Merge pull request #27 from WenjieDu/dev

Updating the docs
WenjieDu · Aug 8, 2023 · 755dfef · 755dfef
2 parents b31bb2b + 8520fb5
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diff --git a/.github/workflows/linting.yml b/.github/workflows/linting.yml
@@ -7,7 +7,6 @@ on:
             - dev
     pull_request:
         branches:
-            - main
             - dev
 
 jobs:
@@ -28,4 +27,4 @@ jobs:
 
             - name: Run linting
               run: |
-                flake8 .
+                flake8 .
diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-<a href='https://github.com/WenjieDu/TSDB'><img src="https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true" align='right' width='235'/></a>
+<a href='https://github.com/WenjieDu/TSDB'><img src="https://raw.githubusercontent.com/PyPOTS/pypots.github.io/main/static/figs/pypots_logos/TSDB_logo_FFBG.svg?sanitize=truee" align='right' width='235'/></a>
 
 # <p align='center'>Welcome to TSDB</p>
 **<p align='center'>A Python Toolbox to Ease Loading Open-Source Time-Series Datasets</p>**
@@ -15,14 +15,14 @@
         <img alt="GPL-v3 license" src="https://img.shields.io/badge/License-GPL--v3-E9BB41">
     </a>
     <!-- GitHub Testing -->
-    <a alt='GitHub Testing' href='https://github.com/WenjieDu/TSDB/actions/workflows/testing_ci.yml'> 
+    <a alt='GitHub Testing' href='https://github.com/WenjieDu/TSDB/actions/workflows/testing_ci.yml'>
         <img src='https://img.shields.io/github/actions/workflow/status/wenjiedu/tsdb/testing_ci.yml?logo=github&color=C8D8E1&label=CI'>
     </a>
     <a href="https://codeclimate.com/github/WenjieDu/TSDB">
         <img alt="Code Climate maintainability" src="https://img.shields.io/codeclimate/maintainability-percentage/WenjieDu/TSDB?color=3C7699&label=Maintainability&logo=codeclimate">
     </a>
     <!-- Coveralls report -->
-    <a alt='Coveralls report' href='https://coveralls.io/github/WenjieDu/TSDB'> 
+    <a alt='Coveralls report' href='https://coveralls.io/github/WenjieDu/TSDB'>
         <img src='https://img.shields.io/coverallsCoverage/github/WenjieDu/TSDB?branch=main&logo=coveralls&color=75C1C4&label=Coverage'>
     </a>
     <a href="https://anaconda.org/conda-forge/tsdb">
@@ -36,7 +36,7 @@
 
 > 📣 TSDB now supports a total of 1️⃣6️⃣8️⃣ time-series datasets ‼️
 
-<a href='https://github.com/WenjieDu/PyPOTS'><img src='https://raw.githubusercontent.com/WenjieDu/PyPOTS/main/docs/_static/figs/PyPOTS_logo.svg?sanitize=true' width='160' align='left' /></a>
+<a href='https://github.com/WenjieDu/PyPOTS'><img src='https://raw.githubusercontent.com/PyPOTS/pypots.github.io/main/static/figs/pypots_logos/PyPOTS_logo_FFBG.svg?sanitize=true' width='160' align='left' /></a>
 TSDB is a part of [PyPOTS project](https://github.com/WenjieDu/PyPOTS) (a Python toolbox for data mining on Partially-Observed Time Series), and was separated from PyPOTS for decoupling datasets from learning algorithms.
 
 TSDB is created to help researchers and engineers get rid of data collecting and downloading, and focus back on data processing details. TSDB provides all-in-one-stop convenience for downloading and loading open-source time-series datasets (available datasets listed [below](https://github.com/WenjieDu/TSDB#-list-of-available-datasets)).
@@ -51,7 +51,7 @@ if it helps with your research. This really means a lot to our open-source resea
 
 
 ## ❖ Usage Examples
-TSDB now is available on <a alt='Anaconda' href='https://anaconda.org/conda-forge/tsdb'><img align='center' src='https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda'></a>❗️ 
+TSDB now is available on <a alt='Anaconda' href='https://anaconda.org/conda-forge/tsdb'><img align='center' src='https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda'></a>❗️
 
 Install it with `conda install tsdb`, you may need to specify the channel with option `-c conda-forge`
 
