_fit_xput_lite#

irispy.utils.response._fit_xput_lite(observation_time, time_cal_coeffs, cal_coeffs)[source]#

To calculate the coefficients of best-fit time function for throughput, for which we apply a fit based on cal_coeffs.

The procedure involved in this function is as follows:

  1. The time difference (in years) is computed from the observation_time and time_cal_coeffs.

  2. A least-squares fit is performed to determine the best fit for the time-dependent effective areas given the time difference.

Goal is to replicate the base functionality of the IDL routine fit_iris_xput.pro in the SSWIDL package but without the optional keyword argument.

Parameters:

  • observation_time (astropy.time.Time) – Observation time.

  • time_cal_coeffs (astropy.time.Time) – Start and end times of intervals of constant cal_coeffs[i]. These should be in “utime” format.

  • cal_coeffs (numpy.ndarray) – Coefficients of best-fit function, with at least two columns.

Returns:

Yields the fit used to compute the effective area using the input times observation_time.

Return type:

numpy.array

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