WenjieDu · WenjieDu · May 6, 2023 · May 6, 2023 · May 6, 2023 · May 6, 2023
diff --git a/.github/workflows/testing_daily.yml b/.github/workflows/testing_daily.yml
@@ -1,9 +1,6 @@
 name: Daily Testing
 
 on:
-    push:
-        branches:
-            - fix_dependency_error_in_daily_testing
     schedule:
         # https://crontab.guru. Run everyday at 0:00AM UTC, i.e. 08:00AM Beijing, i.e. 08:00PM Montreal (summer time)
         - cron: "0 0 * * *"
@@ -39,12 +36,13 @@ jobs:
                   which python
                   which pip
                   python -m pip install --upgrade pip
-                  pip install torch==${{ matrix.torch-version }} --extra-index-url https://download.pytorch.org/whl/cpu
+                  pip install torch==${{ matrix.torch-version }} -f https://download.pytorch.org/whl/cpu
                   python -c "import torch; print('PyTorch:', torch.__version__)"
 
             - name: Install other dependencies
               run: |
-                  pip install -e ".[optional]" -f "https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html"
+                  pip install pypots
+                  pip install torch-geometric torch-scatter torch-sparse -f "https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html"
                   pip install -e ".[dev]"
 
             - name: Fetch the test environment details

diff --git a/README.md b/README.md
@@ -72,24 +72,29 @@ It now supports a total of 119 open-source datasets.
 <br clear="left">
 
 The rest of this readme file is organized as follows:
-[**Installation**](#-installation),
-[**Usage**](#-usage),
-[**Available Algorithms**](#-available-algorithms),
-[**Citing PyPOTS**](#-citing-pypots),
-[**Community**](#-community),
-[**Contribution**](#-contribution).
+[**❖ Installation**](#-installation),
+[**❖ Usage**](#-usage),
+[**❖ Available Algorithms**](#-available-algorithms),
+[**❖ Citing PyPOTS**](#-citing-pypots),
+[**❖ Contribution**](#-contribution),
+[**❖ Community**](#-community).
 
 
 ## ❖ 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 is available on both [PyPI](https://pypi.python.org/pypi/pypots) and [Anaconda](https://anaconda.org/conda-forge/pypots).
+You can install PyPOTS as shown below:
 
-Install it with `conda install pypots`, you may need to specify the channel with option `-c conda-forge`
+``` bash
+# by pip
+pip install pypots            # the first time installation
+pip install pypots --upgrade  # update pypots to the latest version
 
-Install the latest release from PyPI:
-> pip install pypots
+# by conda
+conda install -c conda-forge pypots  # the first time installation
+conda update  -c conda-forge pypots  # update pypots to the latest version
+````
 
-or install from the source code with the latest features not officially released in a version:
+Alternatively, you can install from the latest source code with the latest features but may be not officially released yet:
 > pip install https://github.com/WenjieDu/PyPOTS/archive/main.zip
 
