diff --git a/examples/SWFW/playground.py b/examples/SWFW/playground.py
index e9f0afa5c8..a6a03c11ff 100644
--- a/examples/SWFW/playground.py
+++ b/examples/SWFW/playground.py
@@ -19,18 +19,21 @@
     logger = Log.setup_custom_logger('root')
 
     num_procs = 1
+    
+    N_s = 100
+    N_f = 125
 
     # This comes as read-in for the level class
     lparams = {}
     lparams['restol'] = 1E-12
 
     sparams = {}
-    sparams['maxiter'] = 2
+    sparams['maxiter'] = 4
 
     # This comes as read-in for the problem class
     pparams = {}
-    pparams['lambda_s'] = 1j*np.linspace(0,3,100)
-    pparams['lambda_f'] = 1j*np.linspace(0,8,100)
+    pparams['lambda_s'] = 1j*np.linspace(0.0, 4.0, N_s)
+    pparams['lambda_f'] = 1j*np.linspace(0.0, 8.0, N_f)
     pparams['u0'] = 1
 
     # Fill description dictionary for easy hierarchy creation
@@ -40,7 +43,8 @@
     description['dtype_u'] = mesh
     description['dtype_f'] = rhs_imex_mesh
     description['collocation_class'] = collclass.CollGaussLobatto
-    description['num_nodes'] = [2]
+    description['num_nodes'] = [3]
+    description['do_LU'] = False
     description['sweeper_class'] = imex_1st_order
     description['level_params'] = lparams
 
@@ -62,15 +66,19 @@
 
     uex = P.u_exact(Tend)
 
-    fig = plt.figure(figsize=(8,8))
-    plt.pcolor(pparams['lambda_s'].imag, pparams['lambda_f'].imag, np.absolute(uend.values).T,vmin=1,vmax=1.01)
+    fig = plt.figure(figsize=(4,4))
+    #pcol = plt.pcolor(pparams['lambda_s'].imag, pparams['lambda_f'].imag, np.absolute(uend.values).T, vmin=0.99, vmax=1.01)
+    pcol = plt.pcolor(pparams['lambda_s'].imag, pparams['lambda_f'].imag, np.absolute(uend.values).T, vmin=1.0, vmax=2.0)
     # plt.pcolor(np.imag(uend.values))
-    plt.colorbar()
-    plt.xlabel('$\Delta t \lambda_{slow}$', fontsize=18, labelpad=20)
+    pcol.set_edgecolor('face')
+    plt.plot([0, 4], [0, 4], color='w', linewidth=2.5)
+    #plt.colorbar()
+    plt.gca().set_xticks([0.0, 1.0, 2.0, 3.0])
+    plt.xlabel('$\Delta t \lambda_{slow}$', fontsize=18, labelpad=0.0)
     plt.ylabel('$\Delta t \lambda_{fast}$', fontsize=18)
 
-    plt.show()
-
+    #plt.show()
+    fig.savefig('sdc-fwsw-stability-K'+str(sparams['maxiter'])+'-M'+str(description['num_nodes'][0])+'.pdf', bbox_inches='tight')
     print('error at time %s: %s' %(Tend,np.linalg.norm(uex.values-uend.values,np.inf)/np.linalg.norm(uex.values,
                                                                                                      np.inf)))