Repository: spacetelescope/mirage (language: python)

Issue:
Dependency update nov2022
Update dependencies for the 3.8 and 3.9 environments.
Update column names in moving target position table
Per https://github.com/spacetelescope/jwst/pull/6485 the mt_detector_x and mt_detector_y columns in the moving target position table are going to be renamed to mt_sci_x and mt_sci_y in the next release of the jwst package (1.3.4). Once that is released, we'll need to go into mirage and updated the column names in ramp_generator/moving_target_position_table.py 


Discussion / hints:

Fix patch:
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index ed11e1137..8e57c3654 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -19,12 +19,6 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: Unit tests Python 3.7
-            os: ubuntu-latest
-            python-version: 3.7
-            extras: test
-            test-command: pytest
-
           - name: Unit tests Python 3.8
             os: ubuntu-latest
             python-version: 3.8
@@ -39,7 +33,7 @@ jobs:
 
           - name: Build docs
             os: ubuntu-latest
-            python-version: 3.8
+            python-version: 3.9
             extras: docs
             test-command: sphinx-build docs docs/_build
 
diff --git a/.readthedocs.yml b/.readthedocs.yaml
similarity index 87%
rename from .readthedocs.yml
rename to .readthedocs.yaml
index dcfea8c48..43e6f2843 100644
--- a/.readthedocs.yml
+++ b/.readthedocs.yaml
@@ -1,4 +1,4 @@
-# .readthedocs.yml
+# .readthedocs.yaml
 # Read the Docs configuration file
 # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
 
@@ -8,11 +8,13 @@ version: 2
 build:
   os: "ubuntu-20.04"
   tools:
-    python: "3.8"
+    python: "3.9"
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
+  builder: html
   configuration: docs/conf.py
+  fail_on_warning: true
 
 # Optionally build your docs in additional formats such as PDF and ePub
 formats:
diff --git a/CHANGES.rst b/CHANGES.rst
index 64d6b11a1..d0a2339e1 100644
--- a/CHANGES.rst
+++ b/CHANGES.rst
@@ -1,3 +1,72 @@
+2.3.0
+=====
+
+APT
+---
+
+Bugfix in the APT xml reader for MOS programs with no dithers. (#806)
+
+
+CRDS Reference Files
+--------------------
+
+Remove references to the pixel area map from code and documentation, as this is no longer used. (#790)
+
+
+Packaging
+---------
+
+Update dependency list. Drop support for python 3.7. (#783)
+
+Remove python 3.6 environment file. (#784)
+
+
+Catalogs
+--------
+
+Update the import location of Irsa from astroquery.irsa to the new location of astroquery.ipac.irsa (#772)
+
+
+Dark Current
+------------
+
+Correct bug that was causing metadata from raw darks to not be read in correctly. Allow input raw darks with no ZEROFRAME extension as long as they were collected with a RAPID readout pattern. (#762)
+
+Remove JWST calibration pipeline config files, as they are non longer supported by the pipeline. (#791)
+
+
+Moving Targets
+--------------
+
+Updated the MOVING_TARGET_POSITION table from detector -> sci. (#757)
+
+Fix a bug that was resulting in moving target sources that were brighter than they should have been. (#807)
+
+
+Galaxy and Extended Source Position Angles
+------------------------------------------
+
+Fixed a bug that was causing incorrect position angles of galaxy and extended sources when PAV3 was non-zero. (#767)
+
+Fix galaxy/extended source rotation test (#778)
+
+
+NIRISS SOSS
+-----------
+
+Stores the input star and planet data (including the orbital parameters) to the output FITS files so users can make direct comparisons. The data is stored in a new 'STAR' and (when applicable) 'PLANET' extensions with the units and orbital params saved as header keywords. (#773)
+
+Moves hardcoded max_frames variable into SossSim.create keyword args so users can adjust memory allocation. (#775)
+
+Allow a user to generate a custom wavelength solution before generating SOSS simulations (#787)
+
+
+WFSS
+----
+
+Save "seed_cube" pickle files of point source, galaxy, and extended sources. These are then picked up by the disperser. This will allow overlapping sources to be treated correctly when everything is disersed. (#779)
+
+
 2.2.1
 =====
 
diff --git a/MANIFEST.in b/MANIFEST.in
index b45204985..60ecc3f85 100755
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -10,5 +10,9 @@ include mirage/config/saturation.cfg
 include mirage/config/superbias.cfg
 include mirage/config/xtalk20150303g0.errorcut.txt
 include tests/test_data/NIRISS/niriss_soss_substrip256_clear.yaml
+include mirage/reference_files/jband_transmission.dat
+include mirage/reference_files/alpha_lyr_stis_009.fits
 include examples/niriss_soss_example_data/*
+exclude mirage/reference_files/stellarmodels/atlas/*
+exclude mirage/reference_files/stellarmodels/phoenix/*
 exclude mirage/version.py
diff --git a/docs/catalog_creation.rst b/docs/catalog_creation.rst
index 09562a8b7..1c0e87273 100644
--- a/docs/catalog_creation.rst
+++ b/docs/catalog_creation.rst
@@ -95,8 +95,8 @@ The example below creates a galaxy catalog. The main difference compared to the
 
 .. _create_catalogs:
 
-Create_catalogs - create catalogs using online astronomical databases
----------------------------------------------------------------------
+Create_catalog - create catalogs using online astronomical databases
+--------------------------------------------------------------------
 
 The functions in this module use `astroquery <https://astroquery.readthedocs.io/en/latest/>`_ to search astronomical databases and retrieve source lists for a given pointing. In this way, a user can quickly generate reasonably realistic catalogs of point sources and galaxies for a given pointing.
 
@@ -106,7 +106,7 @@ By default, Mirage will query the ALLWISE source catalog as part of the call to
 
 ::
 
-    from mirage.catalogs import create_catalogs
+    from mirage.catalogs import create_catalog
 
     ra = 80.4  # degrees
     dec = -69.8  # degrees
diff --git a/docs/conf.py b/docs/conf.py
index 0cff80646..3b570bb45 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -8,6 +8,8 @@
 
 # -- Path setup --------------------------------------------------------------
 
+import stsci_rtd_theme
+
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
@@ -15,9 +17,7 @@
 # import os
 # import sys
 # sys.path.insert(0, os.path.abspath('.'))
-import mirage
 from mirage import __version__
-import stsci_rtd_theme
 
 # -- Project information -----------------------------------------------------
 
@@ -68,7 +68,7 @@
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
+language = 'en'
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
@@ -78,14 +78,16 @@
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = 'sphinx'
 
+# Enable nitpicky mode - which ensures that all references in the docs resolve.
+nitpicky = True
 
 # -- Options for HTML output -------------------------------------------------
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-#html_theme = 'alabaster'
-#html_theme = "sphinx_rtd_theme"
+# html_theme = 'alabaster'
+# html_theme = "sphinx_rtd_theme"
 html_theme = "stsci_rtd_theme"
 
 # Theme options are theme-specific and customize the look and feel of a theme
@@ -97,7 +99,7 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+# html_static_path = []
 html_theme_path = [stsci_rtd_theme.get_html_theme_path()]
 
 # Custom sidebar templates, must be a dictionary that maps document names
@@ -116,7 +118,6 @@
 # Output file base name for HTML help builder.
 htmlhelp_basename = 'MIRAGEdoc'
 
-
 # -- Options for LaTeX output ------------------------------------------------
 
 latex_elements = {
@@ -145,7 +146,6 @@
      'STScI  (Hilbert, Volk, Chambers, Sahlmann et al.)', 'manual'),
 ]
 
-
 # -- Options for manual page output ------------------------------------------
 
 # One entry per manual page. List of tuples
@@ -155,7 +155,6 @@
      [author], 1)
 ]
 
-
 # -- Options for Texinfo output ----------------------------------------------
 
 # Grouping the document tree into Texinfo files. List of tuples
@@ -167,5 +166,4 @@
      'Miscellaneous'),
 ]
 
-
 # -- Extension configuration -------------------------------------------------
diff --git a/docs/dark_preparation.rst b/docs/dark_preparation.rst
index dbbc85656..cbae98b55 100644
--- a/docs/dark_preparation.rst
+++ b/docs/dark_preparation.rst
@@ -8,7 +8,7 @@ After creating the seed image `mirage` moves on to preparing the input dark curr
 Adjust Number of Frames/Groups and Integrations
 -----------------------------------------------
 
-Frist the number of groups and integrations are adjusted to match the requested groups and integrations specified in the input yaml file. If the input dark has more groups or integrations than the requested output, the extras are removed. If additional groups or integrations are required above what is present in the dark file, then copies of existing groups/integrations are made and appended to the observation. In the case where extra groups are needed, copies of the existing groups are added to the signal in the final group of the existing dark, such that the dark current signals continue increasing in as they would in a longer integration.
+First the number of groups and integrations are adjusted to match the requested groups and integrations specified in the input yaml file. If the input dark has more groups or integrations than the requested output, the extras are removed. If additional groups or integrations are required above what is present in the dark file, then copies of existing groups/integrations are made and appended to the observation. In the case where extra groups are needed, copies of the existing groups are added to the signal in the final group of the existing dark, such that the dark current signals continue increasing in as they would in a longer integration.
 
 Put into Requested Readout Pattern
 ----------------------------------
diff --git a/docs/example_yaml.rst b/docs/example_yaml.rst
index 0c91d85c8..39177099b 100644
--- a/docs/example_yaml.rst
+++ b/docs/example_yaml.rst
@@ -50,7 +50,6 @@ Below is an example yaml input file for *Mirage*. The yaml file used as the prim
 	  ipc_: crds                 #File containing IPC kernel to apply
 	  invertIPC_: True           #Invert the IPC kernel before the convolution. True or False. Use True if the kernel is designed for the removal of IPC effects, like the JWST reference files are.
 	  occult_: None              #Occulting spots correction image
-	  pixelAreaMap_: crds        #Pixel area map for the detector. Used to introduce distortion into the output ramp.
 	  transmission_: crds        # Transmission image containing fractional throughput map. (e.g. to imprint occulters into fov
 	  subarray_defs_:   config   #File that contains a list of all possible subarray names and coordinates
 	  readpattdefs_:    config   #File that contains a list of all possible readout pattern names and associated NFRAME/NSKIP values
@@ -113,13 +112,6 @@ Below is an example yaml input file for *Mirage*. The yaml file used as the prim
 	  rotation_: 0.0                #y axis rotation (degrees E of N)
 	  tracking_: sidereal           #sidereal or non-sidereal
 
-	newRamp_:
-	  dq_configfile_: config          #config file used by JWST pipeline
-	  sat_configfile_: config         #config file used by JWST pipeline
-	  superbias_configfile_: config   #config file used by JWST pipeline
-	  refpix_configfile_: config      #config file used by JWST pipeline
-	  linear_configfile_: config      #config file used by JWST pipeline
-
 	Output_:
 	  file_: jw42424024002_01101_00001_nrcb5_uncal.fits   # Output filename
 	  directory_: ./                                # Directory in which to place output files
@@ -470,18 +462,6 @@ Occulting spot image
 
 This feature is not yet supported and should be set to **None**.
 
-.. _pixelAreaMap:
-
-Pixel area map
-++++++++++++++
-
-*Reffiles:pixelAreaMap*
-
-Fits file containing the pixel area map for the detector to be simulated. If provided, the pixel area map is multiplied into the seed image at a point when the seed image contains only extended sources. Point sources have the pixel area map applied to them at the time the PSF libraries were created via `webbpsf <https://webbpsf.readthedocs.io/en/stable/>`_. The pixel area map file must be in the format of the `JWST pixel area map reference file <https://jwst-pipeline.readthedocs.io/en/stable/jwst/photom/reference_files.html#area-reference-file>`_.
-
-.. hint::
-	Setting this entry equal to 'crds' will cause Mirage to query the Calibration Reference Database System (CRDS) for the appropriate file, and download that file if it is not already present in your CRDS cache.
-
 .. _transmission:
 
 Transmission Image
@@ -1048,67 +1028,6 @@ Telescope tracking
 Either 'sidereal' or 'non-sidereal' depending on the type of exposure. If it is set to non-sidereal then the exposure will be created as if JWST is
 tracking on the source in the :ref:`movingTargetToTrack <movingTargetToTrack>` catalog. Sources in the :ref:`pointsource <pointsource>`, :ref:`galaxyListFile <galaxyListFile>`, and :ref:`extended <extended>` catalogs will trail across the field of view over the course of the exposure.
 
-.. _newRamp:
-
-newRamp section
----------------
-
-This section of the input file lists JWST calibration pipeline-style configuration files that may be needed when preparing the simulated data. Copies of all of these configuration files are included in the ‘config’ subdirectory of the MIRAGE repository. Therefore, unless you wish to use your own set of configuration files, you can set these fields all to 'config'. This is the default behavior when creating yaml files via the :ref:`yaml generator <yaml_generator>`.
-
-.. hint::
-	In order to create your own set of pipeline configuration files, use the shell command:
-
-	> collect_pipeline_cfg /your/destination/directory
-
-.. _dq_configfile:
-
-DQ step configuration file
-++++++++++++++++++++++++++
-
-*newRamp:dq_configfile*
-
-Name of the JWST calibration pipeline configuration file to be used in the dq_init step when it is run on the raw dark current integration.
-
-
-.. _sat_configfile:
-
-Saturation step configuration file
-++++++++++++++++++++++++++++++++++
-
-*newRamp:sat_configfile*
-
-Name of the JWST calibration pipeline configuration file to be used in the saturation step when it is run on the raw dark current integration.
-
-.. _superbias_configfile:
-
-Superbias step configuration file
-+++++++++++++++++++++++++++++++++
-
-*newRamp:superbias_configfile*
-
-Name of the JWST calibration pipeline configuration file to be used in the superbias step when it is run on the raw dark current integration.
-
-.. _refpix_configfile:
-
-Reference pixel subtraction configuration file
-++++++++++++++++++++++++++++++++++++++++++++++
-
-*newRamp:refpix_configfile*
-
-Name of the JWST calibration pipeline configuration file to be used in the reference pixel subtraction step when it is run on the raw dark current integration.
-
-.. hint::
-    If you choose to use your own reference pixel correction configuration file, we recommend setting the **odd_even_rows** entry to False, as this correction is not typically performed on NIRCam, NISISS, or FGS data.
-
-.. _linear_configfile:
-
-Linearity step configuration file
-+++++++++++++++++++++++++++++++++
-
-*newRamp:linear_configfile*
-
-Name of the JWST calibration pipeline configuration file to be used in the linearity correction step when it is run on the raw dark current integration.
-
 .. _output:
 
 Output section
diff --git a/docs/install.rst b/docs/install.rst
index 2c56bdd43..e599c7102 100644
--- a/docs/install.rst
+++ b/docs/install.rst
@@ -4,7 +4,7 @@ There are two aspects to Mirage installation. First, the software itself must be
 must be downloaded. The preferred installation method is via :ref:`Pypi <pypi>`, as this is the latest stable version of the software.
 
 .. tip::
-    Mirage currently supports python 3.6, 3.7, 3.8, and 3.9. Support for 3.6 will be removed shortly, as the `jwst <https://github.com/spacetelescope/jwst>`_ package, which contains the JWST calibration pipeline, no longer supports 3.6.
+    Mirage currently supports python 3.8 and 3.9. Support for 3.6 and 3.7 has been removed, as the `jwst <https://github.com/spacetelescope/jwst>`_ package, which contains the JWST calibration pipeline, no longer supports python < 3.8.
 
 .. attention::
     **For those running Mac OSX 10.14:**
@@ -17,19 +17,14 @@ must be downloaded. The preferred installation method is via :ref:`Pypi <pypi>`,
 Install from Pypi
 -----------------
 
-Mirage is now hosted on `Pypi <https://pypi.org/project/mirage/>`_. To install the latest stable version of Mirage, use the commands below. In this example, we create
-a conda environment called "mirage" and then install the software into that environment. After installing Mirage, there are three packages which must be installed separately.
-These are: **jwst**, which is the JWST calibration pipeline software, and two packages that help to create dispersed data using the grisms.
+Mirage is hosted on `Pypi <https://pypi.org/project/mirage/>`_. To install the latest stable version of Mirage, use the commands below. In this example, we create
+a conda environment called "mirage" and then install the software into that environment.
 
 ::
 
-    conda create -n mirage python=3.7 -y
+    conda create -n mirage python=3.9 -y
     conda activate mirage
-    pip install healpy
     pip install mirage
-    pip install grismconf
-    pip install nircam_gsim
-    pip install jwst
 
 .. tip::
     Some of Mirage's dependencies rely on `Healpy <https://healpy.readthedocs.io/en/latest/>`_,. Healpy has released different wheels for different versions of Mac OSX. For example, healpy version 1.12.5
@@ -48,7 +43,7 @@ The installation procedure is nearly identical to the case of installing from Py
 
 ::
 
-    conda create -n mirage python=3.7 -y
+    conda create -n mirage python=3.9 -y
     conda activate mirage
     pip install git+https://github.com/spacetelescope/mirage
 
@@ -76,14 +71,10 @@ Installation can then be done via pip, which uses setup.py, or using the conda e
 To install using pip and setup.py:
 Create and activate a new environment. In this example we call the environment "mirage". Then move into the mirage directory, and install Mirage into the new environment::
 
-    conda create -n mirage python=3.7 -y
+    conda create -n mirage python=3.9 -y
     conda activate mirage
     cd mirage
-    pip install healpy
     pip install .
-    pip install grismconf
-    pip install nircam_gsim
-    pip install jwst
 
 .. tip::
     Some of Mirage's dependencies rely on `Healpy <https://healpy.readthedocs.io/en/latest/>`_,. Healpy has released different wheels for different versions of Mac OSX. For example, healpy version 1.12.5
@@ -99,38 +90,25 @@ Install via Environment File
 
 The Mirage repository also contains environment files, which can be used to create an environment with proper versions of all of Mirage's dependencies. After cloning the Mirage repository, the environment file (located within the top-level directory) can be used via the following commands. The *name* keyword is used to specify that the name of the environment. You can name the environment anything you like.
 
-Create a python 3.6 environment using the environment file, activate the environment, and install mirage::
+Create a python 3.8 environment using the environment file, activate the environment, and install mirage::
 
     cd mirage
-    conda env create -f environment_python_3.6.yml --name mirage_py3.6
-    conda activate mirage_py3.6
-    pip install .
-
-
-There are also environment files that can be used to create python 3.7, 3.8, or 3.9 environments::
-
-    cd mirage
-    conda env create -f environment_python_3.7.yml --name mirage_py3.7
-    conda activate mirage_py3.7
-    pip install .
-
-::
-
-    cd mirage
-    conda env create -f environment_python_3.8.yml --name mirage_py3.8
+    conda env create -f environment_python_3.8.yml
     conda activate mirage_py3.8
     pip install .
 
-::
+
+There is also an environment file that can be used to create python 3.9 environment::
 
     cd mirage
-    conda env create -f environment_python_3.9.yml --name mirage_py3.9
+    conda env create -f environment_python_3.9.yml
     conda activate mirage_py3.9
     pip install .
 
 
+
 .. tip::
-    For the python 3.6 and 3.7 cases, `webbpsf <https://webbpsf.readthedocs.io/en/latest/installation.html#requirements-installation>`_ is installed via conda. This means the associated data files will be downloaded and installed with the software itself. No manual installation of the data files is necessary. For the python 3.8 and 3.9 cases most packages, including webbpsf, are installed via pip (astroconda does not yet support python 3.8 and beyond). In this case you must `manually download the collection of webbpsf data files <https://webbpsf.readthedocs.io/en/latest/installation.html#installing-the-required-data-files>`_.
+    For the python 3.8 and 3.9 cases most packages, including webbpsf, are installed via pip (astroconda does not yet support python 3.8 and beyond). In this case you must `manually download the collection of webbpsf data files <https://webbpsf.readthedocs.io/en/latest/installation.html#installing-the-required-data-files>`_.
 
 
 .. _osx1014:
@@ -162,7 +140,7 @@ The installation errors are related to supporting Batman's ability to run calcul
     ::
 
         cd mirage
-        conda env create -f environment_python_3.7.yml --name mirage python=3.7
+        conda env create -f environment_python_3.9.yml
         conda activate mirage
         pip install .
         cd ../batman
diff --git a/docs/observation_generator.rst b/docs/observation_generator.rst
index bf113ef7a..fb0d63c22 100644
--- a/docs/observation_generator.rst
+++ b/docs/observation_generator.rst
@@ -36,7 +36,7 @@ Add Poisson Noise
 Flat Field Effects
 ------------------
 
-If the user provides an illumination flat or pixel flat in the `Reffiles:illumflat` or `Reffiles:pixelflat` yaml file entries, these files are read in and multiplied into the seed exposure.
+If the user provides an illumination flat or pixel flat in the `Reffiles:illumflat` or `Reffiles:pixelflat` yaml file entries, these files are read in and multiplied into the seed exposure. This will adjust the sources' brightness to account for pixel-to-pixel effects, including differences in pixel area across the detector.
 
 IPC
 ---
diff --git a/docs/reference_files.rst b/docs/reference_files.rst
index b3839f429..405932b70 100644
--- a/docs/reference_files.rst
+++ b/docs/reference_files.rst
@@ -14,7 +14,7 @@ After installing Mirage, these reference files can be downloaded using the *down
 
   from mirage.reference_files import downloader
   download_path = '/path/into/which/files/are/downlaoded/'
-  downloader.download_reffiles(download_path, instrument='all', dark_type='linearized', skip_darks=False, single_dark=False, skip_cosmic_rays=False, skip_psfs=False, skip_grism=False)
+  downloader.download_reffiles(download_path, instrument='all', dark_type='linearized', skip_darks=False, single_dark=False, skip_cosmic_rays=False, skip_psfs=False)
 
 The ``instrument`` keyword controls which subset of reference files are downloaded. You can give it the name of a single instrument, a string containing a comma-separated list of instruments, or the string ``all``, which will download reference files for NIRCam, NIRISS, and FGS.
 
diff --git a/docs/seed_images.rst b/docs/seed_images.rst
index 4ada02201..84d0f7377 100644
--- a/docs/seed_images.rst
+++ b/docs/seed_images.rst
@@ -31,7 +31,6 @@ For a given pointing, `jwst_backgrounds` will calculate the total expected backg
 
 Users can also provide a custom background through the use of an input fits file referenced in the "zodiacal" entry of the input yaml file. In this case, the contents of the file are read in and added to the seed image.
 
-Finally, `Mirage` uses the pixel area map to mimic the effects of distortion on the simulated sources. While the locations of the simulated sources within the seed image accurately account for distortion, the brightness of the sources are not affected. The seed image (minus any point sources) is multiplied by the pixel area map in order to adjust the extended sources’ brightness to account for the relative differences in pixel areas across the detector.
 
 .. _mosaic_input:
 
diff --git a/docs/yaml_generator.rst b/docs/yaml_generator.rst
index 96bdbfb30..fc864d623 100644
--- a/docs/yaml_generator.rst
+++ b/docs/yaml_generator.rst
@@ -366,7 +366,6 @@ Here is a view of the dictionary structure required when specifying reference fi
                            'gain':         {detector_name: 'reffile_name.fits'},
                            'distortion':   {detector_name: {filter: {exposure_type: 'reffile_name.asdf'}}},
                            'ipc':          {detector_name: 'reffile_name.fits'},
-                           'area':         {detector_name: {filter: {pupil: {exposure_type: 'reffile_name.asdf'}}}},
                            'transmission': {detector_name: {filter: {pupil: 'reffile_name.fits'}}},
                            'badpixmask':   {detector_name: 'reffile_name.fits'},
                            'pixelflat':    {detector_name: {filter: {pupil: 'reffile_name.fits'}}},
@@ -378,7 +377,6 @@ Here is a view of the dictionary structure required when specifying reference fi
                            'gain':       'reffile_name.fits',
                            'distortion': {pupil: {exposure_type: 'reffile_name.fits'}},
                            'ipc':        'reffile_name.fits',
-                           'area':       {filter: {pupil: {exposure_type: 'reffile_name.asdf'}}},
                            'transmission': {filter: {pupil: 'reffile_name.fits'}},
                            'badpixmask': 'reffile_name.fits',
                            'pixelflat':  {filter: {pupil: 'reffile_name.fits'}},
@@ -390,7 +388,6 @@ Here is a view of the dictionary structure required when specifying reference fi
                            'gain':         {detector_name: 'reffile_name.fits'},
                            'distortion':   {detector_name: {exposure_type: 'reffile_name.fits'}},
                            'ipc':          {detector_name: 'reffile_name.fits'},
-                           'area':         {detector_name: 'reffile_name.asdf'},
                            'transmission': {detector_name: 'reffile_name.fits'},
                            'badpixmask':   {detector_name: {exposure_type: 'reffile_name.fits'}},
                            'pixelflat':    {detector_name: {exposure_type: 'reffile_name.fits'}},
@@ -418,8 +415,6 @@ Here we show an example dictionary for a particular set of observations.
                                           'nrcb4': {'f444w':  {'nrc_image': 'my_reffiles/my_distortion_for_b4.asdf'}}},
                            'ipc':        {'nrcb5': 'my_reffiles/my_ipc_for_b5.fits',
                                           'nrcb4': 'my_reffiles/my_ipc_for_b4.fits'},
-                           'area':       {'nrcb5': {'f322w2': {'clear': {'nrc_image': 'my_reffiles/my_pam_for_b5.asdf'}}},
-                                          'nrcb4': {'f444w':  {'clear': {'nrc_image': 'my_reffiles/my_pam_for_b4.asdf'}}}},
                            'transmission': {'nrcb5': {'f356w': {'clear': 'my_reffiles/my_transmission_for_b5.fits'}}},
                            'badpixmask': {'nrcb5': 'my_reffiles/my_bpm_for_b5.fits',
                                           'nrcb4': 'my_reffiles/my_bpm_for_b4.fits'},
diff --git a/environment_python_3.6.yml b/environment_python_3.6.yml
deleted file mode 100644
index cbf600c56..000000000
--- a/environment_python_3.6.yml
+++ /dev/null
@@ -1,35 +0,0 @@
-channels:
-- http://ssb.stsci.edu/astroconda
-- conda-forge
-- defaults
-dependencies:
-- asdf>=2.1.0
-- astropy>=4.3.1
-- astroquery>=0.3.8
-- batman-package==2.4.8
-- crds>=7.4.1
-- gwcs>=0.11
-- healpy>=1.12.5
-- h5py>=2.8.0
-- ipython
-- jupyter
-- jwxml>=0.3.0
-- lxml>=3.6.4
-- matplotlib>=3.0.0
-- numpy>=1.16
-- photutils>=0.6
-- pytest>=3.8.1
-- python>=3.6,<3.7
-- scipy>=1.1.0
-- sphinx>=2.1
-- synphot>=0.2.0
-- webbpsf>=0.9.0
-- pyyaml>=5.1.2
-- pip:
-    - jwst-backgrounds>=1.1.1
-    - bokeh>=2.2.3
-    - pysiaf>=0.6.1
-    - hotsoss==0.1.7
-    - git+https://github.com/spacetelescope/jwst@0.16.2
-    - git+https://github.com/npirzkal/GRISMCONF
-    - git+https://github.com/npirzkal/NIRCAM_Gsim
diff --git a/environment_python_3.7.yml b/environment_python_3.7.yml
deleted file mode 100644
index d7cf845d3..000000000
--- a/environment_python_3.7.yml
+++ /dev/null
@@ -1,34 +0,0 @@
-channels:
-- http://ssb.stsci.edu/astroconda
-- conda-forge
-- defaults
-dependencies:
-- pip
-- python==3.7.7
-- webbpsf==0.9.1
-- numpy
-- pip:
-    - asdf==2.7.2
-    - astropy==4.3.1
-    - astroquery==0.4.1
-    - bokeh>=2.2.3
-    - batman-package==2.4.8
-    - crds==10.3.8
-    - grismconf==1.32
-    - hotsoss==0.1.7
-    - h5py==3.1.0
-    - ipython==7.20.0
-    - jupyter==1.0.0
-    - jwst==1.3.2
-    - jwst-backgrounds==1.1.2
-    - lxml==4.6.2
-    - matplotlib==3.3.4
-    - nircam_gsim==1.56
-    - numpy==1.20.1
-    - photutils>=1.1.0
-    - pysiaf==0.11.0
-    - pytest==6.2.2
-    - scipy==1.6.1
-    - sphinx==3.5.1
-    - synphot==1.0.1
-    - pyyaml==5.4.1
\ No newline at end of file
diff --git a/environment_python_3.8.yml b/environment_python_3.8.yml
index 1779af853..f0558a2b1 100644
--- a/environment_python_3.8.yml
+++ b/environment_python_3.8.yml
@@ -1,33 +1,35 @@
+name: mirage-py3.8
+
 channels:
 - http://ssb.stsci.edu/astroconda
 - conda-forge
 - defaults
 dependencies:
 - pip
-- python==3.8.5
+- python==3.8.13
 - pip:
-    - asdf==2.7.2
-    - astropy==4.3.1
-    - astroquery==0.4.1
-    - batman-package==2.4.8
-    - bokeh>=2.2.3
-    - crds==10.3.8
+    - asdf==2.13.0
+    - astropy==5.1.1
+    - astroquery==0.4.6
+    - batman-package==2.4.9
+    - bokeh==2.4.3
+    - crds==11.16.16
     - grismconf==1.32
     - hotsoss==0.1.7
-    - h5py==3.1.0
-    - ipython==7.20.0
+    - h5py==3.7.0
+    - ipython==8.6.0
     - jupyter==1.0.0
-    - jwst==1.3.2
+    - jwst==1.8.2
     - jwst-backgrounds==1.1.2
-    - lxml==4.6.2
-    - matplotlib==3.3.4
-    - nircam_gsim==1.56
-    - numpy==1.20.1
-    - photutils>=1.1.0
-    - pysiaf==0.11.0
-    - pytest==6.2.2
-    - scipy==1.6.1
-    - sphinx==3.5.1
-    - synphot==1.0.1
-    - pyyaml==5.4.1
-    - webbpsf==0.9.1
\ No newline at end of file
+    - lxml==4.9.1
+    - matplotlib==3.6.2
+    - nircam_gsim==1.60
+    - numpy==1.23.4
+    - photutils>=1.5.0
+    - pysiaf==0.18.0
+    - pytest==7.2.0
+    - scipy==1.9.3
+    - sphinx==5.3.0
+    - synphot==1.1.1
+    - pyyaml==6.0
+    - webbpsf==1.1.0
\ No newline at end of file
diff --git a/environment_python_3.9.yml b/environment_python_3.9.yml
index 8a70604ad..a8941c36b 100644
--- a/environment_python_3.9.yml
+++ b/environment_python_3.9.yml
@@ -1,33 +1,35 @@
+name: mirage-py3.9
+
 channels:
 - http://ssb.stsci.edu/astroconda
 - conda-forge
 - defaults
 dependencies:
 - pip
-- python==3.9.2
+- python==3.9.13
 - pip:
-    - asdf==2.7.2
-    - astropy==4.3.1
-    - astroquery==0.4.1
-    - batman-package==2.4.8
-    - bokeh>=2.2.3
-    - crds==10.3.8
+    - asdf==2.13.0
+    - astropy==5.1.1
+    - astroquery==0.4.6
+    - batman-package==2.4.9
+    - bokeh==2.4.3
+    - crds==11.16.16
     - grismconf==1.32
     - hotsoss==0.1.7
-    - h5py==3.1.0
-    - ipython==7.20.0
+    - h5py==3.7.0
+    - ipython==8.6.0
     - jupyter==1.0.0
-    - jwst==1.3.2
+    - jwst==1.8.2
     - jwst-backgrounds==1.1.2
-    - lxml==4.6.2
-    - matplotlib==3.3.4
-    - nircam_gsim==1.56
-    - numpy==1.20.1
-    - photutils>=1.1.0
-    - pysiaf==0.11.0
-    - pytest==6.2.2
-    - scipy==1.6.1
-    - sphinx==3.5.1
-    - synphot==1.0.1
-    - pyyaml==5.4.1
-    - webbpsf==0.9.1
\ No newline at end of file
+    - lxml==4.9.1
+    - matplotlib==3.6.2
+    - nircam_gsim==1.60
+    - numpy==1.23.4
+    - photutils>=1.5.0
+    - pysiaf==0.18.0
+    - pytest==7.2.0
+    - scipy==1.9.3
+    - sphinx==5.3.0
+    - synphot==1.1.1
+    - pyyaml==6.0
+    - webbpsf==1.1.0
\ No newline at end of file
diff --git a/mirage/apt/read_apt_xml.py b/mirage/apt/read_apt_xml.py
index ae3583d6b..9db755705 100755
--- a/mirage/apt/read_apt_xml.py
+++ b/mirage/apt/read_apt_xml.py
@@ -2320,7 +2320,13 @@ def read_nirspec_mos(self, template, template_name, obs, proposal_parameter_dict
         # If there are nods, treat those as subpixel dithers. But we won't
         # know about those until we are inside the exposure loop below.
 
