def test(config, log=False, kg='gauss'):
if config in ['IC59','IC79']:
nfiles = 5 if config=='IC79' else 14
for i in range(nfiles):
s = load_sim(config, spline=False, part=i)
if i == 0:
y, bins = ang_hist(s)
x = getMids(bins)
else:
h = ang_hist(s)
y += h[0]
if config in ['IC86','IC86-II','IC86-III']:
s = load_sim(config, spline=False)
y, bins = ang_hist(s)
x = getMids(bins)
# Normalize values
y = y.astype('float')
ycut = (y!=0)
x = x[ycut]
y = y[ycut]
dy = 1/np.sqrt(y)
y /= y.sum()
yerr = y * dy
popt, pcov = fitter(x, y, yerr, kg=kg)
print config, popt, np.sqrt(np.diagonal(pcov))
f0 = np.array([gauss(i, popt[:2]) for i in x])
f1 = np.array([gauss(i, popt[2:]) for i in x])
fit = np.array([myfunc(i, *popt) for i in x])
# Test fit for gaussian with median angular resolution as sigma
#sig = 3.65
#amp = 2 * 1 / (sig * np.sqrt(2*np.pi))
#f2 = np.array([gauss(i, [amp, sig]) for i in x])
# Get area of each gaussian
a0, a1 = f0.sum(), f1.sum()
atot = float(a0 + a1)
#print a0
#print a1
print 'Fraction1: %.2f' % (a0 / atot)
#print 'Unaccounted: %.2f' % (y.sum() - atot)
fig, ax = plt.subplots()
ax.errorbar(x, y, yerr, fmt='.')
ax.plot(x, fit)
#ax.plot(x, f0)
#ax.plot(x, f1)
#ax.plot(x, f2)
ax.set_xlim(0, 20)
if log:
ax.set_yscale('log')
ax.set_ylim(1e-6, 1)
plt.show()
def writeDist(config, infoFile, overwrite=False):
# Load simulation
s = analysis.load_sim(config)
energy = np.log10(s['MC_energy'])
weights = analysis.getWeights(s)
# Read in existing distribution file
lines = []
if os.path.isfile(infoFile):
with open(infoFile, 'r') as f:
lines = f.readlines()
lines = [line.strip() for line in lines]
table = [line.split(' ') for line in lines]
paramList = [i[:3] for i in table]
# Info stored in [config, nmin, nmax, median energy, sigL, sigR, counts]
nList = range(3, 16)
nList.append(100)
newParams = [[config, i, j] for i in nList for j in nList if i < j]
for config, nmin, nmax in newParams:
# Check to see if the params exists already
found = True
try: i = paramList.index([config, str(nmin), str(nmax)])
except ValueError:
found = False
# If it exists, option to overwrite
if found and not overwrite:
print 'Info for', config, nmin, nmax, 'already exists...'
continue
if found and overwrite:
table.remove(table[i])
print 'Working on', config, nmin, nmax
# Calculate information for energy range
cut = (s['nstation'] >= nmin) * (s['nstation'] < nmax)
values = energy[cut]
w = weights[cut]
# Weighted median and 68% containment
median = analysis.weighted_percentile(values, w, 50)
sigL = median - analysis.weighted_percentile(values, w, 16)
sigR = analysis.weighted_percentile(values, w, 84) - median
# Unbiased weighted variance
mean = np.average(values, weights=w)
var = (sum(w * (values-mean)**2) /
(sum(w) - sum(w**2)/sum(w)))
counts = len(values)
# Append to file
newLine = [config, nmin, nmax, median, sigL, sigR, var, counts]
newLine = ['%s' % i for i in newLine]
table.append(newLine)
# Write as you go
lines = [' '.join(line) for line in table]
lines = [line + '\n' for line in lines]
lines.sort()
with open(infoFile, 'w') as f:
f.writelines(lines)