The extract_2d step extracts 2D arrays from spectral images. The extractions are performed within all of the SCI, ERR, and DQ arrays of the input image model, as well as any variance arrays that may be present. It also computes an array of wavelengths to attach to the extracted data. The extracted arrays are stored as one or more slit objects in an output MultiSlitModel and saved as separate tuples of extensions in the output FITS file.


This step uses the bounding_box attribute of the WCS stored in the data model, which is populated by the assign_wcs step. Hence the assign_wcs step must be applied to the science exposure before running this step.

For NIRCam and NIRISS WFSS modes, no bounding_box is attached to the data model by the assign_wcs step. This is to keep the WCS flexible enough to be used with any source catalog or similar list of objects that may be associated with the dispersed image. Instead, there is a helper method that is used to calculate the bounding boxes that contain the spectral trace for each object. One box is made for each spectral order of each object. In regular, automated processing, the extract_2d step uses the source catalog specified in the input model’s meta information to create the list of objects and their corresponding bounding box. This list is used to make the 2D cutouts from the dispersed image.

NIRCam TSGRISM exposures do not use a source catalog, so the step instead relies on the assumption that the source of interest is located at the aperture reference point and centers the extraction there. More details are given below.


This step is currently applied only to NIRSpec Fixed-Slit, NIRSpec MOS, NIRSpec TSO (BrightObj), NIRCam and NIRISS WFSS, and NIRCam TSGRISM observations.

NIRSpec Fixed Slit and MOS

If the step parameter slit_name is left unspecified, the default behavior is to extract all slits that project onto the detector. A single slit may be extracted by specifying the slit name with the slit_name argument. In the case of a NIRSpec fixed-slit exposure the allowed slit names are: “S1600A1”, “S200A1”, “S200A2”, “S200B1” and “S400A1”. For NIRSpec MOS exposures, the slit name is the slitlet number from the MSA metadata file, corresponding to the value of the “SLTNAME” keyword in FITS products, and it has to be provided as a string, e.g. slit_name=’60’.

To find out what slits are available for extraction:

>>> from jwst.assign_wcs import nirspec
>>> nirspec.get_open_slits(input_model) 

The corner locations of the regions to be extracted are determined from the bounding_box contained in the exposure’s WCS, which defines the range of valid inputs along each axis. The input coordinates are in the image frame, i.e. subarray shifts are accounted for.

The output MultiSlitModel data model will have the meta data associated with each slit region populated with the name and region characteristic for the slits, corresponding to the FITS keywords “SLTNAME”, “SLTSTRT1”, “SLTSIZE1”, “SLTSTRT2”, and “SLTSIZE2.” Keyword “DISPAXIS” (dispersion direction) will be copied from the input file to each of the output cutout images.


During normal, automated processing of WFSS grism images, the step parameter grism_objects is left unspecified, in which case the extract_2d step uses the source catalog that is specified in the input model’s meta information, input_model.meta.source_catalog.filename (“SCATFILE” keyword) to define the list of objects to be extracted. Otherwise, a user can submit a list of GrismObjects that contains information about the objects that they want extracted. The GrismObject list can be created automatically by using the method in jwst.assign_wcs.utils.create_grism_bbox. This method also uses the name of the source catalog saved in the input model’s meta information. If it’s better to construct a list of GrismObjects outside of these, the GrismObject itself can be imported from jwst.transforms.models.

The dispersion direction will be documented by copying keyword “DISPAXIS” (1 = horizontal, 2 = vertical) from the input file to the output cutout.

The wfss_mmag_extract and wfss_nbright parameters both affect which objects from a source catalog will be retained for extraction. The rejection or retention of objects proceeds as follows:

  1. As each object is read from the source catalog, they are immediately rejected if their isophotal_abmag > wfss_mmag_extract, meaning that only objects brighter than wfss_mmag_extract will be retained. The default wfss_mmag_extract value of None retains all objects.

