Mathc
neat-matrix-library
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Mathc | neat-matrix-library | |
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2 | 7 | |
15 | 73 | |
- | - | |
3.4 | 0.0 | |
about 1 year ago | over 1 year ago | |
C | C | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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Mathc
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Lesser known examples of "syntactic sugar" in C?
You can go much further than that. Here is snippet from https://github.com/renehorstmann/Mathc which allows you to access all sub-parts of a vec4 - very neat.
- GLSL like header only math library I made for C. What do you think about it? I am using it at work (3d image proc. & robotics) and for some hobby projects (games, etc.)
neat-matrix-library
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Quick question: Care e faza cu a fi crab?
Cu C mă joc că hobby: * https://github.com/nomemory/neat-matrix-library
- On writing your own linear algebra matrix library in C (follow-up article with explanations after submitting the github library a while back)
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As a hobbyist, I've written my own matrices library in C
I am a math hobbyist, and I wanted to work on my linear algebra knowledge. So I've decided to implement some of the most common algorithms from the CS curricula.
After some work, I've come-up with this small library. It has no production value, but it was fun learning experience.
https://github.com/nomemory/neat-matrix-library
- Proiectele open source la care am lucrat în ultimă perioada
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My first deep-dive into linear algebra and numerical analysis. An article describing how to write a C library that performs most of the "academical" algorithms for matrices (Row Echelon, Reduced Row Echelon, LU(P) Factorization, Inverse, Determinants, etc.)
And the resulting code corresponding to the article can be found here: https://github.com/nomemory/neat-matrix-library
- Got back to C after a few years, and created my first C library: NML is a simple matrix library that implements various numerical analysis algorithms (Gauss Elimination, Gauss-Jordan, Gram-Schmidt, LU(P) Factorisation, etc.)
- One of my C projects: NML - a simple matrix library supporting various (LU Decomposition, Gauss Elimination, Gauss-Jordan, Gram-Schmidt, Inverse, Determinant). Any feedback is greatly appreciated.
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