def check_bkg(label):
irf_file = '1dc/1dc/caldb/data/cta/1dc/bcf/' + label + '/irf_file.fits'
log.info(f'Reading {irf_file}')
plt.clf()
bkg = Background3D.read(irf_file, hdu='BACKGROUND')
table = bkg.data.data
raise NotImplementedError
# Columns:
# BGD float32 (21, 36, 36) 1/s/MeV/sr
# ENERG_LO float32 (21,) TeV
# DETX_LO float32 (36,) deg
# DETY_LO float32 (36,) deg
for idx_detx in [18, 21, 22, 23, 24, 25, 26, 27]:
detx = table['DETX_LO'].data.squeeze()[idx_detx]
dety = table['DETY_LO'].data.squeeze()[18]
energy = table['ENERG_LO'].data.squeeze()
bkg = table['BGD'].data.squeeze()[:, idx_detx, 18]
txt = f'detx={detx:.1f}, dety={dety:.1f}'
plt.plot(energy, bkg, label=txt)
plt.legend(loc='lower left')
plt.xlabel('Energy (TeV)')
plt.xlim(0.01, 1)
plt.ylim(1e-6, 1)
plt.ylabel('Background rate (s-1 MeV-1 sr-1)')
plt.loglog()
filename = 'checks/irfs/' + label + '_bkg.png'
log.info(f'Writing {filename}')
plt.savefig(filename)
def get_irfs():
filename = '$GAMMAPY_EXTRA/datasets/cta-1dc/caldb/data/cta//1dc/bcf/South_z20_50h/irf_file.fits'
psf = EnergyDependentMultiGaussPSF.read(filename, hdu='POINT SPREAD FUNCTION')
aeff = EffectiveAreaTable2D.read(filename, hdu='EFFECTIVE AREA')
edisp = EnergyDispersion2D.read(filename, hdu='ENERGY DISPERSION')
bkg = Background3D.read(filename, hdu='BACKGROUND')
return dict(psf=psf, aeff=aeff, edisp=edisp, bkg=bkg)
def read(cls, filename):
"""Read from a FITS file.
Parameters
----------
filename : `str`
File containing the IRFs
"""
filename = str(make_path(filename))
hdu_list = fits.open(filename)
aeff = EffectiveAreaTable2D.read(filename, hdu='EFFECTIVE AREA')
bkg = Background3D.read(filename, hdu='BACKGROUND')
edisp = EnergyDispersion2D.read(filename, hdu='ENERGY DISPERSION')
psf = EnergyDependentMultiGaussPSF.read(filename,
hdu='POINT SPREAD FUNCTION')
if 'SENSITIVITY' in hdu_list:
sensi = SensitivityTable.read(filename, hdu='SENSITIVITY')
else:
sensi = None
return cls(
aeff=aeff,
bkg=bkg,
edisp=edisp,
psf=psf,
ref_sensi=sensi,
)
def background_3d_plot(irf_file_path, ax=None, hdu="BACKGROUND"):
if not ax:
fig = plt.figure(figsize=(10, 7), )
ax = fig.add_subplot(111, projection='3d')
bkg3d = Background3D.read(irf_file_path, hdu=hdu)
energy_reco = np.logspace(-2, 2, 20) * u.TeV
offset_centers = _bin_center(bkg3d.data.axes[1].bins)
data = bkg3d.data.data.sum(axis=0).value
data = _log_data(data)
vmin, vmax = -4, 1.5
data = np.clip(data, vmin, vmax)
X, Y = np.meshgrid(offset_centers, offset_centers)
X, Y, Z, = X.ravel(), Y.ravel(), gaussian_filter(data, sigma=0.8).ravel()
surf = ax.plot_trisurf(X, Y, Z, cmap='viridis', antialiased=True)
ax.zaxis.set_major_locator(mticker.FixedLocator([
-4,
-3,
-2,
-1,
0,
1,
]))
ax.zaxis.set_major_formatter(mticker.FuncFormatter(_log_tick_formatter))
ax.set_zlim([-4, 1])
return ax
def read(cls, filename):
"""Read from a FITS file.
Parameters
----------
filename : `str`
File containing the IRFs
"""
filename = str(make_path(filename))
hdu_list = fits.open(filename)
aeff = EffectiveAreaTable2D.read(filename, hdu='EFFECTIVE AREA')
bkg = Background3D.read(filename, hdu='BACKGROUND')
edisp = EnergyDispersion2D.read(filename, hdu='ENERGY DISPERSION')
psf = EnergyDependentMultiGaussPSF.read(filename, hdu='POINT SPREAD FUNCTION')
if 'SENSITIVITY' in hdu_list:
sensi = SensitivityTable.read(filename, hdu='SENSITIVITY')
else:
sensi = None
return cls(
aeff=aeff,
bkg=bkg,
edisp=edisp,
psf=psf,
ref_sensi=sensi,
)
def get_irfs(config, filename):
'''Get IRFs from file.
