| 1 |
< |
/* |
| 2 |
< |
* Copyright (C) 2000-2004 Object Oriented Parallel Simulation Engine (OOPSE) project |
| 3 |
< |
* |
| 4 |
< |
* Contact: oopse@oopse.org |
| 5 |
< |
* |
| 6 |
< |
* This program is free software; you can redistribute it and/or |
| 7 |
< |
* modify it under the terms of the GNU Lesser General Public License |
| 8 |
< |
* as published by the Free Software Foundation; either version 2.1 |
| 9 |
< |
* of the License, or (at your option) any later version. |
| 10 |
< |
* All we ask is that proper credit is given for our work, which includes |
| 11 |
< |
* - but is not limited to - adding the above copyright notice to the beginning |
| 12 |
< |
* of your source code files, and to any copyright notice that you may distribute |
| 13 |
< |
* with programs based on this work. |
| 14 |
< |
* |
| 15 |
< |
* This program is distributed in the hope that it will be useful, |
| 16 |
< |
* but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 17 |
< |
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| 18 |
< |
* GNU Lesser General Public License for more details. |
| 19 |
< |
* |
| 20 |
< |
* You should have received a copy of the GNU Lesser General Public License |
| 21 |
< |
* along with this program; if not, write to the Free Software |
| 22 |
< |
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. |
| 1 |
> |
/* |
| 2 |
> |
* Copyright (c) 2005 The University of Notre Dame. All Rights Reserved. |
| 3 |
|
* |
| 4 |
+ |
* The University of Notre Dame grants you ("Licensee") a |
| 5 |
+ |
* non-exclusive, royalty free, license to use, modify and |
| 6 |
+ |
* redistribute this software in source and binary code form, provided |
| 7 |
+ |
* that the following conditions are met: |
| 8 |
+ |
* |
| 9 |
+ |
* 1. Acknowledgement of the program authors must be made in any |
| 10 |
+ |
* publication of scientific results based in part on use of the |
| 11 |
+ |
* program. An acceptable form of acknowledgement is citation of |
| 12 |
+ |
* the article in which the program was described (Matthew |
| 13 |
+ |
* A. Meineke, Charles F. Vardeman II, Teng Lin, Christopher |
| 14 |
+ |
* J. Fennell and J. Daniel Gezelter, "OOPSE: An Object-Oriented |
| 15 |
+ |
* Parallel Simulation Engine for Molecular Dynamics," |
| 16 |
+ |
* J. Comput. Chem. 26, pp. 252-271 (2005)) |
| 17 |
+ |
* |
| 18 |
+ |
* 2. Redistributions of source code must retain the above copyright |
| 19 |
+ |
* notice, this list of conditions and the following disclaimer. |
| 20 |
+ |
* |
| 21 |
+ |
* 3. Redistributions in binary form must reproduce the above copyright |
| 22 |
+ |
* notice, this list of conditions and the following disclaimer in the |
| 23 |
+ |
* documentation and/or other materials provided with the |
| 24 |
+ |
* distribution. |
| 25 |
+ |
* |
| 26 |
+ |
* This software is provided "AS IS," without a warranty of any |
| 27 |
+ |
* kind. All express or implied conditions, representations and |
