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# Copyright (C) 2016 EDF
# All Rights Reserved
# This code is published under the GNU Lesser General Public License (GNU LGPL)
import StOptGrids
import StOptReg
import StOptGlobal
import StOptGeners
import imp
import numpy as np
def DynamicProgrammingByRegressionDist(p_grid, p_optimize, p_regressor, p_funcFinalValue, p_pointStock, p_initialRegime, p_fileToDump, p_bOneFile) :
try:
imp.find_module('mpi4py')
found = True
except:
print("Not parallel module found ")
found = False
if found :
# from the optimizer get back the simulation
simulator = p_optimize.getSimulator()
fin = StOptGlobal.FinalStepDPDist(p_grid, p_optimize.getNbRegime(),p_optimize.getDimensionToSplit())
# final values
valuesNext = fin.set(p_funcFinalValue, np.asarray(simulator.getParticles()))
from mpi4py import MPI
world = MPI.COMM_WORLD
# dump
toDump = p_fileToDump
# test if one file generated
if p_bOneFile is False:
toDump += "_" + str(world.rank)
ar = StOptGeners.BinaryFileArchive(toDump, "w")
# name for object in archive
nameAr = "Continuation"
nsteps =simulator.getNbStep()
# iterate on time steps
for iStep in range(nsteps) :
asset = simulator.stepBackwardAndGetParticles()
# conditional espectation operator
if iStep == (simulator.getNbStep() - 1):
p_regressor.updateSimulations(True, asset)
else:
p_regressor.updateSimulations(False, asset)
# transition object
transStep = StOptGlobal.TransitionStepRegressionDPDist(p_grid, p_grid, p_optimize)
valuesAndControl = transStep.oneStep(valuesNext, p_regressor)
transStep.dumpContinuationValues(ar, nameAr, nsteps - 1 - iStep, valuesNext, valuesAndControl[1], p_regressor, p_bOneFile)
valuesNext = valuesAndControl[0]
# reconstruct a small grid for interpolation
return StOptGlobal.reconstructProc0Mpi(p_pointStock, p_grid, valuesNext[p_initialRegime],p_optimize.getDimensionToSplit()).mean()
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