allow changing confidence level for minos

src/cabinetry/fit/__init__.py

@@ -328,6 +328,8 @@ def _run_minos(
     minuit_obj: iminuit.Minuit,
     minos: Union[List[str], Tuple[str, ...]],
     labels: List[str],
+    *,
+    cl: Optional[float] = None,
 ) -> Dict[str, Tuple[float, float]]:
     """Determines parameter uncertainties for a list of parameters with MINOS.
 
@@ -337,6 +339,8 @@ def _run_minos(
         labels (List[str]]): names of all parameters known to ``iminuit``, these names
             are used in output (may be the same as the names under which ``iminiuit``
             knows parameters)
+        cl (Optional[float]), optional): confidence level for the confidence interval,
+            defaults to None (use ``iminuit`` default of 68.27%)
 
     Returns:
         Dict[str, Tuple[float, float]]: uncertainties indexed by parameter name
@@ -347,7 +351,7 @@ def _run_minos(
             log.warning(f"parameter {par_name} not found in model")
             continue
         log.info(f"running MINOS for {par_name}")
-        minuit_obj.minos(par_name)
+        minuit_obj.minos(par_name, cl=cl)
 
     minos_results = {}
 

tests/fit/test_fit.py

@@ -317,6 +317,12 @@ def func_to_minimize(pars):
     assert "b =  1.5909 -0.7262 +0.4738" in [rec.message for rec in caplog.records]
     caplog.clear()
 
+    # custom confidence interval
+    minos_results = fit._run_minos(m, ["b"], ["a", "b"], cl=0.95)
+    assert np.allclose(minos_results["b"][0], -1.47037911)
+    assert np.allclose(minos_results["b"][1], 0.81994008)
+    caplog.clear()
+
     # unknown parameter, MINOS does not run
     m = iminuit.Minuit(func_to_minimize, [1.0, 1.0])
     m.errordef = 1