Metadata-Version: 2.1
Name: ancb
Version: 0.1.2
Summary: Fast, efficient, and powerful NumPy compatible circular buffers.
Home-page: https://github.com/EmDash00/ANCB
License: Apache-2.0
Author: Ember Chow
Author-email: emberchow.business@gmail.com
Requires-Python: >=3.6,<4.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: numpy (>=1.16.4,<2.0.0) ; python_version >= "3.6"
Requires-Dist: numpy (>=1.20.0,<2.0.0) ; python_version >= "3.8" and python_version < "3.12"
Requires-Dist: numpy (>=1.26.0,<2.0.0) ; python_version >= "3.12" and python_version < "3.13"
Project-URL: Documentation, https://ancb-docs.readthedocs.io/en/latest/
Project-URL: Repository, https://github.com/EmDash00/ANCB
Description-Content-Type: text/markdown

# Another NumPy Circular Buffer

[![Build Status](https://travis-ci.com/EmDash00/ANCB.svg?branch=master)](https://travis-ci.com/EmDash00/ANCB)

Another NumPy Circular Buffer (or ANCB for short) is an attempt to make a circular buffer work with NumPy ufuncs for
real-time data processing. One can think of a NumpyCircularbuffer in ANCB as being a fixed length deque with random access
functionality (unlike the deque). For users more familar with NumPy, one can think of this buffer as a way of automatically
rolling the array into the right order.

ANCB was developed by Drason "Emmy" Chow during their time as an undergraduate researcher at IU: Bloomington for use in 
making [Savitzky-Golay filters](https://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_filter), which take an array of positions in chronological or reverse-chronological order and produce
estimates of velocity, acceleration, and possibly higher order derivatives if desired.

Looking for the documentation? You can find it here:  
https://ancb-docs.readthedocs.io/en/latest/