CRAN Package Check Results for Package classyfire

Last updated on 2019-04-22 07:46:36 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1-2 9.13 101.47 110.60 ERROR
r-devel-linux-x86_64-debian-gcc 0.1-2 7.40 78.52 85.92 ERROR
r-devel-linux-x86_64-fedora-clang 0.1-2 127.54 ERROR
r-devel-linux-x86_64-fedora-gcc 0.1-2 123.79 ERROR
r-devel-windows-ix86+x86_64 0.1-2 23.00 113.00 136.00 ERROR
r-patched-linux-x86_64 0.1-2 8.55 99.59 108.14 ERROR
r-patched-solaris-x86 0.1-2 198.70 ERROR
r-release-linux-x86_64 0.1-2 4.34 83.16 87.50 NOTE
r-release-windows-ix86+x86_64 0.1-2 11.00 129.00 140.00 NOTE
r-release-osx-x86_64 0.1-2 NOTE
r-oldrel-windows-ix86+x86_64 0.1-2 18.00 134.00 152.00 NOTE
r-oldrel-osx-x86_64 0.1-2 NOTE

Check Details

Version: 0.1-2
Check: R code for possible problems
Result: NOTE
    .boxRadial: no visible global function definition for 'predict'
    .radialSVM: no visible global function definition for 'predict'
    cfPredict: no visible global function definition for 'predict'
    getPerm5Num: no visible global function definition for 'median'
    getPerm5Num: no visible global function definition for 'quantile'
    ggClassPred: no visible global function definition for 'ftable'
    ggEnsHist: no visible global function definition for 'sd'
    ggPermHist: no visible global function definition for 'sd'
    Undefined global functions or variables:
     ftable median predict quantile sd
    Consider adding
     importFrom("stats", "ftable", "median", "predict", "quantile", "sd")
    to your NAMESPACE file.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 0.1-2
Check: tests
Result: ERROR
     Running 'UnitTestingClassyfire.R' [29s/31s]
    Running the tests in 'tests/UnitTestingClassyfire.R' failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-patched-linux-x86_64

Version: 0.1-2
Check: tests
Result: ERROR
     Running ‘UnitTestingClassyfire.R’ [21s/26s]
    Running the tests in ‘tests/UnitTestingClassyfire.R’ failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1-2
Check: tests
Result: ERROR
     Running ‘UnitTestingClassyfire.R’ [32s/36s]
    Running the tests in ‘tests/UnitTestingClassyfire.R’ failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.1-2
Check: tests
Result: ERROR
     Running ‘UnitTestingClassyfire.R’ [34s/37s]
    Running the tests in ‘tests/UnitTestingClassyfire.R’ failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.1-2
Check: tests
Result: ERROR
     Running 'UnitTestingClassyfire.R' [29s]
    Running the tests in 'tests/UnitTestingClassyfire.R' failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.1-2
Check: tests
Result: ERROR
     Running ‘UnitTestingClassyfire.R’ [52s/67s]
    Running the tests in ‘tests/UnitTestingClassyfire.R’ failed.
    Complete output:
     > # **************************************************************************************************************
     > # Functions for unit testing
     > # **************************************************************************************************************
     >
     > library('RUnit')
     > library('classyfire')
     Loading required package: snowfall
     Loading required package: snow
     Loading required package: e1071
     Loading required package: boot
     Loading required package: neldermead
     Loading required package: optimbase
     Loading required package: Matrix
     Loading required package: optimsimplex
     >
     > set.seed(1)
     >
     > # Test data
     > data(iris)
     > irisClass <- iris[,5]
     > irisData <- iris[,-5]
     > randClass <- c(2, rep(3, length(irisClass)-1))
     > testVec <- t(c(62,20,68,76))
     >
     > # Use parallel = FALSE for testing on CRAN!
     > ensObj <- cfBuild(inputData = irisData, inputClass = irisClass, bootNum = 5, ensNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > permObj <- cfPermute(irisData, irisClass, bootNum = 5, ensNum = 2, permNum = 2, parallel = FALSE)
     snowfall 1.84-6.1 initialized: sequential execution, one CPU.
    
