from apgl.predictors.ABCSMC import ABCSMC import logging import sys import numpy import multiprocessing assert False, "Must run with -O flag" FORMAT = "%(levelname)s:root:%(process)d:%(message)s" logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format=FORMAT) 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() epsilonArray = numpy.ones(10)*0.4 logging.debug("Total time of simulation is " + str(endDate-startDate)) posteriorSampleSize = 30 breakDist = 0.5 logging.debug("Posterior sample size " + str(posteriorSampleSize)) def createModel(t): """ The parameter t is the particle index. """ undirected = True graph = HIVGraph(M, undirected) alpha = 2
from exp.viroscopy.model.HIVEpidemicModel import HIVEpidemicModel from exp.viroscopy.model.HIVRates import HIVRates from exp.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) endDate += HIVModelUtils.toyTestPeriod numRepetitions = 1 undirected = True outputDir = PathDefaults.getOutputDir() + "viroscopy/toy/" theta, sigmaTheta = HIVModelUtils.toyTheta() graphList = [] for j in range(numRepetitions): graph = HIVGraph(M, undirected) logging.debug("Created graph: " + str(graph)) alpha = 2