Merge branch 'issues/CSD-316-beta-user-feedback' into develop

README.md

@@ -135,6 +135,12 @@ The authors of the original implementations integrated to this packages are:
 
 See the references in the documentation for more details.
 
+## Contributing
+
+Would you like to contribute to the development of **ProbINet**? Contributions are welcome and 
+appreciated! You can find detailed information on how to get started here: [Contributing Guide](https://mpi-is.github.io/probinet/contributing.html).
+
+
 ## License
 
 This project is licensed under the GNU GPL version 3 - see the [LICENSE](LICENSE.md) file for

docs/source/conf.py

@@ -48,6 +48,7 @@
     "myst_nb",  # add Jupyter notebooks
     "sphinx.ext.napoleon",  # 'sphinxcontrib.napoleon' is deprecated  # Google style docs
     "sphinxcontrib.bibtex",
+    "sphinx_copybutton",  # adds a copy button to code blocks
 ]
 autodoc_default_options = {
     "members": True,  # when set to True, Sphinx will automatically document all members
@@ -73,7 +74,7 @@
 nb_execution_timeout = 1000  # This is the timeout for executing a notebook cell
 
 # -- Options for  sphinxcontrib extension ---------------------------------------
-bibtex_bibfiles = ['references.bib']
+bibtex_bibfiles = ["references.bib"]
 
 # -- Options for HTML evaluation -------------------------------------------------
 

docs/source/contributing.rst

@@ -0,0 +1,123 @@
+Contributing
+============
+
+Thank you for your interest in contributing to **ProbINet**! Your contributions help improve the
+package and make it more useful for everyone. Please follow the steps below to get started.
+
+Getting Started
+---------------
+
+- Fork this repository to your GitHub account: `https://github.com/MPI-IS/probinet <https://github.com/MPI-IS/probinet>`_. You can fork it by clicking the "Fork" button in the top-right corner of the page.
+- Clone the forked repository to your local machine:
+
+  .. code-block:: bash
+
+     git clone https://github.com/<your-username>/probinet.git
+
+- Navigate to the project directory:
+
+  .. code-block:: bash
+
+     cd probinet
+
+- Add the original repository as a remote named ``upstream`` to keep your fork updated:
+
+  .. code-block:: bash
+
+     git remote add upstream https://github.com/MPI-IS/probinet.git
+
+Setting Up the Development Environment
+--------------------------------------
+
+This project uses ``pyproject.toml`` for dependency management. To set up a development environment:
+
+- Install the package with the ``.dev`` flag:
+
+  .. code-block:: bash
+
+     pip install ".[dev]"
+
+- Verify the installation by running the following command:
+
+  .. code-block:: bash
+
+     pip show probinet
+
+If the package is installed, this will display details about it, such as the version and installation location.
+
+Syncing Your Fork
+-----------------
+
+Before starting work on a new feature or bug fix, ensure your fork is up to date with the original repository:
+
+- Fetch the latest changes from the ``upstream`` repository:
+
+  .. code-block:: bash
+
+     git fetch upstream
+
+- Update your local ``main`` branch:
+
+  .. code-block:: bash
+
+     git checkout main
+     git merge upstream/main
+
+Making Changes
+--------------
+
+- Create a new branch for your contribution:
+
+  .. code-block:: bash
+
+     git checkout -b feature/your-feature-name
+
+- Make your changes in this branch. Ensure the code is:
+
+  - Well-documented.
+  - Aligned with the existing code style.
+
+- Add or update unit tests for your changes. You can see the existing tests in the ``tests`` directory.
+
+Running Tests
+-------------
+
+Tests are written using Python's built-in ``unittest`` framework.
+
+- Run all tests to verify your changes:
+
+  .. code-block:: bash
+
+     python -W ignore -m unittest discover
+
+Submitting Your Contribution
+----------------------------
+
+- Commit your changes with a clear and concise message:
+
+  .. code-block:: bash
+
+     git commit -m "Add description of your changes"
+
+- Push your changes to your fork:
+
+  .. code-block:: bash
+
+     git push origin feature/your-feature-name
+
+- Open a Pull Request (PR) to the **original repository**. Include:
+
+  - A detailed explanation of your changes.
+  - The issue number your PR addresses (if applicable).
+  - Any additional context or screenshots.
+
+  You can view all open and merged Pull Requests `here <https://github.com/MPI-IS/probinet/pulls>`_.
+
+
+Code of Conduct
+---------------
+
+By contributing to this repository, you agree to abide by our `Code of Conduct
+<https://policies.python.org/python.org/code-of-conduct/>`_.
+
+We appreciate your contributions and will review your Pull Request promptly!

docs/source/index.rst

@@ -27,6 +27,12 @@ Thank you for choosing ProbINet. We hope you enjoy using it!
    Cross-Validation And Anomaly Detection With The ACD Algorithm <tutorials/ACD.ipynb>
    Analyzing Network Data With Unknown Community Structure <tutorials/Unknown_structure.ipynb>
 
+.. toctree::
+    :maxdepth: 1
+    :caption: Contributing
+
+    How To Contribute <contributing.rst>
+
 .. toctree::
     :maxdepth: 1
     :caption: References

docs/source/tutorials/ACD.ipynb

@@ -52,7 +52,7 @@
     "\n",
     "In this section, we will load the synthetic data required for our analyses. We will start by \n",
     "importing the necessary libraries and defining the file path for the adjacency matrix, and then, \n",
-    "we will use the `import_data` method to read it."
+    "we will use the `build_adjacency_from_file` method to read it."
    ],
    "id": "600d6df30883a002"
   },
@@ -105,7 +105,7 @@
    "metadata": {},
    "cell_type": "markdown",
    "source": [
-    "As we have seen in previous tutorials, the `import_data` outputs a list of MultiDiGraph NetworkX \n",
+    "As we have seen in previous tutorials, the `build_adjacency_from_file` outputs a list of MultiDiGraph NetworkX\n",
     "objects, a graph adjacency tensor `B`, a transposed graph adjacency tensor `B_T`, and\n",
     " an array with values of entries `A[j, i]` given non-zero entry `(i, j)`. These outputs are \n",
     " essential for analyzing the network structure and performing further computations. \n",
@@ -180,7 +180,6 @@
     "- `cross_validation`: Functions for general cross-validation.\n",
     "- `masking`: Functions for masking data during cross-validation.\n",
     "- `labeling`: Functions for labeling data.\n",
-    "- `metrics`: Functions for computing evaluation metrics.\n",
     "- `main`: Entry point for the cross-validation process. Although each algorithm has its own cross-validation submodule, the `main` submodule provides a unified interface for running cross-validation for all algorithms.\n",
     "\n",
     "Additionally, the module provides specialized cross-validation submodules for different algorithms:\n",