`modules.reduction_utils`

Library of miscellaneous functions used in the reduction pipeline for the Tull coude spectrograph

Last updated: DMK, 9/24/2023

Module Contents

Functions

make_header_manifest(header_manifest_file_name)

param header_manifest_file_name:: File name for the output header manifest CSV file.

gaussian_1d(x_values, amplitude, mean, sigma, background)

Function to return 1D Gaussian.

polynomial_fit_sigma_reject(x_values, y_values, ...[, ...])

Function to perform iterative polynomial fitting based on sigma rejection with the residuals

modules.reduction_utils.make_header_manifest(header_manifest_file_name)

Parameters:: header_manifest_file_name (str) – File name for the output header manifest CSV file.
Returns:: header_df – The data frame with the header information being written to a CSV file.
Return type:: pandas DataFrame

modules.reduction_utils.gaussian_1d(x_values, amplitude, mean, sigma, background)

Function to return 1D Gaussian.

Parameters:

x_values (array) – Array to evaluate the Gaussian at.
amplitude (float) – Amplitude of the Gaussian (value at mean above the background).
mean (float) – Mean of the Gaussian.
sigma (float) – Standard deviation of the Gaussian.
background (float) – Offset of the Gaussian.

Returns:

y_values – Array of Gaussian values at input x_values array.

Return type:

array

modules.reduction_utils.polynomial_fit_sigma_reject(x_values, y_values, polynomial_degree, num_sigma_cut, num_iterations, y_limits=None, return_data=False)