def test_stack(self, flux_points):
stacked = FluxPoints.stack([flux_points, flux_points])
assert len(stacked.table) == 2 * len(flux_points.table)
assert stacked.sed_type == flux_points.sed_type
# In the Fermi-LAT catalogs, integral flux points are given. Currently the flux point fitter only works with differential flux points, so we apply the conversion here.
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flux_points_3fgl = source_fermi_3fgl.flux_points.to_sed_type(
sed_type="dnde", model=source_fermi_3fgl.spectral_model())
flux_points_3fhl = source_fermi_3fhl.flux_points.to_sed_type(
sed_type="dnde", model=source_fermi_3fhl.spectral_model())
# Finally we stack the flux points into a single `~gammapy.spectrum.FluxPoints` object and drop the upper limit values, because currently we can't handle them in the fit:
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# Stack flux point tables
flux_points = FluxPoints.stack(
[flux_points_gammacat, flux_points_3fhl, flux_points_3fgl])
t = flux_points.table
t["dnde_err"] = 0.5 * (t["dnde_errn"] + t["dnde_errp"])
# Remove upper limit points, where `dnde_errn = nan`
is_ul = np.isfinite(t["dnde_err"])
flux_points = FluxPoints(t[is_ul])
flux_points
# ## Power Law Fit
#
# First we start with fitting a simple `~gammapy.modeling.models.PowerLawSpectralModel`.
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