PolarisationFrame

class ska_sdp_datamodels.science_data_model.PolarisationFrame(name)[source]

Polarisation Frame data class

Defines polarisation frames post correlation: include stokesI, stokesIQUV, linear, linearFITS, circular.

TODO: Check if this is correct Attributes

fits_codes: PolarisationFrames that fit the data dimensions in actual coordinates
polarisation_frames: Dictionary containing the source reference frames information
fits_to_datamodels: PolarisationFrames that fit the data dimensions in the code

Attributes Summary

`fits_codes`
`fits_to_datamodels`
`names`	Names
`npol`	Number of correlated polarisations
`polarisation_frames`

Attributes Documentation

fits_codes = {'circular': [-1, -2, -3, -4], 'circularnp': [-1, -2], 'linear': [-5, -6, -7, -8], 'linearnp': [-5, -6], 'stokesI': [1], 'stokesIQ': [1, 2], 'stokesIQUV': [1, 2, 3, 4], 'stokesIV': [1, 4]}

fits_to_datamodels = {'circular': [0, 3, 1, 2], 'circularnp': [0, 1], 'linear': [0, 3, 1, 2], 'linearnp': [0, 1], 'stokesI': [0], 'stokesIQ': [0, 1], 'stokesIQUV': [0, 1, 2, 3], 'stokesIV': [0, 1]}

polarisation_frames = {'circular': {'LL': 3, 'LR': 2, 'RL': 1, 'RR': 0}, 'circularnp': {'LL': 1, 'RR': 0}, 'linear': {'XX': 0, 'XY': 1, 'YX': 2, 'YY': 3}, 'linearFITS': {'XX': 0, 'XY': 2, 'YX': 3, 'YY': 1}, 'linearnp': {'XX': 0, 'YY': 1}, 'stokesI': {'I': 0}, 'stokesIQ': {'I': 0, 'Q': 1}, 'stokesIQUV': {'I': 0, 'Q': 1, 'U': 2, 'V': 3}, 'stokesIV': {'I': 0, 'V': 1}}