TweakRegStep

class jwst.tweakreg.TweakRegStep(name=None, parent=None, config_file=None, _validate_kwds=True, **kws)

Bases: JwstStep

Perform image alignment based on catalogs of sources detected in input images.

Create a Step instance.

Parameters:

namestr

The name of the Step instance. Used in logging messages and in cache filenames. If not provided, one will be generated based on the class name.

parentStep

The parent step of this step. Used to determine a fully-qualified name for this step, and to determine the mode in which to run this step.

config_filestr or pathlib.Path

The path to the config file that this step was initialized with. Use to determine relative path names of other config files.

_validate_kwdsbool

Validate given kws against specs/config.

**kwsdict

Additional parameters to set. These will be set as member variables on the new Step instance.

Attributes Summary

class_alias
reference_file_types
spec

Methods Summary

process(input_data)

Perform image alignment based on catalogs of sources detected in input images.

Attributes Documentation

class_alias = 'tweakreg'

reference_file_types: list = []

spec

save_catalogs = boolean(default=False) # Write out catalogs?
use_custom_catalogs = boolean(default=False) # Use custom user-provided catalogs?
catalog_format = string(default='ecsv') # Catalog output file format
catfile = string(default='') # Name of the file with a list of custom user-provided catalogs
starfinder = option('dao', 'iraf', 'segmentation', default='iraf') # Star finder to use.

# general starfinder options
snr_threshold = float(default=10.0) # SNR threshold above the bkg for star finder
kernel_fwhm = float(default=2.5) # Gaussian kernel FWHM in pixels
bkg_boxsize = integer(default=400) # The background mesh box size in pixels.

# kwargs for DAOStarFinder and IRAFStarFinder, only used if starfinder is 'dao' or 'iraf'
minsep_fwhm = float(default=0.0) # Minimum separation between detected objects in FWHM
sigma_radius = float(default=1.5) # Truncation radius of the Gaussian kernel, units of sigma
sharplo = float(default=0.5) # The lower bound on sharpness for object detection.
sharphi = float(default=2.0) # The upper bound on sharpness for object detection.
roundlo = float(default=0.0) # The lower bound on roundness for object detection.
roundhi = float(default=0.2) # The upper bound on roundness for object detection.
brightest = integer(default=200) # Keep top ``brightest`` objects
peakmax = float(default=None) # Filter out objects with pixel values >= ``peakmax``

# kwargs for SourceCatalog and SourceFinder, only used if starfinder is 'segmentation'
npixels = integer(default=10) # Minimum number of connected pixels
connectivity = option(4, 8, default=8) # The connectivity defining the neighborhood of a pixel
nlevels = integer(default=32) # Number of multi-thresholding levels for deblending
contrast = float(default=0.001) # Fraction of total source flux an object must have to be deblended
multithresh_mode = option('exponential', 'linear', 'sinh', default='exponential') # Multi-thresholding mode
localbkg_width = integer(default=0) # Width of rectangular annulus used to compute local background around each source
apermask_method = option('correct', 'mask', 'none', default='correct') # How to handle neighboring sources
kron_params = float_list(min=2, max=3, default=None) # Parameters defining Kron aperture
deblend = boolean(default=True) # deblend sources?

# align wcs options
enforce_user_order = boolean(default=False) # Align images in user specified order?
expand_refcat = boolean(default=False) # Expand reference catalog with new sources?
minobj = integer(default=15) # Minimum number of objects acceptable for matching
fitgeometry = option('shift', 'rshift', 'rscale', 'general', default='rshift') # Fitting geometry
nclip = integer(min=0, default=3) # Number of clipping iterations in fit
sigma = float(min=0.0, default=3.0) # Clipping limit in sigma units

# xyxymatch options
searchrad = float(default=2.0) # The search radius in arcsec for a match
use2dhist = boolean(default=True) # Use 2d histogram to find initial offset?
separation = float(default=1.0) # Minimum object separation for xyxymatch in arcsec
tolerance = float(default=0.7) # Matching tolerance for xyxymatch in arcsec
xoffset = float(default=0.0), # Initial guess for X offset in arcsec
yoffset = float(default=0.0) # Initial guess for Y offset in arcsec

# Absolute catalog options
abs_refcat = string(default='') # Catalog file name or one of: "'GAIADR3'", "'GAIADR2'", or "'GAIADR1'", or None, or ''
save_abs_catalog = boolean(default=False) # Write out used absolute astrometric reference catalog as a separate product

# Absolute catalog align wcs options
abs_minobj = integer(default=15) # Minimum number of objects acceptable for matching when performing absolute astrometry
abs_fitgeometry = option('shift', 'rshift', 'rscale', 'general', default='rshift')
abs_nclip = integer(min=0, default=3) # Number of clipping iterations in fit when performing absolute astrometry
abs_sigma = float(min=0.0, default=3.0) # Clipping limit in sigma units when performing absolute astrometry

# absolute catalog xyxymatch options
abs_searchrad = float(default=6.0) # The search radius in arcsec for a match when performing absolute astrometry
abs_use2dhist = boolean(default=True) # Use 2D histogram to find initial offset when performing absolute astrometry? We encourage setting this parameter to True. Otherwise, xoffset and yoffset will be set to zero.
abs_separation = float(default=1) # Minimum object separation in arcsec when performing absolute astrometry
abs_tolerance = float(default=0.7) # Matching tolerance for xyxymatch in arcsec when performing absolute astrometry

# SIP approximation options, should match assign_wcs
sip_approx = boolean(default=True) # enables SIP approximation for imaging modes.
sip_max_pix_error = float(default=0.01) # max err for SIP fit, forward.
sip_degree = integer(max=6, default=None) # degree for forward SIP fit, None to use best fit.
sip_max_inv_pix_error = float(default=0.01) # max err for SIP fit, inverse.
sip_inv_degree = integer(max=6, default=None) # degree for inverse SIP fit, None to use best fit.
sip_npoints = integer(default=12) #  number of points for SIP

# stpipe general options
output_use_model = boolean(default=True) # When saving use `DataModel.meta.filename`
in_memory = boolean(default=True) # If False, preserve memory using temporary files at expense of runtime

Methods Documentation

process(input_data)

Perform image alignment based on catalogs of sources detected in input images.

Parameters:

input_dataModelLibrary

A collection of data models. This can also be an ASN-type input to be read into a ModelLibrary.

Returns:

outputModelLibrary

The aligned input data models.