vis class

DAS/visualizer.py

@@ -1,22 +1,130 @@
 #!/bin/python3
+import os, sys
+import time
+import xml.etree.ElementTree as ET
+import matplotlib.pyplot as plt
+import numpy as np
+import seaborn as sns
+from itertools import combinations
 
 class Visualizer:
 
     def __init__(self, execID):
         self.execID = execID
         self.folderPath = "results/"+self.execID
+        self.parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree', 'chi']
 
+    #Store data with a unique key for each params combination
     def plottingData(self):
-        data = []
+        data = {}
+        #Loop over the xml files in the folder
+        for filename in os.listdir(self.folderPath):
+            #Loop over the xmls and store the data in variables
+            if filename.endswith('.xml'):
+                tree = ET.parse(os.path.join(self.folderPath, filename))
+                root = tree.getroot()
+                run = int(root.find('run').text)
+                blockSize = int(root.find('blockSize').text)
+                failureRate = int(root.find('failureRate').text)
+                numberValidators = int(root.find('numberValidators').text)
+                netDegree = int(root.find('netDegree').text)
+                chi = int(root.find('chi').text)
+                tta = int(root.find('tta').text)
+
+                # Loop over all possible combinations of length 4 of the parameters
+                for combination in combinations(self.parameters, 4):
+                    # Get the indices and values of the parameters in the combination
+                    indices = [self.parameters.index(element) for element in combination]
+                    selectedValues = [run, blockSize, failureRate, numberValidators, netDegree, chi]
+                    values = [selectedValues[index] for index in indices]
+                    names = [self.parameters[i] for i in indices]
+                    keyComponents = [f"{name}_{value}" for name, value in zip(names, values)]
+                    key = tuple(keyComponents[:4])
+                    #Get the names of the other 2 parameters that are not included in the key
+                    otherParams = [self.parameters[i] for i in range(6) if i not in indices]
+                    #Append the values of the other 2 parameters and the ttas to the lists for the key
+                    otherIndices = [i for i in range(len(self.parameters)) if i not in indices]
+
+                    #Initialize the dictionary for the key if it doesn't exist yet
+                    if key not in data:
+                        data[key] = {}
+                        #Initialize lists for the other 2 parameters and the ttas with the key
+                        data[key][otherParams[0]] = []
+                        data[key][otherParams[1]] = []
+                        data[key]['ttas'] = []
+
+                    if otherParams[0] in data[key]:
+                        data[key][otherParams[0]].append(selectedValues[otherIndices[0]])
+                    else:
+                        data[key][otherParams[0]] = [selectedValues[otherIndices[0]]]
+                    if otherParams[1] in data[key]:
+                        data[key][otherParams[1]].append(selectedValues[otherIndices[1]])
+                    else:
+                        data[key][otherParams[1]] = [selectedValues[otherIndices[1]]]
+                    data[key]['ttas'].append(tta)
         print("Getting data from the folder...")
         return data
 
+    #Get the keys for all data with the same x and y labels
     def similarKeys(self, data):
-        filteredKeys = []
+        filteredKeys = {}
+        for key1, value1 in data.items():
+            subKeys1 = list(value1.keys())
+            filteredKeys[(subKeys1[0], subKeys1[1])] = [key1]
+            for key2, value2 in data.items():
+                subKeys2 = list(value2.keys())
+                if key1 != key2 and subKeys1[0] == subKeys2[0] and subKeys1[1] == subKeys2[1]:
+                    try:
+                        filteredKeys[(subKeys1[0], subKeys1[1])].append(key2)
+                    except KeyError:
+                        filteredKeys[(subKeys1[0], subKeys1[1])] = [key2]
         print("Getting filtered keys from data...")
         return filteredKeys
 
+    #Title formatting for the figures
+    def formatTitle(self, key):
+        name = ''.join([f" {char}" if char.isupper() else char for char in key.split('_')[0]])
+        number = key.split('_')[1]
+        return f"{name.title()}: {number} "
+
+    #Plot and store the 2D heatmaps in subfolders
     def plotHeatmaps(self):
         data = self.plottingData()
         filteredKeys = self.similarKeys(data)
         print("Plotting heatmaps...")
+        
+        #Create the directory if it doesn't exist already
+        heatmapsFolder = self.folderPath + '/heatmaps'
+        if not os.path.exists(heatmapsFolder):
+            os.makedirs(heatmapsFolder)
+
+        #Plot
+        for labels, keys in filteredKeys.items():
+            for key in keys:
+                xlabels = np.sort(np.unique(data[key][labels[0]]))
+                ylabels = np.sort(np.unique(data[key][labels[1]]))
+                hist, xedges, yedges = np.histogram2d(data[key][labels[0]], data[key][labels[1]], bins=(len(xlabels), len(ylabels)), weights=data[key]['ttas'])
+                hist = hist.T
+                fig, ax = plt.subplots(figsize=(10, 6))
+                sns.heatmap(hist, xticklabels=xlabels, yticklabels=ylabels, cmap='Purples', cbar_kws={'label': 'Time to block availability'}, linecolor='black', linewidths=0.3, annot=True, fmt=".2f", ax=ax)
+                plt.xlabel(labels[0])
+                plt.ylabel(labels[1])
+                filename = ""
+                title = ""
+                paramValueCnt = 0
+                for param in self.parameters:
+                    if param != labels[0] and param != labels[1]:
+                        filename += f"{key[paramValueCnt]}"
+                        formattedTitle = self.formatTitle(key[paramValueCnt])
+                        title += formattedTitle
+                        paramValueCnt += 1
+                title_obj = plt.title(title)
+                font_size = 16 * fig.get_size_inches()[0] / 10
+                title_obj.set_fontsize(font_size)
+                filename = filename + ".png"
+                targetFolder = os.path.join(heatmapsFolder, f"{labels[0]}Vs{labels[1]}")
+                if not os.path.exists(targetFolder):
+                    os.makedirs(targetFolder)
+                plt.savefig(os.path.join(targetFolder, filename))
+                plt.close()
+                plt.clf()