| 1 | /* | 
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| 2 | * Project: MoleCuilder | 
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| 3 | * Description: creates and alters molecular systems | 
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| 4 | * Copyright (C)  2010-2012 University of Bonn. All rights reserved. | 
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| 5 | * | 
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| 6 | * | 
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| 7 | *   This file is part of MoleCuilder. | 
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| 8 | * | 
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| 9 | *    MoleCuilder is free software: you can redistribute it and/or modify | 
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| 10 | *    it under the terms of the GNU General Public License as published by | 
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| 11 | *    the Free Software Foundation, either version 2 of the License, or | 
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| 12 | *    (at your option) any later version. | 
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| 13 | * | 
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| 14 | *    MoleCuilder is distributed in the hope that it will be useful, | 
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| 15 | *    but WITHOUT ANY WARRANTY; without even the implied warranty of | 
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| 16 | *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the | 
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| 17 | *    GNU General Public License for more details. | 
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| 18 | * | 
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| 19 | *    You should have received a copy of the GNU General Public License | 
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| 20 | *    along with MoleCuilder.  If not, see <http://www.gnu.org/licenses/>. | 
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| 21 | */ | 
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| 22 |  | 
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| 23 | /* | 
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| 24 | * ellipsoid.cpp | 
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| 25 | * | 
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| 26 | *  Created on: Jan 20, 2009 | 
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| 27 | *      Author: heber | 
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| 28 | */ | 
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| 29 |  | 
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| 30 | // include config.h | 
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| 31 | #ifdef HAVE_CONFIG_H | 
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| 32 | #include <config.h> | 
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| 33 | #endif | 
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| 34 |  | 
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| 35 | #include "CodePatterns/MemDebug.hpp" | 
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| 36 |  | 
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| 37 | #include <gsl/gsl_multimin.h> | 
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| 38 | #include <gsl/gsl_vector.h> | 
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| 39 |  | 
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| 40 | #include <iomanip> | 
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| 41 |  | 
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| 42 | #include <set> | 
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| 43 |  | 
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| 44 | #include "CodePatterns/Log.hpp" | 
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| 45 | #include "ellipsoid.hpp" | 
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| 46 | #include "LinearAlgebra/Vector.hpp" | 
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| 47 | #include "LinearAlgebra/RealSpaceMatrix.hpp" | 
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| 48 | #include "LinkedCell/linkedcell.hpp" | 
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| 49 | #include "Tesselation/BoundaryPointSet.hpp" | 
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| 50 | #include "Tesselation/boundary.hpp" | 
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| 51 | #include "Tesselation/tesselation.hpp" | 
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| 52 |  | 
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| 53 | #include "RandomNumbers/RandomNumberGeneratorFactory.hpp" | 
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| 54 | #include "RandomNumbers/RandomNumberGenerator.hpp" | 
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| 55 |  | 
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| 56 | /** Determines squared distance for a given point \a x to surface of ellipsoid. | 
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| 57 | * \param x given point | 
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| 58 | * \param EllipsoidCenter center of ellipsoid | 
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| 59 | * \param EllipsoidLength[3] three lengths of half axis of ellipsoid | 
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| 60 | * \param EllipsoidAngle[3] three rotation angles of ellipsoid | 
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| 61 | * \return squared distance from point to surface | 
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| 62 | */ | 
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| 63 | double SquaredDistanceToEllipsoid(Vector &x, Vector &EllipsoidCenter, double *EllipsoidLength, double *EllipsoidAngle) | 
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| 64 | { | 
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| 65 | Vector helper, RefPoint; | 
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| 66 | double distance = -1.; | 
