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JWST NIRCam ETC and Simulator

Project description

=====
pyNRC
=====

A JWST NIRCam ETC and Simulator
===============================

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:target: https://pypi.python.org/pypi/pynrc

.. image:: https://img.shields.io/travis/JarronL/pynrc.svg
:target: https://travis-ci.org/JarronL/pynrc

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:target: https://pynrc.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status

*Authors:* Jarron Leisenring (UA)

*Contributors:* Everett Schlawin (UA), Jonathan Fraine (STScI)

**!!Under Development!!**

pyNRC is a set of Python-based tools for planning observations with JWST NIRCam,
such as an ETC, a simple image slope simulator, and an enhanced data simulator.

While special attention has been placed on NIRCam coronagraphic modes,
this package also works for a variety of NIRCam observing modes including:
- direct imaging
- coronagraphic imaging
- weak lens imaging
- slitless grism spectroscopy
- DHS observations (TBI)

All PSFs are generated via WebbPSF (https://webbpsf.readthedocs.io) to reproduce
realistic JWST images and spectra.

Documentation can be found at https://pynrc.readthedocs.io.

**Note:** pyNRC enables more modes than are officially allowed by the Observatory,
(ie., filter + coronagraphic combinations, subarray sizes, etc.).
Just because you can do something with pyNRC does not mean it will be supported.
Check out https://jwst-docs.stsci.edu/display/JTI/NIRCam+Observing+Modes for more information.

Similar to some of its dependencies, pyNRC requires a host of input data files in
order to generate simulations. Due to the size of these files, they are not included
with this source distribution. Please see the documentation for instructions on how to
to download the required data files.


Revision History
================

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 :mod:`~pynrc.nrc_hci` class to enable
offsets of WFE drifted PSFs.


v0.6.3 (Mar 2018)
-----------------

- First PyPI release.
- Effectively the same as 0.6.3, but better documentation of packaging and distributing.


v0.6.2 (Mar 2018)
-----------------

- Implemented coronagraphic wedges, including arbitrary offsets along bar
- Renamed ``obs_coronagraphy`` to :mod:`~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 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


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