2023-02-22 15:45:39 +00:00
|
|
|
#!/bin/python3
|
2023-02-23 13:37:45 +00:00
|
|
|
import os, sys
|
|
|
|
import time
|
|
|
|
import xml.etree.ElementTree as ET
|
|
|
|
import matplotlib.pyplot as plt
|
|
|
|
import numpy as np
|
2023-07-12 19:15:08 +00:00
|
|
|
import pandas as pd
|
2023-02-23 13:37:45 +00:00
|
|
|
import seaborn as sns
|
|
|
|
from itertools import combinations
|
2023-04-21 09:45:17 +00:00
|
|
|
from mplfinance.original_flavor import candlestick_ohlc
|
2023-04-23 14:55:31 +00:00
|
|
|
import os
|
|
|
|
|
2023-02-22 15:45:39 +00:00
|
|
|
|
|
|
|
class Visualizer:
|
|
|
|
|
2023-04-20 16:15:02 +00:00
|
|
|
def __init__(self, execID, config):
|
2023-02-22 15:45:39 +00:00
|
|
|
self.execID = execID
|
2023-04-20 16:15:02 +00:00
|
|
|
self.config = config
|
2023-02-22 15:45:39 +00:00
|
|
|
self.folderPath = "results/"+self.execID
|
2023-03-30 11:24:30 +00:00
|
|
|
self.parameters = ['run', 'blockSize', 'failureRate', 'numberNodes', 'netDegree', 'chi', 'vpn1', 'vpn2', 'class1ratio', 'bwUplinkProd', 'bwUplink1', 'bwUplink2']
|
2023-02-26 17:36:02 +00:00
|
|
|
self.minimumDataPoints = 2
|
2023-04-27 11:58:51 +00:00
|
|
|
self.maxTTA = 11000
|
2023-02-22 15:45:39 +00:00
|
|
|
|
|
|
|
def plottingData(self):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Store data with a unique key for each params combination"""
|
2023-02-23 13:37:45 +00:00
|
|
|
data = {}
|
2023-03-30 11:24:30 +00:00
|
|
|
bw = []
|
2023-04-21 15:14:55 +00:00
|
|
|
print("Getting data from the folder...")
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Loop over the xml files in the folder"""
|
2023-02-23 13:37:45 +00:00
|
|
|
for filename in os.listdir(self.folderPath):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Loop over the xmls and store the data in variables"""
|
2023-02-23 13:37:45 +00:00
|
|
|
if filename.endswith('.xml'):
|
|
|
|
tree = ET.parse(os.path.join(self.folderPath, filename))
|
|
|
|
root = tree.getroot()
|
|
|
|
run = int(root.find('run').text)
|
2023-07-12 12:03:32 +00:00
|
|
|
blockSize = int(root.find('blockSizeR').text) # TODO: maybe we want both dimensions
|
2023-02-23 13:37:45 +00:00
|
|
|
failureRate = int(root.find('failureRate').text)
|
2023-03-13 14:03:55 +00:00
|
|
|
numberNodes = int(root.find('numberNodes').text)
|
2023-03-30 11:24:30 +00:00
|
|
|
class1ratio = float(root.find('class1ratio').text)
|
2023-02-23 13:37:45 +00:00
|
|
|
netDegree = int(root.find('netDegree').text)
|
2023-07-12 12:03:32 +00:00
|
|
|
chi = int(root.find('chiR').text) # TODO: maybe we want both dimensions
|
2023-03-13 14:00:43 +00:00
|
|
|
vpn1 = int(root.find('vpn1').text)
|
|
|
|
vpn2 = int(root.find('vpn2').text)
|
2023-03-07 13:36:13 +00:00
|
|
|
bwUplinkProd = int(root.find('bwUplinkProd').text)
