das-research/DAS/visualizer.py

#!/bin/python3
import os, sys
import time
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from itertools import combinations
from mplfinance.original_flavor import candlestick_ohlc
import os


class Visualizer:

    def __init__(self, execID, config):
        self.execID = execID
        self.config = config
        self.folderPath = "results/"+self.execID
        self.parameters = ['run', 'blockSize', 'failureRate', 'numberNodes', 'netDegree', 'chi', 'vpn1', 'vpn2', 'class1ratio', 'bwUplinkProd', 'bwUplink1', 'bwUplink2']
        self.minimumDataPoints = 2
        self.maxTTA = 11000

    def plottingData(self):
        """Store data with a unique key for each params combination"""
        data = {}
        bw = []
        print("Getting data from the folder...")
        """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)
                numberNodes = int(root.find('numberNodes').text)
                class1ratio = float(root.find('class1ratio').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)
                tta = float(root.find('tta').text)

                """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):
                    # Get the indices and values of the parameters in the combination

                    indices = [self.parameters.index(element) for element in combination]
                    selectedValues = [run, blockSize, failureRate, numberNodes, netDegree, chi, vpn1, vpn2, class1ratio, bwUplinkProd, bwUplink1, bwUplink2]
                    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])
                    """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]
                    """Append the values of the other 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 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 averageRuns(self, data, runs):
        """Get the average of all runs for each key"""
        newData = {}
        print("Getting the average of the runs...")
        for key, value in data.items():
            runExists = False
            """Check if the key contains 'run_' with a numerical value"""
            for item in key:
                if item.startswith('run_'):
                    runExists = True
                    break
            if runExists:
                ps = list(data[key].keys())
                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])
                        """Average the similar key values"""
                        tta_sums = {}
                        nbRuns = {}
                        ttRuns = []
                        total = []
                        p0 = []
                        p1 = []
                        p2 = []
                        p3 = []
                        for i in range(runs):
                            key0 = (f'run_{i}',) + newKey
                            #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
                                try:
                                    tta_sums[keyPair] += data[key0]['ttas'][i]
                                    if data[key0]["ttas"][i] != self.maxTTA:
                                        nbRuns[keyPair] += 1
                                except KeyError:
                                    tta_sums[keyPair] = data[key0]['ttas'][i]
                                    if data[key0]["ttas"][i] != self.maxTTA:
                                        nbRuns[keyPair] = 1
                                    else:
                                        nbRuns[keyPair] = 0
                        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)
                        for i in range(len(total)):
                            if(ttRuns[i] == 0):     # All tta = -1
                                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]
                        averages = {}
                        averages[ps[0]] = p0
                        averages[ps[1]] = p1
                        averages['ttas'] = total
                        newData[newKey] = averages
        return newData

    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())
            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

    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} "

    def plotHeatmaps(self):
        """Plot and store the 2D heatmaps in subfolders"""
        data= self.plottingData()
        """Average the runs if needed"""
        if(len(self.config.runs) > 1):
            data = self.averageRuns(data, len(self.config.runs))
        filteredKeys = self.similarKeys(data)
        vmin, vmax = 0, self.maxTTA+1000
        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]]))
                if len(xlabels) < self.minimumDataPoints or len(ylabels) < self.minimumDataPoints:
                    continue
                df = pd.DataFrame.from_dict(data[key]).pivot(columns=labels[0], index=labels[1], values='ttas')
                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
                plt.xlabel(self.formatLabel(labels[0]))
                plt.ylabel(self.formatLabel(labels[1]))
                filename = ""
                title = ""
                paramValueCnt = 0
                for param in self.parameters:
                    if param != labels[0] and param != labels[1] and param != 'run':
                        filename += f"{key[paramValueCnt]}"
                        formattedTitle = self.formatTitle(key[paramValueCnt])
                        title += formattedTitle
                        if (paramValueCnt+1) % 5 == 0:
                            title += "\n"
                        paramValueCnt += 1
                title = "Time to Block Availability (ms)"
                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 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 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
        plt.show()