pypeit.core.wavecal.templates module

Module to generate templates for the PypeIt full_template wavelength calibration routine

This function uses direct access to the path attribute in the relevant pypeit data paths. This should not be replicated in other parts of the code. This templates.py script is a developer only script, and it really shouldn’t be distributed as part of the code base.

pypeit.core.wavecal.templates.build_template(in_files, slits, wv_cuts, binspec, outroot, outdir=None, normalize=False, subtract_conti=False, wvspec=None, lowredux=False, ifiles=None, det_cut=None, chk=False, miny=None, overwrite=True, ascii_tbl=False, in_vac=True, shift_wave=False, binning=None, micron=False, reid_files: bool = False)[source]

Generate a full_template for a given instrument

Parameters:

  • in_files (list or str) – Wavelength solution files, XIDL or PypeIt If PypeIt, they can be a mix of WaveCalib JSON and FITS files

  • slits (list) – Slits in the archive files to use

  • wv_cuts (list) – Wavelengths to cut each slit at. The elements of the list correspond to the wavelengths where two spectra are stitched together.

  • binspec (int) – Spectral binning of the archived spectrum

  • outroot (str) – Name of output archive

  • outdir (str) – Name of output directory

  • lowredux (bool, optional) – If true, in_files are from LowRedux

  • reid_files (bool, optional) – If True, in_files are reid_arxiv files

  • wvspec (ndarray, optional) – Manually input the wavelength values

  • ifiles (list, optional) – Ordering of the in_files. Default is np.arange(len(in_files))

  • det_cut (dict, optional) – Cut the detector into pieces. Important for long detectors with wavelengths on one side

  • chk (bool, optional) – Show a plot or two

  • miny (float) – Impose a minimum value

  • normalize (bool, optional) – If provided multiple in_files, normalize each snippet to have the same maximum amplitude.

  • subtract_conti (bool, optional) – Subtract the continuum for the final archive

  • ascii_tbl (bool, optional) – Table is a simple ASCII 2 column wave,flux table

  • in_vac (bool, optional) – True if input wavelengths are in vacuum

  • shift_wave (bool, optional) – Shift wavelengths when splicing to sync up precisely (Recommended) Requires PypeIt file (old JSON works for now)

  • binning (list, optional) – Allows for multiple binnings for input files

  • micron (bool, optional) – If True, assume the in_files archive has a solution in microns, so convert this to Angstroms which is the PypeIt convention. Default=False

pypeit.core.wavecal.templates.cheby_val(coeff, x, nrm, order)[source]
pypeit.core.wavecal.templates.fcheby(xnrm, order)[source]
pypeit.core.wavecal.templates.grab_wvlim(kk, wv_cuts, nslits)[source]

Set the wavelength range to cut on

Parameters:
Returns:

wv_min, wv_max (float, float)

Return type:

tuple

pypeit.core.wavecal.templates.main(flg)[source]
pypeit.core.wavecal.templates.poly_val(coeff, x, nrm)[source]

IDL style function for polynomial

Parameters:
Returns:

Same shape as x

Return type:

numpy.ndarray

pypeit.core.wavecal.templates.pypeit_arcspec(in_file, slit, binspec, binning=None)[source]

Load up the arc spectrum from an input JSON file

Parameters:

  • in_file (str or pathlib.Path) – File containing the arc spectrum and or fit

  • slit (int) – slit index

Returns:

numpy.ndarray, numpy.ndarray, PypeItFit: wave, flux, pypeitFitting

Return type:

tuple

pypeit.core.wavecal.templates.pypeit_identify_record(iwv_calib, binspec, specname, gratname, dispangl, outdir=None)[source]

From within PypeIt, generate a template file if the user manually identifies an arc spectrum

Parameters:

  • iwv_calib (dict) – Wavelength calibration returned by final_fit

  • binspec (int) – Spectral binning

  • specname (str) – Name of instrument

  • gratname (str) – Name of grating

  • dispangl (str) – Dispersion angle

  • outdir (str, None) – Output directory

pypeit.core.wavecal.templates.read_ascii(tbl_file, in_vac=True)[source]

The columns need to be wave, flux And the data should be monoonically increasing in wavelength

Parameters:

  • tbl_file (str) – file of the table

  • in_vac (bool, optional) – If True, wavelenghts are already in vacuum

Returns:

np.ndarray, np.ndarray of wavelength, flux

Return type:

tuple

pypeit.core.wavecal.templates.read_reid(reid_file: str)[source]
pypeit.core.wavecal.templates.xidl_arcspec(xidl_file, slit)[source]

Read an XIDL format solution for a Longslit

Note: These are in air

Parameters:

  • xidl_file (str) – XIDL file

  • slit (int) – The slit in question.

Returns:

  • wave (np.ndarray) – Wavelengths in vacuum for that slit

  • spec (np.ndarray) – Arc spectrum for that slit

pypeit.core.wavecal.templates.xidl_esihires(xidl_file, specbin=1, order_vec=None, log10=True)[source]

Read an XIDL format solution for Keck/HIRES or Keck/ESI

Note: They used air

Parameters:

xidl_file (str) – Keck/HIRES save file

Returns:

np.ndarray, np.ndarray, np.ndarray of orders, wavelength, flux

Return type:

tuple