redback.analysis.generate_new_transient_data_from_gp

redback.analysis.generate_new_transient_data_from_gp(gp_out, t_new, transient, **kwargs)[source]

Generates new transient data based on Gaussian Process (GP) predictions for the given time array and transient object. Depending on the data mode of the transient object (e.g., ‘flux_density’, ‘flux’, ‘magnitude’, or ‘luminosity’), this function updates the data accordingly, adjusting errors and scaling by frequency if necessary.

Parameters:

  • gp_out (object) – The GP output object containing the Gaussian Process model, scaled data, and other related attributes.

  • t_new (array-like) – Array of new time values for which GP predictions are to be generated.

  • transient (object) – The transient object containing the original observation data and related properties such as data mode and unique frequencies or bands.

  • kwargs –

    Additional parameters to modify behavior, such as:

    • inflate_y_err (bool): Flag to indicate whether to inflate GP errors.

    • error (float): Multiplier for adjusting GP error inflation.

Returns:

A new transient object with data updated using GP predictions.

Return type:

object