def plot_polarization_angle(self, show=True, degree=False, **kwargs):
"""Plot the polarization angle as a function of energy.
"""
if self.fit_results == []:
self.fit()
_x = self.emean
_dx = [self.emean - self.emin, self.emax - self.emean]
if degree:
_y = [numpy.degrees(r.phase) for r in self.fit_results]
_dy = [numpy.degrees(r.phase_error) for r in self.fit_results]
else:
_y = [(r.phase) for r in self.fit_results]
_dy = [(r.phase_error) for r in self.fit_results]
# If there's more than one energy binning we also fit the entire
# energy interval, but we don't want the corresponding data point to
# appear in the plot, se we brutally get rid of it.
if len(self.fit_results) > 1:
_x = _x[:-1]
_dx = [_x - self.emin[:-1], self.emax[:-1] - _x]
_y = _y[:-1]
_dy = _dy[:-1]
plt.errorbar(_x, _y, _dy, _dx, fmt='o', **kwargs)
plt.xlabel('Energy [keV]')
if degree:
plt.ylabel('Polarization angle [$^\circ$]')
else:
plt.ylabel('Polarization angle [rad]')
if show:
plt.show()
def view():
_mcube = xBinnedModulationCube(MCUBE_FILE_PATH)
_mcube.fit()
_fit_results = _mcube.fit_results[0]
plt.figure('Polarization degree')
_mcube.plot_polarization_degree(show=False, color='blue')
pol_degree_spline.plot(color='lightgray',label='Spin %s'%spindegree, show=False)
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
#plt.errorbar(_energy_mean, _pol_deg, yerr=_pol_deg_err, color='blue',marker='o')
plt.legend()
plt.figure('Polarization angle')
_mcube.plot_polarization_angle(show=False, color='blue', degree=False)
pol_angle_spline.plot(color='lightgray',label='Spin %s'%spindegree, show=False)
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
#plt.errorbar(_energy_mean,_pol_angle, yerr= _pol_angle_err,color='blue',marker='o')
plt.xlim([1,10])
plt.legend()
plt.figure('MDP %s'%base_name)
mdp = _mcube.mdp99[:-1]
emean = _mcube.emean[:-1]
emin = _mcube.emin[:-1]
emax = _mcube.emax[:-1]
width = (emax-emin)/2.
plt.errorbar(emean,mdp,xerr=width, label='MDP99',marker='o',linestyle='--')
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
plt.xlim([1,10])
plt.ylabel('MPD 99\%')
plt.xlabel('Energy (keV)')
#plt.legend()
plt.show()
def plotmdp():
spin00_pol_degree_spline = buildspline(0.5)
spin00_mcube = xBinnedModulationCube(fetch_mcubepath(0.5))
spin998_pol_degree_spline = buildspline(0.998)
spin998_mcube = xBinnedModulationCube(fetch_mcubepath(0.998))
spin00_mcube.fit()
spin998_mcube.fit()
spin00_fit_results = spin00_mcube.fit_results[0]
spin998_fit_results = spin998_mcube.fit_results[0]
plt.figure('MDP')
spin00_mdp = spin00_mcube.mdp99[:-1]
spin998_mdp = spin998_mcube.mdp99[:-1]
emean = spin00_mcube.emean[:-1]
emin = spin00_mcube.emin[:-1]
emax = spin00_mcube.emax[:-1]
width = (emax-emin)/2.
plt.errorbar(emean,spin00_mdp,xerr=width, label='Spin 0.5',marker='o',linestyle='--')
plt.errorbar(emean,spin998_mdp,xerr=width, label='Spin 0.998',marker='o',linestyle='--')
plt.figtext(0.2, 0.85,'XIPE %s ks'%((SIM_DURATION*NUM_RUNS)/1000.),size=18)
plt.xlim([1,10])
plt.ylabel('MPD 99\%')
plt.xlabel('Energy (keV)')
plt.legend()
plt.show()
def makeMDPComparisonPlot(imaging_file_path):
non_imaging_file_path = imaging_file_path.replace('_imaging.txt','_non_imaging.txt')
print "Using %s for non imaging file path"%non_imaging_file_path
_phase_ave, _phase_err, mdp_imaging = numpy.loadtxt(imaging_file_path, unpack=True)
_phase_ave, _phase_err, mdp_nonimaging = numpy.loadtxt(non_imaging_file_path, unpack=True)
scale_factor = 10.
print "Improvement with imaging"
for i, phase in enumerate(_phase_ave):
imaging = 100*mdp_imaging[i]*(1/numpy.sqrt(scale_factor))
non_imaging = 100*mdp_nonimaging[i]*(1/numpy.sqrt(scale_factor))
print "%s\t Imaging (non):%s (%s) %s"%(phase,imaging,non_imaging,non_imaging/imaging)
sim_label_imaging = 'XIPE %s ks\n Imaging 15"' % (SIM_DURATION*scale_factor/1000.)
