R/fct_cgm.R

In personalscience/taster: Personal Science CGM Analysis Web App

#' CGM-related data structures and functions
#'

#' @title Make New CGM Object
#' @description The new object contains all data relevant to CGM operations:  `glucose_records`, `notes_records` and more.
#' @param con valid database connection
#' @export
CgmObject <- function(con) {


  thisEnv <- environment()


  db <- list(
    thisEnv = thisEnv,
    con = con,
    glucose_records = tbl(con, "glucose_records") %>% collect(),
    notes_records = tbl(con, "notes_records") %>% collect()
    )

  ## Define the value of the list within the current environment.
  assign('this',db,envir=thisEnv)

  structure(db, class = "list",
            con  = con)
}



#'
#' @title Max and Min Glucose Ranges for `user_id`
#' @param user_id user ID
#' @param glucose_records valid glucose records
glucose_ranges_for_id <- function(user_id, glucose_records){

  GLUCOSE_RECORDS <- glucose_records

  ID = user_id
  GLUCOSE_RECORDS %>% filter(user_id == ID & !is.na(value)) %>%

    mutate(time = lubridate::with_tz(time, tzone="America/Los_Angeles")) %>%
    filter(lubridate::hour(time) >=1 & lubridate::hour(time) <=4 & !is.na(value)) %>%
    group_by(date=lubridate::date(time)) %>%
    summarize(mean = mean(value, na.rm = TRUE), sd = sd(value,na.rm = TRUE)) %>%
    ungroup() %>%
    select(mean,sd) %>%
    summarize(mean=mean(mean, na.rm = TRUE),sd=mean(sd, na.rm = TRUE))


}