R/bridge_prism.R

In resplab/framinghamfev1predictorPrism: Peer Models Network PRISM Bridge for the Model framinghamPredictor

model_run<-function(model_input = NULL)
{
    if(length(model_input)==0) {
      model_input <- get_default_input()
    }
    if(is.null(model_input$predictors)) {
      model_input<-unflatten_list(model_input)
    }
    results <- framinghamfev1predictor::make_predictions(resp_var=model_input$resp_var,
                                predictors=model_input$predictors)

    return(as.list(results))
}


prism_get_default_input <- function() {

  model_input <- list(resp_var='fev1', predictors=framinghamfev1predictor::sample_predictors)

  return((flatten_list(model_input)))
}


#Gets a hierarchical named list and flattens it; updating names accordingly
flatten_list<-function(lst,prefix="")
{
  if(is.null(lst)) return(lst)
  out<-list()
  if(length(lst)==0)
  {
    out[prefix]<-NULL
    return(out)
  }

  for(i in 1:length(lst))
  {
    nm<-names(lst[i])

    message(nm)

    if(prefix!="")  nm<-paste(prefix,nm,sep=".")

    if(is.list(lst[[i]]))
      out<-c(out,flatten_list(lst[[i]],nm))
    else
    {
      out[nm]<-lst[i]
    }
  }
  return(out)
}



#Gets a hierarchical named list and flattens it; updating names accordingly
unflatten_list<-function(lst)
{
  if(is.null(lst)) return(lst)
  out<-list()

  nms<-names(lst)

  for(nm in nms)
  {
    path<-paste(strsplit(nm,'.',fixed=T)[[1]],sep="$")
    eval(parse(text=paste("out$",paste(path,collapse="$"),"<-lst[[nm]]",sep="")))
  }

  return(out)
}