eigen3

eigen auto type deduction in general product

≡放荡痞女 提交于 2019-11-30 09:22:15
问题 I have the following piece of code (I apologize for the slightly larger code snippet, this is the minimal example I was able to reduce my problem to): #include <Eigen/Dense> #include <complex> #include <iostream> #include <typeinfo> // Dynamic Matrix over Scalar field template <typename Scalar> using DynMat = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>; // Dynamic column vector over Scalar field template <typename Scalar> using DynVect = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>; //

Get matrix views/blocks from a Eigen::VectorXd without copying (shared memory)

会有一股神秘感。 提交于 2019-11-29 22:53:04
问题 Does anyone know a good way how i can extract blocks from an Eigen::VectorXf that can be interpreted as a specific Eigen::MatrixXf without copying data? (the vector should contains several flatten matrices) e.g. something like that (pseudocode): VectorXd W = VectorXd::Zero(8); // Use data from W and create a matrix view from first four elements Block<2,2> A = W.blockFromIndex(0, 2, 2); // Use data from W and create a matrix view from last four elements Block<2,2> B = W.blockFromIndex(4, 2, 2)

eigen auto type deduction in general product

对着背影说爱祢 提交于 2019-11-29 14:49:18
I have the following piece of code (I apologize for the slightly larger code snippet, this is the minimal example I was able to reduce my problem to): #include <Eigen/Dense> #include <complex> #include <iostream> #include <typeinfo> // Dynamic Matrix over Scalar field template <typename Scalar> using DynMat = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>; // Dynamic column vector over Scalar field template <typename Scalar> using DynVect = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>; // Returns the D x D Identity matrix over the field Derived::Scalar // deduced from the expression Eigen:

how to change 2D Eigen::Tensor to Eigen::Matrix

≯℡__Kan透↙ 提交于 2019-11-29 14:42:21
问题 Seems simple enough. I would have thought some kind of casting would be possible, but I can't seem to find any documentation for it. While I have found ways in my application to avoid using the Eigen::Matrix class, TensorFlow only works with Eigen::Tensor, and another library I use only has functionality for working directly with Eigen::Matrix. It would be spectacular for code readability if I could cast a Tensor as a Matrix and work with that. edit: it seems that TensorFlow DOES have a

Using GDB with Eigen C++ library

我的未来我决定 提交于 2019-11-29 12:36:33
问题 I am using the Eigen C++ library downloadable from http://eigen.tuxfamily.org/. This is a C++ library for easier handling of Matrices and Arrays. I use g++ compiler and gdb for debugging. However, I found that I am unable to print the content of a Matrix (provided by Eigen) while using gdb. 回答1: You have to install a gdb extension that you can find in eigen/debug/gdb/. The comment at the beginning of the file explains how to install it. 回答2: One trick you can use is the .data() member, it

cv::Mat conversion to Eigen-Matrix and back

纵饮孤独 提交于 2019-11-29 12:19:28
I have several feature vectors stored in a cv::Mat where, each row is a feature vector (several rows like this one here: [ x1 y1 x2 y2 x3 y3.... ] ). I have to apply SVD on each feature vector and for that I use Eigen library. But, before applying SVD the feature matrix has to be converted to Eigen::Matrix form. Later, I have to convert the SVD result back to cv::Mat . Could anyone please suggest a nice way to do this? The reason I need it in cv::Mat form is because I have to input it to a Neural Network in OpenCV and only cv::Mat inputs matrices are allowed. Thanks!!! Bull An example from

Unable to find Eigen3 with CMake

社会主义新天地 提交于 2019-11-28 13:35:05
I am kind of desperate: For my studies I need to work with Eigen and CMake. I'm able to use Eigen if I copy the whole library in the directories where my compiler looks by default but as soon as I try to find it via find_package(Eigen3 REQUIRED) I get the following error: CMake Error at /usr/share/cmake/Modules/FindPackageHandleStandardArgs.cmake:148 (message): Could NOT find Eigen3 (missing: EIGEN3_INCLUDE_DIR EIGEN3_VERSION_OK) (Required is at least version "2.91.0") Call Stack (most recent call first): /usr/share/cmake/Modules/FindPackageHandleStandardArgs.cmake:388 (_FPHSA_FAILURE_MESSAGE)

Correct usage of the Eigen::Ref<> class

我只是一个虾纸丫 提交于 2019-11-28 06:53:04
Eigen has introduced the Ref<> class to write functions with Eigen objects as parameters without the use unnecessary temporaries, when writing template functions is not wanted. One can read about this here . When searching the internet further, I found several different declarations of parameters using the Ref<> class. In the Eigen documentation they use const Eigen::Ref<const Eigen::MatrixXf>& for a read-only parameter in the first example. In the second example Eigen::Ref<Eigen::MatrixXd> is introduced for read-and-write parameters, BUT here const Eigen::Ref<const Eigen::MatrixXd> is used

Unable to find Eigen3 with CMake

∥☆過路亽.° 提交于 2019-11-27 07:41:55
问题 I am kind of desperate: For my studies I need to work with Eigen and CMake. I'm able to use Eigen if I copy the whole library in the directories where my compiler looks by default but as soon as I try to find it via find_package(Eigen3 REQUIRED) I get the following error: CMake Error at /usr/share/cmake/Modules/FindPackageHandleStandardArgs.cmake:148 (message): Could NOT find Eigen3 (missing: EIGEN3_INCLUDE_DIR EIGEN3_VERSION_OK) (Required is at least version "2.91.0") Call Stack (most recent

Correct usage of the Eigen::Ref<> class

让人想犯罪 __ 提交于 2019-11-27 01:19:21
问题 Eigen has introduced the Ref<> class to write functions with Eigen objects as parameters without the use unnecessary temporaries, when writing template functions is not wanted. One can read about this here. When searching the internet further, I found several different declarations of parameters using the Ref<> class. In the Eigen documentation they use const Eigen::Ref<const Eigen::MatrixXf>& for a read-only parameter in the first example. In the second example Eigen::Ref<Eigen::MatrixXd> is