| 28 |
+ |
* warranties, including any implied warranty of merchantability, |
| 29 |
+ |
* fitness for a particular purpose or non-infringement, are hereby |
| 30 |
+ |
* excluded. The University of Notre Dame and its licensors shall not |
| 31 |
+ |
* be liable for any damages suffered by licensee as a result of |
| 32 |
+ |
* using, modifying or distributing the software or its |
| 33 |
+ |
* derivatives. In no event will the University of Notre Dame or its |
| 34 |
+ |
* licensors be liable for any lost revenue, profit or data, or for |
| 35 |
+ |
* direct, indirect, special, consequential, incidental or punitive |
| 36 |
+ |
* damages, however caused and regardless of the theory of liability, |
| 37 |
+ |
* arising out of the use of or inability to use software, even if the |
| 38 |
+ |
* University of Notre Dame has been advised of the possibility of |
| 39 |
+ |
* such damages. |
| 40 |
|
*/ |
| 41 |
< |
|
| 41 |
> |
|
| 42 |
|
/** |
| 43 |
|
* @file SquareMatrix3.hpp |
| 44 |
|
* @author Teng Lin |
| 45 |
|
* @date 10/11/2004 |
| 46 |
|
* @version 1.0 |
| 47 |
|
*/ |
| 48 |
< |
#ifndef MATH_SQUAREMATRIX3_HPP |
| 48 |
> |
#ifndef MATH_SQUAREMATRIX3_HPP |
| 49 |
|
#define MATH_SQUAREMATRIX3_HPP |
| 50 |
|
|
| 51 |
|
#include "Quaternion.hpp" |
| 57 |
|
template<typename Real> |
| 58 |
|
class SquareMatrix3 : public SquareMatrix<Real, 3> { |
| 59 |
|
public: |
| 60 |
+ |
|
| 61 |
+ |
typedef Real ElemType; |
| 62 |
+ |
typedef Real* ElemPoinerType; |
| 63 |
|
|
| 64 |
|
/** default constructor */ |
| 65 |
|
SquareMatrix3() : SquareMatrix<Real, 3>() { |
| 66 |
|
} |
| 67 |
+ |
|
| 68 |
+ |
/** Constructs and initializes every element of this matrix to a scalar */ |
| 69 |
+ |
SquareMatrix3(Real s) : SquareMatrix<Real,3>(s){ |
| 70 |
+ |
} |
| 71 |
+ |
|
| 72 |
+ |
/** Constructs and initializes from an array */ |
| 73 |
+ |
SquareMatrix3(Real* array) : SquareMatrix<Real,3>(array){ |
| 74 |
+ |
} |
| 75 |
+ |
|
| 76 |
|
|
| 77 |
|
/** copy constructor */ |
| 78 |
|
SquareMatrix3(const SquareMatrix<Real, 3>& m) : SquareMatrix<Real, 3>(m) { |
| 79 |
|
} |
| 80 |
< |
|
| 80 |
> |
|
| 81 |
|
SquareMatrix3( const Vector3<Real>& eulerAngles) { |
| 82 |
|
setupRotMat(eulerAngles); |
| 83 |
|
} |
| 103 |
|
return *this; |
| 104 |
|
} |
| 105 |
|
|
| 106 |
+ |
|
| 107 |
+ |
SquareMatrix3<Real>& operator =(const Quaternion<Real>& q) { |
| 108 |
+ |
this->setupRotMat(q); |
| 109 |
+ |
return *this; |
| 110 |
+ |
} |
| 111 |
+ |
|
| 112 |
|
/** |
| 113 |
|
* Sets this matrix to a rotation matrix by three euler angles |
| 114 |
|
* @ param euler |
| 231 |
|
*/ |
| 232 |
|
Vector3<Real> toEulerAngles() { |
| 233 |
|
Vector3<Real> myEuler; |
| 234 |
< |
Real phi,theta,psi,eps; |
| 235 |
< |
Real ctheta,stheta; |
| 234 |
> |
Real phi; |
| 235 |
> |
Real theta; |
| 236 |
> |
Real psi; |
| 237 |
> |
Real ctheta; |
| 238 |
> |
Real stheta; |
| 239 |
|
|
| 240 |
|
// set the tolerance for Euler angles and rotation elements |
