tests/testthat/helper-pacotestRegressionTests.R
In MalteKurz/pacotest: Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas
library("pacotest")
library("testthat")
library("VineCopula")
library("numDeriv")
library("methods")
## Define all scenarios of pacotest that should be unit tested
pacotestOptions = list()
# Define the test types
pacotestOptions[[1]] = list(testType='deactivated_test')
pacotestOptions[[2]] = list(testType='deactivated_test')
pacotestOptions[[3]] = list(testType='deactivated_test')
pacotestOptions[[4]] = list(testType='deactivated_test')
pacotestOptions[[5]] = pacotestset(testType='CCC',grouping = "SumMedian", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[6]] = pacotestset(testType='CCC',grouping = "ProdThirdsII", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[7]] = pacotestset(testType='CCC',grouping = "SumThirdsIII", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[8]] = list(testType='deactivated_test')
pacotestOptions[[9]] = list(testType='deactivated_test')
pacotestOptions[[10]] = list(testType='deactivated_test')
pacotestOptions[[11]] = list(testType='deactivated_test')
pacotestOptions[[12]] = list(testType='deactivated_test')
pacotestOptions[[13]] = list(testType='deactivated_test')
pacotestOptions[[14]] = list(testType='deactivated_test')
pacotestOptions[[15]] = list(testType='deactivated_test')
pacotestOptions[[16]] = list(testType='deactivated_test')
pacotestOptions[[17]] = list(testType='deactivated_test')
pacotestOptions[[18]] = list(testType='deactivated_test')
pacotestOptions[[19]] = list(testType='deactivated_test')
pacotestOptions[[20]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[21]] = pacotestset(testType='CCC', grouping = 'TreeCCC',expMinSampleSize=56, finalComparison = 'pairwiseMax', withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[22]] = pacotestset(testType='CCC', grouping = 'TreeCCC',gamma0Partition='SumQuartiles', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[23]] = pacotestset(testType='CCC', grouping = 'TreeCCC',aggInfo="meanPairwise", finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[24]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[25]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',expMinSampleSize=56, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[26]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',gamma0Partition='SumQuartiles', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[27]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',aggInfo="meanPairwise", expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[28]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[29]] = pacotestset(testType='CCC', grouping = 'TreeEC',expMinSampleSize=56, finalComparison = 'pairwiseMax', withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[30]] = pacotestset(testType='CCC', grouping = 'TreeEC',gamma0Partition='SumQuartiles', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[31]] = pacotestset(testType='CCC', grouping = 'TreeEC',aggInfo="meanPairwise", finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[32]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[33]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',expMinSampleSize=56, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[34]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',gamma0Partition='SumQuartiles', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[35]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',aggInfo="meanPairwise", expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
for (indPacotest in 1:35)
{
if (!(pacotestOptions[[indPacotest]]$testType == 'deactivated_test')) {
if (any(indPacotest == c(1:4, 8:19)))
