fringez 0.1.0

Removing atmospheric fringes from ZTF i-band images.

ztf-fringe-model

Getting Started

This repository generates fringe models for ZTF i-band images and subtracts that fringe model from science images, resulting in clean images with the fringes removed.

There are two main scripts for (1) generating fringe models and (2) removing fringes from science images using those models.

Generating Fringe Models

Fringe models are generated with the generate_fringe_model.py script. The models which will be generated are listed in model.py/return_estimators. The number of components in each model fit are set with the --n-components argument. Plots of the eigen-images can be generated for debugging with the --plots argument.

To generate fringe models:

1. Place images containing fringes into a directory. All images within the directory must have the same RCID. Models are made separately for each ZTF RCID. Image names are expected to begin with ztf and end with sciimg.fits.
2. From within this folder, execute python $PATH_TO_DIR/generate_fringe_model.py. By default the script will choose six components and will not generate debugging plots.
3. The ztf-fringe-model/models directory will now contain a model or models of the fringes, named fringe_{MODEL_NAME}_comp{N_COMPONENTS}.c{CID}_q{QID}.{DATE}.model. By default the script will only generate PCArandom models, but more models can be tested by editing the return_estimators function in model.py. The ztf-fringe-model/models directory will also contain a *.model_list file for each model listing the images that went into the creation of the model.

Downloading Fringe Models

Fringe models have been generated for ZTF i-band images and are stored on a NERSC web portal. To download these models, navigate to the models directory and execute the download_models.sh script. You will be asked to input a MODEL_DATE which signifies the version of the saved models. Models will be downloaded to disk and extracted from a tar.gz file. Models (*.model) and the lists of files that created them (*.model_lists) will end up in a models/{MODEL_DATE} folder.

Current model versions (and size after extraction):

• 20190618 (16 GB)

Generating Clean Images

Once a fringe model has been generated for each RCID, images can be cleaned with the remove_fringe.py script. Images can either be cleaned one at a time with the --single-image argument, or all images in a folder can be cleaned with the --all-images-in-folder argument. The fringe images used to create clean images can be saved to disk for debugging with the --debug argument.

To clean a single image:

From within the directory where the science image is located, execute python $PATH_TO_DIR/remove_fringe.py --single-image --image-name={IMAGE_NAME} --fringe-model-name={FRINGE_MODEL_NAME}. The --image-name and fringe-model-name arguments must be set when --single-image is selected.

To clean all images in a folder:

From within the directory where all of the science images are located, execute python $PATH_TO_DIR/remove_fringe.py --all-images-in-folder --fringe-model-folder={FRINGE_MODEL_FOLDER}. The --fringe-model-folder argument must be set when --all-images-in-folder is selected. Cleaning all images is run in --serial by default, but the --parallel argument can be selected as well. Parallelization is executed with mpi4py package and simply splits the list of images in the folder across the processes used to launch the remove_fringe.py script.

All clean images will have the same filename as the science images, but with the extension sciimg.clean.fits. By default the script will not save fringe images to disk. To do so, select the --debug argument.

Requirements

• Python 3

Authors

• Michael Medford [e-mail]
• Peter Nugent [e-mail]