-        dithertype = template.find(ns + 'DitherType').text
+        try:
+            dithertype = template.find(ns + 'DitherType').text
+        except AttributeError:
+            # In some cases where there is no dither, the DitherType entry
+            # is not present at all.
+            dithertype = 'none'
+
         if dithertype.lower() == 'none':
             number_of_primary_dithers = 1
         elif 'point-with-nircam' in dithertype.lower():
diff --git a/mirage/catalogs/catalog_generator.py b/mirage/catalogs/catalog_generator.py
index 2d6f3e9a9..6af014948 100644
--- a/mirage/catalogs/catalog_generator.py
+++ b/mirage/catalogs/catalog_generator.py
@@ -121,7 +121,13 @@ def add_catalog(self, catalog_to_add, magnitude_fill_value=99.):
         # Check the magnitude system from each and make sure they match
         current_mag_labels = list(self.magnitudes.keys())
         new_mag_labels = list(catalog_to_add.magnitudes.keys())
-        mag_sys = self.magnitudes[current_mag_labels[0]][0]
+
+        # Check if this is the first catalog
+        if len(self.magnitudes) > 0:
+            mag_sys = self.magnitudes[current_mag_labels[0]][0]
+        else:
+            mag_sys = catalog_to_add.magnitudes[new_mag_labels[0]][0]
+
         if mag_sys != catalog_to_add.magnitudes[new_mag_labels[0]][0]:
             logger.error("Magnitude systems of the two catalogs do not match. Cannot combine.")
 
diff --git a/mirage/catalogs/create_catalog.py b/mirage/catalogs/create_catalog.py
index 564b6679f..085fd9f2f 100644
--- a/mirage/catalogs/create_catalog.py
+++ b/mirage/catalogs/create_catalog.py
@@ -20,7 +20,7 @@
 from astropy.table import Table, join
 import astropy.units as u
 from astroquery.gaia import Gaia
-from astroquery.irsa import Irsa
+from astroquery.ipac.irsa import Irsa
 from pysiaf.utils.projection import deproject_from_tangent_plane
 
 from mirage.apt.apt_inputs import get_filters, ra_dec_update
@@ -270,7 +270,7 @@ def for_proposal(xml_filename, pointing_filename, point_source=True, extragalact
         for_obs_str = for_obs_str[0:-1]
         xml_base = os.path.basename(xml_filename).split('.xml')[0]
         if out_dir is None:
-            out_dir = os.path.dirname(xml_filename)
+            out_dir = os.path.dirname(os.path.abspath(xml_filename))
 
         starting_index = 1
 
@@ -313,37 +313,44 @@ def for_proposal(xml_filename, pointing_filename, point_source=True, extragalact
         if extragalactic:
             galaxy_cat = None
             for i, instrument in enumerate(instrument_filter_dict):
-                logger.info('\n--- Creating {} extragalactic catalog ---'.format(instrument))
-                filter_list = list(set(instrument_filter_dict[instrument]))
-                tmp_cat, tmp_seed = galaxy_background(mean_ra, mean_dec, 0., full_width, instrument,
-                                                      filter_list, boxflag=False, brightlimit=14.0,
-                                                      seed=galaxy_seed, starting_index=starting_index)
-
-                if galaxy_cat is None:
-                    galaxy_cat = copy.deepcopy(tmp_cat)
-                elif galaxy_cat is not None and tmp_cat is not None:
-                    galaxy_cat = combine_catalogs(galaxy_cat, tmp_cat, starting_index=starting_index)
-
-            starting_index += len(galaxy_cat)
-
-            if save_catalogs:
-                gal_catalog_name = 'galaxies_for_{}_observations_{}.cat'.format(xml_base, for_obs_str)
-
-                # Populate dictionary listing galaxy catalog name associated with each
-                # observation number
-                galaxy_catalog_mapping[str(observation)] = gal_catalog_name
-                for value in for_obs:
-                    galaxy_catalog_mapping[str(value)] = gal_catalog_name
-
-                full_catalog_path = os.path.join(out_dir, gal_catalog_name)
-                galaxy_cat.save(full_catalog_path)
-                logger.info('\nGALAXY CATALOG SAVED: {}'.format(full_catalog_path))
-                galaxy_catalog_names.append(full_catalog_path)
-
-            galaxy_catalog_list.append(galaxy_cat)
+                if instrument.lower() in ['nircam', 'niriss', 'fgs']:
+                    logger.info('\n--- Creating {} extragalactic catalog ---'.format(instrument))
+                    filter_list = list(set(instrument_filter_dict[instrument]))
+                    tmp_cat, tmp_seed = galaxy_background(mean_ra, mean_dec, 0., full_width, instrument,
+                                                          filter_list, boxflag=False, brightlimit=14.0,
+                                                          seed=galaxy_seed, starting_index=starting_index)
+
+                    if galaxy_cat is None:
+                        galaxy_cat = copy.deepcopy(tmp_cat)
+                    elif galaxy_cat is not None and tmp_cat is not None:
+                        galaxy_cat = combine_catalogs(galaxy_cat, tmp_cat, starting_index=starting_index)
+
+            # Protect against cases where the sky area is too large and the background galaxy
+            # search says that it will not proceed
+            if galaxy_cat is not None:
+                starting_index += len(galaxy_cat)
+
+                if save_catalogs:
+                    gal_catalog_name = 'galaxies_for_{}_observations_{}.cat'.format(xml_base, for_obs_str)
+
+                    # Populate dictionary listing galaxy catalog name associated with each
+                    # observation number
+                    galaxy_catalog_mapping[str(observation)] = gal_catalog_name
+                    for value in for_obs:
+                        galaxy_catalog_mapping[str(value)] = gal_catalog_name
+
+                    full_catalog_path = os.path.join(out_dir, gal_catalog_name)
+                    galaxy_cat.save(full_catalog_path)
+                    logger.info('\nGALAXY CATALOG SAVED: {}'.format(full_catalog_path))
+                    galaxy_catalog_names.append(full_catalog_path)
+
+                galaxy_catalog_list.append(galaxy_cat)
         else:
             galaxy_cat = None
 
+    logger.info((f'Catalog creation complete. Created point source catalogs: {ptsrc_catalog_names} ',
+                 f'and galaxy catalogs: {galaxy_catalog_names}'))
+
     return (ptsrc_catalog_list, galaxy_catalog_list, ptsrc_catalog_names, galaxy_catalog_names,
             ptsrc_catalog_mapping, galaxy_catalog_mapping)
 
@@ -1126,7 +1133,7 @@ def combine_and_interpolate(gaia_cat, gaia_2mass, gaia_2mass_crossref, gaia_wise
     twomassflag = [True] * n2mass2
     for n1 in range(n2mass2):
         for loop in range(len(gaia_2mass['ra'])):
-            if gaia_2mass['designation'][loop] == twomass_cat['designation'][n1]:
+            if gaia_2mass['DESIGNATION'][loop] == twomass_cat['designation'][n1]:
                 if ngaia2masscr[n1] >= 0:
                     twomassflag[n1] = False
     matchwise, gaiawiseinds, twomasswiseinds = wise_crossmatch(gaia_cat, gaia_wise, gaia_wise_crossref, wise_cat, twomass_cat)
@@ -1251,6 +1258,7 @@ def combine_and_interpolate(gaia_cat, gaia_2mass, gaia_2mass_crossref, gaia_wise
         outcat.add_magnitude_column(np.squeeze(out_magnitudes[:, n1]), column_name=column_value,
                                     magnitude_system='vegamag')
         n1 = n1+1
+
     return outcat
 
 
@@ -1281,9 +1289,9 @@ def twomass_crossmatch(gaia_cat, gaia_2mass, gaia_2mass_crossref, twomass_cat):
                     GAIA source in the main GAIA table, or a value of -10
                     where there is no match
     """
-    ntable1 = len(gaia_cat['designation'])
+    ntable1 = len(gaia_cat['ra'])
     ntable2 = len(gaia_2mass['ra'])
-    ntable3 = len(gaia_2mass_crossref['designation'])
+    ntable3 = len(gaia_2mass_crossref['ra'])
     ntable4 = len(twomass_cat['ra'])
     ngaia2mass = np.zeros((ntable2), dtype=np.int16) - 10
     ngaia2masscr = np.zeros((ntable4), dtype=np.int16) - 10
@@ -1293,7 +1301,7 @@ def twomass_crossmatch(gaia_cat, gaia_2mass, gaia_2mass_crossref, twomass_cat):
         namematch = []
         match1 = []
         for l1 in range(ntable3):
-            if gaia_2mass['designation'][loop] == gaia_2mass_crossref['designation_2'][l1]:
+            if gaia_2mass['DESIGNATION'][loop] == gaia_2mass_crossref['DESIGNATION'][l1]:
                 nmatch = nmatch + 1
                 namematch.append(gaia_2mass_crossref['designation'][l1])
                 match1.append(loop)
@@ -1308,7 +1316,7 @@ def twomass_crossmatch(gaia_cat, gaia_2mass, gaia_2mass_crossref, twomass_cat):
                 for l2 in range(ntable1):
                     gmag = 0.
                     irmag = -10000.0
-                    if gaia_cat['designation'][l2] == namematch[l1]:
+                    if gaia_cat['DESIGNATION'][l2] == namematch[l1]:
                         ra1 = gaia_cat['ra'][l2]
                         dec1 = gaia_cat['dec'][l2]
                         ra2 = gaia_2mass['ra'][match1[l1]]
@@ -1349,7 +1357,7 @@ def twomass_crossmatch(gaia_cat, gaia_2mass, gaia_2mass_crossref, twomass_cat):
     # index values.
     for loop in range(ntable4):
         for n1 in range(ntable2):
-            if twomass_cat['designation'][loop] == gaia_2mass['designation'][n1]:
+            if twomass_cat['designation'][loop] == gaia_2mass['DESIGNATION'][n1]:
                 ngaia2masscr[loop] = ngaia2mass[n1]
     return ngaia2masscr, ngaia2mass
 
@@ -1424,7 +1432,7 @@ def wise_crossmatch(gaia_cat, gaia_wise, gaia_wise_crossref, wise_cat, twomass_c
         if (d2d[loop].arcsec) < 0.4:
             matchwise[idx[loop]] = True
             for n2 in range(num_gaia):
-                if gaia_cat['designation'][n2] == gaia_wise_crossref['designation'][loop]:
+                if gaia_cat['DESIGNATION'][n2] == gaia_wise_crossref['DESIGNATION'][loop]:
                     gaiawiseinds[idx[loop]] = n2
                     break
     return matchwise, gaiawiseinds, twomasswiseinds
@@ -1938,7 +1946,7 @@ def query_GAIA_ptsrc_catalog(ra, dec, box_width):
     outvalues = {}
     logger.info('Searching the GAIA DR2 catalog')
     for key in data.keys():
-        job = Gaia.launch_job_async(data[key]['query'], dump_to_file=False)
+        job = Gaia.launch_job(data[key]['query'], dump_to_file=False)
         table = job.get_results()
         outvalues[key] = table
         logger.info('Retrieved {} sources for catalog {}'.format(len(table), key))
diff --git a/mirage/catalogs/model_atmosphere.py b/mirage/catalogs/model_atmosphere.py
new file mode 100644
index 000000000..654f38592
--- /dev/null
+++ b/mirage/catalogs/model_atmosphere.py
@@ -0,0 +1,506 @@
+#!/usr/stsci/pyssg/Python-2.7/bin/python
+"""
+Module to download and normalize stellar model atmospheres for soss_simulator.SossModelSim class
+
+Author: Nestor Espinoza
+"""
+
+import numpy as np
+import os
+from pkg_resources import resource_filename
+from scipy import interpolate, ndimage
+import shutil
+import urllib.request as request
+
+import astropy.units as q
+from astropy.io import fits
+from contextlib import closing
+
+
+def closest_value(input_value, possible_values):
+    """
+    This function calculates, given an input_value and an array of possible_values,
+    the closest value to input_value in the array.
+    Parameters
+    ----------
+    input_value: double
+         Input value to compare against possible_values.
+    possible_values: np.ndarray
+         Array of possible values to compare against input_value.
+    Returns
+    -------
+    double
+        Closest value on possible_values to input_value.
+    """
+    distance = np.abs(possible_values - input_value)
+    idx = np.where(distance == np.min(distance))[0]
+
+    return possible_values[idx[0]]
+
+
+def get_atlas_folder(feh):
+    """
+    Given input metallicity, this function defines the first part of the URL that will define what
+    file to download from the STScI website.
+    Parameters
+    ----------
+    feh: np.double
+         [Fe/H] of the desired spectrum.
+    Returns
+    -------
+    string
+        URL of ATLAS models closer to the input metallicity.
+    """
+    # Define closest possible metallicity from ATLAS models:
+    model_metallicity = closest_value(feh, np.array([-2.5, -2.0, -1.5, -1.0, -0.5, 0.0, 0.2, 0.5]))
+    met_sign = 'm'
+
+    # Define the sign before the filename, obtain absolute value if needed:
+    if model_metallicity >= 0.0:
+        met_sign = 'p'
+    else:
+        model_metallicity = np.abs(model_metallicity)
+
+    model_metallicity = ''.join(str(model_metallicity).split('.'))
+    fname = 'https://archive.stsci.edu/hlsps/reference-atlases/cdbs/grid/ck04models/ck{0:}{1:}/'.format(met_sign,
+                                                                                                        model_metallicity)
+
+    return fname
+
+
+def get_phoenix_folder(feh, alpha):
+    """
+    Given input metallicity and alpha-enhancement, this function defines the first part of the URL that will define what
+    file to download from the PHOENIX site.
+    Parameters
+    ----------
+    feh: np.double
+         [Fe/H] of the desired spectrum.
+    alpha: np.double
+         Alpha-enhancement of the desired spectrum.
+    Returns
+    -------
+    string
+        FTP URL of PHOENIX file with the closest properties to the input properties.
+    """
+    # Define closest possible metallicity from PHOENIX models:
+    model_metallicity = closest_value(feh, np.array([-4.0, -3.0, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0]))
+
+    # Same for alpha-enhancement:
+    model_alpha = closest_value(alpha, np.array([-0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.20]))
+    met_sign, alpha_sign = '-', '-'
+
+    # Define the sign before the filename, obtain absolute value if needed:
+    if model_metallicity > 0.0:
+        met_sign = '+'
+    else:
+        model_metallicity = np.abs(model_metallicity)
+    if model_alpha > 0.0:
+        alpha_sign = '+'
+    else:
+        model_alpha = np.abs(model_alpha)
+
+    # Create the folder name
+    if alpha == 0.0:
+        fname = 'ftp://phoenix.astro.physik.uni-goettingen.de/HiResFITS/PHOENIX-ACES-AGSS-COND-2011/Z{0:}{1:.1f}/'.format(
+            met_sign, model_metallicity)
+    else:
+        fname = 'ftp://phoenix.astro.physik.uni-goettingen.de/HiResFITS/PHOENIX-ACES-AGSS-COND-2011/Z{0:}{1:.1f}.Alpha={2:}{3:.2f}/'.format(
+            met_sign, model_metallicity, alpha_sign, model_alpha)
+
+    return fname
+
+
+def download(url, fname):
+    """
+    Download files from ftp server at url in filename fname. Obtained/modified from jfs here: https://stackoverflow.com/questions/11768214/python-download-a-file-over-an-ftp-server
+    Parameters
+    ----------
+    url: string
+        URL pointing to the file to download.
+    fname: string
+        Output filename of the file to download.
+    """
+    with closing(request.urlopen(url)) as r:
+        with open(fname, 'wb') as f:
+            shutil.copyfileobj(r, f)
+
+
+def get_vega():
+    """
+    This functions reads in the spectrum of Vega (Alpha Lyr) from CALSPEC
+    Returns
+    -------
+    astropy.units.quantity.Quantity
+        Wavelength in um of Vega spectrum.
+    astropy.units.quantity.Quantity
+        Flux in erg/s/cm2/A of Vega spectrum.
+    """
+    data = fits.getdata(resource_filename('mirage', 'reference_files/alpha_lyr_stis_009.fits'), header=False)
+
+    # Wavelength is in Angstroms, convert to microns to match the get_phoenix_model function.
+    # Flux is in Flambda (same as Phoenix; i.e., erg/s/cm2/A):
+    return (data['WAVELENGTH'] * q.angstrom).to(q.um), data['FLUX'] * (q.erg / q.s / q.cm ** 2 / q.AA)
+
+
+def read_phoenix_list(phoenix_model_list):
+    """
+    This function extracts filenames, effective temperatures and log-gs given a filename that contains a list of PHOENIX model filenames.
+    Parameters
+    ----------
+    phoenix_model_list: string
+         Filename of file containing, on each row, a PHOENIX model filename.
+    Returns
+    -------
+    np.ndarray
+        Array of PHOENIX model filenames
+    np.ndarray
+        Array containing the effective temperatures (K) of each PHOENIX model filename.
+    np.nadarray
+        Array containing the log-g (cgs) of each PHOENIX model filename.
+    """
+    fin = open(phoenix_model_list, 'r')
+    fnames = np.array([])
+    teffs = np.array([])
+    loggs = np.array([])
+
+    while True:
+        line = fin.readline()
+
+        if line != '':
+            fname = line.split()[-1]
+            teff, logg = fname.split('-')[:2]
+            fnames = np.append(fnames, fname)
+            teffs = np.append(teffs, np.double(teff[3:]))
+            loggs = np.append(loggs, np.double(logg))
+
+        else:
+            break
+
+    return fnames, teffs, loggs
+
+
+def get_phoenix_model(feh, alpha, teff, logg):
+    """
+    This function gets you the closest PHOENIX high-resolution model to the input stellar parameters from the Goettingen website (ftp://phoenix.astro.physik.uni-goettingen.de).
+    Parameters
+    ----------
+    feh: np.double
+         [Fe/H] of the desired spectrum.
+    alpha: np.double
+         Alpha-enhancement of the desired spectrum.
+    teff: np.double
+         Effective temperature (K) of the desired spectrum.
+    logg: np.double
+         Log-gravity (cgs) of the desired spectrum.
+    Returns
+    -------
+    np.ndarray
+        Wavelength in um of the closest spectrum to input properties.
+    np.ndarray
+        Surface flux in f-lambda of the closest spectrum to input properties in units of erg/s/cm**2/angstroms.
+    """
+    # First get grid corresponding to input Fe/H and alpha:
+    url_folder = get_phoenix_folder(feh, alpha)
+
+    # Now define details for filenames and folders. First, extract metallicity and alpha-enhancement in
+    # the PHOENIX filename format (and get rid of the "Z" in, e.g., "Z-1.0.Alpha=-0.20"):
+    phoenix_met_and_alpha = url_folder.split('/')[-2][1:]
+
+    # Define folders where we will save (1) all stellar model data and (2) all phoenix models:
+    stellarmodels_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/')
+    phoenix_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/phoenix/')
+    model_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/phoenix/' + phoenix_met_and_alpha + '/')
+
+    # Check if we even have stellarmodels folder created. Create it if not:
+    if not os.path.exists(stellarmodels_folder_path):
+        os.mkdir(stellarmodels_folder_path)
+
+    # Same for phoenix folder:
+    if not os.path.exists(phoenix_folder_path):
+        os.mkdir(phoenix_folder_path)
+
+    # Check if the current metallicity-alpha folder exists as well:
+    if not os.path.exists(model_folder_path):
+        os.mkdir(model_folder_path)
+
+    # Check if we have the PHOENIX wavelength solution. If not, download it:
+    if not os.path.exists(phoenix_folder_path + 'wavsol.fits'):
+        download('ftp://phoenix.astro.physik.uni-goettingen.de/HiResFITS/WAVE_PHOENIX-ACES-AGSS-COND-2011.fits',
+                      phoenix_folder_path + 'wavsol.fits')
+
+    # Extract wavelength solution:
+    wavelengths = fits.getdata(phoenix_folder_path + 'wavsol.fits')
+
+    # Now, figure out the closest model to the input stellar parameters. For this, first figure out the range of teff and logg
+    # for the current metallicity and alpha. For this, either retrieve from the system or download the full list of PHOENIX models
+    # for the current metallicity and alpha. If not already here, save it on the system:
+    phoenix_model_list = model_folder_path + 'model_list.txt'
+    if not os.path.exists(phoenix_model_list):
+        download(url_folder, phoenix_model_list)
+
+    # Extract information from this list:
+    model_names, possible_teffs, possible_loggs = read_phoenix_list(model_folder_path + 'model_list.txt')
+
+    # Search the closest to the input teff:
+    phoenix_teff = closest_value(teff, possible_teffs)
+
+    # Raise a warning in case the found teff is outside the PHOENIX model range, give some
+    # guidance on how to proceed:
+    if np.abs(phoenix_teff - teff) > 200.:
+        print(
+            '\t Warning: the input stellar effective temperature is outside the {0:}-{1:} K model range of PHOENIX models for {2:}.'.format(
+                np.min(possible_teffs),
+                np.max(possible_teffs), phoenix_met_and_alpha))
+
+        if 'Alpha' in phoenix_met_and_alpha:
+            print(
+                '\t Modelling using a {0:} K model. Using models without alpha-enhancement (alpha = 0.0), which range from 2300 to 12000 K would perhaps help find more suitable temperature models.'.format(
+                    phoenix_teff))
+
+        else:
+            print('\t Modelling using a {0:} K model.'.format(phoenix_teff))
+
+    # Same excercise for logg, given the teffs:
+    idx_logg = np.where(np.abs(phoenix_teff - possible_teffs) == 0.)[0]
+    phoenix_logg = closest_value(logg, possible_loggs[idx_logg])
+
+    # Select final model:
+    idx = np.where((np.abs(phoenix_teff - possible_teffs) == 0.) & (np.abs(possible_loggs == phoenix_logg)))[0]
+    phoenix_model, phoenix_logg = model_names[idx][0], possible_loggs[idx][0]
+
+    # Raise warning for logg as well:
+    if np.abs(phoenix_logg - logg) > 0.5:
+        print(
+        '\t Warning: the input stellar log-gravity is outside the {0:}-{1:} model range of PHOENIX models for {2:} and Teff {3:}.'.format(
+            np.min(possible_loggs[idx_logg]), np.max(possible_loggs[idx_logg]), phoenix_met_and_alpha, phoenix_teff))
+
+    # Check if we already have the downloaded model. If not, download the corresponding file:
+    if not os.path.exists(model_folder_path + phoenix_model):
+        print('\t PHOENIX stellar models for {0:} not found in {1:}. Downloading...'.format(phoenix_met_and_alpha,
+                                                                                            model_folder_path))
+        download(url_folder + phoenix_model, model_folder_path + phoenix_model)
+
+    # Once we have the file, simply extract the data:
+    print('\t Using the {0:} PHOENIX model (Teff {1:}, logg {2:}).'.format(phoenix_model, phoenix_teff, phoenix_logg))
+    flux = fits.getdata(model_folder_path + phoenix_model, header=False)
+
+    # Change units in order to match what is expected by the TSO modules:
+    wav = (wavelengths * q.angstrom).to(q.um)
+    flux = (flux * (q.erg / q.s / q.cm ** 2 / q.cm)).to(q.erg / q.s / q.cm ** 2 / q.AA)
+
+    return wav, flux
+
+
+def get_atlas_model(feh, teff, logg):
+    """
+    This function gets you the closest ATLAS9 Castelli and Kurucz model to the input stellar parameters from the STScI website
+    (http://www.stsci.edu/hst/instrumentation/reference-data-for-calibration-and-tools/astronomical-catalogs/castelli-and-kurucz-atlas).
+    Parameters
+    ----------
+    feh: np.double
+         [Fe/H] of the desired spectrum.
+    teff: np.double
+         Effective temperature (K) of the desired spectrum.
+    logg: np.double
+         Log-gravity (cgs) of the desired spectrum.
+    Returns
+    -------
+    np.ndarray
+        Wavelength in um of the closest spectrum to input properties.
+    np.ndarray
+        Surface flux in f-lambda of the closest spectrum to input properties in units of erg/s/cm**2/angstroms.
+    """
+    # First get grid corresponding to input Fe/H:
+    url_folder = get_atlas_folder(feh)
+
+    # Now define details for filenames and folders. Extract foldername with the metallicity info from the url_folder:
+    atlas_met = url_folder.split('/')[-2]
+
+    # Define folders where we will save (1) all stellar model data and (2) all atlas models:
+    stellarmodels_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/')
+    atlas_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/atlas/')
+    model_folder_path = resource_filename('mirage', 'reference_files/stellarmodels/atlas/' + atlas_met + '/')
+
+    # Check if we even have stellarmodels folder created. Create it if not:
+    if not os.path.exists(stellarmodels_folder_path):
+        os.mkdir(stellarmodels_folder_path)
+
+    # Same for phoenix folder:
+    if not os.path.exists(atlas_folder_path):
+        os.mkdir(atlas_folder_path)
+
+    # Check if the current metallicity-alpha folder exists as well:
+    if not os.path.exists(model_folder_path):
+        os.mkdir(model_folder_path)
+
+    # Define possible teff and loggs (thankfully, this is easier for ATLAS models):
+    possible_teffs, possible_loggs = np.append(np.arange(3500, 13250, 250), np.arange(14000, 51000, 1000)), np.arange(
+        0.0, 5.5, 0.5)
+
+    # Check the closest teff and logg to input ones:
+    atlas_teff = closest_value(teff, possible_teffs)
+    atlas_logg = closest_value(logg, possible_loggs)
+
+    # Raise a warning in case the found teff is outside the ATLAS model range, give some
+    # guidance on how to proceed:
+    if np.abs(atlas_teff - teff) > 200.:
+        print(
+            '\t Warning: the input stellar effective temperature is outside the {0:}-{1:} K model range of ATLAS models for {2:}.'.format(
+                np.min(possible_teffs),
+                np.max(possible_teffs), atlas_met))
+        print('\t Modelling using a {0:} K model.'.format(atlas_teff))
+
+    # Now, if not already in the system, download the model corresponding to the chosen teff:
+    atlas_fname = model_folder_path + atlas_met + '_{0:}.fits'.format(atlas_teff)
+    if not os.path.exists(atlas_fname):
+        download(url_folder + atlas_met + '_{0:}.fits'.format(atlas_teff), atlas_fname)
+
+    # Read the file:
+    d = fits.getdata(atlas_fname)
+
+    # This variable will save non-zero logg at the given temperatures. Only useful to report back to the user and/or input logg
+    # doesn't have data:
+    real_possible_loggs = np.array([])
+
+    # Check if the closest requested logg has any data. If not, check all possible loggs for non-zero data, and select the closest
+    # to the input logg that has data:
+    s_logg = 'g' + ''.join('{0:.1f}'.format(atlas_logg).split('.'))
+    if np.count_nonzero(d[s_logg]) != 0:
+        w, f = d['WAVELENGTH'], d[s_logg]
+    else:
+        real_possible_loggs = np.array([])
+        for loggs in possible_loggs:
+            s_logg = 'g' + ''.join('{0:.1f}'.format(loggs).split('.'))
+            if np.count_nonzero(d[s_logg]) != 0:
+                real_possible_loggs = np.append(real_possible_loggs, loggs)
+        atlas_logg = closest_value(logg, real_possible_loggs)
+        s_logg = 'g' + ''.join('{0:.1f}'.format(atlas_logg).split('.'))
+        w, f = d['WAVELENGTH'], d[s_logg]
+
+    # Raise warning for logg as well:
+    if np.abs(atlas_logg - logg) > 0.5:
+
+        # If real_possible_loggs is empty, calculate it:
+        if len(real_possible_loggs) == 0:
+            for loggs in possible_loggs:
+                s_logg = 'g' + ''.join('{0:.1f}'.format(loggs).split('.'))
+                if np.count_nonzero(d[s_logg]) != 0:
+                    real_possible_loggs = np.append(real_possible_loggs, loggs)
+
+        print(
+        '\t Warning: the input stellar log-gravity is outside the {0:}-{1:} model range of ATLAS models for {2:} and Teff {3:}.'.format(
+            np.min(real_possible_loggs), np.max(real_possible_loggs), atlas_met, atlas_teff))
+
+    # Change units in order to match what is expected by the TSO modules:
+    wav = (w * q.angstrom).to(q.um)
+    flux = f * q.erg / q.s / q.cm ** 2 / q.AA
+    return wav, flux
+
+
+def get_resolution(w, f):
+    """
+    This function returns the (w) wavelength (median) resolution of input spectra (f)
+    Parameters
+    ----------
+    w: np.ndarray
+        Wavelengths of the spectrum
+    f: np.ndarray
+        Value at the given wavelength (can be flux, transmission, etc.)
+    Returns
+    -------
+    np.double
+        The median resolution of the spectrum.
+    """
+    eff_wav = np.sum(w * f) / np.sum(f)
+    delta_wav = np.median(np.abs(np.diff(w)))
+
+    return eff_wav / delta_wav
+
+
+def spec_integral(input_w, input_f, wT, TT):
+    """
+    This function computes the integral of lambda*f*T divided by the integral of lambda*T, where
+    lambda is the wavelength, f the flux (in f-lambda) and T the transmission function. The input
+    stellar spectrum is given by wavelength w and flux f. The input filter response wavelengths
+    are given by wT and transmission curve by TT. It is assumed both w and wT are in the same
+    wavelength units.
+    Parameters
+    ----------
+    input_w: np.ndarray
+        Wavelengths of the input spectrum
+    input_f: np.ndarray
+        Flux (in f-lambda) of the input spectrum
+    wT: np.ndarray
+        Wavelength of the input transmission function
+    TT: np.ndarray
+        Spectral response function of the transmission function
+    Returns
+    -------
+    np.double
+        Value of the integral (over dlambda) of lambda*f*T divided by the integral (over dlambda) of lambda*T.
+    """
+    # If resolution of input spectra in the wavelength range of the response function
+    # is higher than it, degrade it to match the transmission function resolution. First,
+    # check that resolution of input spectra is indeed higher than the one of the
+    # transmisssion. Resolution of input transmission first:
+    min_wav, max_wav = np.min(wT), np.max(wT)
+    resT = get_resolution(wT, TT)
+
+    # Resolution of input spectra in the same wavelength range:
+    idx = np.where((input_w >= min_wav - 10) & (input_w <= max_wav + 10))[0]
+    res = get_resolution(input_w[idx], input_f[idx])
+
+    # If input spetrum resolution is larger, degrade:
+    if res > resT:
+
+        # This can be way quicker if we just take the gaussian weight *at* the evaluated
+        # points in the interpolation. TODO: make faster.
+        f = ndimage.gaussian_filter(input_f[idx], int(np.double(len(idx)) / np.double(len(wT))))
+        w = input_w[idx]
+    else:
+        w, f = input_w, input_f
+
+    interp_spectra = interpolate.interp1d(w, f, fill_value='extrapolate')
+    numerator = np.trapz(wT * interp_spectra(wT) * TT, x=wT)
+    denominator = np.trapz(wT * TT, x=wT)
+
+    return numerator / denominator
+
+
+def scale_spectrum(w, f, jmag):
+    """
+    This function scales an input spectrum to a given jmag. This follows eq. (8) in Casagrande et al. (2014, MNRAS, 444, 392).
+    Parameters
+    ----------
+    w: np.ndarray
+        Wavelengths of the spectrum in microns.
+    f: np.ndarray
+        Flux of the spectrum in erg/s/cm2/A.
+    jmag: np.double
+        2MASS J-magnitude to which we wish to re-scale the spectrum.
+    Returns
+    -------
+    np.ndarray
+        Rescaled spectrum at wavelength w.
+    """
+    # Get filter response (note wT is in microns):
+    wT, TT = np.loadtxt(resource_filename('mirage', 'reference_files/jband_transmission.dat'), unpack=True, usecols=(0, 1))
+
+    # Get spectrum of vega:
+    w_vega, f_vega = get_vega()
+
+    # Use those two to get the absolute flux calibration for Vega (left-most term in equation (9) in Casagrande et al., 2014).
+    # Multiply wavelengths by 1e4 as they are in microns (i.e., transform back to angstroms both wavelength ranges):
+    vega_weighted_flux = spec_integral(np.array(w_vega.to(q.AA)), np.array(f_vega), wT * 1e4, TT)
+
+    # J-band zero-point is thus (maginutde of Vega, m_*, obtained from Table 1 in Casagrande et al, 2014):
+    ZP = -0.001 + 2.5 * np.log10(vega_weighted_flux)
+
+    # Now compute (inverse?) bolometric correction for target star. For this, compute same integral as for vega, but for target:
+    target_weighted_flux = spec_integral(np.array(w) * 1e4, f, np.array(wT) * 1e4, TT)
+
+    # Get scaling factor for target spectrum (this ommits any extinction):
+    scaling_factor = 10 ** (-((jmag + 2.5 * np.log10(target_weighted_flux) - ZP) / 2.5))
+
+    return f * scaling_factor
\ No newline at end of file
diff --git a/mirage/config/dq_init.cfg b/mirage/config/dq_init.cfg
deleted file mode 100755
index f5cd1018b..000000000
--- a/mirage/config/dq_init.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-name = "dq_init"
-class = "jwst.dq_init.DQInitStep"
diff --git a/mirage/config/linearity.cfg b/mirage/config/linearity.cfg
deleted file mode 100755
index 2aed41d45..000000000
--- a/mirage/config/linearity.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-name = "linearity"
-class = "jwst.linearity.LinearityStep"
diff --git a/mirage/config/refpix.cfg b/mirage/config/refpix.cfg
deleted file mode 100755
index afc9d30c4..000000000
--- a/mirage/config/refpix.cfg
+++ /dev/null
@@ -1,7 +0,0 @@
-name = "refpix"
-class = "jwst.refpix.RefPixStep"
-odd_even_columns = True
-use_side_ref_pixels = True
-side_smoothing_length=11
-side_gain=1.0
-odd_even_rows = False
diff --git a/mirage/config/saturation.cfg b/mirage/config/saturation.cfg
deleted file mode 100755
index c9c968c5e..000000000
--- a/mirage/config/saturation.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-name = "saturation"
-class = "jwst.saturation.SaturationStep"
diff --git a/mirage/config/superbias.cfg b/mirage/config/superbias.cfg
deleted file mode 100755
index 4584d6f63..000000000
--- a/mirage/config/superbias.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-name = "superbias" 
-class = "jwst.superbias.SuperBiasStep"
diff --git a/mirage/dark/dark_prep.py b/mirage/dark/dark_prep.py
index e771909eb..2b3925c39 100755
--- a/mirage/dark/dark_prep.py
+++ b/mirage/dark/dark_prep.py
@@ -145,38 +145,12 @@ def check_params(self):
         # indicating the step should be skipped. Create a dictionary of steps
         # and populate with True or False
         self.runStep = {}
-        # self.runStep['linearity'] = self.check_run_step(self.params['Reffiles']['linearity'])
         self.runStep['badpixmask'] = self.check_run_step(self.params['Reffiles']['badpixmask'])
         self.runStep['linearized_darkfile'] = self.check_run_step(self.params['Reffiles']['linearized_darkfile'])
         self.runStep['saturation_lin_limit'] = self.check_run_step(self.params['Reffiles']['saturation'])
         self.runStep['superbias'] = self.check_run_step(self.params['Reffiles']['superbias'])
         self.runStep['linearity'] = self.check_run_step(self.params['Reffiles']['linearity'])
 
