Description

Class:

jwst.tweakreg.TweakRegStep

Alias:

tweakreg

Overview

This step creates image catalogs of point-like sources whose centroids are then used to compute corrections to the WCS of the input images such that sky catalogs obtained from the image catalogs using the corrected WCS will align on the sky.

Source Detection

If the meta.tweakreg_catalog attribute of input data models is a non-empty string and use_custom_catalogs is True, then it will be interpreted as a file name of a user-provided source catalog. The catalog must be in a format automatically recognized by read().

When the meta.tweakreg_catalog attribute of input data models is None or an empty string, then the tweakreg step will attempt to detect sources in the input images. Stars are detected in the image with one of the following source detection algorithms: photutils.detection.DAOStarFinder (default), photutils.detection.IRAFStarFinder, or photutils.segmentation.SourceFinder in conjunction with photutils.segmentation.SourceCatalog.

DAOStarFinder is an implementation of the DAOFIND algorithm (Stetson 1987, PASP 99, 191). It searches images for local density maxima that have a peak amplitude greater than a specified threshold (the threshold is applied to a convolved image) and have a size and shape similar to a defined 2D Gaussian kernel. DAOFind also provides an estimate of the object’s roundness and sharpness, whose lower and upper bounds can be specified.

IRAFStarFinder is a Python implementation of the IRAF star finding algorithm, which also calculates the objects’ centroids, roundness, and sharpness. However, IRAFStarFinder uses image moments instead of 1-D Gaussian fits to projected light distributions like DAOStarFinder.

SourceFinder implements a segmentation algorithm that identifies sources in an image based on a number of connected pixels above a specified threshold value. The sources are deblended using a combination of multi-thresholding and watershed segmentation. SourceCatalog finds the centroids of these sources, which are used as the retrieved star positions.

Warning

It has been shown (STScI Technical Report JWST-STScI-008116, SM-12) that for undersampled PSFs, e.g. for short-wavelength NIRISS imaging data, DAOStarFinder gives bad results no matter the input parameters due to its use of 1-D Gaussian fits. IRAFStarFinder or SourceFinder should be used instead.

Note

SourceFinder is likely to detect non-stellar sources such as galaxies because sources are not assumed to be point-source-like. This may lead to mismatches between the derived source catalog and the reference catalog during the alignment step.

Custom Source Catalogs

Source detection built into the tweakreg step can be disabled by providing a file name to a custom source catalog in the meta.tweakreg_catalog attribute of input data models. The catalog must be in a format automatically recognized by read(). The catalog must contain either 'x' and 'y' or 'xcentroid' and 'ycentroid' columns which indicate source image coordinates (in pixels). Pixel coordinates are 0-indexed. An optional column in the catalog is the 'weight' column, which when present, will be used in fitting.

For the tweakreg step to use user-provided input source catalogs, use_custom_catalogs parameter of the tweakreg step must be set to True.

In addition to setting the meta.tweakreg_catalog attribute of input data models to the custom catalog file name, the tweakreg_step also supports two other ways of supplying custom source catalogs to the step:

  1. Adding tweakreg_catalog attribute to the members of the input ASN table - see ModelContainer for more details. Catalog file names are relative to ASN file path.

  2. Providing a simple two-column text file, specified via step’s parameter catfile, that contains input data models’ file names in the first column and the file names of the corresponding catalogs in the second column. Catalog file names are relative to catfile file path.

Specifying custom source catalogs via either the input ASN file or catfile will update input data models’ meta.tweakreg_catalog attributes to the catalog file names provided in either in the ASN file or catfile.

Note

When custom source catalogs are provided via both catfile and ASN file members’ attributes, the catfile takes precedence and catalogs specified via ASN file are ignored altogether.

Note

  1. Providing a data model file name in the catfile and leaving the corresponding source catalog file name empty – same as setting 'tweakreg_catalog' in the ASN file to an empty string "" – would set the corresponding input data model’s meta.tweakreg_catalog attribute to None. In this case, tweakreg_step will automatically generate a source catalog for that data model.

