mirror of
https://github.com/logos-storage/das-research.git
synced 2026-01-02 13:13:09 +00:00
Plot performance on different deque sizes
This commit is contained in:
parent
a7abfc124d
commit
57a3e807f8
@ -9,6 +9,7 @@ from DAS.tools import *
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from DAS.results import *
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from DAS.observer import *
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from DAS.validator import *
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from time import time
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class Simulator:
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"""This class implements the main DAS simulator."""
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@ -239,7 +240,9 @@ class Simulator:
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progressVector = []
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trafficStatsVector = []
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steps = 0
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# stepsLapses = []
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while(True):
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# tic = time()
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missingVector.append(missingSamples)
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oldMissingSamples = missingSamples
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self.logger.debug("PHASE SEND %d" % steps, extra=self.format)
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@ -264,10 +267,12 @@ class Simulator:
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for i in range(0,self.shape.numberNodes):
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self.validators[i].updateStats()
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trafficStatsVector.append(trafficStats)
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# toc = time()
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missingSamples, sampleProgress, nodeProgress, validatorAllProgress, validatorProgress = self.glob.getProgress(self.validators)
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self.logger.info("step %d, arrived %0.02f %%, ready %0.02f %%, validatedall %0.02f %%, , validated %0.02f %%"
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% (steps, sampleProgress*100, nodeProgress*100, validatorAllProgress*100, validatorProgress*100), extra=self.format)
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# stepsLapses.append(toc - tic)
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cnS = "samples received"
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cnN = "nodes ready"
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@ -306,6 +311,8 @@ class Simulator:
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missingVector.append(missingSamples)
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break
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steps += 1
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# print(f"(send: {self.shape.sendDqSize}, receive: {self.shape.receivedDqSize}) => {stepsLapses}")
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progress = pd.DataFrame(progressVector)
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if self.config.saveRCdist:
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371
dqPerformancePlot.py
Normal file
371
dqPerformancePlot.py
Normal file
@ -0,0 +1,371 @@
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import matplotlib.pyplot as plt
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import os
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def plotData(conf):
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plt.clf()
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plt.grid(True)
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props = dict(boxstyle="round", facecolor="wheat", alpha=0.5)
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plt.text(
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0.05,
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0.05,
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conf["textBox"],
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fontsize=10,
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verticalalignment="bottom",
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transform=plt.gca().transAxes,
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bbox=props,
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)
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plt.plot(conf["data"])
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plt.title(conf["title"])
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plt.ylabel(conf["ylabel"])
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plt.xlabel(conf["xlabel"])
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plt.xticks(fontsize=10)
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plt.yticks(fontsize=10)
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plt.savefig(conf["path"], bbox_inches="tight")
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plot_dir = "plotts/"
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os.makedirs(plot_dir, exist_ok=True)
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# 5k Nodes
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sizes = [
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(39, 395, 103.05640840530396),
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(32, 395, 103.86710143089294),
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(25, 315, 104.80244779586792),
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(18, 115, 142.61494040489197),
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(10, 31, 171.9263310432434),
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(7, 10, 191.59916806221008),
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]
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stepsLapses = [
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[
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0.6611301898956299,
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0.78688645362854,
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1.5642898082733154,
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5.431450366973877,
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13.975221633911133,
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14.78571629524231,
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14.83137059211731,
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14.895769596099854,
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14.69313931465149,
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13.231345176696777,
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4.99576997756958,
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0.702993631362915,
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0.650822639465332,
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0.6674363613128662,
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],
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[
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0.663672685623169,
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0.7919363975524902,
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1.5719895362854004,
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5.482329845428467,
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14.163940191268921,
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14.958719730377197,
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14.957429647445679,
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14.9972825050354,
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14.719813108444214,
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13.26242971420288,
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5.092689514160156,
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0.7198760509490967,
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0.6541843414306641,
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0.6386010646820068,
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],
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[
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0.6593191623687744,
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0.7860581874847412,
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1.5643928050994873,
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5.462092399597168,
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14.010809421539307,
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14.780933380126953,
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14.842840433120728,
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14.740232229232788,
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14.375006914138794,
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10.070922613143921,
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4.714495897293091,
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4.901551246643066,
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2.7569775581359863,
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],
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[
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0.6627669334411621,
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0.787919282913208,
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1.5623910427093506,
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5.312994956970215,
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20.968046188354492,
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21.576714515686035,
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21.61891222000122,
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21.66746997833252,
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21.8339524269104,
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18.25313925743103,
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4.994597673416138,
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0.7638595104217529,
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0.7524452209472656,
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0.6783268451690674,
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],
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[
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0.6688904762268066,
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0.7927229404449463,
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1.5365099906921387,
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8.011052370071411,
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24.87508773803711,
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25.503795862197876,
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25.52624750137329,
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25.243642568588257,
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22.462859630584717,
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15.084798574447632,
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5.83056640625,
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7.130087852478027,
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6.6575610637664795,
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1.4069156646728516,
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],
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[
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0.656153678894043,
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0.7790679931640625,
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1.944002389907837,
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9.286311388015747,
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28.338233470916748,
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28.87402057647705,
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29.03240132331848,
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28.941983222961426,
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28.813721656799316,
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25.514888048171997,
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8.469764709472656,
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],
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]
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# 10k Nodes
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sizes = [
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(50, 400, 213.62911701202393),
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(39, 395, 214.84202361106873),
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(32, 395, 213.54416799545288),
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(25, 315, 217.63313937187195),
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(18, 115, 283.82231521606445),
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(10, 31, 343.50494503974915),
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(7, 10, 394.94820404052734),
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]
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stepsLapses = [
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[
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1.3518695831298828,
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1.4894051551818848,
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2.389191150665283,
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6.95463490486145,
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24.005772352218628,
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30.02708649635315,
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30.45380449295044,
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30.695934772491455,
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30.31646728515625,
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29.054046869277954,
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17.703431129455566,
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2.720566511154175,
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2.1709277629852295,
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1.8627982139587402,
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],
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[
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1.3505363464355469,
