matrigo
matrix library in go (by fr3fou)
gonum
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more (by gonum)
matrigo | gonum | |
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1 | 24 | |
3 | 7,272 | |
- | 0.6% | |
2.1 | 8.3 | |
7 months ago | 3 days ago | |
Go | Go | |
MIT License | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
matrigo
Posts with mentions or reviews of matrigo.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-23.
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gone - A Neural Network Library Written from Scratch with 0 Dependencies
This library was my introduction to the world of machine learning / neural networks. I built it several months ago when the COVID-19 pandemic started. I had to make my own matrix / linear algebra library that was since used in other projects - fr3fou/matrigo. Since then I've built several projects with gone:
gonum
Posts with mentions or reviews of gonum.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-13.
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How to set up interface to accept multi-dimension array?
But if you want to see what can be done for numeric stuff, check out gonum. Personally, I still wouldn't use Go, and I rather suspect it's still pretty easy to reach for something like what you're trying to do and not find it because Go just can't write that type sensibly, but you can at least see what is available, written by people who disagree with me about Go not being a great language for this.
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packages similar to Pandas
Numpy functionality is largely covered by https://www.gonum.org/ but for pandas I'm not sure if there is an equivalent as widely accepted. However, you might try https://github.com/rocketlaunchr/dataframe-go which I have not tried but it looks like it covers some of what you're looking for
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What libraries are missing?
Math libraries. It's just gonum right now. Missing things that often require people to link C or Python libs. E.g. https://github.com/gonum/gonum/issues/354
- Gonum Numerical Packages
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SIMD Accelerated vector math
Maybe this way you could avoid having Mul, Mul_Inplace, Mul_Into variants. Gonum mostly follows the same pattern.
- Modern hardware is fast, so let's choose the slowest language to balance it out
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graph: A generic Go library for creating graph data structures and performing operations on them. It supports different kinds of graphs such as directed graphs, acyclic graphs, or trees.
How does this compare to gonum graph? https://github.com/gonum/gonum/tree/master/graph
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From Python to NumPy
Go is quite a bit cleaner than Python and its concurrency/parallelism primitives can be well suited to scientific workloads.
You may want to have a look at Gonum (https://www.gonum.org), and the Go HEP package developed by CERN (https://go-hep.org).
I was also surprised to see DSP and pretty sophisticated packages, although I never used them: https://awesome-go.com/science-and-data-analysis
And of course Go has Jupyter integration, it's almost like running a script thanks to its fast compilation time.
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Go for science?
You should check out this https://github.com/gonum/gonum
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What makes concurrency in Go better than multiprocesing/multithreading in Python?
No, using CPU extensions and GPUs is a different thing than doing multitasking. There is Gonum but it is still slower than Numpy: https://github.com/gonum/gonum/issues/511