Other plots

.gitignore

@@ -5,3 +5,4 @@ myenv
 doc/_build
 !results/plots.py
 Frontend/
+smallConf.py

DAS/visualizer.py

@@ -6,6 +6,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 import seaborn as sns
 from itertools import combinations
+from mplfinance.original_flavor import candlestick_ohlc
 
 class Visualizer:
 
@@ -83,7 +84,7 @@ class Visualizer:
         return data
 
     def averageRuns(self, data, runs):
-        """Get the average of run 0 and run 1 for each key"""
+        """Get the average of all runs for each key"""
         newData = {}
         allTta = []
         print("Getting the average of the runs...")
@@ -207,3 +208,38 @@ class Visualizer:
         filename = os.path.join(histogramFolder, 'histogram.png')
         plt.savefig(filename)
         plt.clf()
+
+    def plotHist(self, bandwidth):
+        """Plot Bandwidth Frequency Histogram"""
+        plt.hist(bandwidth, bins=5)
+        plt.xlabel('Bandwidth')
+        plt.ylabel('Frequency')
+        plt.title('Bandwidth Histogram')
+
+        """Create the directory if it doesn't exist already"""
+        histogramFolder = self.folderPath + '/histogram'
+        if not os.path.exists(histogramFolder):
+            os.makedirs(histogramFolder)
+        filename = os.path.join(histogramFolder, 'histogram.png')
+        plt.savefig(filename)
+        plt.clf()
+
+    def plotCandleStick(self, TX_prod, TX_avg, TX_max):
+        #x-axis corresponding to steps
+        steps = range(len(TX_prod))
+
+        #Plot the candlestick chart
+        ohlc = []
+        for i in range(len(TX_prod)):
+            ohlc.append([steps[i], TX_prod[i], TX_max[i], TX_avg[i]])
+        fig, ax = plt.subplots()
+        candlestick_ohlc(ax, ohlc, width=0.6, colorup='green', colordown='red')
+
+        #Ticks, title and labels
+        plt.xticks(steps, ['run{}'.format(i) for i in steps], rotation=45)
+        plt.title('Candlestick Chart')
+        plt.xlabel('Step')
+        plt.ylabel('Price')
+
+        #Test
+        plt.show()

smallConf.py

@@ -19,6 +19,13 @@ import numpy as np
 from DAS.shape import Shape
 
 dumpXML = 1
+
+# save progress vectors to XML
+saveProgress = 1
+
+# plot progress for each run to PNG
+plotProgress = 1
+
 visualization = 1
 logLevel = logging.INFO
 
@@ -34,26 +41,26 @@ evenLineDistribution = True
 runs = range(3)
 
 # Number of validators
-numberNodes = range(256, 313, 128)
+numberNodes = range(128, 513, 128)
 
 # Percentage of block not released by producer
-failureRates = range(10, 31, 40)
+failureRates = range(40, 81, 20)
 
 # Block size in one dimension in segments. Block is blockSizes * blockSizes segments.
-blockSizes = range(32,35,16)
+blockSizes = range(64, 113, 128)
 
 # Per-topic mesh neighborhood size
-netDegrees = range(6, 9, 2)
+netDegrees = range(8, 9, 2)
 
 # number of rows and columns a validator is interested in
-chis = range(2, 5, 2)
+chis = range(2, 3, 2)
 
 # ratio of class1 nodes (see below for parameters per class)
-class1ratios = [0.8, 0.9]
+class1ratios = [0.8]
 
 # Number of validators per beacon node
-validatorsPerNode1 = [1]
+validatorsPerNode1 = [2]
-validatorsPerNode2 = [50]
+validatorsPerNode2 = [4]
 
 # Set uplink bandwidth. In segments (~560 bytes) per timestep (50ms?)
 # 1 Mbps ~= 1e6 / 20 / 8 / 560 ~= 11
@@ -67,6 +74,20 @@ deterministic = True
 # If your run is deterministic you can decide the random seed. This is ignore otherwise.
 randomSeed = "DAS"
 
+saveProgress = 1
+saveRCdist = 1
+
+# If True, print diagnostics when the block is not available
+diagnostics = False
+
+# Number of steps without progress to stop simulation
+steps4StopCondition = 7
+
+saveGit = False
+
+successCondition = 0.9
+stepDuration = 50
+
 def nextShape():
     for run, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
         runs, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):