     > predRes <- cfPredict(ensObj , testVec)
     >
     >
     > # Test the initial checks on the input data provided by the user etc.
     > test.initCheck <- function() {
     + checkException(.initCheck(), silent=TRUE)
     + checkException(.initCheck(irisData), silent=TRUE)
     + checkException(.initCheck(inputClass = inputClass), silent=TRUE)
     + checkException(.initCheck(iris, irisClass), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, irisData), silent=TRUE)
     + checkException(.initCheck(irisData, randClass), silent=TRUE)
     + }
     >
     > # Test the main cfBuild function for the construction of the ensemble
     > test.cfBuild <- function() {
     + checkEquals("cfBuild", class(ensObj)[2])
     + checkEquals(13, length(ensObj))
     + checkEquals(95.1, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals(92.16, ensObj$testAcc[1])
     + checkEquals(96.97, ensObj$trainAcc[1])
     + checkEquals(TRUE, any(attributes(ensObj)$names == "testAcc"))
     + checkEquals(100, getConfMatr(ensObj)[1,1])
     + checkEquals(94, getConfMatr(ensObj)[2,2])
     + checkEquals(91, getConfMatr(ensObj)[3,3])
     + }
     >
     > # Test the cfPermute function for permutation testing
     > test.cfPermute <- function() {
     + checkEquals("cfPermute", class(permObj)[2])
     + checkEquals(4, length(permObj))
     + checkEquals(39.22, permObj$avgAcc[1])
     + checkEquals(2, length(permObj$permList))
     + }
     >
     > # Test the cfPredict function for use with unknown data
     > test.cfPredict <- function() {
     + checkEquals("virginica", as.character(predRes[,1]))
     + checkEquals(100, predRes[,2])
     + }
     >
     > # Test the relevant stats functions
     > test.stats <- function() {
     + checkException(getAcc(), silent=TRUE)
     + checkException(getAvgAcc(), silent=TRUE)
     + checkException(getOptParam(), silent=TRUE)
     + checkException(getConfMatr(), silent=TRUE)
     + checkException(getPerm5Num(), silent=TRUE)
     +
     + checkException(getAcc(randClass), silent=TRUE)
     + checkException(getAvgAcc(randClass), silent=TRUE)
     + checkException(getOptParam(randClass), silent=TRUE)
     + checkException(getConfMatr(randClass), silent=TRUE)
     + checkException(getPerm5Num(randClass), silent=TRUE)
     +
     + checkEquals(2, length(getAcc(ensObj)))
     + checkEquals(2, length(getAvgAcc(ensObj)))
     + checkEquals(92.16, getAcc(ensObj)$Test[1])
     + checkEquals(96.97, getAcc(ensObj)$Train[1])
     + checkEquals(95.10, getAvgAcc(ensObj)$Test)
     + checkEquals(96.97, getAvgAcc(ensObj)$Train)
     + checkEquals("matrix", class(getOptParam(ensObj)))
     + checkEquals("table", class(getConfMatr(ensObj)))
     + checkEquals(9, length(getConfMatr(ensObj)))
     + checkEquals(5, length(getPerm5Num(permObj)))
     + checkEquals(33.33, getPerm5Num(permObj)$minimum)
     + }
     >
     > # Test the relevant plot functions
     > test.plots <- function() {
     + checkException(ggEnsTrend(), silent=TRUE)
     + checkException(ggEnsHist(), silent=TRUE)
     + checkException(ggClassPred(), silent=TRUE)
     + checkException(ggPermHist(), silent=TRUE)
     +
     + checkException(ggEnsTrend(permObj), silent=TRUE)
     + checkException(ggEnsHist(permObj), silent=TRUE)
     + checkException(ggClassPred(permObj), silent=TRUE)
     + checkException(ggPermHist(ensObj), silent=TRUE)
     + }
     >
     > # Execute all the tests
     > test.initCheck()
     [1] TRUE
     > test.cfBuild()
     Error in checkEquals(96.97, getAvgAcc(ensObj)$Train) :
     Mean relative difference: 0.005156234
     Calls: test.cfBuild -> checkEquals
     Execution halted
Flavor: r-patched-solaris-x86