See Analysis forįunctions that can be used to fill out common line measurements more Keep such functionality in separate distinct functions. While it might be surprising that these tables do not contain more informationĪbout the lines, this is because the “toolbox” philosophy of specutils aims to um ) > # Derivative technique > import warnings > from specutils.fitting import find_lines_derivative > with warnings. > # Define a noise region for adding the uncertainty > noise_region = SpectralRegion ( 0 * u. Return an QTable that contains columns line_center, On calculating the derivative and then thresholding based on it. The second technique isįind_lines_derivative that will find the lines based The first technique is find_lines_threshold that willįind lines by thresholding the flux based on a factor applied to the There are two techniques implemented in order to find emission and/or absorption Yielding a single composite model result (which can be split back into its This model is then actually fit to the spectrum’s flux, these are used to create a compound model created from the model List of Model objects that have initial guesses for each of Specutils provides conveniences that aim to leverage the general fittingįramework of astropy.modeling to spectral-specific tasks.Īt a high level, this fitting takes the Spectrum1D object and a This concept is often applied mainly to line-fitting, but the same generalĪpproach applies to continuum fitting or even full-spectrum fitting. One of the primary tasks in spectroscopic analysis is fitting models of spectra.
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