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| 67 | RealSpaceMatrix Matrix; | 
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| 68 | double InverseLength[3]; | 
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| 69 | double psi,theta,phi; // euler angles in ZX'Z'' convention | 
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| 70 |  | 
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| 71 | //LOG(3, "Begin of SquaredDistanceToEllipsoid"); | 
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| 72 |  | 
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| 73 | for(int i=0;i<3;i++) | 
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| 74 | InverseLength[i] = 1./EllipsoidLength[i]; | 
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| 75 |  | 
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| 76 | // 1. translate coordinate system so that ellipsoid center is in origin | 
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| 77 | RefPoint = helper = x - EllipsoidCenter; | 
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| 78 | //LOG(4, "Translated given point is at " << RefPoint << "."); | 
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| 79 |  | 
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| 80 | // 2. transform coordinate system by inverse of rotation matrix and of diagonal matrix | 
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| 81 | psi = EllipsoidAngle[0]; | 
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| 82 | theta = EllipsoidAngle[1]; | 
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| 83 | phi = EllipsoidAngle[2]; | 
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| 84 | Matrix.set(0,0, cos(psi)*cos(phi) - sin(psi)*cos(theta)*sin(phi)); | 
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| 85 | Matrix.set(1,0, -cos(psi)*sin(phi) - sin(psi)*cos(theta)*cos(phi)); | 
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| 86 | Matrix.set(2,0, sin(psi)*sin(theta)); | 
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| 87 | Matrix.set(0,1, sin(psi)*cos(phi) + cos(psi)*cos(theta)*sin(phi)); | 
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| 88 | Matrix.set(1,1, cos(psi)*cos(theta)*cos(phi) - sin(psi)*sin(phi)); | 
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| 89 | Matrix.set(2,1, -cos(psi)*sin(theta)); | 
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| 90 | Matrix.set(0,2, sin(theta)*sin(phi)); | 
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| 91 | Matrix.set(1,2, sin(theta)*cos(phi)); | 
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| 92 | Matrix.set(2,2, cos(theta)); | 
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| 93 | helper *= Matrix; | 
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| 94 | helper.ScaleAll(InverseLength); | 
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| 95 | //LOG(4, "Transformed RefPoint is at " << helper << "."); | 
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| 96 |  | 
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| 97 | // 3. construct intersection point with unit sphere and ray between origin and x | 
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| 98 | helper.Normalize(); // is simply normalizes vector in distance direction | 
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| 99 | //LOG(4, "Transformed intersection is at " << helper << "."); | 
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| 100 |  | 
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| 101 | // 4. transform back the constructed intersection point | 
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| 102 | psi = -EllipsoidAngle[0]; | 
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| 103 | theta = -EllipsoidAngle[1]; | 
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| 104 | phi = -EllipsoidAngle[2]; | 
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| 105 | helper.ScaleAll(EllipsoidLength); | 
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| 106 | Matrix.set(0,0, cos(psi)*cos(phi) - sin(psi)*cos(theta)*sin(phi)); | 
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| 107 | Matrix.set(1,0, -cos(psi)*sin(phi) - sin(psi)*cos(theta)*cos(phi)); | 
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| 108 | Matrix.set(2,0, sin(psi)*sin(theta)); | 
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| 109 | Matrix.set(0,1, sin(psi)*cos(phi) + cos(psi)*cos(theta)*sin(phi)); | 
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| 110 | Matrix.set(1,1, cos(psi)*cos(theta)*cos(phi) - sin(psi)*sin(phi)); | 
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| 111 | Matrix.set(2,1, -cos(psi)*sin(theta)); | 
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| 112 | Matrix.set(0,2, sin(theta)*sin(phi)); | 
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| 113 | Matrix.set(1,2, sin(theta)*cos(phi)); | 
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| 114 | Matrix.set(2,2, cos(theta)); | 
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| 115 | helper *= Matrix; | 
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| 116 | //LOG(4, "Intersection is at " << helper << "."); | 
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| 117 |  | 
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| 118 | // 5. determine distance between backtransformed point and x | 
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| 119 | distance = RefPoint.DistanceSquared(helper); | 
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| 120 | //LOG(4, "Squared distance between intersection and RefPoint is " << distance << "."); | 
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| 121 |  | 
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| 122 | return distance; | 
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| 123 | //LOG(3, "End of SquaredDistanceToEllipsoid"); | 
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| 124 | }; | 
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| 125 |  | 
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| 126 | /** structure for ellipsoid minimisation containing points to fit to. | 