{
pacotestOptions[[indPacotest + 35]] = pacotestset(pacotestOptions[[indPacotest]], withEstUncert = TRUE)
}
else
{
pacotestOptions[[indPacotest + 35]] = pacotestset(pacotestOptions[[indPacotest]], withEstUncert = TRUE)
}
} else {
pacotestOptions[[indPacotest + 35]] = list(testType='deactivated_test')
}
}
# Define the test types
pacotestOptions[[71]] = pacotestset(testType='VI')
pacotestOptions[[72]] = pacotestset(testType='EC',grouping = "ProdMedian")
pacotestOptions[[73]] = pacotestset(testType='EC',grouping = "ProdThirdsIII")
pacotestOptions[[74]] = pacotestset(testType='EC',grouping = "SumThirdsII")
for (iTest in c(75:95))
{
pacotestOptions[[iTest]] = list(testType='deactivated_test')
}
for (indPacotest in 1:8)
{
if (!(pacotestOptions[[indPacotest+19]]$testType == 'deactivated_test')) {
pacotestOptions[[indPacotest + 95]] = pacotestset(pacotestOptions[[indPacotest+19]], withEstUncert = TRUE, estUncertWithRanks = TRUE)
} else {
pacotestOptions[[indPacotest + 95]] = list(testType='deactivated_test')
}
}
## setup some seeds
set.seed(1921)
seedsPerTest = sample(1:2222, 250)
## load hard-coded results
if (getRversion() >= "3.6.0")
{
hardCodedResults = read.table("hardCodedResEcorr_rversion_gt3_6_0.csv", header = FALSE, sep = ",")
hardCodedResPacotestRvineSingleCopula = read.table("hardCodedResPacotestRvineSingleCopula_rversion_gt3_6_0.csv", header = FALSE, sep = ",", na.strings=c("NA"))
hardCodedResPacotestRvineSeq = as.matrix(read.table("hardCodedResPacotestRvineSeq_rversion_gt3_6_0.csv", header = FALSE, sep = ",", na.strings=c("NA")))
} else
{
hardCodedResults = read.table("hardCodedResEcorr.csv", header = FALSE, sep = ",")
hardCodedResPacotestRvineSingleCopula = read.table("hardCodedResPacotestRvineSingleCopula.csv", header = FALSE, sep = ",", na.strings=c("NA"))
hardCodedResPacotestRvineSeq = as.matrix(read.table("hardCodedResPacotestRvineSeq.csv", header = FALSE, sep = ",", na.strings=c("NA")))
}
colnames(hardCodedResPacotestRvineSeq) <- NULL
## Simulate sample data
set.seed(3131)
# Simulate first data set
N = 1000
data1 = matrix(runif(3*N),N,3)
theta = (4*data1[,1]-2)^3
etheta = expm1(-theta);
data1[,3] = -1/theta*log(1+etheta/(exp(-theta*data1[,2])*(1/data1[,3]-1)+1));
# Simulate second data set
N = 1002
data2 = matrix(runif(5*N),N,5)
# Simulate third data set
N = 1050
data3 = matrix(runif(3*N),N,3)
theta = 12 + 8*sin(0.4*(3*data3[,1]+2)^2)
etheta = expm1(-theta);
data3[,3] = -1/theta*log(1+etheta/(exp(-theta*data3[,2])*(1/data3[,3]-1)+1));
# Simulate fourth data set
N = 1070
W = matrix(runif(3*N),N,3)
data4 = matrix(NA,N,3)
theta = 2
data4[,1] = W[,1]
data4[,2] = (W[,1]^(-theta)*(W[,2]^((-theta)/(1+theta))-1)+1)^(-1/theta);
theta_23_1 = theta /(1+theta)
data4[,3] = (W[,2]^(-theta_23_1)*(W[,3]^((-theta_23_1)/(1+theta_23_1))-1)+1)^(-1/theta_23_1);
data4[,3] = (W[,1]^(-theta)*(data4[,3]^((-theta)/(1+theta))-1)+1)^(-1/theta);
# Get Pseudo-Obs from the conditional copula C_23|1
U = matrix(NA,N,2)
U[,1] = (data4[,1]^theta*(data4[,2]^(-theta)-1)+1)^(-(1+theta)/theta);
U[,2] = (data4[,1]^theta*(data4[,3]^(-theta)-1)+1)^(-(1+theta)/theta);
data4[,c(2,3)] = U
data = list(data1, data2, data3, data4)
set.seed(51312)
# Data set 6
N= 768
# Four-dimensional D-vine
structure = matrix(c(4,0,0,0,
1,3,0,0,
2,1,2,0,
3,2,1,1),4,4,TRUE)
families = array(3,dim=dim(structure))
families = matrix(c(0,0,0,0,
5,0,0,0,
1,1,0,0,
2,2,2,0),4,4,TRUE)
par2 = matrix(c(0,0,0,0,
0,0,0,0,
0,0,0,0,
2.5,8,6,0),4,4,TRUE)
par = matrix(c(0,0,0,0,
5,0,0,0,
0.4,0.3,0,0,
0.5,0.8,0.6,0),4,4,TRUE)
names = c("V1", "V2", "V3","V4")
rvm = VineCopula::RVineMatrix(structure,families,par,par2,names)
rvm = VineCopula::RVineMatrixNormalize(rvm)
