depiction

This package provides functionality to process and visualize mass-spectrometry imaging data. Currently, it requires your data to be available in the imzML format. The full pipeline is also in the process of being developed.

The project is structured in two general parts:

• depiction: implements the whole functionality to process the data
• depiction_targeted_preproc: implements a pipeline that based on some configuration file creates outputs like qc report and .ome.tiff files

This project is in an early state of development. If you are interested, it's best to reach out to us.

Setup dev environment

Currently, Python 3.12 is required, 3.13 is not compatible yet (missing wheels and e.g. numba/llvmlite).

Install with uv

The application uv provides both very fast installation of all required dependencies, as well as functionality to install a particular version of Python for you.

If you do not have uv installed yet, please consult their installation instructions.

To create a virtual environment using uv and install depiction in editable mode (i.e. changes to code are immediately available in the environment), run the following commands:

uv venv -p 3.12
uv pip install -e ".[dev]"

This creates the virtual environment in the .venv directory. To activate the environment in your shell, you need to source the correct activation script from .venv/bin, e.g. .venv/bin/activate for bash.

If you use an IDE you may want to point the IDE to the Python interpreter at .venv/bin/python.

Set up pre-commit

To check and format the code automatically, you can use pre-commit. In general, you can use the latest version.

pipx install pre-commit
pre-commit install

Now, the checks will be run automatically before each commit. The first time you might have some delay because the hooks are installed.

Test with nox

To run the tests the same way as in the CI, you can use nox. In general, you can use the latest version.

pipx install nox

Then you can run the checks with

nox

or more specifically:

nox -s tests

However, you can also run the tests with pytest or from your IDE if you are in the virtual environment.

Geometry Conventions

TODO these are not used consistently everywhere yet

Dimension names

• (2D) Points: (x, y)
• (2D) Images: (y, x, c)
• Sparse images: (i, c)
• Coordinates: (i, d) and each row corresponds to point ordering (i.e. (x, y))

TODO: y-axis direction, xarray conventions (dims, coords, etc.)