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| 127 | */ | 
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| 128 | struct EllipsoidMinimisation { | 
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| 129 | int N;      //!< dimension of vector set | 
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| 130 | Vector *x;  //!< array of vectors | 
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| 131 | }; | 
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| 132 |  | 
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| 133 | /** Sum of squared distance to ellipsoid to be minimised. | 
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| 134 | * \param *x parameters for the ellipsoid | 
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| 135 | * \param *params EllipsoidMinimisation with set of data points to minimise distance to and dimension | 
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| 136 | * \return sum of squared distance, \sa SquaredDistanceToEllipsoid() | 
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| 137 | */ | 
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| 138 | double SumSquaredDistance (const gsl_vector * x, void * params) | 
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| 139 | { | 
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| 140 | Vector *set= ((struct EllipsoidMinimisation *)params)->x; | 
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| 141 | int N = ((struct EllipsoidMinimisation *)params)->N; | 
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| 142 | double SumDistance = 0.; | 
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| 143 | double distance; | 
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| 144 | Vector Center; | 
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| 145 | double EllipsoidLength[3], EllipsoidAngle[3]; | 
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| 146 |  | 
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| 147 | // put parameters into suitable ellipsoid form | 
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| 148 | for (int i=0;i<3;i++) { | 
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| 149 | Center[i] = gsl_vector_get(x, i+0); | 
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| 150 | EllipsoidLength[i] = gsl_vector_get(x, i+3); | 
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| 151 | EllipsoidAngle[i] = gsl_vector_get(x, i+6); | 
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| 152 | } | 
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| 153 |  | 
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| 154 | // go through all points and sum distance | 
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| 155 | for (int i=0;i<N;i++) { | 
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| 156 | distance = SquaredDistanceToEllipsoid(set[i], Center, EllipsoidLength, EllipsoidAngle); | 
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| 157 | if (!isnan(distance)) { | 
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| 158 | SumDistance += distance; | 
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| 159 | } else { | 
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| 160 | SumDistance = GSL_NAN; | 
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| 161 | break; | 
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| 162 | } | 
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| 163 | } | 
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| 164 |  | 
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| 165 | //LOG(0, "Current summed distance is " << SumDistance << "."); | 
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| 166 | return SumDistance; | 
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| 167 | }; | 
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| 168 |  | 
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| 169 | /** Finds best fitting ellipsoid parameter set in Least square sense for a given point set. | 
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| 170 | * \param *out output stream for debugging | 
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| 171 | * \param *set given point set | 
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| 172 | * \param N number of points in set | 
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| 173 | * \param EllipsoidParamter[3] three parameters in ellipsoid equation | 
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| 174 | * \return true - fit successful, false - fit impossible | 
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| 175 | */ | 
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| 176 | bool FitPointSetToEllipsoid(Vector *set, int N, Vector *EllipsoidCenter, double *EllipsoidLength, double *EllipsoidAngle) | 
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| 177 | { | 
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| 178 | int status = GSL_SUCCESS; | 
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| 179 | LOG(2, "Begin of FitPointSetToEllipsoid "); | 
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| 180 | if (N >= 3) { // check that enough points are given (9 d.o.f.) | 
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| 181 | struct EllipsoidMinimisation par; | 
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| 182 | const gsl_multimin_fminimizer_type *T = gsl_multimin_fminimizer_nmsimplex; | 
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| 183 | gsl_multimin_fminimizer *s = NULL; | 
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| 184 | gsl_vector *ss, *x; | 
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| 185 | gsl_multimin_function minex_func; | 
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| 186 |  | 
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| 187 | size_t iter = 0; | 
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| 188 | double size; | 
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| 189 |  | 
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| 190 | /* Starting point */ | 