sim_label_nonimaging = 'Non imaging'
lc_label = 'Light curve'
plt.errorbar(_phase_ave, 100*mdp_imaging*(1/numpy.sqrt(scale_factor)),xerr=_phase_err, label=sim_label_imaging,fmt='o',markersize=6)
plt.errorbar(_phase_ave, 100*mdp_nonimaging*(1/numpy.sqrt(scale_factor)),xerr=_phase_err, label=sim_label_nonimaging,fmt='v',markersize=6)
pl_normalization_spline.plot(scale=10., show=False,
color='darkgray',label=lc_label)
#on_phase = 0.25, 0.45
#off_phase = 0.45,0.9
plt.axvspan(0.25, 0.45, color='r', alpha=0.45, lw=0)
plt.axvspan(0.45, 0.9, color='gray', alpha=0.25, lw=0)
plt.ylabel('MDP 99\%')
plt.legend()
plt.savefig('crab_complex_mdp_imaging_vs_nonimaging_%i_shaded.png'%(SIM_DURATION*scale_factor/1000.))
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
plt.errorbar(self.time, self.counts/self.timedel,
yerr=self.error/self.timedel, fmt='o')
plt.xlabel('Time [s]')
plt.ylabel('Rate [Hz]')
if show:
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
plt.errorbar(self.channel, self.rate, yerr=self.error, fmt='o')
plt.xlabel('PHA')
plt.ylabel('Rate [Hz]')
plt.yscale('log')
if show:
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
fig = plt.figure('Phasogram')
plt.errorbar(self.phase, self.counts, yerr=self.error, fmt='o')
plt.xlabel('Phase')
plt.ylabel('Counts/bin')
if show:
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
fig = plt.figure('Phasogram')
plt.errorbar(self.phase, self.counts, yerr=self.error, fmt='o')
plt.xlabel('Phase')
plt.ylabel('Counts/bin')
if show:
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
fig = plt.figure('Count spectrum')
plt.errorbar(self.channel, self.rate, yerr=self.error, fmt='o')
plt.xlabel('PHA')
plt.ylabel('Rate [Hz]')
plt.yscale('log')
if show:
plt.show()
def plot(self, show=True, **kwargs):
"""Overloaded plot method.
"""
if not kwargs.has_key('fmt'):
kwargs['fmt'] = 'o'
plt.errorbar(self.phase, self.counts, yerr=self.error,
xerr=0.5*self.phase_delta, **kwargs)
plt.xlabel('Phase')
plt.ylabel('Counts/bin')
if show:
plt.show()
def plot(self, show=True):
"""Overloaded plot method.
"""
fig = plt.figure('Light curve')
plt.errorbar(self.time,
self.counts / self.timedel,
yerr=self.error / self.timedel,
fmt='o')
plt.xlabel('Time [s]')
plt.ylabel('Rate [Hz]')
if show:
plt.show()
def plot_polarization_degree(self, show=True, **kwargs):
"""Plot the polarization degree as a function of energy.
"""
if self.fit_results == []:
self.fit()
_x = self.emean
_dx = [self.emean - self.emin, self.emax - self.emean]
_y = [r.polarization_degree for r in self.fit_results]
_dy = [r.polarization_degree_error for r in self.fit_results]
plt.errorbar(_x, _y, _dy, _dx, fmt='o', **kwargs)
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization degree')
if show:
plt.show()
def plot_polarization_degree(self, show=True, **kwargs):
"""Plot the polarization degree as a function of energy.
"""
if self.fit_results == []:
self.fit()
_x = self.emean
_dx = [self.emean - self.emin, self.emax - self.emean]
_y = [r.polarization_degree for r in self.fit_results]
_dy = [r.polarization_degree_error for r in self.fit_results]
plt.errorbar(_x, _y, _dy, _dx, fmt='o', **kwargs)
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization degree')
if show:
plt.show()
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)
def plot(save_plots=False):
"""
"""
sim_label = 'XIPE %s ks' % (SIM_DURATION/1000.)
