def configPlot(scale=1e4, verbose=False):
prefix = '/data/user/fmcnally/anisotropy/maps/merged/'
fileList = np.array(glob.glob(prefix + 'IC?*_24H_sid.fits'))
alpha = 1/20.
deg = 180./np.pi
# Sort fileList according to configs
configs = np.array([os.path.basename(f).split('_')[0] for f in fileList])
csort = configs.argsort()
configs, fileList = configs[csort], fileList[csort]
dipoleParams = np.zeros((len(fileList), 6))
for i, f in enumerate(fileList):
data = mapFunctions.getMap(f, mapName='data')
bg = mapFunctions.getMap(f, mapName='bg')
p = mapFunctions.multifit(1, data, bg, alpha, params=True)
if verbose:
print configs[i]
ptable = [[key, p[key], p['d'+key]] for key in sorted(p.keys())]
print tabulate(ptable, headers=['Ylm','Value','Error'])
dipoleParams[i] = getDipole(p)
p0, dp0, theta, dTheta, phi, dPhi = dipoleParams.T
if verbose:
for i, config in enumerate(configs):
print config, ':'
print 'Theta: %.3f +/- %.3f' % (theta[i]*deg, dTheta[i]*deg)
print 'Phi: %.3f +/- %.3f' % (phi[i]*deg, dPhi[i]*deg)
fig = plt.figure(figsize=(17,6))
x = range(len(configs))
pltParams = {'fmt':'.','lw':2,'ms':14}
ax = fig.add_subplot(121)
ax.set_title('Dipole Strength vs Energy')
ax.set_xlabel(r'log$_{10}$(E/GeV)')
ax.set_ylabel('Dipole Strength (x %s)' % scale)
ax.errorbar(x, p0*scale, yerr=dp0*scale, **pltParams)
ax.set_xlim(-1, x[-1]+1)
ax.set_xticks(x)
ax.set_xticklabels(configs)
ax = fig.add_subplot(122)
ax.set_title('Dipole Phase vs Energy')
ax.set_xlabel(r'log$_{10}$(E/GeV)')
ax.set_ylabel(r'Dipole Phase ($\phi^{\circ}$)')
phi, dPhi = phi*deg, dPhi*deg
phi[phi>180] -= 360
ax.errorbar(x, phi, yerr=dPhi, **pltParams)
ax.set_xlim(-1, x[-1]+1)
ax.set_xticks(x)
ax.set_xticklabels(configs)
plt.show()
deccut = (dec >= decmin) * (dec <= decmax)
ra = np.array([rad2deg * i for i in ra])
dipole_avg = []
phase_avg = []
fig = plt.figure(0)
num_bands = 24.0
for j in range(len(maps)):
dI = []
angle = []
if len(maps[j]) == 1:
data, bg, local = hp.read_map(maps[j][0], range(3), verbose=False)
else:
data, bg, local = np.sum([hp.read_map(f, range(3), verbose=False) for f in maps[j]], axis=0)
for i in range(int(num_bands)):
if args.usefit:
relint = multifit(args.lmax, data, bg, alpha, **opts)
else:
with np.errstate(invalid="ignore"):
relint = (data - bg) / bg
relint[np.isnan(relint)] = 0.0
# Right ascension cut
ramin = (360.0 / num_bands) * i
ramax = (360.0 / num_bands) * (i + 1)
racut = (ra >= ramin) * (ra <= ramax)
# hp.write_map("racut.fits", [data, bg, local])
n_pix = (racut * deccut).sum()
# print('n_pix = {}'.format(n_pix))
relint[np.logical_not(racut)] = 0.0
relint[np.logical_not(deccut)] = 0.0
def energyPlot(scale=1e4,offset=180, out=False, batch=False, verbose=False):
prefix = '/data/user/fmcnally/anisotropy/maps/merged'
alpha = 1/20.
