{"author":"Matrix Profile Foundation","author_email":"tylerwmarrs@gmail.com","bugtrack_url":null,"classifiers":["Intended Audience :: Developers","Intended Audience :: Information Technology","Intended Audience :: Science/Research","License :: OSI Approved :: Apache Software License","Operating System :: MacOS","Operating System :: Microsoft :: Windows","Operating System :: POSIX","Programming Language :: Python :: 2","Programming Language :: Python :: 3","Topic :: Scientific/Engineering","Topic :: Software Development"],"description":"===============================\n MatrixProfile Documentation\n===============================\n\n.. image:: https://img.shields.io/pypi/v/matrixprofile.svg\n :target: https://pypi.org/project/matrixprofile/\n :alt: PyPI Version\n.. image:: https://pepy.tech/badge/matrixprofile\n :target: https://pepy.tech/project/matrixprofile\n :alt: PyPI Downloads\n.. image:: https://codecov.io/gh/matrix-profile-foundation/matrixprofile/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/matrix-profile-foundation/matrixprofile\n :alt: Code Coverage\n.. image:: https://api.travis-ci.com/matrix-profile-foundation/matrixprofile.svg?branch=master\n :target: https://travis-ci.com/matrix-profile-foundation/matrixprofile\n :alt: Build Status\n.. image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg\n :target: https://opensource.org/licenses/Apache-2.0\n :alt: License\n.. image:: https://img.shields.io/twitter/follow/matrixprofile.svg?style=social\n :target: https://twitter.com/matrixprofile\n :alt: Twitter\n.. image:: https://img.shields.io/discord/589321741277462559?logo=discord\n :target: https://discordapp.com/invite/sBhDNXT\n :alt: Discord\n.. image:: https://joss.theoj.org/papers/10.21105/joss.02179/status.svg\n :target: https://doi.org/10.21105/joss.02179\n :alt: JOSSDOI\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3789780.svg\n :target: https://doi.org/10.5281/zenodo.3789780\n :alt: ZenodoDOI\n\n|\n\n.. image:: https://matrixprofile.org/static/img/mpf-logo.png\n :target: https://matrixprofile.org\n :height: 300px\n :scale: 50%\n :alt: MPF Logo\n\nMatrixProfile\n----------------\nMatrixProfile is a Python 3 library, brought to you by the `Matrix Profile Foundation `_, for mining time series data. The Matrix Profile is a novel data structure with corresponding algorithms (stomp, regimes, motifs, etc.) developed by the `Keogh `_ and `Mueen `_ research groups at UC-Riverside and the University of New Mexico. The goal of this library is to make these algorithms accessible to both the novice and expert through standardization of core concepts, a simplistic API, and sensible default parameter values.\n\nIn addition to this Python library, the Matrix Profile Foundation, provides implementations in other languages. These languages have a pretty consistent API allowing you to easily switch between them without a huge learning curve.\n\n* `tsmp `_ - an R implementation\n* `go-matrixprofile `_ - a Golang implementation\n\nPython Support\n----------------\nCurrently, we support the following versions of Python:\n\n* 3.5\n* 3.6\n* 3.7\n* 3.8\n* 3.9\n\nPython 2 is no longer supported. There are earlier versions of this library that support Python 2.\n\nInstallation\n------------\nThe easiest way to install this library is using pip. If you would like to install it from source, please review the `installation documentation `_ for your platform.\n\n.. code-block:: bash\n\n pip install matrixprofile\n\nGetting Started\n---------------\nThis article provides introductory material on the Matrix Profile:\n`Introduction to Matrix Profiles `_\n\n\nThis article provides details about core concepts introduced in this library:\n`How To Painlessly Analyze Your Time Series `_\n\nOur documentation provides a `quick start guide `_, `examples `_ and `api `_ documentation. It is the source of truth for getting up and running.\n\nAlgorithms\n----------\nFor details about the algorithms implemented, including performance characteristics, please refer to the `documentation `_.\n\n------------\nGetting Help\n------------\nWe provide a dedicated `Discord channel `_ where practitioners can discuss applications and ask questions about the Matrix Profile Foundation libraries. If you rather not join Discord, then please open a `Github issue `_.\n\n------------\nContributing\n------------\nPlease review the `contributing guidelines `_ located in our documentation.\n\n---------------\nCode of Conduct\n---------------\nPlease review our `Code of Conduct documentation `_.\n\n---------\nCitations\n---------\nAll proper acknowledgements for works of others may be found in our `citation documentation `_.\n\n------\nCiting\n------\nPlease cite this work using the `Journal of Open Source Software article `_.\n\n Van Benschoten et al., (2020). MPA: a novel cross-language API for time series analysis. Journal of Open Source Software, 5(49), 2179, https://doi.org/10.21105/joss.02179\n\n.. code:: bibtex\n\n @article{Van Benschoten2020,\n doi = {10.21105/joss.02179},\n url = {https://doi.org/10.21105/joss.02179},\n year = {2020},\n publisher = {The Open Journal},\n volume = {5},\n number = {49},\n pages = {2179},\n author = {Andrew Van Benschoten and Austin Ouyang and Francisco Bischoff and Tyler Marrs},\n title = {MPA: a novel cross-language API for time series analysis},\n journal = {Journal of Open Source Software}\n }\n\n\n","description_content_type":"text/x-rst","docs_url":null,"download_url":"","downloads":{"last_day":-1,"last_month":-1,"last_week":-1},"dynamic":null,"home_page":"https://github.com/matrix-profile-foundation/matrixprofile","keywords":"matrix profile time series discord motif analysis data science anomaly pattern","license":"","license_expression":null,"license_files":null,"maintainer":"","maintainer_email":"","name":"matrixprofile","package_url":"https://pypi.org/project/matrixprofile/","platform":"","project_url":"https://pypi.org/project/matrixprofile/","project_urls":{"Homepage":"https://github.com/matrix-profile-foundation/matrixprofile","Matrix Profile Foundation":"https://matrixprofile.org","Source Code":"https://github.com/matrix-profile-foundation/matrixprofile"},"provides_extra":null,"release_url":"https://pypi.org/project/matrixprofile/1.1.10/","requires_dist":["numpy (>=1.16.2)","matplotlib (>=3.0.3)","protobuf (==3.11.2)","scipy (<2.0.0,>=1.3.2)"],"requires_python":"","summary":"An open source time series data mining library based on Matrix Profile algorithms.","version":"1.1.10","yanked":false,"yanked_reason":null}

Dependencies of matrixprofile (4).
Dependency	Optional
matplotlib	false
numpy	false
protobuf	false
scipy	false

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