def testPickle(self):
numVertices = 10
graph = HIVGraph(numVertices)
graph[0, 0] = 1
graph[3, 5] = 0.1
output = pickle.dumps(graph)
newGraph = pickle.loads(output)
graph[2, 2] = 1
self.assertEquals(newGraph[0, 0], 1)
self.assertEquals(newGraph[3, 5], 0.1)
self.assertEquals(newGraph[2, 2], 0.0)
self.assertEquals(newGraph.getNumEdges(), 2)
self.assertEquals(newGraph.getNumVertices(), numVertices)
self.assertEquals(newGraph.isUndirected(), True)
self.assertEquals(graph[0, 0], 1)
self.assertEquals(graph[3, 5], 0.1)
self.assertEquals(graph[2, 2], 1)
self.assertEquals(graph.getNumEdges(), 3)
self.assertEquals(graph.getNumVertices(), numVertices)
self.assertEquals(graph.isUndirected(), True)
for i in range(numVertices):
nptst.assert_array_equal(graph.getVertex(i), newGraph.getVertex(i))
def profileSimulate(self):
startDate, endDate, recordStep, printStep, M, targetGraph = HIVModelUtils.realSimulationParams()
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
meanTheta = numpy.array([337, 1.4319, 0.211, 0.0048, 0.0032, 0.5229, 0.042, 0.0281, 0.0076, 0.0293])
undirected = True
graph = HIVGraph(M, undirected)
logging.info("Created graph: " + 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(startDate+100)
model.setRecordStep(recordStep)
model.setPrintStep(printStep)
model.setParams(meanTheta)
logging.debug("MeanTheta=" + str(meanTheta))
ProfileUtils.profile('model.simulate()', globals(), locals())
def testInfectionProbability(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.1
graph.getVertex(0)[HIVVertices.stateIndex] = HIVVertices.infected
graph.getVertex(1)[HIVVertices.stateIndex] = HIVVertices.removed
graph.getVertex(2)[HIVVertices.stateIndex] = HIVVertices.infected
for vertexInd1 in range(numVertices):
for vertexInd2 in range(numVertices):
vertex1 = graph.getVertex(vertexInd1)
vertex2 = graph.getVertex(vertexInd2)
if vertex1[HIVVertices.stateIndex]!=HIVVertices.infected or vertex2[HIVVertices.stateIndex]!=HIVVertices.susceptible:
self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), 0.0)
elif vertex1[HIVVertices.genderIndex] == HIVVertices.female and vertex2[HIVVertices.genderIndex] == HIVVertices.male:
self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb)
elif vertex1[HIVVertices.genderIndex] == HIVVertices.male and vertex2[HIVVertices.genderIndex] == HIVVertices.female:
self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb)
elif vertex1[HIVVertices.genderIndex] == HIVVertices.male and vertex2[HIVVertices.orientationIndex]==HIVVertices.bi:
self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb)
else:
self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), 0.0)
def testRemoveEvent(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.1
V = graph.getVertexList().getVertices()
femaleInds = V[:, HIVVertices.genderIndex]==HIVVertices.female
maleInds = V[:, HIVVertices.genderIndex]==HIVVertices.male
biMaleInds = numpy.logical_and(maleInds, V[:, HIVVertices.orientationIndex]==HIVVertices.bi)
self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p)
graph.getVertexList().setInfected(4, t)
graph.getVertexList().setInfected(7, t)
graph.getVertexList().setInfected(8, t)
rates.removeEvent(4, HIVVertices.randomDetect, t)
rates.removeEvent(7, HIVVertices.randomDetect, t)
removedInds= list(graph.getRemovedSet())
hiddenDegSeq[removedInds] = 0
#Check the new degree sequences are correct
self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p)
def createModel(t):
"""
The parameter t is the particle index.
