ENH: Name heatmap values by the maximized parameter

Fixes #101 (comment)

Author: kernc

backtesting/backtesting.py

@@ -1157,8 +1157,9 @@ def optimize(self,
         if not kwargs:
             raise ValueError('Need some strategy parameters to optimize')
 
+        maximize_key = None
         if isinstance(maximize, str):
-
+            maximize_key = str(maximize)
             stats = self._results if self._results is not None else self.run()
             if maximize not in stats:
                 raise ValueError('`maximize`, if str, must match a key in pd.Series '
@@ -1202,6 +1203,7 @@ def __getattr__(self, item):
                           stacklevel=2)
 
         heatmap = pd.Series(np.nan,
+                            name=maximize_key,
                             index=pd.MultiIndex.from_tuples([p.values() for p in param_combos],
                                                             names=next(iter(param_combos)).keys()))
 

backtesting/test/_test.py

@@ -1,3 +1,4 @@
+import inspect
 import os
 import sys
 import time
@@ -400,14 +401,16 @@ def test_optimize(self):
         res = bt.optimize(**OPT_PARAMS)
         self.assertIsInstance(res, pd.Series)
 
-        res2 = bt.optimize(**OPT_PARAMS, maximize=lambda s: s['SQN'])
+        default_maximize = inspect.signature(Backtest.optimize).parameters['maximize'].default
+        res2 = bt.optimize(**OPT_PARAMS, maximize=lambda s: s[default_maximize])
         self.assertDictEqual(res.filter(regex='^[^_]').fillna(-1).to_dict(),
                              res2.filter(regex='^[^_]').fillna(-1).to_dict())
 
         res3, heatmap = bt.optimize(**OPT_PARAMS, return_heatmap=True,
                                     constraint=lambda d: d.slow > 2 * d.fast)
         self.assertIsInstance(heatmap, pd.Series)
         self.assertEqual(len(heatmap), 4)
+        self.assertEqual(heatmap.name, default_maximize)
 
         with _tempfile() as f:
             bt.plot(filename=f, open_browser=False)