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Code/S_add_bf_on_numbers_on_pareto.py

@@ -73,6 +73,7 @@ def add_bf_on_numbers_on_pareto(pathdir, filename, PA, math_expr):
     # Do bf on one parameter at a time
     bf_on_numbers_expr = []
     for w in range(len(eq_numbers)):
+        try:
             param_dict = {}
             unsnapped_param_dict = {'p':1}
             eq_ = unsnap_recur(expr,param_dict,unsnapped_param_dict)
@@ -96,6 +97,9 @@ def add_bf_on_numbers_on_pareto(pathdir, filename, PA, math_expr):
                         jj = jj + 1
 
                 bf_on_numbers_expr = bf_on_numbers_expr + [eq]
+        except:
+            continue
+                
     for i in range(len(bf_on_numbers_expr)):
         try:
             # Calculate the error of the new, snapped expression

Code/S_add_snap_expr_on_pareto.py

@@ -79,6 +79,7 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
     # Do integer snap one parameter at a time
     integer_snapped_expr = []
     for w in range(len(eq_numbers)):
+        try:
             param_dict = {}
             unsnapped_param_dict = {'p':1}
             eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
@@ -91,6 +92,8 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
                     eq = eq.subs(parm, eq_numbers[jj])
                     jj = jj + 1
             integer_snapped_expr = integer_snapped_expr + [eq]
+        except:
+            continue
                 
     # Get the numbers appearing in the expression
     is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
@@ -99,6 +102,7 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
     # Do zero snap one parameter at a time
     zero_snapped_expr = []
     for w in range(len(eq_numbers)):
+        try:
             param_dict = {}
             unsnapped_param_dict = {'p':1}
             eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
@@ -111,6 +115,8 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
                     eq = eq.subs(parm, eq_numbers[jj])
                     jj = jj + 1
             zero_snapped_expr = zero_snapped_expr + [eq]
+        except:
+            continue
 
     # Get the numbers appearing in the expression
     is_atomic_number = lambda expr: expr.is_Atom and expr.is_number
@@ -119,6 +125,7 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
     # Do rational snap one parameter at a time
     rational_snapped_expr = []
     for w in range(len(eq_numbers)):
+        try:
             eq_numbers_snap = copy.deepcopy(eq_numbers)
             param_dict = {}
             unsnapped_param_dict = {'p':1}
@@ -136,6 +143,8 @@ def add_snap_expr_on_pareto(pathdir, filename, math_expr, PA, DR_file=""):
                         eq = eq.subs(parm, eq_numbers_snap[jj])
                     jj = jj + 1
             rational_snapped_expr = rational_snapped_expr + [eq]
+        except:
+            continue
 
     snapped_expr = np.append(integer_snapped_expr,zero_snapped_expr)
     snapped_expr = np.append(snapped_expr,rational_snapped_expr)

Code/S_add_snap_expr_on_pareto_polyfit.py

@@ -79,6 +79,7 @@ def add_snap_expr_on_pareto_polyfit(pathdir, filename, math_expr, PA):
     # Do zero snap one parameter at a time
     zero_snapped_expr = []
     for w in range(len(eq_numbers)):
+        try:
             param_dict = {}
             unsnapped_param_dict = {'p':1}
             eq = unsnap_recur(expr,param_dict,unsnapped_param_dict)
@@ -91,6 +92,8 @@ def add_snap_expr_on_pareto_polyfit(pathdir, filename, math_expr, PA):
                     eq = eq.subs(parm, eq_numbers[jj])
                     jj = jj + 1
             zero_snapped_expr = zero_snapped_expr + [eq]
+        except:
+            continue
 
     for i in range(len(zero_snapped_expr)):
         try:

Code/S_final_gd.py

@@ -138,6 +138,10 @@ def final_gd(data_file, math_expr, lr = 1e-2, N_epochs = 5000):
         else:
             eq = eq.subs(parm, trainable_parameters[ii])
             complexity = complexity + get_number_DL(trainable_parameters[ii].detach().numpy())
+            n_variables = len(eq.free_symbols)
+            n_operations = len(count_ops(eq,visual=True).free_symbols)
+            if n_operations!=0 or n_variables!=0:
+                complexity = complexity + (n_variables+n_operations)*np.log2((n_variables+n_operations))
             ii = ii+1