  2. If an input data model is not listed in the catfile or does not have the 'tweakreg_catalog' attribute provided in the ASN file, then the catalog file name in that model’s meta.tweakreg_catalog attribute will be used. If model.meta.tweakreg_catalog is None, tweakreg_step will automatically generate a source catalog for that data model.

Alignment

The source catalogs for each input image are compared to each other and linear (affine) coordinate transformations that align these catalogs are derived. This fit ensures that all the input images are aligned relative to each other. This step produces a combined source catalog for the entire set of input images as if they were combined into a single mosaic.

If the step parameter abs_refcat is set to ‘GAIADR3’, ‘GAIADR2’, or ‘GAIADR1’, an astrometric reference catalog then gets generated by querying a GAIA-based astrometric catalog web service for all astrometrically measured sources in the combined field-of-view of the set of input images. This catalog is generated from the catalogs available through the STScI MAST Catalogs and has the ability to account for proper motion to a given epoch. The epoch is computed from the observation date and time of the input data.

The combined source catalog derived in the first step then gets cross-matched and fit to this astrometric reference catalog. The pipeline initially supports fitting to the GAIADR3 catalog, with the option to select the GAIADR2 or GAIADR1 instead. The results of this one fit then gets back-propagated to all the input images to align them all to the astrometric reference frame while maintaining the relative alignment between the images.

For this part of alignment, instead of ‘GAIADR1’, ‘GAIADR2’, or ‘GAIADR3’, users can supply an external reference catalog by providing a path to an existing file. A user-supplied catalog must contain 'RA' and 'DEC' columns indicating reference source world coordinates (in degrees). An optional column in the catalog is the 'weight' column, which when present, will be used in fitting. The catalog must be in a format automatically recognized by read().

Grouping

Images taken at the same time (e.g., NIRCam images from all short-wave detectors) can be aligned together; that is, a single correction can be computed and applied to all these images because any error in telescope pointing will be identical in all these images and it is assumed that the relative positions of (e.g., NIRCam) detectors do not change. Identification of images that belong to the same “exposure” and therefore can be grouped together is based on several attributes described in ModelContainer. This grouping is performed automatically in the tweakreg step using the models_grouped property, which assigns a group ID to each input image model in meta.group_id.

However, when detector calibrations are not accurate, alignment of groups of images may fail (or result in poor alignment). In this case, it may be desirable to align each image independently. This can be achieved either by setting the image_model.meta.group_id attribute to a unique string or integer value for each image, or by adding the group_id attribute to the members of the input ASN table - see ModelContainer for more details.

Note

Group ID (group_id) is used by both tweakreg and skymatch steps and so modifying it for one step will affect the results in another step. If it is desirable to apply different grouping strategies to the tweakreg and skymatch steps, one may need to run each step individually and provide a different ASN as input to each step.

WCS Correction

The linear coordinate transformation computed in the previous step is used to define tangent-plane corrections that need to be applied to the GWCS pipeline in order to correct input image WCS. This correction is implemented by inserting a v2v3corr frame with tangent plane corrections into the GWCS pipeline of the image’s WCS.

Step Arguments

The tweakreg step has the following optional arguments:

Source finding parameters:

  • save_catalogs: A boolean indicating whether or not the catalogs should be written out. This parameter is ignored for input data models whose meta.tweakreg_catalog is a non-empty string pointing to a user-supplied source catalog. (Default=False)

  • use_custom_catalogs: A boolean that indicates whether to ignore source catalog in the input data model’s meta.tweakreg_catalog attribute. If False, new catalogs will be generated by the tweakreg step. (Default=False)

  • catalog_format: A str indicating catalog output file format. (Default= 'ecsv')

  • catfile: Name of the file with a list of custom user-provided catalogs. (Default= '')

  • bkg_boxsize: A positive int indicating the background mesh box size in pixels. (Default=400)

  • starfinder: A str indicating the source detection algorithm to use. Allowed values: 'iraf', 'dao', 'segmentation'. (Default= 'dao')

  • snr_threshold: A float value indicating SNR threshold above the background. Required for all star finders. (Default=10.0)