mod_label = 'Input model'
_phase, _phase_err, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
_colors = ['blue']*len(_pol_deg)
plt.figure('Polarization degree')
_good_fit = _pol_deg > 2*_pol_deg_err
_bad_fit = numpy.logical_not(_good_fit)
plt.errorbar(_phase[_good_fit], _pol_deg[_good_fit],
xerr=_phase_err[_good_fit], yerr=_pol_deg_err[_good_fit],
fmt='o', label=sim_label, color='blue')
plt.errorbar(_phase[_bad_fit], _pol_deg[_bad_fit],
xerr=_phase_err[_bad_fit], yerr=_pol_deg_err[_bad_fit],
fmt='o', color='gray')
pol_degree_spline.plot(show=False, label=mod_label, color='green')
plt.axis([0., 1., 0., 0.1])
plt.legend(bbox_to_anchor=(0.37, 0.95))
plt.figtext(0.6, 0.8, '%.2f--%.2f keV' %\
(E_BINNING[0], E_BINNING[-1]), size=16)
if save_plots:
plt.savefig('gk_per_polarization_degree.png')
plt.figure('Polarization angle')
plt.errorbar(_phase[_good_fit], _pol_angle[_good_fit],
xerr=_phase_err[_good_fit], yerr=_pol_angle_err[_good_fit],
fmt='o', label=sim_label, color='blue')
plt.errorbar(_phase[_bad_fit], _pol_angle[_bad_fit],
xerr=_phase_err[_bad_fit], yerr=_pol_angle_err[_bad_fit],
fmt='o', color='gray')
pol_angle_spline.plot(show=False, label=mod_label, color='green',
scale=numpy.radians(1.))
plt.axis([0., 1., -0.1, 1.5])
plt.xlabel('Rotational phase')
plt.ylabel('Polarization angle [rad]')
plt.legend(bbox_to_anchor=(0.37, 0.95))
plt.figtext(0.6, 0.8, '%.2f--%.2f keV' %\
(E_BINNING[0], E_BINNING[-1]), size=16)
if save_plots:
plt.savefig('gk_per_polarization_angle.png')
_ebinning = zip(E_BINNING[:-1], E_BINNING[1:])
if len(_ebinning) > 1:
_ebinning.append((E_BINNING[0], E_BINNING[-1]))
for i, (_emin, _emax) in enumerate(_ebinning):
plt.figure('Phasogram %d' % i)
phasogram = xBinnedPhasogram(_phasg_file_path(i))
_scale = phasogram.counts.sum()/phasogram_spline.norm()/\
len(phasogram.counts)
phasogram_spline.plot(show=False, label=mod_label, scale=_scale,
color='green')
phasogram.plot(show=False, color='blue', label=sim_label )
plt.legend(bbox_to_anchor=(0.37, 0.95))
plt.figtext(0.65, 0.8, '%.2f--%.2f keV' % (_emin, _emax), size=16)
if save_plots:
plt.savefig('gk_per_phasogram_%d.png' % i)
plt.show()
def main():
"""Test the script Retriving RA, Dec and Index for GRB 130427A
"""
from ximpol.utils.matplotlib_ import pyplot as plt
grb_name = 'GRB 050219'
from ximpol.config.grb_swift_download import download_swift_grb_lc_file
file_path = download_swift_grb_lc_file(grb_name)
if file_path is None:
return
grb_ra, grb_dec = get_grb_position(file_path)
grb_index = get_grb_spec_index(file_path)
logger.info('Retriving information for %s:'%grb_name)
logger.info('\tPosition: RA = %fdeg, Dec = %fdeg'%(grb_ra,grb_dec))
logger.info('\tSpectral Index = %f '%grb_index)
grb_lc = parse_light_curve(file_path)
t, tp, tm, f, fp, fm = parse_light_curve_data(file_path)
plt.errorbar(t, f, yerr=[fm, fp], fmt='o')
grb_lc.plot(logx=True, logy=True)
def plot_polarization_angle(self, show=True, degree=True, **kwargs):
"""Plot the polarization angle as a function of energy.
"""
if self.fit_results == []:
self.fit()
_x = self.emean
_dx = [self.emean - self.emin, self.emax - self.emean]
if degree:
_y = [numpy.degrees(r.phase) for r in self.fit_results]
_dy = [numpy.degrees(r.phase_error) for r in self.fit_results]
else:
_y = [(r.phase) for r in self.fit_results]
_dy = [(r.phase_error) for r in self.fit_results]
plt.errorbar(_x, _y, _dy, _dx, fmt='o', **kwargs)
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization angle [$^\circ$]')
if show:
plt.show()
def plot_polarization_angle(self, show=True, degree=True, **kwargs):
"""Plot the polarization angle as a function of energy.
"""
if self.fit_results == []:
self.fit()
_x = self.emean
_dx = [self.emean - self.emin, self.emax - self.emean]
if degree:
_y = [numpy.degrees(r.phase) for r in self.fit_results]
_dy = [numpy.degrees(r.phase_error) for r in self.fit_results]
else:
_y = [(r.phase) for r in self.fit_results]
_dy = [(r.phase_error) for r in self.fit_results]
plt.errorbar(_x, _y, _dy, _dx, fmt='o', **kwargs)
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization angle [$^\circ$]')
if show:
plt.show()
def plot(save=False):
"""Plot the stuff in the analysis file.
