The giscience recipe¶
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giscience
¶
Synopsis¶
Process a science observation.
Description¶
For detailed information please refer to the GIRAFFE pipeline user manual.
It is available at http://www.eso.org/pipelines.
Constructor¶
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cpl.
Recipe
("giscience") Create an object for the recipe giscience.
import cpl
giscience = cpl.Recipe("giscience")
Parameters¶
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giscience.param.
remove_bias
¶ Enable bias removal (bool; default: True) [default=True].
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giscience.param.
bsremove_method
¶ Bias removal method (str; default: ‘PROFILE’) [default=”PROFILE”].
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giscience.param.
bsremove_areas
¶ Bias areas to use (Xl0:Xr0:Yl0:Yr0, … ,Xln:Xrn:Yln:Yrn) (str; default: ‘5:40:0:4095’) [default=”5:40:0:4095”].
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giscience.param.
bsremove_sigma
¶ Sigma Clipping: sigma threshold factor (float; default: 2.5) [default=2.5].
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giscience.param.
bsremove_niter
¶ Sigma Clipping: maximum number of iterations (int; default: 5) [default=5].
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giscience.param.
bsremove_mfrac
¶ Sigma Clipping: minimum fraction of points accepted/total [0.0..1.0] (float; default: 0.8) [default=0.8].
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giscience.param.
bsremove_xorder
¶ Order of X polynomial fit (CURVE method only) (int; default: 1) [default=1].
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giscience.param.
bsremove_yorder
¶ Order of Y polynomial fit (CURVE method only) (int; default: 1) [default=1].
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giscience.param.
bsremove_xstep
¶ Sampling step along X (CURVE method only) (int; default: 1) [default=1].
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giscience.param.
bsremove_ystep
¶ Sampling step along Y (CURVE method only) (int; default: 1) [default=1].
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giscience.param.
extr_method
¶ Extraction method: ‘SUM’, ‘HORNE’ or ‘OPTIMAL’ (str; default: ‘SUM’) [default=”SUM”].
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giscience.param.
extr_ron
¶ New bias sigma (RON) value for bias and dark corrected image (float; default: -1.0) [default=-1.0].
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giscience.param.
extr_psfmodel
¶ PSF profile model: `psfexp’, `psfexp2’ (str; default: ‘psfexp2’) [default=”psfexp2”].
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giscience.param.
extr_psfsigma
¶ Sigma clippging threshold used for rejecting data points during PSF fitting (Horne’s sigma). It is used to reject bad pixels and cosmics. (float; default: 7.0) [default=7.0].
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giscience.param.
extr_psfniter
¶ Maximum number of iterations used for fitting the PSF profile. (int; default: 2) [default=2].
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giscience.param.
extr_hewidth
¶ Horne extraction method: Number of extra pixels added to the fiber half-width. (int; default: 2) [default=2].
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giscience.param.
extr_hmingood
¶ Horne extraction method: Minimum number of points used for the profile fit. It sets the lower limit of data points for the pixel rejection. (int; default: 3) [default=3].
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giscience.param.
extr_omfrac
¶ Optimal extraction method: Minimum fraction of the data points used for fitting the fiber profiles. It sets the lower limit for the pixel rejection. (float; default: 0.9) [default=0.9].
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giscience.param.
extr_owfactor
¶ Optimal extraction method: Factor by which the fiber PSF half width is multiplied. Adjacent spectra within this area are assumed to affect the spectrum being extracted. (float; default: 3.0) [default=3.0].
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giscience.param.
extr_obkgorder
¶ Optimal extraction method: Order of the polynomial background model, which is fitted for each wavelength bin along the spatial direction. (int; default: 2) [default=2].
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giscience.param.
flat_apply
¶ Controls the flat field correction. (bool; default: True) [default=True].
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giscience.param.
transmission_apply
¶ Controls the fiber to fiber transmission correction. (bool; default: False) [default=False].
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giscience.param.
rbin_method
¶ Method to use : `linear’ or `spline’ (str; default: ‘linear’) [default=”linear”].
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giscience.param.
rbin_xresid
¶ Use x residuals during rebinning? `true’/`false’ (bool; default: True) [default=True].
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giscience.param.
rbin_lstep
¶ Lambda step size, only used if scaling method is ‘linear’ (float; default: 0.005) [default=0.005].
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giscience.param.
rbin_scmethod
¶ Scaling method: `log’ or `linear’ (str; default: ‘linear’) [default=”linear”].
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giscience.param.
rbin_size
¶ Size of output rebinned spectra, 0 means calculate size based on wavelength range and lambda stepsize (int; default: 0) [default=0].
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giscience.param.
rbin_range
¶ Rebinning range: `setup’ or `common’ (str; default: ‘setup’) [default=”setup”].
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giscience.param.
siwc_apply
¶ Enable simultaneous wavelength calibration correction. (bool; default: True) [default=True].
