Tutorial release, new features, and bug fix

.devcontainer/devcontainer.json

@@ -0,0 +1,17 @@
+// Some IDEs or editors like PhCharm may not support comments in JSON files, but it is still valid JSON.
+// About configurations for GitHub codebase, please refer to
+// https://docs.github.com/en/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration/setting-up-your-python-project-for-codespaces
+
+{
+ "name": "PyPOTS developing environment",
+
+ "image": "mcr.microsoft.com/devcontainers/universal:2",
+
+ "features": {
+ "ghcr.io/devcontainers/features/conda:1": {},
+ },
+
+ // Please select the machine type with 4GB memory, otherwise the conda command below will exit with code 137,
+ // which is out of memory.
+ "postCreateCommand": "conda env create -f environment-dev.yml",
+}

.github/ISSUE_TEMPLATE/config.yml

@@ -2,5 +2,5 @@ blank_issues_enabled: true
 version: 2.1
 contact_links:
  - name: PyPOTS Community on Slack
- url: pypots-dev.slack.com
+ url: https://pypots-dev.slack.com
  about: General usage questions, community discussions, and the development team are here.

.github/stale.yml

@@ -0,0 +1,22 @@
+# Number of days of inactivity before an issue becomes stale
+daysUntilStale: 7
+
+# Number of days of inactivity before a stale issue is closed
+daysUntilClose: 3
+
+# Issues with these labels will never be considered stale
+exemptLabels:
+ - pinned
+ - keep
+
+# Label to use when marking an issue as stale
+staleLabel: stale
+
+# Comment to post when marking an issue as stale. Set to `false` to disable
+markComment: >
+ This issue has been automatically marked as stale because it has not had
+ recent activity. It will be closed if no further activity occurs. Thank you
+ for your contributions.
+
+# Comment to post when closing a stale issue. Set to `false` to disable
+closeComment: false

.github/workflows/testing.yml

@@ -41,14 +41,15 @@ jobs:
 
  - name: Test with pytest
  run: |
- # run tests separately here due to Segmentation Fault in test_clustering when run all in 
+ # run tests separately here due to Segmentation Fault in test_clustering when run all in
  # one command with `pytest` on MacOS. Bugs not caught, so this is a trade-off to avoid SF.
- python -m pytest -rA pypots/tests/test_classification.py -n auto --cov=pypots --dist=loadgroup 
+ python -m pytest -rA pypots/tests/test_classification.py -n auto --cov=pypots --dist=loadgroup
  python -m pytest -rA pypots/tests/test_imputation.py -n auto --cov=pypots --cov-append --dist=loadgroup
  python -m pytest -rA pypots/tests/test_clustering.py -n auto --cov=pypots --cov-append --dist=loadgroup
  python -m pytest -rA pypots/tests/test_forecasting.py -n auto --cov=pypots --cov-append --dist=loadgroup
  python -m pytest -rA pypots/tests/test_data.py -n auto --cov=pypots --cov-append --dist=loadgroup
  python -m pytest -rA pypots/tests/test_utils.py -n auto --cov=pypots --cov-append --dist=loadgroup
+ python -m pytest -rA pypots/tests/test_cli.py -n auto --cov=pypots --cov-append --dist=loadgroup
 
  - name: Generate the LCOV report
  run: |
@@ -58,4 +59,4 @@ jobs:
  uses: coverallsapp/github-action@master
  with:
  github-token: ${{ secrets.GITHUB_TOKEN }}
- path-to-lcov: 'coverage.lcov'
+ path-to-lcov: 'coverage.lcov'

.pre-commit-config.yaml

@@ -7,16 +7,6 @@ repos:
  - id: end-of-file-fixer
  - id: check-yaml
 
- # hooks for optimizing imports
- - repo: https://github.com/PyCQA/autoflake
- rev: v2.1.1
- hooks:
- - id: autoflake
- args: [
- --check,
- --remove-all-unused-imports,
- ]
-
  # hooks for linting code
  - repo: https://github.com/psf/black
  rev: 22.10.0

