A dynamic Python math library containing numerous mathematical functions implemented from scratch.
Project description
AxiomX 0.0.83462: the Gauss Edition
AxiomX is proud to release the 3rd special edition - the Gauss Edition. This edition is specific to the works of Carl Friedrich Gauss. The version number 0.0.83462 represents the Gauss Constant, which is the reciprocal of the Arithmetic-Geometric mean of 1 and √2. Here are some methods we have added and changed:
- agm(a, b) - returns the arithmetic-geometric mean of a and b.
- sqrt(n) - using Halley's method, which is faster that the Newton-Raphson Method.
- gauss_legendre(step) - This calculates the value of π to step steps. 3 returns an accurate value of π.
Note:
We have added a website for our project. Go to https://bit.ly/AxiomX-py to see our project. This library has been licensed under MIT and no one is supposed to copy code from AxiomX. Hope you all enjoy and please patronize.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file axiomx-0.0.83462.tar.gz.
File metadata
- Download URL: axiomx-0.0.83462.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2a4fd0d28ab2b272d82588a975f87197dc8411f26b70330af5fe1aa2225615ea
|
|
| MD5 |
1d5ee2ec0a003cc9197fbcc70b5e7410
|
|
| BLAKE2b-256 |
9c88365400a49fecf8d83880fb3fb14321af5aa5a48a844b2f8d8cab5eb437ef
|
File details
Details for the file axiomx-0.0.83462-py3-none-any.whl.
File metadata
- Download URL: axiomx-0.0.83462-py3-none-any.whl
- Upload date:
- Size: 5.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
87fdd8991e5faf1cd4be251511ea1b90f298bfa9cccd5da60d65bbeb0b9c65bb
|
|
| MD5 |
e83f7059128be9ae073a4ebde82ffa4d
|
|
| BLAKE2b-256 |
49e01114941d6efecc008048abf6801e6da916a01baaa4e7986f36564998b4ab
|