| 241 |
|
|
| 285 |
|
|
| 286 |
|
return(x + y + z); |
| 287 |
|
} |
| 288 |
+ |
|
| 289 |
+ |
/** Returns the trace of this matrix. */ |
| 290 |
+ |
Real trace() const { |
| 291 |
+ |
return data_[0][0] + data_[1][1] + data_[2][2]; |
| 292 |
+ |
} |
| 293 |
|
|
| 294 |
|
/** |
| 295 |
|
* Sets the value of this matrix to the inversion of itself. |
| 296 |
|
* @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the |
| 297 |
|
* implementation of inverse in SquareMatrix class |
| 298 |
|
*/ |
| 299 |
< |
SquareMatrix3<Real> inverse() { |
| 299 |
> |
SquareMatrix3<Real> inverse() const { |
| 300 |
|
SquareMatrix3<Real> m; |
| 301 |
|
double det = determinant(); |
| 302 |
|
if (fabs(det) <= oopse::epsilon) { |
| 317 |
|
m /= det; |
| 318 |
|
return m; |
| 319 |
|
} |
| 320 |
+ |
/** |
| 321 |
+ |
* Extract the eigenvalues and eigenvectors from a 3x3 matrix. |
| 322 |
+ |
* The eigenvectors (the columns of V) will be normalized. |
| 323 |
+ |
* The eigenvectors are aligned optimally with the x, y, and z |
| 324 |
+ |
* axes respectively. |
| 325 |
+ |
* @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is |
| 326 |
+ |
* overwritten |
| 327 |
+ |
* @param w will contain the eigenvalues of the matrix On return of this function |
| 328 |
+ |
* @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are |
| 329 |
+ |
* normalized and mutually orthogonal. |
| 330 |
+ |
* @warning a will be overwritten |
| 331 |
+ |
*/ |
| 332 |
+ |
static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v); |
| 333 |
+ |
}; |
| 334 |
+ |
/*========================================================================= |
| 335 |
|
|
| 336 |
< |
void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v) { |
| 337 |
< |
int i,j,k,maxI; |
| 281 |
< |
Real tmp, maxVal; |
| 282 |
< |
Vector3<Real> v_maxI, v_k, v_j; |
| 336 |
> |
Program: Visualization Toolkit |
| 337 |
> |
Module: $RCSfile: SquareMatrix3.hpp,v $ |
| 338 |
|
|
| 339 |
< |
// diagonalize using Jacobi |
| 340 |
< |
jacobi(a, w, v); |
| 339 |
> |
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen |
| 340 |
> |
All rights reserved. |
| 341 |
> |
See Copyright.txt or http://www.kitware.com/Copyright.htm for details. |
| 342 |
|
|
| 343 |
< |
// if all the eigenvalues are the same, return identity matrix |
| 344 |
< |
if (w[0] == w[1] && w[0] == w[2] ) { |
| 345 |
< |
v = SquareMatrix3<Real>::identity(); |
| 290 |
< |
return; |
| 291 |
< |
} |
| 343 |
> |
This software is distributed WITHOUT ANY WARRANTY; without even |
| 344 |
> |
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR |
| 345 |
> |
PURPOSE. See the above copyright notice for more information. |
| 346 |
|
|
| 347 |
< |
// transpose temporarily, it makes it easier to sort the eigenvectors |
| 348 |
< |
v = v.transpose(); |
| 349 |
< |
|
| 350 |
< |
// if two eigenvalues are the same, re-orthogonalize to optimally line |
| 351 |
< |
