def test_flatten_models(self):
" MultiFitter.flatten_models "
models = self.make_models(ncg=1)
alltags = [m.datatag for m in models]
models = self.make_models(ncg=1)
models = [models[0], tuple(models[1:])]
tags = [m.datatag for m in MultiFitter.flatten_models(models)]
self.assertEqual(alltags, tags)
models = self.make_models(ncg=1)
models = [models[0], models[1:]]
tags = [m.datatag for m in MultiFitter.flatten_models(models)]
self.assertEqual(alltags, tags)
models = self.make_models(ncg=1)
models = [models[0], [(models[0], models[1]), (models[0], models[2])]]
tags = [m.datatag for m in MultiFitter.flatten_models(models)]
self.assertEqual(alltags, tags)
models = self.make_models(ncg=1)
models = [models[0], [tuple(models[1:]), ()]]
tags = [m.datatag for m in MultiFitter.flatten_models(models)]
self.assertEqual(alltags, tags)
models = self.make_models(ncg=1)
models = [(), models[0], [], (models[1], (), models[2], ()),
[(), tuple(models[1:]), ()], [], [()]]
tags = [m.datatag for m in MultiFitter.flatten_models(models)]
self.assertEqual(alltags, tags)
models = self.make_models(ncg=1)
tags = [m.datatag for m in MultiFitter.flatten_models(models[0])]
self.assertEqual(alltags[:1], tags)
def test_chained_fit_kargs(self):
" MultiFitter(models=[m1, dict(...), m2, ...]) "
models = self.make_models(ncg=1)
models = [models[2], dict(mopt=True), models[1], models[0]]
fitter = MultiFitter(models=models, mopt=None)
fit = fitter.chained_lsqfit(data=self.data,
prior=self.prior,
fast=True,
wavg_all=False)
self.assertTrue(fit.p['b'] is self.prior['b'])
self.assertEqual(fitter.mopt, None)
fitter = MultiFitter(models=fitter.flatten_models(models), mopt=None)
fit = fitter.chained_lsqfit(data=self.data,
prior=self.prior,
fast=True)
self.assertTrue(fit.p['b'] is not self.prior['b'])