|
|
|
|
bwUplink1 = int(root.find('bwUplink1').text)
|
|
|
|
bwUplink2 = int(root.find('bwUplink2').text)
|
2023-03-30 11:41:50 +00:00
|
|
|
tta = float(root.find('tta').text)
|
2023-03-30 11:24:30 +00:00
|
|
|
|
|
|
|
"""Store BW"""
|
|
|
|
bw.append(bwUplinkProd)
|
|
|
|
|
|
|
|
"""Loop over all possible combinations of length of the parameters minus x, y params"""
|
2023-03-21 09:41:52 +00:00
|
|
|
for combination in combinations(self.parameters, len(self.parameters)-2):
|
2023-02-23 13:37:45 +00:00
|
|
|
# Get the indices and values of the parameters in the combination
|
2023-03-26 13:01:07 +00:00
|
|
|
|
2023-02-23 13:37:45 +00:00
|
|
|
indices = [self.parameters.index(element) for element in combination]
|
2023-03-30 11:24:30 +00:00
|
|
|
selectedValues = [run, blockSize, failureRate, numberNodes, netDegree, chi, vpn1, vpn2, class1ratio, bwUplinkProd, bwUplink1, bwUplink2]
|
2023-02-23 13:37:45 +00:00
|
|
|
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)]
|
2023-03-21 09:41:52 +00:00
|
|
|
key = tuple(keyComponents[:len(self.parameters)-2])
|
2023-03-30 11:24:30 +00:00
|
|
|
"""Get the names of the other parameters that are not included in the key"""
|
2023-03-07 13:36:13 +00:00
|
|
|
otherParams = [self.parameters[i] for i in range(len(self.parameters)) if i not in indices]
|
2023-03-30 11:24:30 +00:00
|
|
|
"""Append the values of the other parameters and the ttas to the lists for the key"""
|
2023-02-23 13:37:45 +00:00
|
|
|
otherIndices = [i for i in range(len(self.parameters)) if i not in indices]
|
|
|
|
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Initialize the dictionary for the key if it doesn't exist yet"""
|
2023-02-23 13:37:45 +00:00
|
|
|
if key not in data:
|
|
|
|
data[key] = {}
|
2023-03-30 11:24:30 +00:00
|
|
|
"""Initialize lists for the other parameters and the ttas with the key"""
|
2023-02-23 13:37:45 +00:00
|
|
|
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)
|
2023-02-22 15:45:39 +00:00
|
|
|
return data
|
2023-04-20 16:15:02 +00:00
|
|
|
|
2023-03-30 11:24:30 +00:00
|
|
|
def averageRuns(self, data, runs):
|
2023-04-21 09:45:17 +00:00
|
|
|
"""Get the average of all runs for each key"""
|
2023-03-22 23:17:19 +00:00
|
|
|
newData = {}
|
2023-04-20 19:53:25 +00:00
|
|
|
print("Getting the average of the runs...")
|
2023-03-22 23:17:19 +00:00
|
|
|
for key, value in data.items():
|
|
|
|
runExists = False
|
|
|
|
"""Check if the key contains 'run_' with a numerical value"""
|
|
|
|
for item in key:
|
2023-03-30 11:24:30 +00:00
|
|
|
if item.startswith('run_'):
|
2023-03-22 23:17:19 +00:00
|
|
|
runExists = True
|
|
|
|
break
|
|
|
|
if runExists:
|
2023-04-25 21:32:31 +00:00
|
|
|
ps = list(data[key].keys())
