Package: sigpro
An open source project from Data to AI Lab at MIT.SigPro: Signal Processing Tools for Machine LearningLicense:MITDevelopment Status:Pre-AlphaHomepage:https://github.com/sintel-dev/SigProOverviewSigPro offers an end-to-end solution to efficiently apply multiplesignal processing techniquesto convertraw time seriesintofeature time seriesthat encode the knowledge of domain experts
in order to solve time series machine learning problems.InstallRequirementsSigProhas been developed and tested onPython 3.8, 3.9, 3.10, and 3.11on GNU/Linux and macOS systems.Also, although it is not strictly required, the usage of avirtualenvis highly recommended in order to avoid
interfering with other software installed in the system whereSigProis run.Install with pipThe easiest and recommended way to installSigProis usingpip:pipinstallsigproThis will pull and install the latest stable release fromPyPi.If you want to install from source or contribute to the project please read theContributing Guide.User GuidesSigProcomes 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 ofSigPro.DEVELOPMENT.md: Step by step guide about how to write a validSigProprimitive and contribute it to eitherSigProor your own library.History0.2.0 - 2023-02-02FeaturesDemo Notebooks for Pipeline usage  -Issue #55by @andyx13Addedcontributing_primitiveandbasic_primitivesmodule to assist with new primitive creation/usage   -Issue #54by @andyx13Incorrect classification for stft.json and stft_real.json -Issue #53by @andyx13Support for more complex pipeline architectures -Issue #52by @andyx13Update primitive interfaces -Issue #51by @andyx13Syntax for pipeline creation -Issue #41by @andyx13Load demo dataset at random index -Issue #35by @andyx130.1.2 - 2023-12-11FeaturesPython version update -Issue #44by @andyx13Add demo notebook and per-primitive documentation -Issue #47by @andyx130.1.1 - 2023-04-06FeaturesAccepting single value data frame format -Issue #36by @frances-h @sarahmishUpdate demos -Issue #26by @frances-h0.1.0 - 2021-11-14FeaturesRework SigPro to be class based0.0.3 - 2021-09-27FeaturesAddprocess_signalsfunction to take a collection of primitives and create features for the given data.0.0.2 - 2021-02-05Bug FixesMANIFEST.in: copy the json files of the primitives with the package installation.0.0.1 - 2021-01-26First release to PyPI.This release comes with the first version of thecontributingmodule, which makes it easier
to create new primitives and to test those with the demo data included in this package.This release also includes 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 ofSigPro.DEVELOPMENT.md: Step by step
guide about how to write a validSigProprimitive and contribute it to eitherSigProor
your own library.FeaturesDemo data: Available demo data to test primitives.First primitives: The following list of primitives were added:sigpro.aggregations.amplitude.statistical.crest_factorsigpro.aggregations.amplitude.statistical.kurtosissigpro.aggregations.amplitude.statistical.meansigpro.aggregations.amplitude.statistical.rmssigpro.aggregations.amplitude.statistical.skewsigpro.aggregations.amplitude.statistical.stdsigpro.aggregations.amplitude.statistical.varsigpro.transformations.amplitude.identity.identitysigpro.transformations.frequency.fft.fftsigpro.transformations.frequency.fft.fft_realsigpro.transformations.frequency_time.stft.stftsigpro.transformations.frequency_time.stft.stft_realContributing module.Documentation on how to contribute new primitives and how to run those.