
|
|
|
|
m[8] * m[1] * m[14] +
|
|
|
|
m[8] * m[2] * m[13] +
|
|
|
|
m[12] * m[1] * m[10] -
|
|
|
|
m[12] * m[2] * m[9];
|
|
|
|
|
|
|
|
inv[2] = m[1] * m[6] * m[15] -
|
|
|
|
m[1] * m[7] * m[14] -
|
|
|
|
m[5] * m[2] * m[15] +
|
|
|
|
m[5] * m[3] * m[14] +
|
|
|
|
m[13] * m[2] * m[7] -
|
|
|
|
m[13] * m[3] * m[6];
|
|
|
|
|
|
|
|
inv[6] = -m[0] * m[6] * m[15] +
|
|
|
|
m[0] * m[7] * m[14] +
|
|
|
|
m[4] * m[2] * m[15] -
|
|
|
|
m[4] * m[3] * m[14] -
|
|
|
|
m[12] * m[2] * m[7] +
|
|
|
|
m[12] * m[3] * m[6];
|
|
|
|
|
|
|
|
inv[10] = m[0] * m[5] * m[15] -
|
|
|
|
m[0] * m[7] * m[13] -
|
|
|
|
m[4] * m[1] * m[15] +
|
|
|
|
m[4] * m[3] * m[13] +
|
|
|
|
m[12] * m[1] * m[7] -
|
|
|
|
m[12] * m[3] * m[5];
|
|
|
|
|
|
|
|
inv[14] = -m[0] * m[5] * m[14] +
|
|
|
|
m[0] * m[6] * m[13] +
|
|
|
|
m[4] * m[1] * m[14] -
|
|
|
|
m[4] * m[2] * m[13] -
|
|
|
|
m[12] * m[1] * m[6] +
|
|
|
|
m[12] * m[2] * m[5];
|
|
|
|
|
|
|
|
inv[3] = -m[1] * m[6] * m[11] +
|
|
|
|
m[1] * m[7] * m[10] +
|
|
|
|
m[5] * m[2] * m[11] -
|
|
|
|
m[5] * m[3] * m[10] -
|
|
|
|
m[9] * m[2] * m[7] +
|
|
|
|
m[9] * m[3] * m[6];
|
|
|
|
|
|
|
|
inv[7] = m[0] * m[6] * m[11] -
|
|
|
|
m[0] * m[7] * m[10] -
|
|
|
|
m[4] * m[2] * m[11] +
|
|
|
|
m[4] * m[3] * m[10] +
|
|
|
|
m[8] * m[2] * m[7] -
|
|
|
|
m[8] * m[3] * m[6];
|
|
|
|
|
|
|
|
inv[11] = -m[0] * m[5] * m[11] +
|
|
|
|
m[0] * m[7] * m[9] +
|
|
|
|
m[4] * m[1] * m[11] -
|
|
|
|
m[4] * m[3] * m[9] -
|
|
|
|
m[8] * m[1] * m[7] +
|
|
|
|
m[8] * m[3] * m[5];
|
|
|
|
|
|
|
|
inv[15] = m[0] * m[5] * m[10] -
|
|
|
|
m[0] * m[6] * m[9] -
|
|
|
|
m[4] * m[1] * m[10] +
|
|
|
|
m[4] * m[2] * m[9] +
|
|
|
|
m[8] * m[1] * m[6] -
|
|
|
|
m[8] * m[2] * m[5];
|
|
|
|
|
|
|
|
det = m[0] * inv[0] + m[1] * inv[4] + m[2] * inv[8] + m[3] * inv[12];
|
|
|
|
|
2016-05-09 14:48:08 -03:00
|
|
|
if (is_zero(det) || isinf(det)){
|
2015-05-29 04:04:29 -03:00
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
det = 1.0f / det;
|
|
|
|
|
|
|
|
for (i = 0; i < 16; i++)
|
|
|
|
invOut[i] = inv[i] * det;
|
2020-05-13 14:08:19 -03:00
|
|
|
|
|
|
|
#if CONFIG_HAL_BOARD == HAL_BOARD_SITL
|
|
|
|
if (old >= 0 && feenableexcept(old) < 0) {
|
|
|
|
hal.console->printf("inverse4x4(): warning: error on restoring floating exception mask\n");
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
2015-05-29 04:04:29 -03:00
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* generic matrix inverse code
|
|
|
|
*
|
|
|
|
* @param x, input nxn matrix
|
|
|
|
* @param y, Output inverted nxn matrix
|
|
|
|
* @param n, dimension of square matrix
|
|
|
|
* @returns false = matrix is Singular, true = matrix inversion successful
|
|
|
|
*/
|
|
|
|
bool inverse(float x[], float y[], uint16_t dim)
|
|
|
|
{
|
|
|
|
switch(dim){
|
|
|
|
case 3: return inverse3x3(x,y);
|
|
|
|
case 4: return inverse4x4(x,y);
|
2015-11-24 20:35:57 -04:00
|
|
|
default: return mat_inverse(x,y,dim);
|
2015-05-29 04:04:29 -03:00
|
|
|
}
|
|
|
|
}
|