mesofield 0.4.0b0

Mesofield is an open-source image acquisition Python software package build for the Sipe Laboratory at Pennsylvania State University.

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Mesofield is a PyQt6-based framework for running real-time, multi-camera neuroscience experiments. It coordinates hardware via serial connections and MicroManager (through pymmcore-plus custom MDAEngines and multi-CMMCorePlus instancing) and manages experiment configuration, acquisition orchestration, and data logging. The project is aimed at laboratory use and is not a full production package; some specialised knowledge of device hardware and MicroManager device configuration is necessary to get started.

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Documentation

Documentation lives at gronemeyer.github.io/mesofield and is split by audience:

• Tutorial — the fastest path from a fresh conda env to a working acquisition on your hardware.
• User Guide — for experimenters running acquisitions: launching the GUI, writing experiment.json, interpreting the on-disk output.
• Developer Guide — for developers extending mesofield: custom devices, Procedure subclasses, frame processors, threading models.
• API Reference — auto-generated from docstrings.

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Quick start

conda create -n mesofield python=3.12 -y
conda activate mesofield
pip install -e .

Launch an acquisition by pointing at your rig — experiment.json is optional:

mesofield launch path/to/hardware.yaml      # rig only (author params in the GUI)
mesofield launch path/to/experiment.json    # rig + params (sibling hardware.yaml auto-detected)
mesofield launch path/to/experiment/        # a directory containing either

Scaffold a new experiment:

mesofield new my-experiment

For end-to-end setup, follow the Tutorial.

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System requirements

Tested on Windows 10/11. For multi-camera acquisition with large files we recommend ≥ 32 GB RAM, a 12th-gen Intel i7 or equivalent, and fast local NVMe storage for the experiment directory.

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License

MIT — see LICENSE.