  2. If the computed footprint (bounding box) of the spectral trace of an object lies completely outside the field of view of the grism image, it is rejected.

  3. The list of objects retained after the above two filtering steps have been applied is sorted based on isophotal_abmag (listed for each source in the source catalog) and only the brightest wfss_nbright objects are retained. The default value of wfss_nbright is currently 1000.

All remaining objects are then extracted from the grism image.

WFSS Examples

The extraction of sources from WFSS grism images is a multi-step process, as outlined above. Here we show detailed examples of how to customize the list of WFSS grism objects to be extracted, in order to better explain the various steps. First, the input file (or data model) must aleady have a WCS object assigned to it by running the assign_wcs step. The default values for the wavelength range of each spectral order to be extracted are also required; they are stored in the wavelengthrange reference file, which can be retrieved from CRDS.

Load the grism image, which is assumed to have already been processed through assign_wcs, into an ImageModel data model (used for all 2-D “images”, regardless of whether they actually contain imaging data or dispersed spectra):

>>> from stdatamodels.jwst.datamodels import ImageModel
>>> input_model = ImageModel("jw12345001001_03101_00001_nis_assign_wcs.fits")

Load the extract_2d step and retrieve the wavelengthrange reference file specific for this mode:

>>> from jwst.extract_2d import Extract2dStep
>>> step = Extract2dStep()
>>> refs = {}
>>> reftype = 'wavelengthrange'
>>> refs[reftype] = step.get_reference_file(input_model, reftype)
>>> print(refs)
{'wavelengthrange': '/crds/jwst/references/jwst_niriss_wavelengthrange_0002.asdf'}

Create a list of grism objects for a specified spectral order with a limited minimum magnitude and a specified half-height of the extraction box in the cross-dispersion direction via the wfss_extract_half_height parameter. Note that the half-height parameter only applies to point sources.

>>> from jwst.assign_wcs.util import create_grism_bbox
>>> grism_objects = create_grism_bbox(input_model, refs, mmag_extract=17,
... extract_orders=[1], wfss_extract_half_height=10)
>>> print(len(grism_objects))
>>> print(grism_objects[0])
id: 432
order_bounding {1: ((array(1113), array(1471)), (array(1389), array(1609)))}
sky_centroid: <SkyCoord (ICRS): (ra, dec) in deg
    (3.59204081, -30.40553435)>
sky_bbox_ll: <SkyCoord (ICRS): (ra, dec) in deg
    (3.59375611, -30.40286617)>
sky_bbox_lr: <SkyCoord (ICRS): (ra, dec) in deg
    (3.59520565, -30.40665425)>
sky_bbox_ur: <SkyCoord (ICRS): (ra, dec) in deg
    (3.58950974, -30.4082754)>
sky_bbox_ul:<SkyCoord (ICRS): (ra, dec) in deg
    (3.5880604, -30.40448726)>
xcentroid: 1503.6541213285695
ycentroid: 1298.2882813663837
partial_order: {1: False}
waverange: {1: (0.97, 1.32)}
is_extended: True
isophotal_abmag: 16.185488680084294

Create a list of grism objects for a specified spectral order and wavelength range. In this case we don’t use the default wavelength range limits from the wavelengthrange reference file, but instead designate custom limits via the wavelength_range parameter passed to the create_grism_bbox function, which is a dictionary of the form {spectral_order: (wave_min, wave_max)}. Use the source ID, sid, to identify the object(s) to be modified. The computed extraction limits are stored in the order_bounding attribute, which is ordered (y, x).