Additional source finding parameters for DAO and IRAF:

  • kernel_fwhm: A float value indicating the Gaussian kernel FWHM in pixels. (Default=2.5)

  • minsep_fwhm: A float value indicating the minimum separation between detected objects in units of number of FWHMs. (Default=0.0)

  • sigma_radius: A float value indicating the truncation radius of the Gaussian kernel in units of number of FWHMs. (Default=2.5)

  • sharplo: A float value indicating The lower bound on sharpness for object detection. (Default=0.2)

  • sharphi: A float value indicating the upper bound on sharpness for object detection. (Default=1.0)

  • roundlo: A float value indicating the lower bound on roundness for object detection. (Default=-1.0)

  • roundhi: A float value indicating the upper bound on roundness for object detection. (Default=1.0)

  • brightest: A positive int value indicating the number of brightest objects to keep. If None, keep all objects above the threshold. (Default=200)

  • peakmax: A float value used to filter out objects with pixel values >= peakmax. (Default=None)

Additional source finding parameters for segmentation:

  • npixels: An int value indicating the minimum number of connected pixels that comprises a segment (Default=10)

  • connectivity: An int value indicating the connectivity defining the neighborhood of a pixel. Options are 4, i.e., connected pixels touch along edges, or 8, i.e, connected pixels touch along edges or corners (Default=8)

  • nlevels: An int value indicating the number of multi-thresholding levels for deblending (Default=32)

  • contrast: A float value indicating the fraction of total source flux an object must have to be deblended (Default=0.001)

  • multithresh_mode: A str indicating the multi-thresholding mode. Allowed values: 'exponential', 'linear', 'sinh'. (Default= 'exponential')

  • localbkg_width: An int value indicating the width of rectangular annulus used to compute local background around each source. If set to 0, then local background will not be subtracted. (Default=0)

  • apermask_method: A str indicating the method used to handle neighboring sources when performing aperture photometry. Allowed values: 'correct', 'mask', 'none'. (Default= 'correct')

  • kron_params: A tuple of float values indicating the parameters defining Kron aperture. If None, the parameters (2.5, 1.4, 0.0) are used. (Default=None)

Optimize alignment order:

  • enforce_user_order: a boolean value indicating whether or not take the first image as a reference image and then align the rest of the images to that reference image in the order in which input images have been provided or to optimize order in which images are aligned. (Default=False)

Reference Catalog parameters:

  • expand_refcat: A boolean indicating whether or not to expand reference catalog with new sources from other input images that have been already aligned to the reference image. (Default=False)

Object matching parameters:

  • minobj: A positive int indicating minimum number of objects acceptable for matching. (Default=15)

  • searchrad: A float indicating the search radius in arcsec for a match. (Default=2.0)

  • use2dhist: A boolean indicating whether to use 2D histogram to find initial offset. (Default=True)

  • separation: Minimum object separation in arcsec. (Default=1.0)

  • tolerance: Matching tolerance for xyxymatch in arcsec. (Default=0.7)

  • xoffset: Initial guess for X offset in arcsec. (Default=0.0)

  • yoffset: Initial guess for Y offset in arcsec. (Default=0.0)

Catalog fitting parameters:

  • fitgeometry: A str value indicating the type of affine transformation to be considered when fitting catalogs. Allowed values:

    • 'shift': x/y shifts only

    • 'rshift': rotation and shifts

    • 'rscale': rotation and scale

    • 'general': shift, rotation, and scale

    The default value is “rshift”.

    Note

    Mathematically, alignment of images observed in different tangent planes requires fitgeometry='general' in order to fit source catalogs in the different images even if mis-alignment is caused only by a shift or rotation in the tangent plane of one of the images.

    However, under certain circumstances, such as small alignment errors or minimal dithering during observations that keep tangent planes of the images to be aligned almost parallel, then it may be more robust to use a fitgeometry setting with fewer degrees of freedom such as 'rshift', especially for “ill-conditioned” source catalogs such as catalogs with very few sources, or large errors in source positions, or sources placed along a line or bunched in a corner of the image (not spread across/covering the entire image).

