* using log directory ‘/data/blackswan/ripley/R/packages/tests-devel/morse.Rcheck’
* using R Under development (unstable) (2024-03-16 r86144)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (GCC) 13.2.1 20231011 (Red Hat 13.2.1-4)
    GNU Fortran (GCC) 13.2.1 20231011 (Red Hat 13.2.1-4)
* running under: Fedora Linux 38 (Workstation Edition)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘morse/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘morse’ version ‘3.3.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘morse’ can be installed ... [15s/15s] OK
* used C compiler: ‘gcc (GCC) 13.2.1 20231011 (Red Hat 13.2.1-4)’
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [26s/27s] OK
* checking Rd files ... NOTE
checkRd: (-1) plot.LCx.Rd:34: Lost braces
    34 | \\code{LCx} class. It plots the survival probability as a function of concentration.
       |       ^
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compilation flags used ... OK
* checking compiled code ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... [10s/10s] OK
* checking examples with --run-donttest ... [198s/199s] ERROR
Running examples in ‘morse-Ex.R’ failed
The error most likely occurred in:

> ### Name: MFx
> ### Title: Predict the Multiplication Factor leading to x% of reduction in
> ###   survival at a specific time.
> ### Aliases: MFx MFx.survFit MFx_ode MFx_ode.survFit
> 
> ### ** Examples
> 
> 
> # (1) Load the data
> data("propiconazole")
> 
> # (2) Create an object of class 'survData'
> dataset <- survData(propiconazole)
> 
> ## No test: 
> # (3) Run the survFit function with model_type SD (or IT)
> out_SD <- survFit(dataset, model_type = "SD")
Compiling model graph
   Resolving undeclared variables
   Allocating nodes
Graph information:
   Observed stochastic nodes: 40
   Unobserved stochastic nodes: 84
   Total graph size: 1240

