Memory data models

data_models.memory_data_models Module

The data models used in ARL:

Classes

Configuration([name, data, location, names, …])	Describe a Configuration as locations in x,y,z, mount type, diameter, names, and overall location
GainTable([data, gain, time, interval, …])	Gain table with data_models: time, antenna, gain[:, chan, rec, rec], weight columns
PointingTable([data, pointing, nominal, …])	Pointing table with data_models: time, antenna, offset[:, chan, rec, 2], weight columns
Image([data, wcs, polarisation_frame])	Image class with Image data (as a numpy.array) and the AstroPy implementation of a World Coodinate System
GridData([data, grid_wcs, projection_wcs, …])	Class to hold Gridded data for Fourier processing - Has four or more coordinates: [chan, pol, z, y, x] where x can be u, l; y can be v, m; z can be w, n
ConvolutionFunction([data, grid_wcs, …])	Class to hold Gridded data for Fourier processing - Has four or more coordinates: [chan, pol, z, y, x] where x can be u, l; y can be v, m; z can be w, n
Skycomponent([direction, frequency, name, …])	Skycomponents are used to represent compact sources on the sky.
SkyModel([image, components, gaintable, …])	A model for the sky, including an image, components, gaintable and a mask
Visibility([data, frequency, …])	Visibility table class
BlockVisibility([data, frequency, …])	Block Visibility table class
QA([origin, data, context])	Quality assessment
ScienceDataModel()	Science Data Model