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 and finds technical anomalies and stellar properties from guidestars.
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. On the one hand, telescope-level anomalies could be detected (and, in principle, corrected) using this guide star data. On the other, this data also provides a "free" sky survey in the infrared (0.6 to 5 microns), on which short (~hours to days) time series of stars are recorded --- which one could "mine" if a pipeline existed for it to search for, e.g., stellar variability or even exoplanet transits: a true treasure chest. Here we present a first version of an automated, public quick-look time-series data processing pipeline for NIRISS FGS data. The pipeline 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('/Users/ddeal/JWST-Treasure-Chest/', pid=1534)
With our object spk
, we can start interpeting data from guidestars, such as making a plot of the tracked guidestars within a Program ID.
spk.guidestar_plot()
We can also plot the timeseries of fitted gaussian parameters (use spk.gauss2d_fit
to apply gaussian fitting to all guidestar frames) or the flux timeseries. Mnemonics from JWST technical events can be overplotted on any timeseries, such as high-gain antenna (HGA) movement or when the FGS tracks a new guidestar.
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. Get acquainted with spelunker
with the following example notebooks:
Licence and attribution
This project is under the MIT License, which can be viewed here.
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