|
2023-03-22 23:17:19 +00:00
|
|
|
for item in key:
|
|
|
|
"""Create a new key with the other items in the tuple"""
|
|
|
|
if item.startswith('run_'):
|
|
|
|
newKey = tuple([x for x in key if x != item])
|
2023-03-30 11:24:30 +00:00
|
|
|
"""Average the similar key values"""
|
2023-04-25 21:32:31 +00:00
|
|
|
tta_sums = {}
|
2023-04-26 16:22:17 +00:00
|
|
|
nbRuns = {}
|
|
|
|
ttRuns = []
|
2023-04-25 21:32:31 +00:00
|
|
|
total = []
|
|
|
|
p0 = []
|
|
|
|
p1 = []
|
2023-04-26 16:22:17 +00:00
|
|
|
p2 = []
|
|
|
|
p3 = []
|
2023-03-30 11:24:30 +00:00
|
|
|
for i in range(runs):
|
|
|
|
key0 = (f'run_{i}',) + newKey
|
2023-04-25 21:32:31 +00:00
|
|
|
#Create a dictionary to store the sums of ttas for each unique pair of values in subkeys
|
|
|
|
for i in range(len(data[key0][ps[0]])):
|
|
|
|
keyPair = (data[key0][ps[0]][i], data[key0][ps[1]][i])
|
2023-04-26 16:22:17 +00:00
|
|
|
if data[key0]["ttas"][i] == -1:
|
|
|
|
data[key0]["ttas"][i] = self.maxTTA
|
2023-04-25 21:32:31 +00:00
|
|
|
try:
|
|
|
|
tta_sums[keyPair] += data[key0]['ttas'][i]
|
2023-04-26 16:22:17 +00:00
|
|
|
if data[key0]["ttas"][i] != self.maxTTA:
|
|
|
|
nbRuns[keyPair] += 1
|
2023-04-25 21:32:31 +00:00
|
|
|
except KeyError:
|
|
|
|
tta_sums[keyPair] = data[key0]['ttas'][i]
|
2023-04-26 16:22:17 +00:00
|
|
|
if data[key0]["ttas"][i] != self.maxTTA:
|
|
|
|
nbRuns[keyPair] = 1
|
|
|
|
else:
|
|
|
|
nbRuns[keyPair] = 0
|
2023-04-25 21:32:31 +00:00
|
|
|
for k, tta in tta_sums.items():
|
|
|
|
p0.append(k[0])
|
|
|
|
p1.append(k[1])
|
|
|
|
total.append(tta)
|
2023-04-26 16:22:17 +00:00
|
|
|
for k, run in nbRuns.items():
|
|
|
|
p2.append(k[0])
|
|
|
|
p3.append(k[1])
|
|
|
|
ttRuns.append(run)
|
2023-03-30 11:24:30 +00:00
|
|
|
for i in range(len(total)):
|
2023-04-26 16:22:17 +00:00
|
|
|
if(ttRuns[i] == 0): # All tta = -1
|
2023-04-23 14:55:31 +00:00
|
|
|
total[i] = self.maxTTA
|
2023-04-26 16:22:17 +00:00
|
|
|
elif ttRuns[i] < runs: # Some tta = -1
|
|
|
|
total[i] -= (runs-ttRuns[i]) * self.maxTTA
|
|
|
|
total[i] = total[i]/ttRuns[i]
|
|
|
|
else: # No tta = -1
|
|
|
|
total[i] = total[i]/ttRuns[i]
|
2023-03-22 23:17:19 +00:00
|
|
|
averages = {}
|
2023-04-25 21:32:31 +00:00
|
|
|
averages[ps[0]] = p0
|
|
|
|
averages[ps[1]] = p1
|
|
|
|
averages['ttas'] = total
|
2023-03-22 23:17:19 +00:00
|
|
|
newData[newKey] = averages
|
|
|
|
return newData
|
2023-02-22 15:45:39 +00:00
|
|
|
|
|
|
|
def similarKeys(self, data):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Get the keys for all data with the same x and y labels"""
|
2023-02-23 13:37:45 +00:00
|
|
|
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]
|
2023-02-22 15:45:39 +00:00
|
|
|
print("Getting filtered keys from data...")