-        # If the pipeline is going to be used to create
-        # the linearized dark current ramp, make sure the
-        # specified configuration files are present.
-        if not self.runStep['linearized_darkfile']:
-            dqcheck = self.check_run_step(self.params['newRamp']['dq_configfile'])
-            if not dqcheck:
-                raise FileNotFoundError(("WARNING: DQ pipeline step configuration file not provided. "
-                                         "This file is needed to run the pipeline."))
-            satcheck = self.check_run_step(self.params['newRamp']['sat_configfile'])
-            if not satcheck:
-                raise FileNotFoundError(("WARNING: Saturation pipeline step configuration file not provided. "
-                                         "This file is needed to run the pipeline."))
-            sbcheck = self.check_run_step(self.params['newRamp']['superbias_configfile'])
-            if not sbcheck:
-                raise FileNotFoundError(("WARNING: Superbias pipeline step configuration file not provided. "
-                                        "This file is needed to run the pipeline."))
-            refpixcheck = self.check_run_step(self.params['newRamp']['refpix_configfile'])
-            if not refpixcheck:
-                raise FileNotFoundError(("WARNING: Refpix pipeline step configuration file not provided. "
-                                         "This file is needed to run the pipeline."))
-            lincheck = self.check_run_step(self.params['newRamp']['linear_configfile'])
-            if not lincheck:
-                raise FileNotFoundError(("WARNING: Linearity pipeline step configuration file not provided. "
-                                         "This file is needed to run the pipeline."))
-
     def check_run_step(self, filename):
         """Check to see if a filename exists in the parameter file
         or if it is set to none.
@@ -585,33 +559,24 @@ def linearize_dark(self, darkobj, save_refs=True):
 
         # Run the DQ_Init step
         if self.runStep['badpixmask']:
-            linDark = DQInitStep.call(dark,
-                                      config_file=self.params['newRamp']['dq_configfile'],
-                                      override_mask=self.params['Reffiles']['badpixmask'])
+            linDark = DQInitStep.call(dark, override_mask=self.params['Reffiles']['badpixmask'])
         else:
-            linDark = DQInitStep.call(dark, config_file=self.params['newRamp']['dq_configfile'])
+            linDark = DQInitStep.call(dark)
 
         # If the saturation map is provided, use it. If not, default to whatever is in CRDS
         if self.runStep['saturation_lin_limit']:
-            linDark = SaturationStep.call(linDark,
-                                          config_file=self.params['newRamp']['sat_configfile'],
-                                          override_saturation=self.params['Reffiles']['saturation'])
+            linDark = SaturationStep.call(linDark, override_saturation=self.params['Reffiles']['saturation'])
         else:
-            linDark = SaturationStep.call(linDark,
-                                          config_file=self.params['newRamp']['sat_configfile'])
+            linDark = SaturationStep.call(linDark)
 
         # If the superbias file is provided, use it. If not, default to whatever is in CRDS
         if self.runStep['superbias']:
-            linDark = SuperBiasStep.call(linDark,
-                                         config_file=self.params['newRamp']['superbias_configfile'],
-                                         override_superbias=self.params['Reffiles']['superbias'])
+            linDark = SuperBiasStep.call(linDark, override_superbias=self.params['Reffiles']['superbias'])
         else:
-            linDark = SuperBiasStep.call(linDark,
-                                         config_file=self.params['newRamp']['superbias_configfile'])
+            linDark = SuperBiasStep.call(linDark)
 
         # Reference pixel correction
-        linDark = RefPixStep.call(linDark,
-                                  config_file=self.params['newRamp']['refpix_configfile'])
+        linDark = RefPixStep.call(linDark)
 
         # Save a copy of the superbias- and reference pixel-subtracted
         # dark. This will be used later to add these effects back in
@@ -625,12 +590,9 @@ def linearize_dark(self, darkobj, save_refs=True):
         base_name = self.params['Output']['file'].split('/')[-1]
         linearoutfile = base_name[0:-5] + '_linearized_dark_current_ramp.fits'
         if self.runStep['linearity']:
-            linDark = LinearityStep.call(linDark,
-                                         config_file=self.params['newRamp']['linear_configfile'],
-                                         override_linearity=self.params['Reffiles']['linearity'])
+            linDark = LinearityStep.call(linDark, override_linearity=self.params['Reffiles']['linearity'])
         else:
-            linDark = LinearityStep.call(linDark,
-                                         config_file=self.params['newRamp']['linear_configfile'])
+            linDark = LinearityStep.call(linDark)
 
         # Now we need to put the data back into a read_fits object
         linDarkobj = read_fits.Read_fits()
@@ -1016,7 +978,7 @@ def prepare(self):
                 objname = self.basename + '_linear_dark_prep_object.fits'
             objname = os.path.join(self.params['Output']['directory'], objname)
             hl.writeto(objname, overwrite=True)
-            self.logger.info(("Linearized dark frame plus superbias and reference"
+            self.logger.info(("Linearized dark frame plus superbias and reference "
                               "pixel signals, as well as zeroframe, saved to {}. "
                               "This can be used as input to the observation "
                               "generator.".format(objname)))
diff --git a/mirage/psf/soss_trace.py b/mirage/psf/soss_trace.py
index 7c0bec976..873632b21 100644
--- a/mirage/psf/soss_trace.py
+++ b/mirage/psf/soss_trace.py
@@ -4,6 +4,7 @@
 Authors: Joe Filippazzo
 """
 
+from copy import copy
 import os
 from pkg_resources import resource_filename
 import multiprocessing
@@ -34,7 +35,7 @@ def calculate_psf_tilts():
     using all binned pixels in the given wavelength calibration file
     for both orders and save to file
     """
-    for order in [1, 2]:
+    for order in [1, 2, 3]:
 
         # Get the file
         psf_file = os.path.join(PSF_DIR, 'SOSS_PSF_tilt_order{}.npy'.format(order))
@@ -194,9 +195,13 @@ def generate_SOSS_psfs(filt):
         The filter to use, ['CLEAR', 'F277W']
     """
     try:
-
         import webbpsf
 
+    except ImportError:
+        raise ("Could not import `webbpsf` package. Functionality limited. Generating dummy file.")
+
+    try:
+
         # Get the file
         file = os.path.join(PSF_DIR, 'SOSS_{}_PSF.fits'.format(filt))
 
@@ -228,9 +233,10 @@ def generate_SOSS_psfs(filt):
         hdulist.writeto(file, overwrite=True)
         hdulist.close()
 
-    except (ImportError, OSError, IOError):
+    except NameError:
+
+        print("Something went wrong.")
 
-        print("Could not import `webbpsf` package. Functionality limited. Generating dummy file.")
 
 def get_angle(pf, p0=np.array([0, 0]), pi=None):
     """Compute angle (in degrees) for pf-p0-pi corner
@@ -413,16 +419,13 @@ def psf_tilts(order):
     Parameters
     ----------
     order: int
-        The order to use, [1, 2]
+        The order to use, [1, 2, 3]
 
     Returns
     -------
     np.ndarray
         The angle from the vertical of the psf in each of the 2048 columns
     """
-    if order not in [1, 2]:
-        raise ValueError('Only orders 1 and 2 are supported.')
-
     # Get the file
     psf_file = os.path.join(PSF_DIR, 'SOSS_PSF_tilt_order{}.npy'.format(order))
 
@@ -469,7 +472,7 @@ def put_psf_on_subarray(psf, y, frame_height=256):
     return frame
 
 
-def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False, mprocessing=True):
+def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False, mprocessing=True, wave_sol=None, dirname='default'):
     """
     Generate/retrieve a data cube of shape (3, 2048, 76, 76) which is a
     76x76 pixel psf for 2048 wavelengths for each trace order. The PSFs
@@ -488,18 +491,39 @@ def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False,
         Generate a new cube
     mprocessing: bool
         Use multiprocessing
+    wave_sol: sequence (optional)
+        The user provided wavelength solutions for orders 1, 2, and 3
+    dirname: str (optional)
+        The target subdirectory name for the PSFs that use a custom wavelength solution
 
     Returns
     -------
     np.ndarray
         An array of the SOSS psf at 2048 wavelengths for each order
     """
+    # Check if it's a custom wavelength solution
+    psf_loc = copy(PSF_DIR)
+    if dirname != 'default':
+        dirpath = os.path.join(PSF_DIR, dirname)
+        if not os.path.exists(dirpath):
+            os.system('mkdir {}'.format(dirpath))
+        psf_loc = psf_loc.replace('soss_psfs', 'soss_psfs/{}'.format(dirname))
+
     if generate:
 
-        print('Coffee time! This takes about 5 minutes.')
+        print('This takes about 2 minutes.')
+
+        # Default wavelengths
+        if wave_sol is None:
+            wavelengths = np.mean(utils.wave_solutions(subarray), axis=1)[:3 if filt == 'CLEAR' else 1]
 
-        # Get the wavelengths
-        wavelengths = np.mean(utils.wave_solutions(subarray), axis=1)[:2 if filt == 'CLEAR' else 1]
+        # Or user provided
+        else:
+            if wave_sol.shape != (3, 2048):
+                raise TypeError("'wave_sol' input must be an array of shape (3, 2048)")
+            wavelengths = wave_sol
+
+        # Get trace polynomial coefficients
         coeffs = locate_trace.trace_polynomial(subarray)
 
         # Get the file
@@ -519,8 +543,8 @@ def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False,
             # Evaluate the trace polynomial in each column to get the y-position of the trace center
             trace_centers = np.polyval(coeffs[n], trace_cols)
 
-            # Don't calculate order2 for F277W or order 3 for either
-            if (n == 1 and filt.lower() == 'f277w') or n == 2:
+            # Don't calculate order2 or order 3 for F277W
+            if n > 0 and filt.lower() == 'f277w':
                 pass
 
             else:
@@ -599,7 +623,7 @@ def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False,
                     print('Finished in {} seconds.'.format(time.time()-start))
 
                     # Get the filepath
-                    file = os.path.join(PSF_DIR, 'SOSS_{}_PSF_order{}_{}.npy'.format(filt, n+1, N+1))
+                    file = os.path.join(psf_loc, 'SOSS_{}_PSF_order{}_{}.npy'.format(filt, n+1, N+1))
 
                     # Delete the file if it exists
                     if os.path.isfile(file):
@@ -619,10 +643,12 @@ def SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=False,
 
         else:
 
+            print("Using SOSS PSF files located at {}".format(psf_loc))
+
             # Get the chunked data and concatenate
             full_data = []
             for chunk in [1, 2, 3, 4]:
-                file = os.path.join(PSF_DIR, 'SOSS_{}_PSF_order{}_{}.npy'.format(filt, order, chunk))
+                file = os.path.join(psf_loc, 'SOSS_{}_PSF_order{}_{}.npy'.format(filt, order, chunk))
                 full_data.append(np.load(file))
 
             return np.concatenate(full_data, axis=0)
diff --git a/mirage/ramp_generator/moving_target_position_table.py b/mirage/ramp_generator/moving_target_position_table.py
index 9258e4921..0c35a68fe 100644
--- a/mirage/ramp_generator/moving_target_position_table.py
+++ b/mirage/ramp_generator/moving_target_position_table.py
@@ -126,8 +126,8 @@ def create_mt_pos_entry(time_string, movtarg_x, movtarg_y, refpix_ra, refpix_dec
             (1, ),
             dtype=[
                 ('time', '>f8'),
-                ('mt_detector_x', '>i4'),
-                ('mt_detector_y', '>i4'),
+                ('mt_sci_x', '>i4'),
+                ('mt_sci_y', '>i4'),
                 ('ref_pixel_RA', '>f8'),
                 ('ref_pixel_Dec', '>f8'),
                 ('mt_apparent_RA', '>f8'),
@@ -154,8 +154,8 @@ def create_mt_pos_entry(time_string, movtarg_x, movtarg_y, refpix_ra, refpix_dec
             ]
         )
         position[0]['time'] = mjd_day
-        position[0]['mt_detector_x'] = movtarg_x
-        position[0]['mt_detector_y'] = movtarg_y
+        position[0]['mt_sci_x'] = movtarg_x
+        position[0]['mt_sci_y'] = movtarg_y
         position[0]['ref_pixel_RA'] = refpix_ra
         position[0]['ref_pixel_Dec'] = refpix_dec
         position[0]['mt_apparent_RA'] = movtarg_ra
diff --git a/mirage/ramp_generator/obs_generator.py b/mirage/ramp_generator/obs_generator.py
index 2c45c3556..03cd7774d 100755
--- a/mirage/ramp_generator/obs_generator.py
+++ b/mirage/ramp_generator/obs_generator.py
@@ -91,6 +91,7 @@ def __init__(self, offline=False):
         self.offline = offline
         self.paramfile = 'None'
         self.params = None
+        self.output_files = []
 
         # self.coord_adjust contains the factor by which the
         # nominal output array size needs to be increased
@@ -435,8 +436,6 @@ def add_mirage_info(self):
         hdulist[0].header['DISTORTN'] = (self.params['Reffiles']['astrometric'],
                                          'Distortion reffile used by Mirage')
         hdulist[0].header['IPC'] = (self.params['Reffiles']['ipc'], 'IPC kernel used by Mirage')
-        hdulist[0].header['PIXARMAP'] = (self.params['Reffiles']['pixelAreaMap'],
-                                         'Pixel area map used by Mirage')
         hdulist[0].header['CROSSTLK'] = (self.params['Reffiles']['crosstalk'],
                                          'Crosstalk file used by Mirage')
         hdulist[0].header['FLUX_CAL'] = (self.params['Reffiles']['flux_cal'],
@@ -475,36 +474,6 @@ def add_mirage_info(self):
                                        'Random number generator seed for cosmic rays in Mirage')
         return hdulist
 
-    def add_pam(self, signalramp):
-        """ Apply Pixel Area Map to exposure
-
-        Paramters:
-        ----------
-        signalramp : numpy.ndarray
-            Array containing exposure
-
-        Returns
-        --------
-        signalramp : numpy.ndarary
-            Array after multiplying by the pixel area map
-        """
-        pixAreaMap = self.simple_get_image(self.params['Reffiles']['pixelAreaMap'])
-
-        # If we are making a grism direct image, we need to embed the true pixel area
-        # map in an array of the appropriate dimension, where any pixels outside the
-        # actual aperture are set to 1.0
-        if self.params['Output']['grism_source_image']:
-            mapshape = pixAreaMap.shape
-            g, yd, xd = signalramp.shape
-            pam = np.ones((yd, xd))
-            ys = self.coord_adjust['yoffset']
-            xs = self.coord_adjust['xoffset']
-            pam[ys:ys+mapshape[0], xs:xs+mapshape[1]] = np.copy(pixAreaMap)
-            pixAreaMap = pam
-
-        signalramp *= pixAreaMap
-        return signalramp
-
     def add_superbias_and_refpix(self, ramp, sbref):
         """Add superbias and reference pixel-associated
         signal to the input ramp
@@ -775,7 +744,6 @@ def check_params(self):
         self.runStep['fwpw'] = self.check_run_step(self.params['Reffiles']['filtpupilcombo'])
         self.runStep['linearized_darkfile'] = self.check_run_step(self.params['Reffiles']['linearized_darkfile'])
         self.runStep['badpixfile'] = self.check_run_step(self.params['Reffiles']['badpixmask'])
-        self.runStep['pixelAreaMap'] = self.check_run_step(self.params['Reffiles']['pixelAreaMap'])
 
         # NON-LINEARITY
         # Make sure the input accuracy is a float with reasonable bounds
@@ -1051,11 +1019,15 @@ def cr_funcs(self, npix, seed=4242):
         return crhits, crs_perframe
 
     @logging_functions.log_fail
-    def create(self):
+    def create(self, override_refs=None):
         """MAIN FUNCTION"""
         # Read in the parameter file
         self.read_parameter_file()
 
+        # Override reference files
+        if override_refs is not None:
+            self.params['Reffiles'].update(override_refs)
+
         # Get the log caught up on what's already happened
         self.logger.info('\n\nRunning observation generator....\n')
         self.logger.info('Reading parameter file: {}\n'.format(self.paramfile))
@@ -1772,7 +1744,7 @@ def do_poisson(self, signalimage, seedval):
         newimage = np.random.poisson(signalgain, signalgain.shape).astype(np.float64)
 
         if np.nanmin(signalgain) < 0.:
-            newimage[neg] = negatives[neg]
+            newimage[neg] = negatives[neg].astype(np.float64)
 
         newimage /= self.gain
 
@@ -1805,7 +1777,6 @@ def file_check(self):
                  ['Reffiles', 'linearity'],
                  ['Reffiles', 'saturation'],
                  ['Reffiles', 'ipc'],
-                 ['Reffiles', 'pixelAreaMap'],
                  ['Reffiles', 'gain']]
         plist = [['cosmicRay', 'path']]
         for ref in rlist:
@@ -3083,6 +3054,9 @@ def save_DMS(self, ramp, zeroframe, filename, mod='1b', err_ext=None,
         # Save the datamodel
         outModel.save(filename)
 
+        # Save list of output files
+        self.output_files.append(filename)
+
         # Now we need to adjust the datamodl header keyword
         # If we leave it as Level1bModel, the pipeline doesn't
         # work properly
@@ -3372,6 +3346,10 @@ def save_fits(self, ramp, zeroframe, filename, mod='1b', err_ext=None,
             outModel[groupextnum].data = self.populate_group_table(ct, outModel[0].header['TGROUP'], self.rampexptime,
                                                                    n_int, n_group, n_y, n_x)
         outModel.writeto(filename, overwrite=True)
+
+        # Save list of output files
+        self.output_files.append(filename)
+
         return filename
 
     def resets_before_exp(self):
diff --git a/mirage/reference_files/jband_transmission.dat b/mirage/reference_files/jband_transmission.dat
new file mode 100644
index 000000000..c52c2cc84
--- /dev/null
+++ b/mirage/reference_files/jband_transmission.dat
@@ -0,0 +1,108 @@
+#Wav(um) Response
+1.062   0.
+1.066   4.07068E-04
+1.070   1.54293E-03
+1.075   2.67013E-03
+1.078   5.50643E-03
+1.082   1.22532E-02
+1.084   2.02928E-02
+1.087   3.06470E-02
+1.089   4.05135E-02
+1.093   5.15324E-02
+1.096   5.63529E-02
+1.102   7.18073E-02
+1.105   0.273603
+1.107   0.340997
+1.109   0.358446
+1.112   0.380134
+1.116   0.330668
+1.117   0.239548
+1.120   0.250062
+1.123   0.283301
+1.128   0.258233
+1.129   0.251474
+1.132   0.538119
+1.134   0.223168
+1.138   0.536893
+1.140   0.110203
+1.143   0.529207
+1.147   0.261940
+1.154   0.320155
+1.159   0.174300
+1.164   0.607031
+1.167   0.617933
+1.170   0.676289
+1.173   0.727940
+1.175   0.746531
+1.179   0.830404
+1.182   0.790307
+1.186   0.809605
+1.188   0.836888
+1.192   0.835984
+1.195   0.749936
+1.199   0.708013
+1.202   0.698759
+1.209   0.704854
+1.216   0.700382
+1.221   0.732765
+1.227   0.705725
+1.231   0.842431
+1.236   0.921873
+1.240   0.952505
+1.244   0.967585
+1.247   0.959508
+1.253   0.922697
+1.255   0.892978
+1.258   0.852943
+1.260   0.802308
+1.265   0.750078
+1.270   0.678072
+1.275   0.652417
+1.279   0.638754
+1.286   0.642413
+1.292   0.648560
+1.297   0.682380
+1.302   0.752903
+1.305   0.775942
+1.307   0.811828
+1.310   0.777008
+1.313   0.721030
+1.316   0.952459
+1.319   0.855137
+1.323   0.841401
+1.326   1.00000
+1.330   0.894736
+1.333   0.854912
+1.334   0.537894
+1.336   0.279866
+1.339   0.906532
+1.343   0.689345
+1.346   0.553327
+1.349   0.243177
+1.353   1.43760E-02
+1.355   1.89290E-04
+1.360   4.00791E-02
+1.363   4.53595E-03
+1.370   3.19968E-04
+1.373   3.72168E-02
+1.377   5.38436E-04
+1.383   0.
+1.388   1.44443E-04
+1.392   3.29774E-03
+1.395   3.14438E-04
+1.396   8.47738E-03
+1.397   2.53731E-02
+1.398   0.118446
+1.400   1.35728E-04
+1.401   6.10438E-05
+1.402   5.21326E-02
+1.404   1.03768E-02
+1.406   4.78050E-02
+1.407   4.19727E-04
+1.410   2.36641E-03
+1.412   5.26108E-03
+1.416   8.64765E-03
+1.421   7.28868E-04
+1.426   3.48399E-04
+1.442   3.78145E-04
+1.450   0.
diff --git a/mirage/reference_files/stellarmodels/phoenix/-0.0/model_list.txt b/mirage/reference_files/stellarmodels/phoenix/-0.0/model_list.txt
new file mode 100644
index 000000000..6cbf32275
--- /dev/null
+++ b/mirage/reference_files/stellarmodels/phoenix/-0.0/model_list.txt
@@ -0,0 +1,841 @@
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-0.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-0.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-1.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-1.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02300-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-0.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-0.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-1.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-1.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte02400-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
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+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10000-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10200-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10400-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10600-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte10800-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11000-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11200-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11400-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11600-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte11800-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-2.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-2.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-3.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-3.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-4.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-5.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-5.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
+-rw-r--r--   1 ftp      ftp       6287040 Feb 20  2013 lte12000-6.00-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits
diff --git a/mirage/seed_image/catalog_seed_image.py b/mirage/seed_image/catalog_seed_image.py
index 384a047f8..8314d9672 100644
--- a/mirage/seed_image/catalog_seed_image.py
+++ b/mirage/seed_image/catalog_seed_image.py
@@ -14,6 +14,7 @@
 import logging
 import os
 import copy
+import pickle
 import re
 import shutil
 from yaml.scanner import ScannerError
@@ -53,7 +54,8 @@
 from ..utils.constants import CRDS_FILE_TYPES, MEAN_GAIN_VALUES, SERSIC_FRACTIONAL_SIGNAL, \
                               SEGMENTATION_MIN_SIGNAL_RATE, SUPPORTED_SEGMENTATION_THRESHOLD_UNITS, \
                               LOG_CONFIG_FILENAME, STANDARD_LOGFILE_NAME, TSO_MODES, NIRISS_GHOST_GAP_FILE, \
-                              NIRISS_GHOST_GAP_URL, NIRCAM_SW_GRISMTS_APERTURES, NIRCAM_LW_GRISMTS_APERTURES
+                              NIRISS_GHOST_GAP_URL, NIRCAM_SW_GRISMTS_APERTURES, NIRCAM_LW_GRISMTS_APERTURES, \
+                              DISPERSED_MODES
 from ..utils.flux_cal import fluxcal_info, sersic_fractional_radius, sersic_total_signal
 from ..utils.timer import Timer
 from ..psf.psf_selection import get_gridded_psf_library, get_psf_wings
@@ -945,7 +947,6 @@ def saveSeedImage(self, seed_image, segmentation_map, seed_file_name):
         kw['GAINFILE'] = self.params['Reffiles']['gain']
         kw['DISTORTN'] = self.params['Reffiles']['astrometric']
         kw['IPC'] = self.params['Reffiles']['ipc']
-        kw['PIXARMAP'] = self.params['Reffiles']['pixelAreaMap']
         kw['CROSSTLK'] = self.params['Reffiles']['crosstalk']
         kw['FLUX_CAL'] = self.params['Reffiles']['flux_cal']
         kw['FTHRUPUT'] = self.params['Reffiles']['filter_throughput']
@@ -1639,7 +1640,7 @@ def movingTargetInputs(self, filename, input_type, MT_tracking=False,
             elif input_type == 'extended':
                 stamp, header = self.basic_get_image(entry['filename'])
                 # Rotate the stamp image if requested, but don't do so if the specified pos angle is None
-                stamp = self.rotate_extended_image(stamp, entry['pos_angle'], ra, dec)
+                stamp = self.rotate_extended_image(stamp, entry['pos_angle'])
 
                 # If no magnitude is given, use the extended image as-is
                 if rate != 1.0:
@@ -1662,12 +1663,7 @@ def movingTargetInputs(self, filename, input_type, MT_tracking=False,
                     stamp = s1.fftconvolve(stamp, eval_psf, mode='same')
 
             elif input_type == 'galaxies':
-                if not self.use_intermediate_aperture:
-                    pixelv2, pixelv3 = pysiaf.utils.rotations.getv2v3(self.attitude_matrix, ra, dec)
-                else:
-                    pixelv2, pixelv3 = pysiaf.utils.rotations.getv2v3(self.intermediate_attitude_matrix, ra, dec)
-
-                xposang = self.calc_x_position_angle(pixelv2, pixelv3, entry['pos_angle'])
+                xposang = self.calc_x_position_angle(entry)
 
                 # First create the galaxy
                 stamp = self.create_galaxy(entry['radius'], entry['ellipticity'], entry['sersic_index'],
@@ -2961,6 +2957,9 @@ def make_point_source_image(self, pointSources, segment_number=None, ptsrc_segma
         # Create the empty image
         psfimage = np.zeros(self.output_dims)
 
+        # Create empty seed cube for possible WFSS dispersion
+        seed_cube = {}
+
         if ptsrc_segmap is None:
             # Create empty segmentation map
             ptsrc_segmap = segmap.SegMap()
@@ -3020,12 +3019,21 @@ def make_point_source_image(self, pointSources, segment_number=None, ptsrc_segma
                 self.timer.stop()
                 continue
 
+            self.logger.info("******************************* %s" % (self.basename))
+
             try:
                 psf_to_add = scaled_psf[l1:l2, k1:k2]
                 psfimage[j1:j2, i1:i2] += psf_to_add
 
                 # Add source to segmentation map
                 ptsrc_segmap.add_object_threshold(psf_to_add, j1, i1, entry['index'], self.segmentation_threshold)
+
+                if self.params['Inst']['mode'] in DISPERSED_MODES:
+                    # Add source to seed cube file
+                    stamp = np.zeros(psf_to_add.shape)
+                    flag = psf_to_add >= self.segmentation_threshold
+                    stamp[flag] = entry['index']
+                    seed_cube[entry['index']] = [i1, j1, psf_to_add*1, stamp*1]
             except IndexError:
                 # In here we catch sources that are off the edge
                 # of the detector. These may not necessarily be caught in
@@ -3047,6 +3055,10 @@ def make_point_source_image(self, pointSources, segment_number=None, ptsrc_segma
                     self.logger.info(('Working on source #{}. Estimated time remaining to add all point sources to the stamp image: {} minutes. '
                                       'Projected finish time: {}'.format(i, time_remaining, finish_time)))
 
+        if self.params['Inst']['mode'] in DISPERSED_MODES:
+            # Save the seed cube file of point sources
+            pickle.dump(seed_cube, open("%s_star_seed_cube.pickle" % (self.basename), "wb"), protocol=pickle.HIGHEST_PROTOCOL)
+
         return psfimage, ptsrc_segmap
 
     def create_psf_stamp(self, x_location, y_location, psf_dim_x, psf_dim_y,
@@ -4054,8 +4066,8 @@ def create_galaxy(self, r_Sersic, ellipticity, sersic_index, position_angle, tot
 
         # Using the position angle, calculate the size of the source in the
         # x and y directions
-        y_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.cos(position_angle)), 2 * semi_minor_axis])))
-        x_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.sin(position_angle)), 2 * semi_minor_axis])))
+        x_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.cos(position_angle)), 2 * semi_minor_axis])))
+        y_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.sin(position_angle)), 2 * semi_minor_axis])))
 
         num_pix = x_full_length * y_full_length
 
@@ -4073,8 +4085,8 @@ def create_galaxy(self, r_Sersic, ellipticity, sersic_index, position_angle, tot
 
             # Using the position angle, calculate the size of the source in the
             # x and y directions
-            y_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.cos(position_angle)), 2 * semi_minor_axis])))
-            x_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.sin(position_angle)), 2 * semi_minor_axis])))
+            x_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.cos(position_angle)), 2 * semi_minor_axis])))
+            y_full_length = np.int(np.ceil(np.max([2 * semi_major_axis * np.absolute(np.sin(position_angle)), 2 * semi_minor_axis])))
 
             num_pix = x_full_length * y_full_length
 
@@ -4093,7 +4105,7 @@ def create_galaxy(self, r_Sersic, ellipticity, sersic_index, position_angle, tot
         # Mirage has been using is that the PA is degrees east of north of the
         # semi-major axis
         mod = Sersic2D(amplitude=amplitude, r_eff=r_Sersic, n=sersic_index, x_0=subpixx, y_0=subpixy,
-                       ellip=ellipticity, theta=position_angle+np.pi/2)
+                       ellip=ellipticity, theta=position_angle)
 
         x_half_length = x_full_length // 2
         xmin = int(0 - x_half_length)
@@ -4204,6 +4216,9 @@ def make_galaxy_image(self, file):
         # final output image
         yd, xd = self.output_dims
 
+        # Seed cube for disperser
+        seed_cube = {}
+
         # create the final galaxy countrate image
         galimage = np.zeros((yd, xd))
 
@@ -4229,8 +4244,7 @@ def make_galaxy_image(self, file):
             # is just V3SciYAngle in the SIAF (I think???)
             # v3SciYAng is measured in degrees, from V3 towards the Y axis,
             # measured from V3 towards V2.
-            xposang = self.calc_x_position_angle(entry['V2'], entry['V3'], entry['pos_angle'])
-
+            xposang = self.calc_x_position_angle(entry)
             sub_x = 0.
             sub_y = 0.
 
