minor plot fixes

.gitignore

@@ -1,4 +1,5 @@
 *.swp
 *.pyc
 results/*
-!results/plots.py
+!results/plots.py
+Frontend/

DAS/visualizer.py

@@ -13,9 +13,10 @@ class Visualizer:
         self.execID = execID
         self.folderPath = "results/"+self.execID
         self.parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree', 'chi']
+        self.minimumDataPoints = 2
 
-    #Store data with a unique key for each params combination
     def plottingData(self):
+        #Store data with a unique key for each params combination
         data = {}
         #Loop over the xml files in the folder
         for filename in os.listdir(self.folderPath):
@@ -65,8 +66,8 @@ class Visualizer:
         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):
+        #Get the keys for all data with the same x and y labels
         filteredKeys = {}
         for key1, value1 in data.items():
             subKeys1 = list(value1.keys())
@@ -81,14 +82,19 @@ class Visualizer:
         print("Getting filtered keys from data...")
         return filteredKeys
 
-    #Title formatting for the figures
+    def formatLabel(self, label):
+        #Label formatting for the figures
+        result = ''.join([f" {char}" if char.isupper() else char for char in label])
+        return result.title()
+    
     def formatTitle(self, key):
+        #Title formatting for the figures
         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):
+        #Plot and store the 2D heatmaps in subfolders
         data = self.plottingData()
         filteredKeys = self.similarKeys(data)
         print("Plotting heatmaps...")
@@ -103,12 +109,14 @@ class Visualizer:
             for key in keys:
                 xlabels = np.sort(np.unique(data[key][labels[0]]))
                 ylabels = np.sort(np.unique(data[key][labels[1]]))
+                if len(xlabels) < self.minimumDataPoints or len(ylabels) < self.minimumDataPoints:
+                    continue
                 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.xlabel(self.formatLabel(labels[0]))
-                plt.ylabel(labels[1])
+                plt.ylabel(self.formatLabel(labels[1]))
                 filename = ""
                 title = ""
                 paramValueCnt = 0

results/plots.py

@@ -1,138 +0,0 @@
-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
-
-parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree', 'chi']
-
-#Title formatting for the figures
-def formatTitle(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} "
-
-def getLatestDirectory():
-    resultsFolder = os.getcwd()
-
-    #Get all folders and store their time info and sort
-    directories = [d for d in os.listdir(resultsFolder) if os.path.isdir(os.path.join(resultsFolder, d))]
-    directoriesTime = [(d, os.path.getctime(os.path.join(resultsFolder, d))) for d in directories]
-    directoriesTime.sort(key=lambda x: x[1], reverse=True)
-
-    #Get the path of the latest created folder
-    latestDirectory = directoriesTime[0][0]
-    folderPath = os.path.join(resultsFolder, latestDirectory)
-    return folderPath
-
-def plottingData(folderPath):
-    #Store data with a unique key for each params combination
-    data = {}
-    plotInfo = {}
-
-    #Loop over the xml files in the folder
-    for filename in os.listdir(folderPath):
-        #Loop over the xmls and store the data in variables
-        if filename.endswith('.xml'):
-            tree = ET.parse(os.path.join(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(parameters, 4):
-                # Get the indices and values of the parameters in the combination
-                indices = [parameters.index(element) for element in combination]
-                selectedValues = [run, blockSize, failureRate, numberValidators, netDegree, chi]
-                values = [selectedValues[index] for index in indices]
-                names = [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 = [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(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)
-    return data
-
-def similarKeys(data):
-    #Get the keys for all data with the same x and y labels
-    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]
-    return filteredKeys
-
-def plotHeatmaps(folderPath, filteredKeys, data):
-    #Store the 2D heatmaps in a folder
-    heatmapsFolder = folderPath+'/heatmaps'
-    if not os.path.exists(heatmapsFolder):
-        os.makedirs(heatmapsFolder)
-
-    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 parameters:
-                if param != labels[0] and param != labels[1]:
-                    filename += f"{key[paramValueCnt]}"
-                    title += formatTitle(key[paramValueCnt])
-                    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()
-
-def generateHeatmaps(folderPath):
-    #folderPath = getLatestDirectory()
-    data = plottingData(folderPath)
-    filteredKeys = similarKeys(data)
-    plotHeatmaps(folderPath, filteredKeys, data)
-
-generateHeatmaps(sys.argv[1])