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)