>>> from jwst.assign_wcs.util import create_grism_bbox
>>> grism_objects = create_grism_bbox(input_model, mmag_extract=18,
... wavelength_range={1: (3.01, 4.26)})
>>> print([obj.sid for obj in grism_objects])
[12, 26, 31, 37, 104]
>>> print(grism_objects[-1])
id: 104
order_bounding {1: ((array(1165), array(1566)), (array(1458), array(1577)))}
sky_centroid: <SkyCoord (ICRS): (ra, dec) in deg
    (3.57958792, -30.40926139)>
sky_bbox_ll: <SkyCoord (ICRS): (ra, dec) in deg
    (3.58060118, -30.40800999)>
sky_bbox_lr: <SkyCoord (ICRS): (ra, dec) in deg
    (3.58136873, -30.41001654)>
sky_bbox_ur: <SkyCoord (ICRS): (ra, dec) in deg
    (3.57866098, -30.4107869)>
sky_bbox_ul:<SkyCoord (ICRS): (ra, dec) in deg
    (3.57789348, -30.40878033)>
xcentroid: 1513.4964315117466
ycentroid: 1920.6251490007467
partial_order: {1: False}
waverange: {1: (3.01, 4.26)}
is_extended: True
isophotal_abmag: 17.88278103874113
>>> grism_object[-1].order_bounding[1] = ((1200, 1500), (1480, 1520))
>>> print(grism_object[-1].order_bounding
{1: ((1200, 1500), (1480,1520))}

The grism_objects list created in the above examples can now be used as input to the extract_2d step in order to extract the particular objects defined in that list:

>>> result =, grism_objects=grism_objects)

result is a MultiSlitModel data model, containing one SlitModel instance for each extracted object, which includes meta data that identify each object and the actual extracted data arrays, e.g.:

>>> print(len(result.slits))
>>> result.slits[0].source_id
>>> result.slits[0].data
array([[..., ..., ...]])


There is no source catalog created for TSO grism observations, because no associated direct images are obtained from which to derive such a catalog. So the extract_2d step relies on the fact that the source of interest is placed at the aperture reference point to determine the source location. The aperture reference location, in units of image x and y pixels, is read from the keywords “XREF_SCI” and “YREF_SCI” in the SCI extension header of the input image. These values are used to set the source location for all computations involving the extent of the spectral trace and pixel wavelength assignments.

NIRCam subarrays used for TSGRISM observations always have their “bottom” edge located at the physical bottom edge of the detector and vary in size vertically. The source spectrum trace will always be centered somewhere near row 34 in the vertical direction (dispersion running parallel to rows) of the dispersed image. So the larger subarrays just result in a larger region of sky above the spectrum.

For TSGRISM, extract_2d always produces a cutout that is 64 pixels in height (cross-dispersion direction), regardless of whether the original image is full-frame or subarray. This cutout height is equal to the height of the smallest available subarray (2048 x 64). This is to allow area within the cutout for sampling the background in later steps, such as extract_1d. The slit height is a parameter that a user can set (during reprocessing) to tailor their results, but the entire extent of the image in the dispersion direction (along the image x-axis) is always included in the cutout.

The dispersion direction is horizontal for this mode, and it will be documented by copying the keyword “DISPAXIS” (with value 1) from the input file to the output cutout.

Step Arguments

The extract_2d step has various optional arguments that apply to certain observation modes. For NIRSpec observations there is one applicable argument:


name [string value] of a specific slit region to extract. The default value of None will cause all known slits for the instrument mode to be extracted.

There are several arguments available for Wide-Field Slitless Spectroscopy (WFSS) and Time-Series (TSO) grism spectroscopy:


int. The cross-dispersion extraction size, in units of pixels. Only applies to TSO mode.


int. The cross-dispersion half size of the extraction region, in pixels, applied to point sources. Only applies to WFSS mode.


float (default is None). The minimum (faintest) magnitude object to extract, based on the value of isophotal_abmag in the source catalog. Only applies to WFSS mode.


int (default is 1000). The number of brightest source catalog objects to extract. Can be used in conjunction with wfss_mmag_extract. Only applies to WFSS mode.


list. The list of spectral orders to extract. The default is taken from the wavelengthrange reference file. Applies to both WFSS and TSO modes.


list (default is empty). A list of jwst.transforms.models.GrismObject.