"""
undirected = True
graph = HIVGraph(M, undirected)
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
featureInds= numpy.ones(graph.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, breakDist, matcher, endDate)
graphMetrics.breakDist = 0.0
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, T=float(endDate), T0=float(startDate), metrics=graphMetrics)
model.setRecordStep(recordStep)
return model
def testContactRates(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
t = 0.2
contactList = range(numVertices)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
contactRateInds, contactRates = rates.contactRates([0, 5, 7], contactList, t)
self.assertEquals(contactRates.shape[0], 3)
#Now we have that 0 had contact with another
rates.contactEvent(0, 3, 0.2)
rates.contactEvent(1, 9, 0.1)
infectedInds = numpy.arange(numVertices)
contactRateInds, contactRates = rates.contactRates(infectedInds, contactList, t)
#Note that in some cases an infected has no contacted as the persons do not match
for i in range(infectedInds.shape[0]):
if contactRateInds[i] != -1:
if graph.getVertex(infectedInds[i])[HIVVertices.genderIndex]==graph.getVertex(contactRateInds[i])[HIVVertices.genderIndex]:
self.assertEquals(contactRates[i], rates.heteroContactRate)
elif graph.getVertex(infectedInds[i])[HIVVertices.genderIndex]!=graph.getVertex(contactRateInds[1])[HIVVertices.genderIndex] and graph.getVertex(infectedInds[i])[HIVVertices.orientationIndex]==HIVVertices.bi and graph.getVertex(contactRateInds[i])[HIVVertices.orientationIndex]==HIVVertices.bi:
self.assertEquals(contactRates[i],rates.biContactRate)
def testContructor(self):
numVertices = 10
graph = HIVGraph(numVertices)
self.assertEquals(numVertices, graph.getNumVertices())
self.assertEquals(8, graph.getVertexList().getNumFeatures())
self.assertTrue(graph.isUndirected() == True)
def testRandomDetectionRates(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
t = 0.1
graph.getVertexList().setInfected(0, t)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
infectedList = [0, 2, 9]
rdRates = rates.randomDetectionRates(infectedList, float(graph.size - len(graph.getRemovedSet())))
nptst.assert_array_almost_equal(rdRates, numpy.ones(len(infectedList))*rates.randDetectRate*len(infectedList)/float(graph.size - len(graph.getRemovedSet())))
def simulate(theta, startDate, endDate, recordStep, M, graphMetrics=None):
undirected = True
graph = HIVGraph(M, undirected)
logging.debug("Created graph: " + 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, endDate, startDate, metrics=graphMetrics)
model.setRecordStep(recordStep)
model.setParams(theta)
logging.debug("Theta = " + str(theta))
return model.simulate(True)
def testContactEvent(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
#for i in range(numVertices):
# logging.debug(graph.getVertex(i))
t = 0.2
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
V = graph.getVertexList().getVertices()
femaleInds = V[:, HIVVertices.genderIndex]==HIVVertices.female
maleInds = V[:, HIVVertices.genderIndex]==HIVVertices.male
biMaleInds = numpy.logical_and(maleInds, V[:, HIVVertices.orientationIndex]==HIVVertices.bi)
self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p)
self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p)
for i in range(numVertices):
self.assertEquals(rates.contactTimesArr[i], -1)
rates.contactEvent(0, 9, 0.1)
rates.contactEvent(0, 3, 0.2)
self.assertEquals(graph.getEdge(0, 3), 0.2)
self.assertEquals(graph.getEdge(0, 9), 0.1)
self.assertTrue((rates.contactTimesArr[0] == numpy.array([3])).all())
self.assertTrue((rates.contactTimesArr[9] == numpy.array([0])).all())
self.assertTrue((rates.contactTimesArr[3] == numpy.array([0])).all())
for i in range(numVertices):
self.assertTrue((rates.neighboursList[i] == graph.neighbours(i)).all())
#Check that the degree sequence is correct
degSequence = graph.outDegreeSequence()
r = rates.q-rates.p
self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p + degSequence[femaleInds].sum()*r)