|
|
|
|
return filteredKeys
|
|
|
|
|
2023-02-26 17:36:02 +00:00
|
|
|
def formatLabel(self, label):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Label formatting for the figures"""
|
2023-02-26 17:36:02 +00:00
|
|
|
result = ''.join([f" {char}" if char.isupper() else char for char in label])
|
|
|
|
return result.title()
|
2023-03-21 09:41:52 +00:00
|
|
|
|
2023-02-23 13:37:45 +00:00
|
|
|
def formatTitle(self, key):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Title formatting for the figures"""
|
2023-02-23 13:37:45 +00:00
|
|
|
name = ''.join([f" {char}" if char.isupper() else char for char in key.split('_')[0]])
|
|
|
|
number = key.split('_')[1]
|
|
|
|
return f"{name.title()}: {number} "
|
|
|
|
|
2023-02-22 15:45:39 +00:00
|
|
|
def plotHeatmaps(self):
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Plot and store the 2D heatmaps in subfolders"""
|
2023-03-30 11:24:30 +00:00
|
|
|
data= self.plottingData()
|
|
|
|
"""Average the runs if needed"""
|
2023-04-20 16:15:02 +00:00
|
|
|
if(len(self.config.runs) > 1):
|
|
|
|
data = self.averageRuns(data, len(self.config.runs))
|
2023-02-22 15:45:39 +00:00
|
|
|
filteredKeys = self.similarKeys(data)
|
2023-04-27 11:58:51 +00:00
|
|
|
vmin, vmax = 0, self.maxTTA+1000
|
2023-02-22 15:45:39 +00:00
|
|
|
print("Plotting heatmaps...")
|
2023-04-20 16:15:02 +00:00
|
|
|
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Create the directory if it doesn't exist already"""
|
2023-02-23 13:37:45 +00:00
|
|
|
heatmapsFolder = self.folderPath + '/heatmaps'
|
|
|
|
if not os.path.exists(heatmapsFolder):
|
|
|
|
os.makedirs(heatmapsFolder)
|
|
|
|
|
2023-03-22 23:17:19 +00:00
|
|
|
"""Plot"""
|
2023-02-23 13:37:45 +00:00
|
|
|
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]]))
|
2023-02-26 17:36:02 +00:00
|
|
|
if len(xlabels) < self.minimumDataPoints or len(ylabels) < self.minimumDataPoints:
|
|
|
|
continue
|
2023-07-13 09:30:07 +00:00
|
|
|
df = pd.DataFrame.from_dict(data[key]).pivot(columns=labels[0], index=labels[1], values='ttas')
|
2023-02-23 13:37:45 +00:00
|
|
|
fig, ax = plt.subplots(figsize=(10, 6))
|
2023-07-12 19:15:08 +00:00
|
|
|
sns.heatmap(df, cmap='hot_r', cbar_kws={'label': 'Time to block availability (ms)'}, linecolor='black', linewidths=0.3, annot=True, fmt=".2f", ax=ax) #vmin=vmin, vmax=vmax
|
2023-02-26 17:36:02 +00:00
|
|
|
plt.xlabel(self.formatLabel(labels[0]))
|
|
|
|
plt.ylabel(self.formatLabel(labels[1]))
|
2023-02-23 13:37:45 +00:00
|
|
|
filename = ""
|
|
|
|
title = ""
|
|
|
|
paramValueCnt = 0
|
|
|
|
for param in self.parameters:
|
2023-03-22 23:17:19 +00:00
|
|
|
if param != labels[0] and param != labels[1] and param != 'run':
|
2023-02-23 13:37:45 +00:00
|
|
|
filename += f"{key[paramValueCnt]}"
|
|
|
|
formattedTitle = self.formatTitle(key[paramValueCnt])
|
|
|
|
title += formattedTitle
|
2023-03-30 11:41:50 +00:00
|
|
|
if (paramValueCnt+1) % 5 == 0:
|
|
|
|
title += "\n"
|
2023-02-23 13:37:45 +00:00
|
|
|
paramValueCnt += 1
|
2023-04-27 11:58:51 +00:00
|
|
|
title = "Time to Block Availability (ms)"
|
2023-02-23 13:37:45 +00:00
|
|
|
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()
|
2023-04-20 16:15:02 +00:00
|
|
|
|
2023-03-30 11:24:30 +00:00
|
|
|
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)
|
2023-04-20 16:15:02 +00:00
|
|
|
plt.clf()
|
2023-04-21 09:45:17 +00:00
|
|
|
|
|
|
|
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
|
2023-04-21 15:14:55 +00:00
|
|
|
plt.show()
|