def get_sensitivity(self, observation_time=50):
if self.site in ['south', 'paranal']:
self.E, self.sensitivity = np.loadtxt(ds.get('cta_requirements_South-50h.dat'), unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.sensitivity = np.loadtxt(ds.get('cta_requirements_North-50h.dat'), unpack=True)
return self.E, self.sensitivity
def get_effective_area(self, observation_time=50):
"""
Return the effective area at the given observation time in hours.
NB: Only 50h supported
Returns the energy array and the effective area array
Parameters
----------
observation_time: optional
Returns
-------
`numpy.ndarray`, `numpy.ndarray`
"""
if self.site == 'south':
if observation_time == 50:
self.E, self.effective_area = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-EffArea.txt'),
skiprows=11, unpack=True)
if observation_time == 0.5:
self.E, self.effective_area = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-30m-EffArea.txt'),
skiprows=11, unpack=True)
if self.site == 'north':
if observation_time == 50:
self.E, self.effective_area = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-EffArea.txt'),
skiprows=11, unpack=True)
if observation_time == 0.5:
self.E, self.effective_area = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-30m-EffArea.txt'),
skiprows=11, unpack=True)
return self.E, self.effective_area
def get_angular_resolution(self):
if self.site == 'south':
self.E, self.angular_resolution = np.loadtxt(ds.get('cta_requirements_South-50h-AngRes.dat'), unpack=True)
if self.site == 'north':
self.E, self.angular_resolution = np.loadtxt(ds.get('cta_requirements_North-50h-AngRes.dat'), unpack=True)
return self.E, self.angular_resolution
def get_energy_resolution(self):
if self.site in ['south', 'paranal']:
self.E, self.energy_resolution = np.loadtxt(ds.get('cta_requirements_South-50h-ERes.dat'), unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.energy_resolution = np.loadtxt(ds.get('cta_requirements_North-50h-ERes.dat'), unpack=True)
return self.E, self.energy_resolution
def get_sensitivity(self, observation_time=50):
if self.site in ['south', 'paranal']:
self.E, self.sensitivity = np.loadtxt(
ds.get('cta_requirements_South-50h.dat'), unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.sensitivity = np.loadtxt(
ds.get('cta_requirements_North-50h.dat'), unpack=True)
return self.E, self.sensitivity
def get_energy_resolution(self):
if self.site in ['south', 'paranal']:
self.E, self.energy_resolution = np.loadtxt(ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-Eres.txt'),
skiprows=11, unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.energy_resolution = np.loadtxt(ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-Eres.txt'),
skiprows=11, unpack=True)
return self.E, self.energy_resolution
def get_energy_resolution(self):
if self.site in ['south', 'paranal']:
self.E, self.energy_resolution = np.loadtxt(
ds.get('cta_requirements_South-50h-ERes.dat'), unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.energy_resolution = np.loadtxt(
ds.get('cta_requirements_North-50h-ERes.dat'), unpack=True)
return self.E, self.energy_resolution
def get_angular_resolution(self):
if self.site == 'south':
self.E, self.angular_resolution = np.loadtxt(
ds.get('cta_requirements_South-50h-AngRes.dat'), unpack=True)
if self.site == 'north':
self.E, self.angular_resolution = np.loadtxt(
ds.get('cta_requirements_North-50h-AngRes.dat'), unpack=True)
return self.E, self.angular_resolution
def get_angular_resolution(self):
if self.site == 'south':
self.E, self.angular_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-Angres.txt'),
skiprows=11, unpack=True)
if self.site == 'north':
self.E, self.angular_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-Angres.txt'),
skiprows=11, unpack=True)
return self.E, self.angular_resolution
def get_sensitivity(self, observation_time=50):
if self.site in ['south', 'paranal']:
Emin, Emax, self.sensitivity = np.loadtxt(ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-DiffSens.txt'),