self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p + degSequence[maleInds].sum()*r)
self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p + degSequence[biMaleInds].sum()*r)
def testContactRates3(self):
#Figure out why infection does not explode when we set infection probability
#to a high value and do not detect
undirected = True
numVertices = 20
graph = HIVGraph(numVertices, undirected)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.1
for i in range(10):
graph.getVertexList().setInfected(i, t)
t = 0.2
infectedList = graph.infectedIndsAt(t)
contactList = range(0, numVertices)
contactRateInds, contactRates = rates.contactRates(infectedList, contactList, t)
print(contactRateInds, contactRates)
def setUp(self):
numpy.seterr(invalid='raise')
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
numpy.set_printoptions(suppress=True, precision=4, linewidth=100)
numpy.random.seed(21)
M = 1000
undirected = True
graph = HIVGraph(M, undirected)
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
self.numParams = 6
self.graph = graph
self.meanTheta = numpy.array([100, 0.9, 0.05, 0.001, 0.1, 0.005])
self.hivAbcParams = HIVABCParameters(self.meanTheta, self.meanTheta/2)
def testUpperDetectionRates(self):
"""
See if the upper bound on detection rates is correct
"""
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.1
graph.getVertexList().setInfected(0, t)
graph.getVertexList().setInfected(1, t)
graph.getVertexList().setInfected(8, t)
t = 0.2
rates.removeEvent(8, HIVVertices.randomDetect, t)
rates.infectionProbability = 1.0
infectedList = graph.infectedIndsAt(t)
removedList = graph.removedIndsAt(t)
n = graph.size-removedList
self.assertEquals(rates.upperDetectionRates(infectedList, n), rates.randomDetectionRates(infectedList, n, seed=21).sum())
t = 0.3
rates.contactEvent(0, 2, t)
graph.vlist.setInfected(2, t)
t = 0.4
rates.removeEvent(0, HIVVertices.randomDetect, t)
infectedList = graph.infectedIndsAt(t)
removedSet = graph.removedIndsAt(t)
removedSet = set(removedSet.tolist())
nptst.assert_array_almost_equal(rates.contactTracingRates(infectedList, removedSet, t + rates.ctStartTime + 1), numpy.array([0, rates.ctRatePerPerson]))
upperDetectionRates = rates.ctRatePerPerson + rates.randomDetectionRates(infectedList, n, seed=21).sum()
self.assertEquals(rates.upperDetectionRates(infectedList, n), upperDetectionRates)
def findDerivative(args):
pertScale, startDate, endDate, recordStep, M, targetGraph, seed = args
numpy.random.seed(seed)
meanTheta, sigmaTheta = HIVModelUtils.toyTheta()
epsilon = 5.0
undirected = True
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
graph = HIVGraph(M, undirected)
featureInds= numpy.ones(graph.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)
abcParams = HIVABCParameters(meanTheta, sigmaTheta, pertScale)
newTheta = abcParams.perturbationKernel(meanTheta)
undirected = True
graph = HIVGraph(M, undirected)
graphMetrics = HIVGraphMetrics2(targetGraph, epsilon, matcher, float(endDate))
graphMetrics.breakDist = 1.0
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, T=float(endDate), T0=float(startDate), metrics=graphMetrics)
model.setRecordStep(recordStep)
model.setParams(meanTheta)
times, infectedIndices, removedIndices, graph = model.simulate(True)
return abs(0.7 - graphMetrics.distance())/numpy.linalg.norm(newTheta-meanTheta)
def runModel(theta, endDate=100.0, M=1000):
numpy.random.seed(21)
undirected= True
recordStep = 10
printStep = 10
startDate = 0
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
graph = HIVGraph(M, undirected)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
logging.debug("MeanTheta=" + str(theta))
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, endDate, startDate)
model.setRecordStep(recordStep)
model.setPrintStep(printStep)
model.setParams(theta)
times, infectedIndices, removedIndices, graph = model.simulate(True)
return times, infectedIndices, removedIndices, graph, model
class HIVRatesProfile():
def __init__(self):
#Total number of people in population
self.M = 10000
numInitialInfected = 5
#The graph is one in which edges represent a contact
undirected = True
self.graph = HIVGraph(self.M, undirected)
for i in range(self.M):
vertex = self.graph.getVertex(i)
#Set the infection time of a number of individuals to 0
if i < numInitialInfected:
vertex[HIVVertices.stateIndex] = HIVVertices.infected
outputDirectory = PathDefaults.getOutputDir()
directory = outputDirectory + "test/"
self.profileFileName = directory + "profile.cprof"
def profileContactRate(self):
susceptibleList = list(range(1, self.graph.getNumVertices()))
t = 10
s = 3
gen = scipy.stats.zipf(s)
hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices())
rates = HIVRates(self.graph, hiddenDegSeq)
numContactEvents = 5000
for i in range(numContactEvents):
vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices())
vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices())
rates.contactEvent(vertexInd1, vertexInd2, 5)
print((self.graph.getNumEdges()))
infectedList = range(0, 100)
contactList = range(100, self.M)
t = 10
def runContactRates():
for i in range(100):
rates.contactRates(infectedList, contactList, t)
ProfileUtils.profile('runContactRates()', globals(), locals())
def profileInfectionProbability(self):
s = 3
gen = scipy.stats.zipf(s)
hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices())
rates = HIVRates(self.graph, hiddenDegSeq)
t = 5
#Getting vertices and checking parameters takes the most time
def runInfectionProbs():
for i in range(10000):
vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices())
vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices())
rates.infectionProbability(vertexInd1, vertexInd2, t)
ProfileUtils.profile('runInfectionProbs()', globals(), locals())
def profileContactTracingRate(self):
s = 3
gen = scipy.stats.zipf(s)
hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices())
rates = HIVRates(self.graph, hiddenDegSeq)
#Create a network of sexual contacts
numContactEvents = 10000
for i in range(numContactEvents):
vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices())
vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices())
rates.contactEvent(vertexInd1, vertexInd2, 5)
print((self.graph))
print((self.graph.degreeDistribution()))
#Choose some individuals as being infected and then detected
p = 0.3
q = 0.4
for i in range(self.graph.getNumVertices()):
if numpy.random.rand() < p and not self.graph.getVertex(i)[HIVVertices.stateIndex] == HIVVertices.infected:
self.graph.getVertexList().setInfected(i, 5.0)
if numpy.random.rand() < q:
self.graph.getVertexList().setDetected(i, 6.0, HIVVertices.randomDetect)
infectedSet = self.graph.getInfectedSet()
print((len(infectedSet)))
print((len(self.graph.getRemovedSet())))
removedSet = self.graph.getRemovedSet()
t = 200
def runContactTracingRate():
for j in range(2000):
rates.contactTracingRates(list(infectedSet), removedSet, t)
ProfileUtils.profile('runContactTracingRate()', globals(), locals())
def testContactTracingRate(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.1
graph.getVertexList().setInfected(0, t)
rates.contactEvent(0, 3, 0.2)
rates.contactEvent(0, 9, 0.1)
t = 0.3
graph.getVertexList().setInfected(3, t)
graph.getVertexList().setInfected(9, t)
t = 0.4
rates.removeEvent(0, HIVVertices.randomDetect, t)
removedSet = graph.getRemovedSet()
infectedList = [3, 9]
ctRates = rates.contactTracingRates(infectedList, removedSet, t)
self.assertTrue((ctRates==numpy.array([0.0, 0.0])).all())
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime)
self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all())
#Test contact tracing is within correct time period
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctEndTime-0.01)
self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all())
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctEndTime+1)
self.assertTrue((ctRates == numpy.array([0, 0])).all())
rates.contactEvent(3, 5, t)
graph.getVertexList().setInfected(5, t)
