rapids/src/data/readable_datetime.R

source("renv/activate.R")

library("tidyverse")
library("readr")
library("lubridate")

input <- read.csv(snakemake@input[["sensor_input"]]) %>% arrange(timestamp)
day_segments <- read.csv(snakemake@input[["day_segments"]])
day_segments_type <- snakemake@params[["day_segments_type"]]
sensor_output <- snakemake@output[[1]]
timezone_periods <- snakemake@params[["timezone_periods"]]
fixed_timezone <- snakemake@params[["fixed_timezone"]]

assign_to_day_segment <- function(data, day_segments, day_segments_type, fixed_timezone){
  
  if(day_segments_type == "FREQUENCY_EVERY_DAY"){
    data <- data %>% mutate(local_date_time_obj = lubridate::parse_date_time(local_time, orders = c("HMS", "HM")))
    day_segments <- day_segments %>% mutate(start_time = lubridate::parse_date_time(start_time, orders = c("HMS", "HM")),
                                            end_time = start_time + minutes(length))
    
    # Create a new column for each day_segment
    for(row_id in 1:nrow(day_segments)){
      row = day_segments[row_id,]
      data <- data %>% mutate(!!paste("local_day_segment", row_id, sep = "_") := ifelse(local_date_time_obj >= row$start_time & local_date_time_obj < row$end_time, 
                                                                                        paste0("[", 
                                                                                               row$label, "_", 
                                                                                               local_date, "_",
                                                                                               paste(str_pad(hour(row$start_time),2, pad="0"), str_pad(minute(row$start_time),2, pad="0"), str_pad(second(row$start_time),2, pad="0"),sep =":"),
                                                                                               "]"), NA))
    }
    
  } else if (day_segments_type == "INTERVAL_EVERY_DAY"){
    
    data_dates <- data %>% select(local_date) %>% distinct(local_date)
    inferred_day_segments <- crossing(day_segments, data_dates) %>% 
      mutate(start_local_date_time_obj = lubridate::parse_date_time(paste(local_date, start_time), orders = c("Ymd HMS", "Ymd HM"), tz = fixed_timezone),
             end_local_date_time_obj = start_local_date_time_obj + lubridate::period(length),
             date_time_interval = lubridate::interval(start_local_date_time_obj, end_local_date_time_obj)) %>% 
      group_by(label, local_date) %>% 
      mutate(group_start_datetime = lubridate::parse_date_time(paste(local_date, start_time), orders = c("Ymd HMS", "Ymd HM"), tz = fixed_timezone),
             group_end_datetime = group_start_datetime + lubridate::period(length),
             group_start_datetime = min(group_start_datetime),
             group_end_datetime = max(group_end_datetime)) %>% 
      ungroup()

    
    data <- data %>% mutate(local_date_time_obj = lubridate::ymd_hms(local_date_time, tz = fixed_timezone))
    
    # Create a new column for each day_segment
    for(row_id in 1:nrow(inferred_day_segments)){
      row = inferred_day_segments[row_id,]
      data <- data %>% mutate(!!paste("local_day_segment", row_id, sep = "_") := ifelse(local_date_time_obj %within% row$date_time_interval, 
                                                                                        paste0("[", 
                                                                                               paste(sep= "#",
                                                                                                     row$label,
                                                                                                     lubridate::date(row$group_start_datetime),
                                                                                                     paste(str_pad(hour(row$group_start_datetime),2, pad="0"), str_pad(minute(row$group_start_datetime),2, pad="0"), str_pad(second(row$group_start_datetime),2, pad="0"),sep =":"),
                                                                                                     lubridate::date(row$group_end_datetime),
                                                                                                     paste(str_pad(hour(row$group_end_datetime),2, pad="0"), str_pad(minute(row$group_end_datetime),2, pad="0"), str_pad(second(row$group_end_datetime),2, pad="0"),sep =":")
                                                                                               ),
                                                                                               "]"), NA))
    }
    
