def plot_source_spectra(name):
plot_source_spectrum(source=SourceCatalog3FGL()[name],
label="3FGL",
color="r")
plot_source_spectrum(source=SourceCatalog2FHL()[name],
label="2FHL",
color="g")
plot_source_spectrum(source=SourceCatalog3FHL()[name],
label="3FHL",
color="b")
ax = plt.gca()
ax.set_ylim(1.0e-12, 7.0e-11)
ax.set_xlim(1.0e-4, 2.0)
ax.set_xlabel("Energy (TeV)")
ax.set_ylabel("E^2 dN/dE (erg cm-2 s-1])")
plt.legend(loc=0)
def plot_source_spectra(name):
plot_source_spectrum(source=SourceCatalog3FGL()[name],
label='Fermi 3FGL',
color='r')
plot_source_spectrum(source=SourceCatalog2FHL()[name],
label='Fermi 2FHL',
color='g')
plot_source_spectrum(source=SourceCatalog1FHL()[name],
label='Fermi 1FHL',
color='c')
plot_source_spectrum(source=SourceCatalog3FHL()[name],
label='Fermi 3FHL',
color='b')
ax = plt.gca()
ax.set_ylim(1.e-12, 7.e-11)
ax.set_xlim(1.e-4, 2.)
ax.set_xlabel('Energy (TeV)')
ax.set_ylabel('E^2 dN/dE (erg cm-2 s-1])')
plt.legend(loc=0)
def setup_class(cls):
cls.cat = SourceCatalog2FHL()
def setup_class(cls):
cls.cat = SourceCatalog2FHL()
# Use 2FHL J0534.5+2201 (Crab) as a test source
cls.source_name = "2FHL J0534.5+2201"
cls.source = cls.cat[cls.source_name]
#
# * Load builtins catalogs from [gammapy.catalog](http://docs.gammapy.org/dev/catalog/index.html)
# * Sort and index the underlying Astropy tables
# * Access data from individual sources
#
# Let's start with importing the 2FHL catalog object from the [gammapy.catalog](http://docs.gammapy.org/dev/catalog/index.html) submodule:
# In[ ]:
from gammapy.catalog import SourceCatalog2FHL
# First we initialize the Fermi-LAT 2FHL catalog and directly take a look at the `.table` attribute:
# In[ ]:
fermi_2fhl = SourceCatalog2FHL(
"$GAMMAPY_DATA/catalogs/fermi/gll_psch_v08.fit.gz")
fermi_2fhl.table
# This looks very familiar again. The data is just stored as an [astropy.table.Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) object. We have all the methods and attributes of the `Table` object available. E.g. we can sort the underlying table by `TS` to find the top 5 most significant sources:
#
#
# In[ ]:
# sort table by TS
fermi_2fhl.table.sort("TS")
# invert the order to find the highest values and take the top 5
top_five_TS_2fhl = fermi_2fhl.table[::-1][:5]
# print the top five significant sources with association and source class
#
# * Load builtins catalogs from [gammapy.catalog](http://docs.gammapy.org/dev/catalog/index.html)
# * Sort and index the underlying Astropy tables
# * Access data from individual sources
#
# Let's start with importing the 2FHL catalog object from the [gammapy.catalog](http://docs.gammapy.org/dev/catalog/index.html) submodule:
# In[27]:
from gammapy.catalog import SourceCatalog2FHL
# First we initialize the Fermi-LAT 2FHL catalog and directly take a look at the `.table` attribute:
# In[28]:
fermi_2fhl = SourceCatalog2FHL(
'$GAMMAPY_EXTRA/datasets/catalogs/fermi/gll_psch_v08.fit.gz')
fermi_2fhl.table
# This looks very familiar again. The data is just stored as an [astropy.table.Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) object. We have all the methods and attributes of the `Table` object available. E.g. we can sort the underlying table by `TS` to find the top 5 most significant sources:
#
#
# In[29]:
# sort table by TS
fermi_2fhl.table.sort('TS')
# invert the order to find the highest values and take the top 5
top_five_TS_2fhl = fermi_2fhl.table[::-1][:5]
# print the top five significant sources with association and source class
"""Example how to plot Fermi-LAT catalog spectra.
"""
import matplotlib.pyplot as plt
from gammapy.catalog import SourceCatalog3FGL, SourceCatalog2FHL
from gammapy.utils.energy import EnergyBounds
plt.style.use('ggplot')
# load catalogs
fermi_3fgl = SourceCatalog3FGL()
fermi_2fhl = SourceCatalog2FHL()
# access crab data by corresponding identifier
crab_3fgl = fermi_3fgl['3FGL J0534.5+2201']
crab_2fhl = fermi_2fhl['2FHL J0534.5+2201']
ax = crab_3fgl.spectral_model.plot(crab_3fgl.energy_range,
energy_power=2,
label='Fermi 3FGL',
color='r',
flux_unit='erg-1 cm-2 s-1')
ax.set_ylim(1e-12, 1E-9)
# set up an energy array to evaluate the butterfly
emin, emax = crab_3fgl.energy_range
energy = EnergyBounds.equal_log_spacing(emin, emax, 100)
butterfly_3fg = crab_3fgl.spectrum.butterfly(energy)
butterfly_3fg.plot(crab_3fgl.energy_range,
ax=ax,
energy_power=2,
