it's my first time processing spectra from a black body radiation experiment, I'm using Python and having some troubles... I have this spectra with 2 peaks and uneven background noise which I want to normalize, I tried using specutils 1.1 "continuum-fitting" (documentation here: https://specutils.readthedocs.io/en/stable/fitting.html#continuum-fitting )
My implementation is this:
import matplotlib.pyplot as plt import numpy as np from astropy.modeling import models from astropy import units as u from specutils.spectra import Spectrum1D, SpectralRegion from specutils.fitting import fit_generic_continuum ... x = data[:, 0] y = data[:, 1] plt.plot(x, y, label = 'My Data', c='C0') spectrum = Spectrum1D(flux=y*u.Jy, spectral_axis=x*u.um) g1_fit = fit_generic_continuum(spectrum) y_fit = g1_fit(x*u.um) plt.plot(x, y_fit, label = ' Specutils Continuum Fit', c='C1') plt.legend()
But the result is somewhat disappointing
Am I doing something wrong? Do you have any other way to normalize the background noise in python? any suggestion at all?