  
  } else if ( day_segments_type == "INTERVAL_FLEXIBLE_DAY"){
    data <- data %>% mutate(local_date_time_obj = lubridate::ymd_hms(local_date_time, tz = fixed_timezone))
    day_segments <- day_segments %>% mutate(shift = ifelse(shift == "0", "0seconds", shift),
                                            start_local_date_time_obj = lubridate::ymd_hms(start_date_time, tz = fixed_timezone) + (lubridate::period(shift) * ifelse(shift_direction >= 0, 1, -1)),
                                            end_local_date_time_obj = start_local_date_time_obj + lubridate::period(length),
                                            date_time_interval = lubridate::interval(start_local_date_time_obj, end_local_date_time_obj))
    
    # Create a new column for each day_segment
    for(row_id in 1:nrow(day_segments)){
      row = day_segments[row_id,]
      print(row$length)
      data <- data %>% mutate(!!paste("local_day_segment", row_id, sep = "_") := ifelse(local_date_time_obj %within% row$date_time_interval, 
                                                                                        paste0("[", 
                                                                                              paste(sep= "#",
                                                                                                row$label,
                                                                                                lubridate::date(row$start_local_date_time_obj),
                                                                                                paste(str_pad(hour(row$start_local_date_time_obj),2, pad="0"), str_pad(minute(row$start_local_date_time_obj),2, pad="0"), str_pad(second(row$start_local_date_time_obj),2, pad="0"),sep =":"),
                                                                                                lubridate::date(row$end_local_date_time_obj),
                                                                                                paste(str_pad(hour(row$end_local_date_time_obj),2, pad="0"), str_pad(minute(row$end_local_date_time_obj),2, pad="0"), str_pad(second(row$end_local_date_time_obj),2, pad="0"),sep =":")
                                                                                                ),
                                                                                              "]"), NA))
    }
  }
  
  # Join all day_segments in a single column
  data <- data %>% 
    unite("assigned_segments", starts_with("local_day_segment"), sep = "|", na.rm = TRUE) %>% 
    select(-local_date_time_obj)

  return(data)
}

split_local_date_time <- function(data, day_segments){
  split_data <- data %>% 
    separate(local_date_time, c("local_date","local_time"), "\\s", remove = FALSE) %>%
    separate(local_time, c("local_hour", "local_minute"), ":", remove = FALSE, extra = "drop") %>%
    mutate(local_hour = as.numeric(local_hour),
           local_minute = as.numeric(local_minute))

  return(split_data)
}

if(!is.null(timezone_periods)){
  # TODO: Not active yet
  # timezones <- read_csv(timezone_periods)
  # tz_starts <- timezones$start
  # output <- input %>% 
  #   mutate(timezone = findInterval(timestamp / 1000, tz_starts), # Set an interval ID based on timezones' start column
  #          timezone = ifelse(timezone == 0, 1, timezone), # Correct the first timezone ID
  #          timezone = recode(timezone, !!! timezones$timezone), # Swap IDs for text labels
  #          timezone = as.character(timezone)) %>%
  #   rowwise() %>%
  #   mutate(utc_date_time = as.POSIXct(timestamp/1000, origin="1970-01-01", tz="UTC"),
  #          local_date_time = format(utc_date_time, tz = timezone, usetz = T, "%Y-%m-%d %H:%M:%S"))
  # output <- split_local_date_time(output, day_segments)
  # TODO: Implement day segment assigment with support for multiple timezones
  # output <- assign_to_day_segment(output, day_segments, day_segments_type, fixed_timezone)
  # write.csv(output, sensor_output)
} else if(!is.null(fixed_timezone)){
  output <- input %>% 
    mutate(utc_date_time = as.POSIXct(timestamp/1000, origin="1970-01-01", tz="UTC"),
           local_date_time = format(utc_date_time, tz = fixed_timezone, usetz = F, "%Y-%m-%d %H:%M:%S"))
  output <- split_local_date_time(output, day_segments)
  output <- assign_to_day_segment(output, day_segments, day_segments_type, fixed_timezone)
  write_csv(output, sensor_output)
}