deg = 180./np.pi
colorDict = {0:'b'}
# IceCube information
files, meds, sigL, sigR = [],[],[],[]
ebins = getEbins()
files = getEnergyMaps('IC')
for i in range(len(ebins)-1):
distInfo = readDist_IC('IC', ebins[i], ebins[i+1])
meds += [distInfo[0]]
sigL += [distInfo[1]]
sigR += [distInfo[2]]
# IceTop information
idx0 = len(files)
colorDict[idx0] = 'r'
files += [['%s/IT_24H_sid_STA8.fits' % (prefix)]]
distInfo = readDist_IT('IT', 8, 100)
meds += [distInfo[0]]
sigL += [distInfo[1]]
sigR += [distInfo[2]]
dipoleParams = np.zeros((len(files), 6))
for i, files_i in enumerate(files):
data = mapFunctions.getMap(*files_i, mapName='data')
bg = mapFunctions.getMap(*files_i, mapName='bg')
p = mapFunctions.multifit(1, data, bg, alpha, params=True)
if verbose:
print meds[i]
print('key = {}'.format(sorted(p.keys())))
#ptable = [[key, p[key], p['d'+key]] for key in sorted(p.keys())]
ptable = [[key, p[key]] for key in sorted(p.keys())]
#print tabulate(ptable, headers=['Ylm','Value','Error'])
#print tabulate(ptable, headers=['Ylm','Value'])
print('files_i = {}'.format(files_i))
for key in sorted(p.keys()):
print('p[{}] = {}'.format(key,p[key]))
print('p[Y(1,1)]+p[Y(1,-1)] = {}'.format(np.sqrt(3.0/(4.0*np.pi))*np.power(p['Y(1,1)'],2.0)+np.power(p['Y(1,-1)'],2.0)))
dipoleParams[i] = getDipole(p)
p0, dp0, thetas, dThetas, phis, dPhis = dipoleParams.T
if verbose:
for i, median in enumerate(meds):
print 'Median energy : %.3f' % median
print 'Theta: %.3f +/- %.3f' % (thetas[i]*deg, dThetas[i]*deg)
print 'Phi: %.3f +/- %.3f' % (phis[i]*deg, dPhis[i]*deg)
#fig = plt.figure(figsize=(17,6))
fig = plt.figure()
#pltParams = {'fmt':'.','lw':2,'ms':14}
pltParams = {'lw':2,'ms':14}
#ax = fig.add_subplot(121)
#ax.set_title('Dipole Strength vs Energy')
#ax.set_xlabel(r'log$_{10}$(E/GeV)')
#ax.set_ylabel('Dipole Strength (x %s)' % scale)
#ax.errorbar(x, p0*scale, yerr=dp0*scale, **pltParams)
#ax = fig.add_subplot(122)
ax = fig.add_subplot(111)
ax.set_title('Dipole Phase vs Energy')
ax.set_xlabel(r'Reconstructed Energy (log$_{10}$(E/GeV))')
ax.set_ylabel(r'Dipole Phase ($\phi^{\circ}$)')
for i in range(0, len(meds), idx0):
x = meds[i:i+idx0]
xerr = [sigL[i:i+idx0], sigR[i:i+idx0]]
phi, dPhi = phis[i:i+idx0]*deg, dPhis[i:i+idx0]*deg
# Phi offset (requires renaming ylabels)
pcut = phi > offset
phi[pcut] -= offset
phi[np.logical_not(pcut)] += (360-offset)
ax.errorbar(x, phi, xerr=xerr, yerr=dPhi,
fmt=colorDict[i]+'.', **pltParams)
ax.set_ylim(-10,370)
ax.set_yticks(range(0, 361, 45))
ylabels = [str(i) for i in range(offset, 360-1, 45)]
ylabels += [str(i) for i in range(0, offset+1, 45)]
ax.set_yticklabels(ylabels)
plt.axhline(360-offset, linewidth=1.5, linestyle='--', color='black')
if out:
plt.savefig(out, dpi=300, bbox_inches='tight')
if not batch:
plt.show()
# Produce dipole expansion coeeficient plot
#fig = plt.figure(1)
labels = [r'$l=1$',r'$l=2$',r'$l=3$']
for i in range(1):
#for i in range(len(maps)):
for k in range(10):
# Read in (multiple) input files
data, bg, local = np.sum([hp.read_map(f, range(3), verbose=False)\
for f in maps[i]], axis=0)
a11 = []
a1n1 = []
a11_err = []
a1n1_err = []
for j in [1,2,3]:
p = multifit(j, data, bg, alpha, **opts)
#print('p = {}'.format(p))
a11.append(p['Y(1,1)'])
a1n1.append(p['Y(1,-1)'])
a11_err.append(p['dY(1,1)'])
a1n1_err.append(p['dY(1,-1)'])
fig = plt.figure(i)
plt.errorbar(a1n1,a11,xerr=[a1n1_err,a1n1_err],yerr=[a11_err,a11_err],marker='.',markersize=10,linestyle=':', label='IC energy bin {}'.format(i+1))
#plt.plot(a1n1,a11,marker='.',markersize=10,linestyle=':', label='IC energy bin {}'.format(i+1))
plt.plot([0.0],[0.0],marker='.',markersize=10,linestyle='None', color='black')
#plt.hlines(0.0,-1.,1.,linestyle='-.',color='grey')
#plt.vlines(0.0,-1.,1.,linestyle='-.',color='grey')
ax = fig.axes[0]
ax.axis('on')
tPars = {'fontsize':16}
