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SPECtral Image AnaLysis for SOSS

License: MIT License

Python 0.68% Makefile 0.01% Jupyter Notebook 99.31%

specialsoss's Introduction

specialsoss

Documentation Status

Updates

SPECtral Image AnaLysis for SOSS

Authors: Joe Filippazzo

This pure Python 3.6+ package performs optimal spectral extraction routines for the Single Object Slitless Spectroscopy (SOSS) mode of the Near-Infrared Imager and Slitless Spectrograph (NIRISS) instrument onboard the James Webb Space Telescope (JWST).

Additional resources:

Extracting Spectra from SOSS Observations

The headers in JWST data products provide almost all the information needed to perform the spectral extraction, making the path to your data the only required input. To load your SOSS exposure, simply do

# Imports
import numpy as np
from specialsoss import SossExposure
from pkg_resources import resource_filename

# Load the exposure
file = resource_filename('specialsoss', 'files/SUBSTRIP256_CLEAR_uncal.fits')
obs = SossExposure(file)

Now we can scroll through the ingested data by plotting the frames.

obs.plot_frames()

SOSS Frames

To run a spectral extraction routine, use the extract method with the name of the routine you would like to use. In this example, we'll use the vanilla column sum extraction.

obs.extract('sum', 'uncal')

Finally, we can see the extracted time-series spectra and the monochromatic lightcurves with:

obs.plot_results()

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specialsoss's Issues

Produce plot of lightcurve

User should be able to produce a plot of the total flux at a given wavelength across the TSO

Export file of extracted 1D spectra

Once the spectral extraction is finished, the user should be able to export a single FITS file containing a 1D spectrum for each order in each frame (nints*ngrps*2).

Produce plot of extracted spectra

Users should be able to produce a plot of the 1D extracted spectra in one or more frames with user-defined units.

Run spectral extraction on single frame of reduced data

Be able to run spectral extraction on observational data, which produces a 1D spectrum in user-defined units for orders 1 and 2

Create child classes of preloaded data for testing

Create a test class for ingested CV3 and awesimsoss data

Run spectral extraction on entire TSO

Once the extraction can be run on a single frame (#6 ), use multiprocessing to extract 1D spectra for each frame of the TSO.

Run method to locate the SOSS traces

User should be able to use a default trace location OR run a method that defines the trace location on the detector for orders 1 and 2 (in case of suboptimal pupil wheel rotation or TA)

Method to reduce uncal data with jwst pipeline

User should be able to ingest raw SOSS observations and run it through Level 2B before performing the spectral extraction.

Ingest SOSS ramp image data

Write class to ingest SOSS data and write test to verify.

Locate traces on the detector before extraction of each integration

Since the trace locations may change position from integration to integration, add option to locate the trace before each integration instead of just using predefined trace polynomials.

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