CRAN Package Check Results for Package smartdata

Last updated on 2020-03-31 11:49:25 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.3 6.31 232.71 239.02 OK
r-devel-linux-x86_64-debian-gcc 1.0.3 6.22 170.32 176.54 OK
r-devel-linux-x86_64-fedora-clang 1.0.3 284.95 NOTE
r-devel-linux-x86_64-fedora-gcc 1.0.3 285.66 NOTE
r-devel-windows-ix86+x86_64 1.0.3 31.00 216.00 247.00 ERROR
r-devel-windows-ix86+x86_64-gcc8 1.0.3 27.00 234.00 261.00 ERROR
r-patched-linux-x86_64 1.0.3 7.30 226.11 233.41 OK
r-release-linux-x86_64 1.0.3 6.51 211.33 217.84 OK
r-release-windows-ix86+x86_64 1.0.3 25.00 306.00 331.00 OK
r-release-osx-x86_64 1.0.3 NOTE
r-oldrel-windows-ix86+x86_64 1.0.3 19.00 325.00 344.00 OK
r-oldrel-osx-x86_64 1.0.3 NOTE

Check Details

Version: 1.0.3
Check: package dependencies
Result: NOTE
    Imports includes 23 non-default packages.
    Importing from so many packages makes the package vulnerable to any of
    them becoming unavailable. Move as many as possible to Suggests and
    use conditionally.
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 1.0.3
Check: dependencies in R code
Result: NOTE
    Namespaces in Imports field not imported from:
     ‘Amelia’ ‘Boruta’ ‘DMwR’ ‘MVN’ ‘NoiseFiltersR’ ‘VIM’ ‘adaptiveGPCA’
     ‘class’ ‘clusterSim’ ‘denoiseR’ ‘discretization’ ‘imbalance’ ‘lle’
     ‘missForest’ ‘missMDA’ ‘outliers’ ‘unbalanced’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-release-osx-x86_64, r-oldrel-osx-x86_64

Version: 1.0.3
Check: tests
Result: ERROR
     Running 'testthat.R' [95s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(smartdata)
     Loading required package: mice
    
     Attaching package: 'mice'
    
     The following objects are masked from 'package:base':
    
     cbind, rbind
    
     >
     > test_check("smartdata")
     missForest iteration 1 in progress...done!
     missForest iteration 2 in progress...done!
     missForest iteration 3 in progress...done!
     [1] "ANS is done"
     [1] "0 samples filtered by NEATER"
     [1] "SLS done"
     finding neighbours
     calculating weights
     computing coordinates
     -- 1. Failure: Correct space transformation (@testSpaceTransformation.R#11) ---
     `space_transformation(...)` threw an error.
     Message: .onLoad failed in loadNamespace() for 'S4Vectors', details:
     call: validObject(.Object)
     error: invalid class "LLint" object: superclass "integer_OR_LLint" not defined in the environment of the object's class
     Class: simpleError/error/condition
     Backtrace:
     1. testthat::expect_error(...)
     6. smartdata::space_transformation(...)
     8. smartdata:::preprocess.spaceTransformation(task)
     10. smartdata:::doSpaceTransformation.adaptiveGPCA(task)
     11. smartdata:::mapMethod(spaceTransformationPackages, task$method)
     14. adaptiveGPCA::adaptivegpca
     15. base::getExportedValue(pkg, name)
     16. base::asNamespace(ns)
     17. base::getNamespace(ns)
     18. base::loadNamespace(name)
     21. base::loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
     24. base::loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
     26. base::loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]])
     27. base:::runHook(".onLoad", env, package.lib, package)
    
     Possible methods are: 'multivariate', 'univariate'
     For more information do: ?NoiseFiltersR::AENN
     Parameters for AENN are:
     * k: Number of nearest neighbors for KNN
     Default value: 5
     For more information do: ?NoiseFiltersR::hybridRepairFilter
     Parameters for hybrid are:
     * consensus: Use consensus vote if TRUE. Else, use majority vote
     Default value: FALSE
     * action: Strategy to treat noisy instances: 'remove', 'repair', 'hybrid'
     Default value: remove
     Possible methods are: 'AENN', 'ENN', 'BBNR', 'DROP1', 'DROP2', 'DROP3', 'EF', 'ENG', 'HARF', 'GE', 'INFFC', 'IPF', 'Mode', 'PF', 'PRISM', 'RNN', 'ORBoost', 'edgeBoost', 'edgeWeight', 'TomekLinks', 'dynamic', 'hybrid', 'saturation', 'consensusSF', 'classificationSF', 'C45robust', 'C45voting', 'C45iteratedVoting', 'CVCF'
     Possible methods are: 'gibbs_sampling', 'expect_maximization', 'central_imputation', 'knn_imputation', 'rf_imputation', 'PCA_imputation', 'MCA_imputation', 'FAMD_imputation', 'hotdeck', 'iterative_robust', 'regression_imputation', 'ATN'
     For more information do: ?FSelector::chi.squared
     Parameters for chi_squared are:
     * num_features: Number of attributes to pick (apart from class_attr, if supplied).
     Should be lower than number of features in the
     dataset
     Default value: 1
     Possible methods are: 'CNN', 'ENN', 'multiedit', 'FRIS'
     Possible methods are: 'chi2', 'chi_merge', 'extended_chi2', 'mod_chi2', 'CAIM', 'CACC', 'ameva', 'mdlp', 'equalfreq', 'equalwidth', 'globalequalwidth'
     Possible methods are: 'z_score', 'pos_standardization', 'unitization', 'pos_unitization', 'min_max', 'rnorm', 'rpnorm', 'sd_quotient', 'mad_quotient', 'range_quotient', 'max_quotient', 'mean_quotient', 'median_quotient', 'sum_quotient', 'ssq_quotient', 'norm', 'pnorm', 'znorm'
     Possible methods are: 'RACOG', 'wRACOG', 'PDFOS', 'RWO', 'ADASYN', 'ANSMOTE', 'SMOTE', 'MWMOTE', 'BLSMOTE', 'DBSMOTE', 'SLMOTE', 'RSLSMOTE'
     Possible methods are: 'lle_knn', 'lle_epsilon', 'adaptative_gpca'
     == testthat results ===========================================================
     [ OK: 236 | SKIPPED: 0 | WARNINGS: 89 | FAILED: 1 ]
     1. Failure: Correct space transformation (@testSpaceTransformation.R#11)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 1.0.3
Check: tests
Result: ERROR
     Running 'testthat.R' [100s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(smartdata)
     Loading required package: mice
    
