orca.tasks.peel_experiment
==========================

.. py:module:: orca.tasks.peel_experiment

.. autoapi-nested-parse::

   Experimental peeling pipeline tasks.

   Provides Celery tasks for testing and developing peeling workflows
   including:
   - TTCal peeling with configurable source lists
   - RFI source peeling
   - Multiple peeling iterations with different maxiter settings
   - Diagnostic image generation

   This is an experimental module for peeling algorithm development.



Attributes
----------

.. autoapisummary::

   orca.tasks.peel_experiment.WORKDIR
   orca.tasks.peel_experiment.BASE_73
   orca.tasks.peel_experiment.SOURCES_JSON
   orca.tasks.peel_experiment.RFI_JSON
   orca.tasks.peel_experiment.JULIA060_ENV_NAME
   orca.tasks.peel_experiment.TTCAL_DEV_ENV_PREFIX
   orca.tasks.peel_experiment.CAL_TABLE
   orca.tasks.peel_experiment.DEFAULT_MAXITER
   orca.tasks.peel_experiment.OVRO
   orca.tasks.peel_experiment.CYG_A
   orca.tasks.peel_experiment.CAS_A
   orca.tasks.peel_experiment.R_MASK


Functions
---------

.. autoapisummary::

   orca.tasks.peel_experiment.run_ttcal_with_conda
   orca.tasks.peel_experiment.run_wsclean_stage
   orca.tasks.peel_experiment.run_applycal_pre_peel
   orca.tasks.peel_experiment.parse_utc_from_tag
   orca.tasks.peel_experiment.compute_lst_and_alts
   orca.tasks.peel_experiment.lst_to_hms_str
   orca.tasks.peel_experiment.load_masked_image
   orca.tasks.peel_experiment.robust_rms
   orca.tasks.peel_experiment.compute_rms_from_fits
   orca.tasks.peel_experiment.make_three_panel_png
   orca.tasks.peel_experiment.make_diff_image
   orca.tasks.peel_experiment.peel_experiment_task


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

.. py:data:: WORKDIR

.. py:data:: BASE_73

.. py:data:: SOURCES_JSON

.. py:data:: RFI_JSON

.. py:data:: JULIA060_ENV_NAME
   :value: 'julia060'


.. py:data:: TTCAL_DEV_ENV_PREFIX
   :value: '/opt/devel/pipeline/envs/ttcal_dev'


.. py:data:: CAL_TABLE

.. py:data:: DEFAULT_MAXITER
   :value: 5


.. py:data:: OVRO

.. py:data:: CYG_A

.. py:data:: CAS_A

.. py:data:: R_MASK
   :value: 1833


.. py:function:: run_ttcal_with_conda(env_type: str, ms_name: str, json_path: pathlib.Path, maxiter: int)

   env_type: 'sources' or 'rfi'


.. py:function:: run_wsclean_stage(ms_name: str, suffix: str)

.. py:function:: run_applycal_pre_peel(ms_name: str, caltable_path: pathlib.Path)

.. py:function:: parse_utc_from_tag(tag: str) -> astropy.time.Time

   tag example: '2025-05-06_05_20250506_050008_73MHz_averaged_maxiter05'
   or without the _maxiterXX suffix.


.. py:function:: compute_lst_and_alts(t: astropy.time.Time)

.. py:function:: lst_to_hms_str(lst_angle)

.. py:function:: load_masked_image(fits_path, r_mask=R_MASK)

.. py:function:: robust_rms(vals, nsig=5.0, max_iter=5)

.. py:function:: compute_rms_from_fits(fits_path)

.. py:function:: make_three_panel_png(run_dir: pathlib.Path, tag: str, rms_pre: float, rms_after1: float, rms_after2: float)

.. py:function:: make_diff_image(run_dir: pathlib.Path, tag: str)

.. py:function:: peel_experiment_task(ms_rel_path: str, maxiter: int = DEFAULT_MAXITER)

   Big experiment task:
     - copy MS to WORKDIR/tag_maxiterXX
     - applycal
     - image pre-peel -> RMS_pre
     - ttcal (sources, maxiter=...) + image -> RMS_after1
     - ttcal (RFI, maxiter=...)     + image -> RMS_after2
     - make 3-panel PNG
     - make pre-minus-after2 difference image

   ms_rel_path is relative to BASE_73, e.g.
     '2025-05-06/05/20250506_050008_73MHz_averaged.ms'