rates.removeEvent(5, HIVVertices.randomDetect, t)
removedSet = graph.getRemovedSet()
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime)
self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all())
rates.contactEvent(3, 6, t)
graph.getVertexList().setInfected(6, t)
infectedList = [3, 6, 9]
removedSet = graph.getRemovedSet()
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime)
self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, 0, rates.ctRatePerPerson])).all())
#Now make removedSet bigger than infectedList
graph.getVertexList().setInfected(4, t)
graph.getVertexList().setInfected(7, t)
graph.getVertexList().setInfected(8, t)
graph.getVertexList().setDetected(4, t, HIVVertices.randomDetect)
graph.getVertexList().setDetected(7, t, HIVVertices.randomDetect)
graph.getVertexList().setDetected(8, t, HIVVertices.randomDetect)
#Note: InfectedList is out of order
infectedList = list(graph.getInfectedSet())
sortInds = numpy.argsort(numpy.array(infectedList))
removedSet = graph.getRemovedSet()
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime)
ctRates2 = numpy.array([rates.ctRatePerPerson, 0, rates.ctRatePerPerson])
self.assertTrue((ctRates[sortInds] == ctRates2).all())
#Test the case where InfectedList is out of order and removedSet is small
graph.getVertexList().setInfected(4, t)
graph.getVertex(7)[HIVVertices.stateIndex] = HIVVertices.susceptible
graph.getVertex(8)[HIVVertices.stateIndex] = HIVVertices.susceptible
infectedList = list(graph.getInfectedSet())
sortInds = numpy.argsort(numpy.array(infectedList))
removedSet = graph.getRemovedSet()
ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime)
ctRates2 = numpy.array([rates.ctRatePerPerson, 0, 0, rates.ctRatePerPerson])
self.assertTrue((ctRates[sortInds] == ctRates2).all())
def testContactRates2(self):
undirected = True
numVertices = 10
graph = HIVGraph(numVertices, undirected)
maleVertex = graph.getVertex(0)
maleVertex[HIVVertices.genderIndex] = HIVVertices.male
femaleVertex = maleVertex.copy()
femaleVertex[HIVVertices.genderIndex] = HIVVertices.female
for i in range(5):
graph.setVertex(i, maleVertex)
graph.setVertex(i+5, femaleVertex)
V = graph.getVertexList().getVertices()
contactList = range(numVertices)
#Test that the parameters alpha and C do the right thing
hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
t = 0.2
logging.debug("Rates with no existing contacts")
contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, t)
#When there are no contacts the choice is easy and some random new contacts
#are chosen.
#Now test differences in choice between existing and new contact.
t = 0.3
for i in range(5):
rates.contactEvent(i, i+5, t)
rates.alpha = 1.0
logging.debug("Rates with default alpha=" + str(rates.alpha))
contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 0.4)
for i in range(5):
self.assertTrue(contactRates[i] == rates.contactRate)
self.assertTrue(contactRateInds[i] == i+5)
#Now try changing alpha
logging.debug("Rates with alpha=0.5")
rates.setAlpha(0.5)
contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 0.4)
#Observed probabilities change as expected
#Now increase time and observe probabilities
logging.debug("Rates with t=20")
contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 20)
#Test we don't pick from removed
graph.getVertexList().setInfected(0, t)
graph.getVertexList().setInfected(4, t)
graph.getVertexList().setInfected(7, t)
graph.getVertexList().setInfected(8, t)
#graph.getVertexList().setDetected(4, t, HIVVertices.randomDetect)
#graph.getVertexList().setDetected(7, t, HIVVertices.randomDetect)
rates.removeEvent(4, HIVVertices.randomDetect, t)
rates.removeEvent(7, HIVVertices.randomDetect, t)
infectedSet = graph.getInfectedSet()
susceptibleSet = graph.getSusceptibleSet()
removedSet = graph.getRemovedSet()
contactSet = infectedSet.union(susceptibleSet)
infectedList = list(infectedSet)
removedList = list(removedSet)
contactList = list(contactSet)
