def all_energy_table(pwnlist):
data = yaml.load(open(expandvars('$pwncode/data/pwncat2_phase_lande.yaml')))
table = OrderedDefaultDict(list)
psr_name='PSR'
phase_name='Phase'
optimal_emin_name='Optimal Emin' if confluence else r'Optimal $E_\text{min}$'
optimal_radius_name='Optimal radius'
for pwn in pwnlist:
print pwn
table[psr_name].append(format.pwn(pwn))
phase=PhaseRange(data[pwn]['phase'])
optimal_emin=data[pwn]['optimal_emin']
optimal_radius=data[pwn]['optimal_radius']
table[phase_name].append(phase.pretty_format())
table[optimal_emin_name].append('%.2f' % optimal_emin)
table[optimal_radius_name].append('%.2f' % optimal_radius)
print yaml.dump(table)
if confluence:
write_confluence(table, filebase='phase_range')
else:
write_latex(table, filebase='phase_range')
def plot_phaseogram(ft1,
nbins=100,
filename=None,
title=None,
phase_range=None,
data_kwargs=dict(),
phase_range_kwargs=dict(),
repeat_phase=False,
axes=None,
offset=None,
**kwargs):
""" Simple code to plot a phaseogram. """
phases = get_phases(ft1, **kwargs)
if offset is not None:
phases += offset
phases = phases % 1
if axes is None:
fig = P.figure(None, figsize=(5, 5))
axes = fig.add_subplot(111)
bins = np.linspace(0, 1, nbins + 1)
x, y = histpoints(phases, bins=bins)
if repeat_phase:
x, y = np.append(x, x + 1), np.append(y, y)
k = dict(color='black')
k.update(data_kwargs)
P.plot(x, y, **k)
axes.set_ylim(0)
axes.set_xlim(0, 2 if repeat_phase else 1)
if title is not None:
axes.set_title(title)
axes.set_xlabel('Phase')
axes.set_ylabel('Counts')
axes.grid = True
if phase_range is not None:
phase_range = PhaseRange(phase_range)
if offset is not None:
phase_range = phase_range.offset(offset)
kwargs = dict(alpha=0.25, color='blue')
kwargs.update(phase_range_kwargs)
phase_range.axvspan(axes=axes,
phase_offsets=[0, 1] if repeat_phase else 0,
**kwargs)
if filename is not None:
P.savefig(filename)
return axes, bins
def plot_phaseogram(ft1, nbins=100, filename=None, title=None, phase_range=None,
data_kwargs=dict(),
phase_range_kwargs=dict(), repeat_phase=False, axes=None,
offset=None,
**kwargs):
""" Simple code to plot a phaseogram. """
phases = get_phases(ft1, **kwargs)
if offset is not None:
phases += offset
phases = phases % 1
if axes is None:
fig = P.figure(None, figsize=(5,5))
axes = fig.add_subplot(111)
bins = np.linspace(0,1,nbins+1)
x, y = histpoints(phases, bins=bins)
if repeat_phase:
x,y = np.append(x, x+1), np.append(y, y)
k = dict(color='black')
k.update(data_kwargs)
P.plot(x,y, **k)
axes.set_ylim(0)
axes.set_xlim(0,2 if repeat_phase else 1)
if title is not None:
axes.set_title(title)
axes.set_xlabel('Phase')
axes.set_ylabel('Counts')
axes.grid=True
if phase_range is not None:
phase_range = PhaseRange(phase_range)
if offset is not None:
phase_range = phase_range.offset(offset)
kwargs=dict(alpha=0.25, color='blue')
kwargs.update(phase_range_kwargs)
phase_range.axvspan(axes=axes,
phase_offsets=[0,1] if repeat_phase else 0,
**kwargs)
if filename is not None:
P.savefig(filename)
return axes, bins
def plot_phase_vs_time(ft1,
filename=None,
title=None,
phase_range=None,
phase_range_kwargs=dict(),
axes=None,
**kwargs):
""" Simple code to plot phase vs time. """
phases, times = get_phases_and_times(ft1, **kwargs)
if axes is None:
# here, put a 2d histogram
fig = P.figure(None, figsize=(5, 5))
fig.subplots_adjust(left=0.2)
axes = fig.add_subplot(111)
# Note about 2D histograms:
# http://www.physics.ucdavis.edu/~dwittman/Matplotlib-examples/
hist, xedges, yedges = np.histogram2d(phases,
times,
bins=(50, 50),
range=[[0, 1],
[min(times),
max(times)]])
extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
axes.imshow(hist.T,
extent=extent,
interpolation='nearest',
origin='lower',
aspect='auto')
if phase_range is not None:
kwargs = dict(alpha=0.5, color='white')
kwargs.update(phase_range_kwargs)
