Join Us

This project really needs YOU !!

How to join this project

You can join this project from the following ways. No matter which way you join this work, we greatly appreciate all your help. Thank you very much !!

  • Try this this toolbox. You can follow the procedures in Installation to install this toolbox. If you think this toolbox is useful, you may introduce our work to your friends. If you find bugs, you can report your issues in “Issues”.

  • Contribute to this toolbox. You can help us implement existing datasets or existing algorithms. You also can provide your own datasets or proposed algorithms to this toolbox. All your contributions will be displayed in Contributors. You can follow the below steps to contribute to this toolbox.

    Note

    Because we are also working on this toolbox, what you want to implement may be already finished but has not been published. To avoid the duplicate work, you may check the following work plan and contact us by Email (pikiptyw@gmail.com) before you want to add existing datasets or existing algorithms.

    1. Fork this this repository from the Github. You may read “Forking a repository” to learn how to do it. Simply speaking, you just need to click the “Fork” button in the repository page.

    2. After you fork this repository, you can edit it. You may face the following problems:

      • How to set up the python development enviroment? You may follow the below procedures:

        1. Install the vscode. In vscode, you may want to install the useful extension Python.

        2. Install the Anaconde. You can go to the Conda User Guide to learn how to use the conda.

        3. Install the required packages. Go to the repository dictionary. In your terminal, use conda env create -f environment.yml to create a new virtual enviroment called ssvep_analysis_toolbox. All packages will be automatically installed.

        4. In your terminal, you can use conda activate ssvep_analysis_toolbox to enable this virtual enviroment.

      • How to implement a dataset? Please follow How to define your own dataset class and ref the existing codes to implement your dataset.

      • How to implement a method? Please follow Common methods for all models and ref the existing codes to implement the required functions.

    3. After you finish your work. You can create a pull request to our dev branch (you may read “Create a pull request” to learn how to create a pull request). If we think your codes are satisfied, we will merge your codes to the main branch.

Work Plan