1*bf2c3715SXin Linamespace Eigen { 2*bf2c3715SXin Li 3*bf2c3715SXin Li/** \eigenManualPage TopicAliasing Aliasing 4*bf2c3715SXin Li 5*bf2c3715SXin LiIn %Eigen, aliasing refers to assignment statement in which the same matrix (or array or vector) appears on the 6*bf2c3715SXin Lileft and on the right of the assignment operators. Statements like <tt>mat = 2 * mat;</tt> or <tt>mat = 7*bf2c3715SXin Limat.transpose();</tt> exhibit aliasing. The aliasing in the first example is harmless, but the aliasing in the 8*bf2c3715SXin Lisecond example leads to unexpected results. This page explains what aliasing is, when it is harmful, and what 9*bf2c3715SXin Lito do about it. 10*bf2c3715SXin Li 11*bf2c3715SXin Li\eigenAutoToc 12*bf2c3715SXin Li 13*bf2c3715SXin Li 14*bf2c3715SXin Li\section TopicAliasingExamples Examples 15*bf2c3715SXin Li 16*bf2c3715SXin LiHere is a simple example exhibiting aliasing: 17*bf2c3715SXin Li 18*bf2c3715SXin Li<table class="example"> 19*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 20*bf2c3715SXin Li<tr><td> 21*bf2c3715SXin Li\include TopicAliasing_block.cpp 22*bf2c3715SXin Li</td> 23*bf2c3715SXin Li<td> 24*bf2c3715SXin Li\verbinclude TopicAliasing_block.out 25*bf2c3715SXin Li</td></tr></table> 26*bf2c3715SXin Li 27*bf2c3715SXin LiThe output is not what one would expect. The problem is the assignment 28*bf2c3715SXin Li\code 29*bf2c3715SXin Limat.bottomRightCorner(2,2) = mat.topLeftCorner(2,2); 30*bf2c3715SXin Li\endcode 31*bf2c3715SXin LiThis assignment exhibits aliasing: the coefficient \c mat(1,1) appears both in the block 32*bf2c3715SXin Li<tt>mat.bottomRightCorner(2,2)</tt> on the left-hand side of the assignment and the block 33*bf2c3715SXin Li<tt>mat.topLeftCorner(2,2)</tt> on the right-hand side. After the assignment, the (2,2) entry in the bottom 34*bf2c3715SXin Liright corner should have the value of \c mat(1,1) before the assignment, which is 5. However, the output shows 35*bf2c3715SXin Lithat \c mat(2,2) is actually 1. The problem is that %Eigen uses lazy evaluation (see 36*bf2c3715SXin Li\ref TopicEigenExpressionTemplates) for <tt>mat.topLeftCorner(2,2)</tt>. The result is similar to 37*bf2c3715SXin Li\code 38*bf2c3715SXin Limat(1,1) = mat(0,0); 39*bf2c3715SXin Limat(1,2) = mat(0,1); 40*bf2c3715SXin Limat(2,1) = mat(1,0); 41*bf2c3715SXin Limat(2,2) = mat(1,1); 42*bf2c3715SXin Li\endcode 43*bf2c3715SXin LiThus, \c mat(2,2) is assigned the \e new value of \c mat(1,1) instead of the old value. The next section 44*bf2c3715SXin Liexplains how to solve this problem by calling \link DenseBase::eval() eval()\endlink. 45*bf2c3715SXin Li 46*bf2c3715SXin LiAliasing occurs more naturally when trying to shrink a matrix. For example, the expressions <tt>vec = 47*bf2c3715SXin Livec.head(n)</tt> and <tt>mat = mat.block(i,j,r,c)</tt> exhibit aliasing. 48*bf2c3715SXin Li 49*bf2c3715SXin LiIn general, aliasing cannot be detected at compile time: if \c mat in the first example were a bit bigger, 50*bf2c3715SXin Lithen the blocks would not overlap, and there would be no aliasing problem. However, %Eigen does detect some 51*bf2c3715SXin Liinstances of aliasing, albeit at run time. The following example exhibiting aliasing was mentioned in \ref 52*bf2c3715SXin LiTutorialMatrixArithmetic : 53*bf2c3715SXin Li 54*bf2c3715SXin Li<table class="example"> 55*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 56*bf2c3715SXin Li<tr><td> 57*bf2c3715SXin Li\include tut_arithmetic_transpose_aliasing.cpp 58*bf2c3715SXin Li</td> 59*bf2c3715SXin Li<td> 60*bf2c3715SXin Li\verbinclude tut_arithmetic_transpose_aliasing.out 61*bf2c3715SXin Li</td></tr></table> 62*bf2c3715SXin Li 63*bf2c3715SXin