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Updating the docs #58

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27 changes: 9 additions & 18 deletions README.md
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
<a href='https://github.com/WenjieDu/TSDB'><img src="https://pypots.com/figs/pypots_logos/TSDB/logo_FFBG.svg" align='right' width='200'/></a>

<h2 align="center">Welcome to TSDB</h2>
<h3 align="center">Welcome to TSDB</h3>

*<p align='center'>a Python toolbox to ease loading public time-series datasets</p>*

Expand Down Expand Up @@ -71,7 +71,7 @@ TSDB now is available on <a alt='Anaconda' href='https://anaconda.org/conda-forg

Install it with `conda install tsdb `, you may need to specify the channel with option `-c conda-forge`

or install from PyPI:
or install via PyPI:
> pip install tsdb

or install from source code:
Expand Down Expand Up @@ -120,8 +120,14 @@ and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (tra
[Machine Learning Open Source Software](https://www.jmlr.org/mloss/)). If you use TSDB in your work,
please cite PyPOTS project as below and 🌟star this repository to make others notice this library. 🤗 Thank you!

<p align="center">
<a href="https://pypots.com/ecosystem/">
<img src="https://pypots.com/figs/pypots_logos/Ecosystem/PyPOTS_Ecosystem_Pipeline.png" width="95%"/>
</a>
</p>

``` bibtex
@article{du2023PyPOTS,
@article{du2023pypots,
title={{PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series}},
author={Wenjie Du},
year={2023},
Expand All @@ -137,21 +143,6 @@ doi={10.48550/arXiv.2305.18811},
> PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series.
> arXiv, abs/2305.18811.https://arxiv.org/abs/2305.18811

or

