diff --git a/ovf/core/VFManager.py b/ovf/core/VFManager.py
index 775cb2f..1635561 100644
--- a/ovf/core/VFManager.py
+++ b/ovf/core/VFManager.py
@@ -200,7 +200,6 @@ class VFManager():
             pre_poles=self._poles,
             fit_constant=self.fit_constant,
             fit_proportional=self.fit_proportional,
-            dc_enforce=self.dc_enforce,
             passivity_enforce=self.passivity_enforce
             )
         return self.model_instance
@@ -215,7 +214,6 @@ class VFManager():
                 pre_poles=self._poles,
                 fit_constant=self.fit_constant,
                 fit_proportional=self.fit_proportional,
-                dc_enforce=self.dc_enforce,
                 passivity_enforce=self.passivity_enforce
                 )
             if self.verbose:
diff --git a/ovf/core/basis/MultiPortOrthonormalBasis.py b/ovf/core/basis/MultiPortOrthonormalBasis.py
index f6dd242..897e139 100644
--- a/ovf/core/basis/MultiPortOrthonormalBasis.py
+++ b/ovf/core/basis/MultiPortOrthonormalBasis.py
@@ -4,7 +4,7 @@ from ovf.core.utils import cond_row_inf, cond_col_one, generate_starting_poles
 
 
 class MultiPortOrthonormalBasis:
-    def __init__(self,H,freqs,pre_poles,passivity_enforce=True,dc_enforce=True,fit_constant=True,fit_proportional=False):
+    def __init__(self,H,freqs,pre_poles,passivity_enforce=True,fit_constant=True,fit_proportional=False):
         self._least_squares_condition = None
         self._least_squares_row_condition = None
         self._least_squares_col_condition = None
@@ -19,7 +19,6 @@ class MultiPortOrthonormalBasis:
 
         self.dc_tol = 1e-18
 
-        self.dc_enforce = dc_enforce
         self.fit_constant = fit_constant
         self.fit_proportional = fit_proportional
         self.passivity_enforce = passivity_enforce
@@ -414,17 +413,9 @@ class MultiPortOrthonormalBasis:
         """
         K, N = self.Phi.shape
         Phi   = self.Phi
-        dc_tol = 1e-18
-        has_dc = self.dc_enforce and self.freqs[0] < dc_tol
-        keep = np.ones(K, dtype=bool)
 
         # SK weighting (applied only to the (73) rows we keep in LS)
 
-        if has_dc:
-            # Enforce DC response exactly:
-            k0   = int(np.argmin(np.abs(self.freqs)))
-            keep[k0] = False
-
         if self.fit_constant:  
             one  = np.ones((K, 1), np.complex128)
             Phi_w = np.hstack([one, Phi]) 
@@ -434,7 +425,7 @@ class MultiPortOrthonormalBasis:
                 for j in range(self.ports):
                     M0 = np.zeros((K,N*self.ports**2),dtype=complex)
                     M0[:,index*N:(index+1)*N] = Phi
-                    M0 = np.hstack([M0, -(H[:,i,j].reshape(-1,1) * Phi_w)]).reshape((K, -1))[keep,:]       # (K, 2N),   complex
+                    M0 = np.hstack([M0, -(H[:,i,j].reshape(-1,1) * Phi_w)]).reshape((K, -1))       # (K, 2N),   complex
                     index+=1
                     M_kp = M0 if M_kp is None else np.vstack([M_kp, M0])
             assert M_kp is not None
@@ -445,20 +436,14 @@ class MultiPortOrthonormalBasis:
                 for j in range(self.ports):
                     M0 = np.zeros((K,N*self.ports**2),dtype=complex)
                     M0[:,index*N:(index+1)*N] = Phi
-                    M0 = np.hstack([M0, -(H[:,i,j].reshape(-1,1) * Phi)]).reshape((K, -1))[keep,:]       # (K, 2N),   complex
+                    M0 = np.hstack([M0, -(H[:,i,j].reshape(-1,1) * Phi)]).reshape((K, -1))       # (K, 2N),   complex
                     index+=1
                     M_kp = M0 if M_kp is None else np.vstack([M_kp, M0])
             assert M_kp is not None
 
 
-        if has_dc:
-            A_re  = np.real(M_kp)
-            A_im  = np.imag(M_kp)
-            mask    = np.ones(K, dtype=bool); mask[k0] = False
-
-        else:
-            A_re = np.real(M_kp)
-            A_im = np.imag(M_kp)
+        A_re = np.real(M_kp)
+        A_im = np.imag(M_kp)
 
         A_blocks = [A_re, A_im]
 
@@ -467,17 +452,15 @@ class MultiPortOrthonormalBasis:
             for i in range(self.ports):
                 Hk_sum.append([])
                 for j in range(self.ports):
-                    Hk_kp0 = H[:,i,j][keep]
-                    Hk_sum[i].append(np.sum(np.abs(Hk_kp0)**2))
+                    Hk_sum[i].append(np.sum(np.abs(H[:,i,j])**2))
                     # Hk_kp = Hk_kp0 if Hk_kp is None else np.hstack([Hk_kp, Hk_kp0])
-            K_keep = int(np.count_nonzero(keep))
             A_w0 = []
             b_w0 = []
             # Hk_sum = np.sum(np.abs(Hk_kp)**2)
             for i in range(self.ports):
                 for j in range(self.ports):
                     beta_ij = float(np.sqrt(Hk_sum[i][j]))
-                    mean_row = (beta_ij / K_keep) * np.sum(Phi_w[keep, :], axis=0)
+                    mean_row = (beta_ij / len(Phi_w)) * np.sum(Phi_w, axis=0)
                     A_w0.append(np.concatenate([np.zeros(N*self.ports**2, float),
                                         np.real(mean_row).astype(float)]
                                         ).reshape(1, -1))
@@ -489,16 +472,16 @@ class MultiPortOrthonormalBasis:
             b = np.zeros(m, float)
             b = np.concatenate([b, b_w0])
         else:
-            H_kp = None
+            H_all = None
             for i in range(self.ports):
                 for j in range(self.ports):
-                    H_0 = H[:,i,j][keep]
-                    H_kp = H_0 if H_kp is None else np.hstack([H_kp, H_0])
-            assert H_kp is not None
-            H_kp = H_kp.reshape(-1,1)
+                    H_0 = H[:,i,j]
+                    H_all = H_0 if H_all is None else np.hstack([H_all, H_0])
+            assert H_all is not None
+            H_all = H_all.reshape(-1,1)
             
-            b_re = np.real(d0 * H_kp)
-            b_im = np.imag(d0 * H_kp)
+            b_re = np.real(d0 * H_all)
+            b_im = np.imag(d0 * H_all)
             b = np.concatenate([b_re.ravel(), b_im.ravel()]).astype(float)
 
         # ---- build final stacked-real system ----