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Add additional resources for scientific computing #92

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11 changes: 11 additions & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,7 @@ them.
(C++, BSD, [GitHub](https://github.com/ginkgo-project/ginkgo))
- [blaze](https://bitbucket.org/blaze-lib/blaze) - High-performance C++ math library for dense and sparse arithmetic.
(C++, BSD, Bitbucket)
- [Armadillo](https://arma.sourceforge.net/) - A C++ linear algebra library with a syntax similar to MATLAB. (C++, MPL 2, [GitHub](https://github.com/conradsnicta/armadillo-code))

## Multi-purpose toolkits

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- [NumPy](https://numpy.org/) - Fundamental package needed for scientific computing with Python.
(Python, BSD, [GitHub](https://github.com/numpy/numpy))
- [DifferentialEquations.jl](https://diffeq.sciml.ai/) - Toolbox for solving different types of differential equations numerically. (Julia, MIT, [GitHub](https://github.com/SciML/DifferentialEquations.jl))
- [TensorFlow](https://www.tensorflow.org/) - A framework for building machine learning models, often used in scientific computing. (Python, Apache 2.0, [GitHub](https://github.com/tensorflow/tensorflow))
- [PyTorch](https://pytorch.org/) - An open-source machine learning library based on the Torch library. (Python, BSD, [GitHub](https://github.com/pytorch/pytorch))
- [Dask](https://www.dask.org/) - A parallel computing library that integrates with NumPy, Pandas, and Scikit-learn. (Python, BSD, [GitHub](https://github.com/dask/dask))

## Finite Elements

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(C++, [GitLab](https://gitlab.kitware.com/xdmf/xdmf))
- [Zarr](https://zarr.readthedocs.io/en/stable/) - Format for the storage of chunked, compressed, N-dimensional arrays.
(Python, MIT, [GitHub](https://github.com/zarr-developers/zarr-python))
- [Parquet](https://parquet.apache.org/) - A columnar storage file format optimized for use with big data processing frameworks. (C++, Apache License 2.0, [GitHub](https://github.com/apache/parquet-cpp))
- [Feather](https://arrow.apache.org/docs/python/feather.html) - A binary columnar data format that can be read and written by both Python and R. (C++, Apache License 2.0, [GitHub](https://github.com/wesm/feather))

## Sparse linear solvers

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(Python, MIT, [GitHub](https://github.com/pyamg/pyamg))
- [hypre](https://computing.llnl.gov/projects/hypre-scalable-linear-solvers-multigrid-methods) - Library of high-performance preconditioners and solvers.
(C, Apache 2.0/MIT, [GitHub](https://github.com/hypre-space/hypre))
- [Cholmod](https://developer.nvidia.com/cholmod) - Sparse Cholesky factorization. (C, GPL, [GitHub](https://github.com/DrTimothyAldenDavis/SuiteSparse))

## Visualization

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- [TTK](https://topology-tool-kit.github.io/) - Topological data analysis and visualization.
(C++/Python, BSD, [GitHub](https://github.com/topology-tool-kit/ttk))
- [morphologica](https://github.com/ABRG-Models/morphologica) - Header-only, modern OpenGL code to visualize numerical simulations at runtime. (C++, Apache 2.0, GitHub)
- [Matplotlib](https://matplotlib.org/) - Comprehensive library for creating static, animated, and interactive visualizations in Python. (Python, PSF License, [GitHub](https://github.com/matplotlib/matplotlib))
- [Seaborn](https://seaborn.pydata.org/) - Statistical data visualization library based on Matplotlib. (Python, MIT, [GitHub](https://github.com/mwaskom/seaborn))

## Other libraries and tools

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(Python, MIT, GitHub)
- [HPDDM](https://github.com/hpddm/hpddm) - High-performance unified framework for domain decomposition methods.
(C++, LGPL 3, GitHub)
- [OpenCV](https://opencv.org/): Open Source Computer Vision Library for real-time computer vision. (C++, Apache 2.0, [GitHub](https://github.com/opencv/opencv))
- [Dlib](http://dlib.net/): A toolkit for making real-world machine learning and data analysis applications in C++. (C++, Boost Software License, [GitHub](https://github.com/davisking/dlib))

## Community

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