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1.5087687969207764,
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2.369961738586426,
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6.896838426589966,
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23.798224210739136,
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30.069722414016724,
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30.176551342010498,
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30.49890446662903,
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30.29648232460022,
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28.97600030899048,
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17.854567766189575,
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2.9478790760040283,
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2.149484634399414,
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1.9988489151000977,
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1.4238512516021729,
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],
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[
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1.3641128540039062,
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1.505706548690796,
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2.412487506866455,
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6.97865104675293,
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24.048677921295166,
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29.876856565475464,
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30.403212785720825,
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30.607238054275513,
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30.24274516105652,
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28.874801635742188,
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17.851038694381714,
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2.970747947692871,
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2.152620792388916,
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1.8637866973876953,
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],
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[
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1.3612470626831055,
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1.506117820739746,
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2.3963406085968018,
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6.987675666809082,
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24.04241633415222,
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29.937008142471313,
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30.254473447799683,
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30.574475288391113,
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30.222501516342163,
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23.64164447784424,
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10.550750732421875,
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10.036490678787231,
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10.066076755523682,
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3.668154001235962,
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],
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[
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1.348376750946045,
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1.485114336013794,
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2.3588476181030273,
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6.822790622711182,
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31.541237592697144,
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42.21662974357605,
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43.31953692436218,
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43.17806601524353,
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43.284963846206665,
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40.89579677581787,
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20.15466809272766,
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2.0757288932800293,
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1.4337825775146484,
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1.3437645435333252,
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],
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[
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1.3447542190551758,
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1.4888508319854736,
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2.3689799308776855,
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8.266894340515137,
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40.54838562011719,
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50.60444140434265,
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51.81586265563965,
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51.774033308029175,
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51.12255573272705,
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40.330037355422974,
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16.446475982666016,
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6.193348169326782,
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8.187717914581299,
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8.416587591171265,
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1.9950587749481201,
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],
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[
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1.3593223094940186,
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1.518049955368042,
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2.4925811290740967,
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10.969608068466187,
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47.84677600860596,
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57.691601276397705,
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60.105135917663574,
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59.38239240646362,
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58.89372801780701,
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56.152278423309326,
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33.62856864929199,
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2.8102831840515137,
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],
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]
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# 1k Nodes
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sizes = [
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(39, 395, 19.518831253051758),
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(32, 395, 19.62859344482422),
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(25, 315, 20.106651306152344),
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(18, 115, 27.49130392074585),
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(10, 31, 33.48099613189697),
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(7, 10, 37.46962857246399),
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]
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stepsLapses = [
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[
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0.15041708946228027,
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0.2558310031890869,
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0.834219217300415,
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2.6229143142700195,
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2.849874258041382,
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2.8211777210235596,
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2.8509232997894287,
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2.8175060749053955,
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2.620945453643799,
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1.1062071323394775,
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0.20065641403198242,
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0.1831526756286621,
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],
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[
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0.15043163299560547,
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0.2549173831939697,
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0.8331425189971924,
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2.64731502532959,
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2.850823163986206,
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2.8487398624420166,
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2.8656344413757324,
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2.8288016319274902,
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2.630406379699707,
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1.1487407684326172,
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0.19384264945983887,
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0.171234130859375,
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],
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[
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0.15032672882080078,
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0.2573871612548828,
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0.8333590030670166,
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2.5946173667907715,
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2.809241771697998,
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2.805994749069214,
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2.911816120147705,
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2.610478401184082,
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2.333618402481079,
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1.8721530437469482,
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0.5945620536804199,
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0.1285545825958252,
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],
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[
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0.14538335800170898,
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0.24220609664916992,
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0.813441276550293,
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3.965632200241089,
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4.187340497970581,
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4.174125909805298,
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4.213524580001831,
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4.212984561920166,
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3.867766857147217,
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1.1342151165008545,
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0.17552900314331055,
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0.1555778980255127,
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],
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[
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0.145188570022583,
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0.23859691619873047,
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1.1786553859710693,
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4.681736469268799,
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4.848631381988525,
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4.949578285217285,
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4.779291391372681,
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4.404498338699341,
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3.221503734588623,
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1.7988455295562744,
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1.9808762073516846,
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1.0439932346343994,
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],
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[
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0.14494824409484863,
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0.24969959259033203,
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1.4229578971862793,
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5.471708059310913,
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5.621778964996338,
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5.7769739627838135,
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5.7460150718688965,
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5.6701459884643555,
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5.270337104797363,
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1.9179344177246094,
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],
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]
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for size, lapses in zip(sizes, stepsLapses):
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fname = f"{size[0]}_{size[1]}.png"
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conf = {}
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conf["textBox"] = (
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f"Max Send Deque Size: {size[0]}\nMax Received Deque Size: {size[1]}\nTotal Time Taken: {size[2]:.2f}s"
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)
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conf["title"] = "Step Duration"
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conf["type"] = "plot"
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conf["legLoc"] = 1
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conf["desLoc"] = 1
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conf["colors"] = ["m-"]
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conf["labels"] = ["Step Duration"]
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conf["xlabel"] = "Step"
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conf["ylabel"] = "Time Taken (sec)"
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conf["data"] = lapses
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conf["path"] = plot_dir + fname
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plotData(conf)
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