Did I Find It?
difi is a simple package that takes pre-formatted linkage information from software such as MOPS, pytrax, or THOR and analyzes which objects have been found given a set of known labels (or truths). A key performance criteria is that difi needs to be fast by avoiding Python for loops and instead uses clever pandas.DataFrame manipulation.
difi can be downloaded directly from anaconda:
conda install -c moeyensj difi
Or, if preferred, installed into its own environment via:
conda create -n difi_py310 -c moeyensj difi python=3.10
difi is also available from the Python package index:
pip install difi
A Docker container with the latest version of the code can be pulled using:
docker pull moeyensj/difi:latest
To run the container:
docker run -it moeyensj/difi:latest
The difi code is installed the /projects directory, and is by default also installed in the container's Python installation.
Clone this repository using either ssh or https. Once cloned and downloaded, cd into the repository.
To install difi in its own conda environment please do the following:
conda create -n difi_py310 -c defaults -c conda-forge --file requirements.txt python=3.10
Or, to install difi in a pre-existing conda environment called difi_py310:
conda activate difi_py310
conda install -c defaults -c conda-forge --file requirements.txt
Or, to install difi software using pip:
pip install .
Or, if you would like to make an editable install then:
pip install -e .[tests]
You should now be able to start Python and import difi.
After cloning this repository, you can build a docker image that will allow you to develop the source code:
docker compose build difi
To run the docker container interatively with a terminal:
docker compose run -it difi
If you would like to contribute to difi, please make sure to initialize pre-commit. Pre-commit will automatically lint and format
the source code after any changes have been staged for a commit. To load the appropriate hooks please run:
pre-commit install
The example below can be found in greater detail in this Jupyter Notebook.