 
@@ -166,45 +171,34 @@ We are pursuing to publish a short paper introducing PyPOTS in prestigious acade
 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
-@misc{du2022PyPOTS,
+``` bibtex
+@software{Du2022PyPOTS,
 author = {Wenjie Du},
 title = {{PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series}},
 year = {2022},
-howpublished = {\url{https://github.com/wenjiedu/pypots}},
-url = {\url{https://github.com/wenjiedu/pypots}},
+howpublished = {\url{https://github.com/WenjieDu/PyPOTS}},
+url = {\url{https://github.com/WenjieDu/PyPOTS}},
 doi = {10.5281/zenodo.6823221},
 }
 ```
 
 or
 
-`Wenjie Du. (2022).
-PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series.
-Zenodo. https://doi.org/10.5281/zenodo.6823221`
+> 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). General discussion, Q&A, and our development team are here;
-- [LinkedIn](https://www.linkedin.com/company/pypots). Official announcements and news are here;
-- [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!
 
 By committing your code, you'll
 
-1. make your well-established model out-of-the-box for PyPOTS users to run. Take a look at our [inclusion criteria](https://docs.pypots.com/en/latest/faq.html#inclusion-criteria);
+1. make your well-established model out-of-the-box for PyPOTS users to run,
+   and help your work obtain more exposure and impact.
+   Take a look at our [inclusion criteria](https://docs.pypots.com/en/latest/faq.html#inclusion-criteria);
 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>;
+   <img align="center" src="https://contrib.rocks/image?repo=wenjiedu/pypots">;
 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.
@@ -227,6 +221,18 @@ Your star is your recognition to PyPOTS, and it matters!
 </details>
 
 
+## ❖ Community
+We care about the feedback from our users, so we're building PyPOTS community on
+
+- [Slack](https://pypots-dev.slack.com). General discussion, Q&A, and our development team are here;
+- [LinkedIn](https://www.linkedin.com/company/pypots). Official announcements and news are here;
+- [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 💪!
+
+
 ## ❖ Attention 👀
 ‼️ 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>.

diff --git a/docs/index.rst b/docs/index.rst
@@ -88,11 +88,11 @@ Visit `TSDB <https://github.com/WenjieDu/TSDB>`_ right now to know more about th
 
 The rest of this readme file is organized as follows:
 `❖ Installation <#id1>`_,
-`❖ Usage <#id2>`_,
-`❖ Available Algorithms <#id3>`_,
-`❖ Citing PyPOTS <#id13>`_,
-`❖ Community <#id14>`_,
-`❖ Contribution <#id15>`_.
+`❖ Usage <#id3>`_,
+`❖ Available Algorithms <#id4>`_,
+`❖ Citing PyPOTS <#id14>`_,
+`❖ Contribution <#id15>`_,
+`❖ Community <#id16>`_.
 
 
 ❖ Installation
@@ -148,30 +148,20 @@ notice this work. 🤗
 .. code-block:: bibtex
    :linenos:
 
-   @misc{du2022PyPOTS,
+   @software{Du2022PyPOTS,
    author = {Wenjie Du},
    title = {{PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series}},
-   howpublished = {\url{https://github.com/wenjiedu/pypots}},
    year = {2022},
+   howpublished = {\url{https://github.com/WenjieDu/PyPOTS}},
+   url = {\url{https://github.com/WenjieDu/PyPOTS}},
    doi = {10.5281/zenodo.6823221},
    }
 
 or
 
-   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>`_. General discussion, Q&A, and our development team are here;
-- `LinkedIn <https://www.linkedin.com/company/pypots>`_. Official announcements and news are here;
-- `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 💪!
+   Wenjie Du. (2022).
+   PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series.
+   Zenodo. https://doi.org/10.5281/zenodo.6823221
 
 
 ❖ Contribution
@@ -180,7 +170,9 @@ You're very welcome to contribute to this exciting project!
 
 By committing your code, you'll
 
-1. make your well-established model out-of-the-box for PyPOTS users to run. Take a look at our `inclusion criteria <https://docs.pypots.com/en/latest/faq.html#inclusion-criteria>`_;
+1. make your well-established model out-of-the-box for PyPOTS users to run,
+   and help your work obtain more exposure and impact.
+   Take a look at our `inclusion criteria <https://docs.pypots.com/en/latest/faq.html#inclusion-criteria>`_;
 2. be listed as one of `PyPOTS contributors <https://github.com/WenjieDu/PyPOTS/graphs/contributors>`_:
 3. get mentioned in our `release notes <https://github.com/WenjieDu/PyPOTS/releases>`_;
 
@@ -197,6 +189,18 @@ The lists of PyPOTS stargazers and forkers are shown below, and we're so proud t
    :target: https://github.com/WenjieDu/PyPOTS/network/members
 
 
+❖ Community
+^^^^^^^^^^^^
+We care about the feedback from our users, so we're building PyPOTS community on
+
+- `Slack <https://pypots-dev.slack.com>`_. General discussion, Q&A, and our development team are here;
+- `LinkedIn <https://www.linkedin.com/company/pypots>`_. Official announcements and news are here;
+- `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 💪!
+
 
 ❖ Attention 👀
 ^^^^^^^^^^^^^^^

diff --git a/docs/install.rst b/docs/install.rst
@@ -12,13 +12,13 @@ It is recommended to use **pip** or **conda** for PyPOTS installation as shown b
 
     # by pip
     pip install pypots            # the first time installation
-    pip install --upgrade pypots  # update pypots to the latest version
+    pip install pypots --upgrade  # update pypots to the latest version
 
 .. code-block:: bash
 
     # by conda
     conda install -c conda-forge pypots  # the first time installation
-    conda update -c conda-forge pypots   # update pypots to the latest version
+    conda update  -c conda-forge pypots  # update pypots to the latest version
 