@@ -68,8 +68,8 @@ 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()  # you can delete all cache with delete_cached_data() to free disk space
-tsdb.delete_cached_data(dataset_name='physionet_2012')  # or you can delete only one specific dataset and preserve others
+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
 ```
 
 That's all. Simple and efficient. Enjoy it! 😃

diff --git a/docs/_static/figs/TSDB_logo.svg b/docs/_static/figs/TSDB_logo.svg
diff --git a/docs/conf.py b/docs/conf.py
@@ -65,7 +65,6 @@
 bibtex_bibfiles = ["references.bib"]
 bibtex_default_style = "unsrt"
 
-
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 
@@ -91,7 +90,10 @@
     "last_updated": f"{date_now.year}/{date_now.month}/{date_now.day}",
 }
 
-# html_favicon = "_static/figs/PyPOTS_logo.svg"
+html_favicon = (
+    "https://raw.githubusercontent.com/"
+    "PyPOTS/pypots.github.io/main/static/figs/pypots_logos/PyPOTS_logo_FFBG.svg"
+)
 
 html_sidebars = {
     "**": [

diff --git a/docs/index.rst b/docs/index.rst
@@ -5,7 +5,7 @@
 
 Welcome to TSDB documentation!
 ================================
-.. image:: https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true
+.. image:: https://raw.githubusercontent.com/PyPOTS/pypots.github.io/main/static/figs/pypots_logos/TSDB_logo_FFBG.svg?sanitize=true
    :height: 160
    :align: right
    :target: https://github.com/WenjieDu/TSDB
@@ -43,6 +43,14 @@ Welcome to TSDB documentation!
 
 📣 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?sanitize=true
+   :height: 160
+   :align: left
+   :target: https://github.com/WenjieDu/PyPOTS
+   :alt: PyPOTS logo
+
+TSDB is a part of `PyPOTS project <https://github.com/WenjieDu/PyPOTS>`_ (a Python toolbox for data mining on Partially-Observed Time Series), and was separated from PyPOTS for decoupling datasets from learning algorithms.
+
 TSDB is created to help researchers and engineers get rid of data collecting and downloading, and focus back on data processing details.
 TSDB provides all-in-one-stop convenience for downloading and loading open-source time-series datasets (available datasets listed `below <https://github.com/WenjieDu/TSDB#-list-of-available-datasets>`_).
 
@@ -80,37 +88,28 @@ or install from source code:
    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()  # you can delete all cache with delete_cached_data() to free disk space
-   tsdb.delete_cached_data(dataset_name='physionet_2012')  # or you can delete only one specific dataset and preserve others
+   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
 
 
 That's all. Simple and efficient. Enjoy it! 😃
 
 
 ❖ List of Available Datasets
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-=============================================================================================================================== ==========================================
- Name                                                                                                                            Main Tasks
-=============================================================================================================================== ==========================================
- `PhysioNet Challenge 2012 <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/physionet_2012>`_                       Classification, Forecasting, Imputation
- `PhysioNet Challenge 2019 <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/physionet_2019>`_                       Classification, Imputation
- `Beijing Multi-Site Air-Quality <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/beijing_multisite_air_quality>`_  Forecasting, Imputation
- `Electricity Load Diagrams <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/electricity_load_diagrams>`_           Forecasting, Imputation
- `UCR & UEA Datasets <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/ucr_uea_datasets>`_ (all 163 datasets)        Classification
- `Vessel AIS data <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/vessel_ais>`_                                    Imputation, Forecasting, Classification
-=============================================================================================================================== ==========================================
+=================================================================================================================================================================== ==========================================
+ Name                                                                                                                                                               Main Tasks
+=================================================================================================================================================================== ==========================================
+ `PhysioNet Challenge 2012 <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/physionet_2012>`_  :cite:`silva2012physionet`                               Classification, Forecasting, Imputation
+ `PhysioNet Challenge 2019 <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/physionet_2019>`_  :cite:`reyna2019physionet`                               Classification, Imputation
+ `Beijing Multi-Site Air-Quality <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/beijing_multisite_air_quality>`_  :cite:`zhang2017airquality`         Forecasting, Imputation
+ `Electricity Load Diagrams <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/electricity_load_diagrams>`_  :cite:`trindade2015electricity`              Forecasting, Imputation
+ `UCR & UEA Datasets <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/ucr_uea_datasets>`_ (all 163 datasets)  :cite:`bagnall2018uea` :cite:`dau2018ucr` Classification
+ `Vessel AIS data <https://github.com/WenjieDu/TSDB/tree/main/dataset_profiles/vessel_ais>`_  :cite:`grgicevic2023ais`                                              Imputation, Forecasting, Classification
+=================================================================================================================================================================== ==========================================
 
 ❖ Citing TSDB/PyPOTS
 ^^^^^^^^^^^^^^^^^^^^^
-
-.. image:: https://raw.githubusercontent.com/WenjieDu/PyPOTS/main/docs/_static/figs/PyPOTS_logo.svg?sanitize=true
-   :height: 160
-   :align: left
-   :target: https://github.com/WenjieDu/PyPOTS
-   :alt: PyPOTS logo
-
-TSDB is a part of `PyPOTS project <https://github.com/WenjieDu/PyPOTS>`_ (a Python toolbox for data mining on Partially-Observed Time Series), and was separated from PyPOTS for decoupling datasets from learning algorithms.
-
 The paper introducing PyPOTS is available on arXiv at `this URL <https://arxiv.org/abs/2305.18811>`_.,
 and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for
 `Machine Learning Open Source Software <https://www.jmlr.org/mloss/>`_). If you use PyPOTS in your work,

diff --git a/docs/references.bib b/docs/references.bib
@@ -26,7 +26,7 @@ @article{silva2012physionet
 }
 
 @article{reyna2019physionet,
-title={Early prediction of sepsis from clinical data: the PhysioNet\/Computing in Cardiology Challenge 2019.},
+title={Early prediction of sepsis from clinical data: the PhysioNet/Computing in Cardiology Challenge 2019.},
 author={Reyna, MA and Josef, C and Jeter, R and Shashikumar, SP and Westover, MB and  Nemati, S and Clifford, GD and  Sharma, A},
 journal={Critical Care Medicine},
 volume={48},