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())
def testSimulate(self):
#We want to see if we can get the same simulation twice
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize, pertScale = HIVModelUtils.toyABCParams()
startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams(test=True)
breakSize = (targetGraph.subgraph(targetGraph.removedIndsAt(endDate)).size - targetGraph.subgraph(targetGraph.removedIndsAt(startDate)).size) * breakScale
theta, sigmaTheta, pertTheta = HIVModelUtils.toyTheta()
model = HIVModelUtils.createModel(theta, targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg)
model.setParams(theta)
times, infectedIndices, removedIndices, graph, compTimes, graphMetrics = HIVModelUtils.simulate(model)
numEdges = graph.getNumEdges()
lastRemovedIndices = removedIndices[-1]
#Simulate again
model = HIVModelUtils.createModel(theta, targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg)
model.setParams(theta)
times, infectedIndices, removedIndices, graph, compTimes, graphMetrics = HIVModelUtils.simulate(model)
numEdges2 = graph.getNumEdges()
lastRemovedIndices2 = removedIndices[-1]
self.assertEquals(numEdges, numEdges2)
self.assertEquals(lastRemovedIndices, lastRemovedIndices2)
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]
def loadParams(ind):
if processReal:
resultsDir = PathDefaults.getOutputDir() + "viroscopy/real/theta" + str(ind) + "/"
outputDir = resultsDir + "stats/"
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize, pertScale = HIVModelUtils.realABCParams(True)
startDate, endDate, recordStep, M, targetGraph, numInds = HIVModelUtils.realSimulationParams(test=True, ind=ind)
realTheta, sigmaTheta, pertTheta = HIVModelUtils.estimatedRealTheta(ind)
numInds=2
prefix = "Real"
else:
resultsDir = PathDefaults.getOutputDir() + "viroscopy/toy/theta/"
outputDir = resultsDir + "stats/"
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize, pertScale = HIVModelUtils.toyABCParams()
startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams(test=True)
realTheta, sigmaTheta, pertTheta = HIVModelUtils.toyTheta()
prefix = "Toy"
numInds = 1
breakSize = (targetGraph.subgraph(targetGraph.removedIndsAt(endDate)).size - targetGraph.subgraph(targetGraph.removedIndsAt(startDate)).size) * breakScale
return N, resultsDir, outputDir, recordStep, startDate, endDate, prefix, targetGraph, breakSize, numEpsilons, M, matchAlpha, matchAlg, numInds
from wallhack.viroscopy.model.HIVEpidemicModel import HIVEpidemicModel
from wallhack.viroscopy.model.HIVRates import HIVRates
from wallhack.viroscopy.model.HIVModelUtils import HIVModelUtils
"""
This is the epidemic model for the HIV spread in cuba. We repeat the simulation a number
of times and average the results. The purpose is to test the ABC model selection
by using a known value of theta.
"""
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
numpy.seterr(all="raise")
numpy.random.seed(24)
numpy.set_printoptions(suppress=True, precision=4, linewidth=100)
startDate, endDate, recordStep, M = HIVModelUtils.toySimulationParams(False, test=True)
numRepetitions = 10
undirected = True
outputDir = PathDefaults.getOutputDir() + "viroscopy/toy/"
theta, sigmaTheta, purtTheta = HIVModelUtils.toyTheta()
graphList = []
numInfected = numpy.zeros(numRepetitions)
numRemoved = numpy.zeros(numRepetitions)
for j in range(numRepetitions):
graph = HIVGraph(M, undirected)
logging.debug("Created graph: " + str(graph))
alpha = 2
from wallhack.viroscopy.model.HIVGraphMetrics2 import HIVGraphMetrics2 import matplotlib.pyplot as plt """ This is the epidemic model for the HIV spread in cuba. We want to see how different graphs can get under the same params but different seeds. """ assert False, "Must run with -O flag" logging.basicConfig(stream=sys.stdout, level=logging.DEBUG) numpy.seterr(all='raise') numpy.random.seed(24) numpy.set_printoptions(suppress=True, precision=4, linewidth=100) startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams() meanTheta, sigmaTheta = HIVModelUtils.toyTheta() #In this case, we'll extend the end date endDate *= 2 epsilon = 5.0 reps = 10 graphDists = [] removedArray = [] biArray = [] maleArray = [] femaleArray = [] for i in range(reps):
