diff --git a/figures/energy_perf_bar.py b/figures/energy_perf_bar.py
index d5baac5..3738684 100644
--- a/figures/energy_perf_bar.py
+++ b/figures/energy_perf_bar.py
@@ -35,10 +35,10 @@ def plot_energy_perf_bar(args, threshold_list, budget):
 
 	# finding points with 3% threshold of target budget/inefficiency
 	thresh = 3
-	energy_bar_data = [ [] for thresh in threshold_list]
-	performance_bar_data = [ [] for thresh in threshold_list]
-	energy_bar_data_nocost = [ [] for thresh in threshold_list]
-	performance_bar_data_nocost = [ [] for thresh in threshold_list]
+	energy_bar_data = [ [] for thr in threshold_list]
+	performance_bar_data = [ [] for thr in threshold_list]
+	energy_bar_data_nocost = [ [] for thr in threshold_list]
+	performance_bar_data_nocost = [ [] for thr in threshold_list]
 
 	print budget
 	for threshold_index, cluster_thresh in enumerate(threshold_list):
@@ -268,8 +268,8 @@ def plot_abs_energy_time_bar(args, budget_list, cluster_thresh, perf_cost, energ
 
 	# finding points with 3% threshold of target budget/inefficiency
 	thresh = 3
-	energy_bar_data = [ [] for thresh in budget_list]
-	performance_bar_data = [ [] for thresh in budget_list]
+	energy_bar_data = [ [] for thr in budget_list]
+	performance_bar_data = [ [] for thr in budget_list]
 	for budget_index, budget in enumerate(budget_list):
 		data = []
 		for bmark in benchmarks:
diff --git a/figures/notuning_wtuning.py b/figures/notuning_wtuning.py
index 740917e..864e925 100644
--- a/figures/notuning_wtuning.py
+++ b/figures/notuning_wtuning.py
@@ -84,7 +84,7 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 			print "Inefficiency Budget: "+str(budget)+" Benchmark: "+bmark
 			
 			aggr_opt_point, energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
-			print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
+			#print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
 
 			bmarkDirPath = os.path.join(os.path.join(dir_path, "per_sample_data"), bmark)
 			frontiers_file = os.path.join(bmarkDirPath, "per_sample_frontiers.json")
@@ -180,8 +180,8 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 							performance += get_performance(frontiers_data,optimal_point[0], optimal_point[1], idx)
 							aggr_energy += get_energy(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
 							aggr_performance += get_performance(frontiers_data,	aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
-							if aggr_energy < energy:
-								print "unexpected!"
+#							if aggr_energy < energy:
+#								print "unexpected!"
 				#			print "("+str(optimal_point[0])+", "+str(optimal_point[1])+", "+str(energy)+", "+str(performance)+")  "+"("+str(aggr_opt_point["cpu_freq"])+", "+str(aggr_opt_point["mem_freq"])+", "+str(aggr_energy)+", "+str(aggr_performance)+") --- " + str((energy - aggr_energy) * 100 / aggr_energy) +"  " +str((performance - aggr_performance) * 100 / aggr_performance)
 							if index < len(samplepoints):
 								if idx == samplepoints[index]-2:
@@ -218,8 +218,9 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 			performance_data[budget_index].append(performance)
 			aggr_energy = (aggr_energy + (num_transitions * energy_cost))/1e6
 			aggr_performance = (aggr_performance +(num_transitions * perf_cost))/1e6 
-			print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
-			print "w.tuning: performance (ms): "+str(performance)+" energy(mJ): "+str(energy) + "   "+ str((energy - aggr_energy) * 100 / aggr_energy) +"%  " +str((performance - aggr_performance) * 100 / aggr_performance)+"%\n"
+			#print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
+			#print "w.tuning: performance (ms): "+str(performance)+" energy(mJ): "+str(energy) + "   "+ str((energy - aggr_energy) * 100 / aggr_energy) +"%  " +str((performance - aggr_performance) * 100 / aggr_performance)+"%\n"
+			print "w.tuning: energy: "+ str(((energy - aggr_energy) * 10000 / aggr_energy)/100) +"%   execution time:" +str(((performance - aggr_performance) * 10000 / aggr_performance)/100)+"%\n"
 
 def main(argv):
 	args = parse(argv)
diff --git a/figures/stable_length_box_thresholds.py b/figures/stable_length_box_thresholds.py
index 343bd3f..4019559 100644
--- a/figures/stable_length_box_thresholds.py
+++ b/figures/stable_length_box_thresholds.py
@@ -23,7 +23,7 @@ def plot_stable_length_box(args, threshold_list, budget_list):
 	# finding points with 3% threshold of target budget/inefficiency
 	thresh = 3
 	for bmark in benchmarks: 
-	  box_data = [ [] for thresh in threshold_list]
+	  box_data = [ [] for thr in threshold_list]
 	  for threshold_index, cluster_thresh in enumerate(threshold_list):
 		data = []
 		for budget in budget_list:
diff --git a/figures/stable_line.py b/figures/stable_line.py
index fc79699..ee9e7fa 100644
--- a/figures/stable_line.py
+++ b/figures/stable_line.py
@@ -411,7 +411,7 @@ def plot_stable_length_box_across_thresholds(args, threshold_list, budget):
 
 	# finding points with 3% threshold of target budget/inefficiency
 	thresh = 3
-	box_data = [ [] for thresh in threshold_list]
+	box_data = [ [] for thr in threshold_list]
 	for threshold_index, cluster_thresh in enumerate(threshold_list):
 		data = []
 		for bmark in benchmarks: