def test_divonne():
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))
def proceed_err(nidim, nods, nt):
r_vec = [nt, nidim]
p_integ = PyMikor()
fof = Integrand('FCN', nidim)
fof.normalize_a(2, 600)
exact_res = fof.exact_oscillatory()
v_integ = vegas.Integrator(nidim * [[0, 1]])
v_result = []
v_result.append(v_integ(fof.oscillatory_fcn, nitn=10, neval=1e3).mean)
v_result.append(v_integ(fof.oscillatory_fcn, nitn=10, neval=1e5).mean)
global ave, ucc
ave = fof.a
ucc = fof.u
def IntegCuba(ndim, xx, ncomp, ff, userdata):
# x, y, z = [xx[i] for i in range(ndim.contents.value)]
nnn = ndim.contents.value
sma = 0.
for i in range(nnn):
sma += ave[i] * xx[i]
ff[0] = math.cos(2. * math.pi * ucc[0] + sma)
# res = 1.
# for i in range(nnn):
# res *= 1./(1./math.pow(ave[i], 2) + math.pow(xx[i] - ucc[i], 2))
#ff[0] = res
return 0
NDIM = nidim
NCOMP = 1
NNEW = 1000
NMIN = 2
FLATNESS = 50.
KEY1 = 47
KEY2 = 1
KEY3 = 1
MAXPASS = 5
BORDER = 0.
MAXCHISQ = 10.
MINDEVIATION = .25
NGIVEN = 0
LDXGIVEN = NDIM
NEXTRA = 0
MINEVAL = 0
MAXEVAL = 50000
KEY = 0
def print_header(name):
print('-------------------- %s test -------------------' % name)
def print_results(name, results):
keys = ['nregions', 'neval', 'fail']
text = ["%s %d" % (k, results[k]) for k in keys if k in results]
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)
# print_header('Vegas')
vrs = pycuba.Vegas(IntegCuba, NDIM, verbose=0)
# print_results('Vegas', vrs)
v_result.append(vrs['results'][0]['integral'])
# print_header('Divonne')
cub = pycuba.Divonne(IntegCuba,
NDIM,
mineval=MINEVAL,
maxeval=MAXEVAL,
key1=KEY1,
key2=KEY2,
key3=KEY3,
maxpass=MAXPASS,
border=BORDER,
maxchisq=MAXCHISQ,
mindeviation=MINDEVIATION,
ldxgiven=LDXGIVEN,
verbose=0)
# print_results('Divonne', cub)
v_result.append(cub['results'][0]['integral'])
for v in v_result:
v = math.fabs((v - exact_res) / exact_res)
r_vec.append(format_num(v))
for tab_prime in nods:
p_integ.set_values(1, nidim, tab_prime, 1, sigma=2)
p_result = p_integ(fof.oscillatory_fcn) # , eps=1e-4
p_rel_res = math.fabs((p_result - exact_res) / exact_res)
r_vec.append(format_num(p_rel_res))
with open('data_oscillatory_a_norm1.csv', 'a', newline='') as file:
wr = csv.writer(file, delimiter=',', quoting=csv.QUOTE_ALL)
wr.writerow(r_vec)
del p_integ
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,
)