README.md

@@ -4,59 +4,61 @@
 **<p align="center">A Python Toolbox for Data Mining on Partially-Observed Time Series</p>**
 
 <p align="center">
- <img alt="Python version" src="https://img.shields.io/badge/Python->v3.6-yellow?color=88ada6">
- <img alt="powered by Pytorch" src="https://img.shields.io/static/v1?label=PyTorch&message=%E2%9D%A4%EF%B8%8F&color=bbcdc5&logo=pytorch">
+ <img alt="Python version" src="https://img.shields.io/badge/Python-v3.7--3.10-88ada6?logo=python&logoColor=white">
+ <img alt="powered by Pytorch" src="https://img.shields.io/badge/PyTorch-❤️-bbcdc5?logo=pytorch&logoColor=white">
  <a href="https://pypi.org/project/">
  <img alt="the latest release version" src="https://img.shields.io/github/v/release/wenjiedu/pypots?color=e0eee8&include_prereleases&label=Release">
  </a>
  <a href="https://github.com/WenjieDu/PyPOTS/blob/main/LICENSE">
  <img alt="GPL3 license" src="https://img.shields.io/badge/License-GPL--v3-c0ebd7">
  </a>
- <a href="https://join.slack.com/t/pypots-dev/shared_invite/zt-1gq6ufwsi-p0OZdW~e9UW_IA4_f1OfxA"> 
- <img alt="Slack Workspace" src="https://img.shields.io/badge/Slack-PyPOTS-grey?logo=slack&color=7bcfa6">
+ <a href="https://github.com/WenjieDu/PyPOTS/blob/main/README.md#-community">
+ <img alt="Community" src="https://img.shields.io/badge/join_us-community!-7fecad">
  </a>
  <a href="https://github.com/sponsors/WenjieDu">
- <img alt="GitHub Sponsors" src="https://img.shields.io/github/sponsors/wenjiedu?label=Sponsors&color=7fecad&logo=githubsponsors">
+ <img alt="GitHub Sponsors" src="https://img.shields.io/github/sponsors/wenjiedu?label=Sponsors&color=7bcfa6&logo=githubsponsors">
  </a>
  <a href="https://github.com/WenjieDu/PyPOTS/stargazers">
  <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/wenjiedu/pypots?logo=Github&color=7bcfa6&label=Stars">
  </a>
  <a href="https://github.com/WenjieDu/PyPOTS/forks">
  <img alt="GitHub Repo forks" src="https://img.shields.io/github/forks/wenjiedu/pypots?logo=Github&color=2edfa3&label=Forks">
  </a>
- <a href="https://github.com/WenjieDu/PyPOTS">
- <img alt="Repo size" src="https://img.shields.io/github/repo-size/WenjieDu/PyPOTS?color=25f8cb&label=Repo%20Size&logo=Github">
+ <a href="https://codeclimate.com/github/WenjieDu/PyPOTS">
+ <img alt="Code Climate maintainability" src="https://img.shields.io/codeclimate/maintainability-percentage/WenjieDu/PyPOTS?color=25f8cb&label=Maintainability&logo=codeclimate">
  </a>
- <a href="https://coveralls.io/github/WenjieDu/PyPOTS"> 
+ <a href="https://coveralls.io/github/WenjieDu/PyPOTS">
  <img alt="Coveralls coverage" src="https://img.shields.io/coverallsCoverage/github/WenjieDu/PyPOTS?branch=main&logo=coveralls&color=00e09e&label=Coverage">
  </a>
- <a href="https://anaconda.org/conda-forge/pypots">
- <img alt="Conda downloads" src="https://img.shields.io/conda/dn/conda-forge/pypots?label=Conda%20Downloads&color=48c0a3">
+ <a href="https://github.com/WenjieDu/PyPOTS/actions/workflows/testing.yml">
+ <img alt="GitHub Testing" src="https://img.shields.io/github/actions/workflow/status/wenjiedu/pypots/testing.yml?logo=github&color=48c0a3&label=CI">
  </a>
- <a href="https://pypi.org/project/pypots">
- <img alt="PyPI downloads" src="https://static.pepy.tech/personalized-badge/pypots?period=total&units=international_system&left_color=grey&right_color=teal&left_text=PyPI%20Downloads">
+ <a href="https://doi.org/10.5281/zenodo.6823221">
+ <img alt="Zenodo DOI" src="https://img.shields.io/badge/DOI-10.5281/zenodo.6823221-21a675">
  </a>
- <a href="https://github.com/WenjieDu/PyPOTS/actions/workflows/testing.yml"> 
- <img alt="GitHub Testing" src="https://github.com/WenjieDu/PyPOTS/actions/workflows/testing.yml/badge.svg">
+ <a href="https://anaconda.org/conda-forge/pypots">
+ <img alt="Conda downloads" src="https://img.shields.io/conda/dn/conda-forge/pypots?label=Conda%20Downloads&color=057748&logo=anaconda&logoColor=white">
  </a>
- <a href="https://doi.org/10.5281/zenodo.6823221">
- <img alt="Zenodo DOI" src="https://zenodo.org/badge/DOI/10.5281/zenodo.6823221.svg">
+ <a href="https://pypi.org/project/pypots">
+ <img alt="PyPI downloads" src="https://static.pepy.tech/personalized-badge/pypots?period=total&units=international_system&left_color=grey&right_color=teal&left_text=PyPI%20Downloads&logo=github">
  </a>
+
 </p>
 
