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 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 saveStats(args):
i, theta = args
resultsFileName = outputDir + "SimStats" + str(i) + ".pkl"
lock = FileLock(resultsFileName)
if not lock.fileExists() and not lock.isLocked():
lock.lock()
model = HIVModelUtils.createModel(targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg, theta=thetaArray[i])
times, infectedIndices, removedIndices, graph, compTimes, graphMetrics = HIVModelUtils.simulate(model)
times = numpy.arange(startDate, endDate+1, recordStep)
vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees = HIVModelUtils.generateStatistics(graph, times)
stats = times, vertexArray, infectedIndices, removedGraphStats, finalRemovedDegrees, graphMetrics.objectives, compTimes
Util.savePickle(stats, resultsFileName)
lock.unlock()
else:
logging.debug("Results already computed: " + str(resultsFileName))
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 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
def profileSimulate(self):
startDate, endDates, numRecordSteps, M, targetGraph = HIVModelUtils.realSimulationParams()
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
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+1000)
model.setRecordStep(10)
model.setParams(meanTheta)
logging.debug("MeanTheta=" + str(meanTheta))
ProfileUtils.profile('model.simulate()', globals(), locals())
def testSimulate2(self):
alpha = 2
zeroVal = 0.9
startDate = 0.0
endDate = 200.0
M = 1000
undirected = True
theta, sigmaTheta, pertTheta = HIVModelUtils.toyTheta()
numpy.random.seed(21)
graph = HIVGraph(M, undirected)
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, endDate, startDate, metrics=None)
#model.setRecordStep(recordStep)
model.setParams(theta)
times, infectedIndices, removedIndices, graph = model.simulate(True)
numVertices = graph.size
numEdges = graph.getNumEdges()
#Try again
numpy.random.seed(21)
graph = HIVGraph(M, undirected)
p = Util.powerLawProbs(alpha, zeroVal)
hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices())
rates = HIVRates(graph, hiddenDegSeq)
model = HIVEpidemicModel(graph, rates, endDate, startDate, metrics=None)
model.setParams(theta)
times, infectedIndices, removedIndices, graph = model.simulate(True)
numVertices2 = graph.size
numEdges2 = graph.getNumEdges()
self.assertEquals(numVertices2, numVertices)
self.assertEquals(numEdges2, numEdges)
def createModel(t):
"""
The parameter t is the particle index.
"""
return HIVModelUtils.createModel(targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg)
numProcesses = multiprocessing.cpu_count()
if len(sys.argv) > 2:
i = int(sys.argv[2])
else:
i = 0
FORMAT = "%(levelname)s:root:%(process)d:%(message)s"
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format=FORMAT)
logging.debug("Number of processes: " + str(numProcesses))
logging.debug("Epidemic period index " + str(i))
numpy.set_printoptions(suppress=True, precision=4, linewidth=150)
numpy.seterr(invalid='raise')
resultsDir = PathDefaults.getOutputDir() + "viroscopy/real/"
startDate, endDate, recordStep, M, targetGraph, numInds = HIVModelUtils.realSimulationParams(ind=i)
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize, pertScale = HIVModelUtils.realABCParams(i)
logging.debug("Posterior sample size " + str(N))
logging.debug("Matching algorithm " + str(matchAlg))
logging.debug("="*10 + "Starting new simulation batch with index " + str(i) + "="*10)
logging.debug("Total time of simulation is " + str(endDate-startDate))
breakSize = (targetGraph.subgraph(targetGraph.removedIndsAt(endDate)).size - targetGraph.subgraph(targetGraph.removedIndsAt(startDate)).size) * breakScale
logging.debug("Largest acceptable graph is " + str(breakSize))
def createModel(t):
"""
The parameter t is the particle index.
