Revision History

v1.0.4 (Dec 28, 2021)

  • check if im_star is int or float if not None

  • set nexposures = 1 for level1b using NIRCam() class function

  • deprecate nghxrg.py

  • add tutorial ipynb files

  • update api docs auto generation

  • use webbpsf_ext v1.0.4

v1.0.3 (Dec 23, 2021)

  • Minor updates to seamlessly generate new releases on PyPI and new docs on readthedocs

v1.0.1 (Dec 14, 2021)

  • Default OPD JWST_OTE_OPD_RevAA_prelaunch_predicted.fits

v1.0.0 (Nov 22, 2021)

  • Updates to work with WebbPSF v1 release candidate

  • Move PSF generation to new webbpsf_ext package (https://github.com/JarronL/webbpsf_ext)

  • Create DMS-like level1b FITS files using pipeline data models for imaging and coronagraphy

  • PSF coefficients now use Legendre polynomials by default

  • Create calibration files for each SCA (darks, IPC, noise, flats, linearity, etc)

  • Background roll-off at grism edges

  • SIAF-aware locations

v0.9.0beta (no release)

  • Updates to work with WebbPSF 0.9.0.

  • Start working on commissioning and DMS-like data

  • Add more advanced time-dependent detector effects

  • BEX model isochrones for low-mass companions from Linder et al (2019)

  • There was a pandemic…

v0.8.0beta (no release)

  • Updates to work with WebbPSF 0.8.0.

  • Phasing out support for Python 2

  • Add info on saturation limits in terms of surface brightness

  • Include option to create grism 2nd order

  • Detector pixel timing bugs

  • Field-dependent WFE extrapolated beyond FoV for better sampling diversity

  • Included field-dependent WFE for coronagraphy

  • Added wavelength dispersion of LW coronagraphic PSF

v0.7.0 (Jun 2018)

  • Did not make it out of development before WebbPSF 0.8.0 release.

  • Works with WebbPSF 0.7.0.

    • Field-dependent WFE

    • Image plane distortions

  • Implemented jwst_backgrounds (not required)

v0.6.5 (Mar 2018)

  • Fixed a critical bug where the off-axis PSF size was incorrect when performing WFE drift calculations.

v0.6.4 (Mar 2018)

  • Off-axis PSFs now get drifted in the same way as their on-axis counterparts.

  • Created an intermediate nrc_hci class to enable offsets of WFE drifted PSFs.

v0.6.3 (Mar 2018)

  • First PyPI release.

  • Effectively the same as 0.6.2, but better documentation of packaging and distributing.

v0.6.2 (Mar 2018)

  • Implemented coronagraphic wedges, including arbitrary offsets along bar

  • Renamed obs_coronagraphy to ~pynrc.obs_hci

    • Faster modeling of off-axis PSFs

    • Include coronagraphic features (e.g.: ND squares) in slope images

    • Roll subtracted images include option to use Roll1-Roll2

    • Fixed bug that was slowing down PSF convolution of disks

  • Can now generate docs directly from Jupyter notebooks using nbsphinx extension

  • Coronagraphic tutorials for docs

  • Create the source_spectrum class to fit spectra to observed photometry.

v0.6.0 (Dec 2017)

  • Support for Python 3 (mostly map, dict, and index fixes)

  • Updated code comments for sphinx and readthedocs documentation

  • Create setup.py install file

  • Modify grism PSF shapes due to aperture shape

  • Detector frames times based on ASIC microcode build 10

  • Headers for DMS data

  • Three major changes to PSF coefficients

    • coefficients based on module (SWA, SWB, LWA, LWB), rather than filter

    • WFE drift coefficient relations

    • field-dependent coefficient relation

v0.5.0 (Feb 2017)

  • Initial GitHub release

  • Match version numbering to WebbPSF equivalent

  • ND Acquisition mode

  • Ramp settings optimizer

  • Can now simulate ramps with detector noise

  • Query Euclid’s IPAC server for time/position-dependent Zodiacal emission

  • Added example Jupyter notebooks

v0.1.2 (Jan 2017)

  • Observations subclass for coronagraphs and direct imaging

v0.1.1 (Sep 2016)

  • Add support for LW slitless grism

  • Add support for extended sources

v0.1.0 (Aug 2016)

  • Rewrite of SimNRC and rename pynrc

  • Object oriented multiaccum, DetectorOps, and NIRCam classes

  • Create separate detector instances in NIRCam class

Planned Updates

FoV aware positions

  • Correct coronagraph field locations depending on Lyot optical wedge

  • Filter location relative offsets

Detector updates in ngNRC.py

  • Pixel glow (dark current) based on subarray size

  • Charge diffusion (esp for saturated pixels)

  • Persistence/latent image

  • Optical distortions

  • QE variations across a pixel’s surface

Observation Classes

  • Photometric time series (incl. weak lens)

  • Grism time series

  • Wide-field grism

  • Wide field imaging (esp. SW modules)

Miscellaneous

  • DHS mode