"Generating variable_response..." fails with Error in Error in seq.default(from = min(y, na.rm = TRUE), to = max(y, na.rm = TRUE), : 'from' must be a finite number about modeldown HOT 5 CLOSED

library("titanic")
titanic <- titanic_train
titanic$Survived <- factor(titanic$Survived,labels = c("no","yes"))
titanic$gender <- factor(titanic$Sex)
titanic$Embarked <- factor(titanic$Embarked)
titanic <- na.omit(titanic)
titanic <- titanic[titanic$Embarked != "",]
titanic$Embarked <- factor(titanic$Embarked)
names(titanic) <- tolower(names(titanic))

Skim summary statistics
 n obs: 712 
 n variables: 13 

── Variable type:character ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 variable missing complete   n min max empty n_unique
    cabin       0      712 712   0  15   529      134
     name       0      712 712  13  82     0      712
      sex       0      712 712   4   6     0        2
   ticket       0      712 712   3  18     0      541

── Variable type:factor ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 variable missing complete   n n_unique                   top_counts ordered
 embarked       0      712 712        3 S: 554, C: 130, Q: 28, NA: 0   FALSE
   gender       0      712 712        2    mal: 453, fem: 259, NA: 0   FALSE
 survived       0      712 712        2     no: 424, yes: 288, NA: 0   FALSE

── Variable type:integer ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
    variable missing complete   n   mean     sd p0    p25 p50    p75 p100     hist
       parch       0      712 712   0.43   0.85  0   0      0   1       6 ▇▂▁▁▁▁▁▁
 passengerid       0      712 712 448.59 258.68  1 222.75 445 677.25  891 ▇▇▇▇▇▇▇▇
      pclass       0      712 712   2.24   0.84  1   1      2   3       3 ▅▁▁▃▁▁▁▇
       sibsp       0      712 712   0.51   0.93  0   0      0   1       5 ▇▃▁▁▁▁▁▁

── Variable type:numeric ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 variable missing complete   n  mean    sd   p0   p25   p50 p75   p100     hist
      age       0      712 712 29.64 14.49 0.42 20    28     38  80    ▂▃▇▆▃▂▁▁
     fare       0      712 712 34.57 52.94 0     8.05 15.65  33 512.33 ▇▁▁▁▁▁▁▁

titanic <- na.omit(titanic[,sapply(titanic, class) != 'character']) 

 Error in seq.default(from = min(y, na.rm = TRUE), to = max(y, na.rm = TRUE),  : 
  'from' must be a finite number 
25.
stop("'from' must be a finite number") 
24.
seq.default(from = min(y, na.rm = TRUE), to = max(y, na.rm = TRUE), 
    length = grid.resolution) 
23.
seq(from = min(y, na.rm = TRUE), to = max(y, na.rm = TRUE), length = grid.resolution) 
22.
FUN(X[[i]], ...) 
21.
lapply(pred.var, function(x) {
    if (is.factor(train[, x, drop = TRUE])) {
        levels(train[, x, drop = TRUE])
    } ... 
20.
pred_grid(train = train, pred.var = pred.var, grid.resolution = grid.resolution, 
    quantiles = quantiles, probs = probs, trim.outliers = trim.outliers) 
19.
partial.default(explainer$model, pred.var = variable, train = explainer$data, 
    ..., pred.fun = predictor_pdp, recursive = FALSE) 
18.
partial(explainer$model, pred.var = variable, train = explainer$data, 
    ..., pred.fun = predictor_pdp, recursive = FALSE) 
17.
variable_response(explainer, variable_name, type = type) at generator.R#17
16.
FUN(X[[i]], ...) 
15.
lapply(explainers, function(explainer) {
    variable_response(explainer, variable_name, type = type)
}) at generator.R#17
14.
FUN(X[[i]], ...) 
13.
lapply(types, function(type) {
    lapply(explainers, function(explainer) {
        variable_response(explainer, variable_name, type = type)
    }) ... at generator.R#16
12.
make_variable_plot(variable_name, types, explainers, img_folder, 
    options) at generator.R#35
11.
FUN(X[[i]], ...) 
10.
lapply(variables, make_variable_plot_model, explainers, img_folder, 
    options) at generator.R#51
9.
generator_env$generator(explainers, options, file.path(output_folder, 
    "img")) 
8.
FUN(X[[i]], ...) 
7.
lapply(modules_names, function(module_name) {
    print(paste("Generating ", module_name, "...", sep = ""))
    generator_path <- system.file("extdata", "modules", module_name, 
        "generator.R", package = "modelDown") ... 
6.
generateModules(modules, output_folder, explainers, options) 
5.
modelDown(explain_titanic_rf, explain_titanic_gbm, explain_titanic_svm, 
    explain_titanic_knn, device = "svg", output_folder = "modelDown_Titanic_example") at modelDown_example2.R#55
4.
eval(ei, envir) 
3.
eval(ei, envir) 
2.
withVisible(eval(ei, envir)) 
1.
source("~/R/Interpretability/modelDown_example2.R", echo = TRUE)

