carma | Armadillo matrices and Numpy arrays using Pybind11 | Data Manipulation library

by RUrlus C++ Version: v0.6.3 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | carma Summary

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

CARMA provides fast bidirectional conversions between Numpy arrays and Armadillo matrices, vectors and cubes, much like RcppArmadillo does for R and Armadillo. The library extends the impressive pybind11 library with support for Armadillo. For details on Pybind11 and Armadillo refer to their respective documentation 1, 2.

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Quality

Security

License

Reuse

Support

carma has a low active ecosystem.

It has 48 star(s) with 15 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 44 have been closed. On average issues are closed in 72 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of carma is v0.6.3

Quality

carma has 0 bugs and 0 code smells.

Security

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

carma code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

carma is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

carma releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 920 lines of code, 121 functions and 12 files.

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

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carma Key Features

No Key Features are available at this moment for carma.

carma Examples and Code Snippets

Example

C++

Lines of Code : 31

License : Permissive (Apache-2.0)

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#include 
#include 
#include 
#include 
#include 

namespace py = pybind11;

py::tuple ols(arma::mat& X, arma::colvec& y) {
    // We borrow the data underlying the numpy arrays
    int n = X.n_rows, k = X.n_cols;

    arma::colvec coeffs =

Installation

C++

Lines of Code : 7

License : Permissive (Apache-2.0)

Copy

mkdir build
cd build
# optionally with -DCMAKE_INSTALL_PREFIX:PATH=
cmake -DCARMA_INSTALL_LIB=ON ..
cmake --build . --config Release --target install

FIND_PACKAGE(carma CONFIG REQUIRED)
TARGET_LINK_LIBRARIES( PRIVATE carma::carma)

Installation,CMake subdirectory

C++

Lines of Code : 4

License : Permissive (Apache-2.0)

Copy

ADD_SUBDIRECTORY(extern/carma)
TARGET_LINK_LIBRARIES( PRIVATE carma::carma)

#include 
#include

Community Discussions

Trending Discussions on carma

Why might I get heap corruption using Armadillo matrices with pybind11?

Error by wrapping c++ class with pybind11 using carma (armadillo matrices and numpy arrays)

QUESTION

Why might I get heap corruption using Armadillo matrices with pybind11?

Asked 2021-Sep-20 at 21:59

I've worked on this for a couple weeks and can't make a reproducible example outside my codebase. That's why I need help! I'm not sure if this is a problem with pybind11 or Armadillo. It's not a problem with Carma since it happens in situations with no conversion going on.

EDIT: This actually does appear to be a bug in Carma and my MRE is working.

I've been trying to boil it down to an MRE and have been unsuccessful. I will explain what I know here, but since this isn't enough to reproduce the bug, what I need most are some ideas as to where to look. This is basically a very hard-to-reproduce memory corruption error (heap corruption, Windows fatal exception: code 0xc0000374). It seems to happen when I have a matrix A, not initialized, and assign a matrix to it large enough that Armadillo acquires memory. The crash happens when that memory is released.

I'm on Windows 10, using Armadillo 10.6.2 and pybind11 v2.7.1, compiling using Clang 11.

...

ANSWER

Answered 2021-Sep-20 at 21:59

Credit to the carma developer, @RUrlus, for the answer:

The problem is due to the bindings module, linked to carma, being linked to a library that hasn't been linked to carma. The external library (mc in the MRE) was allocating memory using the standard malloc while pybind11 was using Carma's free on destruction. The mismatch was causing the crash on Windows.

Perhaps in the future there could be a more elegant solution, but for now the workaround is to link external libraries to carma at compile-time, e.g., target_link_libraries(mc PUBLIC armadillo carma) even if that external library doesn't include or use Carma in any obvious way.

Source https://stackoverflow.com/questions/69226084

QUESTION

Error by wrapping c++ class with pybind11 using carma (armadillo matrices and numpy arrays)

Asked 2020-Sep-26 at 15:00

I have a simple example of trying to use carma and pybind11 to go to and from armadillo matrices and numpy arrays based off of this example. Without the printarma() function, the code works i.e. with just wrapping using pybind11 the code compiles and I can run it in python. The problem here seems to be with carma. Here is the code:

...

ANSWER

Answered 2020-Sep-26 at 15:00

At the end it was two things: the virtual function in the Base class needed to add py::array_t & arr to it and the semicolon at the end at .def needed to be deleted along with the m before .def. This code compiles and works in python:

Source https://stackoverflow.com/questions/64043983

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

Vulnerabilities

No vulnerabilities reported

Install carma

CARMA is a header only library that relies on two other header only libraries, Armadillo and Pybind11. It can be integrated in a CMake build using ADD_SUBDIRECTORY(<path_to_carma>) or installation which provides an interface library target carma::carma that has been linked with Python, Numpy, Pybind11 and Armadillo. See build configuration for details.

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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