Parameters
----------
config : `dict`
Configuration dictionary.
filename : fits file
IRFs file
Returns
-------
irfs : `dict`
IRFs dictionary.
'''
offset = Angle(config['selection']['offset_fov'] * u.deg)
psf_fov = EnergyDependentMultiGaussPSF.read(filename, hdu='POINT SPREAD FUNCTION')
psf = psf_fov.to_energy_dependent_table_psf(theta=offset)
print(' psf', psf)
aeff = EffectiveAreaTable2D.read(filename, hdu='EFFECTIVE AREA')
edisp_fov = EnergyDispersion2D.read(filename, hdu='ENERGY DISPERSION')
table = fits.open('irf_file.fits')['BACKGROUND']
table.columns.change_name(str('BGD'), str('Bgd'))
table.header['TUNIT7'] = '1 / (MeV s sr)'
bkg = Background3D.read(filename, hdu='BACKGROUND')
irfs = dict(psf=psf, aeff=aeff, edisp=edisp_fov, bkg=bkg, offset=offset)
return irfs
def test_background_3d_read_gadf():
filename = "$GAMMAPY_DATA/tests/irf/bkg_3d_full_example.fits"
bkg = Background3D.read(filename)
data = bkg.quantity
assert bkg.axes.names == ["energy", "fov_lon", "fov_lat"]
assert data.shape == (20, 15, 15)
assert data.unit == "s-1 MeV-1 sr-1"
def test_background_3D_read():
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
bkg = Background3D.read(filename)
data = bkg.data.data
assert data.shape == (21, 36, 36)
assert data.unit == "s-1 MeV-1 sr-1"
def get_irfs():
"""Load CTA IRFs"""
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
psf = EnergyDependentMultiGaussPSF.read(filename,
hdu="POINT SPREAD FUNCTION")
aeff = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
edisp = EnergyDispersion2D.read(filename, hdu="ENERGY DISPERSION")
bkg = Background3D.read(filename, hdu="BACKGROUND")
return dict(psf=psf, aeff=aeff, edisp=edisp, bkg=bkg)
def test_background_3d_read():
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
bkg = Background3D.read(filename)
data = bkg.quantity
assert bkg.axes.names == ["energy", "fov_lon", "fov_lat"]
assert data.shape == (21, 36, 36)
assert data.unit == "s-1 MeV-1 sr-1"
def load(self):
"""Load HDU as appropriate class.
TODO: this should probably go via an extensible registry.
"""
hdu_class = self.hdu_class
filename = self.path()
hdu = self.hdu_name
if hdu_class == "events":
from gammapy.data import EventList
return EventList.read(filename, hdu=hdu)
elif hdu_class == "gti":
from gammapy.data import GTI
return GTI.read(filename, hdu=hdu)
elif hdu_class == "aeff_2d":
from gammapy.irf import EffectiveAreaTable2D
return EffectiveAreaTable2D.read(filename, hdu=hdu)
elif hdu_class == "edisp_2d":
from gammapy.irf import EnergyDispersion2D
return EnergyDispersion2D.read(filename, hdu=hdu)
elif hdu_class == "psf_table":
from gammapy.irf import PSF3D
return PSF3D.read(filename, hdu=hdu)
elif hdu_class == "psf_3gauss":
from gammapy.irf import EnergyDependentMultiGaussPSF
return EnergyDependentMultiGaussPSF.read(filename, hdu=hdu)
elif hdu_class == "psf_king":
from gammapy.irf import PSFKing
return PSFKing.read(filename, hdu=hdu)
elif hdu_class == "bkg_2d":
from gammapy.irf import Background2D
return Background2D.read(filename, hdu=hdu)
elif hdu_class == "bkg_3d":
from gammapy.irf import Background3D
return Background3D.read(filename, hdu=hdu)
else:
raise ValueError(f"Invalid hdu_class: {hdu_class}")
def test_writeread(self, tmp_path):
path = tmp_path / "tmp.fits"
fits.HDUList([
fits.PrimaryHDU(),
self.aeff.to_table_hdu(),
self.edisp.to_table_hdu(),
self.bkg.to_table_hdu(),
]).writeto(path)
read_aeff = EffectiveAreaTable2D.read(path, hdu="EFFECTIVE AREA")
assert_allclose(read_aeff.data.data, self.aeff_data)
read_edisp = EnergyDispersion2D.read(path, hdu="ENERGY DISPERSION")
assert_allclose(read_edisp.data.data, self.edisp_data)
read_bkg = Background3D.read(path, hdu="BACKGROUND")
assert_allclose(read_bkg.data.data, self.bkg_data)
def test_background_3d_read_write(tmp_path, bkg_3d):
bkg_3d.to_fits().writeto(tmp_path / "bkg3d.fits")