@@ -4298,9 +4312,17 @@ def make_galaxy_image(self, file):
                 if ((j2 > j1) and (i2 > i1) and (l2 > l1) and (k2 > k1) and (j1 < yd) and (i1 < xd)):
                     stamp_to_add = stamp[l1:l2, k1:k2]
                     galimage[j1:j2, i1:i2] += stamp_to_add
+
                     # Add source to segmentation map
                     segmentation.add_object_threshold(stamp_to_add, j1, i1, entry['index'], self.segmentation_threshold)
 
+                    if self.params['Inst']['mode'] in DISPERSED_MODES:
+                        # Add source to the seed cube
+                        stamp = np.zeros(stamp_to_add.shape)
+                        flag = stamp_to_add >= self.segmentation_threshold
+                        stamp[flag] = entry['index']
+                        seed_cube[entry['index']] = [i1, j1, stamp_to_add*1, stamp*1]
+
                 else:
                     pass
                     # print("Source located entirely outside the field of view. Skipping.")
@@ -4319,21 +4341,49 @@ def make_galaxy_image(self, file):
                     self.logger.info(('Working on galaxy #{}. Estimated time remaining to add all galaxies to the stamp image: {} minutes. '
                                       'Projected finish time: {}'.format(entry_index, time_remaining, finish_time)))
 
+        if self.params['Inst']['mode'] in DISPERSED_MODES:
+            # Save the seed cube file of galaxy sources
+            pickle.dump(seed_cube, open("%s_galaxy_seed_cube.pickle" % (self.basename), "wb"), protocol=pickle.HIGHEST_PROTOCOL)
+
         return galimage, segmentation.segmap, ghost_sources_from_galaxies
 
-    def calc_x_position_angle(self, v2_value, v3_value, position_angle):
-        """Calcuate the position angle of the source relative to the x
-        axis of the detector given the source's v2, v3 location and the
-        user-input position angle (degrees east of north).
+    def calc_x_position_angle(self, galaxy_entry):
+        """For Sersic2D galaxies, calcuate the position angle of the source
+        relative to the x axis of the detector given the user-input position
+        angle (degrees east of north).
 
         Parameters
         ----------
-        v2_value : float
-            V2 location of source in units of arcseconds
+        galaxy_entry : astropy.table.Row
+            Row of galaxy info from astropy Table of entries.
+            e.g. output from readGalaxyFile
 
-        v3_value : float
-            V3 location of source in units of arcseconds
+        Returns
+        -------
+        x_posang : float
+            Position angle of source relative to detector x
+            axis, in units of degrees
+        """
+        # Note that this method also works for cases that make use of
+        # an intermediate aperture (e.g. grism time series, although
+        # grism time series obs at the moment only support point sources
+        # currently.)
+        ra_center = galaxy_entry["RA_degrees"]
+        dec_center = galaxy_entry["Dec_degrees"]
+        center = SkyCoord(ra_center, dec_center, unit=u.deg)
+        offset = center.directional_offset_by(galaxy_entry['pos_angle'] * u.deg, 1. * u.arcsec)
+        offset_x, offset_y = self.RADecToXY_astrometric(offset.ra, offset.dec)
+        dx = offset_x - galaxy_entry['pixelx']
+        dy = offset_y - galaxy_entry['pixely']
+        return np.degrees(np.arctan2(dy, dx))
+
+    def calc_x_position_angle_extended(self, position_angle):
+        """For extended sources from fits files with no WCS, calcuate the position
+        angle of the source relative to the x axis of the detector given the source's
+        v2, v3 location and the user-input position angle (degrees east of north).
 
+        Parameters
+        ----------
         position_angle : float
             Position angle of source in degrees east of north
 
@@ -4343,9 +4393,13 @@ def calc_x_position_angle(self, v2_value, v3_value, position_angle):
             Position angle of source relative to detector x
             axis, in units of degrees
         """
-        north_to_east_V3ang = rotations.posangle(self.attitude_matrix, v2_value, v3_value)
-        x_posang = 0. - (self.siaf.V3SciXAngle - north_to_east_V3ang + self.local_roll - position_angle
-                         + 90. - self.params['Telescope']['rotation'])
+        x_posang = self.local_roll + position_angle
+
+        # If we are using a Grism Time series aperture, then we need to use the intermediate
+        # aperture to determine the correct rotation. Currently, we should never be in
+        # here since grism TSO observations only support the use of point sources.
+        if self.use_intermediate_aperture:
+            x_posang = self.intermediate_local_roll + position_angle
         return x_posang
 
     def locate_ghost(self, pixel_x, pixel_y, count_rate, magnitude_system, source_row, obj_type, log_skipped_filters=True):
@@ -4604,7 +4658,7 @@ def getExtendedSourceList(self, filename, ghost_search=True):
             # print('extended source size:', ext_stamp.shape)
 
             # Rotate the stamp image if requested, but don't do so if the specified pos angle is None
-            ext_stamp = self.rotate_extended_image(ext_stamp, values['pos_angle'], ra, dec)
+            ext_stamp = self.rotate_extended_image(ext_stamp, values['pos_angle'])
 
             eshape = np.array(ext_stamp.shape)
             if len(eshape) == 2:
@@ -4735,7 +4789,7 @@ def getExtendedSourceList(self, filename, ghost_search=True):
 
         return extSourceList, all_stamps, ghost_catalog_file
 
-    def rotate_extended_image(self, stamp_image, pos_angle, right_ascention, declination):
+    def rotate_extended_image(self, stamp_image, pos_angle):
         """Given the user-input position angle for the extended source
         image, calculate the appropriate angle of the stamp image
         relative to the detector x axis, and rotate the stamp image.
@@ -4752,12 +4806,6 @@ def rotate_extended_image(self, stamp_image, pos_angle, right_ascention, declina
             or string 'None' will result in no rotation, i.e. the input stamp is returned
             without modification.
 
-        right_ascention : float
-            RA of source, in decimal degrees
-
-        declination : float
-            Dec of source, in decimal degrees
-
         Returns
         -------
         rotated : numpy.ndarray
@@ -4770,12 +4818,8 @@ def rotate_extended_image(self, stamp_image, pos_angle, right_ascention, declina
             return stamp_image
 
         # Add later: check for WCS and use that
-        # if no WCS:
-        if not self.use_intermediate_aperture:
-            pixelv2, pixelv3 = pysiaf.utils.rotations.getv2v3(self.attitude_matrix, right_ascention, declination)
-        else:
-            pixelv2, pixelv3 = pysiaf.utils.rotations.getv2v3(self.intermediate_attitude_matrix, right_ascention, declination)
-        x_pos_ang = self.calc_x_position_angle(pixelv2, pixelv3, pos_angle)
+        x_pos_ang = self.calc_x_position_angle_extended(pos_angle)
+
         rotated = rotate(stamp_image, x_pos_ang, mode='constant', cval=0.)
         return rotated
 
@@ -4784,6 +4828,9 @@ def make_extended_source_image(self, extSources, extStamps, extConvolutions):
         yd, xd = self.output_dims
         extimage = np.zeros(self.output_dims)
 
+        # Prepare seed cube for extended sources
+        seed_cube = {}
+
         # Create corresponding segmentation map
         segmentation = segmap.SegMap()
         segmentation.xdim = xd
@@ -4876,8 +4923,20 @@ def make_extended_source_image(self, extSources, extStamps, extConvolutions):
                 # Add source to segmentation map
                 segmentation.add_object_threshold(stamp_to_add, j1, i1, entry['index'],
                                                   self.segmentation_threshold)
+
+                if self.params['Inst']['mode'] in DISPERSED_MODES:
+                    # Add source to seed cube
+                    stamp = np.zeros(stamp_to_add.shape)
+                    flag = stamp_to_add >= self.segmentation_threshold
+                    stamp[flag] = entry['index']
+                    seed_cube[entry['index']] = [i1, j1, stamp_to_add*1, stamp*1]
+
                 self.n_extend += 1
 
+        if self.params['Inst']['mode'] in DISPERSED_MODES:
+            # Save the seed cube
+            pickle.dump(seed_cube, open("%s_extended_seed_cube.pickle" % (self.basename), "wb"), protocol=pickle.HIGHEST_PROTOCOL)
+
         if self.n_extend == 0:
             self.logger.info("No extended sources present within the aperture.")
         else:
@@ -5056,7 +5115,6 @@ def check_params(self):
         self.runStep['zodiacal'] = self.checkRunStep(self.params['simSignals']['zodiacal'])
         self.runStep['scattered'] = self.checkRunStep(self.params['simSignals']['scattered'])
         # self.runStep['fwpw'] = self.checkRunStep(self.params['Reffiles']['filtpupilcombo'])
-        self.runStep['pixelAreaMap'] = self.checkRunStep(self.params['Reffiles']['pixelAreaMap'])
 
         # Notify user if no catalogs are provided
         if self.params['simSignals']['pointsource'] == 'None':
@@ -5503,63 +5561,6 @@ def read_distortion_reffile(self):
         #    coord_transform = self.simple_coord_transform()
         return coord_transform
 
-    """
-    def calculate_background(self, ra, dec, ffile, back_wave=None, back_sig=None, level='medium'):
-        '''Use the JWST background calculator to come up with
-        an appropriate background level for the observation.
-        Options for level include low, medium, high'''
-        from jwst_backgrounds import jbt
-        from astropy import units as u
-        from astropy.units.equivalencies import si, cgs
-
-        # Read in filter throughput file
-        filt_wav, filt_thru = file_io.read_filter_throughput(ffile)
-
-        # If the user wants a background signal from a particular day,
-        # then extract that array here
-        if self.params['simSignals']['use_dateobs_for_background']:
-            # Interpolate background to match filter wavelength grid
-            bkgd_interp = np.interp(filt_wav, back_wave, back_sig)
-
-            # Combine
-            filt_bkgd = bkgd_interp * filt_thru
-
-            # Integrate over the filter bandpass
-            filt_integ = np.trapz(filt_thru, x=filt_wav)
-
-            # Integrate
-            bval = np.trapz(filt_bkgd, x=filt_wav) / filt_integ * u.MJy / u.steradian
-
-        else:
-            # If the user has requested background in terms of low/medium/high,
-            # then we need to examine all the background arrays.
-            # Loop over each day (in the background)
-            # info, convolve the background curve with the filter
-            # throughput curve, and then integrate. THEN, we can
-            # calculate the low/medium/high values.
-            bval = backgrounds.low_medium_high_background_value(ra, dec, level, filt_wav, filt_thru)
-            bval = bval * u.MJy / u.steradian
-
-        # Convert from MJy/str to ADU/sec
-        # then divide by area of pixel
-        flambda = cgs.erg / si.angstrom / si.cm ** 2 / si.s
-        # fnu = cgs.erg / si.Hz / si.cm ** 2 / si.s
-        photflam = self.photflam * flambda
-        # photnu = self.photfnu * fnu
-        pivot = self.pivot * u.micron
-        mjy = photflam.to(u.MJy, u.spectral_density(pivot))
-
-        # Divide by pixel area in steradians to get
-        # MJy/str per ADU/s
-        pixel_area = self.siaf.XSciScale * u.arcsec * self.siaf.YSciScale * u.arcsec
-        mjy_str = mjy / pixel_area.to(u.steradian)
-
-        # Convert the background signal from MJy/str
-        # to ADU/sec
-        bval /= mjy_str
-        return bval.value
-        """
-
     def saveSingleFits(self, image, name, key_dict=None, image2=None, image2type=None):
         # Save an array into the first extension of a fits file
         h0 = fits.PrimaryHDU()
diff --git a/mirage/seed_image/moving_targets.py b/mirage/seed_image/moving_targets.py
index 7bc1d1e8b..0f3d8a782 100755
--- a/mirage/seed_image/moving_targets.py
+++ b/mirage/seed_image/moving_targets.py
@@ -386,7 +386,7 @@ def subsample(self, image, factorx, factory):
 
         for i in range(xdim):
             for j in range(ydim):
-                substamp[factory*j:factory*(j+1), factorx*i:factorx*(i+1)] = image[j, i]
+                substamp[factory*j:factory*(j+1), factorx*i:factorx*(i+1)] = image[j, i] / (factorx * factory)
         return substamp
 
     def equidistantXY(self,xstart, ystart, xend, yend, dist):
diff --git a/mirage/soss_simulator.py b/mirage/soss_simulator.py
index ef0bf5c2e..db4b00f2b 100644
--- a/mirage/soss_simulator.py
+++ b/mirage/soss_simulator.py
@@ -28,10 +28,12 @@
 from astroquery.simbad import Simbad
 import batman
 from bokeh.plotting import show
+from bokeh.layouts import column
 from hotsoss import utils as hu, plotting, locate_trace
 import numpy as np
-import synphot as sphot
+from scipy import ndimage
 
+from mirage.catalogs import model_atmosphere as ma
 from mirage.seed_image import save_seed, segmentation_map
 from mirage.dark import dark_prep
 from mirage.logging import logging_functions
@@ -58,8 +60,8 @@ def run_required(func):
     @wraps(func)
     def _run_required(*args, **kwargs):
         """Check that the 'tso' attribute is not None"""
-        if args[0].tso_order1_ideal is None:
-            print("No simulation found! Please run the 'simulate' method first.")
+        if args[0].tso_ideal is None:
+            print("No simulation found! Please run the 'create' method first.")
 
         else:
             return func(*args, **kwargs)
@@ -72,7 +74,7 @@ class SossSim():
     Generate NIRISS SOSS time series observations
     """
     def __init__(self, ngrps=2, nints=1, star=None, planet=None, tmodel=None, filter='CLEAR',
-                 subarray='SUBSTRIP256', orders=[1, 2], paramfile=None, obs_date=None, target='New Target',
+                 subarray='SUBSTRIP256', orders=[1, 2, 3], paramfile=None, obs_date=None, target='New Target',
                  title=None, offline=True, test=False, override_dark=None, verbose=True):
         """
         Initialize the TSO object and do all pre-calculations
@@ -126,8 +128,10 @@ def __init__(self, ngrps=2, nints=1, star=None, planet=None, tmodel=None, filter
         self._star = None
         self.ref_params = {"INSTRUME": "NIRISS", "READPATT": "NISRAPID", "EXP_TYPE": "NIS_SOSS", "DETECTOR": "NIS", "PUPIL": "GR700XD", "DATE-OBS": "2020-07-28", "TIME-OBS": "00:00:00", "INSTRUMENT": "NIRISS"}
 
-        # Additional parmeters
+        # Additional parameters
         self.orders = orders
+        self.wave = hu.wave_solutions(subarray)
+        self.avg_wave = None
         self.groupgap = 0
         self.nframes = self.nsample = 1
         self.nresets = self.nresets1 = self.nresets2 = 1
@@ -142,6 +146,9 @@ def __init__(self, ngrps=2, nints=1, star=None, planet=None, tmodel=None, filter
         self.readpatt = 'NISRAPID'
         self.paramfile = paramfile
 
+        # Pupil wheel position to set trace tilt
+        self.PWCPOS = 245.76
+
         # Set instance attributes for the target
         self.lines = at.Table(names=('name', 'profile', 'x_0', 'amp', 'fwhm', 'flux'), dtype=('S20', 'S20', float, float, 'O', 'O'))
         self.star = star
@@ -167,6 +174,16 @@ def add_line(self, x_0, amplitude, fwhm, profile='lorentz', name='Line I'):
             The profile to use, ['voigt', 'lorentz', 'gaussian']
         name: str
             A name for the line
+
+        Examples
+        --------
+        from mirage.soss_simulator import SossBlackbodySim
+        import astropy.units as q
+        bb = SossBlackbodySim(run=False)
+        bb.add_line(2*q.um, max(bb.star[1])*1.5, 0.005*q.um)
+        bb.lines # See list of added lines
+        bb.create()
+        bb.plot(noise=False)
         """
         # Check the profile
         profiles = {'voigt': Voigt1D, 'gaussian': Gaussian1D, 'lorentz': Lorentz1D}
@@ -203,16 +220,16 @@ def add_line(self, x_0, amplitude, fwhm, profile='lorentz', name='Line I'):
         self.lines.add_row([name, profile, x_0, amplitude, fwhm, line])
 
     @run_required
-    def add_noise(self):
+    def add_noise(self, override_refs=None, skip_dark=False):
         """
         Run the signal data through the ramp generator
         """
-        self.message("Starting noise generator...")
+        self.logger.info("Starting noise generator...")
         start = time.time()
 
         # Generate segmentation map with correct dimensions
-        self.segmap = segmentation_map.SegMap()
-        self.segmap.ydim = self.nrows
+        segmap = segmentation_map.SegMap()
+        segmap.ydim = self.nrows
 
         # Prepare dark current exposure if needed.
         if self.override_dark is None:
@@ -220,35 +237,57 @@ def add_noise(self):
             d = dark_prep.DarkPrep(offline=self.offline)
             d.paramfile = self.paramfile
             d.prepare()
-            use_darks = d.dark_files
+            self.use_darks = d.dark_files
         else:
-            self.logger.info('\noverride_dark is set. Skipping call to dark_prep and using these files instead.')
-            use_darks = self.override_dark
+            self.logger.info('Override_dark is set. Skipping call to dark_prep.')
+            self.use_darks = self.override_dark
 
         # Make a seed files split like the dark file
-        if isinstance(use_darks, str):
-            use_darks = [use_darks]
+        if isinstance(self.use_darks, str):
+            self.use_darks = [self.use_darks]
+
+        # Set darks to all zeros if skip_dark
+        if skip_dark:
+            self.logger.info('skip_dark is set. Setting dark frames to all zeroes.')
+            for dfile in self.use_darks:
+                hdu = fits.open(dfile)
+                hdu[1].data *= 0.
+                hdu[2].data *= 0.
+                hdu[3].data *= 0.
+                hdu[4].data *= 0.
+                hdu.flush()
+                hdu.close()
 
         nint = 0
-        nfiles = len(use_darks)
+        nfiles = len(self.use_darks)
         self.tso = np.empty_like(self.tso_ideal)
-        for n, dfile in enumerate(use_darks):
+        self.obs = []
+        for n, dfile in enumerate(self.use_darks):
+            self.logger.info('Using dark file {}/{}: {}'.format(n + 1, len(self.use_darks), dfile))
             dhead = fits.getheader(dfile)
             dnint = dhead['NINTS']
 
-            # Save the raw signal as a seed image
-            seed_seg = self.tso_ideal[nint:nint + dnint, :, :, :]
+            # Get the appropriate seed image segment
+            seed_seg = self.tso_ideal[nint:nint + dnint, :, :, :].astype(np.float64)
+
+            # NaNs and infs break np.random.poisson
+            seed_seg[np.where(np.isnan(seed_seg))] = 0.
+            seed_seg[np.where(np.isinf(seed_seg))] = 0.
+
+            # Save the seed image segment to file
             seedfile, seedinfo = save_seed.save(seed_seg, self.paramfile, self.params, True, False, 1., 2048, (self.nrows, self.ncols), {'xoffset': 0, 'yoffset': 0}, 1, frametime=self.frame_time)
 
             # Combine into final observation
             self.logger.info('Running observation generator for segment {}/{}'.format(n, nfiles))
             obs = obs_generator.Observation(offline=self.offline)
+
+            # Add simulation data
             obs.linDark = dfile
             obs.seed = seed_seg
-            obs.segmap = self.segmap
+            obs.segmap = segmap
             obs.seedheader = seedinfo
             obs.paramfile = self.paramfile
-            obs.create()
+            obs.create(override_refs=override_refs)
 
             if nfiles > 1:
                 os.system('mv {} {}'.format(seedfile, seedfile.replace('_seed_image.fits', '_seg{}_part001_seed_image.fits'.format(str(n + 1).zfill(3)))))
@@ -256,14 +295,68 @@ def add_noise(self):
             # Save ramp to tso attribute
             self.tso[nint:nint + dnint, :, :, :] = obs.raw_outramp
 
+            # Save obs object
+            self.obs.append(obs)
+
             # Pickup where last segment left off
             nint += dnint
 
-        # Log it
-        self.logger.info('\nSOSS simulator complete')
-        self.message('Noise model finished: {} {}'.format(round(time.time() - start, 3), 's'))
+        self.logger.info('SOSS simulator complete')
+        self.logger.info('Noise model finished: {} {}'.format(round(time.time() - start, 3), 's'))
+
+        return obs.output_files
 
-    def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
+    @property
+    def avg_wave(self):
+        """
+        Getter for nominal wavelength value in each column for all orders
+        """
+        return self._avg_wave
+
+    @avg_wave.setter
+    def avg_wave(self, wave_sol):
+        """
+        Setter for the nominal wavelength value in each column for all orders
+
+        Parameters
+        ----------
+        wave_sol: sequence
+            The wavelength solutions. Must be an array of shape (2, 2048), or (3, 2048)
+        """
+        if wave_sol is None:
+            self._avg_wave = np.mean(self.wave, axis=1)
+            self.wave_name = 'default'
+
+        else:
+
+            # Wave name provided
+            if isinstance(wave_sol, tuple):
+                wave_sol, self.wave_name = wave_sol
+
+            # No wave name provided
+            else:
+                self.wave_name = 'custom'
+
+            # Dimensions of input nominal wavelengths
+            dims = wave_sol.shape
+
+            # Make sure it is 2048 columns wide
+            if dims[-1] != 2048:
+                raise ValueError('{} columns provided but wavelength solutions must be 2048 pixels wide.'.format(dims[-1]))
+
+            # Ensure monotonically decreasing due to native trace orientation
+            wave_sol = np.sort(wave_sol, axis=1)[:, ::-1]
+
+            # Set the attribute
+            self._avg_wave = wave_sol
+
+            # Generate new PSFs here!
+            soss_trace.SOSS_psf_cube(filt='CLEAR', order=1, subarray='SUBSTRIP256', generate=True, mprocessing=True, wave_sol=wave_sol, dirname=self.wave_name)
+
+            # Reset PSFs
+            self._reset_psfs()
+
+    def create(self, n_jobs=-1, noise=True, override_dark=None, max_frames=50, **kwargs):
         """
         Create the simulated 4D ramp data given the initialized TSO object
 
@@ -271,10 +364,12 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
         ----------
         n_jobs: int
             The number of cores to use in multiprocessing
-        tparams: dict
-            The transit parameters of the system
-        supersample_factor: int
-            The
+        noise: bool
+            Include noise model in simulation
+        override_dark: str
+            The path to a dark file that should override the default dark
+        max_frames: int
+            The max number of frames to chunk the simulation into to save memory
 
         Example
         -------
@@ -321,15 +416,14 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
         self._reset_psfs()
 
         # Logging
-        self.logger.info('\n\nRunning soss_simulator....\n')
-        self.logger.info('Using parameter file: ')
-        self.logger.info('{}'.format(self.paramfile))
+        self.logger.info('Running soss_simulator....')
+        self.logger.info('Using parameter file: {}'.format(self.paramfile or 'None'))
         begin = time.time()
 
         # Make a simulation of all ones to save time
         if self.test:
 
-            self.message("Generating test simulation of shape {}...".format(self.dims))
+            self.logger.info("Generating test simulation of shape {}...".format(self.dims))
             self.tso_order1_ideal = self.tso_order2_ideal = np.ones((self.nints * self.ngrps, 256, 2048))
 
         # Make a true simulation
@@ -340,7 +434,6 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
                 n_jobs = max_cores
 
             # Chunk along the time axis so results can be dumped into a file and then deleted
-            max_frames = 50
             nints_per_chunk = max_frames // self.ngrps
             nframes_per_chunk = self.ngrps * nints_per_chunk
 
@@ -350,11 +443,13 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
             n_chunks = len(time_chunks)
 
             # Iterate over chunks
-            self.message('Simulating {target} in {title}\nConfiguration: {subarray} + {filter}\nGroups: {ngrps}, Integrations: {nints}\n'.format(**self.info))
+            self.logger.info('Simulating {} in {}'.format(self.target, self.title))
+            self.logger.info('Configuration: {} + {}'.format(self.subarray, self.filter))
+            self.logger.info('Groups: {}, Integrations: {}'.format(self.ngrps, self.nints))
             for chunk, (time_chunk, inttime_chunk) in enumerate(zip(time_chunks, inttime_chunks)):
 
                 # Run multiprocessing to generate lightcurves
-                self.message('Constructing frames for chunk {}/{}...'.format(chunk + 1, n_chunks))
+                self.logger.info('Constructing frames for chunk {}/{}...'.format(chunk + 1, n_chunks))
                 start = time.time()
 
                 # Get transit model for the current time chunk
@@ -381,7 +476,7 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
                     pool = ThreadPool(n_jobs)
                     func = partial(soss_trace.psf_lightcurve, time=time_chunk)
                     data = list(zip(psfs, tmodels))
-                    lightcurves = np.asarray(pool.starmap(func, data), dtype=np.float16)
+                    lightcurves = np.asarray(pool.starmap(func, data), dtype=np.float64)
                     pool.close()
                     pool.join()
                     del pool
@@ -409,7 +504,7 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
                     # Clear memory
                     del frames, lightcurves, psfs
 
-                self.message('Chunk {}/{} finished: {} {}'.format(chunk + 1, n_chunks, round(time.time() - start, 3), 's'))
+                self.logger.info('Chunk {}/{} finished: {} {}'.format(chunk + 1, n_chunks, round(time.time() - start, 3), 's'))
 
         # Trim SUBSTRIP256 array if SUBSTRIP96
         if self.subarray == 'SUBSTRIP96':
@@ -426,18 +521,53 @@ def create(self, n_jobs=-1, noise=True, override_dark=None, **kwargs):
                 setattr(self, order_name, full)
                 del full
 
-        # Reshape into (nints, ngrps, y, x)
+        # Rotate and reshape data
         for order in self.orders:
+
+            # Name of order
             order_name = 'tso_order{}_ideal'.format(order)
+
+            # Rotate trace given relative pupil wheel position
+            pwpos = self.PWCPOS - 245.883
+            if pwpos != 0:
+                rot_order = ndimage.rotate(getattr(self, order_name), pwpos, axes=(-2, -1), reshape=False)
+                setattr(self, order_name, rot_order)
+
+            # Reshape into (nints, ngrps, y, x)
             setattr(self, order_name, getattr(self, order_name).reshape(self.dims).astype(np.float64))
 
         # Make ramps and add noise to the observations
+        obs_files = []
         if noise:
-            self.add_noise(**kwargs)
+            obs_files = self.add_noise(**kwargs)
         else:
             self.tso = self.tso_ideal
 
-        self.message('\nTotal time: {} {}'.format(round(time.time() - begin, 3), 's'))
+        # Add input data if available
+        for ofile in obs_files:
+            temp = fits.open(ofile, mode='update')
+            starhdr = fits.Header()
+            starhdr.append(('WUNIT', 'um', 'Wavelength unit'))
+            starhdr.append(('FUNIT', 'erg/s/cm2/A', 'Flux density unit'))
+            starhdu = fits.BinTableHDU.from_columns([fits.Column(name='WAVELENGTH', array=self.star[0].value, format='D'), fits.Column(name='FLUX', array=self.star[1].value, format='D')], header=starhdr, name='STAR')
+            temp.insert(-1, starhdu)
+            if self.planet is not None:
+                planethdr = fits.Header()
+                planethdr.append(('WUNIT', 'um', 'Wavelength unit'))
+                planethdr.append(('T0', self.tmodel.t0, 'Transit center [JD]'))
+                planethdr.append(('A', self.tmodel.a, 'Semimajor-axis [a/R*]'))
+                planethdr.append(('INC', self.tmodel.inc, 'Inclination [deg]'))
+                planethdr.append(('ECC', self.tmodel.ecc, 'Eccentricity'))
+                planethdr.append(('OMEGA', self.tmodel.w, 'Omega value'))
+                planethdr.append(('LD', self.tmodel.limb_dark, 'Limb darkening profile used'))
+                planethdr.append(('TEFF', self.tmodel.teff, 'Effective temperature [K]'))
+                planethdr.append(('LOGG', self.tmodel.logg, 'Log surface gravity [dex]'))
+                planethdr.append(('FEH', self.tmodel.feh, 'Metallicity'))
+                planethdu = fits.BinTableHDU.from_columns([fits.Column(name='WAVELENGTH', array=self.planet[0].value, format='D'), fits.Column(name='TRANSMISSION', array=self.planet[1], format='D')], header=planethdr, name='PLANET')
+                temp.insert(-1, planethdu)
+            temp.flush()
+
+        self.logger.info('\nTotal time: {} {}'.format(round(time.time() - begin, 3), 's'))
 
     @property
     def filter(self):
@@ -476,8 +606,13 @@ def filter(self, filt):
     def info(self):
         """Summary table for the observation settings"""
         # Pull out relevant attributes
-        track = ['_ncols', '_nrows', '_nints', '_ngrps', '_nresets', '_subarray', '_filter', '_obs_datetime', '_orders', 'ld_profile', '_target', 'title', 'ra', 'dec']
+        track = ['_ncols', '_nrows', '_nints', '_ngrps', '_nresets', '_subarray', '_filter', '_obs_datetime', '_orders', 'ld_profile', '_target', 'title', 'ra', 'dec', 't0', 'per', 'rp', 'a', 'inc', 'ecc', 'w', 'u', 'limb_dark', 'teff', 'logg', 'feh']
         settings = {key.strip('_'): val for key, val in self.__dict__.items() if key in track}
+
+        # Display orbital parameters if available
+        if getattr(self, '_tmodel', None) is not None:
+            settings.update({key: val for key, val in self._tmodel.__dict__.items() if key in track})
+
         return settings
 
     def message(self, message_text):
@@ -713,7 +848,6 @@ def paramfile(self, pfile):
 
         # Set the dependent quantities
         self.wave = hu.wave_solutions(self.subarray)
-        self.avg_wave = np.mean(self.wave, axis=1)
         self.coeffs = locate_trace.trace_polynomial(subarray=self.subarray)
 
         # Reset data, time and psfs
@@ -769,8 +903,8 @@ def planet(self, spectrum):
             # Check the wavelength range
             spec_min = np.nanmin(spectrum[0][spectrum[0] > 0.])
             spec_max = np.nanmax(spectrum[0][spectrum[0] > 0.])
-            sim_min = np.nanmin(self.wave[self.wave > 0.]) * q.um
-            sim_max = np.nanmax(self.wave[self.wave > 0.]) * q.um
+            sim_min = np.nanmin(self.avg_wave[self.avg_wave > 0.]) * q.um
+            sim_max = np.nanmax(self.avg_wave[self.avg_wave > 0.]) * q.um
             if spec_min > sim_min or spec_max < sim_max:
                 print("Wavelength range of input spectrum ({} - {} um) does not cover the {} - {} um range needed for a complete simulation. Interpolation will be used at the edges.".format(spec_min, spec_max, sim_min, sim_max))
 
@@ -821,6 +955,47 @@ def plot(self, idx=0, scale='linear', order=None, noise=True, traces=False, satu
         else:
             return fig
 
+    def plot_input(self, **kwargs):
+        """
+        Plot the 1d stellar spectrum, planet transmission spectrum, and transit lightcurve used as input where available
+        """
+        # Plot the data from the 'star' attribute
+        if self.star is not None:
+
+            # Input data
+            sfig = plotting.plot_spectrum(self.star[0], self.star[1], legend='Input Stellar Spectrum')
+            pfig = None
+            tfig = None
+
+            # Plot the data from the 'planet' attribute
+            if self.planet is not None:
+
+                pfig = plotting.plot_spectrum(self.planet[0], self.planet[1], ylabel='Transmission', legend='Input Planet Transmission', color='green')
+
+            # Plot the transit model
+            if self.tmodel is not None:
+
+                # Set orbital parameters with kwargs (e.g. rp=0.5 to see lightcurve at that planetary radius)
+                tmod = copy(self.tmodel)
+                for key, val in kwargs.items():
+                    setattr(tmod, key, val)
+
+                # Make the transit model
+                mod = batman.TransitModel(tmod, self.time.jd)
+                flux = mod.light_curve(tmod)
+                tfig = plotting.plot_spectrum(self.time.jd, flux, xlabel='Time [JD]', ylabel='Transmission', legend='Theoretical Lightcurve')
+
+                # Print the transit model params
+                print('Input Transit Model Parameters\n------------------------------')
+                for key, val in tmod.__dict__.items():
+                    print('{}: {}'.format(key, val))
+
+            show(column(list(filter(None, [sfig, pfig, tfig]))))
+
+        else:
+
+            print("No input to plot. Please set SossSim.star attribute with 1D data.")
+
     @run_required
     def plot_ramp(self, order=None, noise=True, draw=True):
         """
@@ -923,7 +1098,7 @@ def _reset_psfs(self):
                 # that we can convert the flux at each wavelegth into [ADU/s]
                 response = self.frame_time / (response * q.mJy * ac.c / (wave * q.um)**2).to(self.star[1].unit)
                 flux = np.interp(wave, self.star[0].value, self.star[1].value, left=0, right=0) * self.star[1].unit * response
-                cube = soss_trace.SOSS_psf_cube(filt=self.filter, order=order, subarray=self.subarray) * flux[:, None, None]
+                cube = soss_trace.SOSS_psf_cube(filt=self.filter, order=order, subarray=self.subarray, dirname=self.wave_name) * flux[:, None, None]
                 setattr(self, 'order{}_response'.format(order), response)
                 setattr(self, 'order{}_psfs'.format(order), cube)
 
