fix: Correct handling of strategy 0 for Minuit optimizer (#2277)

* Properly guard the `strategy` option for the Minuit optimizer in the case that
  `strategy` option of 0 is used.
  Without checking `self.strategy is not None` the `if self.strategy` for
  self.strategy==0 evaluates to truthiness of False, giving the wrong value of
  `not do_grad` for do_grad of False.
   - Amends PR #1183
* Use the corrected behavior to improve testing of default in test_minuit_strategy_global.
* Add Daniel Werner to contributors list.

docs/contributors.rst

@@ -31,3 +31,4 @@ Contributors include:
 - Jerry Ling
 - Nathan Simpson
 - Beojan Stanislaus
+- Daniel Werner

src/pyhf/optimize/opt_minuit.py

@@ -102,7 +102,7 @@ def _minimize(
         # 0: Fast, user-provided gradient
         # 1: Default, no user-provided gradient
         strategy = options.pop(
-            'strategy', self.strategy if self.strategy else not do_grad
+            'strategy', self.strategy if self.strategy is not None else not do_grad
         )
         tolerance = options.pop('tolerance', self.tolerance)
         if options:

tests/test_optim.py

@@ -182,10 +182,9 @@ def test_minuit_strategy_global(mocker, backend, strategy):
     m = pyhf.simplemodels.uncorrelated_background([50.0], [100.0], [10.0])
     data = pyhf.tensorlib.astensor([125.0] + m.config.auxdata)
 
-    do_grad = pyhf.tensorlib.default_do_grad
     pyhf.infer.mle.fit(data, m)
     assert spy.call_count == 1
-    assert spy.spy_return.minuit.strategy == strategy if do_grad else 1
+    assert spy.spy_return.minuit.strategy == strategy
 
     pyhf.infer.mle.fit(data, m, strategy=0)
     assert spy.call_count == 2