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whenxuan: fix the about in docs
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‎docs/source/_static/theme_overrides.css‎

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/* Navbar project badge (circular PNG). */
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.navbar-brand img {
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max-height: 2.2rem;
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max-height: 2.85rem;
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width: auto;
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}
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.navbar-brand .logo__title {
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font-size: 1.15rem;
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font-weight: 600;
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letter-spacing: 0.02em;
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}
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/* Hide the floating Read the Docs flyout so the header uses our logo.
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You can also uncheck Addons → Flyout in the RTD dashboard. */
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readthedocs-flyout {

‎docs/source/about/index.rst‎

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About
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=====
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Project
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-------
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PySDKit collects **signal decomposition** algorithms in one Python
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package so they can be used as feature-engineering tools next to NumPy,
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SciPy, and machine-learning stacks.
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SciPy, and machine-learning stacks. A non-stationary recording is
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treated as a sum of simpler modes; those modes can be plotted, scored
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(for example with entropy), or passed to a downstream model through the
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same ``fit_transform`` style as scikit-learn.
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The public API is **mode extraction**: EMD-style sifting, variational
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and chirp models, multivariate / image decompositions, and related
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time-frequency transforms, plus helpers in :mod:`pysdkit.data`,
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:mod:`pysdkit.plot`, :mod:`pysdkit.entropy`, and :mod:`pysdkit.tsa`.
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It is **not** a linear subspace-identification toolbox (state-space
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``A, B, C, D`` from IO data), and it is not a replacement for
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`PyWavelets <https://pywavelets.readthedocs.io/>`_. Install and the
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three-step API are in the :doc:`../user_guide/index`; the gallery is
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under :doc:`../auto_examples/index`.
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Citing PySDKit
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--------------
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Cite **two things** when a result depends on this library.
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1. **The algorithm.** Use the original paper of the method you called
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(EMD, VMD, MVMD, …). Class and module docstrings list those
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references.
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2. **The software.** There is no journal article for the package yet.
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Name the GitHub repository and the **version you actually ran**
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(``pip show pysdkit``, or ``pysdkit.__version__``):
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.. code-block:: text
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@software{pysdkit,
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author = {{PySDKit developers}},
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title = {{PySDKit}: signal decomposition in {Python}},
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url = {https://github.com/wwhenxuan/PySDKit},
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version = {X.Y.Z},
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}
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Replace ``X.Y.Z`` with the installed version. If a software paper
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(for example JOSS) appears later, prefer that citation.
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People
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------
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PySDKit is an open-source project started in April 2024. Releases,
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review, and the documentation are handled by the maintainers; algorithms
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and fixes come from a wider set of contributors.
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It is not a linear subspace-identification toolbox (state-space
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``A, B, C, D`` from IO data). The public API is mode extraction:
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EMD-style sifting, variational / chirp models, image decompositions,
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and related time-frequency transforms.
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.. list-table::
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:header-rows: 1
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:widths: 28 22 50
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- GitHub: https://github.com/wwhenxuan/PySDKit
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* - Name
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- Role
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- Contact
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* - `Whenxuan Wang <https://github.com/wwhenxuan>`_
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- Maintainer
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- wwhenxuan@gmail.com
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* - `RuiZhe Wang <https://github.com/changewam>`_
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- Maintainer
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- 3133986068@qq.com
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Package metadata also lists Rongkun Zhu, Kai Wu, Lei Wang, josefinez,
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Deeksha Manjunath, Yuan Feng, WenTong Zhao, and JacktheFowler. The
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complete, up-to-date list is the
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`GitHub contributors graph <https://github.com/wwhenxuan/PySDKit/graphs/contributors>`_.
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.. image:: https://contrib.rocks/image?repo=wwhenxuan/PySDKit
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:target: https://github.com/wwhenxuan/PySDKit/graphs/contributors
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:alt: GitHub contributors to PySDKit
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License and use
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---------------
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PySDKit is released under the
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`MIT License <https://github.com/wwhenxuan/PySDKit/blob/main/LICENSE>`_.
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You may use, copy, modify, and redistribute it in research, teaching,
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and commercial work, provided the copyright notice and permission
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notice are kept with substantial portions of the code.
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The implementations follow published papers and public reference code.
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Using a method here does not replace citing its authors. The software
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is provided “as is”, without warranty.
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Related work
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------------
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We thank researchers in signal processing for the algorithms themselves,
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and the Python projects that made a unified library practical:
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- `PyEMD <https://github.com/laszukdawid/PyEMD>`_
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- `vmdpy <https://github.com/vrcarva/vmdpy>`_ and
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`ewtpy <https://github.com/vrcarva/ewtpy>`_
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- `EWT-Python <https://github.com/bhurat/EWT-Python>`_
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- `MEMD-Python- <https://github.com/mariogrune/MEMD-Python->`_
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- `PyLMD <https://github.com/shownlin/PyLMD>`_
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- `PyWavelets <https://github.com/PyWavelets/pywt>`_
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- `signal-decomposition <https://github.com/cvxgrp/signal-decomposition>`_
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- `scikit-learn <https://scikit-learn.org/>`_,
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`scikit-image <https://scikit-image.org/>`_,
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`sktime <https://www.sktime.net/>`_, and
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`statsmodels <https://www.statsmodels.org/>`_
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- `SP_Lib <https://github.com/hustcxl/SP_Lib>`_ and
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`dsatools <https://github.com/MVRonkin/dsatools>`_
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Links
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-----
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- Source: https://github.com/wwhenxuan/PySDKit
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- Issues: https://github.com/wwhenxuan/PySDKit/issues
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- PyPI: https://pypi.org/project/PySDKit/
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- Docs: https://pysdkit.readthedocs.io/
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- Code of Conduct: https://github.com/wwhenxuan/PySDKit/blob/main/CODE_OF_CONDUCT.md
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Please cite the original papers of each algorithm you use; class and
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module docstrings point to those references.
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If you want to add an algorithm, tests, or a gallery example, see
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To add an algorithm, tests, or a gallery example, see
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:doc:`../development/index`.

‎docs/source/conf.py‎

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"logo": {
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"image_light": "_static/logo.png",
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"image_dark": "_static/logo.png",
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"text": "pysdkit",
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"text": "PYSDKIT",
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"alt_text": "PySDKit",
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"link": "https://pysdkit.readthedocs.io/",
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},

‎docs/source/index.rst‎

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:link: about/index
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:link-type: doc
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Project scope, citations, and where to find the source.
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License, how to cite, maintainers, and related projects.
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.. toctree::
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:hidden:

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