def test_chained_lsqfit_keyword(self):
" MultiFitter.chained_lsqfit(...) "
# sequential fit
fitter = MultiFitter(models=self.make_models(ncg=1))
fit1 = fitter.lsqfit(data=self.data, prior=self.prior, chained=True)
self.assertTrue(self.agree_ref(fit1.p))
self.assertEqual(list(fit1.chained_fits.keys()), ['l', 'c1', 'c2'])
def test_bootstrap_lsqfit(self):
fitter = MultiFitter(models=self.make_models(ncg=1))
fit = fitter.lsqfit(data=self.data, prior=self.prior)
datalist = gv.bootstrap_iter(self.data, n=10)
ds = gv.dataset.Dataset()
for bf in fit.bootstrapped_fit_iter(datalist=datalist):
ds.append(bf.pmean)
p = gv.dataset.avg_data(ds, bstrap=True)
self.assertTrue(abs(p['a'].mean - 1.) < 5 * p['a'].sdev)
self.assertTrue(abs(p['b'].mean - 0.5) < 5 * p['b'].sdev)
self.assertEqual(ds.samplesize, 10)
pdatalist = (fitter.process_data(d, fitter.models)
for d in gv.bootstrap_iter(self.data, n=10))
ds = gv.dataset.Dataset()
for bf in fit.bootstrapped_fit_iter(pdatalist=pdatalist):
ds.append(bf.pmean)
p = gv.dataset.avg_data(ds, bstrap=True)
self.assertTrue(abs(p['a'].mean - 1.) < 5 * p['a'].sdev)
self.assertTrue(abs(p['b'].mean - 0.5) < 5 * p['b'].sdev)
self.assertEqual(ds.samplesize, 10)
ds = gv.dataset.Dataset()
for bf in fit.bootstrapped_fit_iter(n=10):
ds.append(bf.pmean)
p = gv.dataset.avg_data(ds, bstrap=True)
self.assertTrue(abs(p['a'].mean - 1.) < 5 * p['a'].sdev)
self.assertTrue(abs(p['b'].mean - 0.5) < 5 * p['b'].sdev)
self.assertEqual(ds.samplesize, 10)
def test_marginalization(self):
" MultiFitter.lsqfit(..., mopt=...) "
fitter = MultiFitter(models=self.make_models(ncg=1))
fit4 = fitter.lsqfit(data=self.data, prior=self.prior, mopt=True)
self.assertEqual(str(fit4.p['a']), str(self.ref_fit.p['a']))
self.assertEqual(gv.fmt_chi2(fit4), gv.fmt_chi2(self.ref_fit))
self.assertTrue('b' not in fit4.p)
def test_fast(self):
" MultiFitter.lsqfit(..., fast=False) "
# with fast=False
self.prior['aa'] = self.prior['a'] + gv.gvar('0(1)') * 1e-6
fitter = MultiFitter(models=self.make_models(ncg=1))
fit6 = fitter.lsqfit(data=self.data, prior=self.prior, fast=False)
self.assertTrue(self.agree_ref(fit6.p))
self.assertEqual((fit6.p['a'] / fit6.p['aa']).fmt(ndecimal=5),
'1.00000(0)')
# with fast=True (default)
self.prior['aa'] = self.prior['a'] + gv.gvar('0(1)') * 1e-6
fitter = MultiFitter(models=self.make_models(ncg=1))
fit7 = fitter.lsqfit(data=self.data, prior=self.prior)
self.assertTrue(self.agree_ref(fit7.p))
self.assertTrue('aa' not in fit7.p)
def test_dump_lsqfit(self):
" MultiFitter.lsqfit "
fitter = MultiFitter(models=self.make_models(ncg=1))
dfit = gv.loads(
gv.dumps(fitter.lsqfit(data=self.data, prior=self.prior)))
self.assertEqual(
self.ref_fit.format(True)[:-2],
dfit.format(True)[:-2])
def test_extend(self):
" MultiFitter.lsqfit(..., extend=True) "
fitter = MultiFitter(models=self.make_models(ncg=1))
prior = gv.BufferDict([('log(a)', gv.log(self.prior['a'])),
('b', self.prior['b'])])
fit5 = fitter.lsqfit(data=self.data, prior=prior, extend=True)
self.assertEqual(str(fit5.p['a']), str(self.ref_fit.p['a']))
