Examples of How to Run Cube_Build ================================= It is assumed that the input data have been processed through the calwebb_detector1 pipeline and up through the photom step of the calwebb_spec2 pipeline.

Cube Building for MIRI data

To run cube_build on a single MIRI exposure (containing channel 1 and 2), but only creating an IFU cube for channel 1:

strun jwst.cube_build.CubeBuildStep MIRM103-Q0-SHORT_495_cal.fits --ch=1

The output 3D spectral cube will be saved in a file called MIRM103-Q0-SHORT_495_ch1-short_s3d.fits

To run cube_build using an association table containing 4 dithered images:

strun jwst.cube_build.CubeBuildStep cube_build_4dither_asn.json

where the ASN file cube_build_4dither_asn.json contains:

{"asn_rule": "Asn_MIRIFU_Dither",
 "target": "MYTarget",
 "asn_id": "c3001",
 "asn_pool": "jw00024_001_01_pool",
 "program": "00024","asn_type":"dither",
 "products": [
             {"name": "MIRM103-Q0-Q3",
              [{"exptype": "SCIENCE", "expname": "MIRM103-Q0-SHORT_495_cal.fits"},
               {"exptype": "SCIENCE", "expname": "MIRM103-Q1-SHORT_495_cal.fits"},
               {"exptype": "SCIENCE", "expname": "MIRM103-Q2-SHORT_495_cal.fits"},
               {"exptype": "SCIENCE", "expname": "MIRM103-Q3-SHORT_495_cal.fits"}]}

The default output will be two IFU cubes. The first will contain the combined dithered images for channel 1, sub-channel SHORT and the second will contain the channel 2, sub-channel SHORT data. The output root file names are defined by the product “name” attribute in the association table and results in files MIRM103-Q0-Q3_ch1-short_s3d.fits and MIRM103-Q0-Q3_ch2-short_s3d.fits.

To use the same association table, but combine all the data, use the output_type=multi option:

strun jwst.cube_build.CubeBuildStep cube_build_4dither_asn.json --output_type=multi

The output IFU cube file will be MIRM103-Q0-Q3_ch1-2-short_s3d.fits

Cube building for NIRSpec data

To run cube_build on a single NIRSpec exposure that uses grating G140H and filter F100LP:

strun jwst.cube_build.CubeBuildStep jwtest1004001_01101_00001_nrs2_cal.fits

The output file will be jwtest1004001_01101_00001_nrs2_g140h-f100lp_s3d.fits

To run cube_build using an association table containing data from exposures using G140H+F100LP and G140H+F070LP:

strun jwst.cube_build.CubeBuildStep nirspec_multi_asn.json

where the association file contains:

{"asn_rule": "Asn_NIRSPECFU_Dither",
 "target": "MYTarget",
 "asn_pool": "jw00024_001_01_pool",
 "program": "00024","asn_type":"NRSIFU",
 "products": [
 {"name": "JW3-6-NIRSPEC",
 [{"exptype": "SCIENCE", "expname": "jwtest1003001_01101_00001_nrs1_cal.fits"},
 {"exptype": "SCIENCE", "expname": "jwtest1004001_01101_00001_nrs2_cal.fits"},
 {"exptype": "SCIENCE", "expname": "jwtest1005001_01101_00001_nrs1_cal.fits"},
 {"exptype": "SCIENCE", "expname": "jwtest1006001_01101_00001_nrs2_cal.fits"}]}

The output will be two IFU cubes, one for each grating+filter combination: JW3-6-NIRSPEC_g140h-f070lp_s3d.fits and JW3-6-NIRSPEC_g140h-f100lp_s3d.fits.