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Q: I'd like to participate. How do I begin?
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As GluCat is a library for C++ calculations in Clifford algebras, it is best to find a good source to familiarize yourself with these algebras. For example, Alan Macdonald's book Linear and Geometric Algebra
http://faculty.luther.edu/~macdonal/laga/Once you have some familiarity with Clifford algebras, download and install GluCat and PyClical, and run the PyClical demos and tutorials. This will familiarize you with the notation.
Then start looking at the Python, Cython and C++ code.
— Paul Leopardi (penguian) · 2 years ago
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Q: Other than writing code, how can I contribute?
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0Internationalization
The current code is entirely written and documented in English. It needs an internationalization framework and translations if it is ever to be available in other languages.
— Paul Leopardi (penguian) · 3 years ago -
0User manual
The code has INSTALL, README and TODO files, as well as Doxygen documentation, programming examples, and Python help and tutorials. One thing that is still missing is a manual written from a user's perspective.
— Paul Leopardi (penguian) · 3 years ago
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Q: What's a good bug for a newcomer to tackle?
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Q: What is a bug or issue with GluCat that you've been putting off, neglecting, or just plain avoiding?
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0Porting the linear algebra to Armadillo
The current linear algebra is implemented using Boost uBLAS, which is slow.
It may take some time for you to understand how GluCat uses uBLAS, but once you do, much of the porting should be straightforward, as long as the new linear algebra library has equivalent support for the uBLAS dense and sparse matrix operations used in GluCat.
— Paul Leopardi (penguian) · 2 years ago
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About GluCat
C++ template library and Python interface for calculations with real universal Clifford algebras.
from the profile of Paul Leopardi (penguian)
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