eigen | This is a mirror of the latest stable version of Eigen

 by   libigl C++ Version: Current License: Non-SPDX

kandi X-RAY | eigen Summary

kandi X-RAY | eigen Summary

eigen is a C++ library. eigen has no bugs, it has no vulnerabilities and it has low support. However eigen has a Non-SPDX License. You can download it from GitHub.

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              eigen has a low active ecosystem.
              It has 161 star(s) with 119 fork(s). There are 25 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 1 have been closed. On average issues are closed in 60 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of eigen is current.

            kandi-Quality Quality

              eigen has no bugs reported.

            kandi-Security Security

              eigen has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              eigen has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              eigen releases are not available. You will need to build from source code and install.

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            eigen Key Features

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            eigen Examples and Code Snippets

            No Code Snippets are available at this moment for eigen.

            Community Discussions

            QUESTION

            Read/write Eigen::Matrix with cv::Filestorage
            Asked 2021-Jun-15 at 15:05

            According to the OpenCV Docs, we can use cv::FileStorage to read/write custom data structure from/to config files (XML, YAML, JSON):

            ...

            ANSWER

            Answered 2021-Jun-15 at 15:05

            The issue is due to the intruduction of namespace, indeed you can get a similar issue with this code:

            Source https://stackoverflow.com/questions/67985606

            QUESTION

            Find lowest real value in complex vector
            Asked 2021-Jun-14 at 16:19

            How can I find the smallest positive real number in a complex vector of size N by 1 in Eigen3? For example, in this case I'd like to find the value 3.64038.

            ...

            ANSWER

            Answered 2021-Jun-14 at 14:40

            One option is to create a logical array and then call Eigen::select on it. Inspired by https://forum.kde.org/viewtopic.php?f=74&t=91378

            In this case:

            Source https://stackoverflow.com/questions/67969172

            QUESTION

            Use of std::forward with Eigen::Ref objects
            Asked 2021-Jun-13 at 07:44

            I have a functor Foo defined as follows:

            ...

            ANSWER

            Answered 2021-Jun-13 at 07:44

            QUESTION

            Implementation of Principal Component Analysis from Scratch Orients the Data Differently than scikit-learn
            Asked 2021-Jun-11 at 14:09

            Based on the guide Implementing PCA in Python, by Sebastian Raschka I am building the PCA algorithm from scratch for my research purpose. The class definition is:

            ...

            ANSWER

            Answered 2021-Jun-11 at 12:52

            When calculating an eigenvector you may change its sign and the solution will also be a valid one.

            So any PCA axis can be reversed and the solution will be valid.

            Nevertheless, you may wish to impose a positive correlation of a PCA axis with one of the original variables in the dataset, inverting the axis if needed.

            Source https://stackoverflow.com/questions/67932137

            QUESTION

            Segmentation fault (core dumped) - TFLite
            Asked 2021-Jun-10 at 02:04

            Describe the problem

            To read a model from official TensorFlow source (COCO SSD MobileNet v1) and perform inference with minimal.cc, we get the error below.

            System information

            • Host OS Platform and Distribution : Linux Ubuntu 16.04
            • TensorFlow installed from (source or binary): From source (branch r1.12)
            • Target platform: iMX.6 (Arm v7)

            Please provide the exact sequence of commands/steps when you ran into the problem

            ...

            ANSWER

            Answered 2021-May-24 at 01:57

            Looks like the TensorFlow Lite version is too old to be supported. Please consider using TF 2.5 or beyonds.

            Source https://stackoverflow.com/questions/67623548

            QUESTION

            How to force ctest only run unit tests in some subdirectories?
            Asked 2021-Jun-08 at 06:19

            My cmake project has the following tree structure:

            ...

            ANSWER

            Answered 2021-Jun-08 at 06:19

            The first thing I'd try is ctest's regex selectors. From ctest --help

            Source https://stackoverflow.com/questions/67865677

            QUESTION

            Parameter boundaries using Eigen's Levenberg-Marquardt
            Asked 2021-Jun-04 at 08:42

            I'm using Eigen's Levenberg-Marquardt implementation and wondering how to set some boundaries on the parameters which should be optimized.

