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 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_aeff2d_pointlike():
filename = "$GAMMAPY_DATA/joint-crab/dl3/magic/run_05029748_DL3.fits"
aeff = EffectiveAreaTable2D.read(filename)
hdu = aeff.to_table_hdu()
assert aeff.is_pointlike
assert hdu.header["HDUCLAS3"] == "POINT-LIKE"
def get_irfs():
"""Load CTA IRFs"""
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
psf = EnergyDependentMultiGaussPSF.read(filename,
hdu="POINT SPREAD FUNCTION")
aeff = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
edisp = EnergyDispersion2D.read(filename, hdu="ENERGY DISPERSION")
bkg = Background3D.read(filename, hdu="BACKGROUND")
return dict(psf=psf, aeff=aeff, edisp=edisp, bkg=bkg)
def check_aeff(label):
irf_file = '1dc/1dc/caldb/data/cta/1dc/bcf/' + label + '/irf_file.fits'
log.info(f'Reading {irf_file}')
aeff = EffectiveAreaTable2D.read(irf_file, hdu='EFFECTIVE AREA')
aeff.peek()
filename = 'checks/irfs/' + label + '_aeff.png'
log.info(f'Writing {filename}')
plt.savefig(filename)
def test_effective_area2d_gammapy(aeff2d_hdus):
'''Test our effective area is readable by gammapy'''
from gammapy.irf import EffectiveAreaTable2D
area, hdus = aeff2d_hdus
for hdu in hdus:
with tempfile.NamedTemporaryFile(suffix='.fits') as f:
fits.HDUList([fits.PrimaryHDU(), hdu]).writeto(f.name)
# test reading with gammapy works
aeff2d = EffectiveAreaTable2D.read(f.name)
assert u.allclose(area, aeff2d.data.data, atol=1e-16 * u.m**2)
def get_exposure(geom_etrue):
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
aeff = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
exposure_map = make_map_exposure_true_energy(
pointing=SkyCoord(1, 0.5, unit="deg", frame="galactic"),
livetime=1 * u.hr,
aeff=aeff,
geom=geom_etrue,
)
return exposure_map
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 get_irfs(config):
filename = '$GAMMAPY_EXTRA/datasets/cta-1dc/caldb/data/cta//1dc/bcf/South_z20_50h/irf_file.fits'
offset = Angle(config['selection']['offset_fov'] * u.deg)
psf_fov = EnergyDependentMultiGaussPSF.read(filename, hdu='POINT SPREAD FUNCTION')
psf = psf_fov.to_energy_dependent_table_psf(theta=offset)
print(' psf', psf)
aeff = EffectiveAreaTable2D.read(filename, hdu='EFFECTIVE AREA')
edisp_fov = EnergyDispersion2D.read(filename, hdu='ENERGY DISPERSION')
edisp = edisp_fov.to_energy_dispersion(offset=offset)
# TODO: read background once it's working!
# bkg = Background3D.read(filename, hdu='BACKGROUND')
return dict(psf=psf, aeff=aeff, edisp=edisp)
def test_writeread(self, tmpdir):
filename = str(tmpdir / "testirf.fits")
fits.HDUList([
fits.PrimaryHDU(),
self.aeff.to_fits(),
self.edisp.to_fits(),
self.bkg.to_fits(),
]).writeto(filename)
read_aeff = EffectiveAreaTable2D.read(filename=filename,
hdu="EFFECTIVE AREA")
assert_allclose(read_aeff.data.data, self.aeff_data)
read_edisp = EnergyDispersion2D.read(filename=filename,
hdu="ENERGY DISPERSION")
assert_allclose(read_edisp.data.data, self.edisp_data)
read_bkg = Background3D.read(filename=filename, hdu="BACKGROUND")
assert_allclose(read_bkg.data.data, self.bkg_data)
def get_irfs(config):
filename = '$GAMMAPY_EXTRA/datasets/cta-1dc/caldb/data/cta//1dc/bcf/South_z20_50h/irf_file.fits'
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')
edisp = edisp_fov.to_energy_dispersion(offset=offset)
