apply black

cmaes/_dxnesic.py

@@ -317,16 +317,20 @@ def tell(self, solutions: list[tuple[np.ndarray, float]]) -> None:
         eta_sigma = (
             self._eta_move_sigma
             if norm_p_sigma >= self._chi_n
-            else self._eta_stag_sigma(lamb_feas)
-            if norm_p_sigma >= 0.1 * self._chi_n
-            else self._eta_conv_sigma(lamb_feas)
+            else (
+                self._eta_stag_sigma(lamb_feas)
+                if norm_p_sigma >= 0.1 * self._chi_n
+                else self._eta_conv_sigma(lamb_feas)
+            )
         )
         eta_B = (
             self._eta_move_B(lamb_feas)
             if norm_p_sigma >= self._chi_n
-            else self._eta_stag_B(lamb_feas)
-            if norm_p_sigma >= 0.1 * self._chi_n
-            else self._eta_conv_B(lamb_feas)
+            else (
+                self._eta_stag_B(lamb_feas)
+                if norm_p_sigma >= 0.1 * self._chi_n
+                else self._eta_conv_B(lamb_feas)
+            )
         )
 
         # natural gradient estimation in local coordinate

tools/cmaes_visualizer.py

@@ -17,6 +17,7 @@
   python3 tools/cmaes_visualizer.py --function himmelblau \
     --restart-strategy ipop --frames 500 --interval 10 --pop-per-frame 6
 """
+
 import argparse
 import math
 

tools/ws_cmaes_visualizer.py

@@ -15,6 +15,7 @@
 Example:
   python3 ws_cmaes_visualizer.py --function rot-ellipsoid
 """
+
 import argparse
 import math