def plot(
self,
filename=None,
axes=None,
fignum=None,
figsize=(5.5, 4.5),
spectral_kwargs=dict(color='red', zorder=1.9),
cutoff_kwargs=dict(color='blue', zorder=1.9),
):
if axes is None:
fig = P.figure(fignum, figsize)
axes = SpectralAxes(fig=fig,
rect=(0.22, 0.15, 0.75, 0.8),
flux_units=self.flux_units,
energy_units=self.energy_units)
fig.add_axes(axes)
axes.set_xlim_units(100 * units.MeV, 10**5.5 * units.MeV)
# plot sed
sed = SED(self.sed_4bpd)
sed.plot_points(axes=axes)
if self.hypothesis == 'at_pulsar':
# plot power-law limits
ul = UpperLimit(self.powerlaw_limit)
ul.plot(axes=axes, color='orange', zorder=1.9)
axes.autoscale(False)
# plot spectral model
sp = SpectrumPlotter(axes=axes)
sp.plot(self.spectral_model, **spectral_kwargs)
sp.plot_error(self.spectral_model, alpha=0.25, **spectral_kwargs)
if self.hypothesis != 'extended':
# plot cutoff model
sp.plot(self.cutoff_model, **cutoff_kwargs)
sp.plot_error(self.cutoff_model, alpha=0.25, **cutoff_kwargs)
if self.hypothesis == 'at_pulsar':
ul = UpperLimit(self.cutoff_limit)
ul.plot(axes=axes, color='purple', zorder=1.9)
#if self.code == 'gtlike':
# bf = BandFitter(self.bandfits)
# bf.plot(axes=axes,
# spectral_kwargs=dict(color='green',zorder=1.9),
# spectral_error_kwargs=dict(color='green', alpha=0.25))
if filename is not None:
P.savefig(expandvars(filename))
return axes
def plot(self, filename=None, axes=None, title=None,
sed_results=None,
fignum=None, figsize=(4,4),
model_0_kwargs=dict(color='red', zorder=0),
model_1_kwargs=dict(color='blue', zorder=0),
sed_kwargs=dict(),
plot_kwargs=dict(),):
""" Plots the cutoff test performed of a spectrum using the function
gtlike_test_cutoff.
Input:
cutoff_dict: created by gtlike_test_cutoff
sed_dict: created by GtlikeSED.todict(). Can also be a yaml
file created by GtlikeSED.save().
model_0_kwargs: kwargs for model_0's plot
model_1_kwargs: kwargs for model_0's plot
sed_kwargs: kwargs to pass into SED
E.G. flux_units, flux_units, figsize, ...
"""
if axes is None:
fig = P.figure(fignum,figsize)
axes = SpectralAxes(fig=fig, rect=(0.22,0.15,0.75,0.8),
flux_units=self.flux_units,
energy_units=self.energy_units)
fig.add_axes(axes)
energy = self.results['energy']
axes.set_xlim_units(energy['emin']*units.fromstring(energy['energy_units']),
energy['emax']*units.fromstring(energy['energy_units']))
if sed_results is not None:
sed = SED(sed_results)
sed.plot_points(axes=axes, **sed_kwargs)
sp = SpectrumPlotter(axes=axes)
sp.plot(self.results['hypothesis_0']['spectrum'],
autoscale=False, **model_0_kwargs)
sp.plot_error(self.results['hypothesis_0']['spectrum'],
self.results['hypothesis_0']['spectrum']['covariance_matrix'],
alpha=0.5,
autoscale=False, **model_0_kwargs)
sp.plot(self.results['hypothesis_1']['spectrum'],
autoscale=False, **model_1_kwargs)
sp.plot_error(self.results['hypothesis_1']['spectrum'],
self.results['hypothesis_1']['spectrum']['covariance_matrix'],
alpha=0.5,
autoscale=False, **model_1_kwargs)
if title is not None: axes.set_title(title)
if filename is not None:
P.savefig(expandvars(filename))
return axes
def plot(self, filename=None, axes=None,
fignum=None, figsize=(5.5,4.5),
spectral_kwargs=dict(color='red', zorder=1.9),
cutoff_kwargs=dict(color='blue', zorder=1.9),
):
if axes is None:
fig = P.figure(fignum,figsize)
axes = SpectralAxes(fig=fig,
rect=(0.22,0.15,0.75,0.8),
flux_units=self.flux_units,
energy_units=self.energy_units)
fig.add_axes(axes)
axes.set_xlim_units(100*units.MeV, 10**5.5*units.MeV)
# plot sed
sed = SED(self.sed_4bpd)
sed.plot_points(axes=axes)
if self.hypothesis == 'at_pulsar':
# plot power-law limits
ul=UpperLimit(self.powerlaw_limit)
ul.plot(axes=axes, color='orange', zorder=1.9)
axes.autoscale(False)