 ⦿ `Motivation`: Due to all kinds of reasons like failure of collection sensors, communication error, and unexpected malfunction, missing values are common to see in time series from the real-world environment. This makes partially-observed time series (POTS) a pervasive problem in open-world modeling and prevents advanced data analysis. Although this problem is important, the area of data mining on POTS still lacks a dedicated toolkit. PyPOTS is created to fill in this blank.
 
 ⦿ `Mission`: PyPOTS is born to become a handy toolbox that is going to make data mining on POTS easy rather than tedious, to help engineers and researchers focus more on the core problems in their hands rather than on how to deal with the missing parts in their data. PyPOTS will keep integrating classical and the latest state-of-the-art data mining algorithms for partially-observed multivariate time series. For sure, besides various algorithms, PyPOTS is going to have unified APIs together with detailed documentation and interactive examples across algorithms as tutorials.
 
-<a href="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/WenjieDu/TSDB"><img src="https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true" align="left" width="160"/></a>
-To make various open-source time-series datasets readily available to our users, PyPOTS gets supported by project [TSDB (Time-Series Data Base)](https://github.com/WenjieDu/TSDB), a toolbox making loading time-series datasets super easy! 
+<a href="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/WenjieDu/TSDB"><img src="https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true" align="left" width="160" alt="TSDB logo"/></a>
+To make various open-source time-series datasets readily available to our users, PyPOTS gets supported by project [TSDB (Time-Series Data Base)](https://github.com/WenjieDu/TSDB), a toolbox making loading time-series datasets super easy!
 
 Visit [TSDB](https://github.com/WenjieDu/TSDB) right now to know more about this handy tool 🛠! It now supports a total of 119 open-source datasets.
 <br clear="left">
 
+
 ## ❖ Installation
-PyPOTS now is available on <a href="https://anaconda.org/conda-forge/pypots"><img alt="on Anaconda" align="center" 
-src="https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda"></a>❗️ 
+PyPOTS now is available on <a href="https://anaconda.org/conda-forge/pypots"><img alt="on Anaconda" align="center"
+src="https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda"></a>❗️
 