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| 191 | x = gsl_vector_alloc (9); | 
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| 192 | for (int i=0;i<3;i++) { | 
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| 193 | gsl_vector_set (x, i+0, EllipsoidCenter->at(i)); | 
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| 194 | gsl_vector_set (x, i+3, EllipsoidLength[i]); | 
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| 195 | gsl_vector_set (x, i+6, EllipsoidAngle[i]); | 
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| 196 | } | 
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| 197 | par.x = set; | 
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| 198 | par.N = N; | 
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| 199 |  | 
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| 200 | /* Set initial step sizes */ | 
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| 201 | ss = gsl_vector_alloc (9); | 
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| 202 | for (int i=0;i<3;i++) { | 
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| 203 | gsl_vector_set (ss, i+0, 0.1); | 
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| 204 | gsl_vector_set (ss, i+3, 1.0); | 
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| 205 | gsl_vector_set (ss, i+6, M_PI/20.); | 
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| 206 | } | 
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| 207 |  | 
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| 208 | /* Initialize method and iterate */ | 
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| 209 | minex_func.n = 9; | 
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| 210 | minex_func.f = &SumSquaredDistance; | 
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| 211 | minex_func.params = (void *)∥ | 
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| 212 |  | 
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| 213 | s = gsl_multimin_fminimizer_alloc (T, 9); | 
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| 214 | gsl_multimin_fminimizer_set (s, &minex_func, x, ss); | 
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| 215 |  | 
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| 216 | do { | 
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| 217 | iter++; | 
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| 218 | status = gsl_multimin_fminimizer_iterate(s); | 
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| 219 |  | 
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| 220 | if (status) | 
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| 221 | break; | 
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| 222 |  | 
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| 223 | size = gsl_multimin_fminimizer_size (s); | 
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| 224 | status = gsl_multimin_test_size (size, 1e-2); | 
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| 225 |  | 
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| 226 | if (status == GSL_SUCCESS) { | 
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| 227 | for (int i=0;i<3;i++) { | 
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| 228 | EllipsoidCenter->at(i) = gsl_vector_get (s->x,i+0); | 
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| 229 | EllipsoidLength[i] = gsl_vector_get (s->x, i+3); | 
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| 230 | EllipsoidAngle[i] = gsl_vector_get (s->x, i+6); | 
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| 231 | } | 
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| 232 | LOG(4, setprecision(3) << "Converged fit at: " << *EllipsoidCenter << ", lengths " << EllipsoidLength[0] << ", " << EllipsoidLength[1] << ", " << EllipsoidLength[2] << ", angles " << EllipsoidAngle[0] << ", " << EllipsoidAngle[1] << ", " << EllipsoidAngle[2] << " with summed distance " << s->fval << "."); | 
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| 233 | } | 
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| 234 |  | 
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| 235 | } while (status == GSL_CONTINUE && iter < 1000); | 
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| 236 |  | 
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| 237 | gsl_vector_free(x); | 
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| 238 | gsl_vector_free(ss); | 
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| 239 | gsl_multimin_fminimizer_free (s); | 
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| 240 |  | 
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| 241 | } else { | 
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| 242 | LOG(3, "Not enough points provided for fit to ellipsoid."); | 
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| 243 | return false; | 
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| 244 | } | 
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| 245 | LOG(2, "End of FitPointSetToEllipsoid"); | 
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| 246 | if (status == GSL_SUCCESS) | 
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| 247 | return true; | 
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| 248 | else | 
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| 249 | return false; | 
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| 250 | }; | 
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| 251 |  | 
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| 252 | /** Picks a number of random points from a LC neighbourhood as a fitting set. | 
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| 253 | * \param *out output stream for debugging | 
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| 254 | * \param *T Tesselation containing boundary points | 
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| 255 | * \param *LC linked cell list of all atoms | 
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| 256 | * \param *&x random point set on return (not allocated!) | 
