das-research/DAS/visualizer.py

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#!/bin/python3
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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
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class Visualizer:
def __init__(self, execID):
self.execID = execID
self.folderPath = "results/"+self.execID
self.parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree',
'chi', 'vpn1', 'vpn2', 'bwUplinkProd', 'bwUplink1', 'bwUplink2']
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self.minimumDataPoints = 2
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def plottingData(self):
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#Store data with a unique key for each params combination
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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)
vpn1 = int(root.find('vpn1').text)
vpn2 = int(root.find('vpn2').text)
bwUplinkProd = int(root.find('bwUplinkProd').text)
bwUplink1 = int(root.find('bwUplink1').text)
bwUplink2 = int(root.find('bwUplink2').text)
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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, vpn1, vpn2, bwUplinkProd, bwUplink1, bwUplink2]
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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(len(self.parameters)) if i not in indices]
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#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)
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print("Getting data from the folder...")
return data
def similarKeys(self, data):
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#Get the keys for all data with the same x and y labels
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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]
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print("Getting filtered keys from data...")
return filteredKeys
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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()
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def formatTitle(self, key):
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#Title formatting for the figures
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name = ''.join([f" {char}" if char.isupper() else char for char in key.split('_')[0]])
number = key.split('_')[1]
return f"{name.title()}: {number} "
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def plotHeatmaps(self):
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#Plot and store the 2D heatmaps in subfolders
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data = self.plottingData()
filteredKeys = self.similarKeys(data)
print("Plotting heatmaps...")
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#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]]))
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if len(xlabels) < self.minimumDataPoints or len(ylabels) < self.minimumDataPoints:
continue
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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)
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plt.xlabel(self.formatLabel(labels[0]))
plt.ylabel(self.formatLabel(labels[1]))
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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()