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Spec2D Output

spec2d

Overview

During the data-reduction process, PypeIt creates a series of 2D spectral images prior to extraction of 1D spectra. And, of course, several of these 2D images may have greater value for analysis than the 1D spectra. For the extracted 1D spectra, see spec-1d-output.

For each on-source exposure, PypeIt outputs a series of these images in a single, multi-extension fits file, separated by detector; see spec2dobj_datamodel.

Naming

The 2D spectra files have names like:

spec2d_b27-J1217p3905_KASTb_2015May20T045733.560.fits

See here<science_frame_naming> for a description of the naming convention.

Inspecting

You can open this image in ds9 and play around. But we highly recommend using the pypeit_show_2dspec script which interfaces with ginga.

pypeit_show_2dspec

This script displays the sky-subtracted 2D image for a single detector in a ginga RC viewer. It also overlays the slits and any objects extracted. It should be called from the reduction directory, i.e. above the Science/ folder where the spec2d image is located.

The script usage can be displayed by calling the script with the -h option:

Here is a typical call:

pypeit_show_2dspec Science/spec2d_c17_60L._LRISb_2017Mar20T055336.211.fits

This opens 4 tabs in the ginga display, one for each of the following:

  • Procesed image (sciimg-det##)
  • Sky subtracted image (skysub-det##)
  • Sky residual image (sky_resid-det##)
  • Full residual image which removes the object too (resid-det##)

Red/green lines indicate slit edges. Orange lines (if present) indicate traces for detected objects. Light blue lines (if present) indicate traces for manually extracted objects.

As you mouse around, the x-values shown at the bottom indicate the wavelength.

Warning

If you get an obscure error when executing the above command, it may be that you're trying to view a file created by a previous version of PypeIt. As the code develops, we sometimes change the datamodel of different output files, which are often not backwards compatible. If you run into this error, try reverting to the relevant PypeIt version (the version used to create the file is typically written to the VERSPYP header keyword) or re-reduce the data with the new PypeIt version.

pypeit_parse_slits

This script prints to the screen a short summary of the slit information, detector by detector.

The script usage can be displayed by calling the script with the -h option:

See pypeit_parse_slits for more info.

pypeit_chk_wavecalib

This script prints to the screen a set of simple wavelength calibration diagnostics per each slit, detector by detector.

The script usage can be displayed by calling the script with the -h option:

See pypeit-chk-wavecalib for more info.

Identifying Slits

If you need to generate an image describing the location of each slit/order for a given detector here is the recommended approach:

from pypeit import spec2dobj
spec2DObj = spec2dobj.Spec2DObj.from_file('spec2d_b170320_2083-c17_60L._LRISb_2017Mar20T055336.211.fits', det=2)
slitmask = spec2DObj.slits.slit_img(flexure=spec2DObj.sci_spat_flexure)

If no flexure correction was applied, it will be ignored. This generates an image with pixel values:

  • -1 for a pixel not in any slit/order
  • SPAT_ID for each pixel in the slit identified by SPAT_ID

Current Spec2DObj Data Model

Internally, the image is held in ~pypeit.spec2dobj.AllSpec2DObj, which holds the full set of ~pypeit.spec2dobj.Spec2DObj objects.

All wavelengths are in vacuum.

The data model for the latter is:

Each array and the associated ~pypeit.images.detector_container.DetectorContainer is written as a separate HDU prefixed by the detector number, DET01-.

For a description of how to use the bitmasks (i.e., the *BPMMASK extensions), see our description of the out_masks.