def test_bootstrap(tmp_path, testdata):
with TemporaryDirectoryChanger(tmp_path):
shutil.copy2(testdata / 'nonmem' / 'pheno.mod', tmp_path)
shutil.copy2(testdata / 'nonmem' / 'pheno.dta', tmp_path)
model = Model('pheno.mod')
model.dataset_path = tmp_path / 'pheno.dta'
res = Bootstrap(model, 3).run()
assert len(res.parameter_estimates) == 3
def test_fit_single(tmp_path, testdata):
with TemporaryDirectoryChanger(tmp_path):
shutil.copy2(testdata / 'nonmem' / 'pheno.mod', tmp_path)
shutil.copy2(testdata / 'nonmem' / 'pheno.dta', tmp_path)
model = Model('pheno.mod')
model.dataset_path = tmp_path / 'pheno.dta'
modeling.fit(model)
rundir = tmp_path / 'modelfit_dir1'
assert model.modelfit_results.ofv == pytest.approx(730.8947268137308)
assert rundir.is_dir()
def test_fit_multiple(tmp_path, testdata):
with TemporaryDirectoryChanger(tmp_path):
shutil.copy2(testdata / 'nonmem' / 'pheno.mod',
tmp_path / 'pheno_1.mod')
shutil.copy2(testdata / 'nonmem' / 'pheno.dta',
tmp_path / 'pheno_1.dta')
model_1 = Model('pheno_1.mod')
model_1.dataset_path = tmp_path / 'pheno_1.dta'
model_1.update_source()
shutil.copy2(testdata / 'nonmem' / 'pheno.mod',
tmp_path / 'pheno_2.mod')
shutil.copy2(testdata / 'nonmem' / 'pheno.dta',
tmp_path / 'pheno_2.dta')
model_2 = Model('pheno_2.mod')
model_2.dataset_path = tmp_path / 'pheno_2.dta'
model_2.update_source()
modeling.fit([model_1, model_2])
rundir = tmp_path / 'modelfit_dir1'
assert model_1.modelfit_results.ofv == pytest.approx(730.8947268137308)
assert model_2.modelfit_results.ofv == pytest.approx(730.8947268137308)
assert rundir.is_dir()