# TODO: read background once it's working!
# bkg = Background3D.read(filename, hdu='BACKGROUND')
return dict(psf=psf, aeff=aeff, edisp=edisp)
def test_effective_area2d():
'''Test our effective area is readable by gammapy'''
pytest.importorskip('gammapy')
from pyirf.io import create_aeff2d_hdu
from gammapy.irf import EffectiveAreaTable2D
e_bins = np.geomspace(0.1, 100, 31) * u.TeV
fov_bins = [0, 1, 2, 3] * u.deg
area = np.full((30, 3), 1e6) * u.m**2
for point_like in [True, False]:
with tempfile.NamedTemporaryFile(suffix='.fits') as f:
hdu = create_aeff2d_hdu(area,
e_bins,
fov_bins,
point_like=point_like)
fits.HDUList([fits.PrimaryHDU(), hdu]).writeto(f.name)
# test reading with gammapy works
aeff2d = EffectiveAreaTable2D.read(f.name)
assert u.allclose(area, aeff2d.data.data, atol=1e-16 * u.m**2)
def effective_area_3d_plot(irf_file_path, ax=None, hdu="EFFECTIVE AREA"):
if not ax:
fig = plt.figure(figsize=(10, 7), )
ax = fig.add_subplot(111, projection='3d')
energy_reco = np.logspace(-2, 2, 20) * u.TeV
offsets = np.linspace(0, 6, 13) * u.deg
aeff = EffectiveAreaTable2D.read(irf_file_path, hdu=hdu)
X, Y = np.meshgrid(_bin_center(energy_reco), offsets)
Z = []
for offset in offsets:
t = aeff.to_effective_area_table(offset=offset, energy=energy_reco)
Z.append(t.data.data)
Z = np.vstack(Z).value * u.m**2
X, Y, Z = np.log10(
X.to_value('TeV')).ravel(), Y.ravel(), Z.to('km2').ravel()
surf = ax.plot_trisurf(X,
Y,
Z,
cmap='viridis',
vmin=0,
vmax=np.nanpercentile(Z, 99),
antialiased=True)
ax.xaxis.set_major_formatter(mticker.FuncFormatter(_log_tick_formatter))
ax.view_init(15, -140)
ax.set_ylabel('Offset in FoV / deg')
ax.set_zlabel('Effective Area / $km^2$')
ax.set_xlabel('Reconstructed Energy / TeV')
return ax
"""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,
)
def aeff():
filename = (
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
return EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
def aeff():
filename = "$GAMMAPY_DATA/hess-dl3-dr1/data/hess_dl3_dr1_obs_id_023523.fits.gz"
return EffectiveAreaTable2D.read(filename, hdu="AEFF")
"""Plot the effective area at a given offset"""
import matplotlib.pyplot as plt
from astropy.coordinates import Angle
from gammapy.irf import EffectiveAreaTable2D
filename = "$GAMMAPY_DATA/hess-dl3-dr1/data/hess_dl3_dr1_obs_id_020136.fits.gz"
aeff = EffectiveAreaTable2D.read(filename, hdu="AEFF")
# offset at which we want to examine the effective area
offset = Angle("0.5 deg")
aeff_table = aeff.to_effective_area_table(offset=offset)
aeff_table.plot()
plt.show()
import matplotlib.pyplot as plt
import numpy as np
import astropy.units as u
from astropy.coordinates import SkyCoord
from gammapy.irf import EffectiveAreaTable2D
from gammapy.maps import WcsGeom, MapAxis, WcsNDMap
from gammapy.spectrum.models import PowerLaw
from gammapy.image.models import SkyGaussian
from gammapy.utils.random import get_random_state
from gammapy.cube import make_map_exposure_true_energy, MapFit, MapEvaluator
from gammapy.cube.models import SkyModel
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
aeff = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")
# Define sky model to simulate the data
lon_0_1 = 0.2
lon_0_2 = 0.4
lat_0_1 = 0.1
lat_0_2 = 0.6
spatial_model_1 = SkyGaussian(
lon_0=lon_0_1 * u.deg, lat_0=lat_0_1 * u.deg, sigma="0.3 deg"
)
spatial_model_2 = SkyGaussian(
lon_0=lon_0_2 * u.deg, lat_0=lat_0_2 * u.deg, sigma="0.2 deg"
)
spectral_model_1 = PowerLaw(
index=3, amplitude="1e-11 cm-2 s-1 TeV-1", reference="1 TeV"
)
from gammapy.spectrum.models import PowerLaw
import os
#now reading IRFs from one particular observation
DIR = "/Users/asinha/HESS_data/ash_stereo/run054200-054399/run054213/"
files = os.listdir(DIR)
for afile in files:
if afile[0:4] == "aeff":
f_ar = str(DIR + afile)
if afile[0:5] == "edisp":
f_edp = str(DIR + afile)
if afile[0:3] == "psf":
f_psf = str(DIR + afile)
aeff = EffectiveAreaTable2D.read(f_ar, hdu='EFFECTIVE AREA')
edisp = EnergyDispersion2D.read(f_edp)
#psf = EnergyDependentMultiGaussPSF.read(f_psf, hdu='POINT SPREAD FUNCTION')
# Define obs parameters
livetime = 1.0 * u.hr
offset = 0.01 * u.deg
lo_threshold = 0.1 * u.TeV
hi_threshold = 60 * u.TeV
# Define spectral model
index = 2.0 * u.Unit('')
amplitude = 2.5 * 1e-10 * u.Unit('cm-2 s-1 TeV-1')
reference = 1 * u.TeV
model = PowerLaw(index=index, amplitude=amplitude, reference=reference)
"cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits", ) from astropy.io import fits hdu_list = fits.open(irf_filename) hdu_list.info() # ### Effective area # # The effective area is given as a 2-dim array with energy and field of view offset axes. # In[ ]: from gammapy.irf import EffectiveAreaTable2D aeff = EffectiveAreaTable2D.read(irf_filename, hdu="EFFECTIVE AREA") # In[ ]: type(aeff) # In[ ]: type(aeff.data) # In[ ]: print(aeff.data) # In[ ]:
