Get started

Get started#

excalibuhr is an end-to-end pipeline for extracting high-resolution spectra designed for VLT/CRIRES+. The organization of the reduction folder is on a nightly basis. Multiple targets (such as the telluric standard star) observed in the same night can be processed altogether. Within the folder of individual night, there are the raw, cal, and out folders containing the raw observation and calibration files, the processed calibratoion files, and the processed science data, respectively.

Initialize pipeline#

To begin with, let’s initialize the pipeline with the working directory and the observing night.

from excalibuhr import pipeline

workpath = './'
night = '2023-06-06'

ppl = pipeline.CriresPipeline(
                              workpath, night=night, obs_mode='nod',
                              num_processes=4, clean_start=False
                             )

The num_processes sets the number of parallel processes when reducing science frames. The clean_start gives the option to remove all previous products in case one needs to re-run the pipeline.

Download data#

Then download the raw science data and associated calibration data from ESO Science Archive , and put them all to the raw folder inside the night folder.

Alternatively, the pipeline also has a method for downloading the data using the astroquery package.

username = 'yzhang' #your ESO username
program_id = '107.22TG'

ppl.download_rawdata_eso(login=username, prog_id=program_id)

Run pipeline#

The main steps in the pipeline include organizing raw data, pre-processing (such as dark correction, flat fielding, order tracing, slit-tilt tracing, and background subtraction), spectrum extraction, post-processing (such as wavelength calibration, telluric correction), and saving the output data. It also generates standard plots for visual checks of the results.

To run the whole chain of recipes in the pipeline:

ppl.run_recipes(combine=True)

The combine parameter sets whether combining all frames at each nodding position or processing each individual frame to keep the time resolusion.

This function essentially runs the following recipes:

ppl.extract_header()
ppl.cal_dark()
ppl.cal_flat_raw()
ppl.cal_flat_trace()
ppl.cal_slit_curve()
ppl.cal_flat_norm()
ppl.obs_nodding()
ppl.obs_nodding_combine() #optional
ppl.obs_extract()
ppl.refine_wlen_solution()

If you need more customized reduction, please find the individual recipes explained in the API reference of CriresPipeline class.

Note

  • To extract spectra of spatially resolved planetary companions with the obs_extract recipe, one can either set the companion_sep parameter to the angular separation of the planet in arcseconds or provide the location on the slit with e.g. peak_frac={'A':0.3, 'B':0.8}. These values don’t have to very accurate.

  • If telluric standard stars have been observed during the night, we can use it for the refinement of wavelength solution and instrumental response calibration. In the run_recipes method, specify the std_prop as a dictionary containing the name, teff, vsini, and rv of the standard star.

  • The pipeline can also call Molecfit to correct for telluric absorptions if setting run_molecfit=True.

Access the intermediate data product#

The calibrated 2-dimensional images is save to .npz files and can be simply loaded with the following code for dedicated analysis on off-axis spectral data.

from excalibuhr.data import DETECTOR

extr2d = DETECTOR(filename='the_2d_product_file.npz')

flux2d = extr2d.flux
variance2d = extr2d.var
psf2d = extr2d.psf

# These nested list contains the 2d images per detector and order.
# The shape is (detector x order x spacial pixels x spectral channels).
Contents