Beispiel #1
0
def saveStats(args):    
    i, theta = args 
    
    resultsFileName = outputDir + "SimStats" + str(i) + ".pkl"
    lock = FileLock(resultsFileName)
    
    if not lock.fileExists() and not lock.isLocked():    
        lock.lock()
         
        model = HIVModelUtils.createModel(targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg, theta=thetaArray[i])
        times, infectedIndices, removedIndices, graph, compTimes, graphMetrics = HIVModelUtils.simulate(model)
        times = numpy.arange(startDate, endDate+1, recordStep)
        vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees = HIVModelUtils.generateStatistics(graph, times)
        stats = times, vertexArray, infectedIndices, removedGraphStats, finalRemovedDegrees, graphMetrics.objectives, compTimes
        
        Util.savePickle(stats, resultsFileName)
        lock.unlock()
    else: 
        logging.debug("Results already computed: " + str(resultsFileName))
Beispiel #2
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        thetaArray = loadThetaArray(N, resultsDir, t)[0]
        logging.debug(thetaArray)
        
        paramList = []
        
        for i in range(thetaArray.shape[0]): 
            paramList.append((i, thetaArray[i, :]))
    
        pool = multiprocessing.Pool(multiprocessing.cpu_count())               
        resultIterator = pool.map(saveStats, paramList)  
        #resultIterator = map(saveStats, paramList)  
        pool.terminate()
    
        #Now save the statistics on the target graph 
        times = numpy.arange(startDate, endDate+1, recordStep)
        vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees = HIVModelUtils.generateStatistics(targetGraph, times)
        stats = vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees
        resultsFileName = outputDir + "IdealStats.pkl"
        Util.savePickle(stats, resultsFileName)
else:
    import matplotlib 
    matplotlib.use("GTK3Agg")
    import matplotlib.pyplot as plt     
    
    plotStyles = ['k-', 'kx-', 'k+-', 'k.-', 'k*-']
    
    N, resultsDir, outputDir, recordStep, startDate, endDate, prefix, targetGraph, breakSize, numEpsilons, M, matchAlpha, matchAlg, numInds = loadParams(0) 

    inds = range(numInds)
    numRecordSteps = int((endDate-startDate)/recordStep)+1
    
Beispiel #3
0
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())

rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates)
model.setT0(startDate)
model.setT(endDate)
model.setRecordStep(recordStep)
model.setParams(meanTheta)

logging.debug("MeanTheta=" + str(meanTheta))

times, infectedIndices, removedIndices, graph = model.simulate(True)

statistics = GraphStatistics()
vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats = HIVModelUtils.generateStatistics(graph, times)

numInfectedIndices = [len(x) for x in infectedIndices]

plt.figure(0)
plt.plot(times, numInfectedIndices)
plt.xlabel("Time")
plt.ylabel("Infected")

plt.figure(1)
plt.plot(times, contactGraphStats[:, statistics.numVerticesIndex])
plt.xlabel("Time")
plt.ylabel("Contact graph size")

plt.show()
Beispiel #4
0
def runModel(meanTheta):
    startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams()
    endDate = 1000.0
    recordStep = 50
    undirected = True

    logging.debug("MeanTheta=" + str(meanTheta))
    numReps = 10
    numInfectedIndices = []
    numRemovedIndices = []
    numRemovedEdges = []
    numContactEdges = []

    statistics = GraphStatistics()
    statsTimes = numpy.arange(0, endDate, recordStep)

    for i in range(numReps):
        graph = HIVGraph(M, undirected)
        logging.info("Created graph at index " + str(i) + ": " + str(graph))

        alpha = 2
        zeroVal = 0.9
        p = Util.powerLawProbs(alpha, zeroVal)
        hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())

        rates = HIVRates(graph, hiddenDegSeq)
        model = HIVEpidemicModel(graph, rates)
        model.setT0(startDate)
        model.setT(endDate)
        model.setRecordStep(recordStep)
        model.setParams(meanTheta)
        times, infectedIndices, removedIndices, graph = model.simulate(True)

        vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats = HIVModelUtils.generateStatistics(
            graph, statsTimes
        )

        numInfectedIndices.append([len(x) for x in infectedIndices])
        numRemovedIndices.append([len(x) for x in removedIndices])

        numContactEdges.append(contactGraphStats[:, statistics.numVerticesIndex])
        numRemovedEdges.append(removedGraphStats[:, statistics.numVerticesIndex])

    numInfectedIndices = numpy.array(numInfectedIndices)
    numInfectedIndices = numpy.mean(numInfectedIndices, 0)

    numRemovedIndices = numpy.array(numRemovedIndices)
    numRemovedIndices = numpy.mean(numRemovedIndices, 0)

    numContactEdges = numpy.array(numContactEdges)
    numContactEdges = numpy.mean(numContactEdges, 0)

    numRemovedEdges = numpy.array(numRemovedEdges)
    numRemovedEdges = numpy.mean(numRemovedEdges, 0)

    return statsTimes, numInfectedIndices, numRemovedIndices, numContactEdges, numRemovedEdges, vertexArray[:, 6]
Beispiel #5
0
    featureInds[HIVVertices.hiddenDegreeIndex] = False 
    featureInds[HIVVertices.stateIndex] = False
    featureInds = numpy.arange(featureInds.shape[0])[featureInds]
    matcher = GraphMatch("PATH", alpha=0.5, featureInds=featureInds, useWeightM=False)
    graphMetrics = HIVGraphMetrics2(targetGraph, epsilon, matcher, float(endDate))
    graphMetrics.breakDist = 1.0 

    rates = HIVRates(graph, hiddenDegSeq)
    model = HIVEpidemicModel(graph, rates, T=float(endDate), T0=float(startDate), metrics=graphMetrics)
    model.setRecordStep(recordStep)
    model.setParams(meanTheta)
    
    numpy.random.seed(i)
    times, infectedIndices, removedIndices, graph = model.simulate(True)
    print(times)
    times2, vertexArray, removedGraphStats = HIVModelUtils.generateStatistics(graph, startDate, endDate, recordStep)
    
    print(graphMetrics.dists)
    graphDists.append(graphMetrics.dists)
    removedArray.append(vertexArray[:, 0])
    maleArray.append(vertexArray[:, 1])
    femaleArray.append(vertexArray[:, 2])
    biArray.append(vertexArray[:, 4])

graphDists = numpy.array(graphDists)
removedArray = numpy.array(removedArray)
maleArray = numpy.array(maleArray)
femaleArray = numpy.array(femaleArray)
biArray = numpy.array(biArray)

graphDistsMean = graphDists.mean(0)