data5 = VineCopula::RVineSim(N,rvm)
rvmHatData5 = VineCopula::RVineSeqEst(data5,rvm)
pacotestForData1_4 <- function(data, pacotestOptions)
{
nDataSets = length(data)
res = vector('numeric', length=nDataSets)
for (iDataSet in 1:nDataSets)
{
if (dim(data[[iDataSet]])[2] == 3)
{
res[iDataSet] = pacotest(data[[iDataSet]][,c(2,3)],data[[iDataSet]][,1],pacotestOptions)$pValue
}
else
{
if (dim(data[[iDataSet]])[2] == 5)
{
res[iDataSet] = pacotest(data[[iDataSet]][,c(1,5)],data[[iDataSet]][,c(2,3,4)],pacotestOptions)$pValue
}
}
}
return(res)
}
unitTestKernel <- function(data, pacotestOptions, hardCodedResults, seedsPerTest, thisTestsInd)
{
maxNTests = length(pacotestOptions)
resPacotestComputed = matrix(NA, maxNTests, 4)
for (iTest in thisTestsInd)
{
set.seed(seedsPerTest[iTest])
optionValues = paste(pacotestOptions[[iTest]],';', sep='')
optionNames = paste(names(pacotestOptions[[iTest]]),':', sep='')
optionString = paste(c(rbind(optionNames,optionValues)), collapse=" ")
resPacotestComputed[iTest,] = pacotestForData1_4(data, pacotestOptions[[iTest]])
for (iDataset in 1:4)
{
expect_equal(resPacotestComputed[iTest, iDataset], hardCodedResults[iTest, iDataset], tolerance = 1e-2,
info = paste("Data set number: ", iDataset, "; pacotestOptions: ", optionString, collapse=''))
}
}
return(resPacotestComputed)
}
filterPacotestOptionLists <- function(pacotestOptions, properties, values)
{
maxNTests = length(pacotestOptions)
nProperties = length(properties)
ind = matrix(NA, maxNTests, nProperties)
for (iProperty in 1:nProperties)
{
ind[,iProperty] = sapply(pacotestOptions, function(x) identical(as.character(x[[properties[iProperty]]]), values[iProperty]))
}
xx = apply(ind, 1, all)
yy = 1:maxNTests
thisTestsInd = yy[xx]
return(thisTestsInd)
}
MalteKurz/pacotest documentation built on Nov. 23, 2022, 9:54 p.m.
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library("pacotest")
library("testthat")
library("VineCopula")
library("numDeriv")
library("methods")
## Define all scenarios of pacotest that should be unit tested
pacotestOptions = list()
# Define the test types
pacotestOptions[[1]] = list(testType='deactivated_test')
pacotestOptions[[2]] = list(testType='deactivated_test')
pacotestOptions[[3]] = list(testType='deactivated_test')
pacotestOptions[[4]] = list(testType='deactivated_test')
pacotestOptions[[5]] = pacotestset(testType='CCC',grouping = "SumMedian", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[6]] = pacotestset(testType='CCC',grouping = "ProdThirdsII", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[7]] = pacotestset(testType='CCC',grouping = "SumThirdsIII", withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[8]] = list(testType='deactivated_test')
pacotestOptions[[9]] = list(testType='deactivated_test')
pacotestOptions[[10]] = list(testType='deactivated_test')
pacotestOptions[[11]] = list(testType='deactivated_test')
pacotestOptions[[12]] = list(testType='deactivated_test')
pacotestOptions[[13]] = list(testType='deactivated_test')
pacotestOptions[[14]] = list(testType='deactivated_test')
pacotestOptions[[15]] = list(testType='deactivated_test')
pacotestOptions[[16]] = list(testType='deactivated_test')
pacotestOptions[[17]] = list(testType='deactivated_test')
pacotestOptions[[18]] = list(testType='deactivated_test')
pacotestOptions[[19]] = list(testType='deactivated_test')
