Add new efficiency metric

experiment_burgers.py

@@ -94,7 +94,7 @@ def hash_term(term):
     ''' Parameters of the experiment '''
     write_csv = False
     print_results = True
-    max_iter_number = 1
+    max_iter_number = 50
     title = 'df0'
 
     terms = [('du/dx1', ), ('du/dx2', 'u'), ('u',), ('du/dx2',), ('u', 'du/dx1'), ('du/dx1', 'du/dx2'),]
@@ -153,3 +153,4 @@ def hash_term(term):
         print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.4f}')
         print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.4f}')
         print(f'Average # of found eq per run: {sum(num_found_eq) / len(num_found_eq):.2f}')
+        print(f"Runs where eq was not found: {max_iter_number - len(differences_ls)}")

experiment_burgers_sindy.py

@@ -96,7 +96,7 @@ def hash_term(term):
     ''' Parameters of the experiment '''
     write_csv = False
     print_results = True
-    max_iter_number = 1
+    max_iter_number = 50
     title = 'df0_sindy'
 
     terms = [('u',), ('du/dx1',), ('du/dx2',), ('d^2u/dx2^2',), ('u', 'du/dx1'), ('u', 'du/dx2'), ('u', 'd^2u/dx2^2'),
@@ -156,3 +156,4 @@ def hash_term(term):
         print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.4f}')
         print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.4f}')
         print(f'Average # of found eq: {sum(num_found_eq) / len(num_found_eq):.2f}')
+        print(f"Runs where eq was not found: {max_iter_number - len(differences_ls)}")

experiment_kdv.py

@@ -124,7 +124,7 @@ def hash_term(term):
     ''' Parameters of the experiment '''
     write_csv = False
     print_results = True
-    max_iter_number = 10
+    max_iter_number = 50
     title = 'df0'
 
     time_ls = []
@@ -197,6 +197,7 @@ def hash_term(term):
 
         print()
         print(f'\nAverage time, s: {sum(time_ls) / len(time_ls):.2f}')
-        print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.4f}')
-        print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.4f}')
+        print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.6f}')
+        print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.6f}')
         print(f'Average # of found eq per run: {sum(num_found_eq) / len(num_found_eq):.2f}')
+        print(f"Runs where eq was not found: {max_iter_number - len(differences_ls)}")

experiment_kdv_sindy.py

@@ -103,7 +103,7 @@ def hash_term(term):
     ''' Parameters of the experiment '''
     write_csv = False
     print_results = True
-    max_iter_number = 1
+    max_iter_number = 50
     title = 'df0_sindy'
 
     time_ls = []
@@ -159,3 +159,4 @@ def hash_term(term):
         print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.4f}')
         print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.4f}')
         print(f'Average # of found eq: {sum(num_found_eq) / len(num_found_eq):.2f}')
+        print(f"Runs where eq was not found: {max_iter_number - len(differences_ls)}")

experiment_wave.py

@@ -160,3 +160,4 @@ def hash_term(term):
         print(f'Average MAE per eq: {sum(mean_diff_ls) / len(mean_diff_ls):.4f}')
         print(f'Average minimum MAE per run: {sum(differences_ls) / len(differences_ls):.4f}')
         print(f'Average # of found eq: {sum(num_found_eq) / len(num_found_eq):.2f}')
+        print(f"Runs where eq was not found: {max_iter_number - len(differences_ls)}")