The UVES 6.1.8 pipeline

These pages describe the python interface for the UVES pipeline recipes.

Standard recipes

flames_cal_mkmaster

Creates a master flat frame to support FIBER mode data reduction

flames_cal_orderpos

Defines uves-echelle-simultaneous calibration fibre order positions

flames_cal_predict

Implements the UVES physical model

flames_cal_prep_sff_ofpos

Determines order and fibre postions

flames_cal_wavecal

Performs the wavelength calibration

flames_obs_scired

Reduces a FLAMES science image

uves_cal_cd_align

Measures the reproducability of the cross disperser positioning

uves_cal_mdark

Creates the master dark frame

uves_cal_mkmaster

Creates the master bias/dark/flat frame

uves_cal_orderpos

Defines echelle order positions

uves_cal_predict

Implements the UVES physical model

uves_cal_response

Determines response function and quantum efficiency

uves_cal_tflat

Reduces a TFLAT frame

uves_cal_wavecal

Performs the wavelength calibration

uves_obs_scired

Reduces a science frame

Additional recipes

flames_obs_redchain

Runs the full UVES-FIBRE reduction chain

flames_utl_unpack

Unpack flames-uves packed frames

uves_cal_mbias

Creates the master bias frame

uves_cal_mflat

Creates the master flat field frame

uves_cal_mflat_combine

Combines the master flat field and the master dflat frames

uves_obs_redchain

Runs the full UVES reduction chain

uves_utl_ima_arith

Computes result of ima1 op ima2

uves_utl_remove_crh_single

Remove CRHs from an image

See also

• The UVES Pipeline User Manual in PDF format,

• an overview over the existing ESO pipelines,

• the python-cpl package.

Bug reports

If you experience an unexpected behavior of any component of the UVES pipeline recipes package, please, first refer to the list of known problems and limitations in the pipeline manual of the current UVES pipeline release.

For any other issues or requests, please, send a report to the ESO User Support Department, describing:

• the UVES pipeline version,

• the version of your OS and C compiler,

• the exact sequence of actions that were performed before the problem occurred,

• what were precisely the symptoms and the possible error message(s),

• whether the problem is repeatable.