            As I'm migrating some GNU octave programs to Eigen I expected that there might be some boundaries which can be easily provided as parameters to the module.

            The layout of my implemenation is nearly the same as in this example. I'm not providing the df() implemenatation but rather use Eigen::NumericalDiff in order to approximate it.

            So how do I enforce some boundaries on the parameters which are supplied to minimize()? I thought about setting the errors(fvec) in the operator() to some high values when leaving my expected ranges, but in some small tests this resulted in strange results.

            ...

            ANSWER

            Answered 2021-Jun-04 at 08:42

            I found a solution which is at least working for me.

            The idea is to increase the error vector once the parameters are leaving their sanity boundaries.

            This can be achieved by the following function:

            Source https://stackoverflow.com/questions/67734419

            QUESTION

            Unable to install arm and lme4 packages from OpenSUSE Leap 15.2
            Asked 2021-Jun-03 at 02:15

            I'm using OpenSUSE Leap 15.2 operating system together with pre-installed R v3.5.0. I did not have to install any package except rstudio.

            Here are installation details:

            ...

            ANSWER

            Answered 2021-May-29 at 13:41

            In my experience, these errors on Unix often stem from missing external libraries. For example, installing the R xml2 package requires libxml2-dev to be installed via the system package manager (i.e. outside R) otherwise installation will fail.

            I can't read French, but it looks to me as though the dependency jpeg failed, due to a missing external jpeg library, and then everything cascaded from there. You could try installing some version of the libjpeg library. I know it comes pre-installed in Ubuntu which may be why that worked for you. I'm a little surprised it doesn't come installed already in OpenSUSE, but I have no experience with OpenSUSE.

            Source https://stackoverflow.com/questions/67407328

            QUESTION

            Eigen 3x3 matrix inverse wrong result
            Asked 2021-May-31 at 06:44
            problem description

            I'm using Eigen for some matrix task. Say I have matrix A whose size is 4x3, then its transpose A^T is 3x4 size, then A^T * A is 3x3 size, thus the inverse, (A^T * A)^(-1), is also 3x3 size.

            I would like to get (A^T * A)^(-1). By using the mentioned formula, and by manually defining A^T * A matrix then do inverse, I got different result for (A^T * A)^(-1) matrix. Curious why this two results mismatch and differs very much.

            Reproduce

            Eigen version: git commit 972cf0c28a8d2ee0808c1277dea2c5c206591ce6

            System: Ubuntu 20.04

            Compiler: Clang++, 10.0.0

            Code:

            ...

            ANSWER

            Answered 2021-May-31 at 06:44

            This is just a matter of numerical accuracy. As pointed out by @Damien in the comment, the matrix is ill-conditioned, and thus a small difference in the input can lead to a large change in the results. By copying from the output only the first five digits and using them to manually define the second matrix, a significant part is discarded that is handled internally but not displayed with the standard accuracy of std::cout.

            Take for instance the entry ATA(0,0). By using is ATA << 1.36154e+13,..., any value of the order of 1.e7 or lower is not considered. This is, however, the order of the other entries in the matrix.

            In short, both results are correct, but your manually defined matrix ATA is not the same as the one that is calculated in the first part. (You can take the difference between the two to verify this).

            Source https://stackoverflow.com/questions/67766965

            QUESTION

            How to declare a tensor with Eigen without specifying the dimension?
            Asked 2021-May-18 at 19:09

            I have a function that takes as input a tensor of dimension n, I have to store this tensor to reuse it later. However, I don't know in advance the dimension of my tensor. I would like to do this:

            ...

            ANSWER

            Answered 2021-May-18 at 19:09

            As the parameter N is a non-type template parameter, it must be a value known at compile time. This means that you cannot really store an Eigen::Tensor with unspecified N in a variable, as each instantiation with a different size is a different type.

            You can work around this by using containers such as std::variant and std::any. They make it possible to store an object of a type from either a closed set of types or any type respectively. As an example, you could use std::any to create a helper tensor_holder class like the following:

            Source https://stackoverflow.com/questions/67591689

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install eigen

            You can download it from GitHub.

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            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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