contactRateInds, contactRates = rates.contactRates(infectedList, contactList, 20)
#Contacts cannot be in removed set
self.assertTrue(numpy.intersect1d(contactRateInds, numpy.array(removedList)).shape[0]==0)
numpy.set_printoptions(suppress=True, precision=4, linewidth=100)
startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.realSimulationParams()
endDate = startDate + 10000
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
meanTheta = numpy.array([ 50, 0.5131, 0.3242, 0.1, 0.0001, 0.0, 325, 0.34, 0.001, 0.1, 0.1, 0.1])
outputDir = PathDefaults.getOutputDir() + "viroscopy/"
undirected = True
graph = HIVGraph(M, undirected)
logging.info("Created graph: " + 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)
logging.debug("MeanTheta=" + str(meanTheta))
times, infectedIndices, removedIndices, graph = model.simulate(True)
times, vertexArray, removedGraphStats = HIVModelUtils.generateStatistics(graph, startDate, endDate, recordStep)
plt.figure(0)
def testSimulate2(self):
startDate = 0.0
endDate = 100.0
M = 1000
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
undirected = True
graph = HIVGraph(M, undirected)
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
meanTheta[4] = 0.1
recordStep = 10
printStep = 10
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, endDate, startDate)
model.setRecordStep(recordStep)
model.setPrintStep(printStep)
model.setParams(meanTheta)
initialInfected = graph.getInfectedSet()
times, infectedIndices, removedIndices, graph = model.simulate(True)
#Now test the final graph
edges = graph.getAllEdges()
for i, j in edges:
if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and (graph.vlist.V[i, HIVVertices.orientationIndex] != HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex] != HIVVertices.bi):
self.fail()
finalInfected = graph.getInfectedSet()
finalRemoved = graph.getRemovedSet()
self.assertEquals(numpy.intersect1d(initialInfected, finalRemoved).shape[0], len(initialInfected))
#Test case where there is no contact
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, 0, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
self.assertEquals(len(graph.getInfectedSet()), 100)
self.assertEquals(len(graph.getRemovedSet()), 0)
self.assertEquals(graph.getNumEdges(), 0)
heteroContactRate = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
self.assertEquals(len(graph.getInfectedSet()), 100)
self.assertEquals(len(graph.getRemovedSet()), 0)
edges = graph.getAllEdges()
for i, j in edges:
self.assertNotEqual(graph.vlist.V[i, HIVVertices.genderIndex], graph.vlist.V[j, HIVVertices.genderIndex])
#Number of conacts = rate*people*time
infectedSet = graph.getInfectedSet()
numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum()
self.assertTrue(abs(numHetero*endDate*heteroContactRate- model.getNumContacts()) < 100)
heteroContactRate = 0.01
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
infectedSet = graph.getInfectedSet()
numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum()
self.assertAlmostEqual(numHetero*endDate*heteroContactRate/100, model.getNumContacts()/100.0, 0)
class HIVEpidemicModelTest(unittest.TestCase):
def setUp(self):
numpy.random.seed(21)
numpy.set_printoptions(suppress=True, precision=4)
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
M = 100
undirected = True
self.graph = HIVGraph(M, undirected)
s = 3
self.gen = scipy.stats.zipf(s)
hiddenDegSeq = self.gen.rvs(size=self.graph.getNumVertices())
rates = HIVRates(self.graph, hiddenDegSeq)
self.model = HIVEpidemicModel(self.graph, rates)
def testSimulate(self):
T = 1.0
self.graph.getVertexList().setInfected(0, 0.0)
self.model.setT(T)
times, infectedIndices, removedIndices, graph = self.model.simulate(verboseOut=True)
numInfects = 0
for i in range(graph.getNumVertices()):
if graph.getVertex(i)[HIVVertices.stateIndex] == HIVVertices==infected:
numInfects += 1
self.assertTrue(numInfects == 0 or times[len(times)-1] >= T)
#Test with a larger population as there seems to be an error when the
#number of infectives becomes zero.
