Fast matching of source-sharing derivative time series.
Project description
Fast optimal matching of items for source-sharing derivative time series.
from ssdts_matching import dynamic_timestamp_match
dynamic_timestamp_match(timestamp1, timestamps2, delta=20)1 Installation
Install ssdts_matching with:
pip install ssdts_matching2 Features
Pure Python.
Compatible with Python 3.5+.
Dependencies: * numpy * SortedContainers
3 Use
You can get a matching of two timestamp series with
from ssdts_matching import dynamic_timestamp_match
dynamic_timestamp_match(timestamp1, timestamps2, delta=20)4 Contributing
Package author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed.
4.1 Installing for development
Clone:
git clone git@github.com:shaypal5/ssdts_matching.gitInstall in development mode with test dependencies:
cd ssdts_matching
pip install -e ".[test]"4.2 Running the tests
To run the tests, use:
python -m pytest --cov=ssdts_matching4.3 Adding documentation
This project is documented using the numpy docstring conventions, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings (in my personal opinion, of course). When documenting code you add to this project, please follow these conventions.
5 Credits
Created by Shay Palachy (shay.palachy@gmail.com).
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