Open Source C++ Libraries for Linux

Data visualization can help programmers and scientists identify trends in their data and efficiently communicate these results with their peers. Modern C++ is being used for a variety of scientific applications, and this environment can benefit considerably from graphics libraries that attend the typical design goals toward scientific data visualization. Besides the option of exporting results to other environments, the customary alternatives in C++ are either non-dedicated libraries that depend on existing user interfaces or bindings to other languages. Matplot++ is a graphics library for data visualization that provides interactive plotting, means for exporting plots in high-quality formats for scientific publications, a compact syntax consistent with similar libraries, dozens of plot categories with specialized algorithms, multiple coding styles, and supports generic backends.

XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples.

CGAL or the Computational Geometry Algorithms Library is a C++ library that gives you easy access to a myriad of efficient and reliable geometric algorithms. These algorithms are useful in a wide range of applications, including computer aided design, robotics, molecular biology, medical imaging, geographic information systems and more. CGAL features a great range of data structures and algorithms, including Voronoi diagrams, cell complexes and polyhedra, triangulations, arrangements of curves, surface and volume mesh generation, spatial searching, alpha shapes, geometry processing, and many more. The use of these result in beautiful, visually complex and accurate representations.

DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to expand its capabilities, focusing on versatile data extraction, platform support, and seamless integration with various systems. DocWire SDK is dedicated to streamlining data processing, reducing development time and costs, and harnessing the potential of AI. Its advancements promise a superior experience compared to its predecessor, DocToText.

An experimental CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. Since then it has been renamed to Triceps, so please look at the new location https://sourceforge.net/projects/t

IMGH (IMaGe library in C++ Header files) is a simple, light-weight, and cross-platform image processing library, that supports simple editing and drawing, multiple pixel formats (pointers and float). Designed for developers and researchers.

This project is a tool for beginners to understand why a MPI program works or doesn't. It aims simple MPI codes, with a modest number of Processes. It is a real time view of an executing code, providing help even when the program deadlocks.

It's a free-roaming 3D racing game featuring advanced terrain rendering. For small file-size, a 4k x 4k terrain is available, sampled meter-by-meter so it's very smooth. Lightweight program. This is the form in which I wished to do the first release of the terrain rendering Algorithm I have developed throughout almost 2 years. Written in C++, featuring multithreading (2 threads): a total remake of the first 3D game I did years ago, CTruck3D_Simplex and sequels. This works better, thought the basic idea is the seme. Similar to the old games Terep2 and "1nsane". I am an algorithmist, not a game developer: so it was hard for me to put this togather. But I did this tribute to videogames. Have lots of fun! KEYS: mouse: primary camera control arrows: drive vehicle ; SHIFT: turbo ; TAB: change car. o: change camera ; 1,2: zoom-in/out ; 3,4 : horizontal and vertical camera placement (internal view) u: respawn car c,v,f,r :secondary camera control. 8,9:plane drv

The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++ Libraries for 15+ years and deployed it in millions of devices. Create software for connected embedded devices running Linux, Windows Embedded or QNX. Create cross-platform backends in C++ for iOS and Android applications and combine it with a native or HTML5-based user interface. Create software for IoT devices that talk to cloud backends over HTTP REST APIs. See macchina.io for an IoT platform built with POCO.

We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data with large size.

An innovative Open Source CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. You can think of the Complex Event Processing engine as an in-memory database driven by triggers, or a data-flow machine, or a spreadsheet on steroids (and without the GUI part).

Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming. For additional examples, browse our complete API documentation, or check out our more detailed notebooks. cuDF can be installed with conda (miniconda, or the full Anaconda distribution) from the rapidsai channel. cuDF is supported only on Linux, and with Python versions 3.7 and later. The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

IstiChartLib is one of the simplest c++ library for making chart or graph. It is developed using wxWidgets library. For windows, please use IstiChartLib.zip. For Linux (tested on Ubuntu) use IstiChartLib_Linux.tar.gz. For detailed documentation, please visit www.firagiel.com Password to extract: firagiel

Tiny library written in C++/wxWidgets designed to manage mathematical objects : parser of expressions, plots, matrixes and complex numbers. Ansi and Unicode are supported. Documentation and rich samples are provided. Compiles with MSVC, BCC, GCC and Clang. Now on Git.