PhaseRange(phase_range).axvspan(axes=axes, **kwargs)
axes.set_xlabel('phase')
axes.set_ylabel('MJD')
if title is not None:
axes.set_title(title)
if filename is not None:
P.savefig(filename)
return axes
def load_pwn(filename, savedir=None, **kwargs):
""" By default, pwn roi's are not loadable. """
d = cPickle.load(open(expandvars(filename), 'r'))
extra = d['extra']
ft1 = extra['unphased_ft1']
ltcube = extra['unphased_ltcube']
phase = PhaseRange(extra['phase'])
if exists(ft1) and exists(ltcube) and exists(phase):
return load(filename, **kwargs)
if savedir is None:
save_data = False
savedir = mkdtemp(prefix='/scratch/')
else:
if not os.path.exists(savedir):
os.makedirs(savedir)
save_data = True
print 'new savedir is', savedir
phased_ft1 = PWNRegion.phase_ft1(ft1, phase, savedir)
phased_ltcube = PWNRegion.phase_ltcube(ltcube, phase, savedir)
binfile = join(savedir, 'binned_phased.fits')
roi = load(filename,
ft1files=phased_ft1,
ltcube=phased_ltcube,
binfile=binfile,
**kwargs)
if not save_data:
roi.__del__ = lambda x: shutil.rmtree(savedir)
return roi
def get_results(self,
pwn,
require_all_exists=True,
get_seds=True,
get_variability=True,
get_altdiff=True,
verbosity=None):
filename = join(self.fitdir, pwn, 'results_%s_general.yaml' % pwn)
if verbosity or (verbosity is None and self.verbosity):
print 'Getting results for %s' % pwn
if not exists(filename):
raise PWNResultsException("%s does not exist" % filename)
results = loaddict(filename)
for hypothesis in self.all_hypotheses:
results[hypothesis] = dict()
for code in ['gtlike', 'pointlike']:
for hypothesis in self.all_hypotheses:
filename = join(
self.fitdir, pwn,
'results_%s_%s_%s.yaml' % (pwn, code, hypothesis))
if exists(filename):
results[hypothesis][code] = loaddict(filename)
else:
if require_all_exists:
raise PWNResultsException("%s does not exist" %
filename)
if get_variability:
for hypothesis in ['at_pulsar', 'point']:
filename = join(
self.fitdir, pwn,
'results_%s_variability_%s.yaml' % (pwn, hypothesis))
if exists(filename):
results[hypothesis]['variability'] = loaddict(filename)
else:
if require_all_exists:
raise PWNResultsException('%s does not exist' %
filename)
if get_altdiff:
for hypothesis in ['point']:
results[hypothesis]['gtlike']['altdiff'] = dict()
for dist in ['SNR', 'Lorimer']:
for halo in [4, 10]:
for TS in [150, 100000]:
filename = join(
self.fitdir, pwn,
'results_%s_altdiff_dist_%s_halo_%s_TS_%s_%s.yaml'
% (pwn, dist, halo, TS, hypothesis))
if exists(filename):
results[hypothesis]['gtlike']['altdiff'][
dist, halo, TS] = loaddict(filename)
else:
results[hypothesis]['gtlike']['altdiff'][
dist, halo, TS] = None
if get_seds:
for hypothesis in self.all_hypotheses:
for code, all_binning in [['gtlike', ['1bpd', '2bpd', '4bpd']],
['pointlike', ['4bpd']]]:
results[hypothesis][code]['seds'] = dict()
for binning in all_binning:
filename = join(
self.fitdir, pwn, 'seds', 'sed_%s_%s_%s_%s.yaml' %
(code, binning, hypothesis, pwn))
if exists(filename):
results[hypothesis][code]['seds'][
binning] = loaddict(filename)
else:
if require_all_exists:
raise PWNResultsException("%s does not exist" %
filename)
results['raw_phase'] = PhaseRange(results['phase'])
del results['phase'] # to avoid ambiguity
if self.phase_shift is not None:
import pickle
ps = pickle.load(open(self.phase_shift))
shift = float(ps[pwn.replace('PSRJ', 'J')]['shift'])
""" Convention taken from private correspondence with Matthew Kerr:
me: ok
so i am trying to implement phase shifts in my analysis
did you decide the right way to do it
Matthew: it seems to be +
me: so correct_phase = phase_in_file + shift
Matthew: yes """
results['shifted_phase'] = results['raw_phase'].offset(shift)
return results
def setup_region(name,pwndata,phase, free_radius=5, tempdir=None, maxroi=10,
xml=None, **kwargs):
"""Name of the source
pwndata Yaml file
returns pointlike ROI.
