CRAN Package Check Results for Package edarf

Last updated on 2020-03-07 09:48:33 CET.

Check Details

Version: 1.1.1
Check: Rd \usage sections
Result: WARN
    Documented arguments not in \usage in documentation object 'extract_proximity':
     '...'
    
    Functions with \usage entries need to have the appropriate \alias
    entries, and all their arguments documented.
    The \usage entries must correspond to syntactically valid R code.
    See chapter 'Writing R documentation files' in the 'Writing R
    Extensions' manual.
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-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64

Version: 1.1.1
Check: examples
Result: ERROR
    Running examples in ‘edarf-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: plot_pd
    > ### Title: Plot partial dependence from random forests
    > ### Aliases: plot_pd
    >
    > ### ** Examples
    >
    > library(randomForest)
    randomForest 4.6-14
    Type rfNews() to see new features/changes/bug fixes.
    > library(edarf)
    > data(iris)
    > fit = randomForest(Species ~ ., iris)
    > pd = partial_dependence(fit, "Petal.Width", data = iris)
    > plot_pd(pd)
    Error in value[[3L]](cond) :
     The melt generic in data.table has been passed a pd, but data.table::melt currently only has a method for data.tables. Please confirm your input is a data.table, with setDT(pd) or as.data.table(pd). If you intend to use a method from reshape2, try installing that package first, but do note that reshape2 is deprecated and you should be migrating your code away from using it.
    Calls: plot_pd ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
    Execution halted
Flavor: r-patched-solaris-x86

Version: 1.1.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [34s/32s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(edarf)
     >
     > set.seed(1987)
     >
     > nperm <- 2L
     > n <- 50
     >
     > X1 <- rnorm(n)
     > X2 <- rnorm(n)
     > X3 <- as.ordered(sample(1:3, n, TRUE))
     > b3 <- runif(3, -1, 1)
     >
     > df_regr <- data.frame(X1, X2, X3, "y" = rowSums(poly(X1)) * X2 + model.matrix( ~ -1 + as.factor(X3)) %*% b3)
     > df_classif <- data.frame(X1, X2, X3, "y" = as.factor(ifelse(df_regr$y > median(df_regr$y), 1, 0)))
     > df_multi <- data.frame("yr" = df_regr$y, "yc" = df_classif$y, X1, X2, X3)
     >
     > library(randomForest)
     randomForest 4.6-14
     Type rfNews() to see new features/changes/bug fixes.
     > library(randomForestSRC)
    
     randomForestSRC 2.9.3
    
     Type rfsrc.news() to see new features, changes, and bug fixes.
    
    
     > library(party)
     Loading required package: grid
     Loading required package: mvtnorm
     Loading required package: modeltools
     Loading required package: stats4
     Loading required package: strucchange
     Loading required package: zoo
    
     Attaching package: 'zoo'
    
     The following objects are masked from 'package:base':
    
     as.Date, as.Date.numeric
    
     Loading required package: sandwich
     > library(ranger)
    
     Attaching package: 'ranger'
    
     The following object is masked from 'package:randomForest':
    
     importance
    
     >
     > fits_regr <- list(
     + randomForest(y ~ ., df_regr, proximity = TRUE),
     + randomForest(df_regr[, -which(colnames(df_regr) == "y")], df_regr$y, proximity = TRUE),
     + cforest(y ~ ., df_regr, controls = cforest_control(mtry = 1)),
     + rfsrc(y ~ ., df_regr, proximity = "inbag"),
     + ranger(y ~ ., df_regr, write.forest = TRUE)
     + )
     >
     > fits_classif <- list(
     + randomForest(y ~ ., df_classif, proximity = TRUE),
     + randomForest(df_classif[, -which(colnames(df_classif) == "y")], df_classif$y, proximity = TRUE),
     + cforest(y ~ ., df_classif, controls = cforest_control(mtry = 1)),
     + rfsrc(y ~ ., df_classif, proximity = "inbag"),
     + ranger(y ~ ., df_classif, write.forest = TRUE)
     + )
     >
     > fits_multi <- list(
     + cforest(yr + yc ~ ., df_multi, controls = cforest_control(mtry = 1))
     + )
     >
     > test_check("edarf")
     ── 1. Error: regression (@test_pd.R#3) ────────────────────────────────────────
     The melt generic in data.table has been passed a pd, but data.table::melt currently only has a method for data.tables. Please confirm your input is a data.table, with setDT(pd) or as.data.table(pd). If you intend to use a method from reshape2, try installing that package first, but do note that reshape2 is deprecated and you should be migrating your code away from using it.
     Backtrace:
     1. base::lapply(...)
     2. edarf:::FUN(X[[i]], ...)
     3. edarf::plot_pd(pd)
     4. data.table::melt(pd, id.vars = c(atts$target, facet), na.rm = TRUE)
     5. base::tryCatch(...)
     6. base:::tryCatchList(expr, classes, parentenv, handlers)
     7. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     8. value[[3L]](cond)
    
     ── 2. Error: classification (@test_pd.R#27) ───────────────────────────────────
     The melt generic in data.table has been passed a pd, but data.table::melt currently only has a method for data.tables. Please confirm your input is a data.table, with setDT(pd) or as.data.table(pd). If you intend to use a method from reshape2, try installing that package first, but do note that reshape2 is deprecated and you should be migrating your code away from using it.
     Backtrace:
     1. base::lapply(...)
     2. edarf:::FUN(X[[i]], ...)
     3. edarf::plot_pd(pd)
     4. data.table::melt(pd, id.vars = c(atts$target, facet), na.rm = TRUE)
     5. base::tryCatch(...)
     6. base:::tryCatchList(expr, classes, parentenv, handlers)
     7. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     8. value[[3L]](cond)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 60 | SKIPPED: 0 | WARNINGS: 15 | FAILED: 2 ]
     1. Error: regression (@test_pd.R#3)
     2. Error: classification (@test_pd.R#27)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-solaris-x86