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Author: ss0832

multioptpy/Potential/keep_angle_potential.py

@@ -103,10 +103,7 @@ def calc_energy(self, geom_num_list, bias_pot_params=[]):
         norm2 = torch.linalg.norm(vec2)
 
         # u = cos(theta)
-        # Add epsilon to denominator to prevent NaN if atoms overlap exactly
-        norm1_2 = norm1 * norm2
-        if norm1_2 < 1e-12:
-            norm1_2 = norm1_2 + 1e-12
+        norm1_2 = torch.clamp(norm1 * norm2, min=1e-12)
 
         u = torch.dot(vec1, vec2) / (norm1_2)
         u = torch.clamp(u, -1.0, 1.0)
@@ -137,7 +134,7 @@ def get_quad_params(th_cut):
             # We ignore the d2th/du2 term to ensure positive curvature (convexity)
             d2 = k * (dth_du**2) 
 
-            return val.detach(), d1.detach(), d2.detach()
+            return val, d1, d2
 
 
         # --- BRANCH A: EXACTLY Linear Equilibrium (theta_0 ~ 0) ---
@@ -311,9 +308,7 @@ def get_centroid(key):
         norm1 = torch.linalg.norm(vec1)
         norm2 = torch.linalg.norm(vec2)
 
-        norm1_2 = norm1 * norm2
-        if norm1_2 < 1e-12:
-            norm1_2 = norm1_2 + 1e-12
+        norm1_2 = torch.clamp(norm1 * norm2, min=1e-12)
 
         u = torch.dot(vec1, vec2) / (norm1_2)
         u = torch.clamp(u, -1.0, 1.0)
@@ -339,7 +334,7 @@ def get_quad_params(th_cut):
             # Gauss-Newton Approximation
             d2 = k * (dth_du**2)
 
-            return val.detach(), d1.detach(), d2.detach()
+            return val, d1, d2
 
         # --- BRANCH A: EXACTLY Linear Equilibrium (theta_0 ~ 0) ---
         if torch.abs(theta_0) < epsilon_param: