SkylineMatrix.h
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00001 // This file is part of Eigen, a lightweight C++ template library
00002 // for linear algebra.
00003 //
00004 // Copyright (C) 2008-2009 Guillaume Saupin <guillaume.saupin@cea.fr>
00005 //
00006 // Eigen is free software; you can redistribute it and/or
00007 // modify it under the terms of the GNU Lesser General Public
00008 // License as published by the Free Software Foundation; either
00009 // version 3 of the License, or (at your option) any later version.
00010 //
00011 // Alternatively, you can redistribute it and/or
00012 // modify it under the terms of the GNU General Public License as
00013 // published by the Free Software Foundation; either version 2 of
00014 // the License, or (at your option) any later version.
00015 //
00016 // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
00017 // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
00018 // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
00019 // GNU General Public License for more details.
00020 //
00021 // You should have received a copy of the GNU Lesser General Public
00022 // License and a copy of the GNU General Public License along with
00023 // Eigen. If not, see <http://www.gnu.org/licenses/>.
00024 
00025 #ifndef EIGEN_SKYLINEMATRIX_H
00026 #define EIGEN_SKYLINEMATRIX_H
00027 
00028 #include "SkylineStorage.h"
00029 #include "SkylineMatrixBase.h"
00030 
00046 namespace internal {
00047 template<typename _Scalar, int _Options>
00048 struct traits<SkylineMatrix<_Scalar, _Options> > {
00049     typedef _Scalar Scalar;
00050     typedef Sparse StorageKind;
00051 
00052     enum {
00053         RowsAtCompileTime = Dynamic,
00054         ColsAtCompileTime = Dynamic,
00055         MaxRowsAtCompileTime = Dynamic,
00056         MaxColsAtCompileTime = Dynamic,
00057         Flags = SkylineBit | _Options,
00058         CoeffReadCost = NumTraits<Scalar>::ReadCost,
00059     };
00060 };
00061 }
00062 
00063 template<typename _Scalar, int _Options>
00064 class SkylineMatrix
00065 : public SkylineMatrixBase<SkylineMatrix<_Scalar, _Options> > {
00066 public:
00067     EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(SkylineMatrix)
00068     EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, +=)
00069     EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(SkylineMatrix, -=)
00070 
00071     using Base::IsRowMajor;
00072 
00073 protected:
00074 
00075     typedef SkylineMatrix<Scalar, (Flags&~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0) > TransposedSkylineMatrix;
00076 
00077     Index m_outerSize;
00078     Index m_innerSize;
00079 
00080 public:
00081     Index* m_colStartIndex;
00082     Index* m_rowStartIndex;
00083     SkylineStorage<Scalar> m_data;
00084 
00085 public:
00086 
00087     inline Index rows() const {
00088         return IsRowMajor ? m_outerSize : m_innerSize;
00089     }
00090 
00091     inline Index cols() const {
00092         return IsRowMajor ? m_innerSize : m_outerSize;
00093     }
00094 
00095     inline Index innerSize() const {
00096         return m_innerSize;
00097     }
00098 
00099     inline Index outerSize() const {
00100         return m_outerSize;
00101     }
00102 
00103     inline Index upperNonZeros() const {
00104         return m_data.upperSize();
00105     }
00106 
00107     inline Index lowerNonZeros() const {
00108         return m_data.lowerSize();
00109     }
00110 
00111     inline Index upperNonZeros(Index j) const {
00112         return m_colStartIndex[j + 1] - m_colStartIndex[j];
00113     }
00114 
00115     inline Index lowerNonZeros(Index j) const {
00116         return m_rowStartIndex[j + 1] - m_rowStartIndex[j];
00117     }
00118 
00119     inline const Scalar* _diagPtr() const {
00120         return &m_data.diag(0);
00121     }
00122 
00123     inline Scalar* _diagPtr() {
00124         return &m_data.diag(0);
00125     }
00126 
00127     inline const Scalar* _upperPtr() const {
00128         return &m_data.upper(0);
00129     }
00130 
00131     inline Scalar* _upperPtr() {
00132         return &m_data.upper(0);
00133     }
00134 
00135     inline const Scalar* _lowerPtr() const {
00136         return &m_data.lower(0);
00137     }
00138 
00139     inline Scalar* _lowerPtr() {
00140         return &m_data.lower(0);
00141     }
00142 
00143     inline const Index* _upperProfilePtr() const {
00144         return &m_data.upperProfile(0);
00145     }
00146 
00147     inline Index* _upperProfilePtr() {
00148         return &m_data.upperProfile(0);
00149     }
00150 
00151     inline const Index* _lowerProfilePtr() const {
00152         return &m_data.lowerProfile(0);
00153     }
00154 
00155     inline Index* _lowerProfilePtr() {
00156         return &m_data.lowerProfile(0);
00157     }
00158 
00159     inline Scalar coeff(Index row, Index col) const {
00160         const Index outer = IsRowMajor ? row : col;