``` bibtex
@inproceedings{du2023PyPOTS,
title={{PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series}},
booktitle={9th SIGKDD workshop on Mining and Learning from Time Series (MiLeTS'23)},
author={Wenjie Du},
year={2023},
url={https://arxiv.org/abs/2305.18811},
}
```

> Wenjie Du. (2023).
> PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series.
> In *9th SIGKDD workshop on Mining and Learning from Time Series (MiLeTS'23)*. https://arxiv.org/abs/2305.18811


<details>
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63 changes: 44 additions & 19 deletions docs/index.rst
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.. TSDB documentation master file, created by
sphinx-quickstart on Wed Mar 15 15:23:52 2023.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
.. PyPOTS documentation index page
Created by Wenjie Du <wenjay.du@gmail.com>
License: BSD-3-Clause

Welcome to TSDB documentation!
================================
.. image:: https://pypots.com/figs/pypots_logos/TSDB/logo_FFBG.svg
:height: 160
:height: 180
:align: right
:target: https://github.com/WenjieDu/TSDB
:alt: TSDB logo

**A Python Toolbox Helping Load Time-Series Datasets Easily**
**A Python Toolbox to Ease Loading Public Time-Series Datasets**

.. image:: https://img.shields.io/badge/python-v3-E97040?logo=python&logoColor=white
:alt: Python version

.. image:: https://img.shields.io/github/v/release/wenjiedu/tsdb?color=EE781F&include_prereleases&label=Release&logo=github&logoColor=white
:alt: the latest release version
:target: https://img.shields.io/github/v/release/wenjiedu/tsdb?color=EE781F&include_prereleases&label=Release&logo=github&logoColor=white

.. image:: https://img.shields.io/badge/License-BSD--3-E9BB41?logo=opensourceinitiative&logoColor=white
:alt: License
:target: https://github.com/WenjieDu/TSDB/blob/main/LICENSE

.. image:: https://img.shields.io/github/actions/workflow/status/wenjiedu/tsdb/testing_ci.yml?logo=github&color=C8D8E1&label=CI
:alt: GitHub Testing
:target: https://github.com/WenjieDu/TSDB/actions/workflows/testing_ci.yml

.. image:: https://img.shields.io/codeclimate/maintainability-percentage/WenjieDu/TSDB?color=3C7699&label=Maintainability&logo=codeclimate
:alt: Code Climate maintainability
:target: https://codeclimate.com/github/WenjieDu/TSDB

.. image:: https://img.shields.io/coverallsCoverage/github/WenjieDu/TSDB?branch=main&logo=coveralls&color=75C1C4&label=Coverage
:alt: Coveralls report
:target: https://coveralls.io/github/WenjieDu/TSDB
.. image:: https://img.shields.io/conda/dn/conda-forge/tsdb?label=Conda%20Downloads&color=AED0ED&logo=anaconda&logoColor=white

.. image:: https://img.shields.io/endpoint?url=https://pypots.com/figs/downloads_badges/conda_tsdb_downloads.json
:alt: Conda downloads
:target: https://anaconda.org/conda-forge/pypots
.. image:: https://img.shields.io/endpoint?url=https%3A%2F%2Fraw.githubusercontent.com%2FWenjieDu%2FWenjieDu%2Fmain%2Ffigs%2Fprojects%2Ftsdb_downloads.json

.. image:: https://img.shields.io/endpoint?url=https://pypots.com/figs/downloads_badges/pypi_tsdb_downloads.json
:alt: PyPI downloads
:target: https://pepy.tech/project/tsdb

.. image:: https://img.shields.io/badge/Contributor%20Covenant-v2.1-4baaaa.svg
:alt: CODE of CONDUCT

.. image:: https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FWenjieDu%2FTime_Series_Database&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Visits+since+April+2022&edge_flat=false
:alt: Visit num

📣 TSDB now supports a total of 1️⃣6️⃣9️⃣ time-series datasets ‼️

📣 TSDB now supports a total of 1️⃣6️⃣8️⃣ time-series datasets ‼️

.. image:: https://raw.githubusercontent.com/PyPOTS/pypots.github.io/main/static/figs/pypots_logos/PyPOTS/logo_FFBG.svg
:height: 160
.. image:: https://pypots.com/figs/pypots_logos/PyPOTS/logo_FFBG.svg
:width: 120
:align: left
:target: https://github.com/WenjieDu/PyPOTS
:alt: PyPOTS logo
Expand All @@ -72,7 +79,7 @@ TSDB is available on both `PyPI <https://pypi.python.org/pypi/tsdb>`_ and `Anaco

Install it with `conda install tsdb`, you may need to specify the channel with option `-c conda-forge`

or install from PyPI:
or install via PyPI:

pip install tsdb

Expand All @@ -85,12 +92,22 @@ or install from source code:

import tsdb

tsdb.list_available_datasets() # list all available datasets in TSDB
data = tsdb.load_dataset('physionet_2012') # select the dataset you need and load it, TSDB will download, extract, and process it automatically
tsdb.download_and_extract('physionet_2012', './save_it_here') # if you need the raw data, use download_and_extract()
tsdb.list_cached_data() # datasets you once loaded are cached, and you can check them with list_cached_data()
tsdb.delete_cached_data(dataset_name='physionet_2012') # you can delete only one specific dataset and preserve others
tsdb.delete_cached_data() # or you can delete all cache with delete_cached_data() to free disk space
# list all available datasets in TSDB
tsdb.list()
# select the dataset you need and load it, TSDB will download, extract, and process it automatically
data = tsdb.load('physionet_2012')
# if you need the raw data, use download_and_extract()
tsdb.download_and_extract('physionet_2012', './save_it_here')
# datasets you once loaded are cached, and you can check them with list_cached_data()
tsdb.list_cache()
# you can delete only one specific dataset and preserve others
tsdb.delete_cache(dataset_name='physionet_2012')
# or you can delete all cache with delete_cached_data() to free disk space
tsdb.delete_cache()

# to avoid taking up too much space if downloading many datasets,
# TSDB cache directory can be migrated to an external disk
tsdb.migrate_cache("/mnt/external_disk/TSDB_cache")


That's all. Simple and efficient. Enjoy it! 😃
Expand All @@ -117,6 +134,14 @@ and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (tra
`Machine Learning Open Source Software <https://www.jmlr.org/mloss/>`_). If you use PyPOTS in your work,
please cite it as below and 🌟star `PyPOTS repository <https://github.com/WenjieDu/PyPOTS>`_ to make others notice this library. 🤗


.. image:: https://pypots.com/figs/pypots_logos/Ecosystem/PyPOTS_Ecosystem_Pipeline.png
:height: 300
:align: center
:target: https://pypots.com/ecosystem/
:alt: PyPOTS Ecosystem Pipeline


.. code-block:: bibtex
:linenos:

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