An open source project from Data to AI Lab at MIT.
- License: MIT
- Development Status: Pre-Alpha
- Homepage: https://github.com/sintel-dev/SigPro
SigPro offers an end-to-end solution to efficiently apply multiple signal processing techniques to convert raw time series into feature time series that encode the knowledge of domain experts in order to solve time series machine learning problems.
SigPro has been developed and tested on Python 3.8, 3.9, 3.10, and 3.11 on GNU/Linux and macOS systems.
Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where SigPro is run.
The easiest and recommended way to install SigPro is using pip:
pip install sigpro
This will pull and install the latest stable release from PyPi.
If you want to install from source or contribute to the project please read the Contributing Guide.
SigPro
comes with the following user guides:
- PRIMITIVES.md: Information about the primitive families, their expected input and output.
- USAGE.md: Instructions about how to usee the three main functionalities of
SigPro
. - DEVELOPMENT.md: Step by step guide about how to write a valid
SigPro
primitive and contribute it to eitherSigPro
or your own library.