Shift a target spectrum onto a reference spectrum.

specmatchemp.shift.bootstrap_shift(targ, ref_list, store=None)

Shift a target spectrum using a bootstrapping approach.

First performs a cross-correlation of the target spectrum in a fixed wavelength region against each of the provided references. The reference spectrum which gives the highest median cross-correlation peak is used to shift the rest of the target spectrum.

  • targ (spectrum.Spectrum) – Target spectrum
  • ref_list (list of spectrum.Spectrum) – List of reference spectra
  • store (dict-like object, optional) – h5 file or dict to record diagnostic data.

Shifted and flattened spectrum.

Return type:

shifted (Spectrum)

specmatchemp.shift.correlate(a, v, lowfilter=0)

Custom function to perform 1-dimensional cross-correlation

  • a (np.ndarray) – Input sequence
  • v (np.ndarray) – Input sequence
  • lowfilter (int) – Filter out components with wavelength above this number of pixels

Symmetric cross-correlation array

Return type:


specmatchemp.shift.flatten(w, s, serr=None, mask=None, w_ref=None, wavlim=None)

Flattens a given 2-D spectrum into a 1-D array. Merges overlapped points by taking the mean. If w_ref is given, fills values that don’t occur in the 2D spectrum with np.nan

  • w (np.ndarray) – Wavelength array
  • s (np.ndarray) – Spectrum
  • serr (np.ndarray, optional) – Uncertainty in spectrum
  • mask (np.ndarray, optional) – Boolean mask
  • w_ref (np.nadarray, optional) – Reference, 1-D wavelength array
  • wavlim (2-element iterable, optional) – Wavelength limits

Wavelength, spectrum and uncertainty in spectrum

Return type:

w, s, serr

specmatchemp.shift.rescale_w(s, serr, w, m, w_ref)

Place the given spectrum on the wavelength scale specified by w_ref

  • serr, w (s,) – The spectrum and original wavelength scale.
  • w_ref – The desired wavelength scale

The spectrum and associated error on the desired scale.

specmatchemp.shift.save_shift_to_fits(outpath, shifted, unshifted, shift_data, clobber=False)

Saves the complete shift data to a FITS file.

  • outpath (str) – Path to save output file
  • shifted (Spectrum) – Shifted spectrum
  • unshifted (HiresSpectrum) – Raw spectrum
  • shift_data (dict) – Shift data
  • clobber (bool) – Overwrite existing file at destination
specmatchemp.shift.shift(targ, ref, store=None, lowfilter=20)

Shifts the given spectrum by placing it on the same wavelength scale as the specified reference spectrum, then solves for shifts between the two spectra through cross-correlation.

  • targ (Spectrum) – Target spectrum
  • ref (Spectrum) – Reference spectrum
  • store (optional [file or dict]) – h5 file or dict to record diagnostic data.

Adjusted and flattened spectrum

Return type:

shifted (Spectrum)


Saves the shift data to a BinTableHDU.

Parameters:shift_data (dict) – Shift data output from shift()
specmatchemp.shift.solve_for_shifts(s, mask, s_ref, mask_ref, lowfilter=20)

Solve for the pixel shifts required to align two spectra that are on the same wavelength scale.

Correlates the two spectra, then fits a quadratic to the peak in order to solve for sub-pixel shifts.

  • s – The target spectrum array
  • mask – Mask array for the target spectrum
  • s_ref – The reference spectrum
  • mask_ref – Mask array for the reference spectrum

The pixel shift, the lag and correlation data