Installation
============

You can install **CaliBrain** using either **pip** or **Conda**, depending on your preferences.

We provide the following installation options:

- `pyproject.toml`: Standard modern pip-based installation (recommended).

- `requirements.txt`: Simple pip-based installation (optional).

- `environment.yml`: Conda-based environment installation (optional).

Choose the method that best fits your workflow.

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Pip Installation (Recommended)
-------------------------------

The recommended way to install CaliBrain is using `pip` with the `pyproject.toml` file.

First, clone the repository:

.. code-block:: bash

    git clone https://github.com/braindatalab/CaliBrain.git
    cd CaliBrain

Then install the package:

.. code-block:: bash

    pip install .

If you are actively developing the code and want automatic updates when you edit files:

.. code-block:: bash

    pip install -e .

This will install all dependencies defined inside `pyproject.toml`.

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Simple Pip Installation via requirements.txt
---------------------------------------------

Alternatively, you can install CaliBrain using a traditional `requirements.txt`:

.. code-block:: bash

    pip install -r requirements.txt

Note:
    - This method is simpler but does **not** capture full metadata (e.g., Python version compatibility).
    - Make sure your environment uses a supported Python version (>=3.8).

----

Conda Installation
-------------------

If you prefer to manage dependencies with **Conda**, you can create an isolated Conda environment using the provided `environment.yml` file.

First, clone the repository:

.. code-block:: bash

    git clone https://github.com/braindatalab/CaliBrain.git
    cd CaliBrain

Then create the environment:

.. code-block:: bash

    conda env create -f environment.yml

Activate the environment:

.. code-block:: bash

    conda activate calibrain

Finally, install CaliBrain into the activated environment:

.. code-block:: bash

    pip install .

This ensures that all Conda and pip dependencies are properly installed.

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Which method should I use?
---------------------------

- **Recommended**: Use pip with `pyproject.toml` for clean dependency management (`pip install .`).
- **If you prefer Conda**: Use `environment.yml` to create a Conda environment first.
- **If you just want quick pip install**: Use `requirements.txt`.

All methods lead to the same installed package — just choose the method that matches your ecosystem (pip-only or Conda).

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Minimum Requirements
---------------------

- Python >= 3.8
- Tested on Python 3.8, 3.9, 3.10
- Operating systems: Linux, macOS, Windows (WSL recommended for full compatibility)

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Optional Setup for Development
-------------------------------

If you plan to contribute to CaliBrain or run experiments:

.. code-block:: bash

    pip install -e .[dev]

(Development dependencies will be added soon.)