3.2.3. optimalExtraction

Optimal extraction of the 2d echelle spectrum.

This function performs an optimal extraction of a 2d echelle spectrum. The internal flat spectrum extension is used to generate normalized ‘profiles’ that are used as weighting functions for the spectrum that is going to be extracted. The algorithm further checks for outliers and rejects them. This is to prevent contributions from cosmic hits.

3.2.3.1. Parameters

adinputslist of AstroData

Frames with STRIPES, F_STRIPES, and STRIPES_MASKS extensions as dicts of sparse arrays.

suffixstr

Suffix to be added to output files.

darkstr or AstroData, optional

Processed dark frame. If None, queries the calibration database.

optimal_extraction_fiberslist of int, optional

Fiber numbers (1-5) for optimal extraction. Fibers considered for optimal extraction.

back_varfloat, optional

Manual background variance for frame.

full_outputbool

If True, an additional set of intermediate products will be returned / saved.

penaltyfloat

Scaling penalty factor for mismatch correction between flat field profile and science spectrum during optimal extraction.

s_clipfloat

Sigma-clipping parameter during optimal extraction.

read_noisefloat

Read noise (e-). MX default is 1.14.

gainfloat

Detector gain (e-/ADU). MX default is 2.72.

3.2.3.2. Returns

list of AstroData

Input frames with optimal and box extracted orders for each fiber together with uncertainties and the bad pixel mask result from the optimal extraction. Extensions added, one per fiber N in 1-5:

  • REDUCED_ORDERS_FIBER_N

  • OPTIMAL_REDUCED_FIBER_N

  • OPTIMAL_REDUCED_VAR_N

  • BOX_REDUCED_FIBER_N

  • BOX_REDUCED_VAR_N

  • BOX_REDUCED_FLAT_N

  • BPM_FIBER_N

3.2.3.3. Parameter defaults and options

suffix               ''                   Filename suffix
dark                 None                 Processed dark
optimal_extraction_fibers None                 Fiber numbers (1-5) for optimal extraction
full_output          False                More outputs made
penalty              2.0                  scaling penalty factor
s_clip               5.0                  sigma-clipping factor
back_var             0.0                  background variance
read_noise           1.14                 read noise
gain                 2.72                 gain

3.2.3.4. Algorithm

Todo

add description

3.2.3.5. Issues and Limitations

Todo

add description