Skip to main content

spelunker: a library to extract guidestar data and observe technical and stellar events

Project description

Spelunker — NIRISS FGS quicklook pipeline


spelunker is a package that assists on studying JWST FGS/NIRISS guidestar data.

Authors: Derod Deal (dealderod@ufl.edu), Néstor Espinoza (nespinoza@stsci.edu)

Statement of need

Every time JWST observes an object, it simultaneously observes a nearby star --- a so-called "guide star" --- with the NIRISS Fine Guidance Sensor (FGS) that is used to keep the telescope locked on the target of interest. While researchers typically focus on their science targets, the guide star data can be extremely interesting on its own right both to detect anomalies on science data, as well as to explore time-series data of guidestars themselves. spelunker provides an easy-to-access ("plug-and-play") library to access this guide star data. The library is able to generate time-series for several metrics of the FGS data in an automated fashion, including fluxes and PSF variations, along with derived products from those such as periodograms that can aid on their analysis given only a JWST program ID number.

Installation

To install spelunker, use pip install.

pip install spelunker

Using the library

Get started with spelunker with only two lines of code.

import spelunker

spk = spelunker.load(pid=1534)

This will download guidestar data for Program ID 1534; the spk object itself can then be used to explore this guidestar data! For example, let's make a plot of the guidestar time-series for the first minutes of this PID:

import matplotlib.pyplot as plt

# Convert times from MJD to minutes:
plt.plot( ( spk.fg_time - spk.fg_time[0] ) * 24 * 60, spk.fg_flux )

plt.xlim(0,10)
plt.xlabel('Time from start (minutes)')
plt.ylabel('Counts')

(See below on more information that can be extracted, including fitting 2D gaussians to each FGS integration!). We can even make a plot of the tracked guidestars within this Program ID:

spk.guidestar_plot()

Mnemonics from JWST technical events can be overplotted on any timeseries, such as high-gain antenna (HGA) movement or to identify if the FGS tracks a new guidestar if the jwstuser package is also installed:

import matplotlib.pyplot as plt

spk.mast_api_token = 'insert a token from auth.MAST here'

fig, ax = plt.subplots(figsize=(12,4),dpi=200)

ax = spk.mnemonics_local('GUIDESTAR')
ax = spk.mnemonics('SA_ZHGAUPST', 60067.84, 60067.9) 
ax.plot(spk.fg_time, spk.fg_flux)
plt.legend(loc=3)
plt.xlim(60067.84, 60067.9)
plt.show()

For more information on the tools under spelunker and how to get started, visit the quickstart guide or checkout our readthedocs. Get acquainted with spelunker with the following example notebooks:

Licence and attribution

This project is under the MIT License, which can be viewed here.

Acknowledgments

DD and NE would like to thank the STScI's Space Astronomy Summer Program (SASP) as well as the National Astronomy Consortium (NAC) program which made it possible for them to work together on this fantastic project!

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

spelunker-1.1.1.tar.gz (21.8 kB view details)

Uploaded Source

Built Distribution

spelunker-1.1.1-py3-none-any.whl (22.2 kB view details)

Uploaded Python 3

File details

Details for the file spelunker-1.1.1.tar.gz.

File metadata

  • Download URL: spelunker-1.1.1.tar.gz
  • Upload date:
  • Size: 21.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for spelunker-1.1.1.tar.gz
Algorithm Hash digest
SHA256 8551543277be232cea64be2a8f53cdc39eed8349fd1819644949403519045d19
MD5 d37bc4d644c04c3f0c23058fbb88f949
BLAKE2b-256 a1a037e4a2b2502d13d9e7bae6c03cb6d0021bbf48af878f29121f922ae171d6

See more details on using hashes here.

File details

Details for the file spelunker-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: spelunker-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 22.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for spelunker-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f1780a5f85854625e07272a874f9d1c95fd679b37c72bafa0055fa5c7ec50cfd
MD5 3582cded5ff0b35e396f68ca135db20a
BLAKE2b-256 de1db19ae9594cb1b915a2bc1bcedb729e538fee5c26c23a6435a04b6df6b94a

See more details on using hashes here.

Supported by

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