 Alternatively, you can install from the latest source code which may be not officially released yet:
 

diff --git a/pypots/classification/brits/dataset.py → pypots/classification/brits/data.py b/pypots/classification/brits/dataset.py → pypots/classification/brits/data.py
@@ -7,7 +7,7 @@
 
 from typing import Union
 
-from pypots.imputation.brits.dataset import (
+from pypots.imputation.brits.data import (
     DatasetForBRITS as DatasetForBRITS_Imputation,
 )
 

diff --git a/pypots/classification/brits/model.py b/pypots/classification/brits/model.py
@@ -13,7 +13,7 @@
 from torch.utils.data import DataLoader
 
 from pypots.classification.base import BaseNNClassifier
-from pypots.classification.brits.dataset import DatasetForBRITS
+from pypots.classification.brits.data import DatasetForBRITS
 from pypots.classification.brits.modules import RITS
 from pypots.imputation.brits.model import (
     _BRITS as imputation_BRITS,

diff --git a/pypots/classification/grud/dataset.py → pypots/classification/grud/data.py b/pypots/classification/grud/dataset.py → pypots/classification/grud/data.py
diff --git a/pypots/classification/grud/model.py b/pypots/classification/grud/model.py
@@ -15,7 +15,7 @@
 from torch.utils.data import DataLoader
 
 from pypots.classification.base import BaseNNClassifier
-from pypots.classification.grud.dataset import DatasetForGRUD
+from pypots.classification.grud.data import DatasetForGRUD
 from pypots.imputation.brits.modules import TemporalDecay
 
 

diff --git a/pypots/classification/raindrop/dataset.py → pypots/classification/raindrop/data.py b/pypots/classification/raindrop/dataset.py → pypots/classification/raindrop/data.py
@@ -8,7 +8,7 @@
 
 from typing import Union
 
-from pypots.classification.grud.dataset import DatasetForGRUD
+from pypots.classification.grud.data import DatasetForGRUD
 
 
 class DatasetForRaindrop(DatasetForGRUD):

diff --git a/pypots/classification/raindrop/model.py b/pypots/classification/raindrop/model.py
@@ -24,7 +24,7 @@
 from torch.utils.data import DataLoader
 
 from pypots.classification.base import BaseNNClassifier
-from pypots.classification.grud.dataset import DatasetForGRUD
+from pypots.classification.grud.data import DatasetForGRUD
 from pypots.classification.raindrop.modules import (
     PositionalEncoding,
     ObservationPropagation,

diff --git a/pypots/clustering/crli/dataset.py → pypots/clustering/crli/data.py b/pypots/clustering/crli/dataset.py → pypots/clustering/crli/data.py
diff --git a/pypots/clustering/crli/model.py b/pypots/clustering/crli/model.py
@@ -17,7 +17,7 @@
 from torch.utils.data import DataLoader
 
 from pypots.clustering.base import BaseNNClusterer
-from pypots.clustering.crli.dataset import DatasetForCRLI
+from pypots.clustering.crli.data import DatasetForCRLI
 from pypots.clustering.crli.modules import Generator, Decoder, Discriminator
 from pypots.utils.logging import logger
 from pypots.utils.metrics import cal_mse

diff --git a/pypots/clustering/vader/dataset.py → pypots/clustering/vader/data.py b/pypots/clustering/vader/dataset.py → pypots/clustering/vader/data.py
@@ -8,7 +8,7 @@
 
 from typing import Union
 
-from pypots.clustering.crli.dataset import DatasetForCRLI
+from pypots.clustering.crli.data import DatasetForCRLI
 
 
 class DatasetForVaDER(DatasetForCRLI):

diff --git a/pypots/clustering/vader/model.py b/pypots/clustering/vader/model.py
@@ -24,7 +24,7 @@
     PeepholeLSTMCell,
     ImplicitImputation,
 )
-from pypots.clustering.vader.dataset import DatasetForVaDER
+from pypots.clustering.vader.data import DatasetForVaDER
 from pypots.utils.logging import logger
 from pypots.utils.metrics import cal_mse
 

diff --git a/pypots/imputation/brits/dataset.py → pypots/imputation/brits/data.py b/pypots/imputation/brits/dataset.py → pypots/imputation/brits/data.py
diff --git a/pypots/imputation/brits/model.py b/pypots/imputation/brits/model.py
@@ -18,7 +18,7 @@
 from torch.utils.data import DataLoader
 
 from pypots.imputation.base import BaseNNImputer
-from pypots.imputation.brits.dataset import DatasetForBRITS
+from pypots.imputation.brits.data import DatasetForBRITS
 from pypots.imputation.brits.modules import TemporalDecay, FeatureRegression
 from pypots.utils.metrics import cal_mae
 

diff --git a/pypots/imputation/saits/dataset.py → pypots/imputation/saits/data.py b/pypots/imputation/saits/dataset.py → pypots/imputation/saits/data.py
diff --git a/pypots/imputation/saits/model.py b/pypots/imputation/saits/model.py
@@ -20,7 +20,7 @@
 
 from pypots.data.base import BaseDataset
 from pypots.imputation.base import BaseNNImputer
-from pypots.imputation.saits.dataset import DatasetForSAITS
+from pypots.imputation.saits.data import DatasetForSAITS
 from pypots.imputation.transformer.modules import EncoderLayer, PositionalEncoding
 from pypots.utils.metrics import cal_mae
 

diff --git a/pypots/imputation/transformer/dataset.py → pypots/imputation/transformer/data.py b/pypots/imputation/transformer/dataset.py → pypots/imputation/transformer/data.py
@@ -7,7 +7,7 @@
 
 from typing import Union
 
-from pypots.imputation.saits.dataset import DatasetForSAITS
+from pypots.imputation.saits.data import DatasetForSAITS
 
 
 class DatasetForTransformer(DatasetForSAITS):

diff --git a/pypots/imputation/transformer/model.py b/pypots/imputation/transformer/model.py
@@ -19,7 +19,7 @@
 
 from pypots.data.base import BaseDataset
 from pypots.imputation.base import BaseNNImputer
-from pypots.imputation.transformer.dataset import DatasetForSAITS
+from pypots.imputation.transformer.data import DatasetForSAITS
 from pypots.imputation.transformer.modules import EncoderLayer, PositionalEncoding
 from pypots.utils.metrics import cal_mae