eigency | Cython interface to Eigen library | Data Manipulation library

by wouterboomsma C++ Version: 3.4.0.2 License: MIT

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kandi X-RAY | eigency Summary

eigency is a C++ library typically used in Utilities, Data Manipulation applications. eigency has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Eigency is a Cython interface between Numpy arrays and Matrix/Array objects from the Eigen C++ library. It is intended to simplify the process of writing C++ extensions using the Eigen library. Eigency is designed to reuse the underlying storage of the arrays when passing data back and forth, and will thus avoid making unnecessary copies whenever possible. Only in cases where copies are explicitly requested by your C++ code will they be made.

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Quality

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Support

eigency has a low active ecosystem.

It has 90 star(s) with 23 fork(s). There are 3 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 1 open issues and 23 have been closed. On average issues are closed in 376 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of eigency is 3.4.0.2

Quality

eigency has 0 bugs and 1 code smells.

Security

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

eigency code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

eigency is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

Installation instructions, examples and code snippets are available.

It has 280 lines of code, 37 functions and 5 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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eigency Key Features

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eigency Examples and Code Snippets

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Community Discussions

Trending Discussions on eigency

How to map a list of Numpy matrices to a vector of Eigen matrices in Cython

QUESTION

How to map a list of Numpy matrices to a vector of Eigen matrices in Cython

Asked 2021-Dec-01 at 18:34

I have a C++ function which I want to run from Python. For this I use Cython. My C++ function relies heavily on Eigen matrices which I map to Python's Numpy matrices using Eigency.

I cannot get this to work for the case where I have a list of Numpy matrices.

What does works (mapping a plain Numpy matrix to an Eigen matrix):

I have a C++ function which in the header (Header.h) looks like:

...

ANSWER

Answered 2021-Dec-01 at 18:34

Thanks to @ead I found a solution.

FlattenedMapWithOrder has implementation so it can be assinged to an Eigen::Matrix. However, std::vector does not have such functionality and since std::vector and std::vector are of a different type, they cannot be assigned to one another. More about this here. The implementation in FlattenedMapWithOrder mentioned above is here.

To solve this, the function in the C++ code called from Cython need to simply have as input argument the matching type: std::vector. To do this, the C++ code needs to know the definition of type FlattenedMapWithOrder.

To do this, you need to #include "eigency_cpp.h". Unfortunately, this header is not self contained. Therefore, (credits to @ead) I added these lines:

Source https://stackoverflow.com/questions/69584633

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

Vulnerabilities

No vulnerabilities reported

Install eigency

To import eigency functionality, add the following to your .pyx file:.

Support

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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