Initializing model

> 
> # (4) data to predict
> data_4prediction <- data.frame(time = 1:10, conc = c(0,0.5,3,3,0,0,0.5,3,1.5,0))
> 
> # (5) estimate MF(x=30, t=4), that is for 30% reduction of survival at time 4
> MFx_SD_30.4 <- MFx(out_SD, data_predict = data_4prediction , X = 30, time_MFx = 4)
q50 1 accuracy: 0.6461151  with multiplication factor: 1000 
q50 2 accuracy: 0.6461151  with multiplication factor: 500 
q50 3 accuracy: 0.6461151  with multiplication factor: 250 
q50 4 accuracy: 0.6461151  with multiplication factor: 125 
q50 5 accuracy: 0.6461151  with multiplication factor: 62.5 
q50 6 accuracy: 0.6460602  with multiplication factor: 31.25 
q50 7 accuracy: 0.6097922  with multiplication factor: 15.625 
q50 8 accuracy: 0.03251189  with multiplication factor: 7.8125 
q50 9 accuracy: 0.2769065  with multiplication factor: 3.90625 
q50 10 accuracy: 0.2714956  with multiplication factor: 5.859375 
q50 11 accuracy: 0.1484656  with multiplication factor: 6.835938 
q50 12 accuracy: 0.05771596  with multiplication factor: 7.324219 
q50 13 accuracy: 0.01159361  with multiplication factor: 7.568359 
q50 14 accuracy: 0.01044112  with multiplication factor: 7.69043 
q50 15 accuracy: 0.0004472706  with multiplication factor: 7.629395 
qinf95 1 accuracy: 0.6461151  with multiplication factor: 1000 
qinf95 2 accuracy: 0.6461151  with multiplication factor: 500 
qinf95 3 accuracy: 0.6461151  with multiplication factor: 250 
qinf95 4 accuracy: 0.6461151  with multiplication factor: 125 
qinf95 5 accuracy: 0.6461151  with multiplication factor: 62.5 
qinf95 6 accuracy: 0.6461142  with multiplication factor: 31.25 
qinf95 7 accuracy: 0.6354277  with multiplication factor: 15.625 
qinf95 8 accuracy: 0.1174882  with multiplication factor: 7.8125 
qinf95 9 accuracy: 0.2167843  with multiplication factor: 3.90625 
qinf95 10 accuracy: 0.2093593  with multiplication factor: 5.859375 
qinf95 11 accuracy: 0.06729426  with multiplication factor: 6.835938 
qinf95 12 accuracy: 0.02338237  with multiplication factor: 7.324219 
qinf95 13 accuracy: 0.02255952  with multiplication factor: 7.080078 
qinf95 14 accuracy: 0.0004086767  with multiplication factor: 7.202148 
qsup95 1 accuracy: 0.6461151  with multiplication factor: 1000 
qsup95 2 accuracy: 0.6461151  with multiplication factor: 500 
qsup95 3 accuracy: 0.6461151  with multiplication factor: 250 
qsup95 4 accuracy: 0.6461151  with multiplication factor: 125 
qsup95 5 accuracy: 0.6461149  with multiplication factor: 62.5 
qsup95 6 accuracy: 0.6449167  with multiplication factor: 31.25 
qsup95 7 accuracy: 0.552251  with multiplication factor: 15.625 
qsup95 8 accuracy: 0.05308323  with multiplication factor: 7.8125 
qsup95 9 accuracy: 0.3848032  with multiplication factor: 11.71875 
qsup95 10 accuracy: 0.2201167  with multiplication factor: 9.765625 
qsup95 11 accuracy: 0.09922292  with multiplication factor: 8.789062 
qsup95 12 accuracy: 0.02734824  with multiplication factor: 8.300781 
qsup95 13 accuracy: 0.01076363  with multiplication factor: 8.056641 
qsup95 14 accuracy: 0.008443288  with multiplication factor: 8.178711 
> 
> # (5bis) estimate MF(x,t) along the MF_range from 5 to 10 (50) (X = NULL)
> MFx_SD_range <- MFx(out_SD, data_predict = data_4prediction ,
+                     X = NULL, time_MFx = 4, MFx_range = seq(5, 10, length.out = 50))
> ## End(No test)
> 
> 
> 
> # (1) Load the data
> data("propiconazole")
> 
> # (2) Create an object of class 'survData'
> dataset <- survData(propiconazole)
> 
> ## No test: 
> # (3) Run the survFit function with model_type SD (or IT)
> out_SD <- survFit(dataset, model_type = "SD")
Compiling model graph
   Resolving undeclared variables
   Allocating nodes
Graph information:
   Observed stochastic nodes: 40
   Unobserved stochastic nodes: 84
   Total graph size: 1240

Initializing model

> 
> # (4) data to predict
> data_4prediction <- data.frame(time = 1:10, conc = c(0,0.5,3,3,0,0,0.5,3,1.5,0))
> 
> # (5) estimate MF(x=30, t=4), that is for 30% reduction of survival at time 4
> MFx_SD_30.4 <- MFx_ode(out_SD, data_predict = data_4prediction , X = 30, time_MFx = 4)
Warning in MFx_ode.survFit(out_SD, data_predict = data_4prediction, X = 30,  :
  The function 'MFx_ode' uses 'predict_ode' to compute the predictions for calculating the multiplication factors.
This can take a very long time to compute (minutes to hours).

Prefer the function 'MFx' when possible.
Error in predict_ode.survFit(object = object, data_predict = ls_data_predict[[1]],  : 
  Please provide value for `hb` using `hb_valueFORCED`.
Calls: MFx_ode ... MFx_ode.survFit -> predict_ode -> predict_ode.survFit
Execution halted
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’ [158s/159s]
 [159s/160s] OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* checking for new files in some other directories ... OK
* DONE

Status: 1 ERROR, 1 NOTE
See
  ‘/data/blackswan/ripley/R/packages/tests-devel/morse.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 7:44.69, 448.68 + 12.02