"""
sim_label = 'XIPE %s ks' % (SIM_DURATION/1000.)
sim_label = 'OBS: %s ks' % (SIM_DURATION/1000.)
mod_label = 'Input model'
lc_label = 'Light curve'
_phase, _phase_err, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err, _index, _index_err, _norm,\
_norm_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
plt.figure('Polarization degree')
pl_normalization_spline.plot(scale=0.12, show=False, color='lightgray',
label=lc_label)
_pol_deg_err_p=numpy.where((_pol_deg+_pol_deg_err)<1.0,_pol_deg_err,1.0-_pol_deg)
_pol_deg_err_m=numpy.where((_pol_deg-_pol_deg_err)>0.0,_pol_deg_err,_pol_deg)
#if (_pol_deg+_pol_deg_err)>1.0: _pol_deg_err=1.0-yerr_p
plt.errorbar(_phase, _pol_deg, xerr=_phase_err, yerr=[_pol_deg_err_m,_pol_deg_err_p], fmt='o',
label=sim_label)
pol_degree_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., 0., 0.5])
plt.legend(bbox_to_anchor=(0.45, 0.95))
if save:
save_current_figure('crab_polarization_degree', OUTPUT_FOLDER, False)
plt.figure('Polarization angle')
pl_normalization_spline.plot(scale=0.4, offset=1.25, show=False,
color='lightgray', label=lc_label)
plt.errorbar(_phase, _pol_angle, xerr=_phase_err, yerr=_pol_angle_err,
fmt='o', label=sim_label)
pol_angle_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., 1.25, 3.])
plt.legend(bbox_to_anchor=(0.45, 0.95))
if save:
save_current_figure('crab_polarization_angle', OUTPUT_FOLDER, False)
plt.figure('PL normalization')
plt.errorbar(_phase, _norm, xerr=_phase_err, yerr=_norm_err, fmt='o',
label=sim_label)
pl_normalization_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., None, None])
plt.legend(bbox_to_anchor=(0.45, 0.95))
if save:
save_current_figure('crab_pl_norm', OUTPUT_FOLDER, False)
plt.figure('PL index')
pl_normalization_spline.plot(scale=0.18, offset=1.3, show=False,
color='lightgray', label=lc_label)
plt.errorbar(_phase, _index, xerr=_phase_err, yerr=_index_err, fmt='o',
label=sim_label)
pl_index_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., 1.3, 2.1])
plt.legend(bbox_to_anchor=(0.45, 0.95))
if save:
save_current_figure('crab_pl_index', OUTPUT_FOLDER, False)
plt.show()
def plot_bin(self, i, show=True, fit=True):
"""Plot the azimuthal distribution for the i-th energy slice.
"""
_emin = self.emin[i]
_emax = self.emax[i]
_emean = self.emean[i]
label = '%.2f-%.2f $<$%.2f$>$ keV' % (_emin, _emax, _emean)
plt.errorbar(self.phi_x, self.phi_y[i], yerr=numpy.sqrt(self.phi_y[i]),
fmt='o')
if fit:
fit_results = self.fit_bin(i)
fit_results.plot(label=label)
plt.axis([0., 2*numpy.pi, 0.0, 1.2*self.phi_y[i].max()])
plt.xlabel('Azimuthal angle [rad]')
plt.ylabel('Counts/bin')
plt.text(0.02, 0.92, label, transform=plt.gca().transAxes,
fontsize=15)
if show:
plt.show()
def makeMDP_fE_ComparisonPlot(file_path):
scale_factor = 10.
(_phase_ave, _phase_err, _energy_mean, pulsar_e_err, pulsar_e_err, mdp) =\
numpy.loadtxt(file_path, unpack=True)
print "Phase ave:",_phase_ave
print
print "Energy mean", _energy_mean
#phase_values = [0.025, 0.15, 0.35, 0.675, 0.95]
phase_values = [0.35,0.675]
on, on_phase_color = (0.35,'r')
off, off_phase_color = (0.675,'gray')
#for phase in phase_values:
plt.errorbar(_energy_mean[_phase_ave==on], 100*mdp[_phase_ave==on]*(1/numpy.sqrt(scale_factor)),xerr=pulsar_e_err[_phase_ave==on], label='On Phase',fmt='o',markersize=6,ls='--',color=on_phase_color)
plt.errorbar(_energy_mean[_phase_ave==off], 100*mdp[_phase_ave==off]*(1/numpy.sqrt(scale_factor)),xerr=pulsar_e_err[_phase_ave==off], label='Off Phase',fmt='o',markersize=6,ls='--',color=off_phase_color)
plt.legend()
plt.ylabel('MPD 99\%')
plt.xlabel('Energy (keV)')
plt.savefig('crab_complex_mdp_imaging_fE_%i.png'%(SIM_DURATION*scale_factor/1000.))
plt.show()
def plot_bin(self, i, show=True, fit=True):
"""Plot the azimuthal distribution for the i-th energy slice.
