diff --git a/DRAMSys/analyzer/scripts/plots.py b/DRAMSys/analyzer/scripts/plots.py
index db72ec99..e4b0e71d 100755
--- a/DRAMSys/analyzer/scripts/plots.py
+++ b/DRAMSys/analyzer/scripts/plots.py
@@ -24,6 +24,7 @@ def memory_utilisation_window(connection, tracePath, steps):
 
     cursor = connection.cursor()
     cursor.execute(" SELECT time FROM Power WHERE averagePower = 0 ")
+    #pow(10,12): seconds to picoseconds conversion
     windowSize = pow(10,12)*float(cursor.fetchone()[0])
     # All possible cases of data transfers inside a time window
     queryFull = """ SELECT sum(DataStrobeEnd - DataStrobeBegin) FROM transactions Where DataStrobeBegin > ? and DataStrobeEnd < ?"""  # The data transfer begins and ends inside the time window
@@ -72,13 +73,14 @@ def memory_utilisation_window(connection, tracePath, steps):
     import numpy as np
     from matplotlib.backends.backend_pdf import PdfPages
 
-    time = np.arange(0, (steps+1)*windowSize, windowSize)
+    #windowSize/1000: picoseconds to nanoseconds conversion
+    time = np.arange(0, (steps+1)*windowSize/1000, windowSize/1000)
 
     plt.figure()
 
     subplotIndex = 211
     plt.subplot(subplotIndex)
-    plt.plot(time/1000, bandwidthPercentage)
+    plt.plot(time, bandwidthPercentage)
     plt.xlabel('Time (ns)')
     plt.ylabel('Bandwidth (%)')
     plt.ylim(-1, maximumPercentage + (10 - maximumPercentage%10))
@@ -117,6 +119,7 @@ def power_window(connection, tracePath, steps):
         power[0] = 0
         for i in range((steps)):
             result = cursor.fetchone()
+            #pow(10,9): seconds to nanoseconds conversion
             time[i+1] = float(result[0])*pow(10,9)
             power[i+1] = float(result[1])
 
@@ -169,6 +172,7 @@ def generatePlots(pathToTrace):
         cursor.execute(" SELECT TraceEnd FROM GeneralInfo ")
         traceEnd = float(cursor.fetchone()[0])
         cursor.execute(" SELECT min(time) FROM Power WHERE averagePower = 0")
+        #pow(10,12): seconds to picoseconds conversion
         windowSize = pow(10,12)*float(cursor.fetchone()[0])
         steps = ceil(traceEnd/windowSize)
         for p in plots: