def fit_bin(self, i):
"""Fit the azimuthal distribution for the i-th energy slice.
"""
hist = (self.phi_y[i], self.phi_binning, None)
_fit_results = xAzimuthalResponseGenerator.fit_histogram(hist)
_fit_results.set_polarization(self.modf(self.emean[i]))
logger.info(_fit_results)
self.fit_results.append(_fit_results)
return _fit_results
def fit_bin(self, i):
"""Fit the azimuthal distribution for the i-th energy slice.
"""
hist = (self.phi_y[i], self.phi_binning, None)
_fit_results = xAzimuthalResponseGenerator.fit_histogram(hist)
_fit_results.set_polarization(self.modf(self.emean[i]))
logger.info(_fit_results)
self.fit_results.append(_fit_results)
return _fit_results
def test_constant(self, num_events=1000000, polarization_degree=1.,
polarization_angle=numpy.radians(20.)):
"""Test the modulation factor as a random number generator when
both the polarization angle and degrees are energy- and
time-independent.
"""
poldegree = numpy.full(num_events, polarization_degree)
polangle = numpy.full(num_events, polarization_angle)
self.modf.generator.plot(show=False)
save_current_figure('test_modulation_constant_generator.png',
show=self.interactive)
emin = self.modf.xmin()
emax = self.modf.xmax()
energy = numpy.random.uniform(emin, emax, num_events)
phi = self.modf.rvs_phi(energy, poldegree, polangle)
ebinning = numpy.linspace(emin, emax, 10)
phi_binning = numpy.linspace(0, 2*numpy.pi, 100)
fit_results = []
for i, (_emin, _emax) in enumerate(zip(ebinning[:-1], ebinning[1:])):
_emean = 0.5*(_emin + _emax)
_mask = (energy > _emin)*(energy < _emax)
_phi = phi[_mask]
_hist = plt.hist(_phi, bins=phi_binning, histtype='step')
_fr = xAzimuthalResponseGenerator.fit_histogram(_hist)
_fr.emean = _emean
fit_results.append(_fr)
_fr.plot(label='Energy: %.2f--%.2f keV' % (_emin, _emax))
plt.axis([0., 2*numpy.pi, 0., 1.2*_hist[0].max()])
overlay_tag()
save_current_figure('test_modulation_constant_fit_slice%d.png' % i,
show=self.interactive)
_x = [_fr.emean for _fr in fit_results]
_y = [_fr.phase for _fr in fit_results]
_dy = [_fr.phase_error for _fr in fit_results]
plt.errorbar(_x, _y, yerr=_dy, fmt='o')
plt.plot(_x, numpy.array([polarization_angle]*len(_x)))
plt.xlabel('Energy [keV]')
plt.ylabel('Modulation angle [$^\circ$]')
save_current_figure('test_modulation_constant_angle.png',
show=self.interactive)
_y = [_fr.visibility for _fr in fit_results]
_dy = [_fr.visibility_error for _fr in fit_results]
plt.errorbar(_x, _y, yerr=_dy, fmt='o')
plt.axis([emin, emax, 0, 1])
self.modf.plot(show=False)
plt.xlabel('Energy [keV]')
plt.ylabel('Modulation visibility')
save_current_figure('test_modulation_constant_visibility.png',
show=self.interactive)
def test_constant(self, num_events=1000000, polarization_degree=1.,
polarization_angle=numpy.radians(20.)):
"""Test the modulation factor as a random number generator when
both the polarization angle and degrees are energy- and
time-independent.
"""
poldegree = numpy.full(num_events, polarization_degree)
polangle = numpy.full(num_events, polarization_angle)
self.modf.generator.plot(show=False)
save_current_figure('test_modulation_constant_generator.png',
show=self.interactive)
emin = self.modf.xmin()
emax = self.modf.xmax()
energy = numpy.random.uniform(emin, emax, num_events)
phi = self.modf.rvs_phi(energy, poldegree, polangle)
ebinning = numpy.linspace(emin, emax, 10)
phi_binning = numpy.linspace(0, 2*numpy.pi, 100)
fit_results = []
for i, (_emin, _emax) in enumerate(zip(ebinning[:-1], ebinning[1:])):
_emean = 0.5*(_emin + _emax)
_mask = (energy > _emin)*(energy < _emax)
_phi = phi[_mask]
_hist = plt.hist(_phi, bins=phi_binning, histtype='step')
_fr = xAzimuthalResponseGenerator.fit_histogram(_hist)
_fr.emean = _emean
fit_results.append(_fr)
_fr.plot(label='Energy: %.2f--%.2f keV' % (_emin, _emax))
plt.axis([0., 2*numpy.pi, 0., 1.2*_hist[0].max()])
overlay_tag()
save_current_figure('test_modulation_constant_fit_slice%d.png' % i,
show=self.interactive)
_x = [_fr.emean for _fr in fit_results]
_y = [_fr.phase for _fr in fit_results]
_dy = [_fr.phase_error for _fr in fit_results]
plt.errorbar(_x, _y, yerr=_dy, fmt='o')
plt.plot(_x, numpy.array([polarization_angle]*len(_x)))
plt.xlabel('Energy [keV]')
plt.ylabel('Modulation angle [$^\circ$]')
save_current_figure('test_modulation_constant_angle.png',
show=self.interactive)
_y = [_fr.visibility for _fr in fit_results]
_dy = [_fr.visibility_error for _fr in fit_results]
plt.errorbar(_x, _y, yerr=_dy, fmt='o')
plt.axis([emin, emax, 0, 1])
self.modf.plot(show=False)
plt.xlabel('Energy [keV]')
plt.ylabel('Modulation visibility')
save_current_figure('test_modulation_constant_visibility.png',
show=self.interactive)