"""
_emin = self.emin[i]
_emax = self.emax[i]
_emean = self.emean[i]
label = '%.2f-%.2f $<$%.2f$>$ keV' % (_emin, _emax, _emean)
plt.errorbar(self.phi_x,
self.phi_y[i],
yerr=numpy.sqrt(self.phi_y[i]),
fmt='o')
if fit:
fit_results = self.fit_bin(i)
fit_results.plot(label=label)
view_range = 1.5 * (self.phi_y[i].max() - self.phi_y[i].min())
view_ymin = self.phi_y[i].min() - view_range
view_ymax = self.phi_y[i].max() + view_range
plt.axis([0., 2 * numpy.pi, view_ymin, view_ymax])
plt.xlabel('Azimuthal angle [rad]')
plt.ylabel('Counts/bin')
plt.text(0.02, 0.92, label, transform=plt.gca().transAxes, fontsize=15)
if show:
plt.show()
def view():
#_energy_mean,_emin, _emax, _pol_deg, _pol_deg_err, _pol_angle, \
# _pol_angle_err = \
# # numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
_mcube = xBinnedModulationCube(MCUBE_FILE_PATH)
_mcube.fit()
_fit_results = _mcube.fit_results[0]
plt.figure('Polarization degree')
_mcube.plot_polarization_degree(show=False, color='blue')
pol_degree_spline.plot(color='lightgray',label='Model %s corona'%model_type, show=False)
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
#plt.errorbar(_energy_mean, _pol_deg, yerr=_pol_deg_err, color='blue',marker='o')
plt.legend()
plt.figure('Polarization angle')
_mcube.plot_polarization_angle(show=False, color='blue', degree=False)
pol_angle_spline.plot(color='lightgray',label='Model %s corona'%model_type, show=False)
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
#plt.errorbar(_energy_mean,_pol_angle, yerr= _pol_angle_err,color='blue',marker='o')
plt.legend()
plt.figure('MDP %s'%base_name)
mdp = _mcube.mdp99
emean = _mcube.emean
emin = _mcube.emin
emax = _mcube.emax
width = (emax-emin)/2.
plt.errorbar(emean,mdp,xerr=width, label='MDP99',marker='o',linestyle='--')
plt.figtext(0.2, 0.85,'XIPE %s ks'%(SIM_DURATION/1000.),size=18)
plt.xlim([1,10])
plt.ylabel('MPD 99 %')
plt.xlabel('Energy (keV)')
#plt.legend()
plt.show()
def plot(save=False):
"""Plot the stuff in the analysis file.
"""
for j in range(len(E_BINNING)):
if (j==len(E_BINNING)-1):
analysis_file = ANALYSIS_FILE_PATH
emin=E_BINNING[0]
emax=E_BINNING[-1]
else:
analysis_file = '%s_%d' % (ANALYSIS_FILE_PATH,j)
emin=E_BINNING[j]
emax=E_BINNING[j+1]
sim_label = 'XIPE %s ks' % (SIM_DURATION/1000.)
mod_label = 'Input model'
lc_label = 'Light curve'
_phase, _phase_err, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err, _index, _index_err, _norm,\
_norm_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
plt.figure('Polarization degree (%g-%g keV)' % (emin,emax))
plt.title('Her X-1 (%g-%g keV)' % (emin,emax))
pl_normalization_spline.plot(scale=20, show=False, color='lightgray',
label=lc_label)
plt.errorbar(_phase, _pol_deg, xerr=_phase_err, yerr=_pol_deg_err, fmt='o',
label=sim_label)
pol_degree_spline.plot(show=False, label=mod_label)
# pol_degree_spline_noqed.plot(show=False, label='No QED')
plt.axis([0., 1., 0., 1.1])
plt.legend(bbox_to_anchor=(0.4, 0.5))
if save:
save_current_figure('herx1_polarization_degree_%d' % j, OUTPUT_FOLDER, False)
plt.figure('Polarization angle (%g-%g keV)' % (emin,emax))
plt.title('Her X-1 (%g-%g keV)' % (emin,emax))
pl_normalization_spline.plot(scale=60, offset=0, show=False,
color='lightgray', label=lc_label)
plt.errorbar(_phase, _pol_angle, xerr=_phase_err, yerr=_pol_angle_err,
fmt='o', label=sim_label)
pol_angle_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., 0, 3.15])
plt.legend(bbox_to_anchor=(0.4, 0.3))
if save:
save_current_figure('herx1_polarization_angle_%d' %j, OUTPUT_FOLDER, False)
plt.figure('Flux (%g-%g keV)' % (emin,emax))
plt.title('Her X-1 (%g-%g keV)' % (emin,emax))
plt.errorbar(_phase,
0.21*_norm/(2-_index)*(10.**(2.0-_index)-2.**(2.-_index)), xerr=_phase_err,
yerr=0.21*_norm_err/(2-_index)*(10.**(2-_index)-2.**(2.-_index)), fmt='o',
label=sim_label)
pl_normalization_spline.plot(scale=1,show=False, label=mod_label)
plt.axis([0., 1., None, None])
plt.legend(bbox_to_anchor=(0.75, 0.95))
if save:
save_current_figure('herx1_flux_%d' % j, OUTPUT_FOLDER, False)
plt.show()
def plot(save=False):
"""Plot the stuff in the analysis file.
