Skip to main content

No project description provided

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

winternlc-2.1.1.tar.gz (175.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

winternlc-2.1.1-py3-none-any.whl (34.8 kB view details)

Uploaded Python 3

File details

Details for the file winternlc-2.1.1.tar.gz.

File metadata

  • Download URL: winternlc-2.1.1.tar.gz
  • Upload date:
  • Size: 175.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for winternlc-2.1.1.tar.gz
Algorithm Hash digest
SHA256 edd555959010ec83329838a70ea347fdf92a4924f42ec413cd90609077d5b158
MD5 3bf4df4b010574c4e37b700bcbb7e4e3
BLAKE2b-256 7034949d7ce579beac96f0f6a9e3a14b1912a6479593aeab3069ae800bbb07fd

See more details on using hashes here.

File details

Details for the file winternlc-2.1.1-py3-none-any.whl.

File metadata

  • Download URL: winternlc-2.1.1-py3-none-any.whl
  • Upload date:
  • Size: 34.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for winternlc-2.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 b7986291226cf1ed17dfe6c92806d033701e59fd33586e2947a44c1e71ea617a
MD5 24fef230a7cf1592dbfe3185de20b51e
BLAKE2b-256 e58a0147dcd7b8989707912ed8cf741cdb220002c43cdc5ff6123c2caaf1346f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page