self.assertEqual(gv.fmt_chi2(fit5), gv.fmt_chi2(self.ref_fit))
self.assertTrue('log(a)' in fit5.p)
def test_extend(self):
" MultiFitter.lsqfit(...) "
fitter = MultiFitter(models=self.make_models(ncg=1))
prior = gv.BufferDict([('log(a)', gv.log(self.prior['a'])),
('b', self.prior['b'])])
fit5 = fitter.lsqfit(data=self.data, prior=prior)
self.assertTrue(self.agree_ref(fit5.p))
self.assertTrue(
abs(fit5.chi2 - self.ref_fit.chi2) / 0.1 / self.ref_fit.chi2)
self.assertTrue('log(a)' in fit5.p)
def test_fast(self):
" MultiFitter.lsqfit(..., fast=False) "
# with fast=False
self.prior['aa'] = self.prior['a'] + gv.gvar('0(1)') * 1e-6
fitter = MultiFitter(models=self.make_models(ncg=1))
fit6 = fitter.lsqfit(data=self.data, prior=self.prior, fast=False)
self.assertEqual(
str(fit6.p),
"{'a': 0.99938(46),'b': 0.49985(78),'aa': 0.99938(46)}",
)
# with fast=True (default)
self.prior['aa'] = self.prior['a'] + gv.gvar('0(1)') * 1e-6
fitter = MultiFitter(models=self.make_models(ncg=1))
fit7 = fitter.lsqfit(data=self.data, prior=self.prior)
self.assertEqual(
str(fit7.p),
"{'a': 0.99938(46),'b': 0.49985(78)}",
)
def test_lsqfit_p0(self):
" MultiFitter.lsqfit with p0 "
fitter = MultiFitter(models=self.make_models(ncg=1))
p0 = {'a': 0.9992476083689589, 'b': 0.4996757090188109}
fit2 = fitter.lsqfit(data=self.data, prior=self.prior, p0=p0)
self.assertEqual(self.ref_fit.format()[:-22], fit2.format()[:-22])
self.assertEqual(p0, fit2.p0)
fit2 = fitter.lsqfit(data=self.data, prior=self.prior, p0=3 * [p0])
self.assertEqual(self.ref_fit.format()[:-20], fit2.format()[:-20])
self.assertEqual(p0, fit2.p0)
fn = 'test_multifitter.p'
fit1 = fitter.lsqfit(data=self.data, prior=self.prior, p0=fn)
fit1 = fitter.lsqfit(data=self.data, prior=self.prior, p0=fn)
# should be converged
fit2 = fitter.lsqfit(data=self.data, prior=self.prior, p0=fn)
self.assertTrue(self.agree_ref(fit2.p))
self.assertEqual(fit1.format()[:-70],
fit2.format()[:len(fit1.format()) - 70])
self.assertEqual(fit1.pmean, fit2.p0)
os.unlink(fn)
def test_lsqfit_pdata_coarse_grain(self):
" MultiFitter.lsqfit(pdata=..., ..., ncg=2) "
fitter = MultiFitter(models=self.make_models(ncg=2))
pdata = MultiFitter.process_data(data=self.data, models=fitter.models)
fit3 = fitter.lsqfit(pdata=pdata, prior=self.prior)
self.assertTrue(self.agree_ref(fit3.p))
def test_lsqfit_coarse_grain(self):
" MultiFitter.lsqfit(..., ncg=2) "
fitter = MultiFitter(models=self.make_models(ncg=2))
fit3 = fitter.lsqfit(data=self.data, prior=self.prior)
self.assertTrue(self.agree_ref(fit3.p))
def test_lsqfit(self):
" MultiFitter.lsqfit "
fitter = MultiFitter(models=self.make_models(ncg=1))
fit2 = fitter.lsqfit(data=self.data, prior=self.prior)
self.assertEqual(self.ref_fit.format(), fit2.format())
def test_lsqfit_pdata_coarse_grain(self):
" MultiFitter.lsqfit(pdata=..., ..., ncg=2) "
fitter = MultiFitter(models=self.make_models(ncg=2))
pdata = MultiFitter.process_data(data=self.data, models=fitter.models)
fit3 = fitter.lsqfit(pdata=pdata, prior=self.prior)
self.assertEqual(str(fit3.p), "{'a': 0.99937(46),'b': 0.49994(78)}")