Apply formatting changes

Author: guilyx

jupyddl/data_analyst.py

@@ -509,7 +509,10 @@ def comparative_astar_heuristic_plot(
                 times_y.append(data[node_opened])
 
             ax.plot(
-                nodes_sorted, times_y, "-o", label=h,
+                nodes_sorted,
+                times_y,
+                "-o",
+                label=h,
             )
 
         plt.title("A* heuristics complexity comparison")
@@ -541,7 +544,10 @@ def comparative_greedy_bfs_heuristic_plot(
                 times_y.append(data[node_opened])
 
             ax.plot(
-                nodes_sorted, times_y, "-o", label=h,
+                nodes_sorted,
+                times_y,
+                "-o",
+                label=h,
             )
 
         plt.title("Greedy Best First heuristics complexity comparison")
@@ -616,7 +622,10 @@ def comparative_data_plot(
             for node_opened in nodes_sorted:
                 times_y.append(data[node_opened])
             ax.plot(
-                nodes_sorted, times_y, "-o", label=planner,
+                nodes_sorted,
+                times_y,
+                "-o",
+                label=planner,
             )
         plt.title("Planners complexity comparison")
         plt.legend(loc="upper left")
@@ -744,7 +753,9 @@ def compute_planners_efficiency(self):
         plt.ylabel("Cost to goal")
         for key, val in costs.items():
             ax.plot(
-                val, "-o", label=key,
+                val,
+                "-o",
+                label=key,
             )
             costs[key] = [i for i in costs[key] if i != 0]
         plt.title("Planners efficiency (costs)")

jupyddl/heuristics.py

@@ -78,8 +78,10 @@ def compute(self, state):
                 return self.heuristic_keys[self.current_h](costs)
 
             for ax in self.cache.axioms:
-                fact_costs = self.automated_planner.pddl.compute_costs_one_step_derivation(
-                    facts, fact_costs, ax, self.current_h
+                fact_costs = (
+                    self.automated_planner.pddl.compute_costs_one_step_derivation(
+                        facts, fact_costs, ax, self.current_h
+                    )
                 )
 
             actions = self.automated_planner.available_actions(state)
@@ -208,8 +210,10 @@ def compute(self, state):
                 return max(costs)
 
             for ax in self.cache.axioms:
-                fact_costs = self.automated_planner.pddl.compute_costs_one_step_derivation(
-                    facts, fact_costs, ax, "max"
+                fact_costs = (
+                    self.automated_planner.pddl.compute_costs_one_step_derivation(
+                        facts, fact_costs, ax, "max"
+                    )
                 )
 
             actions = self.automated_planner.available_actions(state)

jupyddl/metrics.py

@@ -22,17 +22,14 @@ def __str__(self):
         else:
             av = 0
             w = 0
-        return (
-            "Expanded %d state(s).\nOpened %d state(s).\nReopened %d state(s).\nEvaluated %d state(s).\nGenerated %d state(s).\nDead ends: %d state(s).\nRuntime: %.2fs.\nTotal heuristic runtime: %.2fs\nComputational weight of heuristic in the search: %.2f%%"
-            % (
-                self.n_expended,
-                self.n_opened,
-                self.n_reopened,
-                self.n_evaluated,
-                self.n_generated,
-                self.deadend_states,
-                self.runtime,
-                av,
-                w,
-            )
+        return "Expanded %d state(s).\nOpened %d state(s).\nReopened %d state(s).\nEvaluated %d state(s).\nGenerated %d state(s).\nDead ends: %d state(s).\nRuntime: %.2fs.\nTotal heuristic runtime: %.2fs\nComputational weight of heuristic in the search: %.2f%%" % (
+            self.n_expended,
+            self.n_opened,
+            self.n_reopened,
+            self.n_evaluated,
+            self.n_generated,
+            self.deadend_states,
+            self.runtime,
+            av,
+            w,
         )