  • nclip: A non-negative integer number of clipping iterations to use in the fit. (Default=3)

  • sigma: A positive float indicating the clipping limit, in sigma units, used when performing fit. (Default=3.0)

Absolute Astrometric fitting parameters:

Parameters used for absolute astrometry to a reference catalog.

  • abs_refcat: String indicating what astrometric catalog should be used. Currently supported options: ‘GAIADR1’, ‘GAIADR2’, ‘GAIADR3’, a path to an existing reference catalog, None, or ''. See jwst.tweakreg.tweakreg_step.SINGLE_GROUP_REFCAT for an up-to-date list of supported built-in reference catalogs.

    When abs_refcat is None or an empty string, alignment to the absolute astrometry catalog will be turned off. (Default= '')

  • abs_minobj: A positive int indicating minimum number of objects acceptable for matching. (Default=15)

  • abs_searchrad: A float indicating the search radius in arcsec for a match. It is recommended that a value larger than searchrad be used for this parameter (e.g. 3 times larger) (Default=6.0)

  • abs_use2dhist: A boolean indicating whether to use 2D histogram to find initial offset. It is strongly recommended setting this parameter to True. Otherwise the initial guess for the offsets will be set to zero (Default=True)

  • abs_separation: Minimum object separation in arcsec. It is recommended that a value smaller than separation be used for this parameter (e.g. 10 times smaller) (Default=0.1)

  • abs_tolerance: Matching tolerance for xyxymatch in arcsec. (Default=0.7)

  • abs_fitgeometry: A str value indicating the type of affine transformation to be considered when fitting catalogs. Allowed values:

    • 'shift': x/y shifts only

    • 'rshift': rotation and shifts

    • 'rscale': rotation and scale

    • 'general': shift, rotation, and scale

    The default value is “rshift”. Note that the same conditions/restrictions that apply to fitgeometry also apply to abs_fitgeometry.

  • abs_nclip: A non-negative integer number of clipping iterations to use in the fit. (Default = 3)

  • abs_sigma: A positive float indicating the clipping limit, in sigma units, used when performing fit. (Default=3.0)

  • save_abs_catalog: A boolean specifying whether or not to write out the astrometric catalog used for the fit as a separate product. (Default=False)

Further Documentation

The underlying algorithms as well as formats of source catalogs are described in more detail at

https://tweakwcs.readthedocs.io/en/latest/

Further description of the input parameters and algorithms for star finding can be found at the following links:

Reference Files

The tweakreg step uses the PARS-TWEAKREGSTEP parameter reference file.

PARS-TWEAKREGSTEP Parameter Reference File

REFTYPE:

PARS-TWEAKREGSTEP

Data model:

N/A

Reference Selection Keywords

CRDS selects appropriate pars-tweakregstep references based on the following keywords.

Instrument

Keywords

FGS

EXP_TYPE

MIRI

EXP_TYPE, FILTER

NIRCAM

EXP_TYPE, FILTER, PUPIL

NIRISS

EXP_TYPE, FILTER, PUPIL

Standard Keywords

The following table lists the keywords that are required to be present in all reference files. The first column gives the FITS keyword names. The second column gives the jwst data model name for each keyword, which is useful when using data models in creating and populating a new reference file. The third column gives the equivalent meta tag in ASDF reference file headers, which is the same as the name within the data model meta tree (second column).

FITS Keyword

Data Model Name

ASDF meta tag

AUTHOR

model.meta.author

author

DATAMODL

model.meta.model_type

model_type

DATE

model.meta.date

date

DESCRIP

model.meta.description

description

FILENAME

model.meta.filename

N/A

INSTRUME

model.meta.instrument.name

instrument: {name}

PEDIGREE

model.meta.pedigree

pedigree

REFTYPE

model.meta.reftype

reftype

TELESCOP

model.meta.telescope

telescope

USEAFTER

model.meta.useafter

useafter

NOTE: More information on standard required keywords can be found here: Standard Required Keywords