skiprows=10, unpack=True)
self.E = logbin_mean(np.append(Emin, Emax[-1]))
if self.site in ['north', 'lapalma']:
Emin, Emax, self.sensitivity = np.loadtxt(ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-DiffSens.txt'),
skiprows=10, unpack=True)
self.E = logbin_mean(np.append(Emin, Emax[-1]))
return self.E, self.sensitivity
def get_energy_resolution(self):
if self.site in ['south', 'paranal']:
self.E, self.energy_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-Eres.txt'),
skiprows=11,
unpack=True)
if self.site in ['north', 'lapalma']:
self.E, self.energy_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-Eres.txt'),
skiprows=11,
unpack=True)
return self.E, self.energy_resolution
def get_angular_resolution(self):
if self.site == 'south':
self.E, self.angular_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-South-20deg-50h-Angres.txt'),
skiprows=11,
unpack=True)
if self.site == 'north':
self.E, self.angular_resolution = np.loadtxt(
ds.get('CTA-Performance-prod3b-v1-North-20deg-50h-Angres.txt'),
skiprows=11,
unpack=True)
return self.E, self.angular_resolution
def get_sensitivity(self, observation_time=50):
if self.site in ['south', 'paranal']:
Emin, Emax, self.sensitivity = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-South-20deg-50h-DiffSens.txt'),
skiprows=10,
unpack=True)
self.E = logbin_mean(np.append(Emin, Emax[-1]))
if self.site in ['north', 'lapalma']:
Emin, Emax, self.sensitivity = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-North-20deg-50h-DiffSens.txt'),
skiprows=10,
unpack=True)
self.E = logbin_mean(np.append(Emin, Emax[-1]))
return self.E, self.sensitivity
def get_effective_area(self, observation_time=50):
"""
Return the effective area at the given observation time in hours.
NB: Only 0.5h supported
Returns the energy array and the effective area array
Parameters
----------
observation_time: optional
Returns
-------
`numpy.ndarray`, `numpy.ndarray`
"""
if self.site == 'south':
self.E, self.effective_area = np.loadtxt(ds.get('cta_requirements_South-30m-EffectiveArea.dat'),
unpack=True)
if self.site == 'north':
self.E, self.effective_area = np.loadtxt(ds.get('cta_requirements_North-30m-EffectiveArea.dat'),
unpack=True)
return self.E, self.effective_area
def get_effective_area(self, observation_time=50):
"""
Return the effective area at the given observation time in hours.
NB: Only 0.5h supported
Returns the energy array and the effective area array
Parameters
----------
observation_time: optional
Returns
-------
`numpy.ndarray`, `numpy.ndarray`
"""
if self.site == 'south':
self.E, self.effective_area = np.loadtxt(
ds.get('cta_requirements_South-30m-EffectiveArea.dat'),
unpack=True)
if self.site == 'north':
self.E, self.effective_area = np.loadtxt(
ds.get('cta_requirements_North-30m-EffectiveArea.dat'),
unpack=True)
return self.E, self.effective_area
def get_effective_area(self, observation_time=50):
"""
Return the effective area at the given observation time in hours.
NB: Only 50h supported
Returns the energy array and the effective area array
Parameters
----------
observation_time: optional
Returns
-------
`numpy.ndarray`, `numpy.ndarray`
"""
if self.site == 'south':
if observation_time == 50:
self.E, self.effective_area = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-South-20deg-50h-EffArea.txt'),
skiprows=11,
unpack=True)
if observation_time == 0.5:
self.E, self.effective_area = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-North-20deg-30m-EffArea.txt'),
skiprows=11,
unpack=True)
if self.site == 'north':
if observation_time == 50:
self.E, self.effective_area = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-North-20deg-50h-EffArea.txt'),
skiprows=11,
unpack=True)
if observation_time == 0.5:
self.E, self.effective_area = np.loadtxt(ds.get(
'CTA-Performance-prod3b-v1-North-20deg-30m-EffArea.txt'),
skiprows=11,
unpack=True)
return self.E, self.effective_area
def test_get_datasets():
for file in filelist:
assert get(file)