def profileSimulateGraphMatch(self):
N, matchAlpha, breakDist, purtScale = HIVModelUtils.toyABCParams()
startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams()
theta, stdTheta = HIVModelUtils.toyTheta()
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]
#QCV is fastest and most accurate
#PATH is slowests but quite accurate
#RANK is very fast by less accurate than PATH
#U is fastest but least accurate
matcher = GraphMatch("QCV", alpha=matchAlpha, featureInds=featureInds, useWeightM=False)
matcher.lambdaM = 50
matcher.init = "rand"
graphMetrics = HIVGraphMetrics2(targetGraph, breakDist, matcher, float(endDate))
def run():
times, infectedIndices, removedIndices, graph = HIVModelUtils.simulate(theta, startDate, endDate, recordStep, M, graphMetrics)
print("Mean distance " + str(graphMetrics.meanDistance()))
ProfileUtils.profile('run()', globals(), locals())