     Attaching package: 'mice'
    
     The following objects are masked from 'package:base':
    
     cbind, rbind
    
     >
     > test_check("smartdata")
     missForest iteration 1 in progress...done!
     missForest iteration 2 in progress...done!
     missForest iteration 3 in progress...done!
     missForest iteration 4 in progress...done!
     [1] "ANS is done"
     [1] "0 samples filtered by NEATER"
     [1] "SLS done"
     finding neighbours
     calculating weights
     computing coordinates
     -- 1. Failure: Correct space transformation (@testSpaceTransformation.R#11) ---
     `space_transformation(...)` threw an error.
     Message: .onLoad failed in loadNamespace() for 'S4Vectors', details:
     call: validObject(.Object)
     error: invalid class "LLint" object: superclass "integer_OR_LLint" not defined in the environment of the object's class
     Class: simpleError/error/condition
     Backtrace:
     1. testthat::expect_error(...)
     6. smartdata::space_transformation(...)
     8. smartdata:::preprocess.spaceTransformation(task)
     10. smartdata:::doSpaceTransformation.adaptiveGPCA(task)
     11. smartdata:::mapMethod(spaceTransformationPackages, task$method)
     14. adaptiveGPCA::adaptivegpca
     15. base::getExportedValue(pkg, name)
     16. base::asNamespace(ns)
     17. base::getNamespace(ns)
     18. base::loadNamespace(name)
     21. base::loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
     24. base::loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
     26. base::loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]])
     27. base:::runHook(".onLoad", env, package.lib, package)
    
     Possible methods are: 'multivariate', 'univariate'
     For more information do: ?NoiseFiltersR::AENN
     Parameters for AENN are:
     * k: Number of nearest neighbors for KNN
     Default value: 5
     For more information do: ?NoiseFiltersR::hybridRepairFilter
     Parameters for hybrid are:
     * consensus: Use consensus vote if TRUE. Else, use majority vote
     Default value: FALSE
     * action: Strategy to treat noisy instances: 'remove', 'repair', 'hybrid'
     Default value: remove
     Possible methods are: 'AENN', 'ENN', 'BBNR', 'DROP1', 'DROP2', 'DROP3', 'EF', 'ENG', 'HARF', 'GE', 'INFFC', 'IPF', 'Mode', 'PF', 'PRISM', 'RNN', 'ORBoost', 'edgeBoost', 'edgeWeight', 'TomekLinks', 'dynamic', 'hybrid', 'saturation', 'consensusSF', 'classificationSF', 'C45robust', 'C45voting', 'C45iteratedVoting', 'CVCF'
     Possible methods are: 'gibbs_sampling', 'expect_maximization', 'central_imputation', 'knn_imputation', 'rf_imputation', 'PCA_imputation', 'MCA_imputation', 'FAMD_imputation', 'hotdeck', 'iterative_robust', 'regression_imputation', 'ATN'
     For more information do: ?FSelector::chi.squared
     Parameters for chi_squared are:
     * num_features: Number of attributes to pick (apart from class_attr, if supplied).
     Should be lower than number of features in the
     dataset
     Default value: 1
     Possible methods are: 'CNN', 'ENN', 'multiedit', 'FRIS'
     Possible methods are: 'chi2', 'chi_merge', 'extended_chi2', 'mod_chi2', 'CAIM', 'CACC', 'ameva', 'mdlp', 'equalfreq', 'equalwidth', 'globalequalwidth'
     Possible methods are: 'z_score', 'pos_standardization', 'unitization', 'pos_unitization', 'min_max', 'rnorm', 'rpnorm', 'sd_quotient', 'mad_quotient', 'range_quotient', 'max_quotient', 'mean_quotient', 'median_quotient', 'sum_quotient', 'ssq_quotient', 'norm', 'pnorm', 'znorm'
     Possible methods are: 'RACOG', 'wRACOG', 'PDFOS', 'RWO', 'ADASYN', 'ANSMOTE', 'SMOTE', 'MWMOTE', 'BLSMOTE', 'DBSMOTE', 'SLMOTE', 'RSLSMOTE'
     Possible methods are: 'lle_knn', 'lle_epsilon', 'adaptative_gpca'
     == testthat results ===========================================================
     [ OK: 236 | SKIPPED: 0 | WARNINGS: 86 | FAILED: 1 ]
     1. Failure: Correct space transformation (@testSpaceTransformation.R#11)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64-gcc8