CRAN Package Check Results for Package semtree

Last updated on 2020-08-07 01:50:00 CEST.

Check Details

Version: 0.9.14
Check: dependencies in R code
Result: NOTE
    Namespaces in Imports field not imported from:
     ‘expm’ ‘matrixStats’ ‘matrixcalc’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86, r-release-macos-x86_64, r-oldrel-macos-x86_64

Version: 0.9.14
Check: tests
Result: ERROR
     Running ‘invariance.R’ [10s/37s]
     Running ‘lavaan.R’ [59s/70s]
     Running ‘tree.R’ [11s/36s]
     Running ‘vim.R’ [30m/31m]
    Running the tests in ‘tests/invariance.R’ failed.
    Complete output:
     > #
     > # testing invariance
     > #
     >
     > # simulation:
     > # factor structure holds over SES but not over age
     > # both SES and age predict a mean difference in cognitive outcome
     >
     > set.seed(123)
     >
     > require("semtree")
     Loading required package: semtree
     Loading required package: OpenMx
     To take full advantage of multiple cores, use:
     mxOption(key='Number of Threads', value=parallel::detectCores()) #now
     Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
     > require("lavaan")
     Loading required package: lavaan
     This is lavaan 0.6-7
     lavaan is BETA software! Please report any bugs.
    
     Attaching package: 'lavaan'
    
     The following object is masked from 'package:OpenMx':
    
     vech
    
     > #
     > lambda <- list()
     > age <- c(0,0,1,1) # 0=young, 1 =old
     > ses <- c(0,1,0,1) # 0=low, 1=high
     > lambda[[1]] <- c(1,0.9,0.8,0.8)
     > lambda[[2]] <- c(1,0.9,0.8,0.8)
     > lambda[[3]] <- c(1,0.4,0.2,0.9)
     > lambda[[4]] <- c(1,0.4,0.2,0.9)
     > cogmean <- 80-age*30 + ses*20
     > cogsd <- 1
     > errsd <- 1
     >
     > Nsub <- 200 # persons per agexSES group
     >
     > cbind(age,ses,cogmean)
     age ses cogmean
     [1,] 0 0 80
     [2,] 0 1 100
     [3,] 1 0 50
     [4,] 1 1 70
     >
     > # simulate data from 4 groups
     > data <- c()
     > for (i in 1:4) {
     + cogsim <- rnorm(n = Nsub,mean = cogmean[i],cogsd)
     + scores <- as.matrix(t(outer(lambda[[i]],cogsim))) + rnorm(Nsub*4,0,errsd)
     + data <- rbind(data,scores)
     + }
     > data <- data.frame(data)
     > names(data) <- paste0("x",1:4)
     >
     > fulldata <- cbind(data, age=rep(age,each=Nsub),ses=rep(ses,each=Nsub))
     > #
     > model<-"
     + ! regressions
     + F=~1.0*x1
     + F=~l2*x2
     + F=~l3*x3
     + F=~l4*x4
     + ! residuals, variances and covariances
     + x1 ~~ VAR_x1*x1
     + x2 ~~ VAR_x2*x2
     + x3 ~~ VAR_x3*x3
     + x4 ~~ VAR_x4*x4
     + F ~~ 1.0*F
     + ! means
     + F~1
     + x1~0*1;
     + x2~0*1;
     + x3~0*1;
     + x4~0*1;
     + ";
     > result<-lavaan(model, data=data, fixed.x=FALSE, missing="FIML");
     Warning message:
     In lav_object_post_check(object) :
     lavaan WARNING: some estimated ov variances are negative
     >
     > manifests<-c("x1","x2","x3","x4")
     > latents<-c("F")
     > model <- mxModel("Unnamed_Model",
     + type="RAM",
     + manifestVars = manifests,
     + latentVars = latents,
     + mxPath(from="F",to=c("x1","x2","x3","x4"), free=c(FALSE,TRUE,TRUE,TRUE),
     + value=c(1.0,1.0,1.0,1.0) , arrows=1, label=c("F__x1","l2","l3","l4") ),
     + mxPath(from="one",to=c("F"), free=c(TRUE), value=c(1.0) , arrows=1, label=c("const__F") ),
     + mxPath(from="one",to=c("x2","x3","x4"), free=c(TRUE,TRUE,TRUE), value=c(1.0,1.0,1.0) , arrows=1, label=c("const__x2","const__x3","const__x4") ),
     + mxPath(from="x1",to=c("x1"), free=c(TRUE), value=c(1.0) , arrows=2, label=c("VAR_x1") ),
     + mxPath(from="x2",to=c("x2"), free=c(TRUE), value=c(1.0) , arrows=2, label=c("VAR_x2") ),
     + mxPath(from="x3",to=c("x3"), free=c(TRUE), value=c(1.0) , arrows=2, label=c("VAR_x3") ),
     + mxPath(from="x4",to=c("x4"), free=c(TRUE), value=c(1.0) , arrows=2, label=c("VAR_x4") ),
     + mxPath(from="F",to=c("F"), free=c(FALSE), value=c(1.0) , arrows=2, label=c("VAR_F") ),
     + mxPath(from="one",to=c("x1"), free=F, value=0, arrows=1),
     + mxData(data[1:50,], type = "raw")
     + );
     >
     > result <- mxTryHard(model)
     Running Unnamed_Model with 11 parameters
    