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giscience.param.
scal_cniter
¶ Slit geometry calibration maximum number of iterations. (int; default: 1) [default=1].
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giscience.param.
scal_zmax
¶ Maximum allowed pixel value. To be effective it must be larger than 0. (float; default: 10000.0) [default=10000.0].
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giscience.param.
scal_cstep
¶ Cross-correlation step. (float; default: -0.005) [default=-0.005].
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giscience.param.
scal_cdomain
¶ Restricts the cross-correlation to the given domain. (str; default: ‘0.,0.’) [default=”0.,0.”].
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giscience.param.
scal_rvlimits
¶ Delta RV limits of the cross-correlation window in km/s. (str; default: ‘-200.,200.’) [default=”-200.,200.”].
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giscience.param.
scal_rvniter
¶ Maximum number of iterations used for the RV determination. (int; default: 3) [default=3].
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giscience.param.
scal_rvwfactor
¶ Data window width factor. The FWHM times this value determines the window width. (float; default: 1.5) [default=1.5].
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giscience.param.
scal_pfniter
¶ Peak model fit maximum number of iterations. (int; default: 50) [default=50].
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giscience.param.
scal_pfntest
¶ Cross-correlation peak fit maximum number of tests (int; default: 7) [default=7].
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giscience.param.
scal_pfdchisq
¶ Cross-correlation peak fit minimum chi-square difference. (float; default: 0.0001) [default=0.0001].
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giscience.param.
recon_min
¶ Minimum wavelength for image reconstruction (float; default: 0.0) [default=0.0].
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giscience.param.
recon_max
¶ Maximum wavelength for image reconstruction (float; default: 0.0) [default=0.0].
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giscience.param.
recon_cube
¶ Turns data cube creation on and off (bool; default: True) [default=True].
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giscience.param.
recon_format
¶ Selects the file format for cubes (str; default: ‘single’) [default=”single”].
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giscience.param.
generate_SDP_format
¶ TRUE if additional files should be generated in Science Data Product (SDP) format. (bool; default: False) [default=False].
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giscience.param.
dummy_association_keys
¶ Sets the number of dummy (empty) ASSONi, ASSOCi and ASSOMi keywords to create. (int; default: 0) [default=0].
The following code snippet shows the default settings for the available parameters.
import cpl
giscience = cpl.Recipe("giscience")
giscience.param.remove_bias = True
giscience.param.bsremove_method = "PROFILE"
giscience.param.bsremove_areas = "5:40:0:4095"
giscience.param.bsremove_sigma = 2.5
giscience.param.bsremove_niter = 5
giscience.param.bsremove_mfrac = 0.8
giscience.param.bsremove_xorder = 1
giscience.param.bsremove_yorder = 1
giscience.param.bsremove_xstep = 1
giscience.param.bsremove_ystep = 1
giscience.param.extr_method = "SUM"
giscience.param.extr_ron = -1.0
giscience.param.extr_psfmodel = "psfexp2"
giscience.param.extr_psfsigma = 7.0
giscience.param.extr_psfniter = 2
giscience.param.extr_hewidth = 2
giscience.param.extr_hmingood = 3
giscience.param.extr_omfrac = 0.9
giscience.param.extr_owfactor = 3.0
giscience.param.extr_obkgorder = 2
giscience.param.flat_apply = True
giscience.param.transmission_apply = False
giscience.param.rbin_method = "linear"
giscience.param.rbin_xresid = True
giscience.param.rbin_lstep = 0.005
giscience.param.rbin_scmethod = "linear"
giscience.param.rbin_size = 0
giscience.param.rbin_range = "setup"
giscience.param.siwc_apply = True
giscience.param.scal_cniter = 1
giscience.param.scal_zmax = 10000.0
giscience.param.scal_cstep = -0.005
giscience.param.scal_cdomain = "0.,0."
giscience.param.scal_rvlimits = "-200.,200."
giscience.param.scal_rvniter = 3
giscience.param.scal_rvwfactor = 1.5
giscience.param.scal_pfniter = 50
giscience.param.scal_pfntest = 7
giscience.param.scal_pfdchisq = 0.0001
giscience.param.recon_min = 0.0
giscience.param.recon_max = 0.0
giscience.param.recon_cube = True
giscience.param.recon_format = "single"
giscience.param.generate_SDP_format = False
giscience.param.dummy_association_keys = 0
You may also set or overwrite some or all parameters by the recipe parameter param, as shown in the following example:
import cpl
giscience = cpl.Recipe("giscience")
[...]
res = giscience( ..., param = {"remove_bias":True, "bsremove_method":"PROFILE"})
See also
cpl.Recipe for more information about the recipe object.
Bug reports¶
Please report any problems to Giraffe Pipeline. Alternatively, you may send a report to the ESO User Support Department.
Copyright¶
This file is part of the GIRAFFE Instrument Pipeline Copyright (C) 2002-2014 European Southern Observatory
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
Code author: Giraffe Pipeline <usd-help@eso.org>