def nornalizeBreitWigner(self, algo='vegas', nwidths=100):
def Integrand(ndim, xx, ncomp, ff, userdata):
a = self.MW - nwidths*self.GW
if a < 0.:
a = 0.0
b = self.MW + nwidths*self.GW
x = xx[0]*(b-a) + a
result = self.BreitWignerQ(x)
ff[0] = result*(b-a)
return 0
NDIM = 1
if algo=='chure':
res = pycuba.Cuhre(Integrand, NDIM, key=13, verbose=0)['results'][0]
elif algo=='vegas':
res = pycuba.Vegas(Integrand, NDIM , epsrel=0.0001, epsabs=1e-12, maxeval=1000000)['results'][0]
elif algo=='quad':
res = integrate.quad(self.BreitWignerQ, self.MW-nwidths*self.GW if self.MW-nwidths*self.GW>0. else 0.0, self.MW+nwidths*self.GW)[0]
self.normBW = res
def test_cuhre():
print_header('Cuhre')
print_results('Cuhre', pycuba.Cuhre(Integrand,
NDIM,
key=KEY,
verbose=2 | 4))
print_header('Vegas')
print_results('Vegas', pycuba.Vegas(Integrand, NDIM, verbose=2))
print_header('Suave')
print_results(
'Suave',
pycuba.Suave(Integrand, NDIM, NNEW, NMIN, FLATNESS, verbose=2 | 4))
print_header('Divonne')
print_results(
'Divonne',
pycuba.Divonne(Integrand,
NDIM,
mineval=MINEVAL,
maxeval=MAXEVAL,
key1=KEY1,
key2=KEY2,
key3=KEY3,
maxpass=MAXPASS,
border=BORDER,
maxchisq=MAXCHISQ,
mindeviation=MINDEVIATION,
ldxgiven=LDXGIVEN,
verbose=2))
print_header('Cuhre')
print_results('Cuhre', pycuba.Cuhre(Integrand,
NDIM,
key=KEY,
verbose=2 | 4))
def run_cuba(**config):
NDIM = config['ndim']
loglikelihood = config['loglikelihood']
def Integrand(ndim, xx, ncomp, ff, userdata):
ff[0] = exp(loglikelihood([xx[i] for i in range(ndim.contents.value)]))
return 0
NCOMP = 1
NNEW = 1000
FLATNESS = 25.
KEY1 = 47
KEY2 = 1
KEY3 = 1
MAXPASS = 5
BORDER = 0.
MAXCHISQ = 10.
MINDEVIATION = .25
NGIVEN = 0
LDXGIVEN = NDIM
NEXTRA = 0
MINEVAL = 100
MAXEVAL = 2000000
epsrel=0.5
epsabs=1e-300
KEY = 0
commonargs = dict(
mineval=MINEVAL, maxeval=MAXEVAL,
epsrel=epsrel, epsabs=epsabs,
seed = config['seed'] + 1, # 0 stands for random
)
def print_results(name, results):
keys = ['nregions', 'neval', 'fail']
keys = list(filter(results.has_key, keys))
text = ["%s %d" % (k, results[k]) for k in keys]
print ("%s RESULT:\t" % name.upper() + "\t".join(text))
for comp in results['results']:
print ("%s RESULT:\t" % name.upper() + "%(integral).8f +- %(error).8f\tp = %(prob).3f\n" % comp)
starttime = time.time()
if config['cuba_algorithm'] == 'Vegas':
results = pycuba.Vegas(Integrand, NDIM, verbose=2, **commonargs)
elif config['cuba_algorithm'] == 'Suave':
results = pycuba.Suave(Integrand, NDIM, NNEW, FLATNESS, verbose=2 | 4, **commonargs)
elif config['cuba_algorithm'] == 'Divonne':
results = pycuba.Divonne(Integrand, NDIM,
key1=KEY1, key2=KEY2, key3=KEY3, maxpass=MAXPASS,
border=BORDER, maxchisq=MAXCHISQ, mindeviation=MINDEVIATION,
ldxgiven=LDXGIVEN, verbose=2, **commonargs)
elif config['cuba_algorithm'] == 'Cuhre':
results = pycuba.Cuhre(Integrand, NDIM, key=KEY, verbose=2 | 4, **commonargs)
else:
assert False, 'Unknown cuba algorithm "%s"!' % config['cuba_algorithm']
duration = time.time() - starttime
print_results(config['cuba_algorithm'], results)
Z = results['results'][0]['integral']
Zerr = results['results'][0]['error']
return dict(
Z_computed = float(log(abs(Z) + 1e-300)),
Z_computed_err = float(log(abs(Z+Zerr) + 1e-300) - log(abs(Z) + 1e-300)),
failed=results['fail'] != 0 and Z >= 0 and Zerr >= 0,
duration = duration,
)