     Beginning initial fit attempt
     Running Unnamed_Model with 11 parameters
    
     Lowest minimum so far: 625.429968234728
     OpenMx status code 6 not in list of acceptable status codes, (0,0)
     Not all eigenvalues of the Hessian are positive: 15624363.2856136, 451788.538331029, 256131.049261366, 84.8321147425072, 80.3110408390835, 33.6991428229913, 29.9347099260331, 24.1712397970557, 0.0128894630899421, 0.00860471046331473, -36951857.1480811
    
     Beginning fit attempt 1 of at maximum 10 extra tries
     Running Unnamed_Model with 11 parameters
    
     Fit attempt worse than current best: 625.488211524676 vs 625.429968234728
    
     Beginning fit attempt 2 of at maximum 10 extra tries
     Running Unnamed_Model with 11 parameters
    
     *** caught segfault ***
     address 0, cause 'memory not mapped'
    
     Traceback:
     1: runHelper(model, frontendStart, intervals, silent, suppressWarnings, unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer, beginMessage)
     2: mxRun(model = model, suppressWarnings = T, unsafe = T, silent = T, intervals = intervals, beginMessage = T)
     3: runWithCounter(model, numdone, silent, intervals = F)
     4: doTryCatch(return(expr), name, parentenv, handler)
     5: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     6: tryCatchList(expr, classes, parentenv, handlers)
     7: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
     8: try(runWithCounter(model, numdone, silent, intervals = F))
     9: withCallingHandlers(expr, warning = function(w) if (inherits(w, classes)) tryInvokeRestart("muffleWarning"))
     10: suppressWarnings(try(runWithCounter(model, numdone, silent, intervals = F)))
     11: mxTryHard(model)
     An irrecoverable exception occurred. R is aborting now ...
    Running the tests in ‘tests/tree.R’ failed.
    Complete output:
     > set.seed(789)
     > require("semtree")
     Loading required package: semtree
     Loading required package: OpenMx
     To take full advantage of multiple cores, use:
     mxOption(key='Number of Threads', value=parallel::detectCores()) #now
     Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
     > data(lgcm)
     >
     > lgcm$agegroup <- as.ordered(lgcm$agegroup)
     > lgcm$training <- as.factor(lgcm$training)
     > lgcm$noise <- as.numeric(lgcm$noise)
     >
     > # LOAD IN OPENMX MODEL.
     > # A SIMPLE LINEAR GROWTH MODEL WITH 5 TIME POINTS FROM SIMULATED DATA
     >
     > manifests <- names(lgcm)[1:5]
     > lgcModel <- mxModel("Linear Growth Curve Model Path Specification",
     + type="RAM",
     + manifestVars=manifests,
     + latentVars=c("intercept","slope"),
     + # residual variances
     + mxPath(
     + from=manifests,
     + arrows=2,
     + free=TRUE,
     + values = c(1, 1, 1, 1, 1),
     + labels=c("residual1","residual2","residual3","residual4","residual5")
     + ),
     + # latent variances and covariance
     + mxPath(
     + from=c("intercept","slope"),
     + connect="unique.pairs",
     + arrows=2,
     + free=TRUE,
     + values=c(1, 1, 1),
     + labels=c("vari", "cov", "vars")
     + ),
     + # intercept loadings
     + mxPath(
     + from="intercept",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(1, 1, 1, 1, 1)
     + ),
     + # slope loadings
     + mxPath(
     + from="slope",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(0, 1, 2, 3, 4)
     + ),
     + # manifest means
     + mxPath(
     + from="one",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(0, 0, 0, 0, 0)
     + ),
     + # latent means
     + mxPath(
     + from="one",
     + to=c("intercept", "slope"),
     + arrows=1,
     + free=TRUE,
     + values=c(1, 1),
     + labels=c("meani", "means")
     + ),
     + mxData(lgcm,type="raw")
     + )
     >
     >
     > # TREE CONTROL OPTIONS.
     > # TO OBTAIN BASIC/DEFAULT SMETREE OPTIONS, SIMPLY TPYE THE FOLLOWING:
     >
     > controlOptions <- semtree.control(method = "naive")
     > controlOptions$alpha <- 0.05
     >
     > # RUN TREE.
     >
     > tree <- semtree(model=lgcModel, data=lgcm, control = controlOptions)
    