# plot spectral model
sp=SpectrumPlotter(axes=axes)
sp.plot(self.spectral_model, **spectral_kwargs)
sp.plot_error(self.spectral_model, alpha=0.25, **spectral_kwargs)
if self.hypothesis != 'extended':
# plot cutoff model
sp.plot(self.cutoff_model, **cutoff_kwargs)
sp.plot_error(self.cutoff_model, alpha=0.25, **cutoff_kwargs)
if self.hypothesis == 'at_pulsar':
ul=UpperLimit(self.cutoff_limit)
ul.plot(axes=axes, color='purple', zorder=1.9)
#if self.code == 'gtlike':
# bf = BandFitter(self.bandfits)
# bf.plot(axes=axes,
# spectral_kwargs=dict(color='green',zorder=1.9),
# spectral_error_kwargs=dict(color='green', alpha=0.25))
if filename is not None:
P.savefig(expandvars(filename))
return axes
def plot(self, filename):
sed = SED(self.sed_points)
# Plot SED points
axes = sed.plot()
# Plot model0, model1
sed.plot_spectrum(self.model0, axes=axes, label='model0')
sed.plot_spectrum(self.comprehensive_model, axes=axes, label='model1')
sed.plot_spectrum(self.comprehensive_model_start,
axes=axes,
label='model1 (start)')
axes.legend()
P.savefig(filename)
def plot(self, filename):
sed = SED(self.sed_points)
# Plot SED points
axes=sed.plot()
# Plot model0, model1
sed.plot_spectrum(self.model0, axes=axes, label='model0')
sed.plot_spectrum(self.comprehensive_model, axes=axes, label='model1')
sed.plot_spectrum(self.comprehensive_model_start, axes=axes, label='model1 (start)')
axes.legend()
P.savefig(filename)
axes_pad=0.0,
axes_class=(SpectralAxes, dict(energy_units='GeV')),
)
for i,pwn in enumerate(cutoff_candidates):
print i,pwn
axes=grid[i]
r = classifier.get_results(pwn)
spectrum = r['spectrum']
sed = r['sed_4bpd']
s = SED(sed)
s.plot_points(axes=axes, zorder=2.1)
sp = SpectrumPlotter(axes=axes)
sp.plot(spectrum, autoscale=False, color='red' if not bw else 'grey', zorder=1.9)
label_axes(grid)
grid[0].set_ylabel('')
grid[4].set_ylabel('')
for i in range(nrows*ncols):
axes=grid[i]
#axes.set_xlim_units(10**2*units.MeV,10**5.5*units.MeV)
axes.set_xlim(0.1,10**2.5)
def plot(
self,
filename=None,
axes=None,
title=None,
sed_results=None,
fignum=None,
figsize=(4, 4),
model_0_kwargs=dict(color='red', zorder=0),
model_1_kwargs=dict(color='blue', zorder=0),
sed_kwargs=dict(),
plot_kwargs=dict(),
):
""" Plots the cutoff test performed of a spectrum using the function
gtlike_test_cutoff.
Input:
cutoff_dict: created by gtlike_test_cutoff
sed_dict: created by GtlikeSED.todict(). Can also be a yaml
file created by GtlikeSED.save().
model_0_kwargs: kwargs for model_0's plot
model_1_kwargs: kwargs for model_0's plot
sed_kwargs: kwargs to pass into SED
E.G. flux_units, flux_units, figsize, ...
"""
if axes is None:
fig = P.figure(fignum, figsize)
axes = SpectralAxes(fig=fig,
rect=(0.22, 0.15, 0.75, 0.8),
flux_units=self.flux_units,
energy_units=self.energy_units)
fig.add_axes(axes)
energy = self.results['energy']
axes.set_xlim_units(
energy['emin'] * units.fromstring(energy['energy_units']),
energy['emax'] * units.fromstring(energy['energy_units']))
if sed_results is not None:
sed = SED(sed_results)
sed.plot_points(axes=axes, **sed_kwargs)
sp = SpectrumPlotter(axes=axes)
sp.plot(self.results['hypothesis_0']['spectrum'],
autoscale=False,
**model_0_kwargs)
sp.plot_error(
self.results['hypothesis_0']['spectrum'],
self.results['hypothesis_0']['spectrum']['covariance_matrix'],
alpha=0.5,
autoscale=False,
**model_0_kwargs)
sp.plot(self.results['hypothesis_1']['spectrum'],
autoscale=False,
**model_1_kwargs)
sp.plot_error(
self.results['hypothesis_1']['spectrum'],
self.results['hypothesis_1']['spectrum']['covariance_matrix'],
alpha=0.5,
autoscale=False,
**model_1_kwargs)
if title is not None: axes.set_title(title)
if filename is not None:
P.savefig(expandvars(filename))
return axes