"""
sim_label = 'XIPE %s ks' % (SIM_DURATION/1000.)
mod_label = 'Input model'
lc_label = 'Light curve'
_phase, _phase_err, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err, _index, _index_err, _norm,\
_norm_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
plt.figure('Polarization degree')
pl_normalization_spline.plot(scale=20, show=False, color='lightgray',
label=lc_label)
plt.errorbar(_phase, _pol_deg, xerr=_phase_err, yerr=_pol_deg_err, fmt='o',
label=sim_label)
pol_degree_spline.plot(show=False, label='QED-On')
pol_degree_spline_noqed.plot(show=False, offset=0.03, scale=1.06,
label='QED-Off')
plt.axis([0., 1., 0., 1.1])
plt.legend(bbox_to_anchor=(0.4, 0.6))
if save:
save_current_figure('4u_polarization_degree', OUTPUT_FOLDER, False)
plt.figure('Polarization angle')
pl_normalization_spline.plot(scale=60, offset=0, show=False,
color='lightgray', label=lc_label)
plt.errorbar(_phase, _pol_angle, xerr=_phase_err, yerr=_pol_angle_err,
fmt='o', label=sim_label)
pol_angle_spline.plot(show=False, label=mod_label)
plt.axis([0., 1., 0, 3.15])
plt.legend(bbox_to_anchor=(0.4, 0.3))
if save:
save_current_figure('4u_polarization_angle', OUTPUT_FOLDER, False)
plt.figure('Flux (2-10 keV)')
plt.errorbar(_phase, 0.21*_norm/(2-_index)*(10.**(2.0-_index)-2.**(2.-_index)), xerr=_phase_err, yerr=0.21*_norm_err/(2-_index)*(10.**(2-_index)-2.**(2.-_index)), fmt='o',
label=sim_label)
pl_normalization_spline.plot(scale=1,show=False, label=mod_label)
plt.axis([0., 1., None, None])
plt.legend(bbox_to_anchor=(0.75, 0.95))
if save:
save_current_figure('4u_flux', OUTPUT_FOLDER, False)
plt.show()
pol_deg = numpy.mean(pol_degree_array, axis=0)
pol_deg_err = numpy.mean(pol_degree_error_array, axis=0)
pol_ang = numpy.mean(pol_angle_array, axis=0)
pol_ang_err = numpy.mean(pol_angle_error_array, axis=0)
fig = plt.figure('Polarization degree')
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization degree')
bad = pol_deg < 3*pol_deg_err
good = numpy.invert(bad)
bad[len(E_BINNING)-1] = False
good[len(E_BINNING)-1] = False
_dx = numpy.array([mod_cube.emean - mod_cube.emin, mod_cube.emax - mod_cube.emean])
if bad.sum() > 0:
plt.errorbar(mod_cube.emean[bad], pol_deg[bad], pol_deg_err[bad],
_dx.T[bad].T, fmt='o', label='Data', color='gray')
if good.sum() > 0:
plt.errorbar(mod_cube.emean[good], pol_deg[good], pol_deg_err[good],
_dx.T[good].T, fmt='o', label='Data', color='blue')
pol_degree.plot(show=False, label='Model', linestyle='dashed', color='green')
plt.legend(bbox_to_anchor=(0.30, 0.95))
plt.axis([1, 10, 0, 0.1])
#plt.savefig('/home/nicco/%s_0_0_10x%dMs_polarization_degree.png' %\
# (NAME_LIST[0:3], TIME/100000))
fig = plt.figure('Polarization angle')
plt.xlabel('Energy [keV]')
plt.ylabel('Polarization angle [$^\circ$]')
if bad.sum() > 0:
plt.errorbar(mod_cube.emean[bad], pol_ang[bad], pol_ang_err[bad],
_dx.T[bad].T, fmt='o', label='Data', color='gray')
def calcMDP(plot=False):
mdp_file = open(MDP_OUTPUT_FILE,'w')
mdp_file.write('#Simulation time %s sec \n'%SIM_DURATION)
mdp_file.write('#Phase Ave delta phase Mean energy delta energy mdp99\n')
nebula_mcube_file = xBinnedModulationCube(NEBULA_MCUBE_FILE_PATH)
nebula_counts = nebula_mcube_file.counts
nebula_mdp = nebula_mcube_file.mdp99
txt = "Pulsar phase\t Emin - Emax\t Pulsar counts\t Nebula counts\t MDP\n"
MDP99_PULSAR = []
phase = []
phase_err = []
for i, (_min, _max) in enumerate(PHASE_BINS):
#zip(PHASE_BINS[:-1],PHASE_BINS[1:])):
pulse_diff = numpy.fabs(_max -_min)
_phase_ave = 0.5*(_min + _max)
phase.append(_phase_ave)
_phase_err = 0.5*(_max - _min)
phase_err.append(_phase_err)
pulsar_phase_mcube_file = xBinnedModulationCube(_mcube_file_path(i))
pulsar_emean = pulsar_phase_mcube_file.emean
for j, _energy_mean in enumerate(pulsar_emean):
pulsar_emin = pulsar_phase_mcube_file.emin[j]
pulsar_emax = pulsar_phase_mcube_file.emax[j]
pulsar_e_err = 0.5*(pulsar_emax-pulsar_emin)
