Data containers used in ska-sdp-datamodels

ska-sdp-datamodels holds data in python Classes. The bulk data and attributes are usually kept in a xarray.Dataset. For each xarray based class there is an accessor which holds class specific methods and properties.

The structure follows the “Memory Data Models” element of the Processing Functions Module view.

Visibility-related models

• Baseline-based visibility table, shape (ntimes, nbaselines, nchan, npol), length ntime): ska_sdp_datamodels.visibility.Visibility

• FlagTable for flagging information: ska_sdp_datamodels.visibility.FlagTable

Image model

• Image (data and WCS header): ska_sdp_datamodels.image.Image

Calibration-related models

• GainTable for gain solutions (as e.g. output from solve_gaintable): ska_sdp_datamodels.calibration.GainTable

• PointingTable for pointing information: ska_sdp_datamodels.calibration.PointingTable

Sky-related models

• SkyComponent (data for a point source or a Gaussian source): ska_sdp_datamodels.sky_model.SkyComponent

• SkyModel (collection of SkyComponents and Images): ska_sdp_datamodels.sky_model.SkyModel

Gridded visibility-related models

• GridData: ska_sdp_datamodels.gridded_visibility.GridData

• ConvolutionFunction: ska_sdp_datamodels.gridded_visibility.ConvolutionFunction

Configuration model

• Telescope Configuration: ska_sdp_datamodels.configuration.Configuration

Note that the package contains a set of example configuration files, which can be used for testing purposes. These are in ska_sdp_datamodels/configuration/example_antenna_files.

Science data models

• ReceptorFrame: ska_sdp_datamodels.science_data_model.ReceptorFrame

• PolarisationFrame: ska_sdp_datamodels.science_data_model.PolarisationFrame

• QualityAssessment: ska_sdp_datamodels.science_data_model.QualityAssessment