// up the eigenvectors with the x, y, and z axes |
| 352 |
< |
for (i = 0; i < 3; i++) { |
| 353 |
< |
if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same |
| 300 |
< |
// find maximum element of the independant eigenvector |
| 301 |
< |
maxVal = fabs(v(i, 0)); |
| 302 |
< |
maxI = 0; |
| 303 |
< |
for (j = 1; j < 3; j++) { |
| 304 |
< |
if (maxVal < (tmp = fabs(v(i, j)))){ |
| 305 |
< |
maxVal = tmp; |
| 306 |
< |
maxI = j; |
| 307 |
< |
} |
| 308 |
< |
} |
| 309 |
< |
|
| 310 |
< |
// swap the eigenvector into its proper position |
| 311 |
< |
if (maxI != i) { |
| 312 |
< |
tmp = w(maxI); |
| 313 |
< |
w(maxI) = w(i); |
| 314 |
< |
w(i) = tmp; |
| 347 |
> |
=========================================================================*/ |
| 348 |
> |
template<typename Real> |
| 349 |
> |
void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, |
| 350 |
> |
SquareMatrix3<Real>& v) { |
| 351 |
> |
int i,j,k,maxI; |
| 352 |
> |
Real tmp, maxVal; |
| 353 |
> |
Vector3<Real> v_maxI, v_k, v_j; |
| 354 |
|
|
| 355 |
< |
v.swapRow(i, maxI); |
| 356 |
< |
} |
| 357 |
< |
// maximum element of eigenvector should be positive |
| 358 |
< |
if (v(maxI, maxI) < 0) { |
| 359 |
< |
v(maxI, 0) = -v(maxI, 0); |
| 360 |
< |
v(maxI, 1) = -v(maxI, 1); |
| 361 |
< |
v(maxI, 2) = -v(maxI, 2); |
| 323 |
< |
} |
| 355 |
> |
// diagonalize using Jacobi |
| 356 |
> |
jacobi(a, w, v); |
| 357 |
> |
// if all the eigenvalues are the same, return identity matrix |
| 358 |
> |
if (w[0] == w[1] && w[0] == w[2] ) { |
| 359 |
> |
v = SquareMatrix3<Real>::identity(); |
| 360 |
> |
return; |
| 361 |
> |
} |
| 362 |
|
|
| 363 |
< |
// re-orthogonalize the other two eigenvectors |
| 364 |
< |
j = (maxI+1)%3; |
| 365 |
< |
k = (maxI+2)%3; |
| 366 |
< |
|
| 367 |
< |
v(j, 0) = 0.0; |
| 368 |
< |
v(j, 1) = 0.0; |
| 369 |
< |
v(j, 2) = 0.0; |
| 370 |
< |
v(j, j) = 1.0; |
| 363 |
> |
// transpose temporarily, it makes it easier to sort the eigenvectors |
| 364 |
> |
v = v.transpose(); |
| 365 |
> |
|
| 366 |
> |
// if two eigenvalues are the same, re-orthogonalize to optimally line |
| 367 |
> |
// up the eigenvectors with the x, y, and z axes |
| 368 |
> |
for (i = 0; i < 3; i++) { |
| 369 |
> |
if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same |
| 370 |
> |
// find maximum element of the independant eigenvector |
| 371 |
> |
maxVal = fabs(v(i, 0)); |
| 372 |
> |
maxI = 0; |
| 373 |
> |
for (j = 1; j < 3; j++) { |
| 374 |
> |
if (maxVal < (tmp = fabs(v(i, j)))){ |
| 375 |
> |
maxVal = tmp; |
| 376 |
> |
maxI = j; |
| 377 |
> |
} |
| 378 |
> |
} |
| 379 |
> |
|
| 380 |
> |
// swap the eigenvector into its proper position |
| 381 |
> |
if (maxI != i) { |
| 382 |
> |
tmp = w(maxI); |
| 383 |
> |
w(maxI) = w(i); |
| 384 |
> |
w(i) = tmp; |
| 385 |
|
|
| 386 |
< |
/** @todo */ |
| 387 |
< |
v_maxI = v.getRow(maxI); |
| 388 |
< |
v_j = v.getRow(j); |
| 389 |
< |
v_k = cross(v_maxI, v_j); |
| 390 |
< |
v_k.normalize(); |
| 391 |
< |