@@ -960,6 +1135,29 @@ def _select_data(self, order, noise, reshape=True):
 
         return tso
 
+    def save_seed_image(self, filepath=None):
+        """
+        Save the seed image (no noise model) to a FITS file
+
+        Parameters
+        ----------
+        filepath: str (optional)
+            A custom filepath for the seed image
+        """
+        # Get the appropriate seed image segment
+        seed_seg = self.tso_ideal.astype(np.float64)
+
+        # NaNs and infs break np.random.poisson
+        seed_seg[np.where(np.isnan(seed_seg))] = 0.
+        seed_seg[np.where(np.isinf(seed_seg))] = 0.
+
+        # Write the file
+        seedfile, seedinfo = save_seed.save(seed_seg, self.paramfile, self.params, True, False, 1., 2048,
+                                            (self.nrows, self.ncols), {'xoffset': 0, 'yoffset': 0}, 1,
+                                            frametime=self.frame_time, filename=filepath)
+
+        return seedfile
+
     @property
     def star(self):
         """Getter for the stellar data"""
@@ -976,7 +1174,7 @@ def star(self, spectrum):
         """
         # Check if the star has been set
         if spectrum is None:
-            self.message("No star to simulate! Please set the self.star attribute!")
+            self.logger.info("No star to simulate! Please set the self.star attribute!")
             self._star = None
 
         else:
@@ -1007,13 +1205,15 @@ def star(self, spectrum):
             # Check the wavelength range
             spec_min = np.nanmin(spectrum[0][spectrum[0] > 0.])
             spec_max = np.nanmax(spectrum[0][spectrum[0] > 0.])
-            sim_min = np.nanmin(self.wave[self.wave > 0.]) * q.um
-            sim_max = np.nanmax(self.wave[self.wave > 0.]) * q.um
+            sim_min = np.nanmin(self.avg_wave[self.avg_wave > 0.]) * q.um
+            sim_max = np.nanmax(self.avg_wave[self.avg_wave > 0.]) * q.um
             if spec_min > sim_min or spec_max < sim_max:
                 print("Wavelength range of input spectrum ({} - {}) does not cover the {} - {} range needed for a complete simulation. Interpolation will be used at the edges.".format(spec_min, spec_max, sim_min, sim_max))
 
-            # Good to go
-            self._star = spectrum
+            # Good to go (Poisson statistics in obs_generator require float16)
+            non_nan = np.invert(np.isnan(spectrum[1]))
+            non_inf = np.invert(np.isinf(spectrum[1]))
+            self._star = [i[non_nan * non_inf] for i in spectrum]
 
     @property
     def subarray(self):
@@ -1043,7 +1243,6 @@ def subarray(self, subarr):
 
         # Set the dependent quantities
         self.wave = hu.wave_solutions(subarr)
-        self.avg_wave = np.mean(self.wave, axis=1)
         self.coeffs = locate_trace.trace_polynomial(subarray=subarr)
 
         # Get correct reference files
@@ -1138,14 +1337,16 @@ def tmodel(self, model, time_unit='days', model_grid='ACES'):
     @property
     def tso_ideal(self):
         """Getter for TSO data without noise"""
-        if self.tso_order1_ideal is None:
-            return None
+        # Get ideal data
+        ideal_data = [getattr(self, 'tso_order{}_ideal'.format(order)) for order in self.orders]
 
-        if 2 in self.orders:
-            return np.sum([self.tso_order1_ideal, self.tso_order2_ideal], axis=0)
+        # If no data, return None
+        if len(ideal_data) == 0:
+            return None
 
+        # Otherwise, return the sum of the orders
         else:
-            return self.tso_order1_ideal
+            return np.sum([getattr(self, 'tso_order{}_ideal'.format(order)) for order in self.orders], axis=0)
 
 
 class SossSpecSim(SossSim):
@@ -1175,6 +1376,7 @@ def __init__(self, ngrps=2, nints=2, filter='CLEAR', subarray='SUBSTRIP256', run
         if add_planet:
             self.planet = hu.PLANET_DATA
             self.tmodel = hu.transit_params(self.time.jd)
+            self.tmodel.t0 = np.mean(self.time.jd)
 
         # Run the simulation
         if run:
@@ -1183,7 +1385,7 @@ def __init__(self, ngrps=2, nints=2, filter='CLEAR', subarray='SUBSTRIP256', run
 
 class SossBlackbodySim(SossSim):
     """Generate a SossSim object with a blackbody spectrum"""
-    def __init__(self, ngrps=2, nints=2, teff=1800, filter='CLEAR', subarray='SUBSTRIP256', run=True, add_planet=False, scale=1., **kwargs):
+    def __init__(self, ngrps=2, nints=2, teff=1800, jmag=9.0, filter='CLEAR', subarray='SUBSTRIP256', run=True, add_planet=False, **kwargs):
         """Get the test data and load the object
 
         Parameters
@@ -1194,6 +1396,8 @@ def __init__(self, ngrps=2, nints=2, teff=1800, filter='CLEAR', subarray='SUBSTR
             The number of integrations for the exposure
         teff: int
             The effective temperature [K] of the test source
+        jmag: float
+            The J band magnitude to scale to
         filter: str
             The name of the filter to use, ['CLEAR', 'F277W']
         subarray: str
@@ -1202,30 +1406,33 @@ def __init__(self, ngrps=2, nints=2, teff=1800, filter='CLEAR', subarray='SUBSTR
             Run the simulation after initialization
         add_planet: bool
             Add a transiting exoplanet
-        scale: int, float
-            Scale the flux by the given factor
         """
         # Generate a blackbody at the given temperature
         bb = BlackBody(temperature=teff * q.K)
         wav = np.linspace(0.5, 2.9, 1000) * q.um
-        flux = (bb(wav) * q.sr / bb.bolometric_flux.value).to(FLAMBDA_CGS_UNITS, q.spectral_density(wav)) * 1E-8 * scale
+        flx = (bb(wav) * q.sr / bb.bolometric_flux.value).to(FLAMBDA_CGS_UNITS, q.spectral_density(wav))
+
+        # Scale model spectrum to user-input J-band
+        flx = ma.scale_spectrum(wav, flx, jmag)
 
         # Initialize base class
-        super().__init__(ngrps=ngrps, nints=nints, star=[wav, flux], subarray=subarray, filter=filter, **kwargs)
+        super().__init__(ngrps=ngrps, nints=nints, star=[wav, flx], subarray=subarray, filter=filter, **kwargs)
 
         # Add planet
         if add_planet:
             self.planet = hu.PLANET_DATA
             self.tmodel = hu.transit_params(self.time.jd)
+            self.tmodel.t0 = np.mean(self.time.jd)
+            self.tmodel.teff = teff
 
-        # Run the simulation
+            # Run the simulation
         if run:
             self.create()
 
 
 class SossModelSim(SossSim):
     """Generate a SossSim object with a theoretical ATLAS or PHOENIX stellar spectrum of choice"""
-    def __init__(self, ngrps=2, nints=2, teff=5700.0, logg=4.0, feh=0.0, alpha=0.0, jmag=9.0, models='ck04models', filter='CLEAR', subarray='SUBSTRIP256', run=True, add_planet=False, scale=1., **kwargs):
+    def __init__(self, ngrps=2, nints=2, teff=5700.0, logg=4.0, feh=0.0, alpha=0.0, jmag=9.0, stellar_model='phoenix', filter='CLEAR', subarray='SUBSTRIP256', run=True, add_planet=False, scale=1., **kwargs):
         """Get the test data and load the object
 
         Parameters
@@ -1257,34 +1464,29 @@ def __init__(self, ngrps=2, nints=2, teff=5700.0, logg=4.0, feh=0.0, alpha=0.0,
         scale: int, float
             Scale the flux by the given factor
         """
-        # # Retrieve PHOENIX or ATLAS stellar models:
-        # if stellar_model.lower() == 'phoenix':
-        #     w, f = model_atmospheres.get_phoenix_model(feh, alpha, teff, logg)
-        # elif stellar_model.lower() == 'atlas':
-        #     w, f = model_atmospheres.get_atlas_model(feh, teff, logg)
-        #
-        # # Now scale model spectrum to user-input J-band:
-        # f = model_atmospheres.scale_spectrum(w, f, jmag)
-
-        # TODO: Retrieve stellar model (https://synphot.readthedocs.io/en/latest/#id13)
-        # TODO: and trash the whole model_atmospheres.py module
-        spectrum = sphot.icat(models, teff, feh, logg) # TODO: Where is icat function?
-        bandpass = sphot.spectrum.SpectralElement.from_filter('2mass_j')
-        obs = sphot.observation.Observation(spectrum, bandpass)
-
-        sp_norm = spectrum.normalize(jmag, band=obs.bandpass)
-        w = sp_norm.waveset
-        f = sp_norm(w)
+        # Retrieve stellar model
+        if stellar_model.lower() == 'phoenix':
+            wav, flx = ma.get_phoenix_model(feh, alpha, teff, logg)
+        elif stellar_model.lower() == 'atlas':
+            wav, flx = ma.get_atlas_model(feh, teff, logg)
+
+        # Scale model spectrum to user-input J-band
+        flx = ma.scale_spectrum(wav, flx, jmag)
 
         # Initialize base class
-        super().__init__(ngrps=ngrps, nints=nints, star=[w, f], subarray=subarray, filter=filter, **kwargs)
+        super().__init__(ngrps=ngrps, nints=nints, star=[wav, flx], subarray=subarray, filter=filter, **kwargs)
 
         # Add planet
         if add_planet:
             self.planet = hu.PLANET_DATA
             self.tmodel = hu.transit_params(self.time.jd)
+            self.tmodel.t0 = np.mean(self.time.jd)
+            self.tmodel.teff = teff
+            self.tmodel.logg = logg
+            self.tmodel.feh = feh
+            self.tmodel.alpha = alpha
 
-        # Run the simulation
+            # Run the simulation
         if run:
             self.create()
 
diff --git a/mirage/utils/constants.py b/mirage/utils/constants.py
index 231f0cec5..1e3207532 100644
--- a/mirage/utils/constants.py
+++ b/mirage/utils/constants.py
@@ -25,6 +25,8 @@
                        "wfss": "NIS_WFSS", "soss": "NIS_SOSS"},
             "fgs": {"imaging": "FGS_IMAGE"}}
 
+DISPERSED_MODES = ['wfss', 'ts_grism']
+
 # Number of detector resets prior to the start of an exposure
 NUM_RESETS_BEFORE_EXP = {"nircam": {"full": 0, "sub": 1},
                          "niriss": {"full": 0, "sub": 1},
diff --git a/mirage/utils/read_fits.py b/mirage/utils/read_fits.py
index 8776957af..c27826b7a 100755
--- a/mirage/utils/read_fits.py
+++ b/mirage/utils/read_fits.py
@@ -117,8 +117,13 @@ def read_datamodel(self):
         #zeros, then set it to None here
         #self.zeroframe = h.zeroframe
         if np.all(h.zeroframe == 0):
-            logger.info("Zeroframe in {} is all zeros. Returning None.".format(self.file))
-            self.zeroframe = None
+            if 'RAPID' in h.meta.exposure.readpatt:
+                logger.info((f"Zeroframe in {os.path.basename(self.file)} is all zeros. Since the readpattern is RAPID, "
+                             "we grab a copy of the first group to be the zeroframe."))
+                self.zeroframe = h.data[:, 0, :, :]
+            else:
+                logger.info("Zeroframe in {} is all zeros. Returning None.".format(self.file))
+                self.zeroframe = None
         else:
             self.zeroframe = h.zeroframe
 
@@ -127,7 +132,7 @@ def read_datamodel(self):
         self.header = {}
         for key in self.translate:
             try:
-                self.header[key] = h.meta[self.translate[key]]
+                self.header[key] = eval(f'h.meta.{self.translate[key]}')
             except:
                 self.header[key] = None
 
diff --git a/mirage/utils/utils.py b/mirage/utils/utils.py
index 3173a4d21..2f26132c1 100755
--- a/mirage/utils/utils.py
+++ b/mirage/utils/utils.py
@@ -467,8 +467,6 @@ def full_paths(params, module_path, crds_dictionary, offline=False):
                                'movingTargetExtended', 'movingTargetToTrack',
                                'psf_wing_threshold_file', 'zodiacal', 'scattered'],
                 'cosmicRay': ['path'],
-                'newRamp': ['dq_configfile', 'sat_configfile', 'superbias_configfile',
-                            'refpix_configfile', 'linear_configfile'],
                 'Output': ['file', 'directory']}
 
     all_config_files = {'nircam': {'Reffiles-subarray_defs': 'NIRCam_subarray_definitions.list',
@@ -478,12 +476,7 @@ def full_paths(params, module_path, crds_dictionary, offline=False):
                                    'Reffiles-filter_throughput': 'placeholder.txt',
                                    'Reffiles-filtpupilcombo': 'nircam_filter_pupil_pairings.list',
                                    'Reffiles-filter_wheel_positions': 'nircam_filter_and_pupil_wheel_positions.txt',
-                                   'simSignals-psf_wing_threshold_file': 'nircam_psf_wing_rate_thresholds.txt',
-                                   'newRamp-dq_configfile': 'dq_init.cfg',
-                                   'newRamp-sat_configfile': 'saturation.cfg',
-                                   'newRamp-superbias_configfile': 'superbias.cfg',
-                                   'newRamp-refpix_configfile': 'refpix.cfg',
-                                   'newRamp-linear_configfile': 'linearity.cfg'},
+                                   'simSignals-psf_wing_threshold_file': 'nircam_psf_wing_rate_thresholds.txt'},
                         'niriss': {'Reffiles-subarray_defs': 'niriss_subarrays.list',
                                    'Reffiles-flux_cal': 'niriss_zeropoints.list',
                                    'Reffiles-crosstalk': 'niriss_xtalk_zeros.txt',
@@ -491,12 +484,7 @@ def full_paths(params, module_path, crds_dictionary, offline=False):
                                    'Reffiles-filter_throughput': 'placeholder.txt',
                                    'Reffiles-filtpupilcombo': 'niriss_dual_wheel_list.txt',
                                    'Reffiles-filter_wheel_positions': 'niriss_filter_and_pupil_wheel_positions.txt',
-                                   'simSignals-psf_wing_threshold_file': 'niriss_psf_wing_rate_thresholds.txt',
-                                   'newRamp-dq_configfile': 'dq_init.cfg',
-                                   'newRamp-sat_configfile': 'saturation.cfg',
-                                   'newRamp-superbias_configfile': 'superbias.cfg',
-                                   'newRamp-refpix_configfile': 'refpix.cfg',
-                                   'newRamp-linear_configfile': 'linearity.cfg'},
+                                   'simSignals-psf_wing_threshold_file': 'niriss_psf_wing_rate_thresholds.txt'},
                         'fgs': {'Reffiles-subarray_defs': 'guider_subarrays.list',
                                 'Reffiles-flux_cal': 'guider_zeropoints.list',
                                 'Reffiles-crosstalk': 'guider_xtalk_zeros.txt',
@@ -504,12 +492,8 @@ def full_paths(params, module_path, crds_dictionary, offline=False):
                                 'Reffiles-filter_throughput': 'placeholder.txt',
                                 'Reffiles-filtpupilcombo': 'guider_filter_dummy.list',
                                 'Reffiles-filter_wheel_positions': 'dummy.txt',
-                                'simSignals-psf_wing_threshold_file': 'fgs_psf_wing_rate_thresholds.txt',
-                                'newRamp-dq_configfile': 'dq_init.cfg',
-                                'newRamp-sat_configfile': 'saturation.cfg',
-                                'newRamp-superbias_configfile': 'superbias.cfg',
-                                'newRamp-refpix_configfile': 'refpix.cfg',
-                                'newRamp-linear_configfile': 'linearity.cfg'}}
+                                'simSignals-psf_wing_threshold_file': 'fgs_psf_wing_rate_thresholds.txt'}
+                        }
     config_files = all_config_files[params['Inst']['instrument'].lower()]
 
     for key1 in pathdict:
diff --git a/mirage/yaml/yaml_generator.py b/mirage/yaml/yaml_generator.py
index 538cdb479..e76995832 100755
--- a/mirage/yaml/yaml_generator.py
+++ b/mirage/yaml/yaml_generator.py
@@ -434,7 +434,6 @@ def add_crds_reffile_names(self):
         photom_arr = deepcopy(empty_col)
         ipc_arr = deepcopy(empty_col)
         ipc_invert = np.array([True] * len(self.info['Instrument']))
-        pixelAreaMap_arr = deepcopy(empty_col)
         transmission_arr = deepcopy(empty_col)
         badpixmask_arr = deepcopy(empty_col)
         pixelflat_arr = deepcopy(empty_col)
@@ -488,8 +487,6 @@ def add_crds_reffile_names(self):
                             crds_key = 'flat'
                         elif key == 'astrometric':
                             crds_key = 'distortion'
-                        elif key == 'pixelAreaMap':
-                            crds_key = 'area'
                         else:
                             crds_key = key
                         reffiles[crds_key] = manual_reffiles[key]
@@ -521,7 +518,6 @@ def add_crds_reffile_names(self):
             photom_arr[match] = reffiles['photom']
             ipc_arr[match] = reffiles['ipc']
             ipc_invert[match] = reffiles['invert_ipc']
-            pixelAreaMap_arr[match] = reffiles['area']
             transmission_arr[match] = reffiles['transmission']
             badpixmask_arr[match] = reffiles['mask']
             pixelflat_arr[match] = reffiles['flat']
@@ -534,7 +530,6 @@ def add_crds_reffile_names(self):
         self.info['photom'] = list(photom_arr)
         self.info['ipc'] = list(ipc_arr)
         self.info['invert_ipc'] = list(ipc_invert)
-        self.info['pixelAreaMap'] = list(pixelAreaMap_arr)
         self.info['transmission'] = list(transmission_arr)
         self.info['badpixmask'] = list(badpixmask_arr)
         self.info['pixelflat'] = list(pixelflat_arr)
@@ -558,7 +553,6 @@ def add_reffile_overrides(self):
         distortion_arr = deepcopy(empty_col)
         photom_arr = deepcopy(empty_col)
         ipc_arr = deepcopy(empty_col)
-        pixelAreaMap_arr = deepcopy(empty_col)
         transmission_arr = deepcopy(empty_col)
         badpixmask_arr = deepcopy(empty_col)
         pixelflat_arr = deepcopy(empty_col)
@@ -592,7 +586,6 @@ def add_reffile_overrides(self):
             distortion_arr[match] = manual_reffiles['distortion']
             photom_arr[match] = manual_reffiles['photom']
             ipc_arr[match] = manual_reffiles['ipc']
-            pixelAreaMap_arr[match] = manual_reffiles['area']
             transmission_arr[match] = manual_reffiles['transmission']
             badpixmask_arr[match] = manual_reffiles['badpixmask']
             pixelflat_arr[match] = manual_reffiles['pixelflat']
@@ -604,7 +597,6 @@ def add_reffile_overrides(self):
         self.info['astrometric'] = list(distortion_arr)
         self.info['photom'] = list(photom_arr)
         self.info['ipc'] = list(ipc_arr)
-        self.info['pixelAreaMap'] = list(pixelAreaMap_arr)
         self.info['transmission'] = list(transmission_arr)
         self.info['badpixmask'] = list(badpixmask_arr)
         self.info['pixelflat'] = list(pixelflat_arr)
@@ -717,7 +709,6 @@ def create_inputs(self):
             self.info['photom'] = column_data
             self.info['ipc'] = column_data
             self.info['invert_ipc'] = np.array([True] * len(self.info['Instrument']))
-            self.info['pixelAreaMap'] = column_data
             self.info['transmission'] = column_data
             self.info['badpixmask'] = column_data
             self.info['pixelflat'] = column_data
@@ -1539,23 +1530,8 @@ def path_defs(self):
         ensure_dir_exists(self.output_dir)
         ensure_dir_exists(self.simdata_output_dir)
 
-        # self.subarray_def_file = self.set_config(self.subarray_def_file, 'subarray_def_file')
-        # self.readpatt_def_file = self.set_config(self.readpatt_def_file, 'readpatt_def_file')
-        # self.filtpupil_pairs = self.set_config(self.filtpupil_pairs, 'filtpupil_pairs')
-        # self.fluxcal = self.set_config(self.fluxcal, 'fluxcal')
-        # self.filter_throughput = self.set_config(self.filter_throughput, 'filter_throughput')
-        # self.dq_init_config = self.set_config(self.dq_init_config, 'dq_init_config')
-        # self.refpix_config = self.set_config(self.refpix_config, 'refpix_config')
-        # self.saturation_config = self.set_config(self.saturation_config, 'saturation_config')
-        # self.superbias_config = self.set_config(self.superbias_config, 'superbias_config')
-        # self.linearity_config = self.set_config(self.linearity_config, 'linearity_config')
-
         if self.observation_list_file is not None:
             self.observation_list_file = os.path.abspath(os.path.expandvars(self.observation_list_file))
-        # if self.crosstalk not in [None, 'config']:
-        #     self.crosstalk = os.path.abspath(os.path.expandvars(self.crosstalk))
-        # elif self.crosstalk == 'config':
-        #     self.crosstalk = os.path.join(self.modpath, 'config', self.configfiles['crosstalk'])
 
     def reffile_setup(self):
         """Create lists of reference files associate with each detector.
@@ -1590,11 +1566,6 @@ def reffile_setup(self):
                 self.psfpixfrac[instrument] = 0.1
 
             # Set global file paths
-            self.configfiles[instrument]['dq_init_config'] = os.path.join(self.modpath, 'config', 'dq_init.cfg')
-            self.configfiles[instrument]['saturation_config'] = os.path.join(self.modpath, 'config', 'saturation.cfg')
-            self.configfiles[instrument]['superbias_config'] = os.path.join(self.modpath, 'config', 'superbias.cfg')
-            self.configfiles[instrument]['refpix_config'] = os.path.join(self.modpath, 'config', 'refpix.cfg')
-            self.configfiles[instrument]['linearity_config'] = os.path.join(self.modpath, 'config', 'linearity.cfg')
             self.configfiles[instrument]['filter_throughput'] = os.path.join(self.modpath, 'config', 'placeholder.txt')
 
         for instrument in 'miri nirspec'.split():
@@ -1843,17 +1814,6 @@ def reffiles_from_dict(self, obs_params):
         except KeyError:
             files['ipc'] = 'none'
 
-        # pixel area map
-        try:
-            if instrument == 'nircam':
-                files['area'] = self.reffile_overrides[instrument]['area'][detector][filtername][pupilname][exptype]
-            elif instrument == 'niriss':
-                files['area'] = self.reffile_overrides[instrument]['area'][filtername][pupilname][exptype]
-            elif instrument == 'fgs':
-                files['area'] = self.reffile_overrides[instrument]['area'][detector]
-        except KeyError:
-            files['area'] = 'none'
-
         # transmission image
         try:
             if instrument == 'nircam':
@@ -2029,8 +1989,6 @@ def write_yaml(self, input):
             f.write(('  invertIPC: {}      # Invert the IPC kernel before the convolution. True or False. Use True if the kernel is '
                      'designed for the removal of IPC effects, like the JWST reference files are.\n'.format(input['invert_ipc'])))
             f.write('  occult: None                                    # Occulting spots correction image\n')
-            f.write(('  pixelAreaMap: {}      # Pixel area map for the detector. Used to introduce distortion into the output ramp.\n'
-                     .format(input['pixelAreaMap'])))
             f.write(('  transmission: {}      # Transmission image containing fractional throughput map. (e.g. to imprint occulters into fov\n'
                      .format(input['transmission'])))
             f.write(('  subarray_defs: {} # File that contains a list of all possible subarray names and coordinates\n'
@@ -2164,13 +2122,6 @@ def write_yaml(self, input):
             f.write('  rotation: {}                    # PA_V3 in degrees, i.e. the position angle of the V3 axis at V1 (V2=0, V3=0) measured from N to E.\n'.format(pav3_value))
             f.write('  tracking: {}   #Telescope tracking. Can be sidereal or non-sidereal\n'.format(input['Tracking']))
             f.write('\n')
-            f.write('newRamp:\n')
-            f.write('  dq_configfile: {}\n'.format(self.configfiles[instrument.lower()]['dq_init_config']))
-            f.write('  sat_configfile: {}\n'.format(self.configfiles[instrument.lower()]['saturation_config']))
-            f.write('  superbias_configfile: {}\n'.format(self.configfiles[instrument.lower()]['superbias_config']))
-            f.write('  refpix_configfile: {}\n'.format(self.configfiles[instrument.lower()]['refpix_config']))
-            f.write('  linear_configfile: {}\n'.format(self.configfiles[instrument.lower()]['linearity_config']))
-            f.write('\n')
             f.write('Output:\n')
             # f.write('  use_stsci_output_name: {} # Output filename should follow STScI naming conventions (True/False)\n'.format(outtf))
             f.write('  directory: {}  # Output directory\n'.format(self.simdata_output_dir))
diff --git a/requirements.txt b/requirements.txt
index 1a4a632cb..067a12f07 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,25 +1,26 @@
-asdf>=2.1.0
-astropy>=4.3.1
-astroquery>=0.3.8
-bokeh>=2.2.3
-batman-package>=2.4.8
-crds>=7.4.1
-grismconf>=1.24
-h5py>=2.8.0
+asdf>=2.13.0
+astropy>=5.1.1
+astroquery>=0.4.6
+bokeh==2.4.3
+batman-package>=2.4.9
+crds>=11.16.16
+grismconf>=1.32
+h5py>=3.7.0
 hotsoss>=0.1.7
-ipython>=7.18.1
+ipython>=8.6.0
 jupyter>=1.0.0
-jwst>=1.3.2
-jwst-backgrounds>=1.1.1
-lxml>=3.6.4
-matplotlib>=3.0.0
-nircam_gsim>=1.56
-numpy>=1.16
-photutils>=0.6
-pysiaf>=0.6.1
-pytest>=3.8.1
-scipy>=1.1.0
-sphinx>=2.1
-synphot>=0.2.0
-webbpsf>=0.9.0
-pyyaml>=5.1.2
+jwst>=1.8.2
+jwst-backgrounds>=1.1.2
+lxml>=4.9.1
+matplotlib>=3.6.2
+nircam_gsim>=1.60
+numpy>=1.23.4
+photutils>=1.5.0
+pysiaf==0.18.0
+pytest>=7.2.0
+scipy>=1.9.3
+sphinx>=5.3.0
+synphot>=1.1.1
+pyyaml>=6.0
+webbpsf>=1.1.0
+
diff --git a/setup.py b/setup.py
index 583532bb3..aa80eb14a 100644
--- a/setup.py
+++ b/setup.py
@@ -89,31 +89,30 @@ def run(self):
     use_scm_version=True,
     setup_requires=['setuptools_scm'],
     install_requires=[
-        'asdf>=2.1.0',
-        'astropy>=4.3.1',
-        'astroquery>=0.3.8',
-        'bokeh>=2.2.3',
+        'asdf>=2.13.0',
+        'astropy>=5.1.1',
+        'astroquery>=0.4.6',
+        'bokeh==2.4.3',
         'batman-package',
-        'crds>=7.4.1',
+        'crds>=11.16.16',
         'grismconf',
-        'gwcs>=0.11',
-        'h5py>=2.8.0',
+        'gwcs>=0.18.1',
+        'h5py>=3.7.0',
         'hotsoss==0.1.7',
         'ipython',
-        'jinja2==3.0.3',
         'jupyter',
         'jwst',
-        'jwst-backgrounds>=1.1.1',
-        'lxml>=3.6.4',
-        'matplotlib>=3.0.0',
-        'NIRCAM_Gsim',
+        'jwst-backgrounds>=1.1.2',
+        'lxml>=4.9.1',
+        'matplotlib>=3.6.2',
+        'nircam_gsim',
         'numpy',
-        'photutils>=0.7.2',
-        'pysiaf>=0.6.1',
-        'scipy>=1.1.0',
-        'synphot>=0.2.0',
-        'webbpsf>=0.9.0',
-        'pyyaml>=5.1.2'
+        'photutils>=1.5.0',
+        'pysiaf==0.18.0',
+        'scipy>=1.9.3',
+        'synphot>=1.1.1',
+        'webbpsf>=1.1.0',
+        'pyyaml>=6.0'
     ],
     include_package_data=True,
     extras_require={


Test patch:
diff --git a/tests/test_ra_dec_to_x_y.py b/tests/test_ra_dec_to_x_y.py
index d417bbf4e..7bad2fd68 100644
--- a/tests/test_ra_dec_to_x_y.py
+++ b/tests/test_ra_dec_to_x_y.py
@@ -8,262 +8,14 @@
 the test_mirage_subarray_source_location subdirectory
 """
 
+from astropy.table import Table
 import numpy as np
 import pysiaf
+import pytest
 
 from mirage.seed_image import catalog_seed_image
 from mirage.utils import siaf_interface
 
