matrixprofile | Python 3 library making time series data mining tasks | Predictive Analytics library

by matrix-profile-foundation Python Version: 1.1.10 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | matrixprofile Summary

matrixprofile is a Python library typically used in Analytics, Predictive Analytics applications. matrixprofile has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install matrixprofile' or download it from GitHub, PyPI.

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

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Quality

Security

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Support

matrixprofile has a low active ecosystem.

It has 162 star(s) with 34 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 10 open issues and 32 have been closed. On average issues are closed in 45 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of matrixprofile is 1.1.10

Quality

matrixprofile has 0 bugs and 0 code smells.

Security

matrixprofile has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

matrixprofile code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

matrixprofile is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

matrixprofile releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

matrixprofile saves you 2347 person hours of effort in developing the same functionality from scratch.

It has 5122 lines of code, 276 functions and 59 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed matrixprofile and discovered the below as its top functions. This is intended to give you an instant insight into matrixprofile implemented functionality, and help decide if they suit your requirements.

Check that ts and query is 1d
Convert a to a NumPy array
Check if a is array - like
Checks if a is one - dimensional
Applies an average average
Generate a new array with a rolling window
Calculate the complexity of a time series
Make an array of NaNs
Generate the top k motifs from a PMP profile
Compute the mass2 of a time series
Takes a PMP data structure and returns a PMP
Return a dict of MatrixProfile
Convert a pearson array to eclients
Clean NaNs from a ts
Check if array is a Pearson array
Moving function
Calculate the standard deviation of an array
Moving median function
Moving over an array
Check if an object is a pmp object
Calculate a moving average
Return True if two ts are similar
Find the motifs in a given profile
Write a profile to disk
Create a profile from a file
Return the indices that are not NaN

Get all kandi verified functions for this library.

matrixprofile Key Features

No Key Features are available at this moment for matrixprofile.

matrixprofile Examples and Code Snippets

No Code Snippets are available at this moment for matrixprofile.

Community Discussions

Trending Discussions on matrixprofile

pandas apply function to each group (output is not really an aggregation)

QUESTION

pandas apply function to each group (output is not really an aggregation)

Asked 2020-Nov-09 at 15:22

I have a list of time-series (=pandas dataframe) and want to calculate for each time-series (of a device) the matrixprofile. One option is to iterate all the devices - which seems to be slow. A second option would be to group by the devices - and apply a UDF. The problem is now, that the UDF will return 1:1 rows i.e. not a single scalar value per group but the same number of rows will be outputted as the input.

Is it still possible to somehow vectorize this calculation for reach group when 1:1 (or at least non scalar values) are returned?

...

ANSWER

Answered 2020-Nov-09 at 14:30

Indeed this (see also the link above in the comment) is a way to get it to work in a faster/more desired way. Perhaps there is even a better alternative

Source https://stackoverflow.com/questions/64751921

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install matrixprofile

You can install using 'pip install matrixprofile' or download it from GitHub, PyPI.
You can use matrixprofile like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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