:py:mod:`aces.sefd.sefd__cc`
============================

.. py:module:: aces.sefd.sefd__cc


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

Classes
~~~~~~~

.. autoapisummary::

   aces.sefd.sefd__cc.ASKAP_array
   aces.sefd.sefd__cc.SEFD



Functions
~~~~~~~~~

.. autoapisummary::

   aces.sefd.sefd__cc.baseline_2vec
   aces.sefd.sefd__cc.baseline_2v
   aces.sefd.sefd__cc.baseline_len
   aces.sefd.sefd__cc.antenna_decompose
   aces.sefd.sefd__cc.find_factor
   aces.sefd.sefd__cc.box_mean
   aces.sefd.sefd__cc.delfunc
   aces.sefd.sefd__cc.bl_scales
   aces.sefd.sefd__cc.bl_noise
   aces.sefd.sefd__cc.bl_noise_fft
   aces.sefd.sefd__cc.fftmeth
   aces.sefd.sefd__cc.remove_mean
   aces.sefd.sefd__cc.decomp
   aces.sefd.sefd__cc._plot0_per_ant
   aces.sefd.sefd__cc.medfilt



Attributes
~~~~~~~~~~

.. autoapisummary::

   aces.sefd.sefd__cc.__author__
   aces.sefd.sefd__cc.logger
   aces.sefd.sefd__cc.pols
   aces.sefd.sefd__cc.pi
   aces.sefd.sefd__cc.antrel01
   aces.sefd.sefd__cc.ASKAP_antennas


.. py:data:: __author__
   :value: 'Dave McConnell <david.mcconnell@csiro.au>'

   

.. py:data:: logger

   

.. py:data:: pols
   :value: [0, 1, 2, 3]

   

.. py:data:: pi

   

.. py:data:: antrel01

   

.. py:data:: ASKAP_antennas

   

.. py:class:: ASKAP_array(name)

   Bases: :py:obj:`object`

   .. py:method:: select_antennas(antennas)


   .. py:method:: gen_baselines()


   .. py:method:: get_ant_names()



.. py:function:: baseline_2vec(bas)


.. py:function:: baseline_2v(a1, a2)


.. py:function:: baseline_len(a1, a2)


.. py:function:: antenna_decompose(products, arr, b_flg)


.. py:function:: find_factor(n_avg)


.. py:function:: box_mean(x, n)


.. py:function:: delfunc(x, f, t, z)


.. py:class:: SEFD(sbid, file_name=None, mset_inx=0, dch=1, ch0=0, ncf=0, scan=-1, dnt=120, nstart=3, nct=0, uvmin=0.0)

   Bases: :py:obj:`object`

   .. py:method:: summary()


   .. py:method:: calc_sefd(difference='none')

      :param difference: Options are 'none', 'time', 'frequency'


   .. py:method:: decompose(what='SEFD')


   .. py:method:: compare(other)


   .. py:method:: save_pickle(file_name)


   .. py:method:: save_hdf5(file_name, per_ant=True)


   .. py:method:: plot_per_ant(plot_file)


   .. py:method:: get_meta()



.. py:function:: bl_scales(n_avg, zvis, flux1934)


.. py:function:: bl_noise(zvis, scale, btau, n_avg, diff)

   :param zvis:
   :param scale:
   :param btau:
   :param n_avg:
   :param diff: Options are 'none', 'time', 'frequency'
   :return:


.. py:function:: bl_noise_fft(zvis, scale, btau, n_avg)


.. py:function:: fftmeth(sig)


.. py:function:: remove_mean(z)


.. py:function:: decomp(prod, lpols, arr, flags)


.. py:function:: _plot0_per_ant(sefd_per_ant, chan_freq, ants, pltname)


.. py:function:: medfilt(x, k)

   Apply a length-k median filter to a 1D array x.
   Boundaries are extended by repeating endpoints.