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| 257 | * \param PointsToPick number of points in set to pick | 
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| 258 | */ | 
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| 259 | void PickRandomNeighbouredPointSet(class Tesselation *T, class LinkedCell_deprecated *LC, Vector *&x, size_t PointsToPick) | 
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| 260 | { | 
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| 261 | size_t PointsLeft = 0; | 
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| 262 | size_t PointsPicked = 0; | 
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| 263 | int Nlower[NDIM], Nupper[NDIM]; | 
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| 264 | set<int> PickedAtomNrs;   // ordered list of picked atoms | 
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| 265 | set<int>::iterator current; | 
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| 266 | int index; | 
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| 267 | TesselPoint *Candidate = NULL; | 
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| 268 | LOG(2, "Begin of PickRandomPointSet"); | 
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| 269 |  | 
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| 270 | // allocate array | 
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| 271 | if (x == NULL) { | 
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| 272 | x = new Vector[PointsToPick]; | 
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| 273 | } else { | 
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| 274 | ELOG(2, "Given pointer to vector array seems already allocated."); | 
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| 275 | } | 
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| 276 |  | 
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| 277 | RandomNumberGenerator &random = RandomNumberGeneratorFactory::getInstance().makeRandomNumberGenerator("mt19937", "uniform_int"); | 
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| 278 | // check that random number generator's bounds are ok | 
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| 279 | ASSERT(random.min() == 0, | 
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| 280 | "PickRandomNeighbouredPointSet: Chosen RandomNumberGenerator's min " | 
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| 281 | +toString(random.min())+" is not 0!"); | 
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| 282 | ASSERT(random.max() >= LC->N[0], | 
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| 283 | "PickRandomNeighbouredPointSet: Chosen RandomNumberGenerator's max " | 
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| 284 | +toString(random.max())+" is too small"+toString(LC->N[0]) | 
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| 285 | +" for axis 0!"); | 
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| 286 | ASSERT(random.max() >= LC->N[1], | 
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| 287 | "PickRandomNeighbouredPointSet: Chosen RandomNumberGenerator's max " | 
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| 288 | +toString(random.max())+" is too small"+toString(LC->N[1]) | 
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| 289 | +" for axis 1!"); | 
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| 290 | ASSERT(random.max() >= LC->N[2], | 
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| 291 | "PickRandomNeighbouredPointSet: Chosen RandomNumberGenerator's max " | 
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| 292 | +toString(random.max())+" is too small"+toString(LC->N[2]) | 
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| 293 | +" for axis 2!"); | 
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| 294 |  | 
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| 295 | do { | 
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| 296 | for(int i=0;i<NDIM;i++) // pick three random indices | 
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| 297 | LC->n[i] = ((int)random() % LC->N[i]); | 
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| 298 | LOG(2, "INFO: Center cell is " << LC->n[0] << ", " << LC->n[1] << ", " << LC->n[2] << "."); | 
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| 299 | // get random cell | 
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| 300 | const TesselPointSTLList *List = LC->GetCurrentCell(); | 
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| 301 | if (List == NULL) {  // set index to it | 
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| 302 | continue; | 
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| 303 | } | 
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| 304 | LOG(2, "INFO: Cell index is No. " << LC->index << "."); | 
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| 305 |  | 
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| 306 | if (DoLog(2)) { | 
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| 307 | std::stringstream output; | 
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| 308 | output << "LC Intervals:"; | 
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| 309 | for (int i=0;i<NDIM;i++) | 
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| 310 | output << " [" << Nlower[i] << "," << Nupper[i] << "] "; | 
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| 311 | LOG(2, output.str()); | 
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| 312 | } | 
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| 313 |  | 
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| 314 | for (int i=0;i<NDIM;i++) { | 
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| 315 | Nlower[i] = ((LC->n[i]-1) >= 0) ? LC->n[i]-1 : 0; | 
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| 316 | Nupper[i] = ((LC->n[i]+1) < LC->N[i]) ? LC->n[i]+1 : LC->N[i]-1; | 
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| 317 | } | 
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| 318 |  | 
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| 319 | // count whether there are sufficient atoms in this cell+neighbors | 