LiAgain, the output shows the aliasing issue. However, by default %Eigen uses a run-time assertion to detect this 64*bf2c3715SXin Liand exits with a message like 65*bf2c3715SXin Li 66*bf2c3715SXin Li\verbatim 67*bf2c3715SXin Livoid Eigen::DenseBase<Derived>::checkTransposeAliasing(const OtherDerived&) const 68*bf2c3715SXin Li[with OtherDerived = Eigen::Transpose<Eigen::Matrix<int, 2, 2, 0, 2, 2> >, Derived = Eigen::Matrix<int, 2, 2, 0, 2, 2>]: 69*bf2c3715SXin LiAssertion `(!internal::check_transpose_aliasing_selector<Scalar,internal::blas_traits<Derived>::IsTransposed,OtherDerived>::run(internal::extract_data(derived()), other)) 70*bf2c3715SXin Li&& "aliasing detected during transposition, use transposeInPlace() or evaluate the rhs into a temporary using .eval()"' failed. 71*bf2c3715SXin Li\endverbatim 72*bf2c3715SXin Li 73*bf2c3715SXin LiThe user can turn %Eigen's run-time assertions like the one to detect this aliasing problem off by defining the 74*bf2c3715SXin LiEIGEN_NO_DEBUG macro, and the above program was compiled with this macro turned off in order to illustrate the 75*bf2c3715SXin Lialiasing problem. See \ref TopicAssertions for more information about %Eigen's run-time assertions. 76*bf2c3715SXin Li 77*bf2c3715SXin Li 78*bf2c3715SXin Li\section TopicAliasingSolution Resolving aliasing issues 79*bf2c3715SXin Li 80*bf2c3715SXin LiIf you understand the cause of the aliasing issue, then it is obvious what must happen to solve it: %Eigen has 81*bf2c3715SXin Lito evaluate the right-hand side fully into a temporary matrix/array and then assign it to the left-hand 82*bf2c3715SXin Liside. The function \link DenseBase::eval() eval() \endlink does precisely that. 83*bf2c3715SXin Li 84*bf2c3715SXin LiFor example, here is the corrected version of the first example above: 85*bf2c3715SXin Li 86*bf2c3715SXin Li<table class="example"> 87*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 88*bf2c3715SXin Li<tr><td> 89*bf2c3715SXin Li\include TopicAliasing_block_correct.cpp 90*bf2c3715SXin Li</td> 91*bf2c3715SXin Li<td> 92*bf2c3715SXin Li\verbinclude TopicAliasing_block_correct.out 93*bf2c3715SXin Li</td></tr></table> 94*bf2c3715SXin Li 95*bf2c3715SXin LiNow, \c mat(2,2) equals 5 after the assignment, as it should be. 96*bf2c3715SXin Li 97*bf2c3715SXin LiThe same solution also works for the second example, with the transpose: simply replace the line 98*bf2c3715SXin Li<tt>a = a.transpose();</tt> with <tt>a = a.transpose().eval();</tt>. However, in this common case there is a 99*bf2c3715SXin Libetter solution. %Eigen provides the special-purpose function 100*bf2c3715SXin Li\link DenseBase::transposeInPlace() transposeInPlace() \endlink which replaces a matrix by its transpose. 101*bf2c3715SXin LiThis is shown below: 102*bf2c3715SXin Li 103*bf2c3715SXin Li<table class="example"> 104*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 105*bf2c3715SXin Li<tr><td> 106*bf2c3715SXin Li\include tut_arithmetic_transpose_inplace.cpp 107*bf2c3715SXin Li</td> 108*bf2c3715SXin Li<td> 109*bf2c3715SXin Li\verbinclude tut_arithmetic_transpose_inplace.out 110*bf2c3715SXin Li</td></tr></table> 111*bf2c3715SXin Li 112*bf2c3715SXin LiIf an xxxInPlace() function is available, then it is best to use it, because it indicates more clearly what you 113*bf2c3715SXin Liare doing. This may also allow %Eigen to optimize more aggressively. These are some of the xxxInPlace() 114*bf2c3715SXin Lifunctions provided: 115*bf2c3715SXin Li 116*bf2c3715SXin Li<table class="manual"> 117*bf2c3715SXin Li<tr><th>Original function</th><th>In-place function</th></tr> 118*bf2c3715SXin Li<tr> <td> MatrixBase::adjoint() </td> <td> MatrixBase::adjointInPlace() </td> </tr> 