00161         const Index inner = IsRowMajor ? col : row;
00162 
00163         eigen_assert(outer < outerSize());
00164         eigen_assert(inner < innerSize());
00165 
00166         if (outer == inner)
00167             return this->m_data.diag(outer);
00168 
00169         if (IsRowMajor) {
00170             if (inner > outer) //upper matrix
00171             {
00172                 const Index minOuterIndex = inner - m_data.upperProfile(inner);
00173                 if (outer >= minOuterIndex)
00174                     return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
00175                 else
00176                     return Scalar(0);
00177             }
00178             if (inner < outer) //lower matrix
00179             {
00180                 const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00181                 if (inner >= minInnerIndex)
00182                     return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
00183                 else
00184                     return Scalar(0);
00185             }
00186             return m_data.upper(m_colStartIndex[inner] + outer - inner);
00187         } else {
00188             if (outer > inner) //upper matrix
00189             {
00190                 const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00191                 if (outer <= maxOuterIndex)
00192                     return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
00193                 else
00194                     return Scalar(0);
00195             }
00196             if (outer < inner) //lower matrix
00197             {
00198                 const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00199 
00200                 if (inner <= maxInnerIndex)
00201                     return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
00202                 else
00203                     return Scalar(0);
00204             }
00205         }
00206     }
00207 
00208     inline Scalar& coeffRef(Index row, Index col) {
00209         const Index outer = IsRowMajor ? row : col;
00210         const Index inner = IsRowMajor ? col : row;
00211 
00212         eigen_assert(outer < outerSize());
00213         eigen_assert(inner < innerSize());
00214 
00215         if (outer == inner)
00216             return this->m_data.diag(outer);
00217 
00218         if (IsRowMajor) {
00219             if (col > row) //upper matrix
00220             {
00221                 const Index minOuterIndex = inner - m_data.upperProfile(inner);
00222                 eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
00223                 return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
00224             }
00225             if (col < row) //lower matrix
00226             {
00227                 const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00228                 eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
00229                 return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
00230             }
00231         } else {
00232             if (outer > inner) //upper matrix
00233             {
00234                 const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00235                 eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
00236                 return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
00237             }
00238             if (outer < inner) //lower matrix
00239             {
00240                 const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00241                 eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
00242                 return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
00243             }
00244         }
00245     }
00246 
00247     inline Scalar coeffDiag(Index idx) const {
00248         eigen_assert(idx < outerSize());
00249         eigen_assert(idx < innerSize());
00250         return this->m_data.diag(idx);
00251     }
00252 
00253     inline Scalar coeffLower(Index row, Index col) const {
00254         const Index outer = IsRowMajor ? row : col;
00255         const Index inner = IsRowMajor ? col : row;
00256 
00257         eigen_assert(outer < outerSize());
00258         eigen_assert(inner < innerSize());
00259         eigen_assert(inner != outer);
00260 
00261         if (IsRowMajor) {
00262             const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00263             if (inner >= minInnerIndex)
00264                 return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
00265             else
00266                 return Scalar(0);
00267 
00268         } else {
00269             const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00270             if (inner <= maxInnerIndex)
00271                 return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
00272             else
00273                 return Scalar(0);
00274         }
00275     }
00276 
00277     inline Scalar coeffUpper(Index row, Index col) const {