pulsar_phase_counts = pulsar_phase_mcube_file.counts[j]
pulsar_mdp = pulsar_phase_mcube_file.mdp99[j]
#scale the nebula counts for the time used for the pulsar phase
scaled_nebula_counts = pulse_diff*nebula_counts[j]
count_sqrt = numpy.sqrt(pulsar_phase_counts + scaled_nebula_counts)
eff_mu_pulsar = pulsar_phase_mcube_file.effective_mu[j]
mdp = 4.292/eff_mu_pulsar*count_sqrt/pulsar_phase_counts
MDP99_PULSAR.append(100*mdp)
_data = (_phase_ave, _phase_err, _energy_mean, pulsar_e_err, pulsar_e_err, mdp)
_fmt = ('%.4e ' * len(_data)).strip()
_fmt = '%s\n' % _fmt
_line = _fmt % _data
mdp_file.write(_line)
#txt += "%s\t %s - %s\t %s\t %s\t %.3f\n"%(PHASE_BINS[i], pulsar_emin[0], pulsar_emax[0], pulsar_phase_counts[0], scaled_nebula_counts[0], 100*mdp)
MDP99_PULSAR = numpy.array(MDP99_PULSAR)
PHASE = numpy.array(phase)
mdp_file.close()
if plot:
scale_factor = 10
sim_label = 'XIPE %s ks' % (SIM_DURATION*scale_factor/1000.)
lc_label = 'Light curve'
plt.errorbar(PHASE, MDP99_PULSAR*(1/numpy.sqrt(10)),xerr=phase_err, label=sim_label,fmt='o')
pl_normalization_spline.plot(scale=10., show=False,
color='lightgray',label=lc_label)
plt.ylabel('MDP 99\%')
plt.legend()
plt.savefig('crab_complex_mdp_nonimaging_%i.png'%(SIM_DURATION*scale_factor/1000.))
#plt.show()
print txt
def plot(save=False):
"""Plot the stuff in the analysis file.
"""
def draw_time_grid(color='blue'):
"""
"""
times = [3600., 3600.*24., 3600.*24.*7.]
labels = ['1 hour', '1 day', '1 week']
for t, l in zip(times, labels):
plt.axvline(t, linestyle='dashed', color=color)
ymin, ymax = plt.gca().get_ylim()
y = ymin + 1.05*(ymax - ymin)
plt.text(t, y, l, ha='center', color=color)
sim_label = 'XIPE'
mod_label = 'Input model'
lc_label = 'Light curve'
_time, _time_errp, _time_errm, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err, _index, _index_err, _norm,\
_norm_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
logger.info(_time)
logger.info((_time_errp + _time_errm)/3600.)
_pol_angle = numpy.degrees(_pol_angle)
_pol_angle_err = numpy.degrees(_pol_angle_err)
plt.figure('Polarization degree')
pol_degree_spline.plot(show=False, label=mod_label, logx=True)
plt.errorbar(_time, _pol_deg, xerr=[_time_errm, _time_errp],
yerr=_pol_deg_err, fmt='o', label=sim_label)
plt.axis([100., 1e6, 0., 0.6])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_polarization_degree',
OUTPUT_FOLDER, False)
plt.figure('Polarization angle')
_x = pol_degree_spline.x
_y = numpy.full(len(_x), polarization_angle(_x, None, None, None))
_y = numpy.degrees(_y)
fmt = dict(xname='Time', xunits='s', yname='Polarization angle',
yunits=r'$^\circ$')
_s = xInterpolatedUnivariateSpline(_x, _y, **fmt)
_s.plot(logx=True, show=False, label=mod_label)
plt.errorbar(_time, _pol_angle, xerr=[_time_errm, _time_errp],
yerr=_pol_angle_err, fmt='o', label=sim_label)
plt.axis([100., 1e6, None, None])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_polarization_angle',
OUTPUT_FOLDER, False)
plt.figure('PL index')
_y = numpy.full(len(_x), PL_INDEX)
fmt = dict(xname='Time', xunits='s', yname='PL index')
_s = xInterpolatedUnivariateSpline(_x, _y, **fmt)
_s.plot(logx=True, show=False, label=mod_label)
plt.errorbar(_time, _index, xerr=[_time_errm, _time_errp], yerr=_index_err,
fmt='o', label=sim_label)
plt.axis([100., 1e6, None, None])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_pl_index', OUTPUT_FOLDER, False)
#plt.figure('PL normalization')
#plt.errorbar(_time, _norm, xerr=[_time_errm, _time_errp], yerr=_norm_err,
# fmt='o', label=sim_label)
#pl_normalization_spline.plot(show=False, label=mod_label)
#plt.axis([100., 1e6, None, None])
#plt.legend(bbox_to_anchor=(0.4, 0.95))
#draw_time_grid()
#if save:
# save_current_figure('grb130427_swift_pl_norm', OUTPUT_FOLDER, False)
plt.figure('Light curve')
lc = xBinnedLightCurve(_lc_file_path())
lc.plot(show=False)