 Install it with `conda install pypots`, you may need to specify the channel with option `-c conda-forge`
 
@@ -66,8 +68,21 @@ Install the latest release from PyPI:
 or install from the source code with the latest features not officially released in a version:
 > pip install https://github.com/WenjieDu/PyPOTS/archive/main.zip
 
-<details open>
-<summary><b>Below is an example applying SAITS in PyPOTS to impute missing values in the dataset PhysioNet2012:</b></summary>
+
+## ❖ Usage
+<a href="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/WenjieDu/BrewedPOTS"><img src="https://raw.githubusercontent.com/WenjieDu/BrewedPOTS/main/figs/BrewedPOTS_logo.jpg" align="left" width="160" alt="BrewedPOTS logo"/></a>
+PyPOTS tutorials have been released. Considering the future workload on it, I separate the tutorials into a single repo,
+and you can find them in [BrewedPOTS](https://github.com/WenjieDu/BrewedPOTS).
+
+If you have further questions, please refer to PyPOTS documentation [📑http:https://pypots.readthedocs.io](http:https://pypots.readthedocs.io).
+Besides, you can also
+[raise an issue](https://github.com/WenjieDu/PyPOTS/issues) or
+[ask in our community](#-community).
+
+We present you a usage example of imputing missing values in time series with PyPOTS below, you can click it to view.
+
+<details>
+<summary><b>Click here to see an example applying SAITS on PhysioNet2012 for imputation:</b></summary>
 
 ``` python
 import numpy as np
@@ -93,12 +108,13 @@ mae = cal_mae(imputation, X_intact, indicating_mask) # calculate mean absolute
 ```
 </details>
 
+
 ## ❖ Available Algorithms
 PyPOTS supports imputation, classification, clustering, and forecasting tasks on multivariate time series with missing values. The currently available algorithms of four tasks are cataloged in the following table with four partitions. The paper references are all listed at the bottom of this readme file. Please refer to them if you want more details.
 
 | ***`Imputation`*** | 🚥 | 🚥 | 🚥 |
 |:----------------------:|:------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|
-| **Type** | **Abbr.** | **Full name of the algorithm/model/paper** | **Year** | 
+| **Type** | **Abbr.** | **Full name of the algorithm/model/paper** | **Year** |
 | Neural Net | SAITS | Self-Attention-based Imputation for Time Series [^1] | 2023 |
 | Neural Net | Transformer | Attention is All you Need [^2];<br>Self-Attention-based Imputation for Time Series [^1];<br><sub>Note: proposed in [^2], and re-implemented as an imputation model in [^1].</sub> | 2017 |
 | Neural Net | BRITS | Bidirectional Recurrent Imputation for Time Series [^3] | 2018 |
@@ -118,9 +134,9 @@ PyPOTS supports imputation, classification, clustering, and forecasting tasks on
 