v_j = cross(v_k, v_maxI); |
| 392 |
< |
v.setRow(j, v_j); |
| 393 |
< |
v.setRow(k, v_k); |
| 386 |
> |
v.swapRow(i, maxI); |
| 387 |
> |
} |
| 388 |
> |
// maximum element of eigenvector should be positive |
| 389 |
> |
if (v(maxI, maxI) < 0) { |
| 390 |
> |
v(maxI, 0) = -v(maxI, 0); |
| 391 |
> |
v(maxI, 1) = -v(maxI, 1); |
| 392 |
> |
v(maxI, 2) = -v(maxI, 2); |
| 393 |
> |
} |
| 394 |
|
|
| 395 |
+ |
// re-orthogonalize the other two eigenvectors |
| 396 |
+ |
j = (maxI+1)%3; |
| 397 |
+ |
k = (maxI+2)%3; |
| 398 |
|
|
| 399 |
< |
// transpose vectors back to columns |
| 400 |
< |
v = v.transpose(); |
| 401 |
< |
return; |
| 402 |
< |
} |
| 348 |
< |
} |
| 399 |
> |
v(j, 0) = 0.0; |
| 400 |
> |
v(j, 1) = 0.0; |
| 401 |
> |
v(j, 2) = 0.0; |
| 402 |
> |
v(j, j) = 1.0; |
| 403 |
|
|
| 404 |
< |
// the three eigenvalues are different, just sort the eigenvectors |
| 405 |
< |
// to align them with the x, y, and z axes |
| 404 |
> |
/** @todo */ |
| 405 |
> |
v_maxI = v.getRow(maxI); |
| 406 |
> |
v_j = v.getRow(j); |
| 407 |
> |
v_k = cross(v_maxI, v_j); |
| 408 |
> |
v_k.normalize(); |
| 409 |
> |
v_j = cross(v_k, v_maxI); |
| 410 |
> |
v.setRow(j, v_j); |
| 411 |
> |
v.setRow(k, v_k); |
| 412 |
|
|
| 353 |
– |
// find the vector with the largest x element, make that vector |
| 354 |
– |
// the first vector |
| 355 |
– |
maxVal = fabs(v(0, 0)); |
| 356 |
– |
maxI = 0; |
| 357 |
– |
for (i = 1; i < 3; i++) { |
| 358 |
– |
if (maxVal < (tmp = fabs(v(i, 0)))) { |
| 359 |
– |
maxVal = tmp; |
| 360 |
– |
maxI = i; |
| 361 |
– |
} |
| 362 |
– |
} |
| 413 |
|
|
| 414 |
< |
// swap eigenvalue and eigenvector |
| 415 |
< |
if (maxI != 0) { |
| 416 |
< |
tmp = w(maxI); |
| 417 |
< |
w(maxI) = w(0); |
| 418 |
< |
w(0) = tmp; |
| 369 |
< |
v.swapRow(maxI, 0); |
| 370 |
< |
} |
| 371 |
< |
// do the same for the y element |
| 372 |
< |
if (fabs(v(1, 1)) < fabs(v(2, 1))) { |
| 373 |
< |
tmp = w(2); |
| 374 |
< |
w(2) = w(1); |
| 375 |
< |
w(1) = tmp; |
| 376 |
< |
v.swapRow(2, 1); |
| 377 |
< |
} |
| 414 |
> |
// transpose vectors back to columns |
| 415 |
> |
v = v.transpose(); |
| 416 |
> |
return; |
| 417 |
> |
} |
| 418 |
> |
} |
| 419 |
|
|
| 420 |
< |
// ensure that the sign of the eigenvectors is correct |
| 421 |
< |
for (i = 0; i < 2; i++) { |
| 381 |
< |
if (v(i, i) < 0) { |
| 382 |
< |
v(i, 0) = -v(i, 0); |
| 383 |
< |
v(i, 1) = -v(i, 1); |
| 384 |
< |
v(i, 2) = -v(i, 2); |
| 385 |
< |
} |
| 386 |
< |
} |
| 420 |
> |
// the three eigenvalues are different, just sort the eigenvectors |
| 421 |
> |
// to align them with the x, y, and z axes |
| 422 |
|
|
| 423 |
< |
// set sign of final eigenvector to ensure that determinant is positive |
| 424 |
< |
if (v.determinant() < 0) { |
| 425 |
< |
v(2, 0) = -v(2, 0); |
| 426 |
< |
v(2, 1) = -v(2, 1); |
| 427 |
< |
v(2, 2) = -v(2, 2); |
| 428 |
< |
} |
| 423 |
> |
// find the vector with the largest x element, make that vector |
| 424 |
> |
// the first vector |