00278         const Index outer = IsRowMajor ? row : col;
00279         const Index inner = IsRowMajor ? col : row;
00280 
00281         eigen_assert(outer < outerSize());
00282         eigen_assert(inner < innerSize());
00283         eigen_assert(inner != outer);
00284 
00285         if (IsRowMajor) {
00286             const Index minOuterIndex = inner - m_data.upperProfile(inner);
00287             if (outer >= minOuterIndex)
00288                 return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
00289             else
00290                 return Scalar(0);
00291         } else {
00292             const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00293             if (outer <= maxOuterIndex)
00294                 return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
00295             else
00296                 return Scalar(0);
00297         }
00298     }
00299 
00300     inline Scalar& coeffRefDiag(Index idx) {
00301         eigen_assert(idx < outerSize());
00302         eigen_assert(idx < innerSize());
00303         return this->m_data.diag(idx);
00304     }
00305 
00306     inline Scalar& coeffRefLower(Index row, Index col) {
00307         const Index outer = IsRowMajor ? row : col;
00308         const Index inner = IsRowMajor ? col : row;
00309 
00310         eigen_assert(outer < outerSize());
00311         eigen_assert(inner < innerSize());
00312         eigen_assert(inner != outer);
00313 
00314         if (IsRowMajor) {
00315             const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00316             eigen_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
00317             return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
00318         } else {
00319             const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00320             eigen_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
00321             return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
00322         }
00323     }
00324 
00325     inline bool coeffExistLower(Index row, Index col) {
00326         const Index outer = IsRowMajor ? row : col;
00327         const Index inner = IsRowMajor ? col : row;
00328 
00329         eigen_assert(outer < outerSize());
00330         eigen_assert(inner < innerSize());
00331         eigen_assert(inner != outer);
00332 
00333         if (IsRowMajor) {
00334             const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00335             return inner >= minInnerIndex;
00336         } else {
00337             const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00338             return inner <= maxInnerIndex;
00339         }
00340     }
00341 
00342     inline Scalar& coeffRefUpper(Index row, Index col) {
00343         const Index outer = IsRowMajor ? row : col;
00344         const Index inner = IsRowMajor ? col : row;
00345 
00346         eigen_assert(outer < outerSize());
00347         eigen_assert(inner < innerSize());
00348         eigen_assert(inner != outer);
00349 
00350         if (IsRowMajor) {
00351             const Index minOuterIndex = inner - m_data.upperProfile(inner);
00352             eigen_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
00353             return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
00354         } else {
00355             const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00356             eigen_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
00357             return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
00358         }
00359     }
00360 
00361     inline bool coeffExistUpper(Index row, Index col) {
00362         const Index outer = IsRowMajor ? row : col;
00363         const Index inner = IsRowMajor ? col : row;
00364 
00365         eigen_assert(outer < outerSize());
00366         eigen_assert(inner < innerSize());
00367         eigen_assert(inner != outer);
00368 
00369         if (IsRowMajor) {
00370             const Index minOuterIndex = inner - m_data.upperProfile(inner);
00371             return outer >= minOuterIndex;
00372         } else {
00373             const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00374             return outer <= maxOuterIndex;
00375         }
00376     }
00377 
00378 
00379 protected:
00380 
00381 public:
00382     class InnerUpperIterator;
00383     class InnerLowerIterator;
00384 
00385     class OuterUpperIterator;
00386     class OuterLowerIterator;
00387 
00389     inline void setZero() {
00390         m_data.clear();
00391         memset(m_colStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
00392         memset(m_rowStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
00393     }
00394 
00396     inline Index nonZeros() const {
00397         return m_data.diagSize() + m_data.upperSize() + m_data.lowerSize();
00398     }
00399 
00401     inline void reserve(Index reserveSize, Index reserveUpperSize, Index reserveLowerSize) {
