Warning This repository is experimental and bare-bones at the moment. It's not ready for general use, but discussions and contributions are welcome!

Celeritas Python interface

You can pronounce this package like "slurpee," or really any other way you want. This celerpy package will be the Python-based front end to the Celeritas binary codes and include a user-friendly execution interface, visualization components, and postprocessing utilities.

Development

To isolate the development environment, this project uses Poetry to manage dependencies, virtual environments, and lockfiles. A persistent development+CI environment is encoded into the distributed poetry.lock file. A simple makefile is included to configure and run for those not familiar with a Poetry envirnment workflow.

Setting up the first time

Install Poetry using Homebrew or pipx.

After cloning the celerpy repository and installing poetry, run make setup to:

• install all project and development dependencies from poetry.lock, and
• install pre-commit hooks.

After running make setup, run make install to install celerpy into the Poetry environment.

Development and testing

Activating the poetry environment will load the python version and all development dependencies. It is faster than manually invoking poetry run or using the included makefile.

$ eval $(poetry env activate)
$ pytest test/
$ mypy celerpy
$ poetry run pytest -vv -s test/test_process.py -k test_context

Pre-commit hooks

Style and linting should be performed automatically at every git commit after you run make pre-commit. They can also be invoked manually with pre-commit run. Use git commit --no-verify to disable temporarily for a particular commit. Pull requests automatically have their style checked and fixed via pre-commit.ci.

Release/versioning

Not yet implemented:

Visualizing a geometry

One of the current uses of celerpy is to launch the celer-geo visualization application from a Celeritas installation, send it geometry inputs, and render the resulting image in Python. The following example shows how to create an image from a GDML file:

from pathlib import Path
import matplotlib.pyplot as plt

from celerpy import model, visualize
from celerpy.settings import settings

# Point to a Celeritas installation prefix containing bin/celer-geo
settings.prefix_path = Path("path/to/celeritas/install")

# Input geometry
geometry = Path("path/to/geometry.gdml")

# Set the image coordinates, direction along the rendered x-axis, and pixels
# used for ray tracing
image = model.ImageInput(
    lower_left=[0, -100, -100],
    upper_right=[0, 100, 100],
    rightward=[0.0, 0.0, 1.0],
    vertical_pixels=1024
)

# Start celer-geo, trace the geometry, and plot the result
with visualize.CelerGeo.from_filename(geometry) as celer_geo:
    trace = visualize.Imager(celer_geo, image)
    fig, ax = plt.subplots()
    trace(ax)
    plt.show()