An object-oriented pipeline for ZTF image processing. Current capabilities include:
- Image coaddition
- Image subbtraction
- Multi-epoch subtractions
- Image alignment and registration
- Forced photometry
- Source detection and machine learning
- Record keeping (via postgres)
- Alert generation
- Image and catalog display
To install the package you can simply do
pip install zuds
However, there are some external tools you need for the image processing steps to work. The sections below present some methods for how you can install everything needed to run the pipeline.
Prerequisites:
This approach requires the conda executable to be installed on your system and used to manage your python and python packages.
Clone this repository, then run
bash build.conda.sh
to install zuds, sextractor, swarp, postgres, and cfitsio.
After you have completed this step, to install hotpants, cd into the hotpants directory and type make. Then copy the hotpants executable to your PATH. It should then be available to the zuds library.
A complete setup of the pipeline+database is available via docker-compose. Clone this repository, then run docker-compose up. A container running a jupyter notebook with the zuds pipeline and all dependencies installed should spin up, as well as a separate container for the database. Navigate to localhost:8174 and open up demo/demo.ipynb to start running a demo of the pipeline in a jupyter notebook.
Note: This approach is not recommended for Mac OSX users due to resource issues with docker on Mac.
You can download and build all of the prerequisite packages manually, then do pip install zuds to install the pipeline.