-reference_file_values = {
-'nircam_NRCA1_FULL': ([1023.4999999998163, 1013.6655281785538, 1003.8299720772586, 984.1556194677335, 949.715171199927, 846.3161706399252, 530.511072051233, 35.229179419690695], [1023.4999999998024, 1033.3109865349104, 1043.122689869189, 1062.7482342576648, 1097.0997294094025, 1200.2048432008278, 1514.8651233861085, 2007.624512937195]),
-'nircam_NRCA1_SUB160': ([79.47575618678025, 69.66838521645195, 59.859819900987986, 40.23911767044774, 5.891489647969138, -97.2373108295451, -412.2985763208228, -906.6825875959386], [79.49770829260206, 89.42717067086005, 99.3572632124251, 119.21932657806428, 153.9838998863188, 258.32194748632446, 576.6820423169911, 1075.0470216746535]),
-'nircam_NRCA1_SUB320': ([159.47558091216615, 149.66550269545337, 139.8542386707577, 120.22816466854283, 85.87121852763767, -17.284902266516838, -332.42341956509244, -826.9087414221374], [159.49570717060442, 169.41549949944988, 179.33592894473213, 199.1786869908267, 233.90954302268483, 338.1469524512713, 656.2051752443804, 1154.113986493605]),
-'nircam_NRCA1_SUB640': ([319.47667565289953, 309.66140058191604, 299.84495704503433, 280.2085761428766, 245.83376069688575, 142.62532411204575, -172.6603187612393, -667.3354208960037], [319.4926777609121, 329.3929293893109, 339.2938320873743, 359.0975784916104, 393.7602984194343, 497.7943256295423, 815.2423013308726, 1312.2279086000126]),
-'nircam_NRCA1_GRISMTS': ([1979.2313427254185, 1969.4657029403556, 1959.6987854642452, 1940.1611289202515, 1905.9580287794251, 1803.2566759785423, 1489.4402307546106, 996.8101661301396], [1081.6230605981543, 1091.4652484083779, 1101.308246675403, 1120.9966617315342, 1155.4590807960228, 1258.90383914193, 1574.6635579960184, 2069.348907430881]),
-'nircam_NRCA1_GRISMTS256': ([1980.593969382693, 1970.8751396619045, 1961.1549394565927, 1941.710440362619, 1907.6694832139522, 1805.4479302391449, 1493.034502532663, 1002.4207430035899], [166.8560247850687, 176.5931842308039, 186.33137545302748, 205.81083726974032, 239.90969257662925, 342.27954897633697, 654.9032345150479, 1145.0875774252333]),
-'nircam_NRCA1_GRISMTS128': ([1980.593969382693, 1970.8751396619045, 1961.1549394565927, 1941.710440362619, 1907.6694832139522, 1805.4479302391449, 1493.034502532663, 1002.4207430035899], [64.85602478506871, 74.5931842308039, 84.33137545302748, 103.81083726974032, 137.90969257662925, 240.27954897633697, 552.9032345150479, 1043.0875774252333]),
-'nircam_NRCA1_GRISMTS64': ([1980.593969382693, 1970.8751396619045, 1961.1549394565927, 1941.710440362619, 1907.6694832139522, 1805.4479302391449, 1493.034502532663, 1002.4207430035899], [32.85602478506871, 42.5931842308039, 52.331375453027476, 71.81083726974032, 105.90969257662925, 208.27954897633697, 520.9032345150479, 1011.0875774252333]),
-'nircam_NRCA1_FP3MIMF': ([230.01329645230203, 220.16578016329447, 210.3173027215032, 190.61747864833296, 156.1336559827463, 52.61388742745237, -263.46740835808714, -758.867577539334], [228.035810836402, 237.73856759049477, 247.44213669726514, 266.8516978803584, 300.8261303287875, 402.8068571504516, 714.1001899332017, 1201.7638443199696]),
-'nircam_NRCA2_FULL': ([1023.5000000000364, 1013.5963968852795, 1003.6919523863716, 983.8805562714804, 949.2026590967788, 845.1099529897176, 527.3780604464274, 29.763924173508826], [1023.4999999996849, 1033.5071104502902, 1043.5144501536506, 1063.529799543284, 1098.5587169468986, 1203.6593720689932, 1524.0438340337425, 2024.5270119055504]),
-'nircam_NRCA2_SUB160': ([79.54427460488432, 69.73797864713833, 59.9305132426025, 40.31208572779815, 5.968679873873953, -97.14558613356894, -412.1443826645177, -906.3676673394888], [79.46916662128297, 89.43758570674981, 99.40657975828083, 119.34628025662391, 154.24618466127345, 258.9861122762421, 578.531581590951, 1078.617115924541]),
-'nircam_NRCA2_SUB320': ([159.54188494413756, 149.72616576465452, 139.9093008986756, 120.27214595588703, 85.89619764879808, -17.313910895855315, -332.58746370339577, -827.1806668062044], [159.47092108037793, 169.44382519784892, 179.41727889898016, 199.3658223513538, 234.28095589522366, 339.06466926056737, 658.7251985490946, 1158.9281354936581]),
-'nircam_NRCA2_SUB640': ([319.5357597688949, 309.7018014528446, 299.86674641473746, 280.19335858571776, 245.75447886593497, 142.35927399288312, -173.4421695224578, -668.7346287976625], [319.4754272890099, 329.4566775209988, 339.4384252119089, 359.4033997331219, 394.3467813240138, 499.21131299218337, 819.0798866266343, 1319.4764456759651]),
-'nircam_NRCA2_FP4MIMF': ([227.99187975603672, 218.03633113619844, 208.08036588496793, 188.16721191969032, 153.31540642792322, 48.73375731775832, -270.1578387442628, -768.4024322602579], [1819.001677607011, 1829.0107218027817, 1839.0195568345182, 1859.0365722450479, 1894.0641058389797, 1999.1268245350198, 2319.0559617225326, 2817.6175196634968]),
-'nircam_NRCA2_MASK210R': ([348.38977658825, 338.4375984775261, 328.48503203060795, 308.57876202638204, 273.7392882071024, 169.19695528496936, -149.54927867999515, -647.4631253158907], [1643.6490057786837, 1653.7154160297741, 1663.7812953780008, 1683.911427903734, 1719.1337663903437, 1824.756211563918, 2146.1451148257684, 2646.128780715589]),
-'nircam_NRCA2_TAMASK210R': ([89.96039966596823, 80.00350722329688, 70.0462642018341, 50.13075486441028, 15.275480236944873, -89.31138945905604, -408.16526728290626, -906.151812849799], [1386.964094673866, 1397.0109836222855, 1407.0574016806372, 1427.1487927146118, 1462.3039200894627, 1567.7293156128726, 1888.562993008456, 2387.834585944479]),
-'nircam_NRCA2_FSTAMASK210R': ([90.8414318960771, 80.88864732874731, 70.93545102356427, 51.02785038685602, 16.18581670684648, -88.36603298283956, -407.1602456062069, -905.219261106582], [1386.8110226814147, 1396.8670031784586, 1406.9225538767187, 1427.032334381539, 1462.2200465789065, 1567.7463680086057, 1888.9195494795258, 2388.8350579999774]),
-'nircam_NRCA2_FULL_MASK210R': ([771.38977658825, 761.4375984775261, 751.485032030608, 731.578762026382, 696.7392882071024, 592.1969552849694, 273.45072132000485, -224.4631253158907], [2800.6490057786837, 2810.715416029774, 2820.781295378001, 2840.911427903734, 2876.1337663903437, 2981.756211563918, 3303.1451148257684, 3803.128780715589]),
-'nircam_NRCA3_FULL': ([1023.4999999999632, 1013.8545390985643, 1004.2075267718307, 984.9088620995956, 951.121385898854, 849.6471994917788, 539.3930480288933, 51.80116507356729], [1023.5000000000216, 1033.3612380824643, 1043.2234600972768, 1062.9508405146105, 1097.483097468811, 1201.1497303171354, 1517.6951539208148, 2013.9237011053606]),
-'nircam_NRCA3_SUB160': ([79.5338418935496, 69.75304155742208, 59.9709852161335, 40.40311577494606, 6.147350037185902, -96.71043319395221, -410.98910346476873, -904.2926377520157], [79.46730385721298, 89.40630741138466, 99.34597657502536, 119.22729957101228, 154.0259188862533, 258.4687236020691, 577.1728651885951, 1076.1569949077625]),
-'nircam_NRCA3_SUB320': ([159.53350680468827, 149.76305670091506, 139.99132768970298, 120.44404420391788, 86.22408341853009, -16.52797168555162, -330.50028911360914, -823.3767125699183], [159.46769402075347, 169.40126159211718, 179.33551941151973, 199.20609361247898, 233.98613956261102, 338.3750356150822, 656.9318609746533, 1155.7404964444077]),
-'nircam_NRCA3_SUB640': ([319.53099854977563, 309.7818385813846, 300.03135356116695, 280.5264197692136, 246.38012791058497, 143.8457036816933, -169.49475211008212, -661.4838227522762], [319.4700735691497, 329.39216120214724, 339.3149888055443, 359.16285156005097, 393.9036296356353, 498.1783548942544, 816.4209115858021, 1314.844842721146]),
-'nircam_NRCA3_GRISMTS': ([1045.0010127124685, 1035.3540796463683, 1025.7055980699247, 1006.4040035537652, 972.6114274296342, 871.1221414679509, 560.8236368821802, 73.16672746439508], [1089.9986569174116, 1099.867841526581, 1109.7379968433038, 1129.4812043926459, 1164.041033237564, 1267.7894414018463, 1584.5758110494012, 2081.1576079700494]),
-'nircam_NRCA3_GRISMTS256': ([1044.9908464362495, 1035.398090575211, 1025.803657123932, 1006.609774654094, 973.0044775299864, 872.0680159654762, 563.3775709436893, 78.03195682720093], [175.01721784844858, 184.77332815292277, 194.530668767493, 214.04902086367815, 248.21781083593567, 350.81142214039187, 664.2371413845646, 1155.9964686548549]),
-'nircam_NRCA3_GRISMTS128': ([1044.9908464362495, 1035.398090575211, 1025.803657123932, 1006.609774654094, 973.0044775299864, 872.0680159654762, 563.3775709436893, 78.03195682720093], [64.01721784844858, 73.77332815292277, 83.53066876749301, 103.04902086367815, 137.21781083593567, 239.81142214039187, 553.2371413845646, 1044.9964686548549]),
-'nircam_NRCA3_GRISMTS64': ([1044.9908464362495, 1035.398090575211, 1025.803657123932, 1006.609774654094, 973.0044775299864, 872.0680159654762, 563.3775709436893, 78.03195682720093], [32.01721784844858, 41.77332815292277, 51.53066876749301, 71.04902086367815, 105.21781083593567, 207.81142214039187, 521.2371413845646, 1012.9964686548549]),
-'nircam_NRCA3_DHSPIL': ([1014.001585272133, 1004.352044284634, 994.7009609729531, 975.3941814523668, 941.5925903448107, 840.0766998059205, 529.700995041399, 41.93435895381242], [1078.9981737336839, 1088.8656158973927, 1098.7340269562935, 1118.4737405954004, 1153.0274380126616, 1256.7573254465017, 1573.4861748654569, 2069.9752624690586]),
-'nircam_NRCA3_DHSPIL_SUB96': ([47.00158527213296, 37.35204428463396, 27.700960972953112, 8.394181452366752, -25.407409655189326, -126.9233001940795, -437.299004958601, -925.0656410461876], [47.99817373368387, 57.86561589739267, 67.73402695629352, 87.47374059540039, 122.0274380126616, 225.75732544650168, 542.4861748654569, 1038.9752624690586]),
-'nircam_NRCA3_DHSPIL_WEDGES': ([1021.5079426491114, 1011.788675215786, 1002.0680061394694, 982.6224750308199, 948.5794053915724, 846.3491051526423, 533.885314252245, 43.11817044266081], [2454.491780199024, 2464.4997516250005, 2474.5083962830568, 2494.5276926728575, 2529.5678349642226, 2634.7356979518304, 2955.6531471779217, 3458.1031260959085]),
-'nircam_NRCA3_FP1': ([460.0234470283126, 450.3024288404314, 440.5800270499893, 421.13108454264477, 387.0822177466363, 284.83583231727744, -27.665458638789914, -518.4624565800366], [1409.9764905883535, 1419.8695812097847, 1429.7634933031618, 1449.5537689057956, 1484.1945487290184, 1588.175178244104, 1905.575201115541, 2402.846542540273]),
-'nircam_NRCA3_FP1_SUB8': ([3.023447028312603, -6.697571159568611, -16.419972950010674, -35.86891545735523, -69.91778225336373, -172.16416768272256, -484.6654586387899, -975.4624565800366], [3.9764905883534993, 13.869581209784656, 23.763493303161795, 43.55376890579555, 78.19454872901838, 182.17517824410402, 499.57520111554095, 996.8465425402728]),
-'nircam_NRCA3_FP1_SUB64': ([31.023447028312603, 21.30242884043139, 11.580027049989326, -7.868915457355229, -41.917782253363725, -144.16416768272256, -456.6654586387899, -947.4624565800366], [31.9764905883535, 41.869581209784656, 51.763493303161795, 71.55376890579555, 106.19454872901838, 210.17517824410402, 527.575201115541, 1024.8465425402728]),
-'nircam_NRCA3_FP2MIMF': ([1818.9873320643433, 1809.4840422052039, 1799.9788350385938, 1780.962690724537, 1747.6661676853284, 1647.6391568382692, 1341.5751425429567, 859.9494226710383], [228.02363813289878, 237.79042583948285, 247.55858723885126, 267.09900775628205, 301.3077699692599, 404.03131546121074, 717.9380727311263, 1210.6668558086637]),
-'nircam_NRCA3_SUB64P': ([31.523787951745817, 21.830938232639255, 12.1366580185869, -7.256180511679759, -41.207304222835546, -143.1636760595734, -454.807853110387, -944.3351916827589], [31.50000796450513, 41.23782523731029, 50.97672033081153, 70.45772718648345, 104.5597225304557, 206.94225365030616, 519.6329271182226, 1010.0002780505613]),
-'nircam_NRCA3_SUB160P': ([79.49562954061662, 70.0228297124504, 60.54802346550173, 41.59241563150772, 8.400990251983785, -91.31696426243434, -396.49215841395153, -876.8650791275685], [79.51960073223972, 89.26471844872367, 99.01130392038999, 118.50885274527195, 152.6434778912294, 255.1512042653676, 568.4564497266822, 1060.3901277143418]),
-'nircam_NRCA3_SUB400P': ([199.4885828804363, 189.99103157857644, 180.49154647548266, 161.48679717255345, 128.21005970786518, 28.241251201632167, -277.65520997402314, -759.0443534775466], [199.52314394752113, 209.285888005973, 219.05002318844186, 238.5824431932259, 272.77736914949344, 375.46062759072856, 689.2550286917876, 1181.8351424301518]),
-'nircam_NRCA4_FULL': ([1023.5000000000055, 1013.6945302466736, 1003.887723099901, 984.2701087010541, 949.926512782387, 846.7993873575252, 531.647688499598, 36.83329082916873], [1023.4999999997228, 1033.520336044648, 1043.5411782478134, 1063.5843676323186, 1098.6647068976233, 1203.9407171664652, 1525.0688322212357, 2027.4542323738174]),
-'nircam_NRCA4_SUB160': ([79.46748477099038, 69.62126700445378, 59.773817532090106, 40.0752349004955, 5.590956500590437, -97.95054476824816, -414.29522501557153, -910.7649360198161], [79.48185103377159, 89.39647205461836, 99.3116931837992, 119.14392350388482, 153.8559991948341, 258.03433334353485, 575.886822110811, 1073.392535063897]),
-'nircam_NRCA4_SUB320': ([159.46968884007606, 149.6265277851046, 139.78212654010088, 120.08961491625905, 85.61587916607846, -17.894617350746103, -334.1506049927748, -830.4998152686298], [159.4845318437632, 169.40849981090332, 179.3330608038757, 199.1839495487867, 233.92860884238678, 338.2041636354503, 656.3478442746559, 1154.29156377562]),
-'nircam_NRCA4_SUB640': ([319.47500881991334, 309.63817631698214, 299.80008655492145, 280.12014673120314, 245.6682476644637, 142.22201178680598, -173.8496878129322, -669.9465548917888], [319.48970825378353, 329.4321656478478, 339.37520158365885, 359.26299662578356, 394.0721013597798, 498.5399042287405, 817.258953321547, 1316.0662811184793]),
-'nircam_NRCA4_FP5MIMF': ([1702.99845265554, 1693.2293173109229, 1683.4587508789102, 1663.9133380479407, 1629.6952032539637, 1526.9377667378963, 1212.8535714102095, 719.5422631230435], [1702.9814049070237, 1713.0705689434035, 1723.1601466244308, 1743.340527726753, 1778.6600476700446, 1884.6465182007232, 2207.8694373013354, 2713.282306308629]),
-'nircam_NRCA4_MASKSWB': ([364.3839339648887, 354.47018936922586, 344.55542867207737, 324.7228757412762, 290.0062700449299, 185.78454061345747, -132.46146190467505, -631.25981411217], [1630.8219655978428, 1640.9269198245279, 1651.0317596922814, 1671.2410724970014, 1706.606067163656, 1812.6886935426246, 2135.805722981411, 2639.659907438592]),
-'nircam_NRCA4_TAMASKSWB': ([106.96601764234856, 97.03680463009584, 87.1066218928471, 67.2433641435955, 32.473472565148654, -71.90468013294424, -390.5949873484219, -889.9836028883692], [1373.878420804067, 1383.9612689060568, 1394.044051841624, 1414.2093991860538, 1449.4979347526314, 1555.3549347044013, 1877.8212701534244, 2380.78415996269]),
-'nircam_NRCA4_TAMASKSWBS': ([110.01021279512713, 100.13037488500345, 90.2493995252197, 70.48405147691142, 35.883871421010554, -67.99779815848467, -385.29825894749627, -882.9347681455181], [1372.686210152287, 1382.7955882650895, 1392.9050045301715, 1413.1239306182397, 1448.507241522464, 1554.65651914222, 1878.0935947419553, 2382.8604134498373]),
-'nircam_NRCA4_FSTAMASKSWB': ([108.00445290939956, 98.09891682925934, 88.19232576205536, 68.37599447454704, 33.68739423435886, -70.45333747922427, -388.48326803691066, -887.0569166306293], [1373.8386951444763, 1383.9352411967257, 1394.0317759784248, 1414.224789845378, 1449.5622702851142, 1555.570257859731, 1878.5385855662257, 2382.43622414741]),
-'nircam_NRCA4_MASKSWB_F182M': ([307.04432419658144, 297.12646758182177, 287.2076099431787, 267.3669085454253, 232.6361897307272, 128.37326074578277, -189.9871635503457, -688.9262286035364], [1631.0100203930856, 1641.1125168206004, 1651.2148896748413, 1671.419240610433, 1706.7754616250959, 1812.8310563883829, 2135.858535233938, 2639.54698986551]),
-'nircam_NRCA4_MASKSWB_F187N': ([315.99716245197135, 306.0799484079548, 296.1617309548851, 276.3223027424657, 241.5937887873588, 137.33729392909822, -181.00528714774646, -679.9225181353536], [1630.9803621878955, 1641.083239465297, 1651.1859946846557, 1671.3911149295973, 1706.748697098863, 1812.808492186693, 2135.8499503249036, 2639.5644844842527]),
-'nircam_NRCA4_MASKSWB_F210M': ([363.07458299361383, 353.16077300588404, 343.2459471090492, 323.4132643546069, 288.6964333175007, 184.47404204013299, -133.77384444871666, -632.5747177344767], [1630.8229782620037, 1640.9278468827665, 1651.0326013529807, 1671.2417439917526, 1706.6064429052694, 1812.6881979187237, 2135.802728108374, 2639.6535372841013]),
-'nircam_NRCA4_MASKSWB_F212N': ([370.01544274515834, 360.1021382108204, 350.18781593031645, 330.35613487543446, 295.6410389396152, 191.42371412609396, -126.81008794555669, -625.5935871602642], [1630.7995724751781, 1640.9047330908998, 1651.009780713479, 1671.2195131532803, 1706.585255567853, 1812.670230296765, 2135.7954721976544, 2639.666251401196]),
-'nircam_NRCA4_MASKSWB_F200W': ([394.5597464691514, 384.64823669080295, 374.735702681358, 354.9075786364033, 320.1986443861614, 215.99931468093166, -102.18442890626272, -600.906040863307], [1630.7163584594232, 1640.8225483563556, 1650.9286293342102, 1671.140440796666, 1706.509861459068, 1812.606185025134, 2135.7691795320898, 2639.7103278738464]),
-'nircam_NRCA4_MASKSWB_NARROW': ([111.38413698015358, 101.45262068698742, 91.52015622937279, 71.65240048651128, 36.874851429290175, -67.52456184270329, -386.2616287911851, -885.6540117667219], [1631.6359443552137, 1641.7299419645478, 1651.8237819238739, 1672.010964096287, 1707.3368054726125, 1813.298632286083, 2136.0138203123024, 2639.1189427071545]),
-'nircam_NRCA4_FULL_MASKSWB': ([523.3839339648887, 513.4701893692259, 503.55542867207737, 483.7228757412762, 449.0062700449299, 344.78454061345747, 26.538538095324952, -472.25981411217003], [2817.821965597843, 2827.926919824528, 2838.0317596922814, 2858.2410724970014, 2893.606067163656, 2999.6886935426246, 3322.805722981411, 3826.659907438592]),
-'nircam_NRCA4_FULL_MASKSWB_F182M': ([466.04432419658144, 456.12646758182177, 446.2076099431787, 426.3669085454253, 391.6361897307272, 287.3732607457828, -30.987163550345713, -529.9262286035364], [2817.0100203930856, 2827.1125168206004, 2837.2148896748413, 2857.419240610433, 2892.775461625096, 2998.831056388383, 3321.858535233938, 3825.54698986551]),
-'nircam_NRCA4_FULL_MASKSWB_F187N': ([474.99716245197135, 465.0799484079548, 455.1617309548851, 435.3223027424657, 400.5937887873588, 296.3372939290982, -22.005287147746458, -520.9225181353536], [2816.9803621878955, 2827.083239465297, 2837.1859946846557, 2857.3911149295973, 2892.748697098863, 2998.808492186693, 3321.8499503249036, 3825.5644844842527]),
-'nircam_NRCA4_FULL_MASKSWB_F210M': ([522.0745829936138, 512.160773005884, 502.2459471090492, 482.4132643546069, 447.6964333175007, 343.474042040133, 25.22615555128334, -473.57471773447674], [2816.8229782620037, 2826.9278468827665, 2837.0326013529807, 2857.2417439917526, 2892.6064429052694, 2998.6881979187237, 3321.802728108374, 3825.6535372841013]),
-'nircam_NRCA4_FULL_MASKSWB_F212N': ([529.0154427451583, 519.1021382108204, 509.18781593031645, 489.35613487543446, 454.6410389396152, 350.42371412609396, 32.18991205444331, -466.5935871602642], [2816.799572475178, 2826.9047330908998, 2837.009780713479, 2857.2195131532803, 2892.585255567853, 2998.670230296765, 3321.7954721976544, 3825.666251401196]),
-'nircam_NRCA4_FULL_MASKSWB_F200W': ([542.293521573094, 532.3811865472749, 522.4678302649484, 502.6380706329328, 467.92630303810586, 363.7186979985105, 45.51192782048088, -453.2381781676627], [2816.754629817443, 2826.8603478901073, 2836.9659551769573, 2857.1768136167616, 2892.544548181224, 2998.6356695467102, 3321.78135938727, 3825.690255288797]),
-'nircam_NRCA5_FULL': ([1023.4999999999161, 1018.6634417331632, 1013.8263230330962, 1004.1504123432998, 987.2122420045221, 936.3578450335696, 781.0253855124345, 537.4066415581242], [1023.499999999897, 1028.402184573697, 1033.304636356964, 1043.1103329363598, 1060.2728012218322, 1111.7784427554927, 1268.8938350062474, 1514.6812247905796]),
-'nircam_NRCA5_SUB160': ([79.4999999999161, 74.66344173316315, 69.82632303309617, 60.15041234329976, 43.21224200452207, -7.642154966430439, -162.97461448756553, -406.5933584418758], [79.499999999897, 84.40218457369701, 89.30463635696401, 99.11033293635978, 116.2728012218322, 167.77844275549273, 324.8938350062474, 570.6812247905796]),
-'nircam_NRCA5_SUB320': ([159.4999999999161, 154.66344173316315, 149.82632303309617, 140.15041234329976, 123.21224200452207, 72.35784503356956, -82.97461448756553, -326.5933584418758], [159.499999999897, 164.402184573697, 169.304636356964, 179.11033293635978, 196.2728012218322, 247.77844275549273, 404.8938350062474, 650.6812247905796]),
-'nircam_NRCA5_SUB640': ([319.4999999999161, 314.66344173316315, 309.8263230330962, 300.15041234329976, 283.21224200452207, 232.35784503356956, 77.02538551243447, -166.5933584418758], [319.499999999897, 324.402184573697, 329.304636356964, 339.1103329363598, 356.2728012218322, 407.77844275549273, 564.8938350062474, 810.6812247905796]),
-'nircam_NRCA5_GRISM256_F322W2': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM128_F322W2': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM64_F322W2': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM256_F277W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM128_F277W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM64_F277W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM256_F356W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM128_F356W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM64_F356W': ([1579.9842856588516, 1575.2529881667379, 1570.5208172401606, 1561.0538653482295, 1544.4783788176424, 1494.689363577391, 1342.3978285613234, 1102.9157438676239], [34.01474027230006, 38.81582781050099, 43.617592301416494, 53.22314041205641, 70.0392669150774, 120.53552724624888, 274.84319288493646, 517.0366819055427]),
-'nircam_NRCA5_GRISM256_F444W': ([951.0015137353776, 946.206500932404, 941.4108121673298, 931.817415217698, 915.0225355876272, 864.5895789014268, 710.463679338653, 468.4885539504486], [34.00372057311972, 38.79928797808441, 43.595409789362066, 53.18930663255651, 69.98387833581717, 120.40673754596003, 274.4136490874413, 515.9218624295254]),
-'nircam_NRCA5_GRISM128_F444W': ([951.0015137353776, 946.206500932404, 941.4108121673298, 931.817415217698, 915.0225355876272, 864.5895789014268, 710.463679338653, 468.4885539504486], [34.00372057311972, 38.79928797808441, 43.595409789362066, 53.18930663255651, 69.98387833581717, 120.40673754596003, 274.4136490874413, 515.9218624295254]),
-'nircam_NRCA5_GRISM64_F444W': ([951.0015137353776, 946.206500932404, 941.4108121673298, 931.817415217698, 915.0225355876272, 864.5895789014268, 710.463679338653, 468.4885539504486], [34.00372057311972, 38.79928797808441, 43.595409789362066, 53.18930663255651, 69.98387833581717, 120.40673754596003, 274.4136490874413, 515.9218624295254]),
-'nircam_NRCA5_GRISM_F322W2': ([1579.9861485000279, 1575.2391070213175, 1570.4912366578787, 1560.9930188174474, 1544.3632396280436, 1494.4145073411833, 1341.6638575994934, 1101.540323777638], [279.01126042148235, 283.8456151181497, 288.68055579789893, 298.35218456730547, 315.28308657711216, 366.1171742985156, 521.3969598129861, 764.9490290948479]),
-'nircam_NRCA5_GRISM_F277W': ([1579.9861485000279, 1575.2391070213175, 1570.4912366578787, 1560.9930188174474, 1544.3632396280436, 1494.4145073411833, 1341.6638575994934, 1101.540323777638], [279.01126042148235, 283.8456151181497, 288.68055579789893, 298.35218456730547, 315.28308657711216, 366.1171742985156, 521.3969598129861, 764.9490290948479]),
-'nircam_NRCA5_GRISM_F356W': ([1579.9861485000279, 1575.2391070213175, 1570.4912366578787, 1560.9930188174474, 1544.3632396280436, 1494.4145073411833, 1341.6638575994934, 1101.540323777638], [279.01126042148235, 283.8456151181497, 288.68055579789893, 298.35218456730547, 315.28308657711216, 366.1171742985156, 521.3969598129861, 764.9490290948479]),
-'nircam_NRCA5_GRISM_F444W': ([951.0016883130542, 946.1936345359767, 941.3849400852921, 931.765637305811, 914.9257594555919, 864.3603532546782, 709.8537820211749, 467.35199368590486], [278.997589500715, 283.82351801477125, 288.6499198095444, 298.3041340313206, 315.2034868665663, 365.9348487165379, 520.829556985495, 763.5735168944049]),
-'nircam_NRCA5_TAGRISMTS32': ([14.993578700049738, 10.219691664707625, 5.445058367348565, -4.10643817515097, -20.828665678571724, -71.04877824054643, -224.57272759085959, -465.74776276799764], [15.006311598870298, 19.815318216115884, 24.62490244761068, 34.24579345116638, 51.087825787715246, 101.65472604295246, 256.1153707899059, 498.3749454020233]),
-'nircam_NRCA5_TAGRISMTS_SCI_F322W2': ([14.984288619293466, 10.251490851736662, 5.517823955591439, -3.9521070312157462, -20.532766145832966, -70.33699416603758, -222.6722348708986, -462.2153848536941], [15.51457008880027, 20.318865446063455, 25.12382892835194, 34.73574866162471, 51.56294156180422, 102.09177155907696, 256.49315278747827, 498.8177409545185]),
-'nircam_NRCA5_TAGRISMTS_SCI_F444W': ([15.001589413173292, 10.205336390938783, 5.40841074808111, -4.187449969033992, -20.986609329596035, -71.43216510933439, -225.59430897565494, -467.6197822704355], [15.503193911379412, 20.30168996321629, 25.100732609669535, 34.70044777326268, 51.5051270584695, 101.95774812008892, 256.050356456318, 497.678179884172]),
-'nircam_NRCA5_SUB64P': ([31.497726593372818, 26.713610986142612, 21.92878318241037, 12.356999639545165, -4.400403746191159, -54.72356742731358, -208.5389654433135, -450.1016048944191], [39.005148775825205, 43.80311341625895, 48.60165288343603, 58.20044605769772, 75.00378087769332, 125.45439304088109, 279.5589338277665, 521.2571632433176]),
-'nircam_NRCA5_SUB160P': ([79.48210808961926, 74.79724228544183, 70.11136494100356, 60.73658781926383, 44.32109393803876, -4.997790788020666, -155.9432570771753, -393.5618256304997], [79.52000074932471, 84.3268626914172, 89.13447568638526, 98.75194181323002, 115.58962725404331, 166.15580639192638, 320.72206249438534, 563.4416523191047]),
-'nircam_NRCA5_SUB400P': ([199.48113348694392, 194.77152122236316, 190.06097098462487, 180.63706760731748, 164.13630107866106, 114.56682063013432, -37.0967528241772, -275.7134259803281], [199.5183701685478, 204.34300618262432, 209.16831500936814, 218.8209392769529, 235.7194084141537, 286.4623773274849, 441.51874106604805, 684.8713636219036]),
-'nircam_NRCA5_GRISMC_WFSS': ([1023.4999999999161, 1018.6634417331632, 1013.8263230330962, 1004.1504123432998, 987.2122420045221, 936.3578450335696, 781.0253855124345, 537.4066415581242], [1023.499999999897, 1028.402184573697, 1033.304636356964, 1043.1103329363598, 1060.2728012218322, 1111.7784427554927, 1268.8938350062474, 1514.6812247905796]),
-'nircam_NRCA5_GRISMR_WFSS': ([1023.4999999999161, 1018.6634417331632, 1013.8263230330962, 1004.1504123432998, 987.2122420045221, 936.3578450335696, 781.0253855124345, 537.4066415581242], [1023.499999999897, 1028.402184573697, 1033.304636356964, 1043.1103329363598, 1060.2728012218322, 1111.7784427554927, 1268.8938350062474, 1514.6812247905796]),
-'nircam_NRCA5_MASK335R': ([193.36201407986073, 188.46956468033545, 183.57692001488567, 173.79105802104186, 156.6640312386296, 105.2707674503099, -51.43212813316529, -296.26112075331275], [922.6927481390226, 927.6418166771791, 932.5905507275129, 942.486999277538, 959.8024286819518, 1011.7214767040136, 1169.6537996880988, 1415.2252371777422]),
-'nircam_NRCA5_MASK430R': ([195.40537234444798, 190.52637246754455, 185.64705292162864, 175.88746630208175, 158.8052099876627, 107.53683744813986, -48.87744846240503, -293.56668104033724], [921.8622978158928, 926.8304852730125, 931.7984166355191, 941.7334963309377, 959.1172961463485, 1011.2474401955797, 1169.8823316379712, 1416.7563874194843]),
-'nircam_NRCA5_MASKLWB': ([198.7303920622021, 193.89456044489316, 189.05818788270608, 179.38382955304974, 162.44857715843227, 111.6046366546891, -43.67545285848746, -287.1174815006166], [909.2985738898296, 914.2969129692683, 919.2951348748238, 929.2912144659531, 946.7831186082826, 999.2481293925221, 1159.0072996119488, 1407.9937662347374]),
-'nircam_NRCA5_TAMASK335R': ([63.879441949551165, 58.98314653907585, 54.08669338584036, 44.29332741065559, 27.153533427116372, -24.275203074769024, -181.05878578857426, -425.92248629548385], [794.714154190704, 799.6532442849812, 804.5920181149727, 814.4686010978867, 831.749442872001, 883.5661004900003, 1041.1996119992773, 1286.3473873180073]),
-'nircam_NRCA5_TAMASK430R': ([66.00409961229445, 61.11931251844749, 56.23423833327752, 46.46324040431432, 29.361329878637434, -21.963570489303038, -178.52685334414923, -423.3730716867708], [794.0295745055741, 798.9881896269771, 803.9465716826626, 813.8626221429013, 831.2133449105645, 883.245998070618, 1041.6006545461396, 1288.0926138001455]),
-'nircam_NRCA5_TAMASKLWB': ([71.3470706916778, 66.5253402523756, 61.70301138540026, 52.056567649125554, 35.169609522771225, -15.533734355700744, -170.42623223121927, -413.39611066938187], [780.4331650484128, 785.4339358121115, 790.4346595817788, 800.4359542993525, 817.937667692493, 870.4374084454548, 1030.3540395466812, 1279.7602906322177]),
-'nircam_NRCA5_TAMASKLWBL': ([69.66857918961523, 64.8230647340331, 59.977043232946016, 50.28348867202135, 33.314968752042205, -17.626288987922408, -173.1799598665898, -416.9788808600607], [781.829029608095, 786.8188177088332, 791.8085085292728, 801.7875859261203, 819.2499301936232, 871.6277715421775, 1031.13602723626, 1279.7795945753287]),
-'nircam_NRCA5_FSTAMASKLWB': ([70.5201207454179, 65.68598946156317, 60.85130555905971, 51.18028927865794, 34.25077099835107, -16.576866845795394, -171.81633701501755, -415.2274747489637], [781.6626805149881, 786.6581492276086, 791.653546327304, 801.6441135935011, 819.1268148022191, 871.5676656702544, 1031.286847825239, 1280.3240796514788]),
-'nircam_NRCA5_FSTAMASK335R': ([64.34985440269406, 59.45559378497137, 54.56114507043162, 44.77169645512163, 27.638461838469084, -23.77290312720538, -180.526190643644, -425.4197300437313], [794.5896057663167, 799.5332825093819, 804.476662556538, 814.3625170215869, 831.6597751304816, 883.527176669842, 1041.330140201736, 1286.7938805451613]),
-'nircam_NRCA5_FSTAMASK430R': ([66.47684591506527, 61.59540455576348, 56.71364958900995, 46.94921020914683, 29.858519043374372, -21.434729011726404, -177.92111095569476, -422.71322792119827], [793.83443439435, 798.7970174168122, 803.7593842743927, 813.6834553218114, 831.0483791686602, 883.1249245210465, 1041.6260869909302, 1288.3909663051672]),
-'nircam_NRCA5_MASKLWB_F250M': ([304.712925632899, 299.8861584078127, 295.05881540681867, 285.4024116039468, 268.4982434902904, 217.74497673416363, 62.71692317908196, -180.40867234082066], [908.7426001179911, 913.7450965977678, 918.7474946621569, 928.7519830629458, 946.258785021826, 998.7699048698337, 1158.6833789232232, 1407.9575978751536]),
-'nircam_NRCA5_MASKLWB_F300M': ([279.87787696358964, 275.0489332151692, 270.21942187418927, 260.558705961108, 243.64707058896397, 192.87200720971805, 37.78321543419224, -205.41924578326916], [908.8762699481881, 913.8778112283021, 918.8792497512459, 928.8818059957339, 946.385184479012, 998.8857065505376, 1158.7637003438067, 1407.9717310091673]),
-'nircam_NRCA5_MASKLWB_F277W': ([279.7773245139033, 274.9483720188771, 270.11885196429694, 260.4581187236763, 243.54645334731117, 192.77130240441784, 37.68226680645648, -205.5205022493683], [908.8768067351862, 913.8783441245068, 918.8797787387361, 928.8823271129413, 946.3856916519635, 998.886170559419, 1158.7640198639383, 1407.9717810178909]),
-'nircam_NRCA5_MASKLWB_F335M': ([271.8339361582971, 267.00429437092225, 262.174087638301, 252.51198889026546, 235.59795909545414, 184.81590830449568, 29.70766467082285, -213.51933678195905], [908.9191010423774, 913.9203304590856, 918.9214557055684, 928.9233811417544, 946.4256419726339, 998.9227045020907, 1158.7891181799514, 1407.9755495114796]),
-'nircam_NRCA5_MASKLWB_F360M': ([248.20432949090127, 243.3726566695036, 238.54042667069325, 228.87430471525977, 211.95330926369866, 161.1509365217994, 5.986175323032512, -237.31190657751654], [909.0437143124896, 914.0440205620034, 919.0442184700787, 929.0442766681163, 946.5432292771875, 999.0300524243339, 1158.8621974496727, 1407.984719357457]),
-'nircam_NRCA5_MASKLWB_F356W': ([239.255022161773, 234.42258769305067, 229.58959898592957, 219.9219684401046, 202.99836132190717, 152.18837126118842, -2.9975524731696623, -246.32216199238633], [909.0904235415228, 914.0903774014578, 919.090221332247, 929.0895667944883, 946.5872566779062, 999.0701718156711, 1158.8892398327134, 1407.987377022289]),
-'nircam_NRCA5_MASKLWB_F410M': ([224.47335071253724, 219.63966729861886, 214.80543449795005, 205.13533033507952, 188.2074412192212, 137.38496463346019, -17.83562222894261, -261.2035747485929], [909.1669814038728, 914.1663498883313, 919.1656058117073, 929.163767332464, 946.6593597216961, 999.1357836685529, 1158.9331332838815, 1407.9907758972]),
-'nircam_NRCA5_MASKLWB_F430M': ([214.81983996761278, 209.9853469890436, 205.150307790454, 195.47860034247833, 178.54793605066607, 127.71736866154333, -27.52566011858835, -270.92160057684305], [909.2165866090118, 914.2155705547175, 919.2144402140111, 929.2118240097407, 946.7060385980412, 999.1781988402536, 1158.9612844516428, 1407.9923338545232]),
-'nircam_NRCA5_MASKLWB_F460M': ([197.22198329940534, 192.38602686432841, 187.54952997889995, 177.87492448762077, 160.93924433559778, 110.09405723444729, -45.18948480956806, -288.6357984340964], [909.306221286176, 914.3044996542203, 919.3026605770056, 929.2986173848208, 946.7903040154306, 999.2546417540057, 1159.011560763266, 1407.993830954325]),
-'nircam_NRCA5_MASKLWB_F480M': ([189.1771146936578, 184.34049453317698, 179.50333655890245, 169.827416810228, 152.8894621724612, 102.03764722226651, -53.26424478707213, -296.7333078264828], [909.3468536033079, 914.3448074382968, 919.3426423778128, 929.3379428512812, 946.8284667900721, 999.2892068863407, 1159.0340929609592, 1407.993933557927]),
-'nircam_NRCA5_MASKLWB_F444W': ([189.3782286329199, 184.54162502456848, 179.70448353679194, 170.0285965626765, 153.09069864402363, 102.23904896091244, -53.0623856175298, -296.53088207232213], [909.3458351297395, 914.3437970927134, 919.3416401966006, 929.3369571083326, 946.8275101669451, 999.2883403655246, 1159.0335277956824, 1407.9939301157592]),
-'nircam_NRCA5_MASKLWB_NARROW': ([326.4302428374958, 321.60540550168844, 316.77998521865834, 307.12740532452835, 290.2298599024423, 239.4959313385807, 84.5218377947474, -158.53518027242558], [908.6240188994125, 913.6273412331211, 918.6305689223054, 928.6367279270885, 946.1464900885658, 998.6667747066149, 1158.6109395994054, 1407.9424254073424]),
-'nircam_NRCA5_FULL_MASK335R': ([678.3620140798607, 673.4695646803355, 668.5769200148857, 658.7910580210419, 641.6640312386296, 590.2707674503099, 433.5678718668347, 188.73887924668725], [2429.6927481390226, 2434.641816677179, 2439.590550727513, 2449.486999277538, 2466.802428681952, 2518.7214767040136, 2676.653799688099, 2922.225237177742]),
-'nircam_NRCA5_FULL_MASK430R': ([1005.405372344448, 1000.5263724675445, 995.6470529216286, 985.8874663020817, 968.8052099876627, 917.5368374481399, 761.122551537595, 516.4333189596628], [2434.862297815893, 2439.8304852730125, 2444.798416635519, 2454.7334963309377, 2472.1172961463485, 2524.2474401955797, 2682.882331637971, 2929.7563874194843]),
-'nircam_NRCA5_FULL_MASKLWB': ([1649.730392062202, 1644.8945604448932, 1640.058187882706, 1630.3838295530497, 1613.4485771584323, 1562.604636654689, 1407.3245471415125, 1163.8825184993834], [2416.2985738898296, 2421.2969129692683, 2426.295134874824, 2436.291214465953, 2453.7831186082826, 2506.248129392522, 2666.007299611949, 2914.9937662347374]),
-'nircam_NRCA5_FULL_MASKLWB_F250M': ([1755.6123706570975, 1750.7855945536394, 1745.9582427075352, 1736.3018213140303, 1719.3976227365727, 1668.6442670411666, 1513.6159654702833, 1270.4900553672699], [2415.743159464365, 2420.7456521002246, 2425.748046302898, 2435.7525269280413, 2453.2593151087513, 2505.770392301906, 2665.683723526274, 2914.95767598329]),
-'nircam_NRCA5_FULL_MASKLWB_F300M': ([1730.8778769635896, 1726.0489332151692, 1721.2194218741893, 1711.558705961108, 1694.647070588964, 1643.872007209718, 1488.7832154341922, 1245.5807542167308], [2415.876269948188, 2420.877811228302, 2425.879249751246, 2435.881805995734, 2453.385184479012, 2505.8857065505376, 2665.7637003438067, 2914.9717310091673]),
-'nircam_NRCA5_FULL_MASKLWB_F277W': ([1730.7773245139033, 1725.948372018877, 1721.118851964297, 1711.4581187236763, 1694.5464533473112, 1643.7713024044178, 1488.6822668064565, 1245.4794977506317], [2415.876806735186, 2420.878344124507, 2425.879778738736, 2435.8823271129413, 2453.3856916519635, 2505.886170559419, 2665.7640198639383, 2914.971781017891]),
-'nircam_NRCA5_FULL_MASKLWB_F335M': ([1722.833936158297, 1718.0042943709223, 1713.174087638301, 1703.5119888902655, 1686.5979590954541, 1635.8159083044957, 1480.7076646708229, 1237.480663218041], [2415.9191010423774, 2420.9203304590856, 2425.9214557055684, 2435.9233811417544, 2453.425641972634, 2505.9227045020907, 2665.7891181799514, 2914.9755495114796]),
-'nircam_NRCA5_FULL_MASKLWB_F360M': ([1699.2043294909013, 1694.3726566695036, 1689.5404266706933, 1679.8743047152598, 1662.9533092636987, 1612.1509365217994, 1456.9861753230325, 1213.6880934224835], [2416.0437143124896, 2421.0440205620034, 2426.0442184700787, 2436.0442766681163, 2453.5432292771875, 2506.030052424334, 2665.8621974496727, 2914.984719357457]),
-'nircam_NRCA5_FULL_MASKLWB_F356W': ([1690.255022161773, 1685.4225876930507, 1680.5895989859296, 1670.9219684401046, 1653.9983613219072, 1603.1883712611884, 1448.0024475268303, 1204.6778380076137], [2416.090423541523, 2421.0903774014578, 2426.090221332247, 2436.0895667944883, 2453.587256677906, 2506.070171815671, 2665.8892398327134, 2914.987377022289]),
-'nircam_NRCA5_FULL_MASKLWB_F410M': ([1675.4733507125372, 1670.6396672986189, 1665.80543449795, 1656.1353303350795, 1639.2074412192212, 1588.3849646334602, 1433.1643777710574, 1189.796425251407], [2416.166981403873, 2421.1663498883313, 2426.1656058117073, 2436.163767332464, 2453.659359721696, 2506.135783668553, 2665.9331332838815, 2914.9907758972]),
-'nircam_NRCA5_FULL_MASKLWB_F430M': ([1665.8198399676128, 1660.9853469890436, 1656.150307790454, 1646.4786003424783, 1629.547936050666, 1578.7173686615433, 1423.4743398814117, 1180.078399423157], [2416.2165866090118, 2421.2155705547175, 2426.214440214011, 2436.2118240097407, 2453.7060385980412, 2506.1781988402536, 2665.9612844516428, 2914.992333854523]),
-'nircam_NRCA5_FULL_MASKLWB_F460M': ([1648.2219832994053, 1643.3860268643284, 1638.5495299789, 1628.8749244876208, 1611.9392443355978, 1561.0940572344473, 1405.810515190432, 1162.3642015659036], [2416.306221286176, 2421.3044996542203, 2426.3026605770056, 2436.298617384821, 2453.7903040154306, 2506.2546417540057, 2666.011560763266, 2914.993830954325]),
-'nircam_NRCA5_FULL_MASKLWB_F480M': ([1640.1771146936578, 1635.340494533177, 1630.5033365589024, 1620.827416810228, 1603.8894621724612, 1553.0376472222665, 1397.7357552129279, 1154.2666921735172], [2416.346853603308, 2421.344807438297, 2426.342642377813, 2436.3379428512812, 2453.828466790072, 2506.2892068863407, 2666.0340929609592, 2914.993933557927]),
