Inverse heatmap
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@ -16,12 +16,13 @@ class Visualizer:
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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 = 999
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self.maxTTA = 99
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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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@ -41,9 +42,8 @@ class Visualizer:
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bwUplink1 = int(root.find('bwUplink1').text)
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bwUplink2 = int(root.find('bwUplink2').text)
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tta = int(root.find('tta').text)
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# if tta == -1:
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# tta = self.maxTTA
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if tta == -1:
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tta = self.maxTTA
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"""Store BW"""
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bw.append(bwUplinkProd)
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@ -80,7 +80,6 @@ class Visualizer:
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else:
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data[key][otherParams[1]] = [selectedValues[otherIndices[1]]]
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data[key]['ttas'].append(tta)
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print("Getting data from the folder...")
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return data
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def averageRuns(self, data, runs):
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@ -116,7 +115,6 @@ class Visualizer:
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else:
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averages[subkey] = data[key][subkey]
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newData[newKey] = averages
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self.maxTTA = max(allTta) + 10
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return newData
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def similarKeys(self, data):
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@ -171,7 +169,7 @@ class Visualizer:
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hist, xedges, yedges = np.histogram2d(data[key][labels[0]], data[key][labels[1]], bins=(len(xlabels), len(ylabels)), weights=data[key]['ttas'], normed=False)
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hist = hist.T
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fig, ax = plt.subplots(figsize=(10, 6))
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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, vmin=vmin, vmax=vmax)
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sns.heatmap(hist, xticklabels=xlabels, yticklabels=ylabels, cmap='hot_r', cbar_kws={'label': 'Time to block availability'}, 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]))
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plt.ylabel(self.formatLabel(labels[1]))
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filename = ""
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