mirror of
https://github.com/codex-storage/das-research.git
synced 2025-02-23 08:18:14 +00:00
Fixed Plots
This commit is contained in:
HajarZaiz
parent
2b7302de64
commit
a6896a60dd
122
results/plots.py
122
results/plots.py
@ -6,34 +6,37 @@ import numpy as np
|
||||
import seaborn as sns
|
||||
from itertools import combinations
|
||||
|
||||
parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree', 'chi']
|
||||
|
||||
#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()
|
||||
def getLatestDirectory():
|
||||
resultsFolder = 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 all folders and store their time info and sort
|
||||
directories = [d for d in os.listdir(resultsFolder) if os.path.isdir(os.path.join(resultsFolder, d))]
|
||||
directoriesTime = [(d, os.path.getctime(os.path.join(resultsFolder, d))) for d in directories]
|
||||
directoriesTime.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)
|
||||
#Get the path of the latest created folder
|
||||
latestDirectory = directoriesTime[0][0]
|
||||
folderPath = os.path.join(resultsFolder, latestDirectory)
|
||||
return folderPath
|
||||
|
||||
#Store data with a unique key for each params combination
|
||||
data = {}
|
||||
plotInfo = {}
|
||||
def plottingData(folderPath):
|
||||
#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 xml files in the folder
|
||||
for filename in os.listdir(folderPath):
|
||||
#Loop over the xmls and store the data in variables
|
||||
if filename.endswith('.xml'):
|
||||
tree = ET.parse(os.path.join(folder_path, filename))
|
||||
tree = ET.parse(os.path.join(folderPath, filename))
|
||||
root = tree.getroot()
|
||||
run = int(root.find('run').text)
|
||||
blockSize = int(root.find('blockSize').text)
|
||||
@ -47,60 +50,64 @@ for filename in os.listdir(folder_path):
|
||||
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]
|
||||
selectedValues = [run, blockSize, failureRate, numberValidators, netDegree, chi]
|
||||
values = [selectedValues[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]
|
||||
otherParams = [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]
|
||||
otherIndices = [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][otherParams[0]] = []
|
||||
data[key][otherParams[1]] = []
|
||||
data[key]['ttas'] = []
|
||||
|
||||
if other_params[0] in data[key]:
|
||||
data[key][other_params[0]].append(selected_values[other_indices[0]])
|
||||
if otherParams[0] in data[key]:
|
||||
data[key][otherParams[0]].append(selectedValues[otherIndices[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]])
|
||||
data[key][otherParams[0]] = [selectedValues[otherIndices[0]]]
|
||||
if otherParams[1] in data[key]:
|
||||
data[key][otherParams[1]].append(selectedValues[otherIndices[1]])
|
||||
else:
|
||||
data[key][other_params[1]] = [selected_values[other_indices[1]]]
|
||||
data[key][otherParams[1]] = [selectedValues[otherIndices[1]]]
|
||||
data[key]['ttas'].append(tta)
|
||||
return data
|
||||
|
||||
|
||||
#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]
|
||||
def similarKeys(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():
|
||||
sub_keys2 = list(value2.keys())
|
||||
if key1 != key2 and sub_keys1[0] == sub_keys2[0] and sub_keys1[1] == sub_keys2[1]:
|
||||
subKeys2 = list(value2.keys())
|
||||
if key1 != key2 and subKeys1[0] == subKeys2[0] and subKeys1[1] == subKeys2[1]:
|
||||
try:
|
||||
filtered_keys[(sub_keys1[0], sub_keys1[1])].append(key2)
|
||||
filteredKeys[(subKeys1[0], subKeys1[1])].append(key2)
|
||||
except KeyError:
|
||||
filtered_keys[(sub_keys1[0], sub_keys1[1])] = [key2]
|
||||
filteredKeys[(subKeys1[0], subKeys1[1])] = [key2]
|
||||
return filteredKeys
|
||||
|
||||
#Store the 2D heatmaps in a folder
|
||||
heatmaps_folder = 'heatmaps'
|
||||
if not os.path.exists(heatmaps_folder):
|
||||
os.makedirs(heatmaps_folder)
|
||||
def plotHeatmaps(filteredKeys, data):
|
||||
#Store the 2D heatmaps in a folder
|
||||
heatmapsFolder = 'heatmaps'
|
||||
if not os.path.exists(heatmapsFolder):
|
||||
os.makedirs(heatmapsFolder)
|
||||
|
||||
for labels, keys in filtered_keys.items():
|
||||
for labels, keys in filteredKeys.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'])
|
||||
xlabels = np.sort(np.unique(data[key][labels[0]]))
|
||||
ylabels = np.sort(np.unique(data[key][labels[1]]))
|
||||
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
|
||||
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")
|
||||
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)
|
||||
plt.xlabel(labels[0])
|
||||
plt.ylabel(labels[1])
|
||||
filename = ""
|
||||
@ -111,10 +118,21 @@ for labels, keys in filtered_keys.items():
|
||||
filename += f"{key[paramValueCnt]}"
|
||||
title += formatTitle(key[paramValueCnt])
|
||||
paramValueCnt += 1
|
||||
plt.title(title)
|
||||
title_obj = plt.title(title)
|
||||
font_size = 16 * fig.get_size_inches()[0] / 10
|
||||
title_obj.set_fontsize(font_size)
|
||||
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))
|
||||
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 generateHeatmaps():
|
||||
folderPath = getLatestDirectory()
|
||||
data = plottingData(folderPath)
|
||||
filteredKeys = similarKeys(data)
|
||||
plotHeatmaps(filteredKeys, data)
|
||||
|
||||
generateHeatmaps()
|
||||
Loading…
x
Reference in New Issue
Block a user