Python HIVGraph.HIVGraph类代码示例

    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)

    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 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 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 testContructor(self):
        numVertices = 10
        graph = HIVGraph(numVertices)

        
        self.assertEquals(numVertices, graph.getNumVertices())
        self.assertEquals(8, graph.getVertexList().getNumFeatures())
        self.assertTrue(graph.isUndirected() == True)

    def testGetSusceptibleSet(self):
        numVertices = 10
        graph = HIVGraph(numVertices)

        self.assertTrue(graph.getSusceptibleSet() == set(range(numVertices)))

        for i in range(9):
            graph.getVertexList().setInfected(i, 0.0)

        self.assertTrue(graph.getSusceptibleSet() == set([9]))

    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 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 testSummary(self): 
        numVertices = 10
        graph = HIVGraph(numVertices)

        graph.getVertexList().setInfected(1, 0.0)
        graph.getVertexList().setInfected(2, 2.0)
        graph.getVertexList().setInfected(7, 3.0)
        
        times = numpy.array([0, 1.0, 3.0, 4.0])
        
        metrics = HIVGraphMetrics(times)
        summary = metrics.summary(graph)
        
        summaryReal = numpy.array([[1,0], [1,0], [3, 0], [3,0]])
        nptst.assert_array_equal(summaryReal, summary)

    def __init__(self):
        #Total number of people in population
        self.M = 1000
        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
            

        p = 0.01
        generator = ErdosRenyiGenerator(p)
        self.graph = generator.generate(self.graph)
        
        perm1 = numpy.random.permutation(self.M)
        perm2 = numpy.random.permutation(self.M)        
        
        sizes = [200, 300, 500, 1000]
        self.summary1 = [] 
        self.summary2 = [] 

        for size in sizes: 
            self.summary1.append(self.graph.subgraph(perm1[0:size]))
            self.summary2.append(self.graph.subgraph(perm2[0:int(size/10)]))
        
        print(self.graph)

 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)

class HIVGraphMetricsProfile():
    def __init__(self):
        #Total number of people in population
        self.M = 1000
        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
            

        p = 0.01
        generator = ErdosRenyiGenerator(p)
        self.graph = generator.generate(self.graph)
        
        perm1 = numpy.random.permutation(self.M)
        perm2 = numpy.random.permutation(self.M)        
        
        sizes = [200, 300, 500, 1000]
        self.summary1 = [] 
        self.summary2 = [] 

        for size in sizes: 
            self.summary1.append(self.graph.subgraph(perm1[0:size]))
            self.summary2.append(self.graph.subgraph(perm2[0:int(size/10)]))
        
        print(self.graph)

    def profileDistance(self): 
        times = numpy.arange(len(self.summary1))
        #metrics = HIVGraphMetrics2(times, GraphMatch("RANK"))
        metrics = HIVGraphMetrics2(times, GraphMatch("U"))
        
        #Can try RANK and Umeyama algorithm - Umeyama is faster      
        self.summary2 = self.summary2[0:2]
        
        ProfileUtils.profile('metrics.distance(self.summary1, self.summary2)', globals(), locals())

    def testInfectedIndsAt(self): 
        numVertices = 10
        graph = HIVGraph(numVertices)

        self.assertTrue(graph.getRemovedSet() == set([]))

        graph.getVertexList().setInfected(1, 0.0)
        graph.getVertexList().setInfected(2, 2.0)
        graph.getVertexList().setInfected(7, 3.0)
        
        
        inds = graph.infectedIndsAt(10)
        nptst.assert_array_equal(inds, numpy.array([1, 2, 7]))
        
        graph.getVertexList().setInfected(5, 12.0)
        nptst.assert_array_equal(inds, numpy.array([1, 2, 7]))

 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)