119*bf2c3715SXin Li<tr class="alt"> <td> DenseBase::reverse() </td> <td> DenseBase::reverseInPlace() </td> </tr> 120*bf2c3715SXin Li<tr> <td> LDLT::solve() </td> <td> LDLT::solveInPlace() </td> </tr> 121*bf2c3715SXin Li<tr class="alt"> <td> LLT::solve() </td> <td> LLT::solveInPlace() </td> </tr> 122*bf2c3715SXin Li<tr> <td> TriangularView::solve() </td> <td> TriangularView::solveInPlace() </td> </tr> 123*bf2c3715SXin Li<tr class="alt"> <td> DenseBase::transpose() </td> <td> DenseBase::transposeInPlace() </td> </tr> 124*bf2c3715SXin Li</table> 125*bf2c3715SXin Li 126*bf2c3715SXin LiIn the special case where a matrix or vector is shrunk using an expression like <tt>vec = vec.head(n)</tt>, 127*bf2c3715SXin Liyou can use \link PlainObjectBase::conservativeResize() conservativeResize() \endlink. 128*bf2c3715SXin Li 129*bf2c3715SXin Li 130*bf2c3715SXin Li\section TopicAliasingCwise Aliasing and component-wise operations 131*bf2c3715SXin Li 132*bf2c3715SXin LiAs explained above, it may be dangerous if the same matrix or array occurs on both the left-hand side and the 133*bf2c3715SXin Liright-hand side of an assignment operator, and it is then often necessary to evaluate the right-hand side 134*bf2c3715SXin Liexplicitly. However, applying component-wise operations (such as matrix addition, scalar multiplication and 135*bf2c3715SXin Liarray multiplication) is safe. 136*bf2c3715SXin Li 137*bf2c3715SXin LiThe following example has only component-wise operations. Thus, there is no need for \link DenseBase::eval() 138*bf2c3715SXin Lieval() \endlink even though the same matrix appears on both sides of the assignments. 139*bf2c3715SXin Li 140*bf2c3715SXin Li<table class="example"> 141*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 142*bf2c3715SXin Li<tr><td> 143*bf2c3715SXin Li\include TopicAliasing_cwise.cpp 144*bf2c3715SXin Li</td> 145*bf2c3715SXin Li<td> 146*bf2c3715SXin Li\verbinclude TopicAliasing_cwise.out 147*bf2c3715SXin Li</td></tr></table> 148*bf2c3715SXin Li 149*bf2c3715SXin LiIn general, an assignment is safe if the (i,j) entry of the expression on the right-hand side depends only on 150*bf2c3715SXin Lithe (i,j) entry of the matrix or array on the left-hand side and not on any other entries. In that case it is 151*bf2c3715SXin Linot necessary to evaluate the right-hand side explicitly. 152*bf2c3715SXin Li 153*bf2c3715SXin Li 154*bf2c3715SXin Li\section TopicAliasingMatrixMult Aliasing and matrix multiplication 155*bf2c3715SXin Li 156*bf2c3715SXin LiMatrix multiplication is the only operation in %Eigen that assumes aliasing by default, <strong>under the 157*bf2c3715SXin Licondition that the destination matrix is not resized</strong>. 158*bf2c3715SXin LiThus, if \c matA is a \b squared matrix, then the statement <tt>matA = matA * matA;</tt> is safe. 159*bf2c3715SXin LiAll other operations in %Eigen assume that there are no aliasing problems, 160*bf2c3715SXin Lieither because the result is assigned to a different matrix or because it is a component-wise operation. 161*bf2c3715SXin Li 162*bf2c3715SXin Li<table class="example"> 163*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 164*bf2c3715SXin Li<tr><td> 165*bf2c3715SXin Li\include TopicAliasing_mult1.cpp 166*bf2c3715SXin Li</td> 167*bf2c3715SXin Li<td> 168*bf2c3715SXin Li\verbinclude TopicAliasing_mult1.out 169*bf2c3715SXin Li</td></tr></table> 170*bf2c3715SXin Li 171*bf2c3715SXin LiHowever, this comes at a price. When executing the expression <tt>matA = matA * matA</tt>, %Eigen evaluates the 172*bf2c3715SXin Liproduct in a temporary matrix which is assigned to \c matA after the computation. This is fine. But %Eigen does 173*bf2c3715SXin Lithe same when the product is assigned to a different matrix (e.g., <tt>matB = matA * matA</tt>). In that case, 174*bf2c3715SXin Liit is more efficient to evaluate the product directly into \c matB instead of evaluating it first into a 175*bf2c3715SXin Litemporary matrix and copying that matrix to \c matB. 176*bf2c3715SXin Li 177*bf2c3715SXin LiThe user can indicate with the \link MatrixBase::noalias() noalias()\endlink function that there is no 178*bf2c3715SXin Lialiasing, as follows: <tt>matB.noalias() = matA * matA</tt>. This allows %Eigen to evaluate the matrix product 179*bf2c3715SXin Li<tt>matA * matA</tt> directly into \c matB. 180*bf2c3715SXin Li 181*bf2c3715SXin Li<table class="example"> 182*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 183*bf2c3715SXin Li<tr><td> 184*bf2c3715SXin Li\include TopicAliasing_mult2.cpp 185*bf2c3715SXin Li</td> 186*bf2c3715SXin Li<td> 187*bf2c3715SXin Li\verbinclude TopicAliasing_mult2.out 188*bf2c3715SXin Li</td></tr></table> 189*bf2c3715SXin Li 190*bf2c3715SXin LiOf course, you should not use \c noalias() when there is in fact aliasing taking place. If you do, then you 191*bf2c3715SXin Limay get wrong results: 192*bf2c3715SXin Li 193*bf2c3715SXin Li<table class="example"> 194*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 195*bf2c3715SXin Li<tr><td> 196*bf2c3715SXin Li\include TopicAliasing_mult3.cpp 197*bf2c3715SXin Li</td> 198*bf2c3715SXin Li<td> 199*bf2c3715SXin Li\verbinclude TopicAliasing_mult3.out 200*bf2c3715SXin Li</td></tr></table> 201*bf2c3715SXin Li 202*bf2c3715SXin LiMoreover, starting in Eigen 3.3, aliasing is \b not assumed if the destination matrix is resized and the product is not directly assigned to the destination. 203*bf2c3715SXin LiTherefore, the following example is also wrong: 204*bf2c3715SXin Li 205*bf2c3715SXin Li<table class="example"> 206*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 207*bf2c3715SXin Li<tr><td> 208*bf2c3715SXin Li\include TopicAliasing_mult4.cpp 209*bf2c3715SXin Li</td> 210*bf2c3715SXin Li<td> 211*bf2c3715SXin Li\verbinclude TopicAliasing_mult4.out 212*bf2c3715SXin Li</td></tr></table> 213*bf2c3715SXin Li 214*bf2c3715SXin LiAs for any aliasing issue, you can resolve it by explicitly evaluating the expression prior to assignment: 215*bf2c3715SXin Li<table class="example"> 216*bf2c3715SXin Li<tr><th>Example</th><th>Output</th></tr> 217*bf2c3715SXin Li<tr><td> 218*bf2c3715SXin Li\include TopicAliasing_mult5.cpp 219*bf2c3715SXin Li</td> 220*bf2c3715SXin Li<td> 221*bf2c3715SXin Li\verbinclude TopicAliasing_mult5.out 222*bf2c3715SXin Li</td></tr></table> 223*bf2c3715SXin Li 224*bf2c3715SXin Li\section TopicAliasingSummary Summary 225*bf2c3715SXin Li 226*bf2c3715SXin LiAliasing occurs when the same matrix or array coefficients appear both on the left- and the right-hand side of 227*bf2c3715SXin Lian assignment operator. 228*bf2c3715SXin Li - Aliasing is harmless with coefficient-wise computations; this includes scalar multiplication and matrix or 229*bf2c3715SXin Li array addition. 230*bf2c3715SXin Li - When you multiply two matrices, %Eigen assumes that aliasing occurs. If you know that there is no aliasing, 231*bf2c3715SXin Li then you can use \link MatrixBase::noalias() noalias()\endlink. 232*bf2c3715SXin Li - In all other situations, %Eigen assumes that there is no aliasing issue and thus gives the wrong result if 233*bf2c3715SXin Li aliasing does in fact occur. To prevent this, you have to use \link DenseBase::eval() eval() \endlink or 234*bf2c3715SXin Li one of the xxxInPlace() functions. 235*bf2c3715SXin Li 236*bf2c3715SXin Li*/ 237*bf2c3715SXin Li} 238