Description

Class:

jwst.coron.AlignRefsStep

Alias:

align_refs

The align_refs step is one of the coronagraphic-specific steps in the coron sub-package that is part of Stage 3 calwebb_coron3 processing. It computes offsets between science target images and reference PSF images, and shifts the PSF images into alignment. The alignment shifts are computed from the first integration and applied to all the subsequent ones for both the science target data and the reference PSF data. Each integration contained in the stacked PSF data (the result of the stack_refs) step is aligned to the first integration within a given science target exposure. This results in a new product for each science target exposure that contains a stack of individual PSF images that have been aligned to the first integration in the science target exposure.

Note that aligning to the first science integration is sufficient because flight data shows that there are minimal drifts during an observation in line-of-sight pointing, or in PSF properties.

Shifts between each PSF and target image are computed using the scipy.optimize.leastsq function. A 2D mask, supplied via a PSFMASK reference file, is used to indicate pixels to ignore when performing the minimization in the leastsq routine. The mask acts as a weighting function in performing the fit. Alignment of a PSF image is performed using the scipy.ndimage.fourier_shift function and the computed sub-pixel offsets.

Arguments

The align_refs step has two optional arguments:

--median_box_length (integer, default=3)

The box size to use when replacing bad pixels with the median in a surrounding box.

--bad_bits (string, default=”DO_NOT_USE”)

The DQ bit values from the input image DQ arrays that should be considered bad and replaced with the median in a surrounding box. For example, setting to "OUTLIER, SATURATED" (or equivalently "16, 2" or "18") will treat all pixels flagged as OUTLIER or SATURATED as bad, while setting to "" or None will treat all pixels as good and omit any bad pixel replacement.

Inputs

The align_refs step takes 2 inputs: a science target exposure containing a 3D stack of calibrated per-integration images and a “_psfstack” product containing a 3D stack of reference PSF images. If the target or PSF images have any of the data quality flags set to those specified by the bad_bits argument, these pixels are replaced with the median value of a region around the flagged data. The size of the box region to use for the replacement can also be specified. These corrected images are used in the align_refs step and passed along for subsequent processing.

3D calibrated images

Data model:

CubeModel

File suffix:

_calints

One of the science target exposures specified in the ASN file used as input to the calwebb_coron3 pipeline. This should be a “_calints” product from the calwebb_image2 pipeline and contains a 3D stack of per-integration images.

3D stacked PSF images

Data model:

CubeModel

File suffix:

_psfstack

A “_psfstack” product created by the stack_refs step, which contains the collection of all PSF images to be used, in the form of a 3D image stack.

Outputs

3D aligned PSF images

Data model:

CubeModel

File suffix:

_psfalign

The output is a CubeModel, where the 0th axis has length equal to the total number of integrations (nints x ncols x nrows). Each Image[n] in the 3D data is the n ^th PSF image aligned to the first science target integration. The file name is exposure-based, using the input science target exposure name as the root, with the addition of the association candidate ID and the “_psfalign” product type suffix, e.g. “jw8607342001_02102_00001_nrcb3_a3001_psfalign.fits.”

Reference Files

The align_refs step uses a PSFMASK reference file.

PSFMASK Reference File

REFTYPE:

PSFMASK

Data model:

PsfMaskModel

The PSFMASK reference file contains a 2-D mask that’s used as a weight function when computing shifts between images.

Reference Selection Keywords for PSFMASK

CRDS selects appropriate PSFMASK references based on the following keywords. PSFMASK is not applicable for instruments not in the table. All keywords used for file selection are required.

Instrument	Keywords
MIRI	INSTRUME, FILTER, CORONMSK, SUBARRAY, DATE-OBS, TIME-OBS
NIRCam	INSTRUME, FILTER, CORONMSK, SUBARRAY, DATE-OBS, TIME-OBS

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

Type Specific Keywords for PSFMASK

In addition to the standard reference file keywords listed above, the following keywords are required in PSFMASK reference files, because they are used as CRDS selectors (see Reference Selection Keywords for PSFMASK):

Keyword	Data Model Name
FILTER	model.meta.instrument.filter
CORONMSK	model.meta.instrument.coronagraph
SUBARRAY	model.meta.subarray.name

Reference File Format

PSFMASK reference files are FITS format, with 1 IMAGE extension. The FITS primary HDU does not contain a data array. The format and content of the file is as follows:

EXTNAME	XTENSION	NAXIS	Dimensions	Data type
SCI	IMAGE	2	ncols x nrows	float

The values in the SCI array give the mask values to be applied to the images when computing relative shifts. The mask acts as a weighting function when performing Fourier fits. The values range from zero (full weighting) to one (pixel completely masked out).