diff --git a/descent/display.py b/descent/display.py
index 7f58dea..fea0cca 100644
--- a/descent/display.py
+++ b/descent/display.py
@@ -12,7 +12,7 @@
     'every': 1,
     'iter': True,
     'obj': True,
-    'gradnorm': True,
+    'gradnorm': False,
     'runtime': True,
     'width': 15,
     'spec': '5g'
diff --git a/descent/main.py b/descent/main.py
index 7ce758e..81970ae 100644
--- a/descent/main.py
+++ b/descent/main.py
@@ -40,7 +40,7 @@ def __init__(self, theta_init):
 
         self.theta = deepcopy(theta_init)
 
-    def run(self, maxiter=1e3, obj_tol=1e-8, param_tol=1e-5):
+    def run(self, maxiter=1e3, obj_tol=-1, param_tol=-1):
 
         self.maxiter = int(maxiter)
         starting_iteration = len(self)
diff --git a/descent/proxops.py b/descent/proxops.py
index ae0725a..08ccf4d 100644
--- a/descent/proxops.py
+++ b/descent/proxops.py
@@ -246,10 +246,17 @@ def __init__(self, axis, gamma):
 
     def __call__(self, x0, rho):
 
-        # Apply Laplacian smoothing
+        # Apply Laplacian smoothing (l2 norm on the parameters multiplied by
+        # the laplacian)
         n = x0.shape[self.axis]
         lap_op = spdiags([(2 + rho / self.gamma) * np.ones(n), -1 * np.ones(n), -1 * np.ones(n)], [0, -1, 1], n, n, format='csc')
 
         x_out = np.rollaxis(spsolve(self.gamma * lap_op, rho * np.rollaxis(x0, self.axis, 0)), self.axis, 0)
 
         return x_out
+
+    def objective(self, x):
+        n = x.shape[self.axis]
+        # lap_op = spdiags([(2 + rho / self.gamma) * np.ones(n), -1 * np.ones(n), -1 * np.ones(n)], [0, -1, 1], n, n, format='csc')
+        # TODO: add objective for this operator
+        return 0