FrankandLopes2025-RefBrain

This repo contains code for analysis and plotting of data in Frank, Lopes, Mohanta, Seckler, Lacroix, and Kronauer 2025.

Python environment and requirements

This repository contains Jupyter notebooks that use the scientific Python stack and image-processing libraries. Two simple ways to create an environment:

1. Using pip (recommended if you prefer venv/virtualenv):

   Create a virtual environment and install requirements:

   python -m venv .venv source .venv/bin/activate pip install --upgrade pip pip install -r requirements.txt

2. Using conda (recommended for binary image libs):

   conda env create -f environment.yml conda activate refbrain-env

If you add new dependencies while working in the repo, please update requirements.txt and environment.yml accordingly.

Lockfiles

For exact, reproducible installs the repository includes two lockfiles created from the active development environment:

• requirements.lock — pip-style lockfile with exact package==version pins. Use with pip-tools or pip-sync to recreate the same environment:

# create a fresh venv and install pinned packages
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.lock

• environment.lock.yml — conda-style lockfile (conda-forge) that pins key conda packages and contains a pip section for the remaining packages. Recreate with:

conda env create -f environment.lock.yml
conda activate frankandlopes-refbrain-lock

Note: The conda lockfile pins major binary packages (e.g., VTK/pyvista) and places pure-python packages under the pip section. If you prefer a different Python version or need to tighten package versions, edit the lockfile accordingly.

Quick notes

• Prefer conda-forge for binary packages (VTK/pyvista): these are provided as pre-built binaries on conda-forge and avoid long/fragile pip builds. Example: conda install -c conda-forge pyvista vtk.