M = 100
undirected = True
graph = HIVGraph(M, undirected)
graph.setRandomInfected(10, 0.95)
self.graph.removeAllEdges()
T = 21.0
hiddenDegSeq = self.gen.rvs(size=self.graph.getNumVertices())
rates = HIVRates(self.graph, hiddenDegSeq)
model = HIVEpidemicModel(self.graph, rates)
model.setRecordStep(10)
model.setT(T)
times, infectedIndices, removedIndices, graph = model.simulate(verboseOut=True)
self.assertTrue((times == numpy.array([0, 10, 20], numpy.int)).all())
self.assertEquals(len(infectedIndices), 3)
self.assertEquals(len(removedIndices), 3)
#TODO: Much better testing
def testSimulate2(self):
startDate = 0.0
endDate = 100.0
M = 1000
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
undirected = True
graph = HIVGraph(M, undirected)
alpha = 2
zeroVal = 0.9
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
meanTheta[4] = 0.1
recordStep = 10
printStep = 10
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, endDate, startDate)
model.setRecordStep(recordStep)
model.setPrintStep(printStep)
model.setParams(meanTheta)
initialInfected = graph.getInfectedSet()
times, infectedIndices, removedIndices, graph = model.simulate(True)
#Now test the final graph
edges = graph.getAllEdges()
for i, j in edges:
if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and (graph.vlist.V[i, HIVVertices.orientationIndex] != HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex] != HIVVertices.bi):
self.fail()
finalInfected = graph.getInfectedSet()
finalRemoved = graph.getRemovedSet()
self.assertEquals(numpy.intersect1d(initialInfected, finalRemoved).shape[0], len(initialInfected))
#Test case where there is no contact
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, 0, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
self.assertEquals(len(graph.getInfectedSet()), 100)
self.assertEquals(len(graph.getRemovedSet()), 0)
self.assertEquals(graph.getNumEdges(), 0)
heteroContactRate = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
self.assertEquals(len(graph.getInfectedSet()), 100)
self.assertEquals(len(graph.getRemovedSet()), 0)
edges = graph.getAllEdges()
for i, j in edges:
self.assertNotEqual(graph.vlist.V[i, HIVVertices.genderIndex], graph.vlist.V[j, HIVVertices.genderIndex])
#Number of conacts = rate*people*time
infectedSet = graph.getInfectedSet()
numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum()
self.assertTrue(abs(numHetero*endDate*heteroContactRate- model.getNumContacts()) < 100)
heteroContactRate = 0.01
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
infectedSet = graph.getInfectedSet()
numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum()
self.assertAlmostEqual(numHetero*endDate*heteroContactRate/100, model.getNumContacts()/100.0, 0)
def testSimulateBis(self):
#Play with bi rate
biContactRate = 0.1
endDate = 100.0
meanTheta = numpy.array([200, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta, endDate=endDate)
infectedSet = graph.getInfectedSet()
numBi = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.bi).sum()
susceptibleSet = graph.getSusceptibleSet()
self.assertTrue(abs(numBi*endDate*biContactRate- model.getNumContacts()) < 10)
numContacts = model.getNumContacts()
edges = graph.getAllEdges()
numMSM = 0
for i, j in edges:
self.assertTrue(graph.vlist.V[i, HIVVertices.orientationIndex]==HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex]==HIVVertices.bi)
if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and graph.vlist.V[i, HIVVertices.genderIndex]==HIVVertices.male:
numMSM += 1
biContactRate = 0.2
meanTheta = numpy.array([200, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
infectedSet = graph.getInfectedSet()
numBi = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.bi).sum()
numContacts2 = model.getNumContacts()
self.assertTrue(abs(numContacts*2-numContacts2) < 15)
#Try infection between men only
biContactRate = 0.2
manBiInfectProb = 1.0
meanTheta = numpy.array([300, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, manBiInfectProb], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
#print(numpy.logical_and(graph.vlist.V[:, HIVVertices.orientationIndex] == HIVVertices.bi, graph.vlist.V[:, HIVVertices.genderIndex] == HIVVertices.male).sum())
newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0]))