pacotestOptions[[20]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[21]] = pacotestset(testType='CCC', grouping = 'TreeCCC',expMinSampleSize=56, finalComparison = 'pairwiseMax', withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[22]] = pacotestset(testType='CCC', grouping = 'TreeCCC',gamma0Partition='SumQuartiles', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[23]] = pacotestset(testType='CCC', grouping = 'TreeCCC',aggInfo="meanPairwise", finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[24]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[25]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',expMinSampleSize=56, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[26]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',gamma0Partition='SumQuartiles', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[27]] = pacotestset(testType='CCC', grouping = 'TreeCCC', finalComparison = 'all',aggInfo="meanPairwise", expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[28]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[29]] = pacotestset(testType='CCC', grouping = 'TreeEC',expMinSampleSize=56, finalComparison = 'pairwiseMax', withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[30]] = pacotestset(testType='CCC', grouping = 'TreeEC',gamma0Partition='SumQuartiles', finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[31]] = pacotestset(testType='CCC', grouping = 'TreeEC',aggInfo="meanPairwise", finalComparison = 'pairwiseMax', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[32]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[33]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',expMinSampleSize=56, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[34]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',gamma0Partition='SumQuartiles', expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
pacotestOptions[[35]] = pacotestset(testType='CCC', grouping = 'TreeEC', finalComparison = 'all',aggInfo="meanPairwise", expMinSampleSize = 100, withEstUncert = FALSE, estUncertWithRanks = FALSE)
for (indPacotest in 1:35)
{
if (!(pacotestOptions[[indPacotest]]$testType == 'deactivated_test')) {
if (any(indPacotest == c(1:4, 8:19)))
{
pacotestOptions[[indPacotest + 35]] = pacotestset(pacotestOptions[[indPacotest]], withEstUncert = TRUE)
}
else
{
pacotestOptions[[indPacotest + 35]] = pacotestset(pacotestOptions[[indPacotest]], withEstUncert = TRUE)
}
} else {
pacotestOptions[[indPacotest + 35]] = list(testType='deactivated_test')
}
}
# Define the test types
pacotestOptions[[71]] = pacotestset(testType='VI')
pacotestOptions[[72]] = pacotestset(testType='EC',grouping = "ProdMedian")
pacotestOptions[[73]] = pacotestset(testType='EC',grouping = "ProdThirdsIII")
pacotestOptions[[74]] = pacotestset(testType='EC',grouping = "SumThirdsII")
for (iTest in c(75:95))
{
pacotestOptions[[iTest]] = list(testType='deactivated_test')
}
for (indPacotest in 1:8)
{
if (!(pacotestOptions[[indPacotest+19]]$testType == 'deactivated_test')) {
pacotestOptions[[indPacotest + 95]] = pacotestset(pacotestOptions[[indPacotest+19]], withEstUncert = TRUE, estUncertWithRanks = TRUE)
} else {
pacotestOptions[[indPacotest + 95]] = list(testType='deactivated_test')
}
}
## setup some seeds
set.seed(1921)
seedsPerTest = sample(1:2222, 250)
## load hard-coded results
if (getRversion() >= "3.6.0")
{
hardCodedResults = read.table("hardCodedResEcorr_rversion_gt3_6_0.csv", header = FALSE, sep = ",")
hardCodedResPacotestRvineSingleCopula = read.table("hardCodedResPacotestRvineSingleCopula_rversion_gt3_6_0.csv", header = FALSE, sep = ",", na.strings=c("NA"))
hardCodedResPacotestRvineSeq = as.matrix(read.table("hardCodedResPacotestRvineSeq_rversion_gt3_6_0.csv", header = FALSE, sep = ",", na.strings=c("NA")))
} else
{
hardCodedResults = read.table("hardCodedResEcorr.csv", header = FALSE, sep = ",")
hardCodedResPacotestRvineSingleCopula = read.table("hardCodedResPacotestRvineSingleCopula.csv", header = FALSE, sep = ",", na.strings=c("NA"))