00402         m_data.reserve(reserveSize, reserveUpperSize, reserveLowerSize);
00403     }
00404 
00413     EIGEN_DONT_INLINE Scalar & insert(Index row, Index col) {
00414         const Index outer = IsRowMajor ? row : col;
00415         const Index inner = IsRowMajor ? col : row;
00416 
00417         eigen_assert(outer < outerSize());
00418         eigen_assert(inner < innerSize());
00419 
00420         if (outer == inner)
00421             return m_data.diag(col);
00422 
00423         if (IsRowMajor) {
00424             if (outer < inner) //upper matrix
00425             {
00426                 Index minOuterIndex = 0;
00427                 minOuterIndex = inner - m_data.upperProfile(inner);
00428 
00429                 if (outer < minOuterIndex) //The value does not yet exist
00430                 {
00431                     const Index previousProfile = m_data.upperProfile(inner);
00432 
00433                     m_data.upperProfile(inner) = inner - outer;
00434 
00435 
00436                     const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
00437                     //shift data stored after this new one
00438                     const Index stop = m_colStartIndex[cols()];
00439                     const Index start = m_colStartIndex[inner];
00440 
00441 
00442                     for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
00443                         m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
00444                     }
00445 
00446                     for (Index innerIdx = cols(); innerIdx > inner; innerIdx--) {
00447                         m_colStartIndex[innerIdx] += bandIncrement;
00448                     }
00449 
00450                     //zeros new data
00451                     memset(this->_upperPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar));
00452 
00453                     return m_data.upper(m_colStartIndex[inner]);
00454                 } else {
00455                     return m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
00456                 }
00457             }
00458 
00459             if (outer > inner) //lower matrix
00460             {
00461                 const Index minInnerIndex = outer - m_data.lowerProfile(outer);
00462                 if (inner < minInnerIndex) //The value does not yet exist
00463                 {
00464                     const Index previousProfile = m_data.lowerProfile(outer);
00465                     m_data.lowerProfile(outer) = outer - inner;
00466 
00467                     const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
00468                     //shift data stored after this new one
00469                     const Index stop = m_rowStartIndex[rows()];
00470                     const Index start = m_rowStartIndex[outer];
00471 
00472 
00473                     for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
00474                         m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
00475                     }
00476 
00477                     for (Index innerIdx = rows(); innerIdx > outer; innerIdx--) {
00478                         m_rowStartIndex[innerIdx] += bandIncrement;
00479                     }
00480 
00481                     //zeros new data
00482                     memset(this->_lowerPtr() + start, 0, (bandIncrement - 1) * sizeof (Scalar));
00483                     return m_data.lower(m_rowStartIndex[outer]);
00484                 } else {
00485                     return m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
00486                 }
00487             }
00488         } else {
00489             if (outer > inner) //upper matrix
00490             {
00491                 const Index maxOuterIndex = inner + m_data.upperProfile(inner);
00492                 if (outer > maxOuterIndex) //The value does not yet exist
00493                 {
00494                     const Index previousProfile = m_data.upperProfile(inner);
00495                     m_data.upperProfile(inner) = outer - inner;
00496 
00497                     const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
00498                     //shift data stored after this new one
00499                     const Index stop = m_rowStartIndex[rows()];
00500                     const Index start = m_rowStartIndex[inner + 1];
00501 
00502                     for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
00503                         m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
00504                     }
00505 
00506                     for (Index innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) {
00507                         m_rowStartIndex[innerIdx] += bandIncrement;
00508                     }
00509                     memset(this->_upperPtr() + m_rowStartIndex[inner] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
