Enabled the Histogram script again

DRAMSys/analyzer/scripts/plots.py

@@ -80,16 +80,16 @@ def memory_utilisation_window(connection, tracePath, steps):
     subplotIndex = 211
     plt.subplot(subplotIndex)
     plt.plot(time, bandwidthPercentage)
-    plt.xlabel('Time (ns)')
-    plt.ylabel('Bandwidth (%)')
+    plt.xlabel('Time [ns]')
+    plt.ylabel('Bandwidth [%]')
     plt.ylim(-1, maximumPercentage + (10 - maximumPercentage%10))
     plt.grid(True)
 
     subplotIndex += 1
     plt.subplot(subplotIndex)
     plt.plot(time, bandwidth)
-    plt.xlabel('Time (ns)')
-    plt.ylabel('Bandwidth (Gibit/s)')
+    plt.xlabel('Time [ns]')
+    plt.ylabel('Bandwidth [Gibit/s]')
     plt.ylim((-0.01)*float(maxDataRate)/1024, ((maximumPercentage + (10 - maximumPercentage%10))/100)*float(maxDataRate)/1024)
     plt.grid(True)
 
@@ -123,7 +123,6 @@ def power_window(connection, tracePath, steps):
         name = ntpath.basename(tracePath)
         basename, extension = os.path.splitext(name)
 
-
         OUTPUT_FILE = 'power_' + basename + '.pdf'
         outputFile = "\n" + "Output file is {0}".format(OUTPUT_FILE)
 
@@ -131,8 +130,8 @@ def power_window(connection, tracePath, steps):
         from matplotlib.backends.backend_pdf import PdfPages
 
         plt.plot(time, power)
-        plt.xlabel('Time (ns)')
-        plt.ylabel('Power (mW)')
+        plt.xlabel('Time [ns]')
+        plt.ylabel('Power [mW]')
         plt.grid(True)
         pdf = PdfPages(OUTPUT_FILE)
         pdf.savefig()
@@ -140,18 +139,33 @@ def power_window(connection, tracePath, steps):
         plt.close()
     return outputFile
 
-# @plot
-# def latency_histogram(connection):
-#     # This function plots an histogram with access latencys
-#     cursor = connection.cursor()
-#     cursor.execute("SELECT ((p2.PhaseEnd - p1.PhaseEnd)/1000) FROM Transactions t, Phases p1, Phases p2 WHERE t.id = p1.Transact and t.id = p2.Transact and p1.PhaseName = \"REQ\" and p2.PhaseName = \"RESP\" ")
-#     result = cursor.fetchall()
-#     #result.sort()
-#     #print(max(result)[0])
-#     import matplotlib.pyplot as plt
-#     plt.hist(result, bins=max(result)[0], histtype='barstacked')
-#     plt.savefig('hist.png')
-#     return "Saved as hist.png"
+@plot
+def latency_histogram(connection, tracePath, steps):
+    # This function plots an histogram with access latencys
+    outputFile = ""
+    cursor = connection.cursor()
+    cursor.execute("SELECT ((p2.PhaseEnd - p1.PhaseEnd)/1000) FROM Transactions t, Phases p1, Phases p2 WHERE t.id = p1.Transact and t.id = p2.Transact and p1.PhaseName = \"REQ\" and p2.PhaseName = \"RESP\" ")
+    result = cursor.fetchall()
+
+    name = ntpath.basename(tracePath)
+    basename, extension = os.path.splitext(name)
+
+    OUTPUT_FILE = 'hist_' + basename + '.pdf'
+    outputFile = "\n" + "Output file is {0}".format(OUTPUT_FILE)
+
+    numberOfBins=50
+
+    import matplotlib.pyplot as plt
+    from matplotlib.backends.backend_pdf import PdfPages
+    plt.hist(result, bins=numberOfBins, histtype='barstacked', facecolor='green')
+    plt.grid(True)
+    plt.xlabel("Access Time [ns]")
+    plt.ylabel("Number (Frequency)")
+    pdf = PdfPages(OUTPUT_FILE)
+    pdf.savefig()
+    pdf.close()
+    plt.close()
+    return outputFile
 
 
 def generatePlots(pathToTrace):
@@ -169,7 +183,7 @@ def generatePlots(pathToTrace):
     else:
         cursor.execute(" SELECT TraceEnd FROM GeneralInfo ")
         traceEnd = float(cursor.fetchone()[0])
-        steps = ceil(traceEnd/windowSize)
+        steps = int(ceil(traceEnd/windowSize))
         for p in plots:
             outputFiles += p(connection, pathToTrace, steps)