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Fix doxy and misc. typos
Found via `codespell -q 3 -I ../eigen-word-whitelist.txt` --- Eigen/src/Core/ProductEvaluators.h | 4 ++-- Eigen/src/Core/arch/GPU/Half.h | 2 +- Eigen/src/Core/util/Memory.h | 2 +- Eigen/src/Geometry/Hyperplane.h | 2 +- Eigen/src/Geometry/Transform.h | 2 +- Eigen/src/Geometry/Translation.h | 12 ++++++------ doc/PreprocessorDirectives.dox | 2 +- doc/TutorialGeometry.dox | 2 +- test/boostmultiprec.cpp | 2 +- test/triangular.cpp | 2 +- 10 files changed, 16 insertions(+), 16 deletions(-)
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@ -20,7 +20,7 @@ namespace internal {
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/** \internal
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* Evaluator of a product expression.
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* Since products require special treatments to handle all possible cases,
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* we simply deffer the evaluation logic to a product_evaluator class
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* we simply defer the evaluation logic to a product_evaluator class
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* which offers more partial specialization possibilities.
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*
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* \sa class product_evaluator
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@ -128,7 +128,7 @@ protected:
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PlainObject m_result;
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};
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// The following three shortcuts are enabled only if the scalar types match excatly.
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// The following three shortcuts are enabled only if the scalar types match exactly.
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// TODO: we could enable them for different scalar types when the product is not vectorized.
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// Dense = Product
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@ -60,7 +60,7 @@ struct __half_raw {
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#if defined(EIGEN_HAS_OLD_HIP_FP16)
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// Make a __half_raw definition that is
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// ++ compatible with that of Eigen and
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// ++ add a implcit conversion to the native __half of the old HIP implementation.
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// ++ add an implicit conversion to the native __half of the old HIP implementation.
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//
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// Keeping ".x" as "unsigned short" keeps the interface the same between the Eigen and HIP implementation.
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//
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@ -177,7 +177,7 @@ EIGEN_DEVICE_FUNC inline void* aligned_malloc(std::size_t size)
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#endif
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#if EIGEN_DEFAULT_ALIGN_BYTES==16
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eigen_assert((size<16 || (std::size_t(result)%16)==0) && "System's malloc returned an unaligned pointer. Compile with EIGEN_MALLOC_ALREADY_ALIGNED=0 to fallback to handmade alignd memory allocator.");
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eigen_assert((size<16 || (std::size_t(result)%16)==0) && "System's malloc returned an unaligned pointer. Compile with EIGEN_MALLOC_ALREADY_ALIGNED=0 to fallback to handmade aligned memory allocator.");
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#endif
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#else
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result = handmade_aligned_malloc(size);
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@ -119,7 +119,7 @@ public:
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* If the dimension of the ambient space is greater than 2, then there isn't uniqueness,
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* so an arbitrary choice is made.
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*/
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// FIXME to be consitent with the rest this could be implemented as a static Through function ??
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// FIXME to be consistent with the rest this could be implemented as a static Through function ??
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EIGEN_DEVICE_FUNC explicit Hyperplane(const ParametrizedLine<Scalar, AmbientDimAtCompileTime>& parametrized)
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{
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normal() = parametrized.direction().unitOrthogonal();
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@ -115,7 +115,7 @@ template<int Mode> struct transform_make_affine;
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* \end{array} \right) \f$
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*
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* Note that for a projective transformation the last row can be anything,
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* and then the interpretation of different parts might be sightly different.
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* and then the interpretation of different parts might be slightly different.
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*
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* However, unlike a plain matrix, the Transform class provides many features
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* simplifying both its assembly and usage. In particular, it can be composed
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@ -70,18 +70,18 @@ public:
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/** Constructs and initialize the translation transformation from a vector of translation coefficients */
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EIGEN_DEVICE_FUNC explicit inline Translation(const VectorType& vector) : m_coeffs(vector) {}
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/** \brief Retruns the x-translation by value. **/
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/** \brief Returns the x-translation by value. **/
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EIGEN_DEVICE_FUNC inline Scalar x() const { return m_coeffs.x(); }
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/** \brief Retruns the y-translation by value. **/
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/** \brief Returns the y-translation by value. **/
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EIGEN_DEVICE_FUNC inline Scalar y() const { return m_coeffs.y(); }
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/** \brief Retruns the z-translation by value. **/
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/** \brief Returns the z-translation by value. **/
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EIGEN_DEVICE_FUNC inline Scalar z() const { return m_coeffs.z(); }
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/** \brief Retruns the x-translation as a reference. **/
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/** \brief Returns the x-translation as a reference. **/
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EIGEN_DEVICE_FUNC inline Scalar& x() { return m_coeffs.x(); }
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/** \brief Retruns the y-translation as a reference. **/
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/** \brief Returns the y-translation as a reference. **/
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EIGEN_DEVICE_FUNC inline Scalar& y() { return m_coeffs.y(); }
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/** \brief Retruns the z-translation as a reference. **/
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/** \brief Returns the z-translation as a reference. **/
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EIGEN_DEVICE_FUNC inline Scalar& z() { return m_coeffs.z(); }
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EIGEN_DEVICE_FUNC const VectorType& vector() const { return m_coeffs; }
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@ -66,7 +66,7 @@ functions by defining EIGEN_HAS_C99_MATH=1.
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Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
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- \b EIGEN_HAS_CXX11_MATH - controls the implementation of some functions such as round, logp1, isinf, isnan, etc.
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Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
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- \b EIGEN_HAS_RVALUE_REFERENCES - defines whetehr rvalue references are supported
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- \b EIGEN_HAS_RVALUE_REFERENCES - defines whether rvalue references are supported
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Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
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- \b EIGEN_HAS_STD_RESULT_OF - defines whether std::result_of is supported
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Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
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@ -111,7 +111,7 @@ rot3 = rot1.slerp(alpha,rot2);\endcode</td></tr>
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<a href="#" class="top">top</a>\section TutorialGeoTransform Affine transformations
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Generic affine transformations are represented by the Transform class which internaly
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Generic affine transformations are represented by the Transform class which internally
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is a (Dim+1)^2 matrix. In Eigen we have chosen to not distinghish between points and
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vectors such that all points are actually represented by displacement vectors from the
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origin ( \f$ \mathbf{p} \equiv \mathbf{p}-0 \f$ ). With that in mind, real points and
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@ -156,7 +156,7 @@ EIGEN_DECLARE_TEST(boostmultiprec)
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std::cout << "NumTraits<Real>::highest() = " << NumTraits<Real>::highest() << std::endl;
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std::cout << "NumTraits<Real>::digits10() = " << NumTraits<Real>::digits10() << std::endl;
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// chekc stream output
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// check stream output
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{
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Mat A(10,10);
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A.setRandom();
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@ -68,7 +68,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
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while (numext::abs2(m1(i,i))<RealScalar(1e-1)) m1(i,i) = internal::random<Scalar>();
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Transpose<MatrixType> trm4(m4);
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// test back and forward subsitution with a vector as the rhs
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// test back and forward substitution with a vector as the rhs
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m3 = m1.template triangularView<Upper>();
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VERIFY(v2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(v2)), largerEps));
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m3 = m1.template triangularView<Lower>();
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