00510                     return m_data.upper(m_rowStartIndex[inner] + m_data.upperProfile(inner));
00511                 } else {
00512                     return m_data.upper(m_rowStartIndex[inner] + (outer - inner));
00513                 }
00514             }
00515 
00516             if (outer < inner) //lower matrix
00517             {
00518                 const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
00519                 if (inner > maxInnerIndex) //The value does not yet exist
00520                 {
00521                     const Index previousProfile = m_data.lowerProfile(outer);
00522                     m_data.lowerProfile(outer) = inner - outer;
00523 
00524                     const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
00525                     //shift data stored after this new one
00526                     const Index stop = m_colStartIndex[cols()];
00527                     const Index start = m_colStartIndex[outer + 1];
00528 
00529                     for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
00530                         m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
00531                     }
00532 
00533                     for (Index innerIdx = outer + 1; innerIdx < outerSize() + 1; innerIdx++) {
00534                         m_colStartIndex[innerIdx] += bandIncrement;
00535                     }
00536                     memset(this->_lowerPtr() + m_colStartIndex[outer] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
00537                     return m_data.lower(m_colStartIndex[outer] + m_data.lowerProfile(outer));
00538                 } else {
00539                     return m_data.lower(m_colStartIndex[outer] + (inner - outer));
00540                 }
00541             }
00542         }
00543     }
00544 
00547     inline void finalize() {
00548         if (IsRowMajor) {
00549             if (rows() > cols())
00550                 m_data.resize(cols(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1);
00551             else
00552                 m_data.resize(rows(), cols(), rows(), m_colStartIndex[cols()] + 1, m_rowStartIndex[rows()] + 1);
00553 
00554             //            eigen_assert(rows() == cols() && "memory reorganisatrion only works with suare matrix");
00555             //
00556             //            Scalar* newArray = new Scalar[m_colStartIndex[cols()] + 1 + m_rowStartIndex[rows()] + 1];
00557             //            Index dataIdx = 0;
00558             //            for (Index row = 0; row < rows(); row++) {
00559             //
00560             //                const Index nbLowerElts = m_rowStartIndex[row + 1] - m_rowStartIndex[row];
00561             //                //                std::cout << "nbLowerElts" << nbLowerElts << std::endl;
00562             //                memcpy(newArray + dataIdx, m_data.m_lower + m_rowStartIndex[row], nbLowerElts * sizeof (Scalar));
00563             //                m_rowStartIndex[row] = dataIdx;
00564             //                dataIdx += nbLowerElts;
00565             //
00566             //                const Index nbUpperElts = m_colStartIndex[row + 1] - m_colStartIndex[row];
00567             //                memcpy(newArray + dataIdx, m_data.m_upper + m_colStartIndex[row], nbUpperElts * sizeof (Scalar));
00568             //                m_colStartIndex[row] = dataIdx;
00569             //                dataIdx += nbUpperElts;
00570             //
00571             //
00572             //            }
00573             //            //todo : don't access m_data profile directly : add an accessor from SkylineMatrix
00574             //            m_rowStartIndex[rows()] = m_rowStartIndex[rows()-1] + m_data.lowerProfile(rows()-1);
00575             //            m_colStartIndex[cols()] = m_colStartIndex[cols()-1] + m_data.upperProfile(cols()-1);
00576             //
00577             //            delete[] m_data.m_lower;
00578             //            delete[] m_data.m_upper;
00579             //
00580             //            m_data.m_lower = newArray;
00581             //            m_data.m_upper = newArray;
00582         } else {
00583             if (rows() > cols())
00584                 m_data.resize(cols(), rows(), cols(), m_rowStartIndex[cols()] + 1, m_colStartIndex[cols()] + 1);
00585             else
00586                 m_data.resize(rows(), rows(), cols(), m_rowStartIndex[rows()] + 1, m_colStartIndex[rows()] + 1);
00587         }
00588     }
00589 
00590     inline void squeeze() {
00591         finalize();
00592         m_data.squeeze();
00593     }
00594 
00595     void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar > ()) {
00596         //TODO
00597     }
00598 
00602     void resize(size_t rows, size_t cols) {
00603         const Index diagSize = rows > cols ? cols : rows;
00604         m_innerSize = IsRowMajor ? cols : rows;
00605 
00606         eigen_assert(rows == cols && "Skyline matrix must be square matrix");
