Search Results for "git for windows"
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Showing 9 open source projects for "git for windows"
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git-stats
Local git statistics including GitHub-like contributions calendars
git-stats is a Node.js command-line tool and library for tracking Git activity locally. It renders commit history as an ANSI contribution calendar similar to the graph displayed on GitHub profiles. Users can select custom date ranges, display global activity, filter commits by author, and compare additions with deletions. Author statistics can also be presented as terminal pie charts. Commit records are stored in a configurable local data file, with a JavaScript configuration file... -
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GIT quick statistics
An efficient way to access various statistics in git repository
git-quick-stats is a simple and efficient way to access various statistics in a git repository. Any git repository may contain tons of information about commits, contributors, and files. Extracting this information is not always trivial, mostly because there are a gadzillion options to a gadzillion git commands. For those who prefer to utilize command-line options, git-quick-stats also has a non-interactive mode supporting both short and long options. You can change to the legacy color... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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wxEcMath
Easy mathematics in wxWidgets
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. -
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CPPQUADPACK
C++ port of QUADPACK with general function defination style.
Numerical integration package in C++. A C++ port of QUADPACK with a general function defination style to provide more flexible function parameter defination. Based on crbond C version QUADPACK(http://www.crbond.com/scientific.htm) . You can get the latest code by : git clone git://git.code.sf.net/p/cppquadpack/code cppquadpack-code -
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The Systems Biology Ontology project (SBO) goal is to develop controlled vocabularies and ontologies tailored specifically for the kinds of problems being faced in Systems Biology, especially in the context of computational modeling. !!!! Important Announcement !!!! We have moved the curation and development of Systems Biology Ontology (SBO) to a git-hub repository https://github.com/EBI-BioModels/SBO. Hence, this SourceForge SBO project has also been retired. Please use the Git-Hub...
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OptLib
C nonlinear optimization library
[PROJECT MIGRATED TO GIT-HUB] OptLib is a library of nonlinear optimization routines focused on the use of stochastic methods, including Simulated Annealing, Genetic Algorithms, and Monte Carlo. Routines are parallelized using MPI. -
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