def setUp(self):
self.method = LevMar()
self.stat = Chi2Gehrels()
self.est = Covariance()
self.gro_fname = self.make_path('gro.txt')
self.gro_delta_fname = self.make_path('gro_delta.txt')
return
def calc_errors(ys):
"""Return errors for ys using the default statistic.
Consolidate this code to make it easier to change if the
default statistic ever changes.
"""
return Chi2Gehrels.calc_staterror(ys)
def test_chi2gehrels_stat(hide_logging, reset_xspec, setup_group):
fit = Fit(setup_group['data'], setup_group['model'], Chi2Gehrels(),
NelderMead())
results = fit.fit()
_fit_chi2gehrels_results_bench = {
'succeeded':
1,
'numpoints':
143,
'dof':
140,
'istatval':
2410.6724538404405,
'statval':
100.22120218142433,
'parvals':
numpy.array(
[1.7831198951601808, 5.376678702350025, -1.9152513828120412])
}
compare_results(_fit_chi2gehrels_results_bench, results)
def test_chi2gehrels_stat(self):
fit = Fit(self.data, self.model, Chi2Gehrels(), NelderMead())
results = fit.fit()
self.compare_results(self._fit_chi2gehrels_results_bench, results)
def fit_asymmetric_err(bench, data):
model = PowLaw1D('p1')
fit = Fit(data, model, Chi2Gehrels(), LevMar())
results = fit.fit()
compare(bench, results)
return model