symforce
SymPy
symforce | SymPy | |
---|---|---|
15 | 34 | |
1,347 | 12,403 | |
1.0% | 3.2% | |
8.9 | 10.0 | |
11 days ago | 3 days ago | |
C++ | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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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.
symforce
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SymPy: Symbolic Mathematics in Python
You might find this library interesting: https://github.com/symforce-org/symforce
- SymForce is a fast symbolic computation and code generation library for robotics
- Fast Symbolic Computation for Robotics
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Literature request: Lie groups and algebra
Personally I followed along the text implementing things using symforce (https://symforce.org/) instead of Sophus.
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Jacobian Matrix possible on arduino?
It isn't related to Arduino, and may be overkill for this application, but Symforce has some cool tools for implementing the 1st option.
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What optimization libraries are you using?
I've been paying around with Symforce and the more I get into it the more excited I get about it. It lets you prototype in high level symbolic math in Python, then once you get things working it autogenerates super optimized C++ for you. And it has the built in tangent space stuff for factor graphs like GTSAM
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Skydio Researchers Open-Source ‘SymForce’: A Fast Symbolic Computation And Code Generation Library For Robotics Applications Like Computer Vision, etc.
Continue reading | Checkout the paper and github
- Fast symbolic computation, code generation, and nonlinear optimization for robotics
SymPy
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AutoCodeRover resolves 22% of real-world GitHub in SWE-bench lite
Thank you for your interest. There are some interesting examples in the SWE-bench-lite benchmark which are resolved by AutoCodeRover:
- From sympy: https://github.com/sympy/sympy/issues/13643. AutoCodeRover's patch for it: https://github.com/nus-apr/auto-code-rover/blob/main/results...
- Another one from scikit-learn: https://github.com/scikit-learn/scikit-learn/issues/13070. AutoCodeRover's patch (https://github.com/nus-apr/auto-code-rover/blob/main/results...) modified a few lines below (compared to the developer patch) and wrote a different comment.
There are more examples in the results directory (https://github.com/nus-apr/auto-code-rover/tree/main/results).
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SymPy: Symbolic Mathematics in Python
That's interesting. You should consider yourself lucky to have met Wolfram employees, as they are obviously vastly outnumbered by users of Mathematica.
I have not met any developers for either of these products but I know that SymPy has a huge list of contributors for a project of its size. See: https://github.com/sympy/sympy/blob/master/AUTHORS
You may not be hearing about SymPy users because SymPy is not a monolithic product. It is a library. If you know mathematicians big into using Python, they are probably aware of SymPy as it is the main attraction when it comes to symbolic computation in Python.
- Matrix Cookbook examples using SymPy
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Fast Symbolic Computation for Robotics
https://github.com/sympy/sympy/issues/9479 suggests that multivariate inequalities are still unsolved in SymPy, though it looks like https://github.com/sympy/sympy/pull/21687 was merged in August. This probably isn't yet implemented in C++ in SymForce yet?
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Solving a simple puzzle using SymPy
bug report opened https://github.com/sympy/sympy/issues/25507
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Stem Formulas
https://news.ycombinator.com/item?id=36463580
From https://news.ycombinator.com/item?id=36159017 :
> sympy.utilities.lambdify.lambdify() https://github.com/sympy/sympy/blob/a76b02fcd3a8b7f79b3a88df... :
>> """Convert a SymPy expression into a function that allows for fast numeric evaluation [with the CPython math module, mpmath, NumPy, SciPy, CuPy, JAX, TensorFlow, SymPy, numexpr,]*
From https://westurner.github.io/hnlog/#comment-19084622 :
> "latex2sympy parses LaTeX math expressions and converts it into the equivalent SymPy form" and is now merged into SymPy master and callable with sympy.parsing.latex.parse_latex(). It requires antlr-python-runtime to be installed. https://github.com/augustt198/latex2sympy https://github.com/sympy/sympy/pull/13706
ENH: 'generate a Jupyter notebook' (nbformat .ipynb JSON) function from this stem formula
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Vectorization: Introduction
https://en.wikipedia.org/wiki/Vectorization :
> Array programming, a style of computer programming where operations are applied to whole arrays instead of individual elements
> Automatic vectorization, a compiler optimization that transforms loops to vector operations
> Image tracing, the creation of vector from raster graphics
> Word embedding, mapping words to vectors, in natural language processing
> Vectorization (mathematics), a linear transformation which converts a matrix into a column vector
Vector (disambiguation) https://en.wikipedia.org/wiki/Vector
> Vector (mathematics and physics):
> Row and column vectors, single row or column matrices
> Vector space
> Vector field, a vector for each point
And then there are a number of CS usages of the word vector for 1D arrays.
Compute kernel: https://en.m.wikipedia.org/wiki/Compute_kernel
GPGPU > Vectorization, Stream Processing > Compute kernels: https://en.wikipedia.org/wiki/General-purpose_computing_on_g...
sympy.utilities.lambdify.lambdify() https://github.com/sympy/sympy/blob/a76b02fcd3a8b7f79b3a88df... :
> """Convert a SymPy expression into a function that allows for fast numeric evaluation [with the CPython math module, mpmath, NumPy, SciPy, CuPy, JAX, TensorFlow, SymPt, numexpr,]
pyorch lambdify PR, sympytorch: https://github.com/sympy/sympy/pull/20516#issuecomment-78428...
Sympytorch:
> Turn SymPy expressions into PyTorch Modules.
> SymPy floats (optionally) become trainable parameters. SymPy symbols are inputs to the Module.
sympy2jax https://github.com/MilesCranmer/sympy2jax :
> Turn SymPy expressions into parametrized, differentiable, vectorizable, JAX functions.
> All SymPy floats become trainable input parameters. SymPy symbols become columns of a passed matrix.
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Has anyone solved the prime number problem on SPOJ yet using pure python?
Look at sympy.isprime for a carefully-optimized pure-Python solution (though if gmpy2 is installed, which it usually is, it will use that instead after trying the easiest cases)
- What can I contribute to SciPy (or other) with my pure math skill? I’m pen and paper mathematician
- Quantum Monism Could Save the Soul of Physics
What are some alternatives?
casadi - CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
SciPy - SciPy library main repository
CppRobotics - Header-only C++ library for robotics, control, and path planning algorithms. Work in progress, contributions are welcome!
NumPy - The fundamental package for scientific computing with Python.
pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Colosseum - Open source simulator for autonomous robotics built on Unreal Engine with support for Unity
Numba - NumPy aware dynamic Python compiler using LLVM
ANMS-Codes - Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution
NetworkX - Network Analysis in Python
openvslam - OpenVSLAM: A Versatile Visual SLAM Framework
ti84-forth - A Forth implementation for the TI-84+ calculator.