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border-bottom-left-radius: 50%; cursor: pointer; transition: all 0.5s ease-in-out;" +icon1.style.cssText = "opacity: 1; color: #160f25;" + +sections.forEach(section =>{ + section.addEventListener("click", function(){ + sections.forEach(s =>{ + s.style.cssText = "background: none; border-top-left-radius: 0%; border-bottom-left-radius: 0%;" + icons[sections.indexOf(s)].style.cssText = "color: #b9aecf; opacity: 0.7;" + paragraphs[sections.indexOf(s)].style.display = "none"; + }); + section.style.cssText = "background: #eee5fdea; border-top-left-radius: 50%; border-bottom-left-radius: 50%; cursor: pointer; transition: all 0.5s ease-in-out;" + icons[sections.indexOf(section)].style.cssText = "opacity: 1; color: #160f25;" + paragraphs[sections.indexOf(section)].style.display = "block"; + }); +}); \ No newline at end of file diff --git a/heatmaps/run=0_numberValidators=256_netDegree=6_chi=4.png b/heatmaps/run=0_numberValidators=256_netDegree=6_chi=4.png deleted file mode 100644 index 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matplotlib.pyplot as plt -import numpy as np - -#Yet to update with the execID format -folder_path = 'results/2023-01-26_10-41-29_912' - -#Store data with a unique key for each (run, numberValidators, netDegree, chi) combination -data = {} - -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) - numberValidators = int(root.find('numberValidators').text) - netDegree = int(root.find('netDegree').text) - chi = int(root.find('chi').text) - blockSize = int(root.find('blockSize').text) - failureRate = int(root.find('failureRate').text) - tta = int(root.find('tta').text) - - #Create a key for this combination of run, numberValidators, netDegree, and chi if it does not exist yet - key = (run, numberValidators, netDegree, chi) - if key not in data: - data[key] = {'blockSizes': [], 'failureRates': [], 'ttas': []} - - #Append the data used for the plot - data[key]['blockSizes'].append(blockSize) - data[key]['failureRates'].append(failureRate) - data[key]['ttas'].append(tta) - -#Store the 2D heatmaps in a folder -heatmaps_folder = 'heatmaps' -if not os.path.exists(heatmaps_folder): - os.makedirs(heatmaps_folder) - -#Plot the heatmaps -for key, values in data.items(): - hist, xedges, yedges = np.histogram2d(values['blockSizes'], values['failureRates'], bins=(10, 10), weights=values['ttas']) - plt.imshow(hist, extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]]) - plt.xlabel('blockSize') - plt.ylabel('failureRate') - plt.colorbar().set_label('tta') - title = f"run={key[0]}, numberValidators={key[1]}, netDegree={key[2]}, chi={key[3]}" - plt.title(title) - filename = f"run={key[0]}_numberValidators={key[1]}_netDegree={key[2]}_chi={key[3]}.png" - plt.savefig(os.path.join(heatmaps_folder, filename)) - plt.clf()