Add postprocessing to visualize energy metrics

Relevant: % hosts with low energy (= RESCUE mode), % hosts with no energy (no transfer possible)

Graphic looks like

and was also added to evaluation pdf.

toolkit/reportSummary/energyAnalysis.py

+import matplotlib.pyplot as plt
+import sys
+import re
+import matplotlib.ticker as ticker
+
+# Script that translates energy level analysis into plots of percentages of hosts with low or no energy.
+# Takes as arguments
+# (1) an energy level report file
+# (2) path to save the graphic to.
+#
+# The energy level analysis file should have a format like:
+#
+# [600]
+# 600,p0,0.8116
+# ...
+# 600,c2999,0.4448
+# [1200]
+# 1200,p0,0.7556
+# ...
+# 50400,c2999,0.0000
+
+# Class responsible for summarizing energy data fed into it by time point and host.
+class EnergyData:
+    # Summarized data
+    timePoints = []
+    zeroEnergyHosts = []
+    lowEnergyHosts = []
+
+    # Current counters
+    currentTimePoint = 0
+    currentTotalHosts = 0
+    currentZeroEnergyHosts = 0
+    currentLowEnergyHosts = 0
+
+    # Transfers current counters into new elements of the summarizing data vectors.
+    def updateData(self):
+        self.timePoints.append(self.currentTimePoint)
+        self.zeroEnergyHosts.append(self.currentZeroEnergyHosts / self.currentTotalHosts)
+        self.lowEnergyHosts.append(self.currentLowEnergyHosts / self.currentTotalHosts)
+
+    # Resets current counters to 0.
+    def resetCounters(self):
+        self.currentTotalHosts = 0
+        self.currentZeroEnergyHosts = 0
+        self.currentLowEnergyHosts = 0
+
+    # Updates counters with a new energy level at the current time point.
+    def updateCounters(self, energyLevel):
+        self.currentTotalHosts += 1
+        if energyLevel == 0:
+            self.currentZeroEnergyHosts += 1
+        elif energyLevel < 0.1:
+            self.currentLowEnergyHosts += 1
+
+# Draws two functions over the same x values.
+# Labels are selected as appropriate for energy analysis.
+def drawPlots(x, y_lowEnergy, y_noEnergy):
+    plt.title('Battery power distribution')
+    plt.xlabel('Minutes in simulation')
+    plt.ylabel('Percentage of hosts')
+    plt.plot(x, y_lowEnergy, '.-', label='Battery 0% < x < 10%')
+    plt.plot(x, y_noEnergy, '.-',  label='No battery left')
+    plt.legend(loc='upper left')
+    plt.grid(True)
+    axes = plt.gca()
+    axes.set_ylim(ymin=0,ymax=1)
+    axes.set_xlim(xmin=0)
+    axes.xaxis.set_major_locator(ticker.IndexLocator(base=60, offset=-10))
+
+# Main function of the script. See script description at the top of the file for further information.
+def main(analysisFileName, graphicFileName):
+    # Read energy level analysis from file
+    with open(analysisFileName) as analysis_file:
+        analysis = analysis_file.readlines()
+
+    # Traverse analysis line by line to find the number of zero and low energy hosts by time
+    data = EnergyData()
+    for line in analysis:
+        timeMatch = re.match("\[(\d+)\]", line)
+        energyMatch = re.match("\d+,\D+\d+,(\d+.\d+)", line)
+        # If the line looks like "[600]", i.e. the report changes to the next time frame, we have to finalize the
+        # data we collected for the last time point (if there was such) and then reset our counters.
+        if timeMatch is not None:
+            if data.currentTimePoint is not 0:
+                data.updateData()
+            data.currentTimePoint = float(timeMatch.group(1)) / 60
+            data.resetCounters()
+        # Otherwise, if the line looks like '600,p0,0.8116', it is another data point for the current time and we
+        # should update our counters using the logged energy.
+        if energyMatch is not None:
+            data.updateCounters(energyLevel=float(energyMatch.group(1)))
+
+    drawPlots(x=data.timePoints, y_lowEnergy=data.lowEnergyHosts, y_noEnergy=data.zeroEnergyHosts)
+
+    # Save to file
+    plt.savefig(graphicFileName)
+    plt.close()
+
+# Make sure script can be called from command line.
+if __name__ == "__main__":
+    main(sys.argv[1], sys.argv[2])
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