R/07_point_converter.R

In PHP2560-Statistical-Programming-R/r-framingham: a grammer for framingham study based risk scores calculation

#' @title point converter
#'
#' @description
#' \code{point_converter} returns relative risk and heart age given framingham point and gender
#'
#' @details
#' \code{point_converter} returns TODO: add some details
#'
#' @param gender A character
#' @param points A number
#' @param bmi A number or NA
#' @return risk and heart_age given \code{points} and \code{gender}  and \code{bmi}
#' @examples
#' point_converter(points=1, gender='M', NA)
#'

# preload required data
male_risk_csv<-read.csv('male_risk.csv')
male_simple_risk_csv<-read.csv('male_simple_risk.csv')
female_simple_risk_csv<-read.csv('female_simple_risk.csv')
female_risk_csv<-read.csv('female_risk.csv')

# define function point
point_converter<-function(points, gender, bmi=NA){
  # initialize
  risk=NA
  heart_age=NA
  #convert
  if((gender=="M" || gender=="m") & !is.na(bmi)){ #specify male and using BMI value
    table<-male_simple_risk_csv #call appropriate index table
    risk=table[which(table$male_simple_point == points),3] #call risk column from index table
    heart_age=table[which(table$male_simple_point == points),4] # call heart age column from index table
  } else if ((gender=="M" || gender=="m") & is.na(bmi)){ #specify male and no BMI value
    table<-male_risk_csv #call appropriate index table
    risk=table[which(table$male_point == points),3] #call risk column from index table
    heart_age=table[which(table$male_point == points),4]# call heart age column from index table
  } else if ((gender=="F" || gender=="f") & !is.na(bmi)){ #specify female and using BMI value
    table<-female_simple_risk_csv #call appropriate index table
    risk=table[which(table$female_simple_point == points),3] #call risk column from index table
    heart_age=table[which(table$female_simple_point == points),4]# call heart age column from index table
  } else if ((gender=="F" || gender=="f") & is.na(bmi)){ #specify female and no BMI value
    table<-female_risk_csv #call appropriate index table
    risk=table[which(table$female_point == points),3] #call risk column from index table
    heart_age=table[which(table$female_point == points),4]# call heart age column from index table
  }
  return(list(
    risk=risk,
    heart_age=heart_age
  ))
}