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A ChRIS plugin to analyze the result produced by an LLD analysis

Version MIT License ci

pl-lld_chxr is a ChRIS ds plugin which takes in LLD (leg length discrepancy) analysis results (e.g. JSON files) and produces filtered summaries and annotated images as output.

Abstract

This plugin processes outputs from an LLD analysis pipeline and allows:

  • Filtering based on measurement differences (limb, tibia, femur)
  • Tag-based filtering and parsing
  • Selection of input files via glob patterns
  • Annotating output images with customizable text overlays

Parameter Reference

Input and Filtering Options

Argument Type Default Description
-f, --fileFilter string json Input file filter glob (e.g., json, *.json)

Measurement Settings

Argument Type Default Description
-m, --measurementsUnit string '' Accepted unit for length measurements
-d, --limbDifference float inf Maximum allowed difference between limbs
-b, --tibiaDifference float inf Maximum allowed tibia difference
-r, --femurDifference float inf Maximum allowed femur difference

Tag Parsing Options

Argument Type Default Description
-s, --splitToken string '' Token used to split input tags
-k, --splitKeyValue string '' Character used to split key-value pairs
-t, --tagInfo string '' Accepted tags and their values

Image Output Customization

Argument Type Default Description
--outputImageExtension string jpg Output image file format
-q, --addTextPos string top Text position on image (top or bottom)
--addText string '' Text to overlay on output image
--addTextSize float 5.0 Font size of overlay text
--addTextColor string white Text color
--addLineSpace float 0.5 Line spacing (smaller = tighter)

Version

Argument Description
-V, --version Print plugin version and exit

Installation

pl-lld_chxr is a ChRIS plugin, meaning it can run from either within ChRIS or the command-line.

Local Usage

To get started with local command-line usage, use Apptainer (a.k.a. Singularity) to run pl-lld_chxr as a container:

apptainer exec docker://fnndsc/pl-lld_chxr lld_chxr [--args values...] input/ output/

To print its available options, run:

apptainer exec docker://fnndsc/pl-lld_chxr lld_chxr --help

Examples

lld_chxr requires two positional arguments: a directory containing input data, and a directory where to create output data. First, create the input directory and move input data into it.

mkdir incoming/ outgoing/
mv some.dat other.dat incoming/
apptainer exec docker://fnndsc/pl-lld_chxr:latest lld_chxr [--args] incoming/ outgoing/

Development

Instructions for developers.

Building

Build a local container image:

docker build -t localhost/fnndsc/pl-lld_chxr .

Running

Mount the source code lld_chxr.py into a container to try out changes without rebuild.

docker run --rm -it --userns=host -u $(id -u):$(id -g) \
    -v $PWD/lld_chxr.py:/usr/local/lib/python3.12/site-packages/lld_chxr.py:ro \
    -v $PWD/in:/incoming:ro -v $PWD/out:/outgoing:rw -w /outgoing \
    localhost/fnndsc/pl-lld_chxr lld_chxr /incoming /outgoing

Testing

Run unit tests using pytest. It's recommended to rebuild the image to ensure that sources are up-to-date. Use the option --build-arg extras_require=dev to install extra dependencies for testing.

docker build -t localhost/fnndsc/pl-lld_chxr:dev --build-arg extras_require=dev .
docker run --rm -it localhost/fnndsc/pl-lld_chxr:dev pytest

Release

Steps for release can be automated by Github Actions. This section is about how to do those steps manually.

Increase Version Number

Increase the version number in setup.py and commit this file.

Push Container Image

Build and push an image tagged by the version. For example, for version 1.2.3:

docker build -t docker.io/fnndsc/pl-lld_chxr:1.2.3 .
docker push docker.io/fnndsc/pl-lld_chxr:1.2.3

Get JSON Representation

Run chris_plugin_info to produce a JSON description of this plugin, which can be uploaded to ChRIS.

docker run --rm docker.io/fnndsc/pl-lld_chxr:1.2.3 chris_plugin_info -d docker.io/fnndsc/pl-lld_chxr:1.2.3 > chris_plugin_info.json

Intructions on how to upload the plugin to ChRIS can be found here: https://chrisproject.org/docs/tutorials/upload_plugin

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A ChRIS plugin to analyze the result produced by an LLD analysis

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