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| 320 | PointsLeft=0; | 
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| 321 | for (LC->n[0] = Nlower[0]; LC->n[0] <= Nupper[0]; LC->n[0]++) | 
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| 322 | for (LC->n[1] = Nlower[1]; LC->n[1] <= Nupper[1]; LC->n[1]++) | 
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| 323 | for (LC->n[2] = Nlower[2]; LC->n[2] <= Nupper[2]; LC->n[2]++) { | 
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| 324 | const TesselPointSTLList *List = LC->GetCurrentCell(); | 
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| 325 | PointsLeft += List->size(); | 
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| 326 | } | 
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| 327 | LOG(2, "There are " << PointsLeft << " atoms in this neighbourhood."); | 
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| 328 | if (PointsLeft < PointsToPick) {  // ensure that we can pick enough points in its neighbourhood at all. | 
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| 329 | continue; | 
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| 330 | } | 
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| 331 |  | 
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| 332 | // pre-pick a fixed number of atoms | 
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| 333 | PickedAtomNrs.clear(); | 
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| 334 | do { | 
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| 335 | index = (((int)random()) % PointsLeft); | 
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| 336 | current = PickedAtomNrs.find(index);  // not present? | 
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| 337 | if (current == PickedAtomNrs.end()) { | 
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| 338 | //LOG(2, "Picking atom Nr. " << index << "."); | 
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| 339 | PickedAtomNrs.insert(index); | 
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| 340 | } | 
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| 341 | } while (PickedAtomNrs.size() < PointsToPick); | 
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| 342 |  | 
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| 343 | index = 0; // now go through all and pick those whose from PickedAtomsNr | 
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| 344 | PointsPicked=0; | 
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| 345 | current = PickedAtomNrs.begin(); | 
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| 346 | for (LC->n[0] = Nlower[0]; LC->n[0] <= Nupper[0]; LC->n[0]++) | 
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| 347 | for (LC->n[1] = Nlower[1]; LC->n[1] <= Nupper[1]; LC->n[1]++) | 
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| 348 | for (LC->n[2] = Nlower[2]; LC->n[2] <= Nupper[2]; LC->n[2]++) { | 
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| 349 | const TesselPointSTLList *List = LC->GetCurrentCell(); | 
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| 350 | //          LOG(2, "Current cell is " << LC->n[0] << ", " << LC->n[1] << ", " << LC->n[2] << " with No. " << LC->index << " containing " << List->size() << " points."); | 
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| 351 | if (List != NULL) { | 
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| 352 | //            if (List->begin() != List->end()) | 
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| 353 | //              LOG(2, "Going through candidates ... "); | 
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| 354 | //            else | 
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| 355 | //              LOG(2, "Cell is empty ... "); | 
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| 356 | for (TesselPointSTLList::const_iterator Runner = List->begin(); Runner != List->end(); Runner++) { | 
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| 357 | if ((current != PickedAtomNrs.end()) && (*current == index)) { | 
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| 358 | Candidate = (*Runner); | 
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| 359 | LOG(2, "Current picked node is " << (*Runner)->getName() << " with index " << index << "."); | 
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| 360 | x[PointsPicked++] = Candidate->getPosition();    // we have one more atom picked | 
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| 361 | current++;    // next pre-picked atom | 
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| 362 | } | 
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| 363 | index++;  // next atom Nr. | 
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| 364 | } | 
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| 365 | //          } else { | 
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| 366 | //            LOG(2, "List for this index not allocated!"); | 
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| 367 | } | 
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| 368 | } | 
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| 369 | LOG(2, "The following points were picked: "); | 
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| 370 | for (size_t i=0;i<PointsPicked;i++) | 
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| 371 | LOG(2, x[i]); | 
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| 372 | if (PointsPicked == PointsToPick)  // break out of loop if we have all | 
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| 373 | break; | 
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| 374 | } while(1); | 
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| 375 |  | 
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| 376 | LOG(2, "End of PickRandomPointSet"); | 
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| 377 | }; | 
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| 378 |  | 
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| 379 | /** Picks a number of random points from a set of boundary points as a fitting set. | 