"""
phase = PhaseRange(phase)
sources=yaml.load(open(pwndata))
catalog_name=sources[name]['catalog']['2fgl']
ltcube=sources[name]['ltcube']
pulsar_position=SkyDir(*sources[name]['dir'])
ft2=sources[name]['ft2']
ft1=sources[name]['ft1']
catalog=FermiCatalog(e("$FERMI/catalogs/gll_psc_v02.fit"))
catalog=Catalog2FGL('$FERMI/catalogs/gll_psc_v05.fit',
latextdir='$FERMI/extended_archives/gll_psc_v05_templates',
free_radius=free_radius)
catalog_source=catalog.get_source(catalog_name)
center=catalog_source.skydir
if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')
binfile=j(tempdir,'binned_phased.fits')
if np.allclose(phase.phase_fraction,1):
phased_ltcube = ltcube
phased_ft1 = ft1
else:
# create a temporary ltcube scaled by the phase factor
phased_ltcube=j(tempdir,'phased_ltcube.fits')
phase_ltcube(ltcube,phased_ltcube, phase=phase)
# apply phase cut to ft1 file
phased_ft1 = j(tempdir,'ft1_phased.fits')
phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase.tolist(dense=False))
from uw.like.pointspec import DataSpecification
ds = DataSpecification(
ft1files = phased_ft1,
ft2files = ft2,
ltcube = phased_ltcube,
binfile = binfile)
sa = SpectralAnalysis(ds,
binsperdec = 8,
emin = 100,
emax = 100000,
irf = "P6_V11_DIFFUSE",
roi_dir = center,
maxROI = maxroi,
minROI = maxroi)
if xml is None:
roi=sa.roi(
diffuse_sources=get_default_diffuse(diffdir="/afs/slac/g/glast/groups/diffuse/mapcubes",
gfile="gll_iem_v02.fit",
ifile="isotropic_iem_v02.txt"),
catalogs = catalog,
phase_factor =1,
**kwargs)
else:
roi=sa.roi_from_xml(
roi_dir=center,
xmlfile = xml,
phase_factor =1,
**kwargs)
print 'bins ',roi.bin_edges
roi.del_source(catalog_name)
return roi
def get_roi(self,
name,
phase,
fit_emin,
fit_emax,
binsperdec,
extended=False,
roi_size=10,
catalog_kwargs=dict(),
**kwargs):
""" Sets up the ROI for studying a LAT Pulsar in the off pulse. """
sourcedict = yaml.load(open(self.pwndata))[name]
ltcube = sourcedict['ltcube']
pulsar_position = SkyDir(*sourcedict['cel'])
ft1 = sourcedict['ft1']
ft2 = sourcedict['ft2']
source = PWNRegion.get_source(name,
position=pulsar_position,
fit_emin=fit_emin,
fit_emax=fit_emax,
sigma=0.1,
extended=extended)
sources = [source]
roi_dir = pulsar_position
phase = PhaseRange(phase)
point_sources, diffuse_sources = [], []
for source in sources:
if isinstance(source, PointSource):
point_sources.append(source)
else:
diffuse_sources.append(source)
diffuse_sources += PWNRegion.get_background()
catalog = PWNRegion.get_catalog(**catalog_kwargs)
binfile = join(self.savedir, 'binned_phased.fits')
phased_ltcube = PWNRegion.phase_ltcube(ltcube, phase, self.savedir)
phased_ft1 = PWNRegion.phase_ft1(ft1, phase, self.savedir)
ds = DataSpecification(ft1files=phased_ft1,
ft2files=ft2,
ltcube=phased_ltcube,
binfile=binfile)
print 'For now, 4 bins per decade. Eventually, this will have to be better.'
sa = SpectralAnalysis(ds,
binsperdec=binsperdec,
emin=100,
emax=1000000,
irf="P7SOURCE_V6",
roi_dir=roi_dir,
maxROI=roi_size,
minROI=roi_size,
event_class=0)
roi = sa.roi(point_sources=point_sources,
diffuse_sources=diffuse_sources,
catalogs=catalog,
phase_factor=1,
fit_emin=fit_emin,
fit_emax=fit_emax,
**kwargs)
print 'bins ', roi.bin_edges
roi.extra = dict(unphased_ft1=ft1, unphased_ltcube=ltcube, phase=phase)
self.roi = roi
return roi