hardCodedResPacotestRvineSeq = as.matrix(read.table("hardCodedResPacotestRvineSeq.csv", header = FALSE, sep = ",", na.strings=c("NA")))
}
colnames(hardCodedResPacotestRvineSeq) <- NULL
## Simulate sample data
set.seed(3131)
# Simulate first data set
N = 1000
data1 = matrix(runif(3*N),N,3)
theta = (4*data1[,1]-2)^3
etheta = expm1(-theta);
data1[,3] = -1/theta*log(1+etheta/(exp(-theta*data1[,2])*(1/data1[,3]-1)+1));
# Simulate second data set
N = 1002
data2 = matrix(runif(5*N),N,5)
# Simulate third data set
N = 1050
data3 = matrix(runif(3*N),N,3)
theta = 12 + 8*sin(0.4*(3*data3[,1]+2)^2)
etheta = expm1(-theta);
data3[,3] = -1/theta*log(1+etheta/(exp(-theta*data3[,2])*(1/data3[,3]-1)+1));
# Simulate fourth data set
N = 1070
W = matrix(runif(3*N),N,3)
data4 = matrix(NA,N,3)
theta = 2
data4[,1] = W[,1]
data4[,2] = (W[,1]^(-theta)*(W[,2]^((-theta)/(1+theta))-1)+1)^(-1/theta);
theta_23_1 = theta /(1+theta)
data4[,3] = (W[,2]^(-theta_23_1)*(W[,3]^((-theta_23_1)/(1+theta_23_1))-1)+1)^(-1/theta_23_1);
data4[,3] = (W[,1]^(-theta)*(data4[,3]^((-theta)/(1+theta))-1)+1)^(-1/theta);
# Get Pseudo-Obs from the conditional copula C_23|1
U = matrix(NA,N,2)
U[,1] = (data4[,1]^theta*(data4[,2]^(-theta)-1)+1)^(-(1+theta)/theta);
U[,2] = (data4[,1]^theta*(data4[,3]^(-theta)-1)+1)^(-(1+theta)/theta);
data4[,c(2,3)] = U
data = list(data1, data2, data3, data4)
set.seed(51312)
# Data set 6
N= 768
# Four-dimensional D-vine
structure = matrix(c(4,0,0,0,
1,3,0,0,
2,1,2,0,
3,2,1,1),4,4,TRUE)
families = array(3,dim=dim(structure))
families = matrix(c(0,0,0,0,
5,0,0,0,
1,1,0,0,
2,2,2,0),4,4,TRUE)
par2 = matrix(c(0,0,0,0,
0,0,0,0,
0,0,0,0,
2.5,8,6,0),4,4,TRUE)
par = matrix(c(0,0,0,0,
5,0,0,0,
0.4,0.3,0,0,
0.5,0.8,0.6,0),4,4,TRUE)
names = c("V1", "V2", "V3","V4")
rvm = VineCopula::RVineMatrix(structure,families,par,par2,names)
rvm = VineCopula::RVineMatrixNormalize(rvm)
data5 = VineCopula::RVineSim(N,rvm)
rvmHatData5 = VineCopula::RVineSeqEst(data5,rvm)
pacotestForData1_4 <- function(data, pacotestOptions)
{
nDataSets = length(data)
res = vector('numeric', length=nDataSets)
for (iDataSet in 1:nDataSets)
{
if (dim(data[[iDataSet]])[2] == 3)
{
res[iDataSet] = pacotest(data[[iDataSet]][,c(2,3)],data[[iDataSet]][,1],pacotestOptions)$pValue
}
else
{
if (dim(data[[iDataSet]])[2] == 5)
{
res[iDataSet] = pacotest(data[[iDataSet]][,c(1,5)],data[[iDataSet]][,c(2,3,4)],pacotestOptions)$pValue
}
}
}
return(res)
}
unitTestKernel <- function(data, pacotestOptions, hardCodedResults, seedsPerTest, thisTestsInd)
{
maxNTests = length(pacotestOptions)
resPacotestComputed = matrix(NA, maxNTests, 4)
for (iTest in thisTestsInd)
{
set.seed(seedsPerTest[iTest])
optionValues = paste(pacotestOptions[[iTest]],';', sep='')
optionNames = paste(names(pacotestOptions[[iTest]]),':', sep='')
optionString = paste(c(rbind(optionNames,optionValues)), collapse=" ")
resPacotestComputed[iTest,] = pacotestForData1_4(data, pacotestOptions[[iTest]])
for (iDataset in 1:4)
{
expect_equal(resPacotestComputed[iTest, iDataset], hardCodedResults[iTest, iDataset], tolerance = 1e-2,
info = paste("Data set number: ", iDataset, "; pacotestOptions: ", optionString, collapse=''))
}
}
return(resPacotestComputed)
}
filterPacotestOptionLists <- function(pacotestOptions, properties, values)
{
maxNTests = length(pacotestOptions)
nProperties = length(properties)
ind = matrix(NA, maxNTests, nProperties)
for (iProperty in 1:nProperties)
{
ind[,iProperty] = sapply(pacotestOptions, function(x) identical(as.character(x[[properties[iProperty]]]), values[iProperty]))
}
xx = apply(ind, 1, all)
yy = 1:maxNTests
thisTestsInd = yy[xx]
return(thisTestsInd)
}
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