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stellar_long_slit

Long-slit stellar reduction from a raw 2-D frame with an arc lamp: geometric rectification, hot-pixel rejection, sky subtraction on both sides of the trace, aperture extraction, polynomial wavelength solution from the lamp identifications, continuum normalisation and BeSS export.
Kind reduction
Status draft - draft: conventions still open for discussion
Version 1.0.0
Source package:spectro-kernel-recipes
Requires spectro-kernel >=0.7

Conventions

Sky fitted column by column on 10-row bands 4 rows away from the trace; aperture of +/- 6 rows; 3rd-order dispersion solution; continuum normalised on 6400-6500 Angstrom. Lamp identifications come from match_lamp_lines or reidentify_arc_features run on the lamp frame with the same geometry.

References

  • Howell 2006, Handbook of CCD Astronomy, 2nd ed., ch. 5 - long-slit reduction
  • Horne 1986, PASP 98, 609 - sky estimate from the rows flanking the trace
  • Tody 1986, Proc. SPIE 627, 733 - IRAF identify / dispcor

Variables

The instrument- or observer-dependent values. Provide them with a profile file, --set name=value, or variables={...} in Python.

Variable Type Required / default Description
tilt_deg float default 0.0
slant_deg float default 0.0
smile_radius float default 0.0
reference_row int required row of the stellar trace
lamp_pixels list required pixel_positions from match_lamp_lines
lamp_wavelengths list required wavelengths_angstrom from match_lamp_lines
object_name str required
instrument str required
observer str required
site str required
date_obs_utc str required ISO-8601 start of exposure (UTC)
exposure_seconds float required

Steps

# Algorithm Parameters
1 correct_tilt_affine tilt_deg='${tilt_deg}'
2 correct_slant_affine slant_deg='${slant_deg}', pivot_row='${reference_row}'
3 correct_smile_polynomial reference_row='${reference_row}', smile_radius='${smile_radius}', polynomial_order=4
4 outlier_rejection_mad_adaptive kernel_size=3, threshold=3.0
5 subtract_sky_2d trace_row='${reference_row}', trace_half_width=6, sky_offset=4, sky_half_width=10
6 extract_spectrum_sum dispersion_axis=1, half_width=6
7 wavelength_calibrate_polynomial pixel_positions='${lamp_pixels}', wavelengths_angstrom='${lamp_wavelengths}', order=3
8 normalize_to_region wave_lo=6400.0, wave_hi=6500.0
9 export_fits_bess object_name='${object_name}', instrument='${instrument}', site='${site}', observer='${observer}', date_obs_utc='${date_obs_utc}', exposure_seconds='${exposure_seconds}', vhelio_kms=0.0

Run it

# profile.yaml holds your instrument values:
#   tilt_deg: 0.0
#   slant_deg: 0.0
#   smile_radius: 0.0
#   reference_row: 0
#   lamp_pixels: []
#   lamp_wavelengths: []
#   object_name: <object_name>
#   instrument: <instrument>
#   observer: <observer>
#   site: <site>
#   date_obs_utc: <date_obs_utc>
#   exposure_seconds: 0.0
spectro pipeline stellar_long_slit --input spectrum.fits --profile profile.yaml
spectro preset show stellar_long_slit      # variables and steps

from spectro_kernel import WorkContext
from spectro_kernel.pipeline import PipelineBuilder

variables = {"tilt_deg": 0.0, "slant_deg": 0.0, "smile_radius": 0.0, "reference_row": 0, "lamp_pixels": [], "lamp_wavelengths": [], "object_name": "<object_name>", "instrument": "<instrument>", "observer": "<observer>", "site": "<site>", "date_obs_utc": "<date_obs_utc>", "exposure_seconds": 0.0}
pipeline = PipelineBuilder().from_preset("stellar_long_slit", variables).build()
result = pipeline.execute(ctx)        # ctx holds the spectrum / frames
print(result.history[-1])             # pipeline:<name> vX.Y.Z + variables

{
  "tool": "run_preset",
  "arguments": {
    "session_id": "<session_id>",
    "preset_name": "stellar_long_slit",
    "variables": {
      "tilt_deg": 0.0,
      "slant_deg": 0.0,
      "smile_radius": 0.0,
      "reference_row": 0,
      "lamp_pixels": [],
      "lamp_wavelengths": [],
      "object_name": "<object_name>",
      "instrument": "<instrument>",
      "observer": "<observer>",
      "site": "<site>",
      "date_obs_utc": "<date_obs_utc>",
      "exposure_seconds": 0.0
    }
  }
}