-'nircam_NRCA5_FULL_MASKLWB_F444W': ([1640.37822863292, 1635.5416250245685, 1630.704483536792, 1621.0285965626765, 1604.0906986440236, 1553.2390489609124, 1397.9376143824702, 1154.4691179276779], [2416.3458351297395, 2421.3437970927134, 2426.3416401966006, 2436.3369571083326, 2453.827510166945, 2506.2883403655246, 2666.0335277956824, 2914.993930115759]),
-'nircam_NRCB1_FULL': ([1023.4999999999695, 1013.6948850433738, 1003.8885247270867, 984.2720805122318, 949.9314217803774, 846.8199409470665, 531.7802843441067, 37.34285966406321], [1023.499999999792, 1033.6276952353464, 1043.7551424249125, 1064.0092784575052, 1099.451509148447, 1205.7576444618703, 1529.5094156205514, 2034.4277410420382]),
-'nircam_NRCB1_FULLP': ([1429.9519704083186, 1420.1428402338292, 1410.3324005366824, 1390.707605771994, 1356.3517218502834, 1253.1899586418467, 937.9559365775901, 443.09723873845155], [1372.0139278999948, 1382.1817985561445, 1392.3493778968682, 1412.6836475847108, 1448.265688610221, 1554.987936237401, 1879.9748063147347, 2386.7077624408194]),
-'nircam_NRCB1_SUB160': ([79.45326208972347, 69.67493772395369, 59.89548648271534, 40.333215020009675, 6.088491982612368, -96.72660267225797, -410.78524590946927, -903.4606741512657], [79.46871417018895, 89.49034522439115, 99.51183764043469, 119.55439372640444, 154.6274243030158, 259.8342339617394, 580.316495562017, 1080.4010546935895]),
-'nircam_NRCB1_SUB320': ([159.45588722633033, 149.6749195835215, 139.89281553455862, 120.32520988831448, 86.07106048843832, -16.773010581644485, -330.9264018357512, -823.7696102769139], [159.47058712322587, 169.5015925374065, 179.53245095088675, 199.5937138777416, 234.69940037512413, 340.00355178658504, 660.776456708609, 1161.295184540314]),
-'nircam_NRCB1_SUB640': ([319.462571689642, 309.6765189893757, 299.8893106911594, 280.31143904598855, 246.0391400360869, 143.13922025567308, -171.19723251816276, -664.3654525769036], [319.4753202450481, 329.52487119686646, 339.57425808355094, 359.6725266050091, 394.84280728878457, 500.3394596589618, 821.6866504909555, 1323.0612660512238]),
-'nircam_NRCB1_FP4MIMF': ([1817.0072950727222, 1807.1878791029708, 1797.3670954493487, 1777.7214392448545, 1743.3284960331034, 1640.0514334070622, 1324.4302427134605, 828.8718302593838], [1819.0002685699587, 1829.2080074439523, 1839.415373523953, 1859.8289708947723, 1895.5490395977386, 2002.6791550158096, 2328.847596625401, 2837.214261436579]),
-'nircam_NRCB1_SUB64P': ([29.4988225048603, 19.678334551866328, 9.856442039449348, -9.791541976554527, -44.188909330523074, -147.48187028873008, -463.1745571312415, -958.9076808522093], [17.99383091553068, 28.219402355422517, 38.444567528908465, 58.893662031301346, 94.67552314631348, 201.9884504210895, 528.6885233984617, 1037.797292431364]),
-'nircam_NRCB1_SUB160P': ([79.5009370140715, 69.68002051968824, 59.85770908455993, 40.20891595680882, 5.810224211904824, -97.48602227399306, -413.18263650177505, -908.9048667631184], [79.49547590393786, 89.71713908864831, 99.93840153640167, 120.3797072974337, 156.14799236671797, 263.4206179244693, 590.0021399640141, 1098.940613172943]),
-'nircam_NRCB1_SUB400P': ([199.50623126060214, 189.68660072806597, 179.86559695866504, 160.2194839423114, 125.82568852434952, 22.54567368535845, -293.08798878806215, -788.6754101584962], [199.49937608033133, 209.70992690557796, 219.92009989146004, 240.3392958400609, 276.0691126758479, 383.2280857833898, 709.4806290089446, 1217.9653433496887]),
-'nircam_NRCB1_MASK210R': ([267.4913112752124, 257.5684600544075, 247.64450365831203, 227.79329143487348, 193.04316873465382, 88.71421593362743, -229.92316016548625, -729.5535982465427], [1629.4449557780254, 1639.6241281495068, 1649.8024955293881, 1670.1567924207757, 1705.7688701196794, 1812.5421495269156, 2137.2990931344557, 2642.338056421541]),
-'nircam_NRCB1_TAMASK210R': ([13.864384630637915, 3.970125727441882, -5.925335023403932, -25.719846905777104, -60.37168250309833, -164.41304312115972, -482.2445106452899, -980.855623744898], [1372.925347180727, 1383.1229371766303, 1393.3198550611032, 1413.711653883594, 1449.3906583408366, 1556.3748679690484, 1881.8753931262358, 2388.428560278039]),
-'nircam_NRCB2_FULL': ([1023.5000000000703, 1013.9079041179562, 1004.3143570627115, 985.1229240773988, 951.524071470462, 850.6231841973535, 542.1857747587015, 57.6461552126068], [1023.4999999996576, 1033.538429727385, 1043.5771197022311, 1063.6552640146124, 1098.79438422909, 1204.22826342966, 1525.663837394558, 2028.0271050930853]),
-'nircam_NRCB2_SUB160': ([79.52011851472446, 69.80409300503845, 60.08691794438539, 40.64913062424682, 6.622034884416507, -95.54188148477306, -407.63265149315293, -897.2923539805242], [79.50257639633264, 89.54708862479629, 99.59152767123578, 119.68017349248521, 154.83449213938684, 260.29000303472776, 581.5758552079806, 1083.0639732446107]),
-'nircam_NRCB2_SUB320': ([159.52065408344959, 149.81402590862047, 140.10622484218334, 120.68711548961232, 86.69248148225722, -15.375769321429516, -327.19118536617293, -816.473550464392], [159.50015181698973, 169.54530393023538, 179.59040852933185, 199.68046242332957, 234.83749199633667, 340.30302033236376, 661.6370326336732, 1163.257083490179]),
-'nircam_NRCB2_SUB640': ([319.5203260378456, 309.8330746010872, 300.1446032623435, 280.76401248357854, 246.8363346460053, 144.96551309940844, -166.28022139781797, -654.7747403651372], [319.4962019480199, 329.5420255130216, 339.5878534356152, 359.6795093641483, 394.83983997729274, 500.3190556651507, 821.729789489671, 1323.5799449807773]),
-'nircam_NRCB2_FP3MIMF': ([1818.9846722006555, 1809.524973143914, 1800.0634456732782, 1781.1349283207187, 1747.9926154639659, 1648.4349073046326, 1343.864808508496, 864.7743476197944], [228.0379724918248, 238.0422480511844, 248.04719477835283, 268.0590767720313, 303.0861213429872, 408.2126247428255, 728.9589156262715, 1230.896995649998]),
-'nircam_NRCB3_FULL': ([1023.500000000141, 1013.6005948622081, 1003.7004710909277, 983.8980855516143, 949.2371457421468, 845.2044803715917, 527.7430824674034, 30.835706174167626], [1023.4999999998247, 1033.4444492531209, 1043.3883640586964, 1063.2745718859462, 1098.0701352940937, 1202.4144852899165, 1519.9716911934356, 2014.4481486470022]),
-'nircam_NRCB3_SUB160': ([79.53071096510439, 69.71738822816064, 59.90300532421679, 40.271070990710996, 5.9050829096916, -97.26884074629925, -412.373577901923, -906.5256268604702], [79.48294600897805, 89.4605926888238, 99.43806334494491, 119.39246363772281, 154.31086065639408, 259.0509961303143, 578.0845834057224, 1075.817542315366]),
-'nircam_NRCB3_SUB320': ([159.5283447317131, 149.70653701675155, 139.8836935940917, 120.23491183728538, 85.83967823115017, -17.420141865645064, -332.76873053463555, -827.2399437908836], [159.48583354201378, 169.46188869788853, 179.43774157277312, 199.38882733363926, 234.30116947273427, 339.02117418910905, 657.9744147914666, 1155.51734292054]),
-'nircam_NRCB3_SUB640': ([319.52287722850406, 309.68470739048826, 299.845552375906, 280.1642996474866, 245.71273353829838, 142.2877387993808, -173.52667676315787, -668.5945502069346], [319.49128545589826, 329.46353018305354, 339.4355187116407, 359.3787134815615, 394.2767227248744, 498.9496691790333, 817.7199361472972, 1314.8409152737163]),
-'nircam_NRCB3_FP5MIMF': ([228.01116337310032, 218.0703964426432, 208.12936305439916, 188.246525125375, 153.4492333238088, 49.042462836049936, -269.20593987324696, -766.0749269573212], [1818.9721823057976, 1828.8569145521692, 1838.7406524720323, 1858.5051168958598, 1893.083118218819, 1996.7393167824669, 2311.8422318379744, 2801.208660519568]),
-'nircam_NRCB3_MASKSWB': ([255.3713236314859, 245.37963359761102, 235.38769574570256, 215.4031064023427, 180.42794249335157, 75.48918741348268, -244.36102874486198, -743.6457986911316], [1620.4309399374752, 1630.3580058688704, 1640.283727071067, 1660.13110016462, 1694.8507624825106, 1798.9050863471257, 2114.9541483864446, 2604.8696738912863]),
-'nircam_NRCB3_TAMASKSWB': ([-1.776703145160127, -11.755036392589432, -21.733580040696552, -41.69126825282433, -76.6189910336883, -181.41259368338854, -500.792878873762, -999.2506120654577], [1362.5758594968638, 1372.4846980776438, 1382.3922592478616, 1402.2035153583106, 1436.8606303982915, 1540.7324451632599, 1856.2758730240798, 2345.5739714119672]),
-'nircam_NRCB3_TAMASKSWBS': ([1.4764258208199408, -8.507060901215482, -18.490998748209677, -38.460202465379325, -73.41043615572835, -178.29008299438465, -498.117937958285, -997.9288440095174], [1364.9639855339083, 1374.929536697393, 1384.8939660470414, 1404.8194289430603, 1439.677934261158, 1544.165958134874, 1861.7090455467187, 2354.5677512985126]),
-'nircam_NRCB4_FULL': ([1023.4999999998074, 1013.749198748202, 1003.9974323063026, 984.4910163704407, 950.3456042462423, 847.8404798345202, 534.8409924487244, 44.19131090030453], [1023.4999999998263, 1033.3460900550003, 1043.1921658129147, 1062.8842613944125, 1097.3451812765295, 1200.724775790512, 1515.7230132056343, 2007.5023162620191]),
-'nircam_NRCB4_SUB160': ([79.464686133952, 69.67420159753283, 59.882629841574726, 40.296236353097584, 6.009681818370609, -96.9279832733232, -411.332791409714, -904.4626556996992], [79.46783592597149, 89.4323267533282, 99.3967037780917, 119.32510376434038, 154.19860171368146, 258.8086696299956, 577.4900881012709, 1074.81968020891]),
-'nircam_NRCB4_SUB320': ([159.46493445943725, 149.67742577473155, 139.88883950822583, 120.30844593331085, 86.03248419687225, -16.872690023613586, -331.1717817837464, -824.1152304035625], [159.46810086328583, 169.42291726860185, 179.37762795755725, 199.28671954666788, 234.1265058024976, 338.63603695027905, 657.0167009924439, 1153.894479482653]),
-'nircam_NRCB4_SUB640': ([319.46729985203, 309.6859488661314, 299.9035398001679, 280.3355591997606, 246.0815084728829, 143.24351329784213, -170.83718213708744, -663.3956737144721], [319.470224951383, 329.40549774722876, 339.3406810191441, 359.21076636468456, 393.9824476664626, 498.28885751499683, 816.061667921892, 1312.0251326853527]),
-'nircam_NRCB4_DHSPIL': ([1034.9981191303127, 1025.2435529340971, 1015.4880237656682, 995.9740890450153, 961.8155405359003, 859.2711733032263, 546.1537260767877, 55.325734908287586], [1078.9981313689373, 1088.848529862669, 1098.6989029290128, 1118.3995597867854, 1152.87535515671, 1256.298764276925, 1571.4230395372017, 2063.3759666212472]),
-'nircam_NRCB4_DHSPIL_SUB96': ([46.998119130312716, 37.243552934097124, 27.48802376566823, 7.974089045015262, -26.184459464099746, -128.7288266967737, -441.84627392321227, -932.6742650917124], [47.998131368937266, 57.84852986266901, 67.69890292901277, 87.3995597867854, 121.87535515670993, 225.2987642769251, 540.4230395372017, 1032.3759666212472]),
-'nircam_NRCB4_DHSPIL_WEDGES': ([1026.4906505703855, 1016.6401779940123, 1006.7888832394027, 987.0838423750638, 952.5922359753673, 849.0595025927595, 533.0388486642339, 38.07405355910248], [2454.9729612183132, 2464.894397512401, 2474.815500417172, 2494.6566911055806, 2529.375439420531, 2633.504711276755, 2950.5593260547153, 3444.789331969499]),
-'nircam_NRCB4_FP1': ([1818.9656633499046, 1809.180904019394, 1799.395075237696, 1779.8202210479585, 1745.5540316986653, 1642.678776637821, 1328.4765387107132, 835.702468725207], [1816.968737234975, 1826.9151071665399, 1836.861378724439, 1856.7536140925854, 1891.5639727369078, 1995.9857631750606, 2314.104120994748, 2810.5882968922115]),
-'nircam_NRCB4_FP1_SUB8': ([2.9656633499046166, -6.819095980606107, -16.60492476230411, -36.17977895204149, -70.44596830133469, -173.3212233621789, -487.52346128928684, -980.297531274793], [3.968737234974924, 13.915107166539883, 23.861378724438964, 43.753614092585394, 78.56397273690777, 182.98576317506058, 501.104120994748, 997.5882968922115]),
-'nircam_NRCB4_FP1_SUB64': ([30.965663349904617, 21.180904019393893, 11.395075237695892, -8.179778952041488, -42.44596830133469, -145.3212233621789, -459.52346128928684, -952.297531274793], [31.968737234974924, 41.91510716653988, 51.861378724438964, 71.7536140925854, 106.56397273690777, 210.98576317506058, 529.104120994748, 1025.5882968922115]),
-'nircam_NRCB4_FP2MIMF': ([230.0182899090728, 220.31004901356357, 210.60097389983252, 191.18033526489285, 157.18630868193713, 55.145255201905115, -256.34317087440627, -744.3054808800339], [228.02645449295676, 237.7646625401145, 247.50296214874822, 266.97982162016524, 301.065085616685, 403.32527550767315, 714.9788972246961, 1201.7197825309204]),
-'nircam_NRCB5_FULL': ([1023.4999999999802, 1018.6774324794693, 1013.854332574907, 1004.2065435659715, 987.3178556331189, 936.6139569836082, 781.7589292430619, 538.9414559465642], [1023.4999999999875, 1028.41390345414, 1033.3277287486342, 1043.1551361836425, 1060.352273811675, 1111.93653070778, 1269.0565328528533, 1514.1428671872418]),
-'nircam_NRCB5_FULLP': ([1727.0239671373756, 1722.185935584941, 1717.3472530449392, 1707.6679436978154, 1690.7229597933906, 1639.841570833131, 1484.3675707528982, 1240.3537579706776], [1728.0146270938676, 1733.0003563559299, 1737.985891693363, 1747.9563708473934, 1765.4027606313919, 1817.7260853331668, 1977.0148888566828, 2225.215148074108]),
-'nircam_NRCB5_SUB160': ([79.49895642472939, 74.67516141585122, 69.8508448876778, 60.20065524810582, 43.307870986685884, -7.407513464929593, -162.28998565577933, -405.12619639417426], [79.50031301068191, 84.41141524357681, 89.32243455587809, 99.14421574109792, 116.33146158094269, 167.88569221758962, 324.9108892412746, 569.8384858788261]),
-'nircam_NRCB5_SUB320': ([159.49895642472939, 154.67516141585122, 149.8508448876778, 140.20065524810582, 123.30787098668588, 72.5924865350704, -82.28998565577933, -325.12619639417426], [159.5003130106819, 164.4114152435768, 169.3224345558781, 179.14421574109792, 196.3314615809427, 247.88569221758962, 404.9108892412746, 649.8384858788261]),
-'nircam_NRCB5_SUB640': ([319.4989564247294, 314.6751614158512, 309.8508448876778, 300.2006552481058, 283.3078709866859, 232.5924865350704, 77.71001434422067, -165.12619639417426], [319.5003130106819, 324.4114152435768, 329.3224345558781, 339.1442157410979, 356.3314615809427, 407.8856922175896, 564.9108892412746, 809.8384858788261]),
-'nircam_NRCB5_SUB64P': ([27.974320751310188, 23.133001464763765, 18.290976210312238, 8.604817167721194, -8.352677235709507, -59.27553109951964, -214.91066067469455, -459.27217048527837], [53.11518238778581, 58.125197085457785, 63.134948946593795, 73.15365353612833, 90.68376713053976, 143.25305291005725, 303.24074682289756, 552.3632650128993]),
-'nircam_NRCB5_SUB160P': ([101.49537376755939, 96.65366377953069, 91.81125345561873, 82.12434111497032, 65.16558218878208, 14.239340073623907, -141.4024889950374, -385.7641211047887], [132.19614779575886, 137.20448817241595, 142.2125687849341, 152.22794014783722, 169.7522506211817, 222.30436162918613, 382.242026959294, 631.2942425106467]),
-'nircam_NRCB5_SUB400P': ([282.91826525939814, 278.0766926908768, 273.2344322618046, 263.54785698783644, 246.58980675724683, 195.66658399578614, 40.04186593730083, -204.27107908936114], [313.35868536822045, 318.3623899285276, 323.3658480393806, 333.37201452665977, 350.8803461711807, 403.3855295551075, 563.1900239930346, 812.0672406678768]),
-'nircam_NRCB5_TAPSIMG32': ([15.518761014687698, 10.693369368162848, 5.867241323878716, -3.787214657154891, -20.68952223180804, -71.44906758364368, -226.60780346697106, -470.2944241979458], [15.504655607587665, 20.511820248528693, 25.5187996280074, 35.53219254440705, 53.053762213301525, 105.60321547025069, 265.5859974269979, 514.8828708850824]),
-'nircam_NRCB5_GRISMC_WFSS': ([1023.4999999999802, 1018.6774324794693, 1013.854332574907, 1004.2065435659715, 987.3178556331189, 936.6139569836082, 781.7589292430619, 538.9414559465642], [1023.4999999999875, 1028.41390345414, 1033.3277287486342, 1043.1551361836425, 1060.352273811675, 1111.93653070778, 1269.0565328528533, 1514.1428671872418]),
-'nircam_NRCB5_GRISMR_WFSS': ([1023.4999999999802, 1018.6774324794693, 1013.854332574907, 1004.2065435659715, 987.3178556331189, 936.6139569836082, 781.7589292430619, 538.9414559465642], [1023.4999999999875, 1028.41390345414, 1033.3277287486342, 1043.1551361836425, 1060.352273811675, 1111.93653070778, 1269.0565328528533, 1514.1428671872418]),
-'nircam_NRCB5_MASK335R': ([122.72082399540022, 117.81813608201946, 112.91504300584143, 103.10765209780061, 85.94090904257723, 34.41266629739857, -122.85519628559473, -369.08009017187305], [918.9710827542058, 923.9253523074103, 928.8790617250997, 938.7847861492119, 956.1142941213084, 1008.05933853634, 1165.9266147774506, 1411.001653344908]),
-'nircam_NRCB5_MASK430R': ([120.76705598088552, 115.85788740921816, 110.94843181805243, 101.12867156704328, 83.94143000460065, 32.36058806079859, -124.9813816266942, -371.03372416607203], [918.0890833259541, 923.0148553276335, 927.9399985180626, 937.7883832708039, 955.0168757054607, 1006.6536266707153, 1163.5292766887392, 1406.8732021063415]),
-'nircam_NRCB5_MASKLWB': ([118.88347197401094, 113.9734767794663, 109.06332331886381, 99.2425553781652, 82.05480480104768, 30.482198158359324, -126.73908880067995, -372.27793393888805], [916.8888222782871, 921.7841893762075, 926.678849457142, 936.4660319089912, 953.5866551708723, 1004.8938069583528, 1160.7053004141108, 1402.177631547047]),
-'nircam_NRCB5_TAMASK335R': ([-3.8090515900735227, -8.699441415248202, -13.59031361319012, -23.373495209864814, -40.49862207976639, -91.9078301971117, -248.86929903538612, -494.80483950634334], [791.0580948670531, 796.0283708724719, 800.9981754494274, 810.9363576027963, 828.3235313576815, 880.4483086487953, 1038.9294560942863, 1285.1895216172375]),
-'nircam_NRCB5_TAMASK430R': ([-5.870245290761204, -10.770637390299044, -15.67140138040213, -25.474034247206646, -42.632130019377655, -94.13197494991891, -251.2902891358035, -497.2717858386238], [790.3432743806243, 795.287013467916, 800.2302196879155, 810.1150198715895, 827.4081758399743, 879.2462257022748, 1036.8074274167507, 1281.4703122281999]),
-'nircam_NRCB5_TAMASKLWB': ([-7.911905623820758, -12.816902351214367, -17.722152387142273, -27.53340017975688, -44.70541862877974, -96.23807646557293, -253.40922758474244, -499.1169576710357], [789.3059381536968, 794.2210628352223, 799.1355850760174, 808.962807353611, 826.1545219213453, 877.6829287791429, 1034.2476304695056, 1277.168925024867]),
-'nircam_NRCB5_TAMASKLWBL': ([-9.889873593673883, -14.793779122937508, -19.697803906747936, -29.506197044411124, -46.67191270710691, -98.17547778826327, -255.15794789739812, -500.22929803030206], [787.9480343735431, 792.8320731387116, 797.7154281745507, 807.4800706435226, 824.5614751391468, 875.75272206912, 1031.2278320905398, 1272.2293612578233]),
-'niriss_NIS_CEN': ([1023.4999999999874, 1018.9088930953566, 1014.3177691298857, 1005.1354699099895, 989.0662812851969, 940.8574524783501, 793.9239331008537, 564.3126252415295], [1023.4999999998655, 1028.2283385271237, 1032.9567315171885, 1042.4136822999405, 1058.9638820923024, 1108.6187006171883, 1259.989449601091, 1496.641253217673]),
-'niriss_NIS_AMI1': ([45.00720718135949, 40.416066158526746, 35.82492952999496, 26.642668092404392, 10.573741506461374, -37.63292825843121, -184.5504423395364, -414.128189602216], [39.99845586323488, 44.733976859967925, 49.46941777484892, 58.94006404815241, 75.51296353267128, 125.22652354861373, 276.69825535514804, 513.3243206435903]),
-'niriss_NIS_AMI2': ([17.00711829790407, 12.41597190975267, 7.824828288564049, -1.3574519548244552, -17.426426592765665, -65.63335005793533, -212.5524889957078, -442.13436183658905], [56.998128646000396, 61.73343893597996, 66.46867379901698, 75.93892184979097, 92.51116854832549, 142.22309885284176, 293.6926879056682, 530.3226058187541]),
-'niriss_NIS_AMI3': ([17.00771149404909, 12.416513145510862, 7.825318721225813, -1.3570596952035885, -17.426195323876073, -65.63352300202143, -212.5532663627357, -442.1348054439594], [23.99858586739174, 28.734646608007893, 33.470625079485785, 42.94233992858699, 59.5170885738404, 109.2360392740876, 260.7228129149554, 497.3685862885593]),
-'niriss_NIS_AMI4': ([59.007423839113926, 54.41626726451864, 49.825116240520174, 40.642829439487286, 24.573869250690223, -23.632823000236613, -170.5497879577972, -400.1254635784859], [22.99874633782042, 27.73457920059741, 32.470327833202646, 41.94157716521056, 58.515492656779315, 108.23180701587967, 259.7093964564616, 496.33806136689213]),
-'niriss_NIS_AMITA': ([32.006064968208875, 27.41503005718505, 22.823996881497578, 13.64193446280342, -2.426668670016852, -50.63254879459657, -197.54909181647156, -427.12821566874027], [31.997607471081437, 36.731607651451895, 41.465542514086565, 50.933220736430826, 67.50106622668386, 117.20051069145609, 268.63828299312615, 505.2348272486878]),
-'niriss_NIS_WFSS_OFFSET': ([1021.5000270905317, 1016.9089161911488, 1012.317788245434, 1003.1354811072239, 987.0662787560752, 938.8574096676024, 791.9237732186542, 562.3122837410754], [1020.099946265382, 1024.8282944714213, 1029.5566969596382, 1039.0136662054224, 1055.5638966460647, 1105.2187953154457, 1256.5897031704453, 1493.241641860147]),
-'niriss_NIS_WFSS64': ([2015.4961485292135, 2010.906989282463, 2006.317813496251, 1997.1394118760707, 1981.0770463545157, 1932.8886728850098, 1786.0165248317835, 1556.4931005028407], [2015.5111131408703, 2020.2332362730644, 2024.9553991949615, 2034.399843565157, 2050.9279969003837, 2100.5152312591053, 2251.660759573061, 2487.866958307759]),
-'niriss_NIS_WFSS64R': ([31.498014871190207, 26.908672575436412, 22.319347156971162, 13.140745084091577, -2.921661709368891, -51.10793638549012, -197.9568755358721, -427.41608548742715], [795.0043057970163, 799.725302114086, 804.4463011297355, 813.8883103992773, 830.4118788698848, 879.9832793092559, 1031.0717032898424, 1267.2249804321784]),
-'niriss_NIS_WFSS64R3': ([31.495044698902348, 26.906208412085107, 22.317359158388854, 13.139621006227117, -2.921551713662211, -51.106135354815706, -197.96559923597647, -427.4707669977556], [1748.0106384563303, 1752.7325520320026, 1757.4545161244598, 1766.8985958903688, 1783.426221771741, 1833.012803976082, 1984.1672275506482, 2220.4339360963922]),
-'niriss_NIS_WFSS64C': ([794.9945975915822, 790.4024998518081, 785.810403209003, 776.6262146199454, 760.5539071004162, 712.3373015931452, 565.3986400028587, 335.8591332219878], [31.498930370720245, 36.23291924814794, 40.966947656249886, 50.43512101510714, 67.0047874229358, 116.71634606242515, 268.2356327078951, 504.9912757202055]),
-'niriss_NIS_WFSS64C3': ([1747.9941613502156, 1743.4042786083346, 1738.8143772105304, 1729.6345184205504, 1713.5695858709137, 1665.3734210741038, 1518.4777418626356, 1288.924552167759], [31.508825676076867, 36.23354495786202, 40.9583074738091, 50.407961100454486, 66.94526155307722, 116.56014737107398, 267.7911990341054, 504.1306102951021]),
-'niriss_NIS_WFSS128': ([1967.995396248094, 1963.406185892808, 1958.8169587805223, 1949.638453871584, 1933.5759056323668, 1885.3869705427935, 1738.5130266393453, 1508.9867868998224], [1968.010853369844, 1972.7334498473692, 1977.4560896055232, 1986.901498229857, 2003.4313735210171, 2053.0240478677747, 2204.188972673742, 2440.435678237672]),
-'niriss_NIS_WFSS128R': ([63.49803222240689, 58.908714708249136, 54.31941231498104, 45.14085107215624, 29.078499232703507, -19.10773185056314, -165.95753458488798, -395.42033703467473], [795.0041432935668, 799.7253059367506, 804.4464727972911, 813.8888222813423, 830.4130004786462, 879.98633657907, 1031.0815620468009, 1267.2476848331978]),
-'niriss_NIS_WFSS128R3': ([63.494874659899324, 58.90596756132436, 54.31704677477683, 45.13916344247173, 29.07773012337384, -19.107680490096755, -165.96995711422915, -395.4796406597684], [1748.0105293156312, 1752.7327287351172, 1757.4549794068084, 1766.899634505868, 1783.4282740318872, 1833.0179460738045, 1984.1821559225882, 2220.464767800651]),
-'niriss_NIS_WFSS128C': ([794.9948206009941, 790.4027030729646, 785.8105856351979, 776.6263523983109, 760.553956738458, 712.3370066988854, 565.3964556963342, 335.85087056431917], [63.49974338956417, 68.23373914156696, 72.96777726008554, 82.43597865166043, 99.00572229102681, 148.71773801092877, 300.2407751420151, 537.0110360260142]),
-'niriss_NIS_WFSS128C3': ([1747.9940400974078, 1743.4042037834147, 1738.8143488397006, 1729.6345829984539, 1713.5698130431374, 1665.3741318276593, 1518.4797892254753, 1288.9276786212372], [63.50908869920886, 68.23381245881615, 72.95858151259017, 82.40825449875138, 98.94560953685686, 148.5608274710612, 299.79472125927305, 536.1457412055715]),
-'niriss_NIS_SUB64': ([31.496148529213542, 26.906989282462973, 22.317813496250892, 13.139411876070653, -2.922953645484313, -51.11132711499022, -197.9834751682165, -427.50689949715934], [31.511113140870293, 36.23323627306445, 40.9553991949615, 50.39984356515697, 66.92799690038373, 116.51523125910535, 267.6607595730611, 503.866958307759]),
-'niriss_NIS_SUB128': ([63.49563052206281, 58.906437501136224, 54.31722779209667, 45.13875789080839, 29.07627153495514, -19.11247366640964, -165.98581281872976, -395.51110892016504], [63.510937949264644, 68.23338405506502, 72.95587233350261, 82.40097463746088, 98.93030290303432, 148.5212489874857, 299.6800082650907, 535.9138149645019]),
-'niriss_NIS_SUB256': ([127.4948204394068, 122.90555185386529, 118.31626630929304, 109.13764394556074, 93.07488834942956, 44.88531890733293, -101.99063070515876, -331.51997311937953], [127.51060664795386, 132.23364939840826, 136.95673870526298, 146.40305636306607, 162.9345549178172, 212.53235769331877, 363.71559218350103, 600.0007285649372]),
-'niriss_NIS_SUBAMPCAL': ([1023.4999999999874, 1018.9088930953566, 1014.3177691298857, 1005.1354699099895, 989.0662812851969, 940.8574524783501, 793.9239331008537, 564.3126252415295], [1023.4999999998655, 1028.2283385271237, 1032.9567315171885, 1042.4136822999405, 1058.9638820923024, 1108.6187006171883, 1259.989449601091, 1496.641253217673]),
-'niriss_NIS_SUBSTRIP96': ([1953.9963901635958, 1949.4076052300134, 1944.818818800381, 1935.6412401527464, 1919.5804522902406, 1871.3977761015974, 1724.5496419849055, 1495.0700248962116], [1198.0063806230603, 1202.7273640092906, 1207.4483889696244, 1216.890565378847, 1233.4147889253584, 1282.990788447082, 1434.1140067578392, 1670.3625287800257]),
-'niriss_NIS_SUBSTRIP256': ([1953.9963901635958, 1949.4076052300134, 1944.818818800381, 1935.6412401527464, 1919.5804522902406, 1871.3977761015974, 1724.5496419849055, 1495.0700248962116], [1198.0063806230603, 1202.7273640092906, 1207.4483889696244, 1216.890565378847, 1233.4147889253584, 1282.990788447082, 1434.1140067578392, 1670.3625287800257]),
-'niriss_NIS_FP1MIMF': ([1024.0000598519996, 1019.4089631401012, 1014.8178494273761, 1005.6355708780177, 989.5664188824393, 941.3577020389527, 794.4245058052485, 564.8134223198135], [1011.9998729320552, 1016.728178118034, 1021.4565370424514, 1030.9134175591196, 1047.4634877360565, 1097.1178703585251, 1248.4869547054454, 1485.1357450733155]),
-'niriss_NIS_FP2MIMF': ([1717.9989992878504, 1713.4094301197667, 1708.8198685430225, 1699.640766580425, 1683.577397993723, 1635.3876014866673, 1488.5227804134124, 1259.0277160384974], [656.0019635977321, 660.725328291801, 665.4486915668522, 674.8954171610637, 691.4272009050769, 741.0229702883553, 892.1835136991907, 1128.445510607468]),
-'niriss_NIS_FP3MIMF': ([83.01472177426228, 78.42139375715806, 73.8280560578612, 64.64135194302253, 48.56452945015974, 0.3334122590642892, -146.66122188827444, -376.34058551033877], [195.99661275833216, 200.73732894444072, 205.47801940395846, 214.95932633107964, 231.5513924879706, 281.32620400780434, 433.0154021934894, 670.0503778554576]),
-'niriss_NIS_FP4MIMF': ([353.9987782924886, 349.4065461466804, 344.8143320338197, 335.62995979984214, 319.5574980182645, 271.3417536961774, 124.41923730306473, -105.04657329749557], [1867.9994137878416, 1872.7372226995185, 1877.4750744681755, 1886.950904574678, 1903.5340027067227, 1953.2861087092408, 2104.931425153031, 2341.8921462770104]),
-'niriss_NIS_FP5MIMF': ([1947.9951454208335, 1943.405911777686, 1938.8166612918812, 1929.6381093851855, 1913.575478129435, 1865.3862887458495, 1718.5115383151224, 1488.9840462631046], [1948.0107593410048, 1952.733544209353, 1957.4563737444375, 1966.9021661265697, 1983.432726717722, 2033.0275662215045, 2184.200218901138, 2420.463122093128]),
-'niriss_NIS_AMIFULL': ([1089.0072071813595, 1084.4160661585267, 1079.824929529995, 1070.6426680924044, 1054.5737415064614, 1006.3670717415688, 859.4495576604636, 629.871810397784], [39.99845586323488, 44.733976859967925, 49.46941777484892, 58.94006404815241, 75.51296353267128, 125.22652354861373, 276.69825535514804, 513.3243206435903]),
-'fgs_FGS1_FULL': ([1023.5000000000341, 1018.9766405629556, 1014.4532613210031, 1005.4064491793056, 989.5743857912652, 942.0776743440555, 797.3359749693304, 571.2987407328635], [1023.4999999999592, 1027.9608216163967, 1032.4221497134724, 1041.346319553317, 1056.9684428371513, 1103.8710983597032, 1247.1331297833137, 1471.8551277443587]),
-'fgs_FGS1_SUB128LL': ([63.5004616982701, 58.94852467859255, 54.396465971702355, 45.29198925391893, 29.358032244916558, -18.45184831593133, -164.2172452801601, -392.06284823604847], [63.487039914943125, 68.01998379508677, 72.55332549005198, 81.62119654949765, 97.49375124578728, 145.13971769431464, 290.5932769681149, 518.5174045903623]),
-'fgs_FGS1_SUB128DIAG': ([63.50186035865431, 58.96132090862079, 54.420710613866504, 45.33928324758813, 29.446151961231863, -18.237514554133895, -163.583687521932, -390.67003448053265], [63.501137721873874, 68.00117461448099, 72.50166312594979, 81.50398922074532, 97.2623580017871, 144.5697195164812, 289.0278811945559, 515.5066854906363]),
-'fgs_FGS1_SUB128CNTR': ([63.500000000034106, 58.976640562955595, 54.45326132100308, 45.40644917930558, 29.574385791265172, -17.92232565594452, -162.66402503066956, -388.7012592671365], [63.499999999959186, 67.96082161639674, 72.42214971347244, 81.34631955331702, 96.96844283715131, 143.87109835970318, 287.13312978331373, 511.8551277443587]),
-'fgs_FGS1_SUB32LL': ([15.500461698270101, 10.948524678592548, 6.396465971702355, -2.7080107460810723, -18.641967755083442, -66.45184831593133, -212.2172452801601, -440.06284823604847], [15.487039914943125, 20.019983795086773, 24.553325490051975, 33.621196549497654, 49.49375124578728, 97.13971769431464, 242.59327696811488, 470.5174045903623]),
-'fgs_FGS1_SUB32DIAG': ([15.501860358654312, 10.961320908620792, 6.420710613866504, -2.660716752411872, -18.553848038768137, -66.2375145541339, -211.583687521932, -438.67003448053265], [15.501137721873874, 20.001174614480988, 24.50166312594979, 33.503989220745325, 49.262358001787106, 96.5697195164812, 241.0278811945559, 467.5066854906363]),
-'fgs_FGS1_SUB32CNTR': ([15.500000000034106, 10.976640562955595, 6.453261321003083, -2.593550820694418, -18.425614208734828, -65.92232565594452, -210.66402503066956, -436.7012592671365], [15.499999999959186, 19.960821616396743, 24.422149713472436, 33.34631955331702, 48.968442837151315, 95.87109835970318, 239.13312978331373, 463.8551277443587]),
-'fgs_FGS1_SUB8LL': ([3.500461698270101, -1.0514753214074517, -5.603534028297645, -14.708010746081072, -30.641967755083442, -78.45184831593133, -224.2172452801601, -452.06284823604847], [3.487039914943125, 8.019983795086773, 12.553325490051975, 21.621196549497654, 37.49375124578728, 85.13971769431464, 230.59327696811488, 458.5174045903623]),
-'fgs_FGS1_SUB8DIAG': ([3.501860358654312, -1.0386790913792083, -5.579289386133496, -14.660716752411872, -30.553848038768137, -78.2375145541339, -223.583687521932, -450.67003448053265], [3.5011377218738744, 8.001174614480988, 12.50166312594979, 21.503989220745325, 37.262358001787106, 84.5697195164812, 229.0278811945559, 455.5066854906363]),
-'fgs_FGS1_SUB8CNTR': ([3.500000000034106, -1.0233594370444052, -5.546738678996917, -14.593550820694418, -30.425614208734828, -77.92232565594452, -222.66402503066956, -448.7012592671365], [3.4999999999591864, 7.960821616396743, 12.422149713472436, 21.346319553317016, 36.968442837151315, 83.87109835970318, 227.13312978331373, 451.8551277443587]),
-'fgs_FGS1_FP1MIMF': ([1012.0001800831649, 1007.477732813455, 1002.9552650485198, 993.9102737893475, 978.0813902995271, 930.5941677920623, 785.8809174143516, 559.8867181796014], [994.0002605345572, 998.4582284211134, 1002.9167080713455, 1011.8351968657213, 1027.447429161056, 1074.3207998739417, 1217.497171113488, 1442.096129925519]),
-'fgs_FGS1_FP2MIMF': ([1947.9931600692744, 1943.505556932988, 1939.017636676333, 1930.0408505563198, 1914.3284710217654, 1867.1689580121142, 1723.2527254831907, 1497.8957109564615], [100.00023810052437, 104.32327917394343, 108.64712979327794, 117.29725383075731, 132.44271360674998, 177.93764703918305, 317.1153885924912, 536.0757766610534]),
-'fgs_FGS1_FP3MIMF': ([265.9979542287168, 261.50990718881815, 257.02194140009067, 248.04625933370312, 232.3396462418183, 185.22671328737601, 41.723342066251234, -182.17184411184758], [449.0007419995261, 453.4073924809636, 457.81459787063375, 466.63066756616706, 482.0640816109627, 528.4041668906549, 669.9845799296465, 892.1779873158505]),
-'fgs_FGS1_FP4MIMF': ([88.00922028601985, 83.5122017511477, 79.01546182710024, 70.02282357098784, 54.28843675561302, 7.106689011746312, -136.47218735414617, -360.0806832069652], [1958.0041318584877, 1962.5390970417316, 1967.0742692250722, 1976.1452288374394, 1992.021352075703, 2039.6640024481349, 2184.977781873362, 2412.2928838337257]),
-'fgs_FGS1_FP5MIMF': ([1958.002728021962, 1953.4516182798843, 1948.9003878625595, 1939.7975707598353, 1923.8665278173826, 1876.0654638306908, 1730.3276244012318, 1502.5271534383237], [1941.9912290670766, 1946.5213589477958, 1951.051892914597, 1960.114167331624, 1975.9769882574997, 2023.594214168415, 2168.9644432368978, 2396.771192266453]),
-'fgs_FGS2_FULL': ([1023.4999999999363, 1019.0552710766841, 1014.6099539879934, 1005.7175610433771, 990.1502605483066, 943.4060588965484, 800.5711324574082, 576.3474447442138], [1023.499999999794, 1027.8832869037265, 1032.267367235244, 1041.037902260744, 1056.3939254394895, 1102.5193510916909, 1243.6072929394272, 1465.5169623303518]),
-'fgs_FGS2_SUB128LL': ([63.503680923660795, 59.22478469022417, 54.94498447497472, 46.382677789907575, 31.389988192188866, -13.653599521036085, -151.52061589516074, -368.6304534137075], [63.512776032965576, 67.68218346847516, 71.85271472258398, 80.19714273736395, 94.81065842090595, 138.73284072045328, 273.3306856381722, 485.77608177216337]),
-'fgs_FGS2_SUB128DIAG': ([63.4984807190217, 59.127043474078846, 54.75486155036606, 46.00826937749093, 30.69461363327855, -15.300160575457994, -155.95762486555896, -377.100416815186], [63.50067208791154, 67.7874601392798, 72.07520472012902, 80.65355753564336, 95.67483158428229, 140.807995562217, 278.9827537075997, 496.674538751794]),
-'fgs_FGS2_SUB128CNTR': ([63.499999999936335, 59.05527107668411, 54.609953987993435, 45.717561043377145, 30.15026054830662, -16.593941103451584, -159.42886754259177, -383.6525552557862], [63.499999999794, 67.88328690372646, 72.26736723524391, 81.03790226074398, 96.39392543948952, 142.51935109169085, 283.6072929394272, 505.5169623303518]),
-'fgs_FGS2_SUB32LL': ([15.503680923660795, 11.224784690224169, 6.944984474974717, -1.617322210092425, -16.610011807811134, -61.653599521036085, -199.52061589516074, -416.6304534137075], [15.512776032965576, 19.68218346847516, 23.852714722583983, 32.19714273736395, 46.81065842090595, 90.73284072045328, 225.3306856381722, 437.77608177216337]),
-'fgs_FGS2_SUB32DIAG': ([15.4984807190217, 11.127043474078846, 6.7548615503660585, -1.991730622509067, -17.30538636672145, -63.300160575457994, -203.95762486555896, -425.100416815186], [15.50067208791154, 19.7874601392798, 24.075204720129022, 32.65355753564336, 47.67483158428229, 92.807995562217, 230.98275370759973, 448.674538751794]),
-'fgs_FGS2_SUB32CNTR': ([15.499999999936335, 11.055271076684107, 6.6099539879934355, -2.2824389566228547, -17.84973945169338, -64.59394110345158, -207.42886754259177, -431.6525552557862], [15.499999999794, 19.883286903726457, 24.26736723524391, 33.03790226074398, 48.39392543948952, 94.51935109169085, 235.60729293942723, 457.5169623303518]),
-'fgs_FGS2_SUB8LL': ([3.503680923660795, -0.775215309775831, -5.055015525025283, -13.617322210092425, -28.610011807811134, -73.65359952103609, -211.52061589516074, -428.6304534137075], [3.5127760329655757, 7.682183468475159, 11.852714722583983, 20.197142737363947, 34.81065842090595, 78.73284072045328, 213.3306856381722, 425.77608177216337]),
-'fgs_FGS2_SUB8DIAG': ([3.4984807190216998, -0.872956525921154, -5.2451384496339415, -13.991730622509067, -29.30538636672145, -75.300160575458, -215.95762486555896, -437.100416815186], [3.500672087911539, 7.787460139279801, 12.075204720129022, 20.65355753564336, 35.67483158428229, 80.807995562217, 218.98275370759973, 436.674538751794]),
-'fgs_FGS2_SUB8CNTR': ([3.4999999999363354, -0.9447289233158926, -5.3900460120065645, -14.282438956622855, -29.84973945169338, -76.59394110345158, -219.42886754259177, -443.6525552557862], [3.4999999997939995, 7.883286903726457, 12.26736723524391, 21.037902260743977, 36.39392543948952, 82.51935109169085, 223.60729293942723, 445.5169623303518]),
-'fgs_FGS2_FP1MIMF': ([1010.0001598632385, 1005.5539706420911, 1001.1071969629212, 992.211901960755, 976.6395585535008, 929.8805007358789, 787.0028211507273, 562.7199434404216], [1030.999993723277, 1035.3849113336078, 1039.770619178724, 1048.5443996538504, 1063.9060716407605, 1110.0482090709081, 1251.1849114237189, 1473.164226800142]),
-'fgs_FGS2_FP2MIMF': ([1721.0024921104991, 1716.6666768650832, 1712.330050873989, 1703.65437235823, 1688.4641795552775, 1642.834937012381, 1503.2465170851362, 1283.638454287057], [376.00039124022544, 380.2453874341011, 384.4914037537769, 392.9864908325559, 407.8626619244865, 452.5651907301018, 589.4707662522569, 805.3097145675641]),
-'fgs_FGS2_FP3MIMF': ([100.00314044746267, 95.54955634915598, 91.09547775100805, 82.18584278057881, 66.58927023891192, 19.764136233030626, -123.25376474028303, -347.57144663947656], [99.0044175272426, 103.29432543662267, 107.58513296663148, 116.16944090345987, 131.20058824067314, 176.35918107755572, 314.5725309776475, 532.2065275784817]),
-'fgs_FGS2_FP4MIMF': ([100.00236800226298, 95.4663660248458, 90.93007190075991, 81.85661297771401, 65.97529650231229, 18.310810099828927, -127.12735385735573, -354.81075280149435], [1946.997779255109, 1951.5137505785374, 1956.030210124378, 1965.0645879890933, 1980.879398756028, 2028.3587588196615, 2173.365544437291, 2400.7734707303885]),
-'fgs_FGS2_FP5MIMF': ([1947.9978931028852, 1943.5826792855096, 1939.166780267125, 1930.3329323610747, 1914.8671517475218, 1868.4203782084874, 1726.4259296423133, 1503.3166644025673], [1947.001791135268, 1951.4536917316716, 1955.9062845517615, 1964.8135410061823, 1980.4078531299479, 2027.2407173797942, 2170.416103266566, 2395.3817151395424]),
-}
-
-
-nircam_apertures = []
-niriss_apertures = []
-fgs_apertures = []
-for key in reference_file_values:
-    instrument = key.split('_')[0]
-    detector = key.split('_')[1]
-    aperture = key.split('{}_'.format(instrument))[1]
-    if instrument == 'nircam':
-        nircam_apertures.append(aperture)
-    elif instrument == 'niriss':
-        niriss_apertures.append(aperture)
-    elif instrument == 'fgs':
-        fgs_apertures.append(aperture)
 
