edges_cal.cal_coefficients.CalibrationObservation.inject

CalibrationObservation.inject(lna_s11: ndarray = None, source_s11s: dict[str, numpy.ndarray] = None, c1: ndarray = None, c2: ndarray = None, t_unc: ndarray = None, t_cos: ndarray = None, t_sin: ndarray = None, averaged_spectra: dict[str, numpy.ndarray] = None, thermistor_temp_ave: dict[str, numpy.ndarray] = None) → CalibrationObservation

Make a new CalibrationObservation based on this, with injections.

Parameters:

• lna_s11 – The LNA S11 as a function of frequency to inject.

• source_s11s – Dictionary of {source: S11} for each source to inject.

• c1 – Scaling parameter as a function of frequency to inject.

• c2 ([type], optional) – Offset parameter to inject as a function of frequency.

• t_unc – Uncorrelated temperature to inject (as function of frequency)

• t_cos – Correlated temperature to inject (as function of frequency)

• t_sin – Correlated temperature to inject (as function of frequency)

• averaged_spectra – Dictionary of {source: spectrum} for each source to inject.

Returns:

CalibrationObservation – A new observation object with the injected models.