Our great sponsors
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
spacetimeengine
A Python utility for analyzing a given solution to the Einstein's field equations. Built on Sympy.
-
visualequation
Visualequation creates equations visually. It is powered by LaTeX. Equations can be exported to PNG, EPS, PDF and SVG and you can recover equations for further edition.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
A decade ago when I was interested in General Relativity I wanted to write a simple program to handle symbolic calculations for Einstein field equations (Starting with metric and calculated affine connections, ricci tensor …etc.). Sympy was an option (better because python was the only language I know well) but I found it hard and actually couldn't make it work. I used mathematica which was new for me but did it in a couple of hours. I expanded it later and used it to calculate a lot of things in a black hole paper I published later.
I checked now, and it seems that on this front a lot of development in sympy made it possible that we know how very good libraries built on top of it [1] [2]. There is even now a Jupyter notebook example on schwarzschild metric [3].
[1] https://docs.einsteinpy.org
[2]https://github.com/spacetimeengineer/spacetimeengine
[3] https://github.com/sympy/sympy/blob/master/examples/intermed...
You might find this library interesting: https://github.com/symforce-org/symforce
A decade ago when I was interested in General Relativity I wanted to write a simple program to handle symbolic calculations for Einstein field equations (Starting with metric and calculated affine connections, ricci tensor …etc.). Sympy was an option (better because python was the only language I know well) but I found it hard and actually couldn't make it work. I used mathematica which was new for me but did it in a couple of hours. I expanded it later and used it to calculate a lot of things in a black hole paper I published later.
I checked now, and it seems that on this front a lot of development in sympy made it possible that we know how very good libraries built on top of it [1] [2]. There is even now a Jupyter notebook example on schwarzschild metric [3].
[1] https://docs.einsteinpy.org
[2]https://github.com/spacetimeengineer/spacetimeengine
[3] https://github.com/sympy/sympy/blob/master/examples/intermed...
The JupyterLite Python-compiled-to-WASM build has NumPy, SciPy, matplotlib, and SymPy installed; so you can do computer algebra with SymPy in a browser tab.
https://JupyterLite.rtfd.io/
https://github.com/jupyterlite/jupyterlite/tree/main/py/jupy... :
> Initial support for interactive visualization libraries such as: altair, bqplot, ipywidgets, matplotlib, and plotly
SymPy was instrumental to my PhD implementation, mainly for simplifying math expressions. Nothing was even close at the time
https://github.com/verdverm/pypge