properly treat optional arguments

src/cabinetry/fit/__init__.py

@@ -370,6 +370,7 @@ def _goodness_of_fit(
     model: pyhf.pdf.Model,
     data: List[float],
     best_twice_nll: float,
+    *,
     fix_pars: Optional[List[bool]] = None,
 ) -> float:
     """Calculates goodness-of-fit p-value with a saturated model.
@@ -421,7 +422,7 @@ def _goodness_of_fit(
     # of bins minus the number of unconstrained parameters
     n_dof = sum(
         model.config.channel_nbins.values()
-    ) - model_utils.unconstrained_parameter_count(model, fix_pars)
+    ) - model_utils.unconstrained_parameter_count(model, fix_pars=fix_pars)
     log.debug(f"number of degrees of freedom: {n_dof}")
 
     if n_dof <= 0:
@@ -507,7 +508,9 @@ def fit(
 
     if goodness_of_fit:
         # calculate goodness-of-fit with saturated model
-        p_val = _goodness_of_fit(model, data, fit_results.best_twice_nll, fix_pars)
+        p_val = _goodness_of_fit(
+            model, data, fit_results.best_twice_nll, fix_pars=fix_pars
+        )
         fit_results = fit_results._replace(goodness_of_fit=p_val)
 
     return fit_results

src/cabinetry/model_utils.py

@@ -483,6 +483,7 @@ def prediction(
 
 def unconstrained_parameter_count(
     model: pyhf.pdf.Model,
+    *,
     fix_pars: Optional[List[bool]] = None,
 ) -> int:
     """Returns the number of unconstrained, non-constant parameters in a model.

tests/fit/test_fit.py

@@ -353,7 +353,7 @@ def test__goodness_of_fit(
     assert mock_pars.call_args[1] == {}
     assert mock_count.call_count == 1
     assert mock_count.call_args[0][0].spec == model.spec
-    assert mock_count.call_args[1] == {}
+    assert mock_count.call_args[1] == {"fix_pars": None}
     assert "Delta NLL = 0.084185" in [rec.message for rec in caplog.records]
     assert np.allclose(p_val, 0.91926079)
     caplog.clear()
@@ -372,7 +372,7 @@ def test__goodness_of_fit(
     assert mock_pars.call_count == 2  # no new call (no auxdata)
     assert mock_count.call_count == 3
     assert mock_count.call_args[0][0].spec == model.spec
-    assert mock_count.call_args[1] == {}
+    assert mock_count.call_args[1] == {"fix_pars": None}
     assert (
         "cannot calculate p-value: 0 degrees of freedom and Delta NLL = 0.000000"
         in [rec.message for rec in caplog.records]
@@ -480,7 +480,8 @@ def test_fit(mock_fit, mock_print, mock_gof):
 
     # goodness-of-fit test
     fit_results_gof = fit.fit(model, data, goodness_of_fit=True)
-    assert mock_gof.call_args_list == [((model, data, 2.0, None), {})]
+    assert mock_gof.call_args[0] == (model, data, 2.0)
+    assert mock_gof.call_args[1] == {"fix_pars": None}
     assert fit_results_gof.goodness_of_fit == 0.1
 
 

tests/test_model_utils.py

@@ -372,7 +372,7 @@ def test_unconstrained_parameter_count(example_spec, example_spec_shapefactor):
     model = pyhf.Workspace(example_spec_shapefactor).model()
     fix_pars = model.config.suggested_fixed()
     fix_pars[0] = True
-    assert model_utils.unconstrained_parameter_count(model, fix_pars) == 2
+    assert model_utils.unconstrained_parameter_count(model, fix_pars=fix_pars) == 2
 
     # fixed parameters are skipped in counting
     example_spec_shapefactor["measurements"][0]["config"]["parameters"].append(