"""
thetaArray = loadThetaArray(N, resultsDir, t)[0]
logging.debug(thetaArray)
paramList = []
for i in range(thetaArray.shape[0]):
paramList.append((i, thetaArray[i, :]))
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
times = numpy.arange(startDate, endDate+1, recordStep)
vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees = HIVModelUtils.generateStatistics(targetGraph, times)
stats = vertexArray, infectedIndices, removedIndices, contactGraphStats, removedGraphStats, finalRemovedDegrees
resultsFileName = outputDir + "IdealStats.pkl"
Util.savePickle(stats, resultsFileName)
else:
import matplotlib
matplotlib.use("GTK3Agg")
import matplotlib.pyplot as plt
plotStyles = ['k-', 'kx-', 'k+-', 'k.-', 'k*-']
N, resultsDir, outputDir, recordStep, startDate, endDate, prefix, targetGraph, breakSize, numEpsilons, M, matchAlpha, matchAlg, numInds = loadParams(0)
inds = range(numInds)
numRecordSteps = int((endDate-startDate)/recordStep)+1
def run():
times, infectedIndices, removedIndices, graph = HIVModelUtils.simulate(theta, startDate, endDate, recordStep, M, graphMetrics)
print("Mean distance " + str(graphMetrics.meanDistance()))
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
matplotlib.use("GTK3Agg")
import matplotlib.pyplot as plt
"""
This is the epidemic model for the HIV spread in cuba. Let's try to get an
exponential infection.
"""
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.realSimulationParams()
M = 100
endDate = startDate + 1000
meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta()
meanTheta = numpy.array([ 1, 0.1, 0.0, 0.00, 0.5, 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())
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):
assert False, "Must run with -O flag"
if len(sys.argv) > 1:
numProcesses = int(sys.argv[1])
else:
numProcesses = multiprocessing.cpu_count()
FORMAT = "%(levelname)s:root:%(process)d:%(message)s"
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format=FORMAT)
logging.debug("Number of processes: " + str(numProcesses))
numpy.set_printoptions(suppress=True, precision=4, linewidth=150)
numpy.seterr(invalid='raise')
resultsDir = PathDefaults.getOutputDir() + "viroscopy/real/"
startDates, endDates, numRecordSteps, M, targetGraph = HIVModelUtils.realSimulationParams()
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize = HIVModelUtils.realABCParams()
logging.debug("Posterior sample size " + str(N))
alpha = 2
zeroVal = 0.9
for i, endDate in enumerate(endDates):
startDate = startDates[i]
logging.debug("="*10 + "Starting new simulation batch with index " + str(i) + "="*10)
logging.debug("Total time of simulation is " + str(endDate-startDate))
breakSize = targetGraph.subgraph(targetGraph.removedIndsAt(endDate)).size * breakScale
logging.debug("Largest acceptable graph is " + str(breakSize))
assert False, "Must run with -O flag"
if len(sys.argv) > 1:
numProcesses = int(sys.argv[1])
else:
numProcesses = multiprocessing.cpu_count()
FORMAT = "%(levelname)s:root:%(process)d:%(message)s"
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format=FORMAT)
logging.debug("Number of processes: " + str(numProcesses))
numpy.set_printoptions(suppress=True, precision=4, linewidth=150)
numpy.seterr(invalid='raise')
resultsDir = PathDefaults.getOutputDir() + "viroscopy/toy/"
startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.toySimulationParams()
N, matchAlpha, breakScale, numEpsilons, epsilon, minEpsilon, matchAlg, abcMaxRuns, batchSize, pertScale = HIVModelUtils.toyABCParams()
logging.debug("Total time of simulation is " + str(endDate-startDate))
logging.debug("Posterior sample size " + str(N))
epsilonArray = numpy.ones(numEpsilons)*epsilon
breakSize = (targetGraph.subgraph(targetGraph.removedIndsAt(endDate)).size - targetGraph.subgraph(targetGraph.removedIndsAt(startDate)).size) * breakScale
logging.debug("Largest acceptable graph is " + str(breakSize))
def createModel(t):
"""
The parameter t is the particle index.
"""
return HIVModelUtils.createModel(targetGraph, startDate, endDate, recordStep, M, matchAlpha, breakSize, matchAlg)