| 425 |
> |
maxVal = fabs(v(0, 0)); |
| 426 |
> |
maxI = 0; |
| 427 |
> |
for (i = 1; i < 3; i++) { |
| 428 |
> |
if (maxVal < (tmp = fabs(v(i, 0)))) { |
| 429 |
> |
maxVal = tmp; |
| 430 |
> |
maxI = i; |
| 431 |
> |
} |
| 432 |
> |
} |
| 433 |
|
|
| 434 |
< |
// transpose the eigenvectors back again |
| 435 |
< |
v = v.transpose(); |
| 436 |
< |
return ; |
| 434 |
> |
// swap eigenvalue and eigenvector |
| 435 |
> |
if (maxI != 0) { |
| 436 |
> |
tmp = w(maxI); |
| 437 |
> |
w(maxI) = w(0); |
| 438 |
> |
w(0) = tmp; |
| 439 |
> |
v.swapRow(maxI, 0); |
| 440 |
> |
} |
| 441 |
> |
// do the same for the y element |
| 442 |
> |
if (fabs(v(1, 1)) < fabs(v(2, 1))) { |
| 443 |
> |
tmp = w(2); |
| 444 |
> |
w(2) = w(1); |
| 445 |
> |
w(1) = tmp; |
| 446 |
> |
v.swapRow(2, 1); |
| 447 |
> |
} |
| 448 |
> |
|
| 449 |
> |
// ensure that the sign of the eigenvectors is correct |
| 450 |
> |
for (i = 0; i < 2; i++) { |
| 451 |
> |
if (v(i, i) < 0) { |
| 452 |
> |
v(i, 0) = -v(i, 0); |
| 453 |
> |
v(i, 1) = -v(i, 1); |
| 454 |
> |
v(i, 2) = -v(i, 2); |
| 455 |
|
} |
| 456 |
< |
}; |
| 456 |
> |
} |
| 457 |
|
|
| 458 |
+ |
// set sign of final eigenvector to ensure that determinant is positive |
| 459 |
+ |
if (v.determinant() < 0) { |
| 460 |
+ |
v(2, 0) = -v(2, 0); |
| 461 |
+ |
v(2, 1) = -v(2, 1); |
| 462 |
+ |
v(2, 2) = -v(2, 2); |
| 463 |
+ |
} |
| 464 |
+ |
|
| 465 |
+ |
// transpose the eigenvectors back again |
| 466 |
+ |
v = v.transpose(); |
| 467 |
+ |
return ; |
| 468 |
+ |
} |
| 469 |
+ |
|
| 470 |
+ |
/** |
| 471 |
+ |
* Return the multiplication of two matrixes (m1 * m2). |
| 472 |
+ |
* @return the multiplication of two matrixes |
| 473 |
+ |
* @param m1 the first matrix |
| 474 |
+ |
* @param m2 the second matrix |
| 475 |
+ |
*/ |
| 476 |
+ |
template<typename Real> |
| 477 |
+ |
inline SquareMatrix3<Real> operator *(const SquareMatrix3<Real>& m1, const SquareMatrix3<Real>& m2) { |
| 478 |
+ |
SquareMatrix3<Real> result; |
| 479 |
+ |
|
| 480 |
+ |
for (unsigned int i = 0; i < 3; i++) |
| 481 |
+ |
for (unsigned int j = 0; j < 3; j++) |
| 482 |
+ |
for (unsigned int k = 0; k < 3; k++) |
| 483 |
+ |
result(i, j) += m1(i, k) * m2(k, j); |
| 484 |
+ |
|
| 485 |
+ |
return result; |
| 486 |
+ |
} |
| 487 |
+ |
|
| 488 |
+ |
template<typename Real> |
| 489 |
+ |
inline SquareMatrix3<Real> outProduct(const Vector3<Real>& v1, const Vector3<Real>& v2) { |
| 490 |
+ |
SquareMatrix3<Real> result; |
| 491 |
+ |
|
| 492 |
+ |
for (unsigned int i = 0; i < 3; i++) { |
| 493 |
+ |
for (unsigned int j = 0; j < 3; j++) { |
| 494 |
+ |
result(i, j) = v1[i] * v2[j]; |
| 495 |
+ |
} |
| 496 |
+ |
} |
| 497 |
+ |
|
| 498 |
+ |
return result; |
| 499 |
+ |
} |
| 500 |
+ |
|
| 501 |
+ |
|
| 502 |
|
typedef SquareMatrix3<double> Mat3x3d; |
| 503 |
|
typedef SquareMatrix3<double> RotMat3x3d; |
| 504 |
|
|
| 505 |
|
} //namespace oopse |
| 506 |
|
#endif // MATH_SQUAREMATRIX_HPP |
| 507 |
+ |
|