00607 
00608         if (diagSize % 2) { // diagSize is odd
00609             const Index k = (diagSize - 1) / 2;
00610 
00611             m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
00612                     2 * k * k + k + 1,
00613                     2 * k * k + k + 1);
00614 
00615         } else // diagSize is even
00616         {
00617             const Index k = diagSize / 2;
00618             m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
00619                     2 * k * k - k + 1,
00620                     2 * k * k - k + 1);
00621         }
00622 
00623         if (m_colStartIndex && m_rowStartIndex) {
00624             delete[] m_colStartIndex;
00625             delete[] m_rowStartIndex;
00626         }
00627         m_colStartIndex = new Index [cols + 1];
00628         m_rowStartIndex = new Index [rows + 1];
00629         m_outerSize = diagSize;
00630 
00631         m_data.reset();
00632         m_data.clear();
00633 
00634         m_outerSize = diagSize;
00635         memset(m_colStartIndex, 0, (cols + 1) * sizeof (Index));
00636         memset(m_rowStartIndex, 0, (rows + 1) * sizeof (Index));
00637     }
00638 
00639     void resizeNonZeros(Index size) {
00640         m_data.resize(size);
00641     }
00642 
00643     inline SkylineMatrix()
00644     : m_outerSize(-1), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
00645         resize(0, 0);
00646     }
00647 
00648     inline SkylineMatrix(size_t rows, size_t cols)
00649     : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
00650         resize(rows, cols);
00651     }
00652 
00653     template<typename OtherDerived>
00654     inline SkylineMatrix(const SkylineMatrixBase<OtherDerived>& other)
00655     : m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
00656         *this = other.derived();
00657     }
00658 
00659     inline SkylineMatrix(const SkylineMatrix & other)
00660     : Base(), m_outerSize(0), m_innerSize(0), m_colStartIndex(0), m_rowStartIndex(0) {
00661         *this = other.derived();
00662     }
00663 
00664     inline void swap(SkylineMatrix & other) {
00665         //EIGEN_DBG_SKYLINE(std::cout << "SkylineMatrix:: swap\n");
00666         std::swap(m_colStartIndex, other.m_colStartIndex);
00667         std::swap(m_rowStartIndex, other.m_rowStartIndex);
00668         std::swap(m_innerSize, other.m_innerSize);
00669         std::swap(m_outerSize, other.m_outerSize);
00670         m_data.swap(other.m_data);
00671     }
00672 
00673     inline SkylineMatrix & operator=(const SkylineMatrix & other) {
00674         std::cout << "SkylineMatrix& operator=(const SkylineMatrix& other)\n";
00675         if (other.isRValue()) {
00676             swap(other.const_cast_derived());
00677         } else {
00678             resize(other.rows(), other.cols());
00679             memcpy(m_colStartIndex, other.m_colStartIndex, (m_outerSize + 1) * sizeof (Index));
00680             memcpy(m_rowStartIndex, other.m_rowStartIndex, (m_outerSize + 1) * sizeof (Index));
00681             m_data = other.m_data;
00682         }
00683         return *this;
00684     }
00685 
00686     template<typename OtherDerived>
00687             inline SkylineMatrix & operator=(const SkylineMatrixBase<OtherDerived>& other) {
00688         const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
00689         if (needToTranspose) {
00690             //         TODO
00691             //            return *this;
00692         } else {
00693             // there is no special optimization
00694             return SkylineMatrixBase<SkylineMatrix>::operator=(other.derived());
00695         }
00696     }
00697 
00698     friend std::ostream & operator <<(std::ostream & s, const SkylineMatrix & m) {
00699 
00700         EIGEN_DBG_SKYLINE(
00701         std::cout << "upper elements : " << std::endl;
00702         for (Index i = 0; i < m.m_data.upperSize(); i++)
00703             std::cout << m.m_data.upper(i) << "\t";
00704         std::cout << std::endl;
00705         std::cout << "upper profile : " << std::endl;
00706         for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
00707             std::cout << m.m_data.upperProfile(i) << "\t";
00708         std::cout << std::endl;
00709         std::cout << "lower startIdx : " << std::endl;
00710         for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
00711             std::cout << (IsRowMajor ? m.m_colStartIndex[i] : m.m_rowStartIndex[i]) << "\t";
00712         std::cout << std::endl;
00713 
00714 
00715         std::cout << "lower elements : " << std::endl;
00716         for (Index i = 0; i < m.m_data.lowerSize(); i++)
00717             std::cout << m.m_data.lower(i) << "\t";
00718         std::cout << std::endl;
00719         std::cout << "lower profile : " << std::endl;
00720         for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
00721             std::cout << m.m_data.lowerProfile(i) << "\t";
