The muse_bias recipe
===============================================================

.. data:: muse_bias

Synopsis
--------

Combine several separate bias images into one master bias file.

Description
-----------

This recipe combines several separate bias images into one master bias file. The master bias contains the combined pixel values, in adu, of the raw bias exposures, with respect to the image combination method used. Processing trims the raw data and records the overscan statistics, corrects the data levels using the overscan (if overscan is not "none") and combines the exposures using input parameters. The read-out noise is computed for each quadrant of the raw input images and stored as QC parameter. The variance extension is filled with an initial value accordingly, before image combination. Further QC statistics are computed on the output master bias. Additionally, bad columns are searched for and marked in the data quality extension.


Constructor
-----------

.. method:: cpl.Recipe("muse_bias")
   :noindex:

   Create an object for the recipe muse_bias.

::

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

Parameters
----------

.. py:attribute:: muse_bias.param.nifu

    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].
.. py:attribute:: muse_bias.param.overscan

    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"].
.. py:attribute:: muse_bias.param.ovscreject

    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"].
.. py:attribute:: muse_bias.param.ovscsigma

    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].
.. py:attribute:: muse_bias.param.ovscignore

    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].
.. py:attribute:: muse_bias.param.combine

    Type of image combination to use. (str; default: 'sigclip') [default="sigclip"].
.. py:attribute:: muse_bias.param.nlow

    Number of minimum pixels to reject with minmax. (int; default: 1) [default=1].
.. py:attribute:: muse_bias.param.nhigh

    Number of maximum pixels to reject with minmax. (int; default: 1) [default=1].
.. py:attribute:: muse_bias.param.nkeep

    Number of pixels to keep with minmax. (int; default: 1) [default=1].
.. py:attribute:: muse_bias.param.lsigma

    Low sigma for pixel rejection with sigclip. (float; default: 3.0) [default=3.0].
.. py:attribute:: muse_bias.param.hsigma

    High sigma for pixel rejection with sigclip. (float; default: 3.0) [default=3.0].
.. py:attribute:: muse_bias.param.losigmabadpix

    Low sigma to find dark columns in the combined bias (float; default:  30.0) [default=30.0].
.. py:attribute:: muse_bias.param.hisigmabadpix

    High sigma to find bright columns in the combined bias (float;  default: 3.0) [default=3.0].
.. py:attribute:: muse_bias.param.merge

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


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

::

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

   muse_bias.param.nifu = 0
   muse_bias.param.overscan = "vpoly"
   muse_bias.param.ovscreject = "dcr"
   muse_bias.param.ovscsigma = 30.0
   muse_bias.param.ovscignore = 3
   muse_bias.param.combine = "sigclip"
   muse_bias.param.nlow = 1
   muse_bias.param.nhigh = 1
   muse_bias.param.nkeep = 1
   muse_bias.param.lsigma = 3.0
   muse_bias.param.hsigma = 3.0
   muse_bias.param.losigmabadpix = 30.0
   muse_bias.param.hisigmabadpix = 3.0
   muse_bias.param.merge = False


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

::

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


.. seealso:: `cpl.Recipe <https://packages.python.org/python-cpl/recipe.html>`_
   for more information about the recipe object.

Bug reports
-----------

Please report any problems to `Peter Weilbacher <usd-help@eso.org>`_. Alternatively, you may 
send a report to the `ESO User Support Department <usd-help@eso.org>`_.

Copyright
---------

This file is part of the MUSE Instrument Pipeline
Copyright (C) 2005, 2019 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  02111-1307  USA

.. codeauthor:: Peter Weilbacher <usd-help@eso.org>
