WaveCalib

Overview

This file describes the data model for the WaveCalib.

The images are written to disk as a multi-extension FITS file prefixed by WaveCalib in the Calibrations/ folder. See Calibration Frame Naming for the naming convention.

Inspecting

pypeit_chk_wavecalib

You can print a set of simple diagnostics to the screen with the pypeit_chk_wavecalib script, e.g. :

$ pypeit_chk_wavecalib Calibrations/WaveCalib_A_1_MSC03.fits

 N. SpatID minWave Wave_cen maxWave dWave Nlin     IDs_Wave_range    IDs_Wave_cov(%) measured_fwhm  RMS
--- ------ ------- -------- ------- ----- ---- --------------------- --------------- ------------- -----
  0     35  6422.5   7753.8  9053.2 0.325   48  6508.325 -  9047.930            96.5           3.5 0.046
  1     93  6310.0   7641.4  8940.8 0.325   49  6336.179 -  8931.145            98.6           3.6 0.036
  2    140  6440.8   7772.1  9071.5 0.325   47  6508.325 -  9047.930            96.5           3.6 0.049
  3    184  6301.2   7632.6  8932.0 0.325   50  6306.533 -  8931.145            99.8           3.6 0.037
  4    243  6257.1   7588.5  8887.9 0.325   49  6268.229 -  8821.832            97.1           3.6 0.034
  • SpatID is the spatial position of the slit/order.

  • minWave, maxWave, Wave_cen, dWave are, respectively, the minimum wavelength value, the maximum wavelength value, the central wavelength, and the wavelength dispersion of the calibrated arc spectra. All the values are in Angstrom.

  • Nlin, IDs_Wave_range, IDs_Wave_cov(%) are, respectively, the number, the wavelength range, and the spectral coverage of the identified and fitted arc lines.

  • measured_fwhm is the measured arc lines FWHM (in binned pixels of the input arc frame), i.e, the approximate spectral resolution. Note that this not necessarily the fwhm used to identify the arc lines during the wavelength calibration, see FWHM.

  • RMS is the RMS of the wavelength solution (in pixels).

PNGs

At present, the only way to visually examine the quality of this step is by viewing the PNG file generated by the code. PypeIt QA describes how to access them.

There is 1 PNG file generated per slit. Here is an example from the shane_kast_red spectrograph.

../_images/arc_1d_fit.png

What you hope to see in your QA is:

  • On the left, many of the blue arc lines marked with IDs

  • In the upper right, an RMS < 0.1 pixels

  • In the lower right, a random scatter about 0 residuals

Troubleshooting

Wavelength solutions are amongst the most challenging part of data reduction. See Wavelength Calibration for extensive details on how PypeIt performs wavelength calibration and related issues.

Current WaveCalib Data Model

Internally, the image is held in pypeit.wavecalib.WaveCalib which subclasses from pypeit.datamodel.DataContainer.

The datamodel written to disk is:

Version 1.1.2

HDU Name

HDU Type

Data Type

Description

PRIMARY

astropy.io.fits.PrimaryHDU

Empty data HDU. Contains basic header information.

SPAT_IDS

astropy.io.fits.ImageHDU

integer

Slit spat_ids. Named distinctly from that in WaveFit

SPAT_ID-?__WAVEFIT

astropy.io.fits.BinTableHDU

WaveFit result for slit_id=?

SPAT_ID-?__PYPEITFIT

astropy.io.fits.BinTableHDU

PypeItFit element of the WaveFit datamodel for slit_id=?

ARC_SPECTRA

astropy.io.fits.ImageHDU

floating

2D array: 1D extracted spectra, slit by slit (nspec, nslits)