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GutenTAG is an extensible tool to generate time series datasets with and without anomalies; integrated with TimeEval.

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We are user of this repo to create time series. We like to introduce new mode on a top of supervised and semi-supervised, call "ts-augmentation' where we produce - time...

enhancement
good first issue
help wanted
:medal_sports: very low
comp: GutenTAG (general)

This doesn't return a dataset with a timestamp. I can add my own timestamps. But it would be better I could configure the start date and time and get the...

enhancement
good first issue
:medal_sports: very low

Use an existing time series as base oscillation for a new dataset. This allows injecting our anomalies into existing time series. The file must be formatted in our canonical file...

enhancement
:medal_sports: very low

Take a subsequence and flip it vertically: ![image](https://user-images.githubusercontent.com/10573700/217221460-ce98f711-d5ec-4c90-b253-a94f27babfda.png) This anomaly can be used for periodic datasets only. Add an option for a smooth transition if the start and end does...

enhancement
good first issue
:medal_sports: low

Normalization anomalies can be constructed by combining mean and amplitude anomaly kinds, however, this is difficult to achieve. Add a new anomaly kind that allows to specify the way a...

enhancement
good first issue
:medal_sports: low

Some existing anomaly kinds use smooth transitions. We should allow all (except extremum) anomalies to do this, and therefore move it to the anomaly itself instead of the anomaly kind....

enhancement
:medal_sports: low

Add configuration options to post-process (each individual channel) of a time series. Post-processing options include: - smoothing using convolution along t - segment smoothing (smooth different parts of the time...

enhancement
:medal_sports: very low

Example configuration: ```yaml timeseries: - name: "mytest" length: 1000 base-oscillations: - kind: "formula" formula: base: kind: "ecg" frequency: 1 variance: 0 operation: kind: "*" operand: 1 ```

enhancement
good first issue
:medal_sports: very low

Bumps [pypa/gh-action-pypi-publish](https://github.com/pypa/gh-action-pypi-publish) from 1.8.14 to 1.9.0. Release notes Sourced from pypa/gh-action-pypi-publish's releases. v1.9.0 💅 Cosmetic Output Improvements @​woodruffw💰 updated the tense on password nudge in #234 @​shenxianpeng💰 helped us disable...

dependencies

Bumps [pypa/gh-action-pypi-publish](https://github.com/pypa/gh-action-pypi-publish) from 1.8.14 to 1.10.1. Release notes Sourced from pypa/gh-action-pypi-publish's releases. v1.10.1 🚑🔏 Oopsie... We missed a tiny bug in the attestations feature the other day The problem was...

dependencies