def __getitem__(self, name):
""" returns an HParray object corresponding to the name
"""
if name == 'galactic':
return hpm.HParray(name, self.df['final'] - self.df['src'])
if name == 'isotropic':
return hpm.HParray(name, self.df['egb'])
if name == 'sources':
return hpm.HParray(name, self.df['src'] + self.df['UN'])
return hpm.HParray(name, self.df[name])
def check_bubble_maps(cubefile):
if not os.path.exists(cubefile):
bubble = [
diffuse.HealpixCube(f) for f in [
'../uw8600/bubbles.fits', '../uw8604/bubbles_v2.fits',
'../uw8605/bubbles_v3.fits', '../uw8606/bubbles_v4.fits'
]
]
for b in bubble:
b.load()
# multiply them all together
energies = bubble[0].energies
pr = np.array([b.vec for b in bubble[0]])
for bb in bubble[1:]:
pr *= np.array([b.vec for b in bb])
t = [
healpix_map.HParray('{:.0f} MeV'.format(energy), v)
for energy, v in zip(energies, pr)
]
bcube = healpix_map.HEALPixFITS(t, energies=energies)
healpix_map.multi_ait(t,
vmin=0.8,
vmax=2.0,
cmap=plt.get_cmap('jet'),
grid_color='grey',
cblabel='ratio to diffuse',
title='bubbles correction to diffuse')
bcube.write(cubefile)
else:
print 'Using existing file {}'.format(cubefile)
def __init__(self,
modelname,
energy=131,
root='/nfs/farm/g/glast/g/catalog/pointlike/fermi/gardian/',
reload=False):
from astropy.table import Table
cfile = '{}{}_{:d}.fits'.format(root, modelname, energy)
if not os.path.exists(cfile) or reload:
print 'Will create file {}'.format(cfile)
GarDian(modelname=mname, energy=energy).write(cfile)
assert os.path.exists(cfile), 'File "{}" not found'.format(cfile)
self.df = Table.read(cfile, hdu=1).to_pandas()
self.modelname, self.energy = modelname, energy
self.nside = nside = int(np.sqrt(len(self.df) / 12))
print 'read file {}'.format(cfile)
# add locations to the DataFrame
glon, glat = healpy.pix2ang(nside, range(12 * nside**2), lonlat=True)
glon[glon > 180] -= 360
self.df['glon'] = glon
self.df['glat'] = glat
# a column with combined sources
self.df['sources'] = self.df['src'] + self.df['UN']
data, model = np.array(self.df['counts']), np.array(self.df['final'])
resid = (data - model) / np.sqrt(model)
#print resid.mean(), resid.std()
self.pulls = hpm.HParray('f{} pulls'.format(energy),
(data - model) / np.sqrt(model))
self.df['pull'] = self.pulls.vec
self.label = '{} @ {:.0f} MeV'.format(self.modelname, self.energy)
def setEnergy(self, energy):
self.load()
if energy == self.energy: return
self.eindex = -1
for i, e in enumerate(self.energies):
if abs(e - energy) < 0.01 * e:
self.eindex = i
self.energy = energy
break
assert self.eindex >= 0, 'Energy %.0f not found' % energy
cname = self.col_names[self.eindex]
self.hpm = healpix_map.HParray(cname, self.columns.field(cname))
def ait_plot(self,
vmin=0,
vmax=None,
log=False,
ax=None,
cmap=plt.get_cmap('coolwarm'),
**kwargs):
y = hpm.HParray('', self.map)
y.plot(title='{} @ {:.2f} GeV'.format(self.cname, self.energy / 1e3),
ait_kw=dict(),
log=log,
vmin=vmin,
vmax=vmax,
cmap=cmap,
**kwargs).grid()
def modify_by_patch(self, patch, newfile=None):
modlayer = []
for i, layer in enumerate((self)):
name = layer.name
a = layer.vec
if i < len(patch):
p = patch[i]
else:
p = patch[-1]
b = p.vec
print layer.name, ',',
modlayer.append(
healpix_map.HParray(layer.name, healpix_map.multiply(a, b)))
print
outmap = healpix_map.HEALPixFITS(modlayer, energies=self.energies)
if newfile is not None: outmap.write(newfile)
return outmap
def __init__(self, cubefile, sigsfile, start=0, stop=8, deg=2):
check_bubble_maps(cubefile)
m = diffuse.HealpixCube(cubefile); m.load()
msig = diffuse.HealpixCube(sigsfile); msig.load()
meas = np.array([m[i].vec for i in range(8)])
sig = np.array([msig[i].vec for i in range(8)])
self.planes = np.array(range(start,stop)) # plane numbers
self.values = meas[start:,:]
weights = 100./sig[start:,:] #from percent
self.wtmean = weights.mean(axis=1)
self.fit, self.residuals, self.rank, self.svals, self.rcond =\
np.polyfit(self.planes,self.values, deg=deg, full=True, w=self.wtmean)
labels= 'intercept slope curvature'.split()
self.hpfit=[healpix_map.HParray(labels[deg-i], self.fit[i,:]) for i in range(deg,-1,-1)]
def ait_plot(self, comp, fraction=False, **kwargs):
fig, ax = plt.subplots(figsize=(16, 8))
if not fraction:
defaults = dict(
log=True,
vmin=1,
vmax=1000.,
title=kwargs.get('title', comp),
)
defaults.update(**kwargs)
t = self[comp].plot(axes=ax, **defaults)
else:
defaults = dict(vmin=0, vmax=100.)
defaults.update(**kwargs)
a = self[comp].vec
b = self['final'].vec - self['src'].vec
title = '{} / total (%)'.format(comp)
t = hpm.HParray(title, a / b * 100.).plot(axes=ax,
title=title,
cbtext='%',
**defaults)
t.grid(color='lightgrey')
def __getitem__(self, index):
"""return a plane as a HParray object"""
energy = self.energies[index]
col = self.column(energy)
return healpix_map.HParray('{:.0f} MeV'.format(energy), col)
def write(self, filename):
"""generate a FITS file with all the (combined) maps for this energy
"""
hh = [hpm.HParray(name, value.map) for name, value in self.iteritems()]
t = hpm.HEALPixFITS(hh)
t.write(filename)
