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
