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Code for low-level WINTER data corrections, such as bad pixel masking and nonlinearity corrections

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winter-telescope/winternlc

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WINTER corrections

CI License: MIT Coverage Status

A package for implementing nonlinearity corrections for WINTER.

  • Current implementation is with a rational function with 8 parameters.
  • Also has the ability to generate/fit polynomial and other rational functions.

TODO: add more to the bad pixel masking.

  • Currently it only masks pixels which fail the rational fit or are tied high.
  • To add: dead pixel and highly nonlinear pixels to the mask.

Installation

pip install -e ".[dev]"
pre-commit install

Download corrections files

The corrections files are too large for GIT, but these are automatically downloaded from zenodo:

DOI

The file winter_corrections/config.py specifices which version and zenodo URL to grab. The current recommended versions are as follows:

  • v0.1: original corrections files from June 2024 with six operational sensors.
  • v1.1: latest correction files from September 2024 with five operational sensors.

Get Started

You can use winternlc directly from the command line.

winternlc-apply /path/to/data.fits

This will apply the nonlinearity correction to the data and save the corrected data to a new file.

You can also run the correction on multiple files at once.

winternlc-apply /path/to/data1.fits /path/to/data2.fits

Alternatively, you can specify a directory and all the files in the directory will be corrected.

winternlc-apply /path/to/directory

In all cases, you can also specify the output directory.

winternlc-apply /path/to/data.fits --output-dir /path/to/output

If you do not specify an output directory, the corrected files will be saved in the same directory as the input files.

See the help message for more information.

winternlc --help

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Code for low-level WINTER data corrections, such as bad pixel masking and nonlinearity corrections

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