# This should be implemented in the binned LC class.
plt.xscale('log')
plt.yscale('log')
plt.axis([100., 1e6, None, None])
draw_time_grid()
if save:
save_current_figure('grb130427_swift_lc', OUTPUT_FOLDER, False)
plt.show()
def plot(save=False):
"""Plot the stuff in the analysis file.
"""
def draw_time_grid(color='blue'):
"""
"""
times = [3600., 3600. * 24., 3600. * 24. * 7.]
labels = ['1 hour', '1 day', '1 week']
for t, l in zip(times, labels):
plt.axvline(t, linestyle='dashed', color=color)
ymin, ymax = plt.gca().get_ylim()
y = ymin + 1.05 * (ymax - ymin)
plt.text(t, y, l, ha='center', color=color)
sim_label = 'XIPE'
mod_label = 'Input model'
lc_label = 'Light curve'
_time, _time_errp, _time_errm, _pol_deg, _pol_deg_err, _pol_angle,\
_pol_angle_err, _index, _index_err, _norm,\
_norm_err = numpy.loadtxt(ANALYSIS_FILE_PATH, unpack=True)
logger.info(_time)
logger.info((_time_errp + _time_errm) / 3600.)
_pol_angle = numpy.degrees(_pol_angle)
_pol_angle_err = numpy.degrees(_pol_angle_err)
plt.figure('Polarization degree')
pol_degree_spline.plot(show=False, label=mod_label, logx=True)
plt.errorbar(_time,
_pol_deg,
xerr=[_time_errm, _time_errp],
yerr=_pol_deg_err,
fmt='o',
label=sim_label)
plt.axis([100., 1e6, 0., 0.6])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_polarization_degree',
OUTPUT_FOLDER, False)
plt.figure('Polarization angle')
_x = pol_degree_spline.x
_y = numpy.full(len(_x), polarization_angle(_x, None, None, None))
_y = numpy.degrees(_y)
fmt = dict(xname='Time',
xunits='s',
yname='Polarization angle',
yunits=r'$^\circ$')
_s = xInterpolatedUnivariateSpline(_x, _y, **fmt)
_s.plot(logx=True, show=False, label=mod_label)
plt.errorbar(_time,
_pol_angle,
xerr=[_time_errm, _time_errp],
yerr=_pol_angle_err,
fmt='o',
label=sim_label)
plt.axis([100., 1e6, None, None])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_polarization_angle',
OUTPUT_FOLDER, False)
plt.figure('PL index')
_y = numpy.full(len(_x), PL_INDEX)
fmt = dict(xname='Time', xunits='s', yname='PL index')
_s = xInterpolatedUnivariateSpline(_x, _y, **fmt)
_s.plot(logx=True, show=False, label=mod_label)
plt.errorbar(_time,
_index,
xerr=[_time_errm, _time_errp],
yerr=_index_err,
fmt='o',
label=sim_label)
plt.axis([100., 1e6, None, None])
plt.legend(bbox_to_anchor=(0.4, 0.95))
draw_time_grid()
if save:
save_current_figure('grb130427_swift_pl_index', OUTPUT_FOLDER, False)
#plt.figure('PL normalization')
#plt.errorbar(_time, _norm, xerr=[_time_errm, _time_errp], yerr=_norm_err,
# fmt='o', label=sim_label)
#pl_normalization_spline.plot(show=False, label=mod_label)
#plt.axis([100., 1e6, None, None])
#plt.legend(bbox_to_anchor=(0.4, 0.95))
#draw_time_grid()
#if save:
# save_current_figure('grb130427_swift_pl_norm', OUTPUT_FOLDER, False)
plt.figure('Light curve')
lc = xBinnedLightCurve(_lc_file_path())
lc.plot(show=False)
# This should be implemented in the binned LC class.
plt.xscale('log')
plt.yscale('log')
plt.axis([100., 1e6, None, None])
draw_time_grid()
if save:
save_current_figure('grb130427_swift_lc', OUTPUT_FOLDER, False)
plt.show()