ska_ost_senscalc.common.model

class ska_ost_senscalc.common.model.BeamSize(beam_maj: astropy.units.quantity.Quantity, beam_min: astropy.units.quantity.Quantity, beam_pa: astropy.units.quantity.Quantity)[source]
class ska_ost_senscalc.common.model.CalculatorInputPSS(*, freq_centre: float, bandwidth: float, num_stations: int, pointing_centre: str, duration: float, elevation_limit: float, chan_width: float, dm: float, pulse_period: float, intrinsic_pulse_width: float)[source]

This dataclass represents the internal model of the Calculator for the PSS mode.

The following units are implicitly assumed (first three parameters are inherited from CalculatorInput): - freq_centre, bandwidth: [MHz] - duration: [h] - chan_width: [Hz] - dm: [pc/cm^3] - pulse_period, intrinsic_pulse_width: [ms]

class ska_ost_senscalc.common.model.ConfusionNoise(value: astropy.units.quantity.Quantity | list[astropy.units.quantity.Quantity], limit: ska_ost_senscalc.common.model.Limit | list[ska_ost_senscalc.common.model.Limit])[source]
class ska_ost_senscalc.common.model.Limit(value)[source]

Enumeration for different types of limit

class ska_ost_senscalc.common.model.Weighting(value)[source]

Enumeration for different weighting

class ska_ost_senscalc.common.model.WeightingInput(*, dec: astropy.coordinates.angles.Latitude, weighting_mode: ska_ost_senscalc.common.model.Weighting, freq_centre: list[astropy.units.quantity.Quantity], subarray_configuration: Union[ska_ost_senscalc.subarray.MIDArrayConfiguration, ska_ost_senscalc.subarray.LOWArrayConfiguration], telescope: ska_ost_senscalc.utilities.Telescope, calc_mode: Union[ska_ost_senscalc.low.model.LowSpectralMode, ska_ost_senscalc.mid.model.MidSpectralMode], robustness: int = None, taper: astropy.units.quantity.Quantity = <Quantity 0. arcsec>)[source]
class ska_ost_senscalc.common.model.WeightingResult(weighting_factor: float, surface_brightness_conversion_factor: list[astropy.units.quantity.Quantity], beam_size: list[ska_ost_senscalc.common.model.BeamSize], confusion_noise: ska_ost_senscalc.common.model.ConfusionNoise = None)[source]