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#!/usr/bin/python3
# Copyright (C) 2016 EDF
# All Rights Reserved
# This code is published under the GNU Lesser General Public License (GNU LGPL)
import numpy as np
import unittest
import random
import StOptGrids
import StOptReg
import StOptGeners
# unit test for dumping binary archive of regressed value and Read then
######################################################################
class testBinaryArchiveStOpt(unittest.TestCase):
def testSimpleStorageAndLectureRecGrid(self):
# low value for the mesh
lowValues =np.array([1.,2.,3.],dtype=np.float64)
# size of the mesh
step = np.array([0.7,2.3,1.9],dtype=np.float64)
# number of step
nbStep = np.array([4,5,6], dtype=np.int32)
# degree of the polynomial in each direction
degree = np.array([2,1,3], dtype=np.int32)
# create the Legendre grid
grid = StOptGrids.RegularLegendreGrid(lowValues,step,nbStep,degree )
# simulate the perburbed values
################################
nbSimul =40000
np.random.seed(1000)
x = np.random.uniform(-1.,1.,size=(1,nbSimul));
# mesh
nbMesh = np.array([16],dtype=np.int32)
# Create the regressor
#####################
regressor = StOptReg.LocalLinearRegression(False,x,nbMesh)
# regressed values same values for each point of the grid
#########################################################
toReal = (2+x[0,:]+(1+x[0,:])*(1+x[0,:]))
# function to regress
toRegress = toReal + 4*np.random.normal(0.,1,nbSimul)
# create a matrix (number of stock points by number of simulations)
toRegressMult = np.zeros(shape=(len(toRegress),grid.getNbPoints()))
for i in range(toRegressMult.shape[1]):
toRegressMult[:,i] = toRegress
# into a list : two times to test 2 regimes
listToReg = []
listToReg.append(toRegressMult)
listToReg.append(toRegressMult)
# Create the binary archive to dump
###################################
archiveToWrite = StOptGeners.BinaryFileArchive("MyArchive","w")
# step 1
archiveToWrite.dumpGridAndRegressedValue("toStore", 1,listToReg, regressor,grid)
# step 3
archiveToWrite.dumpGridAndRegressedValue("toStore", 3,listToReg, regressor,grid)
# Read the regressed values
###########################
archiveToRead = StOptGeners.BinaryFileArchive("MyArchive","r")
contValues = archiveToRead.readGridAndRegressedValue(3,"toStore")
# list of 2 continuation values
##############################
stockPoint = np.array([1.5,3.,5.])
uncertainty = np.array([0.])
value =contValues[0].getValue(stockPoint,uncertainty)
# non regular grid
def testSimpleStorageAndLectureNonRegular(self):
# create the Legendre grid
grid = StOptGrids.GeneralSpaceGrid([[ 1., 1.7, 2.4, 3.1, 3.8 ],
[2., 4.3, 6.6, 8.9, 11.2, 15.],
[3., 4.9, 5.8, 7.7, 10.,20.]])
# simulate the perburbed values
################################
nbSimul =40000
np.random.seed(1000)
x = np.random.uniform(-1.,1.,size=(1,nbSimul));
# mesh
nbMesh = np.array([16],dtype=np.int32)
# Create the regressor
#####################
regressor = StOptReg.LocalLinearRegression(False,x,nbMesh)
# regressed values same values for each point of the grid
#########################################################
toReal = (2+x[0,:]+(1+x[0,:])*(1+x[0,:]))
# function to regress
toRegress = toReal + 4*np.random.normal(0.,1,nbSimul)
# create a matrix (number of stock points by number of simulations)
toRegressMult = np.zeros(shape=(len(toRegress),grid.getNbPoints()))
for i in range(toRegressMult.shape[1]):
toRegressMult[:,i] = toRegress
# into a list : two times to test 2 regimes
listToReg = []
listToReg.append(toRegressMult)
listToReg.append(toRegressMult)
# Create the binary archive to dump
###################################
archiveToWrite = StOptGeners.BinaryFileArchive("MyArchive","w")
# step 1
archiveToWrite.dumpGridAndRegressedValue("toStore", 1,listToReg, regressor,grid)
# step 3
archiveToWrite.dumpGridAndRegressedValue("toStore", 3,listToReg, regressor,grid)
# Read the regressed values
###########################
archiveToRead = StOptGeners.BinaryFileArchive("MyArchive","r")
contValues = archiveToRead.readGridAndRegressedValue(3,"toStore")
# list of 2 continuation values
##############################
stockPoint = np.array([1.5,3.,5.])
uncertainty = np.array([0.])
value =contValues[0].getValue(stockPoint,uncertainty)
if __name__ == '__main__':
unittest.main()
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