 
 ## ❖ Citing PyPOTS
-We are pursuing to publish a short paper introducing PyPOTS in prestigious academic venues, e.g. JMLR (track for 
-[Machine Learning Open Source Software](https://www.jmlr.org/mloss/)). Before that, PyPOTS is using its DOI from Zenodo 
-for reference. If you use PyPOTS in your research, please cite it as below and 🌟star this repository to make others 
+We are pursuing to publish a short paper introducing PyPOTS in prestigious academic venues, e.g. JMLR (track for
+[Machine Learning Open Source Software](https://www.jmlr.org/mloss/)). Before that, PyPOTS is using its DOI from Zenodo
+for reference. If you use PyPOTS in your research, please cite it as below and 🌟star this repository to make others
 notice this work. 🤗
 
 ```bibtex
@@ -136,21 +152,31 @@ doi = {10.5281/zenodo.6823221},
 
 or
 
-`Wenjie Du. (2022). 
-PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series. 
+`Wenjie Du. (2022).
+PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series.
 Zenodo. https://doi.org/10.5281/zenodo.6823221`
 
 
+## ❖ Community
+We care about the feedback from our users, so we're building PyPOTS community on
+
+- [Slack](https://pypots-dev.slack.com);
+- [WeChat (微信公众号)](https://mp.weixin.qq.com/s/m6j83SJNgz-xySSZd-DTBw). We also run a group chat on WeChat, and you can get the QR code from the official account after following it;
+
+If you have any suggestions or want to contribute ideas or share time-series related papers, join us and tell.
+PyPOTS community is open, transparent, and surely friendly. Let's work together to build and improve PyPOTS 💪!
+
+
 ## ❖ Contribution
-You're very welcome to contribute to this exciting project! 
+You're very welcome to contribute to this exciting project!
 
 By committing your code, you'll
-- make your well-established model out-of-the-box for PyPOTS users to run;
-- be listed as one of [PyPOTS contributors](https://github.com/WenjieDu/PyPOTS/graphs/contributors): <a href="https://github.com/wenjiedu/pypots/graphs/contributors"><img align="center" src="https://contrib.rocks/image?repo=wenjiedu/pypots"></a>;
-- get mentioned in our [release notes](https://github.com/WenjieDu/PyPOTS/releases);
- 
-You can also contribute to PyPOTS by simply staring🌟 this repo to help more people notice it. 
-Your star is your recognition to PyPOTS, and it matters! 
+1. make your well-established model out-of-the-box for PyPOTS users to run (Similar to [**Scikit-learn**](https://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms), we set current inclusion criteria as: the paper should be published for at least 1 year, have 10+ citations, and the usefulness to our users can be claimed);
+2. be listed as one of [PyPOTS contributors](https://github.com/WenjieDu/PyPOTS/graphs/contributors): <a href="https://github.com/wenjiedu/pypots/graphs/contributors"><img align="center" src="https://contrib.rocks/image?repo=wenjiedu/pypots"></a>;
+3. get mentioned in our [release notes](https://github.com/WenjieDu/PyPOTS/releases);
+
+You can also contribute to PyPOTS by simply staring🌟 this repo to help more people notice it.
+Your star is your recognition to PyPOTS, and it matters!
 
 <details open>
 <summary><b><i>👏 Click here to view PyPOTS stargazers and forkers.<br>We're so proud to have more and more awesome users, as well as more bright ✨stars: </i></b></summary>
@@ -160,13 +186,9 @@ Your star is your recognition to PyPOTS, and it matters!
 
 
 ## ❖ Attention 👀
-The documentation and tutorials are under construction. 
-
-‼️ PyPOTS is currently under developing. If you like it and look forward to its growth, <ins>please give PyPOTS a star 
-and watch it to keep you posted on its progress and to let me know that its development is meaningful</ins>. If you have 
-any feedback, or want to contribute ideas/suggestions or share time-series related algorithms/papers, please join PyPOTS 
-community and chat on <a href="https://join.slack.com/t/pypots-dev/shared_invite/zt-1gq6ufwsi-p0OZdW~e9UW_IA4_f1OfxA"><img alt="Slack Workspace" align="center" src="https://img.shields.io/badge/Slack-join_us!-grey?logo=slack&color=teal"></a>, 
-or create an issue. If you have any additional questions or have interests in collaboration, please take a look at 
+‼️ PyPOTS is currently under developing. If you like it and look forward to its growth, <ins>please give PyPOTS a star
+and watch it to keep you posted on its progress and to let me know that its development is meaningful</ins>.
+If you have any additional questions or have interests in collaboration, please take a look at
 [my GitHub profile](https://github.com/WenjieDu) and feel free to contact me 🤝.
 
 Thank you all for your attention! 😃

environment-dev.yml

@@ -41,3 +41,4 @@ dependencies:
  - conda-forge::black
  - conda-forge::flake8
  - conda-forge::pre-commit
+ - conda-forge::jupyterlab