bkg_3d_2 = Background3D.read(tmp_path / "bkg3d.fits")
axis = bkg_3d_2.data.axis("energy")
assert axis.nbin == 2
assert axis.unit == "TeV"
axis = bkg_3d_2.data.axis("fov_lon")
assert axis.nbin == 3
assert axis.unit == "deg"
axis = bkg_3d_2.data.axis("fov_lat")
assert axis.nbin == 3
assert axis.unit == "deg"
data = bkg_3d_2.data.data
assert data.shape == (2, 3, 3)
assert data.unit == "s-1 MeV-1 sr-1"
def test_writeread(self, tmpdir):
filename = str(tmpdir / "testirf.fits")
fits.HDUList([
fits.PrimaryHDU(),
self.aeff.to_fits(),
self.edisp.to_fits(),
self.bkg.to_fits(),
]).writeto(filename)
read_aeff = EffectiveAreaTable2D.read(filename=filename,
hdu="EFFECTIVE AREA")
assert_allclose(read_aeff.data.data, self.aeff_data)
read_edisp = EnergyDispersion2D.read(filename=filename,
hdu="ENERGY DISPERSION")
assert_allclose(read_edisp.data.data, self.edisp_data)
read_bkg = Background3D.read(filename=filename, hdu="BACKGROUND")
assert_allclose(read_bkg.data.data, self.bkg_data)
def test_background_3d_read_write(tmp_path, bkg_3d):
bkg_3d.to_table_hdu().writeto(tmp_path / "bkg3d.fits")
bkg_3d_2 = Background3D.read(tmp_path / "bkg3d.fits")
axis = bkg_3d_2.axes["energy"]
assert axis.nbin == 2
assert axis.unit == "TeV"
axis = bkg_3d_2.axes["fov_lon"]
assert axis.nbin == 3
assert axis.unit == "deg"
axis = bkg_3d_2.axes["fov_lat"]
assert axis.nbin == 3
assert axis.unit == "deg"
data = bkg_3d_2.quantity
assert data.shape == (2, 3, 3)
assert data.unit == "s-1 GeV-1 sr-1"
def bkg_3d():
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
return Background3D.read(filename, hdu="BACKGROUND")
"""Example of how to create an ObservationCTA from CTA's 1DC"""
from gammapy.data import ObservationCTA, EventList, GTI
from gammapy.irf import (
EnergyDependentMultiGaussPSF,
EffectiveAreaTable2D,
EnergyDispersion2D,
Background3D,
)
filename = "$GAMMAPY_DATA/cta-1dc/data/baseline/gps/gps_baseline_110380.fits"
event_list = EventList.read(filename)
gti = GTI.read(filename)
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
aeff = EffectiveAreaTable2D.read(filename)
bkg = Background3D.read(filename)
edisp = EnergyDispersion2D.read(filename, hdu="Energy Dispersion")
psf = EnergyDependentMultiGaussPSF.read(filename, hdu="Point Spread Function")
obs = ObservationCTA(
obs_id=event_list.table.meta["OBS_ID"],
events=event_list,
gti=gti,
psf=psf,
aeff=aeff,
edisp=edisp,
bkg=bkg,
pointing_radec=event_list.pointing_radec,
observation_live_time_duration=event_list.observation_live_time_duration,
observation_dead_time_fraction=event_list.observation_dead_time_fraction,
)
# This is how for analysis you could slice out the PSF
# at a given field of view offset
psf.to_energy_dependent_table_psf("1 deg")
# ### Background
#
# The hadronic background for CTA DC-1 is given as a template model with an absolute rate that depends on `energy`, `detx` and `dety`. The coordinates `detx` and `dety` are angles in the "field of view" coordinate frame.
#
# Note that really the background model for DC-1 and most CTA IRFs produced so far are radially symmetric, i.e. only depend on the FOV offset. The background model here was rotated to fill the FOV in a rotationally symmetric way, for no good reason.
# In[ ]:
from gammapy.irf import Background3D
bkg = Background3D.read(irf_filename, hdu="BACKGROUND")
print(bkg)
# In[ ]:
# TODO: implement a peek method for Background3D
# bkg.peek()
# In[ ]:
bkg.data.evaluate(energy="3 TeV", fov_lon="1 deg", fov_lat="0 deg")
# ## Index files and DataStore
#
# As we saw, you can access all of the CTA data using Astropy and Gammapy.
#
"""Plot the background rate from the HESS DL3 data release 1.""" import matplotlib.pyplot as plt from gammapy.irf import Background3D filename = "$GAMMAPY_DATA/hess-dl3-dr1/data/hess_dl3_dr1_obs_id_020136.fits.gz" bkg = Background3D.read(filename, hdu="BKG") bkg.peek() plt.show()
