def make_test_arf():
from gammapy.irf import np_to_arf
from gammapy.irf import abramowski_effective_area
effective_area = abramowski_effective_area(np.diff(EBOUNDS))
arf = np_to_arf(effective_area, EBOUNDS)
filename = 'xspec_test_arf.fits'
logging.info('Writing {0}'.format(filename))
arf.writeto(filename, clobber=True)
def make_test_arf():
from gammapy.irf import np_to_arf
from gammapy.irf import abramowski_effective_area
effective_area = abramowski_effective_area(np.diff(EBOUNDS))
arf = np_to_arf(effective_area, EBOUNDS)
filename = 'xspec_test_arf.fits'
logging.info('Writing {0}'.format(filename))
arf.writeto(filename, clobber=True)
from gammapy.spectrum.models import PowerLaw
from gammapy.spectrum import calculate_predicted_counts, SpectrumExtraction, PHACountsSpectrum, SpectrumObservation
from gammapy.utils.random import get_random_state
import numpy as np
import astropy.units as u
import matplotlib.pyplot as plt
e_true = SpectrumExtraction.DEFAULT_TRUE_ENERGY
e_reco = SpectrumExtraction.DEFAULT_RECO_ENERGY
# EDISP
edisp = EnergyDispersion.from_gauss(e_true=e_true, e_reco=e_true, sigma=0.2)
# AEFF
nodes = np.sqrt(e_true[:-1] * e_true[1:])
data = abramowski_effective_area(energy=nodes)
aeff = EffectiveAreaTable(data=data, energy=e_true)
lo_threshold = aeff.find_energy(0.1 * aeff.max_area)
# MODEL
model = PowerLaw(index=2.3 * u.Unit(""), amplitude=2.5 * 1e-12 * u.Unit("cm-2 s-1 TeV-1"), reference=1 * u.TeV)
# COUNTS
livetime = 2 * u.h
npred = calculate_predicted_counts(model=model, aeff=aeff, edisp=edisp, livetime=livetime)
bkg = 0.2 * npred.data
alpha = 0.1
counts_kwargs = dict(
energy=npred.energy,
"""Plot approximate effective area for HESS, HESS2 and CTA."""
import numpy as np
import matplotlib.pyplot as plt
from astropy.units import Quantity
from gammapy.irf import abramowski_effective_area
energy = Quantity(np.logspace(-3, 3, 100), 'TeV')
for instrument in ['HESS', 'HESS2', 'CTA']:
a_eff = abramowski_effective_area(energy, instrument)
plt.plot(energy.value, a_eff.value, label=instrument)
plt.loglog()
plt.xlabel('Energy (TeV)')
plt.ylabel('Effective Area (cm^2)')
plt.xlim([1e-3, 1e3])
plt.ylim([1e3, 1e12])
plt.legend(loc='best')
plt.show()
from gammapy.spectrum import (calculate_predicted_counts, SpectrumExtraction,
PHACountsSpectrum, SpectrumObservation)
from gammapy.utils.random import get_random_state
import numpy as np
import astropy.units as u
import matplotlib.pyplot as plt
e_true = SpectrumExtraction.DEFAULT_TRUE_ENERGY
e_reco = SpectrumExtraction.DEFAULT_RECO_ENERGY
# EDISP
edisp = EnergyDispersion.from_gauss(e_true=e_true, e_reco=e_true, sigma=0.2)
# AEFF
nodes = np.sqrt(e_true[:-1] * e_true[1:])
data = abramowski_effective_area(energy=nodes)
aeff = EffectiveAreaTable(data=data, energy=e_true)
lo_threshold = aeff.find_energy(0.1 * aeff.max_area)
# MODEL
model = PowerLaw(index=2.3 * u.Unit(''),
amplitude=2.5 * 1e-12 * u.Unit('cm-2 s-1 TeV-1'),
reference=1 * u.TeV)
# COUNTS
livetime = 2 * u.h
npred = calculate_predicted_counts(model=model,
aeff=aeff,
edisp=edisp,
livetime=livetime)
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Plot approximate effective area for HESS, HESS2 and CTA.
"""
import numpy as np
import matplotlib.pyplot as plt
from astropy.units import Quantity
from gammapy.irf import abramowski_effective_area
energy = Quantity(np.logspace(-3, 3, 100), 'TeV')
for instrument in ['HESS', 'HESS2', 'CTA']:
a_eff = abramowski_effective_area(energy, instrument)
plt.plot(energy.value, a_eff.value, label=instrument)
plt.loglog()
plt.xlabel('Energy (TeV)')
plt.ylabel('Effective Area (cm^2)')
plt.xlim([1e-3, 1e3])
plt.ylim([1e3, 1e12])
plt.legend(loc='best')
plt.show()