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| 380 | * \param *out output stream for debugging | 
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| 381 | * \param *T Tesselation containing boundary points | 
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| 382 | * \param *&x random point set on return (not allocated!) | 
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| 383 | * \param PointsToPick number of points in set to pick | 
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| 384 | */ | 
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| 385 | void PickRandomPointSet(class Tesselation *T, Vector *&x, size_t PointsToPick) | 
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| 386 | { | 
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| 387 | size_t PointsLeft = (size_t) T->PointsOnBoundaryCount; | 
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| 388 | size_t PointsPicked = 0; | 
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| 389 | double value, threshold; | 
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| 390 | PointMap *List = &T->PointsOnBoundary; | 
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| 391 | LOG(2, "Begin of PickRandomPointSet"); | 
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| 392 |  | 
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| 393 | // allocate array | 
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| 394 | if (x == NULL) { | 
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| 395 | x = new Vector[PointsToPick]; | 
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| 396 | } else { | 
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| 397 | ELOG(2, "Given pointer to vector array seems already allocated."); | 
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| 398 | } | 
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| 399 |  | 
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| 400 | RandomNumberGenerator &random = RandomNumberGeneratorFactory::getInstance().makeRandomNumberGenerator("mt19937", "uniform_int"); | 
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| 401 | const double rng_min = random.min(); | 
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| 402 | const double rng_max = random.max(); | 
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| 403 | if (List != NULL) | 
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| 404 | for (PointMap::iterator Runner = List->begin(); Runner != List->end(); Runner++) { | 
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| 405 | threshold = 1. - (double)(PointsToPick - PointsPicked)/(double)PointsLeft; | 
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| 406 | value = (double)random()/(double)(rng_max-rng_min); | 
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| 407 | if (value > threshold) { | 
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| 408 | x[PointsPicked] = (Runner->second->node->getPosition()); | 
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| 409 | PointsPicked++; | 
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| 410 | //LOG(3, "Current node is " << *Runner->second->node << " with " << value << " ... " << threshold << ": IN."); | 
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| 411 | } else { | 
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| 412 | //LOG(3, "Current node is " << *Runner->second->node << " with " << value << " ... " << threshold << ": OUT."); | 
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| 413 | } | 
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| 414 | PointsLeft--; | 
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| 415 | } | 
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| 416 | LOG(2, "The following points were picked: "); | 
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| 417 | for (size_t i=0;i<PointsPicked;i++) | 
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| 418 | LOG(3, x[i]); | 
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| 419 |  | 
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| 420 | LOG(2, "End of PickRandomPointSet"); | 
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| 421 | }; | 
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| 422 |  | 
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| 423 | /** Finds best fitting ellipsoid parameter set in least square sense for a given point set. | 
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| 424 | * \param *out output stream for debugging | 
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| 425 | * \param *T Tesselation containing boundary points | 
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| 426 | * \param *LCList linked cell list of all atoms | 
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| 427 | * \param N number of unique points in ellipsoid fit, must be greater equal 6 | 
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| 428 | * \param number of fits (i.e. parameter sets in output file) | 
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| 429 | * \param *filename name for output file | 
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| 430 | */ | 
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| 431 | void FindDistributionOfEllipsoids(class Tesselation *T, class LinkedCell_deprecated *LCList, int N, int number, const char *filename) | 
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| 432 | { | 
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| 433 | ofstream output; | 
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| 434 | Vector *x = NULL; | 
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| 435 | Vector Center; | 
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| 436 | Vector EllipsoidCenter; | 
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| 437 | double EllipsoidLength[3]; | 
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| 438 | double EllipsoidAngle[3]; | 
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| 439 | double distance, MaxDistance, MinDistance; | 
