In el-mrt/auto-statistics: Approach for an autoML implementation

library(tidyverse)
corrplot_setup <- list(
  data = params$content$cor_matrix
)

defaultW <- getOption("warn")
options(warn = -1)

cat("\n")
params$content[["cor_matrix"]]$print_report()
cat("\n")

features <- names(params$content)
features <- features[!features %in% "cor_matrix"]
for(feature in features){
  cat('\n###', feature, '\n')
  feature_content <- params$content[[feature]]
  purrr::walk(feature_content, function(x){
    cat("\n")
    x$print_report()
    cat("\n")
  })
}

options(warn = defaultW)

if(params$append_custom){
  cat('\n##', 'Custom Report', '\n')
  purrr::walk(params$custom_plot$plot, function(plot){
    print(plot)
    cat("\n")
  })  
}