The vmmoscombine recipe

vmmoscombine

Synopsis

Combine reduced MOS observations from different OBs.

Description

This recipe is used to sum the contributes from a sequence of 2D-extracted spectral frames generated by the recipes vmmosobsstare, vmmosobsjitter, and vmmoscombine itself. The only restriction is that all frames must be obtained with the same mask. Sky subtraction, fringing correction, flat fielding, etc., are not applied, since they had been applied in the previous reduction of each input dataset.

Each input image is corrected to airmass zero before the stacking, and for this reason an atmospheric extinction table must always be specified. Optionally a correction for the instrument response can also be applied.

Input files

DO category:             Type:       Explanation:          Required:
MOS_SCIENCE_EXTRACTED    Product     Combined slit spectra     Y
GRISM_TABLE              Calib       Grism table               Y
EXTINCT_TABLE            Calib       Atmospheric extinction    Y
MOS_SPECPHOT_TABLE       Calib       Response curve            .

Output files

DO category:             Data type:  Explanation:
MOS_SCIENCE_REDUCED      FITS image  Extracted objects spectra
MOS_SCIENCE_FLUX_REDUCED FITS image  Flux calibrated objects spectra
MOS_SCIENCE_EXTRACTED    FITS image  Combined slit spectra
OBJECT_TABLE             FITS table  Objects spectra identification
WINDOW_TABLE             FITS table  Objects positions in slit

The positions of the extracted slit spectra and of the detected objects that they may contain are listed in the window table.

If a spectro-photometric table (produced by the recipe vmmosstandard) is specified and a flux calibration is requested, then a MOS_SCIENCE_FLUX_REDUCED image is also created. This image is identical to the MOS_SCIENCE_REDUCED, but the spectra it contains are flux calibrated, and expressed in units of erg/cm/cm/s/Angstrom.

For more details, please refer to the VIMOS Pipeline User’s Guide.

Constructor

cpl.Recipe("vmmoscombine")

Create an object for the recipe vmmoscombine.

import cpl
vmmoscombine = cpl.Recipe("vmmoscombine")

Parameters

vmmoscombine.param.StackMethod

Frames combination method (str; default: ‘Average’) [default=”Average”].

vmmoscombine.param.KSigmaLow

Low threshold for K-sigma clipping method. (float; default: 5.0) [default=5.0].

vmmoscombine.param.KSigmaHigh

High threshold for K-sigma clipping method. (float; default: 5.0) [default=5.0].

vmmoscombine.param.MinRejection

Number of lowest rejected values for rejection method. (long; default: 1) [default=1].

vmmoscombine.param.MaxRejection

Number of highest rejected values for rejection method. (long; default: 1) [default=1].

vmmoscombine.param.DetectionLevel

Object detection level in units of sigma. (float; default: 2.0) [default=2.0].

vmmoscombine.param.WatershedLevels

Number of levels in the watershed method in object detection. (long; default: 32) [default=32].

vmmoscombine.param.WatershedFraction

Flux fraction to use in watershed. (float; default: 0.01) [default=0.01].

vmmoscombine.param.MinObjectSize

Minimal size for an object candidate to be considered an object. (long; default: 2) [default=2].

vmmoscombine.param.MaxObjectSize

Maximal size for an object candidate for not trying deblend into sub- objects. (long; default: 7) [default=7].

vmmoscombine.param.CalibrateFlux

Extracted spectra are flux calibrated. (bool; default: False) [default=False].

The following code snippet shows the default settings for the available parameters.

import cpl
vmmoscombine = cpl.Recipe("vmmoscombine")

vmmoscombine.param.StackMethod = "Average"
vmmoscombine.param.KSigmaLow = 5.0
vmmoscombine.param.KSigmaHigh = 5.0
vmmoscombine.param.MinRejection = 1
vmmoscombine.param.MaxRejection = 1
vmmoscombine.param.DetectionLevel = 2.0
vmmoscombine.param.WatershedLevels = 32
vmmoscombine.param.WatershedFraction = 0.01
vmmoscombine.param.MinObjectSize = 2
vmmoscombine.param.MaxObjectSize = 7
vmmoscombine.param.CalibrateFlux = False

You may also set or overwrite some or all parameters by the recipe parameter param, as shown in the following example:

import cpl
vmmoscombine = cpl.Recipe("vmmoscombine")
[...]
res = vmmoscombine( ..., param = {"StackMethod":"Average", "KSigmaLow":5.0})

See also

cpl.Recipe for more information about the recipe object.

Bug reports

Please report any problems to ESO VIMOS Pipeline Team and VIMOS Consortium. Alternatively, you may send a report to the ESO User Support Department.