orca.utils.calibratormodel
==========================

.. py:module:: orca.utils.calibratormodel

.. autoapi-nested-parse::

   Calibrator sky model generation for OVRO-LWA.

   This module generates sky models for calibration sources with primary beam
   corrections. Supports both full-sky models and specific source selection
   (e.g., Cygnus A only for delay calibration).

   Classes:
       model_generation: Main class for generating CASA component lists.

   The generated component lists can be applied to measurement sets using
   CASA's ft task for model-based calibration.



Classes
-------

.. autoapisummary::

   orca.utils.calibratormodel.model_generation


Functions
---------

.. autoapisummary::

   orca.utils.calibratormodel.conv_deg


Module Contents
---------------

.. py:function:: conv_deg(dec)

.. py:class:: model_generation(vis=None, filename='calibrator_source_list.txt', pol='I,Q,U,V', separate_pol=True, model=True)

   .. py:property:: vis


   .. py:attribute:: min_beam_val
      :value: 0.01



   .. py:attribute:: separate_pol
      :value: True



   .. py:property:: pol


   .. py:property:: calfilepath


   .. py:attribute:: outpath


   .. py:attribute:: polarisations


   .. py:attribute:: num_pol


   .. py:property:: filename


   .. py:attribute:: output_freq
      :value: None



   .. py:attribute:: includesun
      :value: False



   .. py:attribute:: solar_flux
      :value: 16000



   .. py:attribute:: solar_alpha
      :value: 2.2



   .. py:attribute:: modelcl
      :value: None



   .. py:attribute:: verbose
      :value: True



   .. py:attribute:: overwrite
      :value: True



   .. py:attribute:: predict
      :value: True



   .. py:attribute:: model
      :value: True



   .. py:attribute:: point_source_model_needed
      :value: True



   .. py:attribute:: primary_beam_model
      :value: '/lustre/msurajit/beam_model_nivedita/OVRO-LWA_soil_pt.h5'



   .. py:method:: gen_model_file()

      :param filename: output txt file that contains clean components for all visible strong calibration sources
          in wsclean format
      :param visibility: input visibility
      :return: N/A



   .. py:method:: write_source_file(current_pol_index, source_name, muller_matrix, source_num)


   .. py:method:: primary_beam_value(current_pol_index, muller_matrix)
      :staticmethod:


      returns elements from the first column of Muller Matrix



   .. py:method:: ctrl_freq()


   .. py:method:: predict_flux(flux_hi, sp, muller_matrix, ref_freq)

      Given a flux at reference frequency in MHz and a sp_index, return the flux other frequenct

      :param flux_hi: flux at the reference frequency
      :param sp: spectral index
      :param ref_freq: reference frequency in MHz
      :param output_freq: output frequency in MHz
      :return: flux caliculated at the output frequency



   .. py:method:: get_risen_source_list()


   .. py:method:: point_source_model(included_sources=None)


   .. py:method:: reset_image(imagename)


   .. py:method:: generate_model_from_component_list(imagename)


   .. py:method:: correct_for_restoring_beam(image)


   .. py:method:: check_negative_in_model()


   .. py:method:: do_prediction()


   .. py:method:: gen_dummy_image(imagename)


   .. py:method:: gen_model_cl(included_sources=None)

      Generate source models for bright sources as CASA clean components

      :param msfile: input visibility
      :param ref_freq: reference frequency of the preset flux values of bright sources
      :param output_freq: output frequency to be written into the CASA component list
      :param includesun: if True, add a precribed solar flux to the source list
      :return: