remove old print statements

guided_mrmp/conflict_resolvers/curve_path.py

@@ -173,15 +173,15 @@ if __name__ == "__main__":
     N = 40
     smooth_points, control_points = smooth_path(points, N, alpha=-.5, sigma=0.8)
 
-    print(f"smooth_points = {smooth_points}")
+    # print(f"smooth_points = {smooth_points}")
 
     # Example usage with a smooth path
     # path_points, control_points = smooth_path(points, N=100, alpha=0.2, sigma=1.5)
     headings = calculate_headings(smooth_points)
 
     # Displaying the headings
-    for i, heading in enumerate(headings):
-        print(f"Segment {i}: Heading = {np.degrees(heading):.2f} degrees")
+    # for i, heading in enumerate(headings):
+    #     print(f"Segment {i}: Heading = {np.degrees(heading):.2f} degrees")
 
     # Plotting
     plt.figure(figsize=(8, 8))

guided_mrmp/conflict_resolvers/subproblems/subproblem_og.py

@@ -23,8 +23,8 @@ class Subproblem:
         # These are still in the original environment's coordinates
         self.temp_starts = temp_starts
         self.temp_goals = temp_goals
-        print(f"temp starts = {self.temp_starts}")
-        print(f"temp goals = {self.temp_goals}")
+        # print(f"temp starts = {self.temp_starts}")
+        # print(f"temp goals = {self.temp_goals}")
 
         # Location of the subproblem in the original environment's coordinates
         self.top_left = None
@@ -104,7 +104,6 @@ class Subproblem:
         # Find the best in the original environment
         best_global = self.find_global_subproblem(S,find_best)
 
-        print(f"best global = {best_global}")
 
         if best_global is None: 
             return None
@@ -562,8 +561,8 @@ class Subproblem:
         if prioritize_goal_assignment: self.temp_goals = self.assign_temp_goals(top_left, bottom_right)
         else: self.temp_goals = self.assign_temp_goals(top_left, bottom_right)
 
-        print(f"temp starts afer reassignment= {self.temp_starts}")
-        print(f"temp goals after reassignment= {self.temp_goals}")
+        # print(f"temp starts afer reassignment= {self.temp_starts}")
+        # print(f"temp goals after reassignment= {self.temp_goals}")
         
         row_range = abs(bottom_right[0] - top_left[0])
         col_range = abs(top_left[1] - bottom_right[1])
@@ -581,9 +580,6 @@ class Subproblem:
                 x = bottom_right[0]-x_count
                 y = bottom_right[1]-y_count
 
-                print(f"x = {x}")
-                print(f"y = {y}")
-
                 starts = []
                 goals = []
 
@@ -591,7 +587,6 @@ class Subproblem:
                     start = self.temp_starts[k]
                     goal = self.temp_goals[k]
 
-                    print(f"goal = {goal}")
                     
 
                     start_x = start[0] 
@@ -723,7 +718,7 @@ class Subproblem:
         return True
 
 def find_subproblem(c, conflicts, S, robots, starts, goals, obstacle_map, find_best, prioritised):
-    print(f"finding best subproblem")
+    # print(f"finding best subproblem")
     two_by_three = Subproblem(obstacle_map, c, robots, starts, goals, conflicts,23)
     three_by_three = Subproblem(obstacle_map, c, robots, starts, goals, conflicts,33)
     two_by_five = Subproblem(obstacle_map, c, robots, starts, goals, conflicts,25)
@@ -788,7 +783,7 @@ def find_subproblem(c, conflicts, S, robots, starts, goals, obstacle_map, find_b
     # print(f"conflicts = {conflicts}")
     # type = best[3]  
 
-    print(f"best subproblem = {best_subproblem.transformed_goals}")
+    # print(f"best subproblem = {best_subproblem.transformed_goals}")
     return conflicts, best_subproblem
 
 
@@ -810,8 +805,8 @@ def order_query(starts, goals):
         ordered_goals - The goals in the correct order
         new_to_old - The mapping of indices, so that we can recover the original order.
     """
-    print(f"starts = {starts}")
-    print(f"goals = {goals}")
+    # print(f"starts = {starts}")
+    # print(f"goals = {goals}")
     fake_starts = []
     for start in starts:
         fake_starts.append([3*(start[0]), start[1]])
@@ -973,6 +968,6 @@ def query_library(obstacle_map, s, lib_2x3, lib_3x3, lib_2x5):
             s.flip()
         if count >= 10: break
 
-    if sol == None: print("returning None")
+    # if sol == None: print("returning None")
     return sol