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 pandas as pd
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import seaborn as sns
from itertools import combinations
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from mplfinance.original_flavor import candlestick_ohlc
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import os
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class Visualizer:
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def __init__(self, execID, config):
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self.execID = execID
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self.config = config
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self.folderPath = "results/"+self.execID
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self.parameters = ['run', 'blockSize', 'failureRate', 'numberNodes', 'netDegree', 'chi', 'vpn1', 'vpn2', 'class1ratio', 'bwUplinkProd', 'bwUplink1', 'bwUplink2']
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self.minimumDataPoints = 2
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self.maxTTA = 11000
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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 = {}
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bw = []
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print("Getting data from the folder...")
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"""Loop over the xml files in the folder"""
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for filename in os.listdir(self.folderPath):
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"""Loop over the xmls and store the data in variables"""
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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('blockSizeR').text) # TODO: maybe we want both dimensions
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failureRate = int(root.find('failureRate').text)
numberNodes = int(root.find('numberNodes').text)
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class1ratio = float(root.find('class1ratio').text)
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netDegree = int(root.find('netDegree').text)
chi = int(root.find('chiR').text) # TODO: maybe we want both dimensions
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)
tta = float(root.find('tta').text)
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"""Store BW"""
bw.append(bwUplinkProd)
"""Loop over all possible combinations of length of the parameters minus x, y params"""
for combination in combinations(self.parameters, len(self.parameters)-2):
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# Get the indices and values of the parameters in the combination
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indices = [self.parameters.index(element) for element in combination]
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selectedValues = [run, blockSize, failureRate, numberNodes, netDegree, chi, vpn1, vpn2, class1ratio, 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[:len(self.parameters)-2])
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"""Get the names of the other 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 parameters and the ttas to the lists for the key"""
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otherIndices = [i for i in range(len(self.parameters)) if i not in indices]
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"""Initialize the dictionary for the key if it doesn't exist yet"""
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if key not in data:
data[key] = {}
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"""Initialize lists for the other parameters and the ttas with the key"""
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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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return data
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def averageRuns(self, data, runs):
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"""Get the average of all runs for each key"""
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newData = {}
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print("Getting the average of the runs...")
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for key, value in data.items():
runExists = False
"""Check if the key contains 'run_' with a numerical value"""
for item in key:
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if item.startswith('run_'):
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runExists = True
break
if runExists:
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ps = list(data[key].keys())
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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])
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"""Average the similar key values"""
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tta_sums = {}
nbRuns = {}
ttRuns = []
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total = []
p0 = []
p1 = []
p2 = []
p3 = []
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for i in range(runs):
key0 = (f'run_{i}',) + newKey
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#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])
if data[key0]["ttas"][i] == -1:
data[key0]["ttas"][i] = self.maxTTA
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try:
tta_sums[keyPair] += data[key0]['ttas'][i]
if data[key0]["ttas"][i] != self.maxTTA:
nbRuns[keyPair] += 1
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except KeyError:
tta_sums[keyPair] = data[key0]['ttas'][i]
if data[key0]["ttas"][i] != self.maxTTA:
nbRuns[keyPair] = 1
else:
nbRuns[keyPair] = 0
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for k, tta in tta_sums.items():
p0.append(k[0])
p1.append(k[1])
total.append(tta)
for k, run in nbRuns.items():
p2.append(k[0])
p3.append(k[1])
ttRuns.append(run)
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for i in range(len(total)):
if(ttRuns[i] == 0): # All tta = -1
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total[i] = self.maxTTA
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]
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averages = {}
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averages[ps[0]] = p0
averages[ps[1]] = p1
averages['ttas'] = total
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newData[newKey] = averages
return newData
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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):
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"""Label formatting for the figures"""
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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()
"""Average the runs if needed"""
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if(len(self.config.runs) > 1):
data = self.averageRuns(data, len(self.config.runs))
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filteredKeys = self.similarKeys(data)
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vmin, vmax = 0, self.maxTTA+1000
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print("Plotting heatmaps...")
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"""Create the directory if it doesn't exist already"""
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heatmapsFolder = self.folderPath + '/heatmaps'
if not os.path.exists(heatmapsFolder):
os.makedirs(heatmapsFolder)
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"""Plot"""
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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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df = pd.DataFrame.from_dict(data[key]).pivot(columns=labels[0], index=labels[1], values='ttas')
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fig, ax = plt.subplots(figsize=(10, 6))
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
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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:
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if param != labels[0] and param != labels[1] and param != 'run':
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filename += f"{key[paramValueCnt]}"
formattedTitle = self.formatTitle(key[paramValueCnt])
title += formattedTitle
if (paramValueCnt+1) % 5 == 0:
title += "\n"
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paramValueCnt += 1
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title = "Time to Block Availability (ms)"
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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()
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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)
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plt.clf()
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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
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plt.show()