     *** caught segfault ***
     address 0, cause 'memory not mapped'
    
     Traceback:
     1: runHelper(model, frontendStart, intervals, silent, suppressWarnings, unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer, beginMessage)
     2: mxRun(full.model, suppressWarnings = T, silent = T)
     3: doTryCatch(return(expr), name, parentenv, handler)
     4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
     7: try(mxRun(full.model, suppressWarnings = T, silent = T))
     8: growTree(model, sub2, control, invariance, meta, edgelabel = 0, depth = depth + 1, constraints)
     9: growTree(model = model, mydata = dataset, control = control, invariance = invariance, meta = meta, constraints = constraints, ...)
     10: semtree(model = lgcModel, data = lgcm, control = controlOptions)
     An irrecoverable exception occurred. R is aborting now ...
    Running the tests in ‘tests/vim.R’ failed.
    Complete output:
     > set.seed(789)
     > require("semtree")
     Loading required package: semtree
     Loading required package: OpenMx
     To take full advantage of multiple cores, use:
     mxOption(key='Number of Threads', value=parallel::detectCores()) #now
     Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
     > data(lgcm)
     >
     > lgcm$agegroup <- as.ordered(lgcm$agegroup)
     > lgcm$training <- as.factor(lgcm$training)
     > lgcm$noise <- as.numeric(lgcm$noise)
     >
     > # LOAD IN OPENMX MODEL.
     > # A SIMPLE LINEAR GROWTH MODEL WITH 5 TIME POINTS FROM SIMULATED DATA
     >
     > manifests <- names(lgcm)[1:5]
     > lgcModel <- mxModel("Linear Growth Curve Model Path Specification",
     + type="RAM",
     + manifestVars=manifests,
     + latentVars=c("intercept","slope"),
     + # residual variances
     + mxPath(
     + from=manifests,
     + arrows=2,
     + free=TRUE,
     + values = c(1, 1, 1, 1, 1),
     + labels=c("residual1","residual2","residual3","residual4","residual5")
     + ),
     + # latent variances and covariance
     + mxPath(
     + from=c("intercept","slope"),
     + connect="unique.pairs",
     + arrows=2,
     + free=TRUE,
     + values=c(1, 1, 1),
     + labels=c("vari", "cov", "vars")
     + ),
     + # intercept loadings
     + mxPath(
     + from="intercept",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(1, 1, 1, 1, 1)
     + ),
     + # slope loadings
     + mxPath(
     + from="slope",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(0, 1, 2, 3, 4)
     + ),
     + # manifest means
     + mxPath(
     + from="one",
     + to=manifests,
     + arrows=1,
     + free=FALSE,
     + values=c(0, 0, 0, 0, 0)
     + ),
     + # latent means
     + mxPath(
     + from="one",
     + to=c("intercept", "slope"),
     + arrows=1,
     + free=TRUE,
     + values=c(1, 1),
     + labels=c("meani", "means")
     + ),
     + mxData(lgcm,type="raw")
     + )
     >
     >
     > fr <- semforest(lgcModel, lgcm,control = semforest.control(num.trees = 15))
Flavor: r-patched-solaris-x86