self.assertTrue((graph.vlist.V[newInfects, HIVVertices.orientationIndex] == HIVVertices.bi).all())
self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.male).all())
def testSimulateInfects(self):
#Test varying infection probabilities
heteroContactRate = 0.1
manWomanInfectProb = 1.0
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, manWomanInfectProb, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0]))
self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.female).all())
manWomanInfectProb = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, manWomanInfectProb, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
newInfects2 = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0]))
self.assertTrue((graph.vlist.V[newInfects2, HIVVertices.genderIndex] == HIVVertices.female).all())
self.assertTrue(newInfects.shape[0] > newInfects2.shape[0])
#Now only women infect
heteroContactRate = 0.1
womanManInfectProb = 1.0
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, womanManInfectProb, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0]))
self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.male).all())
womanManInfectProb = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, womanManInfectProb, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
newInfects2 = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0]))
self.assertTrue((graph.vlist.V[newInfects2, HIVVertices.genderIndex] == HIVVertices.male).all())
self.assertTrue(newInfects.shape[0] > newInfects2.shape[0])
def testSimulateDetects(self):
heteroContactRate = 0.05
endDate = 100
randDetectRate = 0
meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
detectedSet = graph.getRemovedSet()
self.assertEquals(len(detectedSet), 0)
heteroContactRate = 0.0
randDetectRate = 0.01
meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
detectedSet = graph.getRemovedSet()
self.assertTrue(len(detectedSet) < 100*randDetectRate*endDate)
randDetectRate = 0.005
meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
detectedSet2 = graph.getRemovedSet()
print(len(detectedSet), len(detectedSet2))
self.assertTrue(abs(len(detectedSet)*2 - len(detectedSet2))<15)
removedGraph = graph.subgraph(list(graph.getRemovedSet()))
edges = removedGraph.getAllEdges()
for edge in edges:
i, j = edge
self.assertEquals(removedGraph.vlist.V[i, HIVVertices.detectionTimeIndex]. HIVVertices.randomDetect)
self.assertEquals(removedGraph.vlist.V[j, HIVVertices.detectionTimeIndex]. HIVVertices.randomDetect)
#Test contact tracing
randDetectRate = 0
setCtRatePerPerson = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, setCtRatePerPerson, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta)
detectedSet = graph.getRemovedSet()
self.assertEquals(len(detectedSet), 0)
randDetectRate = 0.001
setCtRatePerPerson = 0.1
meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, setCtRatePerPerson, heteroContactRate, 0, 0, 0, 0], numpy.float)
times, infectedIndices, removedIndices, graph, model = runModel(meanTheta, endDate=500.0)
detectedSet = graph.getRemovedSet()
removedGraph = graph.subgraph(list(graph.getRemovedSet()))
edges = removedGraph.getAllEdges()
for i in removedGraph.getAllVertexIds():
if removedGraph.vlist.V[i, HIVVertices.detectionTypeIndex] == HIVVertices.contactTrace:
self.assertTrue(removedGraph.vlist.V[i, HIVVertices.detectionTimeIndex] >= 180)
@unittest.skip("")
def testFindStandardResults(self):
times = [3, 12, 22, 25, 40, 50]
infectedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]]
removedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]]
self.model.setT(51.0)
self.model.setRecordStep(10)
times, infectedIndices, removedIndices = self.model.findStandardResults(times, infectedIndices, removedIndices)
self.assertTrue((numpy.array(times)==numpy.arange(0, 60, 10)).all())
#Now try case where simulation is slightly longer than T and infections = 0
numpy.random.seed(21)
times = [3, 12, 22, 25, 40, 50]
infectedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]]
removedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]]
self.model.setT(51.0)
self.model.setRecordStep(10)
times, infectedIndices, removedIndices = self.model.findStandardResults(times, infectedIndices, removedIndices)
logging.debug(times)