00722         std::cout << std::endl;
00723         std::cout << "lower startIdx : " << std::endl;
00724         for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
00725             std::cout << (IsRowMajor ? m.m_rowStartIndex[i] : m.m_colStartIndex[i]) << "\t";
00726         std::cout << std::endl;
00727         );
00728         for (Index rowIdx = 0; rowIdx < m.rows(); rowIdx++) {
00729             for (Index colIdx = 0; colIdx < m.cols(); colIdx++) {
00730                 s << m.coeff(rowIdx, colIdx) << "\t";
00731             }
00732             s << std::endl;
00733         }
00734         return s;
00735     }
00736 
00738     inline ~SkylineMatrix() {
00739         delete[] m_colStartIndex;
00740         delete[] m_rowStartIndex;
00741     }
00742 
00744     Scalar sum() const;
00745 };
00746 
00747 template<typename Scalar, int _Options>
00748 class SkylineMatrix<Scalar, _Options>::InnerUpperIterator {
00749 public:
00750 
00751     InnerUpperIterator(const SkylineMatrix& mat, Index outer)
00752     : m_matrix(mat), m_outer(outer),
00753     m_id(_Options == RowMajor ? mat.m_colStartIndex[outer] : mat.m_rowStartIndex[outer] + 1),
00754     m_start(m_id),
00755     m_end(_Options == RowMajor ? mat.m_colStartIndex[outer + 1] : mat.m_rowStartIndex[outer + 1] + 1) {
00756     }
00757 
00758     inline InnerUpperIterator & operator++() {
00759         m_id++;
00760         return *this;
00761     }
00762 
00763     inline InnerUpperIterator & operator+=(Index shift) {
00764         m_id += shift;
00765         return *this;
00766     }
00767 
00768     inline Scalar value() const {
00769         return m_matrix.m_data.upper(m_id);
00770     }
00771 
00772     inline Scalar* valuePtr() {
00773         return const_cast<Scalar*> (&(m_matrix.m_data.upper(m_id)));
00774     }
00775 
00776     inline Scalar& valueRef() {
00777         return const_cast<Scalar&> (m_matrix.m_data.upper(m_id));
00778     }
00779 
00780     inline Index index() const {
00781         return IsRowMajor ? m_outer - m_matrix.m_data.upperProfile(m_outer) + (m_id - m_start) :
00782                 m_outer + (m_id - m_start) + 1;
00783     }
00784 
00785     inline Index row() const {
00786         return IsRowMajor ? index() : m_outer;
00787     }
00788 
00789     inline Index col() const {
00790         return IsRowMajor ? m_outer : index();
00791     }
00792 
00793     inline size_t size() const {
00794         return m_matrix.m_data.upperProfile(m_outer);
00795     }
00796 
00797     inline operator bool() const {
00798         return (m_id < m_end) && (m_id >= m_start);
00799     }
00800 
00801 protected:
00802     const SkylineMatrix& m_matrix;
00803     const Index m_outer;
00804     Index m_id;
00805     const Index m_start;
00806     const Index m_end;
00807 };
00808 
00809 template<typename Scalar, int _Options>
00810 class SkylineMatrix<Scalar, _Options>::InnerLowerIterator {
00811 public:
00812 
00813     InnerLowerIterator(const SkylineMatrix& mat, Index outer)
00814     : m_matrix(mat),
00815     m_outer(outer),
00816     m_id(_Options == RowMajor ? mat.m_rowStartIndex[outer] : mat.m_colStartIndex[outer] + 1),
00817     m_start(m_id),
00818     m_end(_Options == RowMajor ? mat.m_rowStartIndex[outer + 1] : mat.m_colStartIndex[outer + 1] + 1) {
00819     }
00820 
00821     inline InnerLowerIterator & operator++() {
00822         m_id++;
00823         return *this;
00824     }
00825 
00826     inline InnerLowerIterator & operator+=(Index shift) {
00827         m_id += shift;
00828         return *this;
00829     }
00830 
00831     inline Scalar value() const {
00832         return m_matrix.m_data.lower(m_id);
00833     }
00834 
00835     inline Scalar* valuePtr() {
00836         return const_cast<Scalar*> (&(m_matrix.m_data.lower(m_id)));
00837     }
00838 
00839     inline Scalar& valueRef() {
00840         return const_cast<Scalar&> (m_matrix.m_data.lower(m_id));
00841     }
00842 
00843     inline Index index() const {
00844         return IsRowMajor ? m_outer - m_matrix.m_data.lowerProfile(m_outer) + (m_id - m_start) :
00845                 m_outer + (m_id - m_start) + 1;
00846         ;
00847     }
00848 
00849     inline Index row() const {
00850         return IsRowMajor ? m_outer : index();
00851     }
00852 
00853     inline Index col() const {
00854         return IsRowMajor ? index() : m_outer;
00855     }
00856 
00857     inline size_t size() const {
00858         return m_matrix.m_data.lowerProfile(m_outer);
00859     }
00860 
00861     inline operator bool() const {
00862         return (m_id < m_end) && (m_id >= m_start);
00863     }
00864 
00865 protected:
00866     const SkylineMatrix& m_matrix;
00867     const Index m_outer;
00868     Index m_id;
00869     const Index m_start;
00870     const Index m_end;
00871 };
00872 
00873 #endif // EIGEN_SkylineMatrix_H


libicr
Author(s): Robert Krug
autogenerated on Mon Jan 6 2014 11:33:24