feat: par_names handles non-scalar modifiers with 1 parameter

src/pyhf/pdf.py

@@ -319,13 +319,10 @@ def par_slice(self, name):
         """
         return self.par_map[name]['slice']
 
-    def par_names(self, fstring='{name}[{index}]'):
+    def par_names(self):
         """
         The names of the parameters in the model including binned-parameter indexing.
 
-        Args:
-            fstring (:obj:`str`): Format string for the parameter names using ``name`` and ``index`` variables. Default: ``'{name}[{index}]'``.
-
         Returns:
             :obj:`list`: Names of the model parameters.
 
@@ -336,18 +333,16 @@ def par_names(self, fstring='{name}[{index}]'):
             ... )
             >>> model.config.par_names()
             ['mu', 'uncorr_bkguncrt[0]', 'uncorr_bkguncrt[1]']
-            >>> model.config.par_names(fstring='{name}_{index}')
-            ['mu', 'uncorr_bkguncrt_0', 'uncorr_bkguncrt_1']
         """
         _names = []
         for name in self.par_order:
-            _npars = self.param_set(name).n_parameters
-            if _npars == 1:
+            param_set = self.param_set(name)
+            if param_set.is_scalar:
                 _names.append(name)
                 continue
 
             _names.extend(
-                [fstring.format(name=name, index=idx) for idx in range(_npars)]
+                [f'{name}[{index}]' for index in range(param_set.n_parameters)]
             )
         return _names
 

tests/test_optim.py

@@ -581,7 +581,7 @@ def test_minuit_param_names(mocker):
     data = [10] + pdf.config.auxdata
     _, result = pyhf.infer.mle.fit(data, pdf, return_result_obj=True)
     assert 'minuit' in result
-    assert result.minuit.parameters == ('mu', 'uncorr_bkguncrt')
+    assert result.minuit.parameters == ('mu', 'uncorr_bkguncrt[0]')
 
     pdf.config.par_names = mocker.Mock(return_value=None)
     _, result = pyhf.infer.mle.fit(data, pdf, return_result_obj=True)

tests/test_pdf.py

@@ -890,3 +890,34 @@ def test_reproducible_model_spec():
         {'bounds': [[0, 5]], 'inits': [1], 'name': 'mu'}
     ]
     assert pyhf.Model(model_from_ws.spec)
+
+
+def test_par_names_scalar_nonscalar():
+    """
+    Testing to ensure that nonscalar parameters are still indexed, even if
+    n_parameters==1.
+    """
+    spec = {
+        'channels': [
+            {
+                'name': 'channel',
+                'samples': [
+                    {
+                        'name': 'goodsample',
+                        'data': [1.0],
+                        'modifiers': [
+                            {'type': 'normfactor', 'name': 'scalar', 'data': None},
+                            {'type': 'shapesys', 'name': 'nonscalar', 'data': [1.0]},
+                        ],
+                    },
+                ],
+            }
+        ]
+    }
+
+    model = pyhf.Model(spec, poi_name="scalar")
+    assert model.config.par_order == ["scalar", "nonscalar"]
+    assert model.config.par_names() == [
+        'scalar',
+        'nonscalar[0]',
+    ]