orca.transform.spectrum
=======================

.. py:module:: orca.transform.spectrum

.. autoapi-nested-parse::

   Spectrum extraction from visibility data.

   Provides functions for generating dynamic spectra and time series from
   measurement set visibility data. Supports phase shifting, weighting,
   beam correction, and DFT-based spectrum extraction.



Attributes
----------

.. autoapisummary::

   orca.transform.spectrum.logger
   orca.transform.spectrum.N_CHAN
   orca.transform.spectrum.REDIS_URL
   orca.transform.spectrum.REDIS_EXPIRE_S
   orca.transform.spectrum.REDIS_KEY_PREFIX
   orca.transform.spectrum.ROW_NUMS


Functions
---------

.. autoapisummary::

   orca.transform.spectrum.gen_spectrum
   orca.transform.spectrum.dynspec_map
   orca.transform.spectrum.dynspec_reduce
   orca.transform.spectrum.test_make_dynspec_fits


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

.. py:data:: logger

.. py:data:: N_CHAN
   :value: 192


.. py:data:: REDIS_URL

.. py:data:: REDIS_EXPIRE_S
   :value: 36000


.. py:data:: REDIS_KEY_PREFIX
   :value: 'spec-'


.. py:data:: ROW_NUMS
   :value: [('LWA-128&LWA-160', 54282), ('LWA-048&LWA-051', 33335), ('LWA-018&LWA-237', 30360),...


.. py:function:: gen_spectrum(ms: str, sourcename: str, data_column: str = 'CORRECTED_DATA', timeavg: bool = False, outdir: str = None, target_coordinates: str = None, apply_weights: str = None, apply_beam: bool = False)

   Generate spectrum (I,V,XX,XY,YX,YY) from the visibilities; if target_coordinates not assigned, assumes source of interest
   is already at phase center; if apply_weights not assigned, no weights applied.

   :param ms: The measurement set.
   :param sourcename: The source for which spectrum is being generated. Used for naming output file.
   :param data_column: MS data column on which to operate. Default is CORRECTED_DATA.
   :param timeavg: Average in time. Default is False.
   :param outdir: Path to where output .npz file should be written. Default is path to input ms.
   :param apply_weights: Imaging weights npy file (from wsclean-2.5 -store-imaging-weights,
                         IMAGING_WEIGHT_SPECTRUM column).

   :returns: Path to output .npz file containing spectrum.


.. py:function:: dynspec_map(subband_no: int, scan_no: int, ms: str, bcal: str) -> List[_SnapshotSpectrum]

   Map task for dynamic spectrum generation.

   Applies calibration and extracts spectrum data for a single snapshot,
   storing results in Redis for later reduction.

   :param subband_no: Subband index (0-15).
   :param scan_no: Scan/timestamp index.
   :param ms: Path to the measurement set.
   :param bcal: Path to bandpass calibration table.

   :returns: List of _SnapshotSpectrum objects with Redis keys.


.. py:function:: dynspec_reduce(spectra: Iterable[List[_SnapshotSpectrum]], start_ts: datetime.datetime, out_dir: str) -> None

   Reduce task to combine spectrum data into FITS files.

   Collects spectrum data from Redis, combines across time and frequency,
   and writes output FITS files with proper WCS headers.

   :param spectra: Iterable of spectrum lists from dynspec_map tasks.
   :param start_ts: Start timestamp for the observation.
   :param out_dir: Output directory for FITS files.


.. py:function:: test_make_dynspec_fits()