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| 440 | LOG(0, "Begin of FindDistributionOfEllipsoids"); | 
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| 441 |  | 
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| 442 | // construct center of gravity of boundary point set for initial ellipsoid center | 
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| 443 | Center.Zero(); | 
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| 444 | for (PointMap::iterator Runner = T->PointsOnBoundary.begin(); Runner != T->PointsOnBoundary.end(); Runner++) | 
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| 445 | Center += (Runner->second->node->getPosition()); | 
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| 446 | Center.Scale(1./T->PointsOnBoundaryCount); | 
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| 447 | LOG(4, "DEBUG: Center of PointsOnBoundary is at " << Center << "."); | 
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| 448 |  | 
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| 449 | // Output header | 
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| 450 | output.open(filename, ios::trunc); | 
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| 451 | output << "# Nr.\tCenterX\tCenterY\tCenterZ\ta\tb\tc\tpsi\ttheta\tphi" << endl; | 
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| 452 |  | 
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| 453 | // loop over desired number of parameter sets | 
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| 454 | for (;number >0;number--) { | 
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| 455 | LOG(1, "Determining data set " << number << " ... "); | 
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| 456 | // pick the point set | 
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| 457 | x = NULL; | 
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| 458 | //PickRandomPointSet(T, LCList, x, N); | 
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| 459 | PickRandomNeighbouredPointSet(T, LCList, x, N); | 
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| 460 |  | 
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| 461 | // calculate some sensible starting values for parameter fit | 
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| 462 | MaxDistance = 0.; | 
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| 463 | MinDistance = x[0].ScalarProduct(x[0]); | 
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| 464 | for (int i=0;i<N;i++) { | 
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| 465 | distance = x[i].ScalarProduct(x[i]); | 
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| 466 | if (distance > MaxDistance) | 
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| 467 | MaxDistance = distance; | 
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| 468 | if (distance < MinDistance) | 
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| 469 | MinDistance = distance; | 
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| 470 | } | 
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| 471 | //LOG(2, "MinDistance " << MinDistance << ", MaxDistance " << MaxDistance << "."); | 
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| 472 | EllipsoidCenter = Center;  // use Center of Gravity as initial center of ellipsoid | 
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| 473 | for (int i=0;i<3;i++) | 
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| 474 | EllipsoidAngle[i] = 0.; | 
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| 475 | EllipsoidLength[0] = sqrt(MaxDistance); | 
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| 476 | EllipsoidLength[1] = sqrt((MaxDistance+MinDistance)/2.); | 
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| 477 | EllipsoidLength[2] = sqrt(MinDistance); | 
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| 478 |  | 
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| 479 | // fit the parameters | 
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| 480 | if (FitPointSetToEllipsoid(x, N, &EllipsoidCenter, &EllipsoidLength[0], &EllipsoidAngle[0])) { | 
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| 481 | LOG(1, "Picking succeeded!"); | 
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| 482 | // output obtained parameter set | 
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| 483 | output << number << "\t"; | 
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| 484 | for (int i=0;i<3;i++) | 
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| 485 | output << setprecision(9) << EllipsoidCenter[i] << "\t"; | 
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| 486 | for (int i=0;i<3;i++) | 
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| 487 | output << setprecision(9) << EllipsoidLength[i] << "\t"; | 
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| 488 | for (int i=0;i<3;i++) | 
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| 489 | output << setprecision(9) << EllipsoidAngle[i] << "\t"; | 
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| 490 | output << endl; | 
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| 491 | } else { // increase N to pick one more | 
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| 492 | LOG(1, "Picking failed!"); | 
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| 493 | number++; | 
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| 494 | } | 
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| 495 | delete[](x);  // free allocated memory for point set | 
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| 496 | } | 
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| 497 | // close output and finish | 
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| 498 | output.close(); | 
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| 499 |  | 
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| 500 | LOG(0, "End of FindDistributionOfEllipsoids"); | 
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| 501 | }; | 
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