def saveStats(args):
i, theta, startDate, endDate, recordStep = args
resultsFileName = outputDir + "SimStats" + str(i) + ".pkl"
try:
with open(resultsFileName) as f: pass
except IOError as e:
featureInds= numpy.ones(targetGraph.vlist.getNumFeatures(), numpy.bool)
featureInds[HIVVertices.dobIndex] = False
featureInds[HIVVertices.infectionTimeIndex] = False
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, 1.0, matcher, float(endDate))
times, infectedIndices, removedIndices, graph = HIVModelUtils.simulate(thetaArray[i], startDate, endDate, recordStep, M, graphMetrics)
times, vertexArray, removedGraphStats = HIVModelUtils.generateStatistics(graph, startDate, endDate, recordStep)
stats = times, vertexArray, removedGraphStats, graphMetrics.dists, graphMetrics.graphDists, graphMetrics.labelDists
Util.savePickle(stats, resultsFileName)
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)
times, vertexArray, removedGraphStats = HIVModelUtils.generateStatistics(graph, startDate, endDate, recordStep)
plt.figure(0)
plt.plot(times, vertexArray[:, 0])
plt.xlabel("Time")
plt.ylabel("Removed")
plt.figure(1)
plt.plot(times, vertexArray[:, 4])
plt.xlabel("Time")
plt.ylabel("Bi Detect")
plt.figure(2)
plt.plot(times, vertexArray[:, 5])
plt.xlabel("Time")
plt.ylabel("Rand Detect")
thetaArray = loadThetaArray(N, resultsDir, t)[0]
logging.debug(thetaArray)
paramList = []
for i in range(thetaArray.shape[0]):
paramList.append((i, thetaArray[i, :], startDate, endDate, recordStep))
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
stats = HIVModelUtils.generateStatistics(targetGraph, startDate, endDate, recordStep)
resultsFileName = outputDir + "IdealStats.pkl"
Util.savePickle(stats, resultsFileName)
else:
j = 0
resultsDir = PathDefaults.getOutputDir() + "viroscopy/real/theta" + str(j) + "/"
outputDir = resultsDir + "stats/"
endDate = endDates[j]
for i in range(maxT):
thetaArray, distArray = loadThetaArray(N, resultsDir, i)
if thetaArray.shape[0] == N:
t = i