Version: 0.9.14
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    Segmentation Fault - core dumped
    --- re-building ‘constraints.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Loading required package: OpenMx
    To take full advantage of multiple cores, use:
     mxOption(key='Number of Threads', value=parallel::detectCores()) #now
     Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
    Warning: code chunks must not depend on the uncached chunk "difsim"
    
     *** caught segfault ***
    address 0, cause 'memory not mapped'
    
    Traceback:
     1: runHelper(model, frontendStart, intervals, silent, suppressWarnings, unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer, beginMessage)
     2: mxRun(full.model, suppressWarnings = T, silent = T)
     3: doTryCatch(return(expr), name, parentenv, handler)
     4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
     7: try(mxRun(full.model, suppressWarnings = T, silent = T))
     8: growTree(model, sub1, control, invariance, meta, edgelabel = 1, depth = depth + 1, constraints)
     9: growTree(model = model, mydata = dataset, control = control, invariance = invariance, meta = meta, constraints = constraints, ...)
    10: semtree(model.cfa, data = cfa.sim, constraints = semtree.constraints(global.invariance = c("F__x1", "F__x2", "F__x3", "F__x4")))
    11: eval(expr, envir, enclos)
    12: eval(expr, envir, enclos)
    13: withVisible(eval(expr, envir, enclos))
    14: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)
    15: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler))
    16: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
    17: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos, debug = debug, last = i == length(out), use_try = stop_on_error != 2L, keep_warning = keep_warning, keep_message = keep_message, output_handler = output_handler, include_timing = include_timing)
    18: evaluate::evaluate(...)
    19: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), stop_on_error = if (options$error && options$include) 0L else 2L, output_handler = knit_handlers(options$render, options))
    20: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), stop_on_error = if (options$error && options$include) 0L else 2L, output_handler = knit_handlers(options$render, options)))
    21: block_exec(params)
    22: call_block(x)
    23: process_group.block(group)
    24: process_group(group)
    25: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { setwd(wd) cat(res, sep = "\n", file = output %n% "") message("Quitting from lines ", paste(current_lines(i), collapse = "-"), " (", knit_concord$get("infile"), ") ") })
    26: process_file(text, output)
    27: knit(input, text = text, envir = envir, quiet = quiet)
    28: knit2html(..., force_v1 = TRUE)
    29: (if (grepl("\\.[Rr]md$", file)) knit2html_v1 else if (grepl("\\.[Rr]rst$", file)) knit2pandoc else knit)(file, encoding = encoding, quiet = quiet, envir = globalenv(), ...)
    30: vweave(...)
    31: engine$weave(file, quiet = quiet, encoding = enc)
    32: doTryCatch(return(expr), name, parentenv, handler)
    33: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    34: tryCatchList(expr, classes, parentenv, handlers)
    35: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = "weave", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = "texi2pdf", engine = engine) }}, error = function(e) { OK <<- FALSE message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", file, conditionMessage(e)))})
    36: tools:::.buildOneVignette("constraints.Rmd", "/home/ripley/R/packages/tests32/semtree.Rcheck/vign_test/semtree", TRUE, FALSE, "constraints", "UTF-8", "/tmp/RtmpUVaa60/working_dir/RtmpzBayhe/file83b3de6549a.rds")
    An irrecoverable exception occurred. R is aborting now ...
    --- re-building ‘getting-started.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    --- finished re-building ‘getting-started.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘constraints.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86