mirror of
https://github.com/logos-storage/das-research.git
synced 2026-01-07 15:43:08 +00:00
120 lines
5.3 KiB
Python
120 lines
5.3 KiB
Python
import os
|
|
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
|
|
|
|
#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} "
|
|
|
|
results_folder = os.getcwd()
|
|
|
|
#Get all folders and store their time info and sort
|
|
directories = [d for d in os.listdir(results_folder) if os.path.isdir(os.path.join(results_folder, d))]
|
|
directories_ctime = [(d, os.path.getctime(os.path.join(results_folder, d))) for d in directories]
|
|
directories_ctime.sort(key=lambda x: x[1], reverse=True)
|
|
|
|
#Get the path of the latest created folder
|
|
latest_directory = directories_ctime[0][0]
|
|
folder_path = os.path.join(results_folder, latest_directory)
|
|
|
|
#Store data with a unique key for each params combination
|
|
data = {}
|
|
plotInfo = {}
|
|
|
|
parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree', 'chi']
|
|
|
|
#Loop over the xml files in the folder
|
|
for filename in os.listdir(folder_path):
|
|
#Loop over the xmls and store the data in variables
|
|
if filename.endswith('.xml'):
|
|
tree = ET.parse(os.path.join(folder_path, 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]
|
|
selected_values = [run, blockSize, failureRate, numberValidators, netDegree, chi]
|
|
values = [selected_values[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
|
|
other_params = [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
|
|
other_indices = [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][other_params[0]] = []
|
|
data[key][other_params[1]] = []
|
|
data[key]['ttas'] = []
|
|
|
|
if other_params[0] in data[key]:
|
|
data[key][other_params[0]].append(selected_values[other_indices[0]])
|
|
else:
|
|
data[key][other_params[0]] = [selected_values[other_indices[0]]]
|
|
if other_params[1] in data[key]:
|
|
data[key][other_params[1]].append(selected_values[other_indices[1]])
|
|
else:
|
|
data[key][other_params[1]] = [selected_values[other_indices[1]]]
|
|
data[key]['ttas'].append(tta)
|
|
|
|
|
|
#Get the keys for all data with the same x and y labels
|
|
filtered_keys = {}
|
|
for key1, value1 in data.items():
|
|
sub_keys1 = list(value1.keys())
|
|
filtered_keys[(sub_keys1[0], sub_keys1[1])] = [key1]
|
|
for key2, value2 in data.items():
|
|
sub_keys2 = list(value2.keys())
|
|
if key1 != key2 and sub_keys1[0] == sub_keys2[0] and sub_keys1[1] == sub_keys2[1]:
|
|
try:
|
|
filtered_keys[(sub_keys1[0], sub_keys1[1])].append(key2)
|
|
except KeyError:
|
|
filtered_keys[(sub_keys1[0], sub_keys1[1])] = [key2]
|
|
|
|
#Store the 2D heatmaps in a folder
|
|
heatmaps_folder = 'heatmaps'
|
|
if not os.path.exists(heatmaps_folder):
|
|
os.makedirs(heatmaps_folder)
|
|
|
|
for labels, keys in filtered_keys.items():
|
|
for key in keys:
|
|
hist, xedges, yedges = np.histogram2d(data[key][labels[0]], data[key][labels[1]], bins=(3, 3), weights=data[key]['ttas'])
|
|
hist = hist.T
|
|
xlabels = [f'{val:.2f}' for val in xedges[::2]] + [f'{xedges[-1]:.2f}']
|
|
ylabels = [f'{val:.2f}' for val in yedges[::2]] + [f'{yedges[-1]:.2f}']
|
|
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")
|
|
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
|
|
plt.title(title)
|
|
filename = filename + ".png"
|
|
target_folder = os.path.join(heatmaps_folder, f"{labels[0]}Vs{labels[1]}")
|
|
if not os.path.exists(target_folder):
|
|
os.makedirs(target_folder)
|
|
plt.savefig(os.path.join(target_folder, filename))
|
|
plt.clf() |