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.github/workflows/python-package.yml

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- name: Upload updated requirements.txt
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.github/workflows/test-and-coverage.yml

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# Upload the coverage report as an artifact
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- name: Upload coverage report
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path: htmlcov

AUTHORS.rst

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* Chris Barnes <christopher.barnes@ucl.ac.uk>
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* Alex Fedorec <a.fedorec@ucl.ac.uk>
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* Pedro Fontanarrosa <pfontanarrosa@gmail.com>
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* Chania Clare <chania.clare.21@ucl.ac.uk>
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Contributors
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------------

CONTRIBUTING.rst

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* Use GitHub issues to suggest enhancements.
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* Be clear and detailed in your suggestion.
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Common Issues:
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----------------
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- My example doesn't show in documentation. Make sure that your Jupter notebook is in the correct folder, and more importantly, *that it has a title!*
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Additional Notes
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-----------------
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README.rst

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:target: https://codecov.io/gh/ucl-cssb/MIMIC
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Overview
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---------
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--------
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MIMIC: A Comprehensive Python Package for Simulating, Inferring, and Predicting
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Microbial Community Interactions
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benefiting the scientific and applied microbiology communities.
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Structure
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-----------
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---------
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The repository is organized into the following main directories:
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- `AUTHORS.rst`: A list of authors and contributors to the project.
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- `build/`: Contains files generated by the build process.
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- `CONTRIBUTING.rst`: Guidelines for contributing to the project.
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- `docs/`: Contains the project's documentation.
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- `dist/`: Contains distribution packages.
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- `docs/`: Contains the project's documentation and Sphinx sources.
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- `docs/source/notebooks/`: Jupyter notebooks categorized by model type.
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- `examples/`: Contains example scripts and notebooks demonstrating how to use the package.
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- `HISTORY.rst`: A log of changes made in each version of the project.
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- `LICENSE`: The license for the project.
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- `mimic/`: The main directory for the project's source code.
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- `data_imputation/`: Data imputation-related modules.
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- `model_infer/`: Inference models.
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- `model_simulate/`: Simulation models.
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- `utilities/`: Utility scripts.
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- `README.rst`: The main README file for the project, providing an overview and basic usage examples.
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- `environment.yml`: The Conda environment file for macOS and Ubuntu.
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- `environment_windows.yml`: The Conda environment file for Windows.
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- `requirements.in`: The pip requirements input file.
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- `requirements.txt`: The compiled list of Python dependencies.
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- `setup.py`: The build script for the project.
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- `tests/`: Contains unit tests for the project's code.
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- `.github/`: Contains GitHub templates and workflows.
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Installation
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--------------
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------------
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.. install-begin
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Prerequisites
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^^^^^^^^^^^^^
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- **Conda Package Manager**: We recommend using Conda to manage the environment due to dependencies that may not be available via pip.
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Installation Steps
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^^^^^^^^^^^^^^^^^^
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For macOS and Ubuntu
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""""""""""""""""""""
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5. **Run the Code**
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Refer to the `Usage`_ section below for instructions on how to run the code.
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Refer to the Usage section below for instructions on how to run the code.
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"""""""""""
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.. code-block:: bash
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conda activate mimic_env_windows
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conda activate mimic_env
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4. **Install the Package**
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Install the package in editable mode:
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.. code-block:: bash
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pip install -e .
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5. **Run the Code**
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Refer to the `Usage`_ section below for instructions on how to run the code.
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Refer to the Usage section below for instructions on how to run the code.
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Alternative Installation Using Pip Only
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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If you prefer to use pip without Conda, you can install the package and its dependencies by compiling `requirements.in` into `requirements.txt`:
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If you prefer to use pip without Conda, you can install the package and its dependencies by compiling ``requirements.in`` into ``requirements.txt``:
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.. code-block:: bash
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**Note**: This method may not install all dependencies correctly, especially if there are packages that are only available via Conda. We recommend using the Conda installation method for full functionality.
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Compilers
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A g++ compiler is required for the PyMC3 package.
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.. install-end
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-----
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.. usage-begin
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To get started with MIMIC, you can explore a variety of detailed examples and comprehensive documentation.
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- **Documentation**: Visit our [complete documentation](https://yourdocumentationurl.com) for detailed guides, API references, and more.
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- **Examples**: Check out our [Examples Directory](https://yourdocumentationurl.com/examples) which includes Jupyter notebooks demonstrating how to use MIMIC for different applications and scenarios.
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- **Documentation**: Visit our `complete documentation <https://ucl-cssb.github.io/MIMIC/>`_ for detailed guides and more.
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- **Examples**: Check out our `Examples Directory <https://github.com/ucl-cssb/MIMIC/tree/master/examples>`_ which includes Jupyter notebooks demonstrating how to use MIMIC for different applications and scenarios.
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The documentation is regularly updated with the latest information on usage, features, and examples to help you effectively utilize the MIMIC package in your research or applications.
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.. usage-end
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Contributing
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-------------
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------------
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We welcome contributions to the MIMIC project. Please refer to our `Contribution Guidelines <CONTRIBUTING.rst>`_ for more information.
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We welcome contributions to the MIMIC project. Please refer to our
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`Contribution Guidelines <CONTRIBUTING.rst>`_ for more information.
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License
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This project is licensed under the `LICENSE <LICENSE>`_.
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Acknowledgements
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----------------
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This project is based on methods proposed in `this paper <https://onlinelibrary.wiley.com/doi/full/10.1002/bies.201600188>`_.
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Contact
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For questions or feedback, please `contact us <mailto:christopher.barnes@ucl.ac.uk>`_.

docs/source/examples.rst

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Examples
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========
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Jupyter Notebook Examples by Model
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------------------------------------
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Consumer Resource Model (CRM)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. toctree::
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:maxdepth: 2
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notebooks/CRM/examples-sim-CRM
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Gaussian Processes (GP)
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~~~~~~~~~~~~~~~~~~~~~~~
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Multivariate Autoregressive Model (MVAR)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Multi-Model Analysis
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~~~~~~~~~~~~~~~~~~~~
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:maxdepth: 2
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notebooks/MultiModel/Herold/examples-Herold-VAR
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notebooks/MultiModel/Herold/examples-Herold-sVAR
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notebooks/MultiModel/Herold/examples_impute_data
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Vector Autoregression (VAR)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Generalized Lotka-Volterra (gLV)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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:maxdepth: 2
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notebooks/gLV/examples-Rutter-Dekker
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notebooks/gLV/examples-Stein
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notebooks/gLV/examples-bayes-gLV
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notebooks/gLV/examples-lasso-gLV
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notebooks/gLV/examples-ridge-gLV
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notebooks/gLV/examples-sim-gLV
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Generalized Metabolic Lotka-Volterra (gMLV)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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notebooks/gMLV/examples-ridge-lasso-gMLV
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notebooks/gMLV/examples-sim-gMLV
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