sessionInfo()
R version 3.5.2 (2018-12-20)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.2 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so

locale:
 [1] LC_CTYPE=fr_FR.UTF-8       LC_NUMERIC=C               LC_TIME=fr_FR.UTF-8        LC_COLLATE=fr_FR.UTF-8     LC_MONETARY=fr_FR.UTF-8    LC_MESSAGES=fr_FR.UTF-8   
 [7] LC_PAPER=fr_FR.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] kableExtra_1.1.0    caret_6.0-81        ggplot2_3.1.0       lattice_0.20-38     gbm_2.1.5           e1071_1.7-1         randomForest_4.6-14 modelDown_0.1.1    
 [9] DALEX_0.2.9         titanic_0.1.0      

loaded via a namespace (and not attached):
  [1] readxl_1.3.1       hnp_1.2-6          plyr_1.8.4         lazyeval_0.2.2     sp_1.3-1           splines_3.5.2      AlgDesign_1.1-7.3  digest_0.6.18     
  [9] foreach_1.4.4      htmltools_0.3.6    gdata_2.18.0       magrittr_1.5       cluster_2.0.7-1    ROCR_1.0-7         openxlsx_4.1.0     recipes_0.1.4     
 [17] readr_1.3.1        gower_0.2.0        gmodels_2.18.1     xts_0.11-2         tseries_0.10-46    colorspace_1.4-1   rvest_0.3.2        ggrepel_0.8.0     
 [25] haven_2.1.0        xfun_0.5           dplyr_0.8.0.1      crayon_1.3.4       ALEPlot_1.1        survival_2.43-3    zoo_1.8-5          iterators_1.0.10  
 [33] glue_1.3.1         gtable_0.2.0       ipred_0.9-8        webshot_0.5.1      questionr_0.7.0    car_3.0-2          quantmod_0.4-13    abind_1.4-6       
 [41] scales_1.0.0       mvtnorm_1.0-10     DBI_1.0.0          GGally_1.4.0       miniUI_0.1.1.1     Rcpp_1.0.1         plotROC_2.2.1      viridisLite_0.3.0 
 [49] xtable_1.8-3       spData_0.3.0       units_0.6-2        foreign_0.8-71     spdep_1.0-2        proxy_0.4-23       stats4_3.5.2       lava_1.6.5        
 [57] prodlim_2018.04.18 httr_1.4.0         yaImpute_1.0-31    gplots_3.0.1.1     RColorBrewer_1.1-2 factoextra_1.0.5   pkgconfig_2.0.2    reshape_0.8.8     
 [65] nnet_7.3-12        deldir_0.1-16      labeling_0.3       tidyselect_0.2.5   rlang_0.3.2        reshape2_1.4.3     later_0.8.0        munsell_0.5.0     
 [73] cellranger_1.1.0   tools_3.5.2        generics_0.0.2     factorMerger_0.3.6 fdrtool_1.2.15     evaluate_0.13      stringr_1.4.0      ModelMetrics_1.2.2
 [81] knitr_1.22         auditor_0.3.2      zip_2.0.1          pdp_0.7.0          caTools_1.17.1.2   purrr_0.3.2        packrat_0.5.0      nlme_3.1-137      
 [89] whisker_0.3-2      mime_0.6           xml2_1.2.0         compiler_3.5.2     rstudioapi_0.10    curl_3.3           klaR_0.6-14        tibble_2.1.1      
 [97] stringi_1.4.3      highr_0.8          forcats_0.4.0      Matrix_1.2-16      classInt_0.3-1     pillar_1.3.1       LearnBayes_2.15.1  combinat_0.0-8    
[105] data.table_1.12.0  bitops_1.0-6       httpuv_1.5.0       agricolae_1.3-0    R6_2.4.0           promises_1.0.1     KernSmooth_2.23-15 gridExtra_2.3     
[113] rio_0.5.16         codetools_0.2-16   boot_1.3-20        MASS_7.3-51.1      gtools_3.8.1       assertthat_0.2.1   withr_2.1.2        expm_0.999-4      
[121] hms_0.4.2          quadprog_1.5-5     grid_3.5.2         rpart_4.1-13       timeDate_3043.102  coda_0.19-2        class_7.3-15       rmarkdown_1.12    
[129] breakDown_0.2.0    carData_3.0-2      TTR_0.23-4         ggpubr_0.2         sf_0.7-3           shiny_1.2.0        lubridate_1.7.4   
>