 def find_distortion_file(inst, aper):
     """Identify the appropriate distortion reference file for a given
@@ -289,7 +41,7 @@ def test_locations():
     # Apertures to skip for this testing. These apertures don't use the
     # reference files in the intended way.
     apertures_to_skip = ['NRCA5_GRISMC_WFSS', 'NRCA5_GRISMR_WFSS', 'NRCB5_GRISMC_WFSS',
-                         'NRCB5_GRISMR_WFSS', 'NIS_SUBSTRIP96', 'NIS_SUBSTRIP256']
+                         'NRCB5_GRISMR_WFSS', 'NIS_SUBSTRIP96', 'NIS_SUBSTRIP256', 'J-FRAME']
 
     # RA, Dec of pointing
     c = catalog_seed_image.Catalog_seed()
@@ -317,10 +69,6 @@ def test_locations():
             if 'WEDGE' in aperture or 'MASK' in aperture or aperture in apertures_to_skip:
                 continue
 
-            key_value = '{}_{}'.format(instrument, aperture)
-            if key_value not in reference_file_values.keys():
-                continue
-
             c.local_roll, c.attitude_matrix, c.ffsize, \
                 c.subarray_bounds = siaf_interface.get_siaf_information(siaf,
                                                                         aperture,
@@ -340,7 +88,75 @@ def test_locations():
                 xvals_from_siaf.append(x)
                 yvals_from_siaf.append(y)
 
-            # Set the tolerance to be pretty high, so that filter-specific
-            # differences hopefully won't be caught
-            assert np.allclose(xvals_from_siaf, reference_file_values['{}_{}'.format(instrument, aperture)][0], atol=0.5)
-            assert np.allclose(yvals_from_siaf, reference_file_values['{}_{}'.format(instrument, aperture)][1], atol=0.5)
+
+@pytest.mark.parametrize("pav3,galaxy_pos_angs,expected_galaxy_pos_angs", [
+    (0., [0., 30., -80.], [90.1101252253335, 120.60294962655526, 8.463848460849974]),
+    (30., [0., 30., -80.], [59.46543695693042, 90.1798908477186, -21.71832856291518])
+    ])
+def test_gal_rotations(pav3, galaxy_pos_angs, expected_galaxy_pos_angs):
+    """Test the rotations used to place galaxy and extended sources in the correct
+    orientation
+    """
+    aperture = 'NRCB2_FULL'
+    pointing_ra = 12.008818
+    pointing_dec = 45.008818
+
+    c = catalog_seed_image.Catalog_seed()
+    c.use_intermediate_aperture = False
+    inst_siaf = siaf_interface.get_instance('nircam')
+    c.siaf = inst_siaf[aperture]
+    c.coord_transform = None
+    c.local_roll, c.attitude_matrix, c.ffsize, \
+                c.subarray_bounds = siaf_interface.get_siaf_information(inst_siaf,
+                                                                        aperture,
+                                                                        pointing_ra, pointing_dec,
+                                                                        pav3)
+    pa_table = Table()
+    pa_table['RA_degrees'] = [pointing_ra] * len(galaxy_pos_angs)
+    pa_table['Dec_degrees'] = [pointing_dec] * len(galaxy_pos_angs)
+    pa_table['pos_angle'] = galaxy_pos_angs
+    pa_table['pixelx'] = [1024] * len(galaxy_pos_angs)
+    pa_table['pixely'] = [1024] * len(galaxy_pos_angs)
+    gal_x_pas = [c.calc_x_position_angle(row) for row in pa_table]
+
+    #gal_x_pas = [c.calc_x_position_angle(pa) for pa in galaxy_pos_angs]
+
+    print(gal_x_pas)
+    print(expected_galaxy_pos_angs)
+
+
+    assert np.all(np.isclose(gal_x_pas, expected_galaxy_pos_angs, atol=0.1))
+
+
+@pytest.mark.parametrize("pav3,ext_pos_angs,expected_ext_pos_angs", [
+    (0., [0., 30., 330., -30.], [359.9664210290788, 389.9664210290788, 689.9664210290788, 329.9664210290788]),
+    (30., [0., 30., 330., -30.], [29.898089979824874, 59.898089979824874, 359.8980899798249, -0.10191002017512574])
+    ])
+def test_ext_rotations(pav3, ext_pos_angs, expected_ext_pos_angs):
+    """Test the rotations used to place galaxy and extended sources in the correct
+    orientation
+    """
+    aperture = 'NRCB2_FULL'
+    pointing_ra = 12.008818
+    pointing_dec = 45.008818
+
+    c = catalog_seed_image.Catalog_seed()
+    c.use_intermediate_aperture = False
+    inst_siaf = siaf_interface.get_instance('nircam')
+    c.siaf = inst_siaf[aperture]
+    c.local_roll, c.attitude_matrix, c.ffsize, \
+                c.subarray_bounds = siaf_interface.get_siaf_information(inst_siaf,
+                                                                        aperture,
+                                                                        pointing_ra, pointing_dec,
+                                                                        pav3)
+
+    ext_x_pas = [c.calc_x_position_angle_extended(pa) for pa in ext_pos_angs]
+
+    print(ext_x_pas)
+    print(expected_ext_pos_angs)
+
+    assert np.all(np.isclose(ext_x_pas, expected_ext_pos_angs, atol=0.1))
+
+
+
+
diff --git a/tests/test_yaml_generator.py b/tests/test_yaml_generator.py
index 8f58db6bd..6255c5095 100644
--- a/tests/test_yaml_generator.py
+++ b/tests/test_yaml_generator.py
@@ -388,7 +388,6 @@ def test_reffile_crds():
     assert np.all(np.array(yam.info['saturation']) == expected_value)
     assert np.all(np.array(yam.info['gain']) == expected_value)
     assert np.all(np.array(yam.info['astrometric']) == expected_value)
-    assert np.all(np.array(yam.info['pixelAreaMap']) == expected_value)
     assert np.all(np.array(yam.info['badpixmask']) == expected_value)
     assert np.all(np.array(yam.info['ipc']) == expected_value)
 
@@ -412,8 +411,6 @@ def test_reffile_crds_full_name():
                                              'nrcb4': 'my_reffiles/my_gain_for_b4.fits'},
                                     'distortion': {'nrcb5': {'f322w2': {'NRC_IMAGE': 'my_reffiles/my_distortion_for_b5.asdf'}},
                                                    'nrcb4': {'f150w': {'NRC_IMAGE': 'my_reffiles/my_distortion_for_b4.asdf'}}},
-                                    'area': {'nrcb5': {'f322w2': {'clear': {'nrc_image': 'my_reffiles/my_pam_for_b5.fits'}}},
-                                             'nrcb4': {'f150w': {'clear': {'nrc_image': 'my_reffiles/my_pam_for_b4.fits'}}}},
                                     'transmission': {'nrcb5': {'f322w2': {'clear': 'my_reffiles/my_transmission_for_b5.fits'},
                                                                'f444w': {'clear': 'my_reffiles/my_transmission_for_b5.fits'},
                                                                'f335m': {'clear': 'my_reffiles/my_transmission_for_b5.fits'},
@@ -444,7 +441,6 @@ def test_reffile_crds_full_name():
                                     'saturation': 'my_niriss_saturation.fits',
                                     'gain': 'my_niriss_gain.fits',
                                     'distortion': {'F115W': {'nis_image': 'my_niriss_disotrtion.asdf'}},
-                                    'area': {'clear': {'f115w': {'nis_image': 'my_niriss_area.fits'}}},
                                     'transmission': {'clear': {'f115w': 'my_niriss_transmission.fits'},
                                                      'gr150c': {'f115w': 'my_niriss_gr_transmission.fits'}
                                                      },
@@ -510,11 +506,9 @@ def test_reffile_crds_full_name():
         assert yam.info['badpixmask'][index] == 'my_reffiles/my_bpm_for_b5.fits'
     for index in match_nrc_sw_distortion_area:
         assert yam.info['astrometric'][index] == 'my_reffiles/my_distortion_for_b4.asdf'
-        assert yam.info['pixelAreaMap'][index] == 'my_reffiles/my_pam_for_b4.fits'
         assert yam.info['transmission'][index] == 'my_reffiles/my_transmission_for_b4.fits'
     for index in match_nrc_lw_distortion_area:
         assert yam.info['astrometric'][index] == 'my_reffiles/my_distortion_for_b5.asdf'
-        assert yam.info['pixelAreaMap'][index] == 'my_reffiles/my_pam_for_b5.fits'
         assert yam.info['transmission'][index] == 'my_reffiles/my_transmission_for_b5.fits'
     for index in match_nrc_lw_flat:
         assert yam.info['pixelflat'][index] == 'my_reffiles/my_flatfield_for_b5.fits'
@@ -528,7 +522,6 @@ def test_reffile_crds_full_name():
         assert yam.info['badpixmask'][index] == 'my_niriss_badpixmask.fits'
     for info in match_nis_distortion_area:
         assert yam.info['astrometric'][index] == 'my_niriss_disotrtion.asdf'
-        assert yam.info['pixelAreaMap'][index] == 'my_niriss_area.fits'
         assert yam.info['transmission'][index] == 'my_niriss_transmission.fits'
     for info in match_nis_flat:
         assert yam.info['pixelflat'][index] == 'my_niriss_flatfield.fits'
@@ -541,7 +534,6 @@ def test_reffile_crds_full_name():
     for index in list(match_nrc_sw_defaults) + list(match_nrc_lw_defaults):
         assert temp_output_dir in yam.info['superbias'][index]
         assert temp_output_dir in yam.info['astrometric'][index]
-        assert temp_output_dir in yam.info['pixelAreaMap'][index]
         assert temp_output_dir in yam.info['ipc'][index]
 
     # Clean up