The muse_lsf recipe



Compute the LSF


Compute the slice and wavelength dependent LSF from a lines spectrum (ARC lamp).



Create an object for the recipe muse_lsf.

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



IFU to handle. If set to 0, all IFUs are processed serially. If set to -1, all IFUs are processed in parallel. (int; default: 0) [default=0].


If this is “none”, stop when detecting discrepant overscan levels (see ovscsigma), for “offset” it assumes that the mean overscan level represents the real offset in the bias levels of the exposures involved, and adjusts the data accordingly; for “vpoly”, a polynomial is fit to the vertical overscan and subtracted from the whole quadrant. (str; default: ‘vpoly’) [default=”vpoly”].


This influences how values are rejected when computing overscan statistics. Either no rejection at all (“none”), rejection using the DCR algorithm (“dcr”), or rejection using an iterative constant fit (“fit”). (str; default: ‘dcr’) [default=”dcr”].


If the deviation of mean overscan levels between a raw input image and the reference image is higher than |ovscsigma x stdev|, stop the processing. If overscan=”vpoly”, this is used as sigma rejection level for the iterative polynomial fit (the level comparison is then done afterwards with |100 x stdev| to guard against incompatible settings). Has no effect for overscan=”offset”. (float; default: 30.0) [default=30.0].


The number of pixels of the overscan adjacent to the data section of the CCD that are ignored when computing statistics or fits. (int; default: 3) [default=3].


Save the pixel table after the LSF subtraction. (bool; default: False) [default=False].


Minimal quality flag in line catalog for selection (int; default: 3) [default=3].


Wavelength window (half size) around each line to estimate LSF (float; default: 7.5) [default=7.5].


Image size in LSF direction (int; default: 150) [default=150].


Image size in line wavelength direction (int; default: 30) [default=30].


Size of the regression window in LSF direction (float; default: 0.7) [default=0.7].


Merge output products from different IFUs into a common file. (bool; default: False) [default=False].


Type of lampwise image combination to use. (str; default: ‘sigclip’) [default=”sigclip”].


LSF generation method. Depending on this value, either an interpolated LSF cube is created, or a table with the parameters of a hermitean gaussian. (str; default: ‘interpolate’) [default=”interpolate”].

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

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

muse_lsf.param.nifu = 0
muse_lsf.param.overscan = "vpoly"
muse_lsf.param.ovscreject = "dcr"
muse_lsf.param.ovscsigma = 30.0
muse_lsf.param.ovscignore = 3
muse_lsf.param.save_subtracted = False
muse_lsf.param.line_quality = 3
muse_lsf.param.lsf_range = 7.5
muse_lsf.param.lsf_size = 150
muse_lsf.param.lambda_size = 30
muse_lsf.param.lsf_regression_window = 0.7
muse_lsf.param.merge = False
muse_lsf.param.combine = "sigclip"
muse_lsf.param.method = "interpolate"

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

import cpl
muse_lsf = cpl.Recipe("muse_lsf")
res = muse_lsf( ..., param = {"nifu":0, "overscan":"vpoly"})

See also

cpl.Recipe for more information about the recipe object.

Bug reports

Please report any problems to Ole Streicher. Alternatively, you may send a report to the ESO User Support Department.